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Observational Studies: Cohort and Case-Control Studies

Jae w. song.

1 Research Fellow, Section of Plastic Surgery, Department of Surgery The University of Michigan Health System; Ann Arbor, MI

Kevin C. Chung

2 Professor of Surgery, Section of Plastic Surgery, Department of Surgery The University of Michigan Health System; Ann Arbor, MI

Observational studies are an important category of study designs. To address some investigative questions in plastic surgery, randomized controlled trials are not always indicated or ethical to conduct. Instead, observational studies may be the next best method to address these types of questions. Well-designed observational studies have been shown to provide results similar to randomized controlled trials, challenging the belief that observational studies are second-rate. Cohort studies and case-control studies are two primary types of observational studies that aid in evaluating associations between diseases and exposures. In this review article, we describe these study designs, methodological issues, and provide examples from the plastic surgery literature.

Because of the innovative nature of the specialty, plastic surgeons are frequently confronted with a spectrum of clinical questions by patients who inquire about “best practices.” It is thus essential that plastic surgeons know how to critically appraise the literature to understand and practice evidence-based medicine (EBM) and also contribute to the effort by carrying out high-quality investigations. 1 Well-designed randomized controlled trials (RCTs) have held the pre-eminent position in the hierarchy of EBM as level I evidence ( Table 1 ). However, RCT methodology, which was first developed for drug trials, can be difficult to conduct for surgical investigations. 3 Instead, well-designed observational studies, recognized as level II or III evidence, can play an important role in deriving evidence for plastic surgery. Results from observational studies are often criticized for being vulnerable to influences by unpredictable confounding factors. However, recent work has challenged this notion, showing comparable results between observational studies and RCTs. 4 , 5 Observational studies can also complement RCTs in hypothesis generation, establishing questions for future RCTs, and defining clinical conditions.

Levels of Evidence Based Medicine

From REF 1 .

Observational studies fall under the category of analytic study designs and are further sub-classified as observational or experimental study designs ( Figure 1 ). The goal of analytic studies is to identify and evaluate causes or risk factors of diseases or health-related events. The differentiating characteristic between observational and experimental study designs is that in the latter, the presence or absence of undergoing an intervention defines the groups. By contrast, in an observational study, the investigator does not intervene and rather simply “observes” and assesses the strength of the relationship between an exposure and disease variable. 6 Three types of observational studies include cohort studies, case-control studies, and cross-sectional studies ( Figure 1 ). Case-control and cohort studies offer specific advantages by measuring disease occurrence and its association with an exposure by offering a temporal dimension (i.e. prospective or retrospective study design). Cross-sectional studies, also known as prevalence studies, examine the data on disease and exposure at one particular time point ( Figure 2 ). 6 Because the temporal relationship between disease occurrence and exposure cannot be established, cross-sectional studies cannot assess the cause and effect relationship. In this review, we will primarily discuss cohort and case-control study designs and related methodologic issues.

Analytic Study Designs. Adapted with permission from Joseph Eisenberg, Ph.D.

Temporal Design of Observational Studies: Cross-sectional studies are known as prevalence studies and do not have an inherent temporal dimension. These studies evaluate subjects at one point in time, the present time. By contrast, cohort studies can be either retrospective (latin derived prefix, “retro” meaning “back, behind”) or prospective (greek derived prefix, “pro” meaning “before, in front of”). Retrospective studies “look back” in time contrasting with prospective studies, which “look ahead” to examine causal associations. Case-control study designs are also retrospective and assess the history of the subject for the presence or absence of an exposure.

COHORT STUDY

The term “cohort” is derived from the Latin word cohors . Roman legions were composed of ten cohorts. During battle each cohort, or military unit, consisting of a specific number of warriors and commanding centurions, were traceable. The word “cohort” has been adopted into epidemiology to define a set of people followed over a period of time. W.H. Frost, an epidemiologist from the early 1900s, was the first to use the word “cohort” in his 1935 publication assessing age-specific mortality rates and tuberculosis. 7 The modern epidemiological definition of the word now means a “group of people with defined characteristics who are followed up to determine incidence of, or mortality from, some specific disease, all causes of death, or some other outcome.” 7

Study Design

A well-designed cohort study can provide powerful results. In a cohort study, an outcome or disease-free study population is first identified by the exposure or event of interest and followed in time until the disease or outcome of interest occurs ( Figure 3A ). Because exposure is identified before the outcome, cohort studies have a temporal framework to assess causality and thus have the potential to provide the strongest scientific evidence. 8 Advantages and disadvantages of a cohort study are listed in Table 2 . 2 , 9 Cohort studies are particularly advantageous for examining rare exposures because subjects are selected by their exposure status. Additionally, the investigator can examine multiple outcomes simultaneously. Disadvantages include the need for a large sample size and the potentially long follow-up duration of the study design resulting in a costly endeavor.

Cohort and Case-Control Study Designs

Advantages and Disadvantages of the Cohort Study

Cohort studies can be prospective or retrospective ( Figure 2 ). Prospective studies are carried out from the present time into the future. Because prospective studies are designed with specific data collection methods, it has the advantage of being tailored to collect specific exposure data and may be more complete. The disadvantage of a prospective cohort study may be the long follow-up period while waiting for events or diseases to occur. Thus, this study design is inefficient for investigating diseases with long latency periods and is vulnerable to a high loss to follow-up rate. Although prospective cohort studies are invaluable as exemplified by the landmark Framingham Heart Study, started in 1948 and still ongoing, 10 in the plastic surgery literature this study design is generally seen to be inefficient and impractical. Instead, retrospective cohort studies are better indicated given the timeliness and inexpensive nature of the study design.

Retrospective cohort studies, also known as historical cohort studies, are carried out at the present time and look to the past to examine medical events or outcomes. In other words, a cohort of subjects selected based on exposure status is chosen at the present time, and outcome data (i.e. disease status, event status), which was measured in the past, are reconstructed for analysis. The primary disadvantage of this study design is the limited control the investigator has over data collection. The existing data may be incomplete, inaccurate, or inconsistently measured between subjects. 2 However, because of the immediate availability of the data, this study design is comparatively less costly and shorter than prospective cohort studies. For example, Spear and colleagues examined the effect of obesity and complication rates after undergoing the pedicled TRAM flap reconstruction by retrospectively reviewing 224 pedicled TRAM flaps in 200 patients over a 10-year period. 11 In this example, subjects who underwent the pedicled TRAM flap reconstruction were selected and categorized into cohorts by their exposure status: normal/underweight, overweight, or obese. The outcomes of interest were various flap and donor site complications. The findings revealed that obese patients had a significantly higher incidence of donor site complications, multiple flap complications, and partial flap necrosis than normal or overweight patients. An advantage of the retrospective study design analysis is the immediate access to the data. A disadvantage is the limited control over the data collection because data was gathered retrospectively over 10-years; for example, a limitation reported by the authors is that mastectomy flap necrosis was not uniformly recorded for all subjects. 11

An important distinction lies between cohort studies and case-series. The distinguishing feature between these two types of studies is the presence of a control, or unexposed, group. Contrasting with epidemiological cohort studies, case-series are descriptive studies following one small group of subjects. In essence, they are extensions of case reports. Usually the cases are obtained from the authors' experiences, generally involve a small number of patients, and more importantly, lack a control group. 12 There is often confusion in designating studies as “cohort studies” when only one group of subjects is examined. Yet, unless a second comparative group serving as a control is present, these studies are defined as case-series. The next step in strengthening an observation from a case-series is selecting appropriate control groups to conduct a cohort or case-control study, the latter which is discussed in the following section about case-control studies. 9

Methodological Issues

Selection of subjects in cohort studies.

The hallmark of a cohort study is defining the selected group of subjects by exposure status at the start of the investigation. A critical characteristic of subject selection is to have both the exposed and unexposed groups be selected from the same source population ( Figure 4 ). 9 Subjects who are not at risk for developing the outcome should be excluded from the study. The source population is determined by practical considerations, such as sampling. Subjects may be effectively sampled from the hospital, be members of a community, or from a doctor's individual practice. A subset of these subjects will be eligible for the study.

Levels of Subject Selection. Adapted from Ref 9 .

Attrition Bias (Loss to follow-up)

Because prospective cohort studies may require long follow-up periods, it is important to minimize loss to follow-up. Loss to follow-up is a situation in which the investigator loses contact with the subject, resulting in missing data. If too many subjects are loss to follow-up, the internal validity of the study is reduced. A general rule of thumb requires that the loss to follow-up rate not exceed 20% of the sample. 6 Any systematic differences related to the outcome or exposure of risk factors between those who drop out and those who stay in the study must be examined, if possible, by comparing individuals who remain in the study and those who were loss to follow-up or dropped out. It is therefore important to select subjects who can be followed for the entire duration of the cohort study. Methods to minimize loss to follow-up are listed in Table 3 .

Methods to Minimize Loss to Follow-Up

Adapted from REF 2 .

CASE-CONTROL STUDIES

Case-control studies were historically borne out of interest in disease etiology. The conceptual basis of the case-control study is similar to taking a history and physical; the diseased patient is questioned and examined, and elements from this history taking are knitted together to reveal characteristics or factors that predisposed the patient to the disease. In fact, the practice of interviewing patients about behaviors and conditions preceding illness dates back to the Hippocratic writings of the 4 th century B.C. 7

Reasons of practicality and feasibility inherent in the study design typically dictate whether a cohort study or case-control study is appropriate. This study design was first recognized in Janet Lane-Claypon's study of breast cancer in 1926, revealing the finding that low fertility rate raises the risk of breast cancer. 13 , 14 In the ensuing decades, case-control study methodology crystallized with the landmark publication linking smoking and lung cancer in the 1950s. 15 Since that time, retrospective case-control studies have become more prominent in the biomedical literature with more rigorous methodological advances in design, execution, and analysis.

Case-control studies identify subjects by outcome status at the outset of the investigation. Outcomes of interest may be whether the subject has undergone a specific type of surgery, experienced a complication, or is diagnosed with a disease ( Figure 3B ). Once outcome status is identified and subjects are categorized as cases, controls (subjects without the outcome but from the same source population) are selected. Data about exposure to a risk factor or several risk factors are then collected retrospectively, typically by interview, abstraction from records, or survey. Case-control studies are well suited to investigate rare outcomes or outcomes with a long latency period because subjects are selected from the outset by their outcome status. Thus in comparison to cohort studies, case-control studies are quick, relatively inexpensive to implement, require comparatively fewer subjects, and allow for multiple exposures or risk factors to be assessed for one outcome ( Table 4 ). 2 , 9

Advantages and Disadvantages of the Case-Control Study

An example of a case-control investigation is by Zhang and colleagues who examined the association of environmental and genetic factors associated with rare congenital microtia, 16 which has an estimated prevalence of 0.83 to 17.4 in 10,000. 17 They selected 121 congenital microtia cases based on clinical phenotype, and 152 unaffected controls, matched by age and sex in the same hospital and same period. Controls were of Hans Chinese origin from Jiangsu, China, the same area from where the cases were selected. This allowed both the controls and cases to have the same genetic background, important to note given the investigated association between genetic factors and congenital microtia. To examine environmental factors, a questionnaire was administered to the mothers of both cases and controls. The authors concluded that adverse maternal health was among the main risk factors for congenital microtia, specifically maternal disease during pregnancy (OR 5.89, 95% CI 2.36-14.72), maternal toxicity exposure during pregnancy (OR 4.76, 95% CI 1.66-13.68), and resident area, such as living near industries associated with air pollution (OR 7.00, 95% CI 2.09-23.47). 16 A case-control study design is most efficient for this investigation, given the rarity of the disease outcome. Because congenital microtia is thought to have multifactorial causes, an additional advantage of the case-control study design in this example is the ability to examine multiple exposures and risk factors.

Selection of Cases

Sampling in a case-control study design begins with selecting the cases. In a case-control study, it is imperative that the investigator has explicitly defined inclusion and exclusion criteria prior to the selection of cases. For example, if the outcome is having a disease, specific diagnostic criteria, disease subtype, stage of disease, or degree of severity should be defined. Such criteria ensure that all the cases are homogenous. Second, cases may be selected from a variety of sources, including hospital patients, clinic patients, or community subjects. Many communities maintain registries of patients with certain diseases and can serve as a valuable source of cases. However, despite the methodologic convenience of this method, validity issues may arise. For example, if cases are selected from one hospital, identified risk factors may be unique to that single hospital. This methodological choice may weaken the generalizability of the study findings. Another example is choosing cases from the hospital versus the community; most likely cases from the hospital sample will represent a more severe form of the disease than those in the community. 2 Finally, it is also important to select cases that are representative of cases in the target population to strengthen the study's external validity ( Figure 4 ). Potential reasons why cases from the original target population eventually filter through and are available as cases (study participants) for a case-control study are illustrated in Figure 5 .

Levels of Case Selection. Adapted from Ref 2 .

Selection of Controls

Selecting the appropriate group of controls can be one of the most demanding aspects of a case-control study. An important principle is that the distribution of exposure should be the same among cases and controls; in other words, both cases and controls should stem from the same source population. The investigator may also consider the control group to be an at-risk population, with the potential to develop the outcome. Because the validity of the study depends upon the comparability of these two groups, cases and controls should otherwise meet the same inclusion criteria in the study.

A case-control study design that exemplifies this methodological feature is by Chung and colleagues, who examined maternal cigarette smoking during pregnancy and the risk of newborns developing cleft lip/palate. 18 A salient feature of this study is the use of the 1996 U.S. Natality database, a population database, from which both cases and controls were selected. This database provides a large sample size to assess newborn development of cleft lip/palate (outcome), which has a reported incidence of 1 in 1000 live births, 19 and also enabled the investigators to choose controls (i.e., healthy newborns) that were generalizable to the general population to strengthen the study's external validity. A significant relationship with maternal cigarette smoking and cleft lip/palate in the newborn was reported in this study (adjusted OR 1.34, 95% CI 1.36-1.76). 18

Matching is a method used in an attempt to ensure comparability between cases and controls and reduces variability and systematic differences due to background variables that are not of interest to the investigator. 8 Each case is typically individually paired with a control subject with respect to the background variables. The exposure to the risk factor of interest is then compared between the cases and the controls. This matching strategy is called individual matching. Age, sex, and race are often used to match cases and controls because they are typically strong confounders of disease. 20 Confounders are variables associated with the risk factor and may potentially be a cause of the outcome. 8 Table 5 lists several advantages and disadvantages with a matching design.

Advantages and Disadvantages for Using a Matching Strategy

Multiple Controls

Investigations examining rare outcomes may have a limited number of cases to select from, whereas the source population from which controls can be selected is much larger. In such scenarios, the study may be able to provide more information if multiple controls per case are selected. This method increases the “statistical power” of the investigation by increasing the sample size. The precision of the findings may improve by having up to about three or four controls per case. 21 - 23

Bias in Case-Control Studies

Evaluating exposure status can be the Achilles heel of case-control studies. Because information about exposure is typically collected by self-report, interview, or from recorded information, it is susceptible to recall bias, interviewer bias, or will rely on the completeness or accuracy of recorded information, respectively. These biases decrease the internal validity of the investigation and should be carefully addressed and reduced in the study design. Recall bias occurs when a differential response between cases and controls occurs. The common scenario is when a subject with disease (case) will unconsciously recall and report an exposure with better clarity due to the disease experience. Interviewer bias occurs when the interviewer asks leading questions or has an inconsistent interview approach between cases and controls. A good study design will implement a standardized interview in a non-judgemental atmosphere with well-trained interviewers to reduce interviewer bias. 9

The STROBE Statement: The Strengthening the Reporting of Observational Studies in Epidemiology Statement

In 2004, the first meeting of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) group took place in Bristol, UK. 24 The aim of the group was to establish guidelines on reporting observational research to improve the transparency of the methods, thereby facilitating the critical appraisal of a study's findings. A well-designed but poorly reported study is disadvantaged in contributing to the literature because the results and generalizability of the findings may be difficult to assess. Thus a 22-item checklist was generated to enhance the reporting of observational studies across disciplines. 25 , 26 This checklist is also located at the following website: www.strobe-statement.org . This statement is applicable to cohort studies, case-control studies, and cross-sectional studies. In fact, 18 of the checklist items are common to all three types of observational studies, and 4 items are specific to each of the 3 specific study designs. In an effort to provide specific guidance to go along with this checklist, an “explanation and elaboration” article was published for users to better appreciate each item on the checklist. 27 Plastic surgery investigators should peruse this checklist prior to designing their study and when they are writing up the report for publication. In fact, some journals now require authors to follow the STROBE Statement. A list of participating journals can be found on this website: http://www.strobe-statement.org./index.php?id=strobe-endorsement .

Due to the limitations in carrying out RCTs in surgical investigations, observational studies are becoming more popular to investigate the relationship between exposures, such as risk factors or surgical interventions, and outcomes, such as disease states or complications. Recognizing that well-designed observational studies can provide valid results is important among the plastic surgery community, so that investigators can both critically appraise and appropriately design observational studies to address important clinical research questions. The investigator planning an observational study can certainly use the STROBE statement as a tool to outline key features of a study as well as coming back to it again at the end to enhance transparency in methodology reporting.

Acknowledgments

Supported in part by a Midcareer Investigator Award in Patient-Oriented Research (K24 AR053120) from the National Institute of Arthritis and Musculoskeletal and Skin Diseases (to Dr. Kevin C. Chung).

None of the authors has a financial interest in any of the products, devices, or drugs mentioned in this manuscript.

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What is Observational Study Design and Types

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Table of Contents

Most people think of a traditional experimental design when they consider research and published research papers. There is, however, a type of research that is more observational in nature, and it is appropriately referred to as “observational studies.”

There are many valuable reasons to utilize an observational study design. But, just as in research experimental design, different methods can be used when you’re considering this type of study. In this article, we’ll look at the advantages and disadvantages of an observational study design, as well as the 3 types of observational studies.

What is Observational Study Design?

An observational study is when researchers are looking at the effect of some type of intervention, risk, a diagnostic test or treatment, without trying to manipulate who is, or who isn’t, exposed to it.

This differs from an experimental study, where the scientists are manipulating who is exposed to the treatment, intervention, etc., by having a control group, or those who are not exposed, and an experimental group, or those who are exposed to the intervention, treatment, etc. In the best studies, the groups are randomized, or chosen by chance.

Any evidence derived from systematic reviews is considered the best in the hierarchy of evidence, which considers which studies are deemed the most reliable. Next would be any evidence that comes from randomized controlled trials. Cohort studies and case studies follow, in that order.

Cohort studies and case studies are considered observational in design, whereas the randomized controlled trial would be an experimental study.

Let’s take a closer look at the different types of observational study design.

The 3 types of Observational Studies

The different types of observational studies are used for different reasons. Selecting the best type for your research is critical to a successful outcome. One of the main reasons observational studies are used is when a randomized experiment would be considered unethical. For example, a life-saving medication used in a public health emergency. They are also used when looking at aetiology, or the cause of a condition or disease, as well as the treatment of rare conditions.

Case Control Observational Study

Researchers in case control studies identify individuals with an existing health issue or condition, or “cases,” along with a similar group without the condition, or “controls.” These two groups are then compared to identify predictors and outcomes. This type of study is helpful to generate a hypothesis that can then be researched.

Cohort Observational Study

This type of observational study is often used to help understand cause and effect. A cohort observational study looks at causes, incidence and prognosis, for example. A cohort is a group of people who are linked in a particular way, for example, a birth cohort would include people who were born within a specific period of time. Scientists might compare what happens to the members of the cohort who have been exposed to some variable to what occurs with members of the cohort who haven’t been exposed.

Cross Sectional Observational Study

Unlike a cohort observational study, a cross sectional observational study does not explore cause and effect, but instead looks at prevalence. Here you would look at data from a particular group at one very specific period of time. Researchers would simply observe and record information about something present in the population, without manipulating any variables or interventions. These types of studies are commonly used in psychology, education and social science.

Advantages and Disadvantages of Observational Study Design

Observational study designs have the distinct advantage of allowing researchers to explore answers to questions where a randomized controlled trial, or RCT, would be unethical. Additionally, if the study is focused on a rare condition, studying existing cases as compared to non-affected individuals might be the most effective way to identify possible causes of the condition. Likewise, if very little is known about a condition or circumstance, a cohort study would be a good study design choice.

A primary advantage to the observational study design is that they can generally be completed quickly and inexpensively. A RCT can take years before the data is compiled and available. RCTs are more complex and involved, requiring many more logistics and details to iron out, whereas an observational study can be more easily designed and completed.

The main disadvantage of observational study designs is that they’re more open to dispute than an RCT. Of particular concern would be confounding biases. This is when a cohort might share other characteristics that affect the outcome versus the outcome stated in the study. An example would be that people who practice good sleeping habits have less heart disease. But, maybe those who practice effective sleeping habits also, in general, eat better and exercise more.

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Observational vs. Experimental Study: A Comprehensive Guide

Explore the fundamental disparities between experimental and observational studies in this comprehensive guide by Santos Research Center, Corp. Uncover concepts such as control group, random sample, cohort studies, response variable, and explanatory variable that shape the foundation of these methodologies. Discover the significance of randomized controlled trials and case control studies, examining causal relationships and the role of dependent variables and independent variables in research designs.

This enlightening exploration also delves into the meticulous scientific study process, involving survey members, systematic reviews, and statistical analyses. Investigate the careful balance of control group and treatment group dynamics, highlighting how researchers meticulously assign variables and analyze statistical patterns to discern meaningful insights. From dissecting issues like lung cancer to understanding sleep patterns, this guide emphasizes the precision of controlled experiments and controlled trials, where variables are isolated and scrutinized, paving the way for a deeper comprehension of the world through empirical research.

Introduction to Observational and Experimental Studies

These two studies are the cornerstones of scientific inquiry, each offering a distinct approach to unraveling the mysteries of the natural world.

Observational studies allow us to observe, document, and gather data without direct intervention. They provide a means to explore real-world scenarios and trends, making them valuable when manipulating variables is not feasible or ethical. From surveys to meticulous observations, these studies shed light on existing conditions and relationships.

Experimental studies , in contrast, put researchers in the driver's seat. They involve the deliberate manipulation of variables to understand their impact on specific outcomes. By controlling the conditions, experimental studies establish causal relationships, answering questions of causality with precision. This approach is pivotal for hypothesis testing and informed decision-making.

At Santos Research Center, Corp., we recognize the importance of both observational and experimental studies. We employ these methodologies in our diverse research projects to ensure the highest quality of scientific investigation and to answer a wide range of research questions.

Observational Studies: A Closer Look

In our exploration of research methodologies, let's zoom in on observational research studies—an essential facet of scientific inquiry that we at Santos Research Center, Corp., expertly employ in our diverse research projects.

What is an Observational Study?

Observational research studies involve the passive observation of subjects without any intervention or manipulation by researchers. These studies are designed to scrutinize the relationships between variables and test subjects, uncover patterns, and draw conclusions grounded in real-world data.

Researchers refrain from interfering with the natural course of events in controlled experiment. Instead, they meticulously gather data by keenly observing and documenting information about the test subjects and their surroundings. This approach permits the examination of variables that cannot be ethically or feasibly manipulated, making it particularly valuable in certain research scenarios.

Types of Observational Studies

Now, let's delve into the various forms that observational studies can take, each with its distinct characteristics and applications.

Cohort Studies:  A cohort study is a type of observational study that entails tracking one group of individuals over an extended period. Its primary goal is to identify potential causes or risk factors for specific outcomes or treatment group. Cohort studies provide valuable insights into the development of conditions or diseases and the factors that influence them.

Case-Control Studies:  Case-control studies, on the other hand, involve the comparison of individuals with a particular condition or outcome to those without it (the control group). These studies aim to discern potential causal factors or associations that may have contributed to the development of the condition under investigation.

Cross-Sectional Studies:  Cross-sectional studies take a snapshot of a diverse group of individuals at a single point in time. By collecting data from this snapshot, researchers gain insights into the prevalence of a specific condition or the relationships between variables at that precise moment. Cross-sectional studies are often used to assess the health status of the different groups within a population or explore the interplay between various factors.

Advantages and Limitations of Observational Studies

Observational studies, as we've explored, are a vital pillar of scientific research, offering unique insights into real-world phenomena. In this section, we will dissect the advantages and limitations that characterize these studies, shedding light on the intricacies that researchers grapple with when employing this methodology.

Advantages: One of the paramount advantages of observational studies lies in their utilization of real-world data. Unlike controlled experiments that operate in artificial settings, observational studies embrace the complexities of the natural world. This approach enables researchers to capture genuine behaviors, patterns, and occurrences as they unfold. As a result, the data collected reflects the intricacies of real-life scenarios, making it highly relevant and applicable to diverse settings and populations.

Moreover, in a randomized controlled trial, researchers looked to randomly assign participants to a group. Observational studies excel in their capacity to examine long-term trends. By observing one group of subjects over extended periods, research scientists gain the ability to track developments, trends, and shifts in behavior or outcomes. This longitudinal perspective is invaluable when studying phenomena that evolve gradually, such as chronic diseases, societal changes, or environmental shifts. It allows for the detection of subtle nuances that may be missed in shorter-term investigations.

Limitations: However, like any research methodology, observational studies are not without their limitations. One significant challenge of statistical study lies in the potential for biases. Since researchers do not intervene in the subjects' experiences, various biases can creep into the data collection process. These biases may arise from participant self-reporting, observer bias, or selection bias in random sample, among others. Careful design and rigorous data analysis are crucial for mitigating these biases.

Another limitation is the presence of confounding variables. In observational studies, it can be challenging to isolate the effect of a specific variable from the myriad of other factors at play. These confounding variables can obscure the true relationship between the variables of interest, making it difficult to establish causation definitively. Research scientists must employ statistical techniques to control for or adjust these confounding variables.

Additionally, observational studies face constraints in their ability to establish causation. While they can identify associations and correlations between variables, they cannot prove causality or causal relationship. Establishing causation typically requires controlled experiments where researchers can manipulate independent variables systematically. In observational studies, researchers can only infer potential causation based on the observed associations.

Experimental Studies: Delving Deeper

In the intricate landscape of scientific research, we now turn our gaze toward experimental studies—a dynamic and powerful method that Santos Research Center, Corp. skillfully employs in our pursuit of knowledge.

What is an Experimental Study?

While some studies observe and gather data passively, experimental studies take a more proactive approach. Here, researchers actively introduce an intervention or treatment to an experiment group study its effects on one or more variables. This methodology empowers researchers to manipulate independent variables deliberately and examine their direct impact on dependent variables.

Experimental research are distinguished by their exceptional ability to establish cause-and-effect relationships. This invaluable characteristic allows researchers to unlock the mysteries of how one variable influences another, offering profound insights into the scientific questions at hand. Within the controlled environment of an experimental study, researchers can systematically test hypotheses, shedding light on complex phenomena.

Key Features of Experimental Studies

Central to statistical analysis, the rigor and reliability of experimental studies are several key features that ensure the validity of their findings.

Randomized Controlled Trials:  Randomization is a critical element in experimental studies, as it ensures that subjects are assigned to groups in a random assignment. This randomly assigned allocation minimizes the risk of unintentional biases and confounding variables, strengthening the credibility of the study's outcomes.

Control Groups:  Control groups play a pivotal role in experimental studies by serving as a baseline for comparison. They enable researchers to assess the true impact of the intervention being studied. By comparing the outcomes of the intervention group to those of survey members of the control group, researchers can discern whether the intervention caused the observed changes.

Blinding:  Both single-blind and double-blind techniques are employed in experimental studies to prevent biases from influencing the study or controlled trial's outcomes. Single-blind studies keep either the subjects or the researchers unaware of certain aspects of the study, while double-blind studies extend this blindness to both parties, enhancing the objectivity of the study.

These key features work in concert to uphold the integrity and trustworthiness of the results generated through experimental studies.

Advantages and Limitations of Experimental Studies

As with any research methodology, this one comes with its unique set of advantages and limitations.

Advantages:  These studies offer the distinct advantage of establishing causal relationships between two or more variables together. The controlled environment allows researchers to exert authority over variables, ensuring that changes in the dependent variable can be attributed to the independent variable. This meticulous control results in high-quality, reliable data that can significantly contribute to scientific knowledge.

Limitations:  However, experimental ones are not without their challenges. They may raise ethical concerns, particularly when the interventions involve potential risks to subjects. Additionally, their controlled nature can limit their real-world applicability, as the conditions in experiments may not accurately mirror those in the natural world. Moreover, executing an experimental study in randomized controlled, often demands substantial resources, with other variables including time, funding, and personnel.

Observational vs Experimental: A Side-by-Side Comparison

Having previously examined observational and experimental studies individually, we now embark on a side-by-side comparison to illuminate the key distinctions and commonalities between these foundational research approaches.

Key Differences and Notable Similarities

Methodologies

• Observational Studies : Characterized by passive observation, where researchers collect data without direct intervention, allowing the natural course of events to unfold.
• Experimental Studies : Involve active intervention, where researchers deliberately manipulate variables to discern their impact on specific outcomes, ensuring control over the experimental conditions.
• Observational Studies : Designed to identify patterns, correlations, and associations within existing data, shedding light on relationships within real-world settings.
• Experimental Studies : Geared toward establishing causality by determining the cause-and-effect relationships between variables, often in controlled laboratory environments.
• Observational Studies : Yield real-world data, reflecting the complexities and nuances of natural phenomena.
• Experimental Studies : Generate controlled data, allowing for precise analysis and the establishment of clear causal connections.

Observational studies excel at exploring associations and uncovering patterns within the intricacies of real-world settings, while experimental studies shine as the gold standard for discerning cause-and-effect relationships through meticulous control and manipulation in controlled environments. Understanding these differences and similarities empowers researchers to choose the most appropriate method for their specific research objectives.

When to Use Which: Practical Applications

The decision to employ either observational or experimental studies hinges on the research objectives at hand and the available resources. Observational studies prove invaluable when variable manipulation is impractical or ethically challenging, making them ideal for delving into long-term trends and uncovering intricate associations between certain variables (response variable or explanatory variable). On the other hand, experimental studies emerge as indispensable tools when the aim is to definitively establish causation and methodically control variables.

At Santos Research Center, Corp., our approach to both scientific study and methodology is characterized by meticulous consideration of the specific research goals. We recognize that the quality of outcomes hinges on selecting the most appropriate method of research study. Our unwavering commitment to employing both observational and experimental research studies further underscores our dedication to advancing scientific knowledge across diverse domains.

Conclusion: The Synergy of Experimental and Observational Studies in Research

In conclusion, both observational and experimental studies are integral to scientific research, offering complementary approaches with unique strengths and limitations. At Santos Research Center, Corp., we leverage these methodologies to contribute meaningfully to the scientific community.

Explore our projects and initiatives at Santos Research Center, Corp. by visiting our website or contacting us at (813) 249-9100, where our unwavering commitment to rigorous research practices and advancing scientific knowledge awaits.

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The Ultimate Guide to Qualitative Research - Part 1: The Basics

• Introduction and overview
• What is qualitative research?
• What is qualitative data?
• Examples of qualitative data
• Qualitative vs. quantitative research
• Mixed methods
• Qualitative research preparation
• Theoretical perspective
• Theoretical framework
• Literature reviews

Research question

• Conceptual framework
• Conceptual vs. theoretical framework

Data collection

• Qualitative research methods
• Focus groups
• Observational research

What is a case study?

Applications for case study research, what is a good case study, process of case study design, benefits and limitations of case studies.

• Ethnographical research
• Ethical considerations
• Confidentiality and privacy
• Power dynamics
• Reflexivity

Case studies

Case studies are essential to qualitative research , offering a lens through which researchers can investigate complex phenomena within their real-life contexts. This chapter explores the concept, purpose, applications, examples, and types of case studies and provides guidance on how to conduct case study research effectively.

Whereas quantitative methods look at phenomena at scale, case study research looks at a concept or phenomenon in considerable detail. While analyzing a single case can help understand one perspective regarding the object of research inquiry, analyzing multiple cases can help obtain a more holistic sense of the topic or issue. Let's provide a basic definition of a case study, then explore its characteristics and role in the qualitative research process.

Definition of a case study

A case study in qualitative research is a strategy of inquiry that involves an in-depth investigation of a phenomenon within its real-world context. It provides researchers with the opportunity to acquire an in-depth understanding of intricate details that might not be as apparent or accessible through other methods of research. The specific case or cases being studied can be a single person, group, or organization – demarcating what constitutes a relevant case worth studying depends on the researcher and their research question .

Among qualitative research methods , a case study relies on multiple sources of evidence, such as documents, artifacts, interviews , or observations , to present a complete and nuanced understanding of the phenomenon under investigation. The objective is to illuminate the readers' understanding of the phenomenon beyond its abstract statistical or theoretical explanations.

Characteristics of case studies

Case studies typically possess a number of distinct characteristics that set them apart from other research methods. These characteristics include a focus on holistic description and explanation, flexibility in the design and data collection methods, reliance on multiple sources of evidence, and emphasis on the context in which the phenomenon occurs.

Furthermore, case studies can often involve a longitudinal examination of the case, meaning they study the case over a period of time. These characteristics allow case studies to yield comprehensive, in-depth, and richly contextualized insights about the phenomenon of interest.

The role of case studies in research

Case studies hold a unique position in the broader landscape of research methods aimed at theory development. They are instrumental when the primary research interest is to gain an intensive, detailed understanding of a phenomenon in its real-life context.

In addition, case studies can serve different purposes within research - they can be used for exploratory, descriptive, or explanatory purposes, depending on the research question and objectives. This flexibility and depth make case studies a valuable tool in the toolkit of qualitative researchers.

Remember, a well-conducted case study can offer a rich, insightful contribution to both academic and practical knowledge through theory development or theory verification, thus enhancing our understanding of complex phenomena in their real-world contexts.

What is the purpose of a case study?

Case study research aims for a more comprehensive understanding of phenomena, requiring various research methods to gather information for qualitative analysis . Ultimately, a case study can allow the researcher to gain insight into a particular object of inquiry and develop a theoretical framework relevant to the research inquiry.

Why use case studies in qualitative research?

Using case studies as a research strategy depends mainly on the nature of the research question and the researcher's access to the data.

Conducting case study research provides a level of detail and contextual richness that other research methods might not offer. They are beneficial when there's a need to understand complex social phenomena within their natural contexts.

The explanatory, exploratory, and descriptive roles of case studies

Case studies can take on various roles depending on the research objectives. They can be exploratory when the research aims to discover new phenomena or define new research questions; they are descriptive when the objective is to depict a phenomenon within its context in a detailed manner; and they can be explanatory if the goal is to understand specific relationships within the studied context. Thus, the versatility of case studies allows researchers to approach their topic from different angles, offering multiple ways to uncover and interpret the data .

The impact of case studies on knowledge development

Case studies play a significant role in knowledge development across various disciplines. Analysis of cases provides an avenue for researchers to explore phenomena within their context based on the collected data.

This can result in the production of rich, practical insights that can be instrumental in both theory-building and practice. Case studies allow researchers to delve into the intricacies and complexities of real-life situations, uncovering insights that might otherwise remain hidden.

Types of case studies

In qualitative research , a case study is not a one-size-fits-all approach. Depending on the nature of the research question and the specific objectives of the study, researchers might choose to use different types of case studies. These types differ in their focus, methodology, and the level of detail they provide about the phenomenon under investigation.

Understanding these types is crucial for selecting the most appropriate approach for your research project and effectively achieving your research goals. Let's briefly look at the main types of case studies.

Exploratory case studies

Exploratory case studies are typically conducted to develop a theory or framework around an understudied phenomenon. They can also serve as a precursor to a larger-scale research project. Exploratory case studies are useful when a researcher wants to identify the key issues or questions which can spur more extensive study or be used to develop propositions for further research. These case studies are characterized by flexibility, allowing researchers to explore various aspects of a phenomenon as they emerge, which can also form the foundation for subsequent studies.

Descriptive case studies

Descriptive case studies aim to provide a complete and accurate representation of a phenomenon or event within its context. These case studies are often based on an established theoretical framework, which guides how data is collected and analyzed. The researcher is concerned with describing the phenomenon in detail, as it occurs naturally, without trying to influence or manipulate it.

Explanatory case studies

Explanatory case studies are focused on explanation - they seek to clarify how or why certain phenomena occur. Often used in complex, real-life situations, they can be particularly valuable in clarifying causal relationships among concepts and understanding the interplay between different factors within a specific context.

Intrinsic, instrumental, and collective case studies

These three categories of case studies focus on the nature and purpose of the study. An intrinsic case study is conducted when a researcher has an inherent interest in the case itself. Instrumental case studies are employed when the case is used to provide insight into a particular issue or phenomenon. A collective case study, on the other hand, involves studying multiple cases simultaneously to investigate some general phenomena.

Each type of case study serves a different purpose and has its own strengths and challenges. The selection of the type should be guided by the research question and objectives, as well as the context and constraints of the research.

The flexibility, depth, and contextual richness offered by case studies make this approach an excellent research method for various fields of study. They enable researchers to investigate real-world phenomena within their specific contexts, capturing nuances that other research methods might miss. Across numerous fields, case studies provide valuable insights into complex issues.

Critical information systems research

Case studies provide a detailed understanding of the role and impact of information systems in different contexts. They offer a platform to explore how information systems are designed, implemented, and used and how they interact with various social, economic, and political factors. Case studies in this field often focus on examining the intricate relationship between technology, organizational processes, and user behavior, helping to uncover insights that can inform better system design and implementation.

Health research

Health research is another field where case studies are highly valuable. They offer a way to explore patient experiences, healthcare delivery processes, and the impact of various interventions in a real-world context.

Case studies can provide a deep understanding of a patient's journey, giving insights into the intricacies of disease progression, treatment effects, and the psychosocial aspects of health and illness.

Asthma research studies

Specifically within medical research, studies on asthma often employ case studies to explore the individual and environmental factors that influence asthma development, management, and outcomes. A case study can provide rich, detailed data about individual patients' experiences, from the triggers and symptoms they experience to the effectiveness of various management strategies. This can be crucial for developing patient-centered asthma care approaches.

Other fields

Apart from the fields mentioned, case studies are also extensively used in business and management research, education research, and political sciences, among many others. They provide an opportunity to delve into the intricacies of real-world situations, allowing for a comprehensive understanding of various phenomena.

Case studies, with their depth and contextual focus, offer unique insights across these varied fields. They allow researchers to illuminate the complexities of real-life situations, contributing to both theory and practice.

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Understanding the key elements of case study design is crucial for conducting rigorous and impactful case study research. A well-structured design guides the researcher through the process, ensuring that the study is methodologically sound and its findings are reliable and valid. The main elements of case study design include the research question , propositions, units of analysis, and the logic linking the data to the propositions.

The research question is the foundation of any research study. A good research question guides the direction of the study and informs the selection of the case, the methods of collecting data, and the analysis techniques. A well-formulated research question in case study research is typically clear, focused, and complex enough to merit further detailed examination of the relevant case(s).

Propositions

Propositions, though not necessary in every case study, provide a direction by stating what we might expect to find in the data collected. They guide how data is collected and analyzed by helping researchers focus on specific aspects of the case. They are particularly important in explanatory case studies, which seek to understand the relationships among concepts within the studied phenomenon.

Units of analysis

The unit of analysis refers to the case, or the main entity or entities that are being analyzed in the study. In case study research, the unit of analysis can be an individual, a group, an organization, a decision, an event, or even a time period. It's crucial to clearly define the unit of analysis, as it shapes the qualitative data analysis process by allowing the researcher to analyze a particular case and synthesize analysis across multiple case studies to draw conclusions.

Argumentation

This refers to the inferential model that allows researchers to draw conclusions from the data. The researcher needs to ensure that there is a clear link between the data, the propositions (if any), and the conclusions drawn. This argumentation is what enables the researcher to make valid and credible inferences about the phenomenon under study.

Understanding and carefully considering these elements in the design phase of a case study can significantly enhance the quality of the research. It can help ensure that the study is methodologically sound and its findings contribute meaningful insights about the case.

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Conducting a case study involves several steps, from defining the research question and selecting the case to collecting and analyzing data . This section outlines these key stages, providing a practical guide on how to conduct case study research.

Defining the research question

The first step in case study research is defining a clear, focused research question. This question should guide the entire research process, from case selection to analysis. It's crucial to ensure that the research question is suitable for a case study approach. Typically, such questions are exploratory or descriptive in nature and focus on understanding a phenomenon within its real-life context.

Selecting and defining the case

The selection of the case should be based on the research question and the objectives of the study. It involves choosing a unique example or a set of examples that provide rich, in-depth data about the phenomenon under investigation. After selecting the case, it's crucial to define it clearly, setting the boundaries of the case, including the time period and the specific context.

Previous research can help guide the case study design. When considering a case study, an example of a case could be taken from previous case study research and used to define cases in a new research inquiry. Considering recently published examples can help understand how to select and define cases effectively.

Developing a detailed case study protocol

A case study protocol outlines the procedures and general rules to be followed during the case study. This includes the data collection methods to be used, the sources of data, and the procedures for analysis. Having a detailed case study protocol ensures consistency and reliability in the study.

The protocol should also consider how to work with the people involved in the research context to grant the research team access to collecting data. As mentioned in previous sections of this guide, establishing rapport is an essential component of qualitative research as it shapes the overall potential for collecting and analyzing data.

Collecting data

Gathering data in case study research often involves multiple sources of evidence, including documents, archival records, interviews, observations, and physical artifacts. This allows for a comprehensive understanding of the case. The process for gathering data should be systematic and carefully documented to ensure the reliability and validity of the study.

Analyzing and interpreting data

The next step is analyzing the data. This involves organizing the data , categorizing it into themes or patterns , and interpreting these patterns to answer the research question. The analysis might also involve comparing the findings with prior research or theoretical propositions.

Writing the case study report

The final step is writing the case study report . This should provide a detailed description of the case, the data, the analysis process, and the findings. The report should be clear, organized, and carefully written to ensure that the reader can understand the case and the conclusions drawn from it.

Each of these steps is crucial in ensuring that the case study research is rigorous, reliable, and provides valuable insights about the case.

The type, depth, and quality of data in your study can significantly influence the validity and utility of the study. In case study research, data is usually collected from multiple sources to provide a comprehensive and nuanced understanding of the case. This section will outline the various methods of collecting data used in case study research and discuss considerations for ensuring the quality of the data.

Interviews are a common method of gathering data in case study research. They can provide rich, in-depth data about the perspectives, experiences, and interpretations of the individuals involved in the case. Interviews can be structured , semi-structured , or unstructured , depending on the research question and the degree of flexibility needed.

Observations

Observations involve the researcher observing the case in its natural setting, providing first-hand information about the case and its context. Observations can provide data that might not be revealed in interviews or documents, such as non-verbal cues or contextual information.

Documents and artifacts

Documents and archival records provide a valuable source of data in case study research. They can include reports, letters, memos, meeting minutes, email correspondence, and various public and private documents related to the case.

These records can provide historical context, corroborate evidence from other sources, and offer insights into the case that might not be apparent from interviews or observations.

Physical artifacts refer to any physical evidence related to the case, such as tools, products, or physical environments. These artifacts can provide tangible insights into the case, complementing the data gathered from other sources.

Ensuring the quality of data collection

Determining the quality of data in case study research requires careful planning and execution. It's crucial to ensure that the data is reliable, accurate, and relevant to the research question. This involves selecting appropriate methods of collecting data, properly training interviewers or observers, and systematically recording and storing the data. It also includes considering ethical issues related to collecting and handling data, such as obtaining informed consent and ensuring the privacy and confidentiality of the participants.

Data analysis

Analyzing case study research involves making sense of the rich, detailed data to answer the research question. This process can be challenging due to the volume and complexity of case study data. However, a systematic and rigorous approach to analysis can ensure that the findings are credible and meaningful. This section outlines the main steps and considerations in analyzing data in case study research.

Organizing the data

The first step in the analysis is organizing the data. This involves sorting the data into manageable sections, often according to the data source or the theme. This step can also involve transcribing interviews, digitizing physical artifacts, or organizing observational data.

Categorizing and coding the data

Once the data is organized, the next step is to categorize or code the data. This involves identifying common themes, patterns, or concepts in the data and assigning codes to relevant data segments. Coding can be done manually or with the help of software tools, and in either case, qualitative analysis software can greatly facilitate the entire coding process. Coding helps to reduce the data to a set of themes or categories that can be more easily analyzed.

Identifying patterns and themes

After coding the data, the researcher looks for patterns or themes in the coded data. This involves comparing and contrasting the codes and looking for relationships or patterns among them. The identified patterns and themes should help answer the research question.

Interpreting the data

Once patterns and themes have been identified, the next step is to interpret these findings. This involves explaining what the patterns or themes mean in the context of the research question and the case. This interpretation should be grounded in the data, but it can also involve drawing on theoretical concepts or prior research.

Verification of the data

The last step in the analysis is verification. This involves checking the accuracy and consistency of the analysis process and confirming that the findings are supported by the data. This can involve re-checking the original data, checking the consistency of codes, or seeking feedback from research participants or peers.

Like any research method , case study research has its strengths and limitations. Researchers must be aware of these, as they can influence the design, conduct, and interpretation of the study.

Understanding the strengths and limitations of case study research can also guide researchers in deciding whether this approach is suitable for their research question . This section outlines some of the key strengths and limitations of case study research.

Benefits include the following:

• Rich, detailed data: One of the main strengths of case study research is that it can generate rich, detailed data about the case. This can provide a deep understanding of the case and its context, which can be valuable in exploring complex phenomena.
• Flexibility: Case study research is flexible in terms of design , data collection , and analysis . A sufficient degree of flexibility allows the researcher to adapt the study according to the case and the emerging findings.
• Real-world context: Case study research involves studying the case in its real-world context, which can provide valuable insights into the interplay between the case and its context.
• Multiple sources of evidence: Case study research often involves collecting data from multiple sources , which can enhance the robustness and validity of the findings.

On the other hand, researchers should consider the following limitations:

• Generalizability: A common criticism of case study research is that its findings might not be generalizable to other cases due to the specificity and uniqueness of each case.
• Time and resource intensive: Case study research can be time and resource intensive due to the depth of the investigation and the amount of collected data.
• Complexity of analysis: The rich, detailed data generated in case study research can make analyzing the data challenging.
• Subjectivity: Given the nature of case study research, there may be a higher degree of subjectivity in interpreting the data , so researchers need to reflect on this and transparently convey to audiences how the research was conducted.

Being aware of these strengths and limitations can help researchers design and conduct case study research effectively and interpret and report the findings appropriately.

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OBSERVATION

Methods, Tools & Techniques

Methods, Tools and Techniques are ways of gathering data and collecting the information to learn what changes have happened.

(Adapted from: http://atlasti.com/observational-research )

Observation is a method in which a person observes behaviour to note changes in people or places, typically as the result of an intervention. Most simply it is learning through observing and documenting.

Observation is most common in psychology and other social sciences. It lets the researcher describe situations under study using the five senses.

Using observation in different ways

You can use observational research in different ways.  At one end is the controlled observation, where the researcher completely manages the environment. At the other is participant observation where the researcher joins the group to understand behaviour and changes. Both have strengths and weaknesses which are often linked to how much an evaluator or researcher has influenced the environment and it’s subjects.

Observation covers a lot of ground. It can involve just watching people, listening to everyday conversations, interviewing individuals and or groups, filling questionnaires and checklists. In short, observing.

Naturalistic (or nonparticipant) observation happens when a researcher       doesn’t intervene and studies behaviour that occurs naturally.

In participant observation , the researcher take a full part. Most commonly, this happens when the researcher joins a group to observe behaviour that otherwise would be inaccessible.

Case Studies as observation

Case Studies are a type of observational research that involve a thorough descriptive analysis of a single individual, group, or event. There is no single way to conduct a case study so researchers use a range of methods from unstructured interviewing to direct observation.

VIDEO RESOURCE

Understanding Observational Research

USEFUL RESOURCES

This Forum for Qualitative Social Research site includes a comprehensive explanation of observation methods, recommendations on what to observe , ethics in observation and tips to collect useful data.

This slide deck created by Melanie Bryant from Swinburne University in Australia presents the basics of conducting participant observation in applied research projects.

Characteristics of effective observers

• Having an open, nonjudgmental attitude.
• Being interested in learning about others.
• Being a careful observer, recorder and a good listener.
• Being open to the unexpected.
• Allows insight into contexts, relationships and behaviour. By being able to observe the flow of behaviour in its own setting, the evidence gathered can be more credible than, say, surveys, which rely on the participants’ memory, honesty and awareness.
• Observation is often used to generate new ideas. As it gives the person gathering evidence the opportunity to explore the total situation, it often suggests lines of enquiry and outcomes not thought of before. It can provide new information that is crucial for service improvements, project design, other data collection, and interpretation of other data.

Disadvantages & Limitations

• Observation usually takes a lot of time compared with other methods.
• In social services, observation requires a high level of trust between the person collecting information and participants. Sometimes service staff have easy access to the homes, workplaces and social settings that clients are part of. Often however, these settings are not open to observers, so it can be difficult to find authentic environments to observe changes in behaviour.
• In participant observation it can be difficult to get time/privacy for recording. For example, with participant observations, researchers can’t take notes openly as this would affect their participation. This means they have to wait until they are alone and rely on memory.
• Observations are often small-scale and conclusions may not be able to be generalised. It can also be difficult to claim the intervention was responsible for the changes observed.
• The researcher needs to be trained or experienced enough to recognise events that are significant and worth further attention.
• If the researcher becomes too involved they may lose objectivity and become biased. There is always the danger that we will see what we expect, or want, to see. This is a problem for anyone within an organisation doing any evaluation work.

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Methodology

• What Is Qualitative Observation? | Definition & Examples

What Is Qualitative Observation? | Definition & Examples

Published on March 18, 2023 by Tegan George . Revised on June 22, 2023.

Qualitative observation is a research method where the characteristics or qualities of a phenomenon are described without using any quantitative measurements or data. Rather, the observation is based on the observer’s subjective interpretation of what they see, hear, smell, taste, or feel.

Qualitative observations can be done using various methods, including direct observation, interviews , focus groups , or case studies . They can provide rich and detailed information about the behavior, attitudes, perceptions, and experiences of individuals or groups.

Table of contents

When to use qualitative observation, examples of qualitative observation, types of qualitative observations, advantages and disadvantages of qualitative observations, other interesting articles, frequently asked questions.

Qualitative observation is a type of observational study , often used in conjunction with other types of research through triangulation . It is often used in fields like social sciences, education, healthcare, marketing, and design. This type of study is especially well suited for gaining rich and detailed insights into complex and/or subjective phenomena.

A qualitative observation could be a good fit for your research if:

• You are conducting exploratory research . If the goal of your research is to gain a better understanding of a phenomenon, object, or situation, qualitative observation is a good place to start.
• When your research topic is complex, subjective, or cannot be examined numerically. Qualitative observation is often able to capture the complexity and subjectivity of human behavior, particularly for topics like emotions, attitudes, perceptions, or cultural practices. These may not be quantifiable or measurable through other methods.
• You are relying on triangulation within your research approach. Qualitative observation is a solid addition to triangulation approaches, where multiple sources of data are used to validate and verify research findings.

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Qualitative observation is commonly used in marketing to study consumer behavior, preferences, and attitudes towards products or services.

During the focus group, you focus particularly on qualitative observations, taking note of the participants’ facial expressions, body language, word choice, and tone of voice.

Qualitative observation is often also used in design fields, to better understand user needs, preferences, and behaviors. This can aid in the development of products and services that better meet user needs.

You are particularly focused on any usability issues that could impact customer satisfaction. You run a series of testing sessions, focusing on reactions like facial expressions, body language, and verbal feedback.

There are several types of qualitative observation. Here are some of the most common types to help you choose the best one for your work.

Qualitative observations are a great choice of research method for some projects, but they definitely have their share of disadvantages to consider.

Advantages of qualitative observations

• Qualitative observations allow you to generate rich and nuanced qualitative data —aiding you in understanding a phenomenon or object and providing insights into the more complex and subjective aspects of human experience.
• Qualitative observation is a flexible research method that can be adjusted based on research goals and timeline. It also has the potential to be quite non-intrusive, allowing observation of participants in their natural settings without disrupting or influencing their behavior.
• Qualitative observation is often used in combination with other research methods, such as interviews or surveys , to provide a more complete picture of the phenomenon being studied. This triangulation can help improve the reliability and validity of the research findings.

Disadvantages of qualitative observations

• Like many observational studies, qualitative observations are at high risk for many research biases , particularly on the side of the researcher in the case of observer bias . These biases can also bleed over to the participant size, in the case of the Hawthorne effect or social desirability bias .
• Qualitative observations are typically based on a small sample size , which makes them very unlikely to be representative of the larger population. This greatly limits the generalizability of the findings if used as a standalone method, and the data collection process can be long and onerous.
• Like other human subject research, qualitative observation has its share of ethical considerations to keep in mind and protect, particularly informed consent, privacy, and confidentiality.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Student’s  t -distribution
• Normal distribution
• Null and Alternative Hypotheses
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Data cleansing
• Reproducibility vs Replicability
• Peer review
• Prospective cohort study

Research bias

• Implicit bias
• Cognitive bias
• Placebo effect
• Hawthorne effect
• Hindsight bias
• Affect heuristic
• Social desirability bias

Data analysis in qualitative observation often involves searching for any recurring patterns, themes, and categories in your data. This process may involve coding the data, developing conceptual frameworks or models, and conducting thematic analysis . This can help you generate strong hypotheses or theories based on your data.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

An observational study is a great choice for you if your research question is based purely on observations. If there are ethical, logistical, or practical concerns that prevent you from conducting a traditional experiment , an observational study may be a good choice. In an observational study, there is no interference or manipulation of the research subjects, as well as no control or treatment groups .

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Observation Method in Psychology: Naturalistic, Participant and Controlled

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Associate Editor for Simply Psychology

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On This Page:

The observation method in psychology involves directly and systematically witnessing and recording measurable behaviors, actions, and responses in natural or contrived settings without attempting to intervene or manipulate what is being observed.

Used to describe phenomena, generate hypotheses, or validate self-reports, psychological observation can be either controlled or naturalistic with varying degrees of structure imposed by the researcher.

There are different types of observational methods, and distinctions need to be made between:

1. Controlled Observations 2. Naturalistic Observations 3. Participant Observations

In addition to the above categories, observations can also be either overt/disclosed (the participants know they are being studied) or covert/undisclosed (the researcher keeps their real identity a secret from the research subjects, acting as a genuine member of the group).

In general, conducting observational research is relatively inexpensive, but it remains highly time-consuming and resource-intensive in data processing and analysis.

The considerable investments needed in terms of coder time commitments for training, maintaining reliability, preventing drift, and coding complex dynamic interactions place practical barriers on observers with limited resources.

Controlled Observation

Controlled observation is a research method for studying behavior in a carefully controlled and structured environment.

The researcher sets specific conditions, variables, and procedures to systematically observe and measure behavior, allowing for greater control and comparison of different conditions or groups.

The researcher decides where the observation will occur, at what time, with which participants, and in what circumstances, and uses a standardized procedure. Participants are randomly allocated to each independent variable group.

Rather than writing a detailed description of all behavior observed, it is often easier to code behavior according to a previously agreed scale using a behavior schedule (i.e., conducting a structured observation).

The researcher systematically classifies the behavior they observe into distinct categories. Coding might involve numbers or letters to describe a characteristic or the use of a scale to measure behavior intensity.

The categories on the schedule are coded so that the data collected can be easily counted and turned into statistics.

For example, Mary Ainsworth used a behavior schedule to study how infants responded to brief periods of separation from their mothers. During the Strange Situation procedure, the infant’s interaction behaviors directed toward the mother were measured, e.g.,

• Proximity and contact-seeking
• Contact maintaining
• Avoidance of proximity and contact
• Resistance to contact and comforting

The observer noted down the behavior displayed during 15-second intervals and scored the behavior for intensity on a scale of 1 to 7.

Sometimes participants’ behavior is observed through a two-way mirror, or they are secretly filmed. Albert Bandura used this method to study aggression in children (the Bobo doll studies ).

A lot of research has been carried out in sleep laboratories as well. Here, electrodes are attached to the scalp of participants. What is observed are the changes in electrical activity in the brain during sleep ( the machine is called an EEG ).

Controlled observations are usually overt as the researcher explains the research aim to the group so the participants know they are being observed.

Controlled observations are also usually non-participant as the researcher avoids direct contact with the group and keeps a distance (e.g., observing behind a two-way mirror).

• Controlled observations can be easily replicated by other researchers by using the same observation schedule. This means it is easy to test for reliability .
• The data obtained from structured observations is easier and quicker to analyze as it is quantitative (i.e., numerical) – making this a less time-consuming method compared to naturalistic observations.
• Controlled observations are fairly quick to conduct which means that many observations can take place within a short amount of time. This means a large sample can be obtained, resulting in the findings being representative and having the ability to be generalized to a large population.

Limitations

• Controlled observations can lack validity due to the Hawthorne effect /demand characteristics. When participants know they are being watched, they may act differently.

Naturalistic Observation

Naturalistic observation is a research method in which the researcher studies behavior in its natural setting without intervention or manipulation.

It involves observing and recording behavior as it naturally occurs, providing insights into real-life behaviors and interactions in their natural context.

Naturalistic observation is a research method commonly used by psychologists and other social scientists.

This technique involves observing and studying the spontaneous behavior of participants in natural surroundings. The researcher simply records what they see in whatever way they can.

In unstructured observations, the researcher records all relevant behavior with a coding system. There may be too much to record, and the behaviors recorded may not necessarily be the most important, so the approach is usually used as a pilot study to see what type of behaviors would be recorded.

Compared with controlled observations, it is like the difference between studying wild animals in a zoo and studying them in their natural habitat.

With regard to human subjects, Margaret Mead used this method to research the way of life of different tribes living on islands in the South Pacific. Kathy Sylva used it to study children at play by observing their behavior in a playgroup in Oxfordshire.

Collecting Naturalistic Behavioral Data

Technological advances are enabling new, unobtrusive ways of collecting naturalistic behavioral data.

The Electronically Activated Recorder (EAR) is a digital recording device participants can wear to periodically sample ambient sounds, allowing representative sampling of daily experiences (Mehl et al., 2012).

Studies program EARs to record 30-50 second sound snippets multiple times per hour. Although coding the recordings requires extensive resources, EARs can capture spontaneous behaviors like arguments or laughter.

EARs minimize participant reactivity since sampling occurs outside of awareness. This reduces the Hawthorne effect, where people change behavior when observed.

The SenseCam is another wearable device that passively captures images documenting daily activities. Though primarily used in memory research currently (Smith et al., 2014), systematic sampling of environments and behaviors via the SenseCam could enable innovative psychological studies in the future.

• By being able to observe the flow of behavior in its own setting, studies have greater ecological validity.
• Like case studies , naturalistic observation is often used to generate new ideas. Because it gives the researcher the opportunity to study the total situation, it often suggests avenues of inquiry not thought of before.
• The ability to capture actual behaviors as they unfold in real-time, analyze sequential patterns of interactions, measure base rates of behaviors, and examine socially undesirable or complex behaviors that people may not self-report accurately.
• These observations are often conducted on a micro (small) scale and may lack a representative sample (biased in relation to age, gender, social class, or ethnicity). This may result in the findings lacking the ability to generalize to wider society.
• Natural observations are less reliable as other variables cannot be controlled. This makes it difficult for another researcher to repeat the study in exactly the same way.
• Highly time-consuming and resource-intensive during the data coding phase (e.g., training coders, maintaining inter-rater reliability, preventing judgment drift).
• With observations, we do not have manipulations of variables (or control over extraneous variables), meaning cause-and-effect relationships cannot be established.

Participant Observation

Participant observation is a variant of the above (natural observations) but here, the researcher joins in and becomes part of the group they are studying to get a deeper insight into their lives.

If it were research on animals , we would now not only be studying them in their natural habitat but be living alongside them as well!

Leon Festinger used this approach in a famous study into a religious cult that believed that the end of the world was about to occur. He joined the cult and studied how they reacted when the prophecy did not come true.

Participant observations can be either covert or overt. Covert is where the study is carried out “undercover.” The researcher’s real identity and purpose are kept concealed from the group being studied.

The researcher takes a false identity and role, usually posing as a genuine member of the group.

On the other hand, overt is where the researcher reveals his or her true identity and purpose to the group and asks permission to observe.

• It can be difficult to get time/privacy for recording. For example, researchers can’t take notes openly with covert observations as this would blow their cover. This means they must wait until they are alone and rely on their memory. This is a problem as they may forget details and are unlikely to remember direct quotations.
• If the researcher becomes too involved, they may lose objectivity and become biased. There is always the danger that we will “see” what we expect (or want) to see. This problem is because they could selectively report information instead of noting everything they observe. Thus reducing the validity of their data.

Recording of Data

With controlled/structured observation studies, an important decision the researcher has to make is how to classify and record the data. Usually, this will involve a method of sampling.

In most coding systems, codes or ratings are made either per behavioral event or per specified time interval (Bakeman & Quera, 2011).

The three main sampling methods are:

Event-based coding involves identifying and segmenting interactions into meaningful events rather than timed units.

For example, parent-child interactions may be segmented into control or teaching events to code. Interval recording involves dividing interactions into fixed time intervals (e.g., 6-15 seconds) and coding behaviors within each interval (Bakeman & Quera, 2011).

Event recording allows counting event frequency and sequencing while also potentially capturing event duration through timed-event recording. This provides information on time spent on behaviors.

• Interval recording is common in microanalytic coding to sample discrete behaviors in brief time samples across an interaction. The time unit can range from seconds to minutes to whole interactions. Interval recording requires segmenting interactions based on timing rather than events (Bakeman & Quera, 2011).
• Instantaneous sampling provides snapshot coding at certain moments rather than summarizing behavior within full intervals. This allows quicker coding but may miss behaviors in between target times.

Coding Systems

The coding system should focus on behaviors, patterns, individual characteristics, or relationship qualities that are relevant to the theory guiding the study (Wampler & Harper, 2014).

Codes vary in how much inference is required, from concrete observable behaviors like frequency of eye contact to more abstract concepts like degree of rapport between a therapist and client (Hill & Lambert, 2004). More inference may reduce reliability.

Coding schemes can vary in their level of detail or granularity. Micro-level schemes capture fine-grained behaviors, such as specific facial movements, while macro-level schemes might code broader behavioral states or interactions. The appropriate level of granularity depends on the research questions and the practical constraints of the study.

Another important consideration is the concreteness of the codes. Some schemes use physically based codes that are directly observable (e.g., “eyes closed”), while others use more socially based codes that require some level of inference (e.g., “showing empathy”). While physically based codes may be easier to apply consistently, socially based codes often capture more meaningful behavioral constructs.

Most coding schemes strive to create sets of codes that are mutually exclusive and exhaustive (ME&E). This means that for any given set of codes, only one code can apply at a time (mutual exclusivity), and there is always an applicable code (exhaustiveness). This property simplifies both the coding process and subsequent data analysis.

For example, a simple ME&E set for coding infant state might include: 1) Quiet alert, 2) Crying, 3) Fussy, 4) REM sleep, and 5) Deep sleep. At any given moment, an infant would be in one and only one of these states.

Macroanalytic coding systems

Macroanalytic coding systems involve rating or summarizing behaviors using larger coding units and broader categories that reflect patterns across longer periods of interaction rather than coding small or discrete behavioral acts. 

Macroanalytic coding systems focus on capturing overarching themes, global qualities, or general patterns of behavior rather than specific, discrete actions.

For example, a macroanalytic coding system may rate the overall degree of therapist warmth or level of client engagement globally for an entire therapy session, requiring the coders to summarize and infer these constructs across the interaction rather than coding smaller behavioral units.

These systems require observers to make more inferences (more time-consuming) but can better capture contextual factors, stability over time, and the interdependent nature of behaviors (Carlson & Grotevant, 1987).

Examples of Macroanalytic Coding Systems:

• Emotional Availability Scales (EAS) : This system assesses the quality of emotional connection between caregivers and children across dimensions like sensitivity, structuring, non-intrusiveness, and non-hostility.
• Classroom Assessment Scoring System (CLASS) : Evaluates the quality of teacher-student interactions in classrooms across domains like emotional support, classroom organization, and instructional support.

Microanalytic coding systems

Microanalytic coding systems involve rating behaviors using smaller, more discrete coding units and categories.

These systems focus on capturing specific, discrete behaviors or events as they occur moment-to-moment. Behaviors are often coded second-by-second or in very short time intervals.

For example, a microanalytic system may code each instance of eye contact or head nodding during a therapy session. These systems code specific, molecular behaviors as they occur moment-to-moment rather than summarizing actions over longer periods.

Microanalytic systems require less inference from coders and allow for analysis of behavioral contingencies and sequential interactions between therapist and client. However, they are more time-consuming and expensive to implement than macroanalytic approaches.

Examples of Microanalytic Coding Systems:

• Facial Action Coding System (FACS) : Codes minute facial muscle movements to analyze emotional expressions.
• Specific Affect Coding System (SPAFF) : Used in marital interaction research to code specific emotional behaviors.
• Noldus Observer XT : A software system that allows for detailed coding of behaviors in real-time or from video recordings.

Mesoanalytic coding systems

Mesoanalytic coding systems attempt to balance macro- and micro-analytic approaches.

In contrast to macroanalytic systems that summarize behaviors in larger chunks, mesoanalytic systems use medium-sized coding units that target more specific behaviors or interaction sequences (Bakeman & Quera, 2017).

For example, a mesoanalytic system may code each instance of a particular type of therapist statement or client emotional expression. However, mesoanalytic systems still use larger units than microanalytic approaches coding every speech onset/offset.

The goal of balancing specificity and feasibility makes mesoanalytic systems well-suited for many research questions (Morris et al., 2014). Mesoanalytic codes can preserve some sequential information while remaining efficient enough for studies with adequate but limited resources.

For instance, a mesoanalytic couple interaction coding system could target key behavior patterns like validation sequences without coding turn-by-turn speech.

In this way, mesoanalytic coding allows reasonable reliability and specificity without requiring extensive training or observation. The mid-level focus offers a pragmatic compromise between depth and breadth in analyzing interactions.

Examples of Mesoanalytic Coding Systems:

• Feeding Scale for Mother-Infant Interaction : Assesses feeding interactions in 5-minute episodes, coding specific behaviors and overall qualities.
• Couples Interaction Rating System (CIRS): Codes specific behaviors and rates overall qualities in segments of couple interactions.
• Teaching Styles Rating Scale : Combines frequency counts of specific teacher behaviors with global ratings of teaching style in classroom segments.

Preventing Coder Drift

Coder drift results in a measurement error caused by gradual shifts in how observations get rated according to operational definitions, especially when behavioral codes are not clearly specified.

This type of error creeps in when coders fail to regularly review what precise observations constitute or do not constitute the behaviors being measured.

Preventing drift refers to taking active steps to maintain consistency and minimize changes or deviations in how coders rate or evaluate behaviors over time. Specifically, some key ways to prevent coder drift include:

• Operationalize codes : It is essential that code definitions unambiguously distinguish what interactions represent instances of each coded behavior. 
• Ongoing training : Returning to those operational definitions through ongoing training serves to recalibrate coder interpretations and reinforce accurate recognition. Having regular “check-in” sessions where coders practice coding the same interactions allows monitoring that they continue applying codes reliably without gradual shifts in interpretation.
• Using reference videos : Coders periodically coding the same “gold standard” reference videos anchors their judgments and calibrate against original training. Without periodic anchoring to original specifications, coder decisions tend to drift from initial measurement reliability.
• Assessing inter-rater reliability : Statistical tracking that coders maintain high levels of agreement over the course of a study, not just at the start, flags any declines indicating drift. Sustaining inter-rater agreement requires mitigating this common tendency for observer judgment change during intensive, long-term coding tasks.
• Recalibrating through discussion : Having meetings for coders to discuss disagreements openly explores reasons judgment shifts may be occurring over time. Consensus on the application of codes is restored.
• Adjusting unclear codes : If reliability issues persist, revisiting and refining ambiguous code definitions or anchors can eliminate inconsistencies arising from coder confusion.

Essentially, the goal of preventing coder drift is maintaining standardization and minimizing unintentional biases that may slowly alter how observational data gets rated over periods of extensive coding.

Through the upkeep of skills, continuing calibration to benchmarks, and monitoring consistency, researchers can notice and correct for any creeping changes in coder decision-making over time.

Reducing Observer Bias

Observational research is prone to observer biases resulting from coders’ subjective perspectives shaping the interpretation of complex interactions (Burghardt et al., 2012). When coding, personal expectations may unconsciously influence judgments. However, rigorous methods exist to reduce such bias.

Coding Manual

A detailed coding manual minimizes subjectivity by clearly defining what behaviors and interaction dynamics observers should code (Bakeman & Quera, 2011).

High-quality manuals have strong theoretical and empirical grounding, laying out explicit coding procedures and providing rich behavioral examples to anchor code definitions (Lindahl, 2001).

Clear delineation of the frequency, intensity, duration, and type of behaviors constituting each code facilitates reliable judgments and reduces ambiguity for coders. Application risks inconsistency across raters without clarity on how codes translate to observable interaction.

Coder Training

Competent coders require both interpersonal perceptiveness and scientific rigor (Wampler & Harper, 2014). Training thoroughly reviews the theoretical basis for coded constructs and teaches the coding system itself.

Multiple “gold standard” criterion videos demonstrate code ranges that trainees independently apply. Coders then meet weekly to establish reliability of 80% or higher agreement both among themselves and with master criterion coding (Hill & Lambert, 2004).

Ongoing training manages coder drift over time. Revisions to unclear codes may also improve reliability. Both careful selection and investment in rigorous training increase quality control.

Blind Methods

To prevent bias, coders should remain unaware of specific study predictions or participant details (Burghardt et al., 2012). Separate data gathering versus coding teams helps maintain blinding.

Coders should be unaware of study details or participant identities that could bias coding (Burghardt et al., 2012).

Separate teams collecting data versus coding data can reduce bias.

In addition, scheduling procedures can prevent coders from rating data collected directly from participants with whom they have had personal contact. Maintaining coder independence and blinding enhances objectivity.

Data Analysis Approaches

Data analysis in behavioral observation aims to transform raw observational data into quantifiable measures that can be statistically analyzed.

It’s important to note that the choice of analysis approach is not arbitrary but should be guided by the research questions, study design, and nature of the data collected.

Interval data (where behavior is recorded at fixed time points), event data (where the occurrence of behaviors is noted as they happen), and timed-event data (where both the occurrence and duration of behaviors are recorded) may require different analytical approaches.

Similarly, the level of measurement (categorical, ordinal, or continuous) will influence the choice of statistical tests.

Researchers typically start with simple descriptive statistics to get a feel for their data before moving on to more complex analyses. This stepwise approach allows for a thorough understanding of the data and can often reveal unexpected patterns or relationships that merit further investigation.

simple descriptive statistics

Descriptive statistics give an overall picture of behavior patterns and are often the first step in analysis.

• Frequency counts tell us how often a particular behavior occurs, while rates express this frequency in relation to time (e.g., occurrences per minute).
• Duration measures how long behaviors last, offering insight into their persistence or intensity.
• Probability calculations indicate the likelihood of a behavior occurring under certain conditions, and relative frequency or duration statistics show the proportional occurrence of different behaviors within a session or across the study.

These simple statistics form the foundation of behavioral analysis, providing researchers with a broad picture of behavioral patterns. 

They can reveal which behaviors are most common, how long they typically last, and how they might vary across different conditions or subjects.

For instance, in a study of classroom behavior, these statistics might show how often students raise their hands, how long they typically stay focused on a task, or what proportion of time is spent on different activities.

contingency analyses

Contingency analyses help identify if certain behaviors tend to occur together or in sequence.

• Contingency tables , also known as cross-tabulations, display the co-occurrence of two or more behaviors, allowing researchers to see if certain behaviors tend to happen together.
• Odds ratios provide a measure of the strength of association between behaviors, indicating how much more likely one behavior is to occur in the presence of another.
• Adjusted residuals in these tables can reveal whether the observed co-occurrences are significantly different from what would be expected by chance.

For example, in a study of parent-child interactions, contingency analyses might reveal whether a parent’s praise is more likely to follow a child’s successful completion of a task, or whether a child’s tantrum is more likely to occur after a parent’s refusal of a request.

These analyses can uncover important patterns in social interactions, learning processes, or behavioral chains.

sequential analyses

Sequential analyses are crucial for understanding processes and temporal relationships between behaviors.

• Lag sequential analysis looks at the likelihood of one behavior following another within a specified number of events or time units.
• Time-window sequential analysis examines whether a target behavior occurs within a defined time frame after a given behavior.

These methods are particularly valuable for understanding processes that unfold over time, such as conversation patterns, problem-solving strategies, or the development of social skills.

observer agreement

Since human observers often code behaviors, it’s important to check reliability . This is typically done through measures of observer agreement.

• Cohen’s kappa is commonly used for categorical data, providing a measure of agreement between observers that accounts for chance agreement.
• Intraclass correlation coefficient (ICC) : Used for continuous data or ratings.

Good observer agreement is crucial for the validity of the study, as it demonstrates that the observed behaviors are consistently identified and coded across different observers or time points.

advanced statistical approaches

As researchers delve deeper into their data, they often employ more advanced statistical techniques.

• For instance, an ANOVA might reveal differences in the frequency of aggressive behaviors between children from different socioeconomic backgrounds or in different school settings.
• This approach allows researchers to account for dependencies in the data and to examine how behaviors might be influenced by factors at different levels (e.g., individual characteristics, group dynamics, and situational factors).
• This method can reveal trends, cycles, or patterns in behavior over time, which might not be apparent from simpler analyses. For instance, in a study of animal behavior, time series analysis might uncover daily or seasonal patterns in feeding, mating, or territorial behaviors.

representation techniques

Representation techniques help organize and visualize data:

• Many researchers use a code-unit grid, which represents the data as a matrix with behaviors as rows and time units as columns.
• This format facilitates many types of analyses and allows for easy visualization of behavioral patterns.
• Standardized formats like the Sequential Data Interchange Standard (SDIS) help ensure consistency in data representation across studies and facilitate the use of specialized analysis software.
• Indeed, the complexity of behavioral observation data often necessitates the use of specialized software tools. Programs like GSEQ, Observer, and INTERACT are designed specifically for the analysis of observational data and can perform many of the analyses described above efficiently and accurately.

Bakeman, R., & Quera, V. (2017). Sequential analysis and observational methods for the behavioral sciences. Cambridge University Press.

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10 Observational Research Examples

Dave Cornell (PhD)

Dr. Cornell has worked in education for more than 20 years. His work has involved designing teacher certification for Trinity College in London and in-service training for state governments in the United States. He has trained kindergarten teachers in 8 countries and helped businessmen and women open baby centers and kindergartens in 3 countries.

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Chris Drew (PhD)

This article was peer-reviewed and edited by Chris Drew (PhD). The review process on Helpful Professor involves having a PhD level expert fact check, edit, and contribute to articles. Reviewers ensure all content reflects expert academic consensus and is backed up with reference to academic studies. Dr. Drew has published over 20 academic articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education and holds a PhD in Education from ACU.

Observational research involves observing the actions of people or animals, usually in their natural environments.

For example, Jane Goodall famously observed chimpanzees in the wild and reported on their group behaviors. Similarly, many educational researchers will conduct observations in classrooms to gain insights into how children learn.

Examples of Observational Research

1. jane goodall’s research.

Jane Goodall is famous for her discovery that chimpanzees use tools. It is one of the most remarkable findings in psychology and anthropology .

Her primary method of study involved simply entering the natural habitat of her research subjects, sitting down with pencil and paper, and making detailed notes of what she observed.

Those observations were later organized and transformed into research papers that provided the world with amazing insights into animal behavior.

When she first discovered that chimpanzees use twigs to “fish” for termites, it was absolutely stunning. The renowned Louis Leakey proclaimed: “we must now redefine tool, redefine man, or accept chimps as humans.”

2. Linguistic Development of Children

Answering a question like, “how do children learn to speak,” can only be answered by observing young children at home.

By the time kids get to first grade, their language skills have already become well-developed, with a vocabulary of thousands of words and the ability to use relatively complex sentences.

Therefore, a researcher has to conduct their study in the child’s home environment. This typically involves having a trained data collector sit in a corner of a room and take detailed notes about what and how parents speak to their child.

Those observations are later classified in a way that they can be converted into quantifiable measures for statistical analysis.

For example, the data might be coded in terms of how many words the parents spoke, degree of sentence complexity, or emotional dynamic of being encouraging or critical. When the data is analyzed, it might reveal how patterns of parental comments are linked to the child’s level of linguistic development.

Related Article: 15 Action Research Examples

3. Consumer Product Design  

Before Apple releases a new product to the market, they conduct extensive analyses of how the product will be perceived and used by consumers.

The company wants to know what kind of experience the consumer will have when using the product. Is the interface user-friendly and smooth? Does it fit comfortably in a person’s hand?

Is the overall experience pleasant?

So, the company will arrange for groups of prospective customers come to the lab and simply use the next iteration of one of their great products. That lab will absolutely contain a two-way mirror and a team of trained observers sitting behind it, taking detailed notes of what the test groups are doing. The groups might even be video recorded so their behavior can be observed again and again.

That will be followed by a focus group discussion , maybe a survey or two, and possibly some one-on-one interviews.  

4. Satellite Images of Walmart

Observational research can even make some people millions of dollars. For example, a report by NPR describes how stock market analysts observe Walmart parking lots to predict the company’s earnings.

The analysts purchase satellite images of selected parking lots across the country, maybe even worldwide. That data is combined with what they know about customer purchasing habits, broken down by time of day and geographic region.

Over time, a detailed set of calculations are performed that allows the analysts to predict the company’s earnings with a remarkable degree of accuracy .

This kind of observational research can result in substantial profits.

5. Spying on Farms

Similar to the example above, observational research can also be implemented to study agriculture and farming.

By using infrared imaging software from satellites, some companies can observe crops across the globe. The images provide measures of chlorophyll absorption and moisture content, which can then be used to predict yields. Those images also allow analysts to simply count the number of acres being planted for specific crops across the globe.

In commodities such as wheat and corn, that prediction can lead to huge profits in the futures markets.

It’s an interesting application of observational research with serious monetary implications.

6. Decision-making Group Dynamics  

When large corporations make big decisions, it can have serious consequences to the company’s profitability, or even survival.

Therefore, having a deep understanding of decision-making processes is essential. Although most of us think that we are quite rational in how we process information and formulate a solution, as it turns out, that’s not entirely true.

Decades of psychological research has focused on the function of statements that people make to each other during meetings. For example, there are task-masters, harmonizers, jokers, and others that are not involved at all.

A typical study involves having professional, trained observers watch a meeting transpire, either from a two-way mirror, by sitting-in on the meeting at the side, or observing through CCTV.

By tracking who says what to whom, and the type of statements being made, researchers can identify weaknesses and inefficiencies in how a particular group engages the decision-making process.

See More: Decision-Making Examples

7. Case Studies

A case study is an in-depth examination of one particular person. It is a form of observational research that involves the researcher spending a great deal of time with a single individual to gain a very detailed understanding of their behavior.

The researcher may take extensive notes, conduct interviews with the individual, or take video recordings of behavior for further study.

Case studies give a level of detailed information that is not available when studying large groups of people. That level of detail can often provide insights into a phenomenon that could lead to the development of a new theory or help a researcher identify new areas of research.

Researchers sometimes have no choice but to conduct a case study in situations in which the phenomenon under study is “rare and unusual” (Lee & Saunders, 2017). Because the condition is so uncommon, it is impossible to find a large enough sample of cases to study with quantitative methods.

Go Deeper: Pros and Cons of Case Study Research

8. Infant Attachment

One of the first studies on infant attachment utilized an observational research methodology . Mary Ainsworth went to Uganda in 1954 to study maternal practices and mother/infant bonding.  

Ainsworth visited the homes of 26 families on a bi-monthly basis for 2 years, taking detailed notes and interviewing the mothers regarding their parenting practices.

Her notes were then turned into academic papers and formed the basis for the Strange Situations test that she developed for the laboratory setting.

The Strange Situations test consists of 8 situations, each one lasting no more than a few minutes. Trained observers are stationed behind a two-way mirror and have been trained to make systematic observations of the baby’s actions in each situation.

9. Ethnographic Research  

Ethnography is a type of observational research where the researcher becomes part of a particular group or society.

The researcher’s role as data collector is hidden and they attempt to immerse themselves in the community as a regular member of the group.

By being a part of the group and keeping one’s purpose hidden, the researcher can observe the natural behavior of the members up-close. The group will behave as they would naturally and treat the researcher as if they were just another member. This can lead to insights into the group dynamics , beliefs, customs and rituals that could never be studied otherwise.

10. Time and Motion Studies

Time and motion studies involve observing work processes in the work environment. The goal is to make procedures more efficient, which can involve reducing the number of movements needed to complete a task.

Reducing the movements necessary to complete a task increases efficiency, and therefore improves productivity. A time and motion study can also identify safety issues that may cause harm to workers, and thereby help create a safer work environment.

The two most famous early pioneers of this type of observational research are Frank and Lillian Gilbreth.  

Lilian was a psychologist that began to study the bricklayers of her husband Frank’s construction company. Together, they figured out a way to reduce the number of movements needed to lay bricks from 18 to 4 (see original video footage here ).

The couple became quite famous for their work during the industrial revolution and

Lillian became the only psychologist to appear on a postage stamp (in 1884).

Why do Observational Research?

Psychologists and anthropologists employ this methodology because:

• Psychologists find that studying people in a laboratory setting is very artificial. People often change their behavior if they know it is going to be analyzed by a psychologist later.
• Anthropologists often study unique cultures and indigenous peoples that have little contact with modern society. They often live in remote regions of the world, so, observing their behavior in a natural setting may be the only option.
• In animal studies , there are lots of interesting phenomenon that simply cannot be observed in a laboratory, such as foraging behavior or mate selection. Therefore, observational research is the best and only option available.

Read Also: Difference Between Observation and Inference

Observational research is an incredibly useful way to collect data on a phenomenon that simply can’t be observed in a lab setting. This can provide insights into human behavior that could never be revealed in an experiment (see: experimental vs observational research ).

Researchers employ observational research methodologies when they travel to remote regions of the world to study indigenous people, try to understand how parental interactions affect a child’s language development, or how animals survive in their natural habitats.

On the business side, observational research is used to understand how products are perceived by customers, how groups make important decisions that affect profits, or make economic predictions that can lead to huge monetary gains.

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Ainsworth, M. D. S., Blehar, M., Waters, E., & Wall, S. (1978). Patterns of attachment: A

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Crowe, S., Cresswell, K., Robertson, A., Huby, G., Avery, A., & Sheikh, A. (2011). The case study approach. BMC Medical Research Methodology , 11 , 100. https://doi.org/10.1186/1471-2288-11-100

d’Apice, K., Latham, R., & Stumm, S. (2019). A naturalistic home observational approach to children’s language, cognition, and behavior. Developmental Psychology, 55 (7),1414-1427. https://doi.org/10.1037/dev0000733

Lee, B., & Saunders, M. N. K. (2017).  Conducting Case Study Research for Business and Management Students.  SAGE Publications.

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Observation

Observation, as the name implies, is a way of collecting data through observing. This data collection method is classified as a participatory study, because the researcher has to immerse herself in the setting where her respondents are, while taking notes and/or recording. Observation data collection method may involve watching, listening, reading, touching, and recording behavior and characteristics of phenomena.

Observation as a data collection method can be structured or unstructured. In structured or systematic observation, data collection is conducted using specific variables and according to a pre-defined schedule. Unstructured observation, on the other hand, is conducted in an open and free manner in a sense that there would be no pre-determined variables or objectives.

Moreover, this data collection method can be divided into overt or covert categories. In overt observation research subjects are aware that they are being observed. In covert observation, on the other hand, the observer is concealed and sample group members are not aware that they are being observed. Covert observation is considered to be more effective because in this case sample group members are likely to behave naturally with positive implications on the authenticity of research findings.

Advantages of observation data collection method include direct access to research phenomena, high levels of flexibility in terms of application and generating a permanent record of phenomena to be referred to later. At the same time, this method is disadvantaged with longer time requirements, high levels of observer bias, and impact of observer on primary data, in a way that presence of observer may influence the behaviour of sample group elements.

It is important to note that observation data collection method may be associated with certain ethical issues. As it is discussed further below in greater details, fully informed consent of research participant(s) is one of the basic ethical considerations to be adhered to by researchers. At the same time, the behaviour of sample group members may change with negative implications on the level of research validity if they are notified about the presence of the observer.

This delicate matter needs to be addressed by consulting with dissertation supervisor, and commencing the primary data collection process only after ethical aspects of the issue have been approved by the supervisor.

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Research Methods (Case Studies & Observation Studies) 0 Pages | Leaving School | 31/08/2024

• Case Studies & Observation Studies

——————————————————

Observation Studies

Categories of behaviour: If the researcher is undertaking a natural observation , he may need to divide the behaviour he sees into categories so that a quick record can be made. If the researcher wants to understand how the public respond to a woman collapsing in the street, for example, his categories might include 1.) Ignores and walks on. 2.) Hesitates and walks on. 3.) Checks to see if the woman is ok. 4.) Calls 999.

Inter-observer reliability: In order to test the reliability of an observer’s records, it might be sensible to have two observers who are working to exactly the same category and score sheet, so that they can compare their results at the end of the observation period. If these observations closely match each other then it can be assumed their observations have been accurate. If there is a significant difference it may be necessary to start the observation over again.

Advantages of natural observation Natural observations are high in ecological validity . A string of natural actions can be observed. In a laboratory situation people are often asked to complete unnatural tasks.

Disadvantages of natural observation In the absence ofcontrolled variables it is difficult to establish why someone behaved in a certain way. This type of study is reliant on the accuracy of the observation. There are ethical issues involved in an observation of this kind i.e. the people being observed may not know that this is the case. Should they be told? And if they are told, would their behaviour still be natural? Natural observations can be awkward to plan as well as time consuming.

• Research Methods
• Hypotheses and Experimental Designs
• Standardised Procedures & Instructions
• Ecological Validity & Sampling Methods
• Making Sense of Data & Anomalous Results
• Survey Methods & Ethical Considerations
• Remember it, Test it!

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CANTON, Ohio, August 19, 2024 – US Acute Care Solutions (USACS), the nation’s largest physician-owned emergency and inpatient medicine practice, announced today that it has named Kelly Abbrescia, DO, MMM, FACEP, a Regional Vice President of its South Division. Most recently, Dr. Abbrescia served as the Medical Director at Carteret Health Care in Morehead City, NC. Throughout her career, Dr. Abbrescia has held numerous leadership roles, notably serving as the System Medical Director at Bayhealth Medical Center prior to joining USACS. She also served as a Major in the US Army at Brooke Army Medical Center in Fort Sam Houston, Texas, after completing an Emergency Medical Services (EMS) fellowship. President of the USACS South Division, Brandon Lewis, DO, MBA, FACEP, FACOEP, said, “Dr. Abbrescia has been highly impressive in her short tenure with us, and we expect great things from her as she steps into this role for our division. Our leadership team is looking forward to working with her in this new capacity.” Dr. Abbrescia said, “Since joining USACS, I have been impressed by the outstanding leadership efforts that have taken place and felt called to apply for this instrumental role within the South Division. It is an honor and privilege to serve my colleagues as a regional vice president and I am eager to hit the ground running to make an immediate impact.” Dr. Abbrescia earned her bachelor’s degree from Duquesne University and her medical degree from Philadelphia College of Osteopathic Medicine. She went on to complete her emergency medicine residency and EMS fellowship at Albert Einstein Medical Center where she served as Chief Resident. Dr. Abbrescia also earned her master’s degree in medical management from Carnegie Mellon University – Heinz School of Business and is Lean Six Sigma Green Belt certified. About USACS Founded by emergency medicine and inpatient physicians across the country, USACS is solely owned by its physicians and hospital system partners. The group is a national leader in integrated acute care, including emergency medicine, hospitalist, and critical care services. USACS provides high-quality care to approximately ten million patients annually across more than 400 programs and is aligned with many of the leading health systems in the country. Visit usacs.com for more. ### Media Contact Marty Richmond Corporate Communications Department US Acute Care Solutions 330.493.4443 x1406 [email protected]

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Observation Care That Works

The Challenge

How to cut length of stay, lower readmissions and raise patient satisfaction with a dedicated observation unit. .

A dedicated observation care unit forms an essential component of the integrated network of inpatient and outpatient services that combine to achieve the triple-aim: improved patient experiences, better outcomes and lowered costs.

US Acute Care Solutions can point to years of data - and outcomes - that prove the immense value of a dedicated observation care unit. 

The Solution

The usacs observation care model.

Several characteristics distinguish the USACS model:

• A Dedicated Unit

Open Observation Units inevitably fall victim to misuse by other operations within the hospital. With extensive experience, USACS has proven that this approach creates bottlenecks and crowding. Maintaining a closed unit prevents this, and provides a home for specially trained providers with clear protocols and procedures.

• Specially Trained Observation Providers

USACS has invested heavily in training programs for NPs and PAs to ensure superior observation care. Observation patients are distinguished by a very specific set of symptoms and presentations, allowing USACS to tailor its educational programs around the specific situations and criteria our providers regularly encounter.

•  Quality & Efficient Care

As in USACS Emergency Departments, Observation Units are furnished with a variety of quality control mechanisms and efficiency protocols. All USACS Observation Care units have achieved an average length of stay under 20 hours.

• Clear Admission Protocols

Failure to adequately define what qualifies as an observation patient and failure to adequately educate the care providers on the criteria are hallmarks of an underperforming observation care program. USACS educates both the Emergency Department providers and the Observation Care providers on the criteria for observation care patients while continually evaluating individual protocols to calibrate the scope as appropriate.

The Results

90 th percentile or higher for patient satisfaction, key performance goals: observation care.

All USACS  Observation Care units  aim for and have achieved the following key performance measures:

• Quality: Readmit rate of less than 3%
• Throughput: A length of stay of less than 20 hours
• Patient Satisfaction: 90th percentile or higher

While USACS units have seen dramatic falls in Length of Stay for its Observation Care patients, the introduction of a dedicated USACS Observation Care unit also contributes additional benefits, including reduced Left Without Being Seen (LWBS) rates in the Emergency Department, reduced reliance on diversion and boarding hours, and reduced need for management by hospitalists. Hospitals also face less exposure to RAC audits.

Finally, the addition of a dedicated Observation Care unit has helped USACS partner hospitals position themselves for the future. As a result of improved ability to manage growing patient populations, hospitals now face less pressure to devote resources to facilities expansion and managing overcrowding. Instead, it can focus on delivering quality and efficient care to their communities.

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• Research Methods
• Post last modified: 26 August 2021
• Reading time: 36 mins read
• Post category: Research Methodology

4 Research Methods

4 Major Research Methods are:

Observations

Schedule and questionnaire, case study method.

Table of Content

• 1.1.1 Types of Interview
• 1.1.2 Features of Interviews
• 1.1.3 Essentials for an Effective Interview
• 1.1.4 Advantages of Interviews
• 1.1.5 Disadvantages of Interviews
• 1.1.6 Interview Process
• 1.1.7 Problems Faced in an Interview
• 1.2.1 Characteristics of Observation Method
• 1.2.2 Types of Observation
• 1.2.3 Prerequisites of Observation
• 1.2.4 Advantages of observations
• 1.2.5 Disadvantages of observations
• 1.2.6 Use of observation in business research
• 1.3.1 Importance of questionnaires
• 1.3.2 Types of Questionnaire
• 1.3.3 Advantages of Questionnaires
• 1.3.4 Disadvantages of Questionnaires
• 1.3.5 Preparation of an Effective Questionnaire
• 1.3.6 Difference between schedule and questionnaire
• 1.4.1 Assumptions of case study method
• 1.4.2 Advantages of Case Study Method
• 1.4.3 Disadvantages of Case Study Method
• 1.4.4 Case study as a method of business research

Interviewing is a very effective method of data collection. It is a systematic and objective conversation between an investigator and respondent for collecting relevant data for a specific research study. Along with conversation, learning about the gestures, facial expressions and environmental conditions of a respondent are also very important.

Generally, interview collects a wide range of data from factual demographic data to highly personal and intimate information relating to a person’s opinions, attitudes, values and beliefs, past experience and future intentions.

The interview method is very important in the collection of data from the respondent who is less educated or illiterate. Personal interview is more feasible when the area covered for survey is compact. Probing is a very important part of an interview.

Types of Interview

The following are the various types of interviews:

Structured or directive interview

In this type of interview, the investigator goes to the respondent with a detailed schedule. Some questions in same sequence are asked from all respondents.

Unstructured or non-directive interview

In this type of interview, the respondent is encouraged to give his honest opinion on a given topic without or with minimum help from others.

Focused interview

This is a semi-structured interview where the respondent shares the effect of the experience to the given conditions with the researcher or investigator. It is conducted with those respondents only who have prior experience of conditions given by the investigator.

Analysis of the attitude, emotional feelings for the situations under study is main purpose behind conducting these interviews. A set of fix questions may not be required in this interview but a relevant topic is required which is known to the respondent.

Clinical interview

While a focussed interview is concerned with effects of specific experience, clinical interviews are concerned with broad underlying feelings or motivations or the course of the individual’s life experiences with reference to the research study. It encourages the interviewee to share his experience freely.

Depth interview

To analyse or study the respondent’s emotions, opinions, etc., depth interviews are conducted. This kind of interview aims to collect intensive data about individuals, especially their opinions.

It is a lengthy process to get unbiased data from the respondent. Interviewers should avoid advising or showing this agreement. Instead, the investigator has to motivate the respondent to answer the questions.

Features of Interviews

The following are some of the features of interviews

• The interviewer and the respondent are the participants in any interview. They both are unknown to each other and so it is important for an interviewer to introduce himself first to the respondent.
• An interview has a beginning and a termination point in the relationship between the participants.
• Interview is not a mere casual conversational exchange. It has a specific purpose of collecting data which is relevant to the study.
• Interview is a mode of obtaining a verbal response to questions to put verbally. It is not always face to face.
• Success of interview depends on the interviewer and respondent and how they perceive each other.
• It is not a standardized process.

Essentials for an Effective Interview

The following are the requirements for a successful interview:

• Data availability : The respondent should have complete knowledge of the information required for specific study.
• Role perception : The interviewer and the respondent should be aware of their roles in the interview process. The respondent should be clear about the topic or questions which have to be answered by him. Similarly, it is the responsibility of the interviewer to make the respondent comfortable by introducing himself first. The investigator should not affect the interview situation through subjective attitude and argumentation.
• Respondent’s motivation : The respondent can hesitate to answer the questions. In this case, the approach and skills of the interviewer are very important as he has to motivate the respondent to answer or express himself.

Advantages of Interviews

The following are the advantages of the interview method:

• In-depth and detailed information is collected.
• The interviewer tries to improve the responses and quality of data received.
• He can control the conditions in favour of the research study.
• Interviews help in gathering supplementary information which can be helpful to the study.
• Interviews use special scoring devices, visuals and materials to improve the quality of data or information collected.
• Interviews use observation and probing by the interviewer to see the accuracy and dependability of given data by the respondent.
• Interviews are flexible in nature.

Disadvantages of Interviews

The following are the disadvantages of interviews:

• Interviews consume more time and cost.
• The respondent’s responses can be affected by the way the interviewer asks the questions.
• The respondent may refuse to answer some personal questions which are relevant to the study.
• Recording and coding of data during the interview process may sometimes be difficult for the interviewer.
• The interviewer may not have good communication or interactive skills.

Interview Process

The following are the stages in an interview process:

Preparation

The interviewer needs to make certain preparations to make an interview successful. The interviewer should keep all the copies of the schedule or guide ready. They need to prepare the lists of respondents with their addresses, contact number and meeting time.

They should prepare themselves with all the approaches and skills required to conduct an interview. They should prepare themselves to face all adverse situations during the interview. If the interviewer is not doing such planning, they can fail to collect the right information from respondent.

Introduction

The interviewer is not known to the respondent. Therefore, the interviewer must introduce himself first to every respondent. In the introduction, the interviewer should tell about himself, his organization details and the purpose of his visit.

If the interviewer knows someone who the respondent is familiar with, then he can use that person’s reference to make the respondent more comfortable. The following are some steps which help in motivating the respondent:

• The interviewer should introduce himself with a smiling face and always greet the respondent.
• He should identify and call the respondent by name.
• He must describe how the respondent is selected.
• He should explain the purpose and usefulness of the study.
• He should focus on the value of the respondent’s cooperation.

Developing report

It is important for an interviewer to develop a rapport with the respondent before starting the interview. By doing this, a cordial relationship is established between them. It helps the interviewer understand the inherent nature of the respondent which helps in building a rapport and the discussion can be started with some general topic or with the help of a person who is commonly known to both of them.

Carrying the interview forward

After establishing a rapport, the skills of the interviewer are required to carry the interview forward. The following are some guidelines that should be followed:

• Start the interview in an informal and natural manner.
• Ask all the questions in the same sequence as in the schedule.
• Do not take an answer for granted. It is not necessary that an interviewee will know all answers or will give all answers. The interviewer has to create interest for answering questions.
• The objective of the question should be known to the interviewer to ensure that the correct information is collected for research study.
• Explain the question if it has not been understood properly by the respondent.
• Listen to the respondent carefully with patience.
• Never argue with the respondent.
• Show your concern and interest in the information given by the respondent.
• Do not express your own opinion for answers of any question in the schedule.
• Continue to motivate the respondent.
• If the respondent is unable to frame the right answer, the interviewer should help him by providing alternate questions.
• Ensure that the conversation does not go off track.
• If the respondent is unable to answer a particular question due to some reasons, drop the question at that moment. This question can be asked indirectly later on.

Recording the interview

Responses should be recorded in the same sequence as they are given by the respondent. The response should be recorded at the same time as it is generated. It may be very difficult to remember all the responses later for recording them.

Recording can be done in writing but there may be some problems if the writing skills of an interviewer are not good. Hence, the use of electronic devices like tape recorders can help in this purpose. The interviewer should also record all his probes and other comments on the schedule, but they should be in brackets to ensure that they are set off from response.

Closing the interview

After the interview is over, the interviewer must thank the respondent for his cooperation. He must collect all the papers before leaving the respondent. If the respondent wants to know the result of the survey, the interviewer must ensure that the results are mailed to him when they are ready.

At the end, the interviewer must edit the schedule to check that all the questions have been asked and recorded. Also, abbreviations in recording should be replaced by full words.

Problems Faced in an Interview

The following are some of the main problems faced in an interview:

Inadequate response

Kahn and Cannel laid down five principal symptoms of inadequate response. They are given as follows:

• Partial response in which the respondent gives a relevant but incomplete answer.
• Non-response in which the respondent remains silent or refuses to answer the questions.
• Irrelevant response in which the respondent’s answer is not relevant to the question asked.
• Inaccurate response in which the reply is biased.
• Verbalized response problem which arises because of the respondent’s failure to understand the question.

Interviewer’s biasness, refusal, incapability to understand questions

An interviewer can affect the performance of an interview with his own responses and suggestions. Such biasing factors can never be overcome fully, but their effect can be reduced by training and development techniques.

Non response

Some respondents out of the total respondents fail to respond to the schedule. The reasons for this non response can be non availability, refusal, incapability to understand questions, etc.

Non availability

Some respondents are not available at their places at the time of call. This could be because of odd timings or working hours.

Some respondents refuse to answer the questions. There can be many reasons for this, such as language, odd hours, sickness, no interest in such studies, etc.

Inaccessibility

Some respondents can be inaccessible because of various reasons such as migration, touring job, etc.

Observation can be defined as viewing or seeing. Observation means specific viewing with the purpose of gathering the data for a specific research study. Observation is a classical method of scientific study. It is very important in any research study as it is an effective method for data collection.

Characteristics of Observation Method

The following are the characteristics of the observation method of data collection:

• Physical and mental activity : Eyes observe so many things in our surroundings but our focus or attention is only on data which is relevant to research study.
• Observation is selective : It is very difficult for a researcher to observe everything in his surroundings. He only observes the data which is purposive for his research study and meets with the scope of his study. The researcher ignores all the data which is not relevant to the study.
• Observation is purposive and not casual : Observation is purposive as it is relevant to a particular study. The purpose of observation is to collect data for the research study. It focusses on human behaviour which occurs in a social phenomenon. It analyses the relationship of different variables in a specific context.
• Accuracy and standardization : Observation of pertinent data should be accurate and standardized for its applications.

Types of Observation

Different concepts define the classification of observations.

With respect to an investigator’s role, observation may be:

Participant observation

Non-participant observation

With respect to the method of observation, it can be classified into the following:

Direct observation

Indirect observation

With reference to the control on the system to be observed, observation can be classified into the following:

Controlled observation

Uncontrolled observation

In participant type of observation, the observer is an active participant of the group or process. He participates as well as observes as a part of a phenomenon;

For example, to study the behaviour of management students towards studying and understanding marketing management, the observer or researcher has to participate in the discussion with students without telling them about the observation or purpose. When respondents are unaware of observations, then only their natural interest can be studied.

In non-participant observation, the observer does not participate in the group process. He acknowledges the behaviour of the group without telling the respondents. It requires a lot of skills to record observations in an unnoticeable manner.

In direct observation, the observer and researcher personally observe all the happenings of a process or an event when the event is happening. In this method, the observer records all the relevant aspects of an event which are necessary for study.

He is free to change the locations and focus of the observation. One major limitation of the method is that the observer may not be able to cover all relevant events when they are happening.

Physical presence of an observer is not required and recording is done with the help of mechanical, photographic or electronic devices;

For example, close circuit TV (CCTV) cameras are used in many showrooms to observe the behaviour of customers. It provides a permanent record for an analysis of different aspects of the event.

All observations are done under pre-specified conditions over extrinsic and intrinsic variables by adopting experimental design and systematically recording observations. Controlled observations are carried out either in the laboratory or the field.

There is no control over extrinsic and intrinsic variables. It is mainly used for descriptive research. Participant observation is a typical uncontrolled one.

Prerequisites of Observation

The following are the prerequisites of observation:

• The conditions of observation must provide accurate results. An observer should be in a position to observe the object clearly.
• The right number of respondents should be selected as the sample size for the observation to produce the desired results.
• Accurate and complete recording of an event.
• If it is possible, two separate observers and sets of instruments can be used in all or some observations. Then the result can be compared to measure accuracy and completeness.

Advantages of observations

The following are the advantages of observations:

• It ensures the study of behaviour in accordance with the occurrence of events. The observer does not ask anything from the representatives, he just watches the doing and saying of the sample.
• The data collected by observation defines the observed phenomenon as they occur in their natural settings.
• When an object is not able to define the meaning of its behaviour, observation is best method for analysis; for example, animals, birds and children.
• Observation covers the entire happenings of an event.
• Observation is less biased as compared to questioning.
• It is easier to conduct disguised observation studies as opposed to disguised questioning.
• The use of mechanical devices can generate accurate results.

Disadvantages of observations

The following are the limitations of observation:

• Past studies and events are of no use to observation. For these events and study, one has to go through narrations, people and documents.
• It is difficult to understand attitudes with the help of observation.
• Observations cannot be performed by the choice of the observer. He has to wait for an event to occur.
• It is difficult to predict when and where the event will occur. Thus, it may not be possible for an observer to reach in every event.
• Observation requires more time and money.

Use of observation in business research

Observation is very useful in the following business research purposes:

• Buying behaviour of customer, lifestyles, customs, interpersonal relations, group dynamics, leadership styles, managerial style and actions.
• Physical characteristics of inanimate things like houses, factories, stores, etc.
• Movements in a production plant.
• Flow of traffic, crowd and parking on road.

Primary data can be collected with the help of emails and surveys. The respondents receive the questionnaires from the researcher and are asked to fill them completely and return them to the researcher. It can be performed only when the respondents are educated.

The mail questionnaire should be simple and easy to understand so that the respondents can answer all questions easily. In mail questionnaires, all the answers have to be given and recorded by the respondents and not by the researcher or investigator, as in the case of the personal interview method. There is no face-to-face interaction between the investigator and respondent and so the respondent is free to give answers of his own choice.

Importance of questionnaires

A questionnaire is a very effective method as well as research tool in any research study. It ensures the collection of a diversified and wide range of scientific data to complete the research objectives. The questionnaire provides all the inputs in the form of relevant data to all statistical methods used in a research study.

Types of Questionnaire

The following are the various categories of questionnaires:

• Structured or standard questionnaire Structured or standard questionnaires contain predefined questions in order to collect the required data for research study. These questions are the same for all the respondents. Questions are in the same language and in the same order for all the respondents.
• Unstructured questionnaire In unstructured questionnaires, the respondent has the freedom

Process of Data Collection

The researcher prepares the mailing list by collecting the addresses of all the respondents with the help of primary and secondary sources of data. A covering letter must accompany every questionnaire, indicating the purpose and importance of the research and importance of cooperation of the respondent for the success of the research study.

Advantages of Questionnaires

The following are the advantages of questionnaires:

• Wide reach and extensive coverage
• Easy to contact the person who is busy
• Respondent’s convenience in completion of questionnaire
• More impersonal, provides more anonymity
• No interviewer’s biasness

Disadvantages of Questionnaires

The following are the disadvantages of questionnaires:

• Low response by respondent
• Low scope in many societies where literary level is low
• More time requirement

Preparation of an Effective Questionnaire

While preparing a questionnaire, the researcher must focus on some key parameters to prepare it. These key parameters are as follows:

• Proper use of open and close probe
• Proper sequence of questions
• Use of simple language
• Asking no personal question in which the respondent is hesitating to answer
• Should not be time consuming
• Use of control questions indicating reliability of the respondent

Collecting Data through Schedule

This method is very similar to the collection of data through questionnaires. The only difference is that in schedule, enumerators are appointed. These enumerators go to the respondents, ask the stated questions in the same sequence as the schedule and record the reply of respondents.

Schedules may be given to the respondents and the enumerators should help them solve the problems faced while answering the question in the given schedule. Thus, enumerator selection is very important in data collection through schedules.

Difference between schedule and questionnaire

Both questionnaire and schedule are popular methods of data collection. The following are the main differences between questionnaire and schedule:

• A questionnaire is generally sent to the respondents through mail, but in case of schedule, it is sent through enumerators.
• Questionnaires are relatively cheaper mediums of data collection as compared to schedules. In the case of questionnaires, the cost is incurred in preparing it and mailing it to respondent, while in schedule, more money is required for hiring enumerators, training them and incurring their field expenses.
• The response rate in questionnaires is low as many people return it without filling. On the other hand, the response rate in schedules is high because they are filled by enumerators.
• In collecting data through questionnaires, the identity of the respondent may not be known, but this is not the case when it comes to schedules.
• Data collection through questionnaires requires a lot of time, which is comparatively very less in case of schedules.
• Generally, there is no personal contact in case of questionnaires, but in schedules, personal contact is always there.
• The literacy level of the respondent is very important while filling questionnaires, but in schedules, the literacy level of the respondent is not a major concern as the responses have to be recorded by enumerators.
• Wider distribution of questionnaires is possible but this is difficult with schedules.
• There is less accuracy and completeness of responses in questionnaires as compared to schedules.
• The success of questionnaires depends on the quality of questions but success of a schedule depends on the enumerators.
• The physical appearance of questionnaire matters a lot, which is less important in case of schedules.
• Observation method cannot be used along with questionnaires but it can be used along with schedule.

We explore and analyse the life of a social chapter or entity, whether it be a family, a person, an institution or a community, with the help of a case study. The purpose of case study method is to identify the factors and reasons that account for particular behaviour patterns of a sample chapter and its association with other social or environmental factors.

Generally social researchers use case study method to understand the complex social phenomenon and to identify the factors related to this phenomenon.

Case study provides the clues and ideas to a researcher for further research study. By adopting case study method, a researcher gets to know about happenings in the past, which could be related to the research studies and analyse the problem with better perspectives.

Assumptions of case study method

The assumptions made in a case study method are as follows:

• Case study depends on the imagination of the investigator who is analysing the case study. The investigator makes up his procedure as he goes along.
• History related to the case is complete and as coherent as it could be.
• It is advisable to supplement the case data by observational, statistical and historical data, since these provide standards for assessing the reliability and consistency of the case material.
• Efforts should be made to ascertain the reliability of life history data by examining the internal consistency of the material.
• A judicious combination of techniques of data collection is a prerequisite for securing data that is culturally meaningful and scientifically significant.

Advantages of Case Study Method

Key advantages of the case study method are as follows:

• Provides the basis for understanding complex social phenomenon and all related factors affecting the social phenomenon.
• Provides clues and ideas for exploratory research. When the researcher is not able to get a fair idea about the research, past happenings mentioned in a case study help the researcher get clues and ideas.
• Case study helps in generating objectives for exploratory research.
• It suggests the new courses of inquiry.
• Case study helps in formulating research hypothesis.

Disadvantages of Case Study Method

Some important disadvantages of case study method are as follows:

• Reliability : Data collected through case study may not be reliable or it can be difficult to verify the reliability of data in the current scenario.
• Adequacy : Data collected through case studies may not be adequate for research work as data is not pertinent to the research conditions.
• Representative : Data presented by case studies represents the happenings with unknown circumstances to a researcher. Hence, it cannot be the true representation of events to a researcher.

Case study as a method of business research

A detailed case study helps the researcher identify the reasons behind business related problems. As it can be possible that that particular incident has happened in past, so the current issues can be sorted out, by referring to the same case.

In depth analysis of selected cases is of particular value to business research when a complex set of variables may be at work in generating observed results and intensive study is needed to unravel the complexities.

The exploratory investigator should have an active curiosity and willingness to deviate from the initial plan, when the finding suggests a new course of enquiry, which might prove more productive. With the help of case study method, the risk can be minimized in any decision-making process.

Business Ethics

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Corporate social responsibility (CSR)

• Theories of CSR
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• Developing a CSR Strategy
• Implement CSR Commitments
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• Environmental CSR
• CSR with Communities and in Supply Chain
• Community Interventions
• CSR Monitoring
• CSR Reporting
• Voluntary Codes in CSR
• What is Corporate Ethics?

Lean Six Sigma

• What is Six Sigma?
• What is Lean Six Sigma?
• Value and Waste in Lean Six Sigma
• Six Sigma Team
• MAIC Six Sigma
• Six Sigma in Supply Chains
• What is Binomial, Poisson, Normal Distribution?
• What is Sigma Level?
• What is DMAIC in Six Sigma?
• What is DMADV in Six Sigma?
• Six Sigma Project Charter
• Project Decomposition in Six Sigma
• Critical to Quality (CTQ) Six Sigma
• Process Mapping Six Sigma
• Flowchart and SIPOC
• Gage Repeatability and Reproducibility
• Statistical Diagram
• Lean Techniques for Optimisation Flow
• Failure Modes and Effects Analysis (FMEA)
• What is Process Audits?
• Six Sigma Implementation at Ford
• IBM Uses Six Sigma to Drive Behaviour Change
• Research Methodology
• What is Research?
• What is Hypothesis?
• Sampling Method
• Data Collection in Research

Methods of Collecting Data

• Application of Business Research
• Levels of Measurement
• What is Sampling?
• Hypothesis Testing

Research Report

• What is Management?
• Planning in Management
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• What is Controlling?
• What is Coordination?
• What is Staffing?
• Organization Structure
• What is Departmentation?
• Span of Control
• What is Authority?
• Centralization vs Decentralization
• Organizing in Management
• Schools of Management Thought
• Classical Management Approach
• Is Management an Art or Science?
• Who is a Manager?

Operations Research

• What is Operations Research?
• Operation Research Models
• Linear Programming
• Linear Programming Graphic Solution
• Linear Programming Simplex Method
• Linear Programming Artificial Variable Technique
• Duality in Linear Programming
• Transportation Problem Initial Basic Feasible Solution
• Transportation Problem Finding Optimal Solution
• Project Network Analysis with Critical Path Method
• Project Network Analysis Methods
• Project Evaluation and Review Technique (PERT)
• Simulation in Operation Research
• Replacement Models in Operation Research

Operation Management

• What is Strategy?
• What is Operations Strategy?
• Operations Competitive Dimensions
• Operations Strategy Formulation Process
• What is Strategic Fit?
• Strategic Design Process
• Focused Operations Strategy
• Corporate Level Strategy
• Expansion Strategies
• Stability Strategies
• Retrenchment Strategies
• Competitive Advantage
• Strategic Choice and Strategic Alternatives
• What is Production Process?
• What is Process Technology?
• What is Process Improvement?
• Strategic Capacity Management
• Production and Logistics Strategy
• Taxonomy of Supply Chain Strategies
• Factors Considered in Supply Chain Planning
• Operational and Strategic Issues in Global Logistics
• Logistics Outsourcing Strategy
• What is Supply Chain Mapping?
• Supply Chain Process Restructuring
• Points of Differentiation
• Re-engineering Improvement in SCM
• What is Supply Chain Drivers?
• Supply Chain Operations Reference (SCOR) Model
• Customer Service and Cost Trade Off
• Internal and External Performance Measures
• Linking Supply Chain and Business Performance
• Netflix’s Niche Focused Strategy
• Disney and Pixar Merger
• Process Planning at Mcdonald’s

Service Operations Management

• What is Service?
• What is Service Operations Management?
• What is Service Design?
• Service Design Process
• Service Delivery
• What is Service Quality?
• Gap Model of Service Quality
• Juran Trilogy
• Service Performance Measurement
• Service Decoupling
• IT Service Operation
• Service Operations Management in Different Sector

Procurement Management

• What is Procurement Management?
• Procurement Negotiation
• Types of Requisition
• RFX in Procurement
• What is Purchasing Cycle?
• Vendor Managed Inventory
• Internal Conflict During Purchasing Operation
• Spend Analysis in Procurement
• Sourcing in Procurement
• Supplier Evaluation and Selection in Procurement
• Blacklisting of Suppliers in Procurement
• Total Cost of Ownership in Procurement
• Incoterms in Procurement
• Documents Used in International Procurement
• Transportation and Logistics Strategy
• What is Capital Equipment?
• Procurement Process of Capital Equipment
• Acquisition of Technology in Procurement
• What is E-Procurement?
• E-marketplace and Online Catalogues
• Fixed Price and Cost Reimbursement Contracts
• Contract Cancellation in Procurement
• Ethics in Procurement
• Legal Aspects of Procurement
• Global Sourcing in Procurement
• Intermediaries and Countertrade in Procurement

Strategic Management

• What is Strategic Management?
• What is Value Chain Analysis?
• Mission Statement
• Business Level Strategy
• What is SWOT Analysis?
• What is Competitive Advantage?
• What is Vision?
• What is Ansoff Matrix?
• Prahalad and Gary Hammel
• Strategic Management In Global Environment
• Competitor Analysis Framework
• Competitive Rivalry Analysis
• Competitive Dynamics
• What is Competitive Rivalry?
• Five Competitive Forces That Shape Strategy
• What is PESTLE Analysis?
• Fragmentation and Consolidation Of Industries
• What is Technology Life Cycle?
• What is Diversification Strategy?
• What is Corporate Restructuring Strategy?
• Resources and Capabilities of Organization
• Role of Leaders In Functional-Level Strategic Management
• Functional Structure In Functional Level Strategy Formulation
• Information And Control System
• What is Strategy Gap Analysis?
• Issues In Strategy Implementation
• Matrix Organizational Structure
• What is Strategic Management Process?

Supply Chain

• What is Supply Chain Management?
• Supply Chain Planning and Measuring Strategy Performance
• What is Warehousing?
• What is Packaging?
• What is Inventory Management?
• What is Material Handling?
• What is Order Picking?
• Receiving and Dispatch, Processes
• What is Warehouse Design?
• What is Warehousing Costs?

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• Study Protocol
• Open access
• Published: 28 August 2024

ALLin4IPE- an international research study on interprofessional health professions education: a protocol for an ethnographic multiple-case study of practice architectures in sites of students’ interprofessional clinical placements across four universities

• Annika Lindh Falk 1 ,
• Madeleine Abrandt Dahlgren 1 ,
• Johanna Dahlberg 1 ,
• Bente Norbye 2 ,
• Anita Iversen 2 ,
• Kylie J. Mansfield 3 ,
• Eileen McKinlay 4 ,
• Sonya Morgan 4 ,
• Julia Myers 4 &
• Linda Gulliver 4  

BMC Medical Education volume  24 , Article number:  940 ( 2024 ) Cite this article

Metrics details

The global discourse on future health care emphasises that learning to collaborate across professions is crucial to assure patient safety and meet the changing demands of health care. The research on interprofessional education (IPE) is diverse but with gaps in curricula design and how IPE is enacted in practice.

Purpose and aims

This research project will identify. 1) how IPE in clinical placements emerges, evolves, and is enacted by students when embedded in local health care practices, 2) factors critical for the design of IPE for students at clinical placements across the four countries.

A study involving four countries (Sweden, Norway, Australia and New Zealand) using the theory of practice architectures will be undertaken between 2023 and 2027. The project is designed as an international, collaborative multiple-case ethnographic study, using the theoretical framework of practice architectures (TPA). It will include four ethnographic case studies of IPE, one in each country. Data will be collected in the following sequence: (1) participant observation of students during interprofessional placements, (2) interviews with students at clinical placement and stakeholders/professionals, (3) Non-clinical documents may be used to support the analysis, and collection of photos may be use as memory aids for documenting context. An analysis of “sayings, doings and relatings” will address features of the cultural- discursive, material-economic, social-political elements making up the three key dimensions of TPA. Each of the four international cases will be analysed separately. A cross case analysis will be undertaken to establish common learning and critical IPE design elements across the four collaborating universities.

The use of TPA framework and methodology in the analysis of data will make it possible to identify comparable dimensions across the four research sites, enabling core questions to be addressed critical for the design of IPE. The ethnographic field studies will generate detailed descriptions that take account of country-specific cultural and practice contexts. The study will also generate new knowledge as to how IPE can be collaboratively researched.

Peer Review reports

The global discourse on future health care emphasizes interprofessional collaborative capability as being crucial to meet changing demands on health care systems. These demands are the result of aging populations, increasing inequities in health care outcomes, the increasing number of those with complex health conditions and shortage of health care personnel [ 1 , 2 ]. The World Health Organisation (WHO) [ 2 ] states interprofessional education (IPE) “occurs when students from two or more professions learn about , from and with each other to enable effective collaboration and improve health outcomes” (p. 10), signalling that IPE involves interaction between students in learning activities. When the students understand the value of collaborative practice, they are better prepared to become a member of the collaborative practice team and provide better health services. The rationale for IPE, according to WHO [ 2 ] is that health professions should strive to design IPE activities to develop and optimize students’ collaborative competences to prepare them for the above challenges in their future working life [ 2 ], something that is also emphasized in the Winterthur/Doha declaration of Interprofessional. Global 2023 [ 3 ].

Efforts to explore IPE from the international research community are rapidly growing [ 4 ]. Meta-analyses and scoping reviews of IPE initiatives indicate a diverse picture of IPE programmes [ 5 , 6 , 7 ]. Vuurberg et al. [ 8 ], in their review of research studies on IPE between 1970 and 2017, point to a paucity of research regarding the influence of collaborative work on the development of professional interpersonal skills. In recent years it has been argued that there is a potential to offer IPE in clinical placements thus providing authentic learning opportunities for students in the context of complex health care practices [ 9 ]. Interprofessional learning during clinical placements is a step forward to develop and strengthen students’ interprofessional competencies, professional identity, and confidence [ 10 , 11 ].

Several reviews regarding students’ perceptions about IPE in clinical placements mostly report positive experiences, e.g., increased communication skills and increased knowledge of each other’s roles [ 12 , 13 , 14 ]. Results also indicate increased abilities with regard to working within a team and improved communication [e.g., 15 – 16 ]. Longer periods of IPE activities seem to strengthen students’ professional identity formation and overcome traditional hierarchical prejudices that can exist in interprofessional teams [e.g., 17 – 18 ]. On the other hand, it has also been suggested [ 19 ] that the lack of attention to power and conflict in the IPE literature might indicate a neglect of the impact of organizational, structural and institutional issues; and thereby might veil the very problems that IPE attempts to solve.

Published examples of IPE activities in clinical placements have covered a wide range of types of activities as well as numbers of hours and days. Initiatives have been developed that extend over a few hours or a day. Students taking responsibility for a team round in clinical placement [ 20 ] or structured interprofessional workshops about falls prevention [ 21 ], are both examples of formal activities arranged during clinical placement periods. A workplace-driven, informal, arrangement where students on uni-professional clinical placement were engaged in interprofessional teamwork for one day [ 22 ] is another example. Interprofessional activities where students practice together for a longer period have been developed and implemented during the past 25 years. Interprofessional training wards where students work together, often for a period of around two weeks, with the overall responsibility for patients’ care, have been a successful activity developed worldwide [ 23 , 24 , 25 ]. The heterogeneity of activities, educational approaches, and outcome measures, makes it difficult to compare between programmes, both at national and international levels [ 26 , 27 , 28 , 29 , 30 ]. To overcome this, the importance of international collaborative efforts to research interprofessional education practices has been emphasized [ 31 ] but to date, such collaborations are scarce. In particular, there is a need for theory-based research and observational methods to discover and understand the basis of interprofessional actions and interactions [ 7 , 32 ]. Moreover, multiple site studies are needed to inform IPE educational design, since the heterogeneity of learning activities and practices varies with the different health care systems. Visser, et al. [ 33 ] in their systematic review, described barriers and enablers of IPE at an individual level but also at a process/curricular and cultural/organizational level of the educational programmes, while Pullon et al. [ 34 ] discussed the importance of paying attention to both individual and contextual factors for sustainable collaborative practice. This indicates a need for research approaches that allow broader perspectives considering not only the experiences of the individual, but also those of the local contexts where IPE is occurring. Recent theories on research on professional learning emphasize the importance of considering the complexity and dynamics of the practices and contexts, i.e., the social and material conditions under which the learning takes place [ 35 , 36 , 37 ]. A scoping review highlighted the use of socio-material approaches as a theoretical lens to understand professional learning practices in IPE and interprofessional collaboration (IPC) [ 38 ]. Using a socio-material perspective makes it possible to gain a deeper understanding of how IPE practices emerge within a clinical setting, and furthermore, to develop an understanding of complex situations such as power relationships, human resource shortages in health care, patient safety and more.

In this study, the focus is on identifying how interprofessional collaboration and learning emerge when embedded in clinical practice placements designed for such purposes. The study is designed as an international, collaborative multiple-case ethnographic study. It will involve four sites of health care clinical practice situated locally in Sweden, Norway, Australia, and New Zealand. The multiple case study ethnographic research design [ 39 ] will be used in combination with Kemmis’ theory of practice architectures (TPA) [ 40 ]. This approach will make it possible to identify similarities and differences across the four countries and different sites of IPE.

Context of study

Each country has endorsed the WHO’s global call for Interprofessional Education and Collaborative Practice (IPECP) in different ways, which has been influenced by their national and local health care organization [ 2 ]. The local experience of teaching IPE, how the learning experience is designed, and for how long the students have an IPE clinical placement, varies between the four universities. Linköping University (Sweden) has long-standing experience of an IPE-curriculum including all health education programmes. UiT The Arctic University of Norway has a long history of IPE and builds on selected interprofessional learning activities including 13 health – and social programmes at the most. The University of Otago (New Zealand) has centrally organized IPE with a staged implementation strategy for all health and social services students to undertake IPE learning activities, while the University of Wollongong (Australia) is at an early phase of developing and implementing IPE across a variety of health and social programmes. The different contexts and establishment of IPE at the four sites make up a natural variation suitable for multiple case study research [ 39 ]. A summary of key contextual issues provides a background to each country (Table  1 ).

Theoretical framework – theory of practice architecture (TPA)

We will use a theoretical framework based on Kemmis’ TPA [ 36 , 40 ] (see Fig.  1 ). The TPA is increasingly being used to understand professional practice and the potential to learn in new ways. [ 36 , 37 , 40 ]. The theoretical framework uses the three recognized practice architecture dimensions of cultural-discursive, material-economic and social-political, along with their associated elements. The cultural-discursive dimension includes the interactions, discourses, and words (‘sayings’) which make the professional practice understandable; this reveals what to say and think in or about a practice, and what it means. The material-economic dimension enables and constrains how people can act and interact in physical and material space (‘doings’); this reveals the different types of activities and work performed by the professionals within a physical environment and the way these ‘doings’ influence others in the same practice. The social-political dimension describes the relationships that form between individuals and groups (‘relatings’); this reveals how relationships between certain arrangements of professionals develop, their roles, and whether and how relations continue to exist or not [ 44 ]. The emphasis is therefore on the relationships between material arrangements and human actions and what these produce [ 37 ], and that these relationships are more, or less likely to happen, in certain circumstances [ 45 ].

Kemmis´ theory of practice architectures (TPA) [ 40 ] p.97. (with permission from the author)

According to TPA, IPE in clinical placements can be viewed as an organized set of actions and interactions embedded in a professional practice. This means that both human and non-human factors are considered. The focus of the study is the students’ sayings, doings and relatings with fellow students, patients, supervisors, and staff, in the complex dynamic and relational dimensions of practice, i.e. the social and material conditions under which the clinical placement or learning activity is arranged.

The aims of this research project are to identify:

how IPE in clinical placements emerges, evolves, and is enacted by students when embedded in local health care practices,

factors critical for the design of IPE for students at clinical placements across the four countries.

Four research questions (RQ) will be explored:

How do interprofessional clinical placements enable students collaborative learning activities? RQ2. How do students’ sayings, doings and relatings in practice shape interprofessional collaboration and learning?

What challenges do interprofessional clinical practice placements bring to established health care practices?

What lessons from the case studies can inform the global discourse on interprofessional educational practice?

Case study site selection

Each case study site has been purposively selected within each country and across the four countries (see Table  2 ). Purposive selection has been used to ensure maximal variation [ 46 ].

Data collection

Methodology.

Four case studies will be undertaken, one each by the local research groups based in Sweden, Norway, Australia, and New Zealand and using a common ethnographic methodology.

An ethnographic approach focuses on understanding the social processes and cultures of different contexts [ 47 ], and usually comprises a range of qualitative methods. It is recognized as a suitable research method for acquiring knowledge about how practices are arranged and interrelated within naturally occurring physical and social environments, and about the contexts in which activities and knowledge-sharing can take place [ 45 , 48 ].

The initial site visits by each respective country’s local research team will take place in late 2023 and early 2024. At each case site the researcher(s), all connected to health profession education, will use the case study observational research (CSOR) method where non-participant observation guides data collection. In the CSOR method, the direct observations of participants’ behaviours and interactions are given priority and precedence over self-reported forms of data collection, and collection of non-observational data is informed by the analysis of the observational data to enable further investigation of observations [ 49 , 50 ].

Direct observation allows the researcher to see what is occurring rather than having participants describe what they do through interviews. Observations of students will follow the naturally occurring rhythm of interprofessional activities during the day. Examples of such activities are the students planning together their daily work, encounters with patients, deliberations following their work on what seems to be proper treatment and advice for the patient in question, students interactions with staff and supervisors, and their daily reflections on how they have been working together and what they have learned. Each case site is different, and the IPE learning activities is of different length and with different learning outcomes. In each case site, researchers will act as observers of interprofessional students in action and write detailed fieldnotes or record audio memos on the interactions and their context. Field notes will also incorporate the researcher’s reflections “including feelings, actions and responses to the situation” [ 39 ]. Brief informal conversations with students may be conducted during or immediately after the observations if clarity is needed about what has been observed, and these will be recorded in the field notes [ 47 ]. Non-clinical documents may be used to support the analysis, and photographs may be collected for documenting context and to aid recall. These comprehensive observations will facilitate the systematic collection of data while still acknowledging the influence and interpretations of the researcher in the data collection process. The CSOR method will make it possible to gain access to observed actions, interactions and discussions that take place between students (sayings, doings and relatings), and between students and patients, staff, and others.

In each case, the observational data and field notes (and if needed non-clinical documentation and/or photographs for context) will be immediately circulated to the local research team and reflexive feedback provided for inclusion in the analysis. Following this rapid analysis of observational data and guided by what further data is needed or needing to be corroborated, formal interviews will be booked as soon as possible with students, patients, clinical tutors, IPE teachers and others, Formal interviews (audio recorded) will be guided by a template of core questions developed by the research project team. This common template will be augmented by other questions informed by each initial case analysis. Data will be transcribed either selectively or fully; English language translation will occur where data are being analysed for comparative analysis.

Theoretical approach

Data analysis will use TPA [ 40 ] including an analysis “tool kit” [ 51 ]. The tool kit is a theory and method package to investigate practices by the systematic interpretation of the case study data. A “zooming in – zooming out” methodological approach [ 51 ], will make visible details in a specific local practice; “zooming in” allows getting close to the practices being observed (to answer RQ1 and RQ2) and then “zooming out” allows the researcher to expand their scope and look for connections between different practices (RQ3 and RQ4). The connections between practices in the research study will be identified through focusing on the three dimensions of practice architectures: the cultural-discursive, material-economic, and social-political. The agreed tool kit approach will include a layered, purposeful constant comparative analysis [ 52 ], comprising three phases of individual and collaborative activities, using English as the common language. First the systematic collection and analysis of observations and field notes of those observations and other qualitative data by each local research team, will be guided by the theoretical perspective on how students interact in relation to social and material arrangements. Second, the data in each of the four case study sites will be analysed by each local research team and verified locally and collectively; this will lead to site-specific findings. Third, comparisons will be made between the four different sites by cross-checking and developing and refining the interpretations of all the data.

Practical approach

Each country will follow the data collection and analysis process outlined in the methods for their case site and each case site will be analysed separately. Each local research team will have regular meetings to ensure that a reflexive, but uniform approach is undertaken as data is collected. These meetings will also include workshops for collaborative data analysis. Monthly meetings will also be held between the four countries’ project research teams as case data collection and analysis progresses and a similar reflexive process used. This will ensure the analyses of each case follows the same process and will provide assurance of mutual understanding across sites. To enable this, anonymized observational data (and fieldnotes), interview data and photographic or document extracts will be shared, analysed and reviewed in workshops. Following completion of each case study in the four different countries, a cross-case process [ 39 ] will be undertaken. Each local research teams will first have undertaken the primary analysis, combining data from fieldnotes and interview transcript generating preliminary themes to identify the sayings, doings and relatings are emerging and connected in the efforts of collaborate around the patient. As the findings are first collated, observed aspects from students’ sayings, doings and relatings, projects and dispositions will be revealed. As a second layer of analysis, the findings will analytically be connected to practice architectures, such as the cultural-discursive, the material-economic and the socio-political arrangements. The use of a common scheme for how to document the analysis is important for comparative reasons and indicate points for shared analyses across the research teams to consider the respective results, identify similarities and differences across the four sites, and explore any learning principles that might apply to IPE internationally. It is intended for each country to use the same processes to anonymize, catalogue and code the transcribed data. The research agreement also includes a process to enable sharing of selected portions of data and coding software databases using password-protected systems [ 53 ].

Ethical approval and consent

The research group in each country will be responsible for (1) seeking ethical approval for their respective case, (2) gaining consent from each local site to undertake the respective case study, (3) establishing rules for storage of the data. The following countries have received ethical approval to proceed: Sweden (Dnr 2023-02277-01), Norway (No.889163), New Zealand (No. H23/035), Australia (underway).

Establishing trustworthiness

The following processes and definitions proposed by Korstjens and Moser [ 54 ] based on Lincoln and Guba [ 55 ] will be used to ensure trustworthiness in the implementation of this study (Table  3 ).

A timeline for the research project has been established (Table  4 ).

This research project is innovative as it takes an international approach to a globally identified educational challenge regarding methods to design and implement IPE in clinical practice settings. The approach, using case studies in four different countries, will explicitly acknowledge that educational phenomena and learning are contextually bound and situated and that although each country involved is different, common learning can be gained.

It is hoped that the four case studies will lead to new understanding and conceptualization of how IPE can be arranged within and across diverse contexts, languages, and local conditions. Furthermore, the cases may establish some of the challenges interprofessional clinical placements for students may bring to existing or established health care practices.

It is recognized however that while each country’s case will lead to new understanding for that country, it may be challenging to establish cross country learning as the context of each may be very different. Although English language will be adopted for communication, there may be subtle differences in how language is used and understood between English and non-English speaking countries, as well as between English speaking countries.

Taking account of local context as well as developing joint findings will be a challenge. The TPA will give opportunities to identify and analyse how students´ interprofessional clinical activities are embedded in the complex practice of routine health care at a local level within each country, and between countries. The theory will make it possible to capture how the students act in practice and how they relate to each other in clinical placements. It is hoped it will also show how clinical and interprofessional practices are influenced through the three different dimensions (cultural-discursive, material-economic, and social-political) and if these may construct, enable, or constrain practice work and knowledge-sharing. Possible examples may include: (1) the influence of a discipline’s language or discourse; the way of speaking that forms the framework for understanding themselves and others, (2) the arrangement of a health care setting; the way the environment influences where students can meet and work together (e.g. patient care rooms, rooms used for ward rounds and corridors), and (3) the development of relationships; the way social norms and political influences impact on relationships between different disciplines and groups [ 40 , 45 ]. It is possible when the analysis progresses that the three dimensions referred to above may show nuanced differences between countries which previously have been difficult to articulate and account for.

Undertaking this international collaborative research is important for IPE research going forward. International collaborative research projects in IPE are rare but have been recommended for the consolidation and growth of the IPE research knowledge base [ 31 ].

The design of IPE in clinical placements should be informed by evidence and best practice. This includes using theoretical approaches which can be replicated or further developed, such as the TPA.

This research will advance a model of IPE based on TPA. It will provide new understanding and conceptualization of how IPE can be arranged across diverse contexts and local conditions, but with a common aim to provide collaborative practice-ready graduates able to respond to the increasing healthcare demands of the future.

Therefore, the broader impact of the proposed study is expected to contribute to: (1) the local and international educational IPE community regarding design of IPE in clinical practice, and (2) the international IPE research community regarding how IPE in practice can be collaboratively researched.

Data availability

Selected data will be reported in the Results section but will not be available as datasets.

Abbreviations

Case Study Observational Research

Interprofessional Education

Interprofessional Education and Collaborative Practice

Interprofessional Collaboration

Theory of Practice Architectures

World Health Organisation

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Acknowledgements

The research team gratefully acknowledge the contribution of the advisor: Nick Hopwood, Professor of Professional Learning, University of Technology, Sydney, Australia.

Open access funding provided by Linköping University. This study is funded by the Swedish Research Council: 2022–03210. The funder had no role in the study design, collection, analysis and interpretation of the data; writing of the protocol, or in the decision to submit the paper for publication.

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ALF, MAD, JD, BN, AI, KM, EM & LG contributed to the conception and design of the overall study. ALF is the overall Principal investigator (PI) and PI of the Swedish case study; AI is the PI of the Norwegian case study, KM is the PI of the Australian case study, EM is the PI of the New Zealand case study. ALF, MAD & JD developed the analysis plan. JD drafted the initial protocol. ALF, MAD, JD, BN, AI, KM, EM, LG, SM & JM revised the protocol critically for important intellectual content and read and approved the final version of the manuscript to be published.

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Lindh Falk, A., Abrandt Dahlgren, M., Dahlberg, J. et al. ALLin4IPE- an international research study on interprofessional health professions education: a protocol for an ethnographic multiple-case study of practice architectures in sites of students’ interprofessional clinical placements across four universities. BMC Med Educ 24 , 940 (2024). https://doi.org/10.1186/s12909-024-05902-4

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Uric acid and risk of gestational diabetes mellitus: an observational study and mendelian randomization analysis

• Nuerbiya Xilifu 1 , 2   na1 ,
• Rui Zhang 1   na1 ,
• Yongling Dai 2 ,
• Miyeshaer Maimaiti 2 ,
• Zhangyan Li 1 ,
• Ju Yang 3 ,
• Shufei Zang 1 &
• Jun Liu 1  

Reproductive Biology and Endocrinology volume  22 , Article number:  108 ( 2024 ) Cite this article

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Metrics details

Our aim was to explore the relationship between serum uric acid (UA) levels in early pregnancy and the development of gestational diabetes mellitus (GDM), and to further explore whether there is a causal relationship.

684 pregnant women with GDM and 1162 pregnant women without GDM participated in this study. 311 pregnant women with GDM and 311 matched controls were enrolled in a 1:1 case-control study. We used conditional logistic regression to explore the relationship between UA levels and the risk of developing GDM. The causal relationship between the two was examined by two-sample Mendelian randomization (MR) analysis.

In the 1:1 matched population, the odds ratio (OR) of developing GDM compared with the extreme tertiles of UA levels was 1.967 (95% confidence interval [CI]: 1.475–2.625; P  < 0.001). Restricted cubic spline analyses showed a linear relationship between UA and GDM when UA exceeded 222 µmol/L. GDM and UA levels maintained a statistically significant positive correlation in different stratified regression analyses ( P  < 0.001). However, no evidence of a causal relationship between uric acid and GDM was found by MR analyses with an OR of 1.06 (95% CI: 0.91–1.25) per unit increase in UA.

There is a positive correlation between UA levels in early pregnancy and the subsequent risk of developing GDM. However, no genetic evidence was found to support a cause-effect relationship between UA and GDM.

λ The positive correlation between serum uric acid level and gestational diabetes mellitus persisted after a 1:1 case-control matching program.

λ High uric acid level remained an independent risk factor for developing gestational diabetes mellitus in the stratified analyses.

λ The positive correlation between serum uric acid level and the development of gestational diabetes mellitus increased when serum uric acid exceeded 222 µmol/L.

λ Our two-sample mendelian randomization analysis did not produce genetic evidence of a causal relationship between uric acid and gestational diabetes mellitus.

Introduction

GDM is a disease characterized by elevated blood glucose during pregnancy that increases adverse pregnancy outcomes and poses a significant risk to mother and child [ 1 ]. GDM is a key risk factor for postpartum type 2 diabetes in pregnant women [ 2 ]. Although early diagnosis and treatment of GDM can reduce the risk of adverse pregnancy outcomes, many of the current diagnostic and management approaches remain controversial. There is a lot of evidence suggesting that the mechanisms and clinical biomarkers of GDM deserve further investigation for the early prevention of GDM [ 3 ]. Given that blood glucose levels during pregnancy are affected by a variety of factors, including diet, mood, stress, and medications and that the diagnosis of GDM using a single oral glucose tolerance test (OGTT) is subject to a certain degree of underdiagnosis and misdiagnosis, there is an urgent need to explore novel biomarkers, mechanisms, and targeted measures for GDM.

UA was once overlooked except for gout and kidney stones, but the results of large quantities of recent researches suggest that it is one of the most important metabolized substances [ 4 ]. Some studies have demonstrated that hyperuricemia is positively related to metabolic syndrome and diabetes mellitus [ 5 ]. Although studies have reported that excessive serum uric acid levels are positively associated with insulin resistance and risk of type 2 diabetes, the relationship between serum uric acid and risk of GDM has been inconsistent and relatively limited [ 6 ].

Mendelian randomization (MR) analyses assess the causal effect of genes to predict the relationship between exposure and outcome through gene-based instrumental variables [ 7 ]. Mendelian and other genetic studies have been conducted to eliminate potential confounders and reverse causality [ 8 ]. Several MR analyses have explored the causal relation between serum UA levels and type 2 diabetes, but all have reported negative results [ 9 , 10 ]. We are aware that no MR studies have been conducted on the relationship between serum UA levels and the risk of GDM. Therefore, it is essential to explore whether there is a causal relationship between the two.

We hypothesized that elevated UA in early pregnancy is a risk factor for t developing GDM. We analyzed data from a case-control study to examine the association between early gestational UA levels and subsequent GDM risk in pregnant Chinese women. We analyzed data from the International Consortium to further explore the possible causal relationship between uric acid and GDM by two-sample MR analysis.

Study design and participants

Our case-control study included 1908 singleton pregnant women. Pregnant women were recruited from the obstetrics departments of the Shanghai Fifth People’s Hospital affiliated with Fudan University between February 2018 and June 2022. The procedure of this retrospective study was described in Fig.  1 .

Flowchart of this study

Pregnant women who have a record of pregnancy in this institution are included. The exclusion criteria were twin or multiple pregnancies, diagnosis of diabetes mellitus or other metabolic or infectious diseases, UA testing beyond the 24th week of gestation, or incomplete maternal and fetal records. Ultimately, 1846 women (1162 without and 684 with GDM) were included in the analysis.

GDM is diagnosed if at least one of the following thresholds is reached in the 2-hour 75-g OGTT: fasting plasma glucose ≥ 5.1 mmol/L, 1-hour plasma glucose ≥ 10.0 mmol/L, or 2-hour plasma glucose ≥ 8.5 mmol/L [ 11 ]. All 1846 participants had no significant pre-pregnancy diabetes and 684 women were diagnosed with GDM.

Pregnancy data collection and laboratory evaluation

After fasting overnight for 12 h, blood samples were collected for biochemical parameter testing (Cobas 8000 Automatic Biochemical Analyzer; Roche, Basel, Switzerland). We measured blood pressure and anthropometric parameters.

Sources of data for MR analysis

Genetic variants related to uric acid were screened based on a genome-wide association study of 162,255 Japanese, of which the number of participants related to UA was 109,029 [ 12 ]. The study retrieved single-nucleotide polymorphisms (SNPs) associated with UA with genome-wide significance ( P  < 5 × 10 − 8 ) and linkage disequilibrium between SNPs were estimated using the clumping method (r 2  < 0.001, window size = 10,000 kb) using European samples from the 1000 Genomes Project. Forty-three SNPs associated with UA were identified, and we researched these SNPs in the PhenoScanner database to examine whether these genetic variants were associated with potential confounders of GDM. Finally, 35 SNPs were enrolled in the main MR analysis.

Data from the FinnGen consortium were used to analyze the relationship between the selected SNPs and GDM. The analysis included 6033 GDM cases in approximately 123,000 women [ 13 ]. Detailed data are shown in the Supplementary Tables.

Statistical analyses

Continuous variables are expressed as mean ± standard deviation or median (interquartile range), and for categorical variables frequencies or percentiles are used. To avoid potential bias, we used a case-control matching method to match the variables of age, family history of diabetes mellitus, parity, and BMI, with matching tolerances of 0, 0, 0, 0, 0, and 0.25. To further validate the relationship between UA and GDM, we created a retrospective cohort that included the same subjects, in which participants were divided into three groups according to the tertiles of UA: the lowest group (< 199 µmol/L), middle group (199–243 µmol/L), and highest group (> 243 µmol/L). We used conditional logistic regression analysis to estimate the independent association between UA levels and GDM risk in the case-control study. In the retrospective cohort, we adjusted for UA in Model 1 and made additional adjustments for lifestyle and metabolic risk factors, including maternal age, pre-pregnancy BMI, history of diabetes, and history of GDM in Model 2. In Model 3, we further adjusted for alanine aminotransferase (ALT), creatinine (Cr), low-density lipoprotein (LDL), triglyceride (TG), fasting blood glucose (FBG) levels and diastolic blood pressure (DBP). In the cohort study, a restricted cubic spline was used to estimate the relationship between UA and GDM, and subject operating characteristic curves were plotted.

Two-sample MR analysis was performed using the “TwoSampleMR” R package [ 14 ]. In the main analysis, we used MR inverse variance weighting (IVW), which is a regression weighted by the inverse of the SNP-outcome association variances [ 15 ]. The MR-Egger intercept test [ 16 ] and MR-PRESSO test [ 17 ] were used to identify and account for potential horizontal pleiotropy. The Cochran’s Q test [ 18 ] was used to detect heterogeneity.

All statistical analyses were performed using SPSS software (version 25.0; IBM SPSS Inc., Chicago, IL, USA) and R software version 4.0.2. All P -values were two-tailed, and statistical significance was set at P  < 0.05.

Association between serum UA levels and GDM in observational study

Table  1 shows the demographic and metabolic characteristics of the participants categorized as women without GDM (control group, n  = 1162) and those with GDM (GDM group, n  = 684). The control group consisted of women with physiologic pregnancies who were routinely screened for GDM at mid-pregnancy with negative results. The average age of the women with GDM was significantly higher than that of the control group, whereas no differences were found in systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting blood glucose (FBG), aspartate transaminase (AST), and cholesterol. Pre-pregnancy BMI and alanine aminotransferase (ALT), creatinine (Cr), UA, triglycerides (TG), and low-density lipoprotein cholesterol (LDL-C) levels were higher in women who developed GDM than in women in the control group.

A 1:1 case-control matching procedure was used to avoid possible bias. After 1:1 a case-control matching procedure, matching for parameters such as age, family history of diabetes mellitus, parity, and BMI, the results of the conditional logistic regression analysis (enter method) showed a positive association between UA and GDM (OR: 1.967; 95% CI: 1.475–2.625, in the highest tertile vs. the lowest tertile; P  < 0.001), as shown in Table  2 .

The participants’ characteristics across the tertiles of UA levels were shown in Table  3 . There were no differences in SBP, FBG levels or history of GDM across the tertiles of UA levels. Participants with higher levels of UA were likely to have higher DBP and ALT, AST, TG, cholesterol, and LDL-C levels but lower high-density lipoprotein cholesterol (HDL-C) levels. In the fully adjusted model, the OR for the occurrence of GDM comparing with the extreme tertiles of UA levels was 2.788 (95% CI: 2.060–3.772; P  < 0.001), and the P -values were stable during the process of adjusting for different models, as shown in Table  4 . After regression analysis of the different subgroups, UA still showed a significant correlation with GDM, as shown in Table  5 .

Restricted cubic splines showed a positively correlated linear relationship between uric acid levels and GDM risk, especially when uric acid was above 222 µmol/L ( P for nonlinearity < 0.001, P overall < 0.001, Fig.  2 ). The area under the receiver operating characteristic curve (ROC) of UA combined with basal factors (age, GDM history, pre-pregnancy BMI, TG, ALT, Cr, LDL, FBG, and DBP) for predicting GDM was 0.803 (95% CI: 0.781–0.826, P  < 0.001, Fig.  3 ).

Dose-response relationship between UA concentrations and risk of GDM in restricted cubic spline analysis

ROC curves combined basal factors (age, previous GDM history, pre-pregnancy BMI, TG, ALT, Cr, LDL, FBG and DBP) with serum UA

Association between genetic variants of UA and GDM

We further performed MR analysis to estimate the causal effect size of genetically determined UA levels on GDM. The characteristics of the selected SNPs and their associations with GDM risk and UA levels are shown in Supplementary Table 1 . We detected an outlier SNP (rs1260326) using the MR-PRESSO test and performed MR analysis after deleting this SNP. No evidence of a causal relationship between serum UA and GDM risk was found (OR: 1.06, 95% CI: 0.91–1.25) per standard deviation increase in UA (IVW-MR in Table  6 ). Similar results were observed for the weighted median method, simple mode, weighted mode, and MR-Egger regression (Table  6 ). The MR-Egger intercept test suggested no unbalanced horizontal pleiotropy (MR-Egger intercept = -0.007; P  = 0.385). Cochran’s Q statistics using separately selected SNPs showed significant heterogeneity ( P  < 0.05) in UA (Table  7 ). More Details of the MR analysis were summarized in Supporting Information (Supfig 1 - 4 ).

Our study found a positive association between elevated serum UA levels and increased risk of GDM. However, MR analysis fails to demonstrate a causal relationship between serum UA levels and GDM risk.

Many observational studies support a positive correlation between serum UA levels and diabetes risk as well as GDM. Rasika et al. [ 19 ]. Susan reported that the risk of GDM in pregnant women increases as serum UA levels rise in the first trimester. In a prospective study, Duo et al. [ 20 ]. demonstrated that elevated serum UA levels were positively associated with the development of GDM, and the association was enhanced when serum UA exceeded 240 µmol/L. A systematic review and meta-analysis showed that elevated UA levels are positively related to the risk of GDM, especially in early pregnancy [ 6 ]. Our results are consistent with these findings. We conducted a 1:1 case-control matching program and found that the significant correlation between UA and GDM persisted after matching.

Previous studies have identified several potential risk factors for GDM (age, BMI, family history of diabetes, and history of GDM) [ 21 , 22 ]. To correct these potential consolidating factors, we conducted a stratified regression analysis. Even after adjusting for metabolic risk factors in the model, high UA levels remained an independent risk factor for developing GDM. We used spline regression analysis to explore the relationship between UA levels and the occurrence of GDM. When we examined the association between UA levels and GDM, a J-shaped association was observed. When serum UA exceeded 222 µmol/L, the positive correlation between serum UA levels and the development of GDM increased. Various mechanisms may account for the positive association between UA levels and GDM risk. Firstly, hyperuricemia may potentially cause β-cell dysfunction by inducing oxidative stress, inducible nitric oxide (NO) synthase and inflammation within β-cells [ 23 , 24 , 25 , 26 ]. Secondly, insulin resistance plays a critical role in the pathogenesis of GDM, and the results of many researches have shown that hyperuricemia is closely associated with insulin resistance [ 27 , 28 , 29 , 30 , 31 ]. Furthermore, hyperuricemia may induce oxidative stress, which in turn leads to endocrine dysfunction in adipose tissue, leading to the development of metabolic syndrome [ 32 ].

Although many studies have indicated that UA is a crucial factor in the development of GDM, evidence reveals that UA may play only a bystander role in the risk of GDM. Maged et al. [ 33 ]. reported that the serum UA concentration was not positively related to the development of GDM. Güngör et al. [ 34 ]. also proved that UA levels were higher in patients with diabetes; however, this elevation was not statistically significant. Therefore, it remains unknown whether there is a causal relationship between serum UA levels and GDM risk.

Yan et al. [ 35 ]. provided evidence of a causal association between UA and macrovascular disease in Chinese diabetic women using MR analysis. Although several MR studies have evaluated the potential causal relationship between serum UA levels and diabetes risk, no positive results have been reported. Three European studies and a Chinese study found no causal association between UA and diabetes risk [ 9 , 10 , 36 , 37 ]. We are unaware of any studies that have performed MR analyses of UA and GDM to explore their genetic causality. Therefore, additional MR studies are necessary to explore the causal associations between serum UA levels and GDM risk. Although serum UA levels were significantly correlated with an increased incidence of GDM, our two-sample MR analysis did not produce genetic evidence of a causal relationship between them. There are several possible reasons for these negative results. Firstly, this study used summary-level data, which could lead to potential mediators between genotype and disease risk that may not have been controlled for. Secondly, datasets of exposures and outcomes were obtained from individuals of Japanese and European descent who had varying risks of developing GDM. In addition, the limited number of SNPs included in the MR analysis and the relatively small effect of SNPs on UA levels may lead to negative conclusions. Finally, in observational studies, blood UA may be a secondary factor to adverse metabolic phenotypes, and residual confounders may induce a positive association of UA and GDM in previous studies. Notably, factors such as alcohol consumption, smoking, physical activity, renal function, or diuretic use have all been reported to be associated with GDM and serum uric acid levels, but only a few studies have corrected for them. Therefore, additional MR and prospective cohort studies are necessary to examine the causal relationship between serum UA levels and GDM risk, especially in different populations.

Our study has several advantages. First, our study included a well-matched retrospective design, making it even more compelling. Second, as far as we know, this is the first Mendelian randomized study to investigate the relationship between UA and GDM. The MR design effectively minimizes the potential biases caused by confounding and reverse causality in observational studies. However, this study had certain limitations. Firstly, consistent with previous MR studies, the SNPs employed in the present study explained only a portion of serum UA changes. In future studies, it will be necessary to identify additional UA susceptibility genes to investigate the causal relationship between these two factors. Secondly, our analysis was limited to specific racial populations, which limits its generalization to other populations. Finally, although we considered the possible GDM risk factors, the possibility of residual confounders could not be excluded.

In conclusion, although elevated serum UA levels were significantly related to an increased risk of GDM, the results of the MR study did not provide evidence of a causal relationship between serum UA levels and GDM risk.

Data availability

The datasets during the current study are not publicly available but are available from the corresponding author on reasonable request.

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This study was funded by the Natural Science Foundation of China (82270852), the Science and Technology Innovation Action Plan “Biomedical Technology Support Special Project” of Shanghai (21S31901800).

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Nuerbiya Xilifu and Rui Zhang co-first authors.

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Department of Endocrinology, Shanghai Fifth People’s Hospital, Fudan University, 801 Heqin Road, Shanghai, 200240, China

Nuerbiya Xilifu, Rui Zhang, Zhangyan Li, Shufei Zang & Jun Liu

Endocrine Metabolism Department, the Second People’s Hospital of Kashgar Prefecture, No. 1, Health Road, Kashi City, Kashi Region, Xinjiang, 844000, China

Nuerbiya Xilifu, Yongling Dai & Miyeshaer Maimaiti

Department of Pathology, Shanghai Fifth People’s Hospital, Fudan University, 801 Heqin Road, Shanghai, 200240, China

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Nuerbiya·Xilifu: Clinical data collection, Formal analysis, Writing original draft. Zhang Rui: Data analysis, Supervision, Writing review and editing. Miyeshaer·Maimaiti: Clinical data collection. Li Zhangyan: Clinical data collection. Zang Shufei and Yang Ju: Subject design and supervision. Liu Jun: Conceptualization, Supervision, Writing review and editing. All authors read and approved the final manuscript.

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Correspondence to Ju Yang , Shufei Zang or Jun Liu .

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Xilifu, N., Zhang, R., Dai, Y. et al. Uric acid and risk of gestational diabetes mellitus: an observational study and mendelian randomization analysis. Reprod Biol Endocrinol 22 , 108 (2024). https://doi.org/10.1186/s12958-024-01278-8

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Application of objective optical quality analysis system in guiding early posterior capsule opacification laser treatment: An observational study

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• 1 Department of Ophthalmology, Jinan Second People's Hospital, Jinan, China.
• PMID: 39183412
• PMCID: PMC11346832
• DOI: 10.1097/MD.0000000000039386

In the present study, we aimed to demonstrate the objective guiding role of objective scatter index (OSI) in patients with early stage posterior capsule opacification (PCO), especially in patients with multifocal intraocular lens (IOL) implantation. A prospective randomized case analysis was conducted on elderly patients experiencing PCO, exhibiting best-corrected visual acuity (BCVA) below 0.2 LogMAR. Exclusion criteria comprised patients with diabetes, glaucoma, high myopia, trauma, endothelial dystrophy, maculopathy or prior eye surgery affecting visual acuity. The main observational indicators were patient gender, age, post-cataract surgery duration, BCVA (LogMAR), and OSI values. For patients undergoing laser posterior capsulotomy, meticulous documentation of pre-laser OSI values and post-laser OSI values was undertaken. Subjective visual quality was then compared using the Chinese version visual function index-14 (VF-14-CN). The study comprised 65 eyes from 56 patients. PCO developed, on average, 2.06 ± 0.94 years (ranging from 0.5 to 4 years) after the initial surgery, with the OSI consistently exceeding 3.0. Among these cases, only 40 eyes underwent laser posterior capsulotomy using Nd:YAG laser, including 26 eyes implanted with monofocal IOLs and 14 eyes implanted with multifocal IOLs. Following laser posterior capsulotomy for early-stage secondary cataracts, there was a significant decrease in OSI values compared to the presurgery state, coupled with a notable increase in VF-14-CN scores. Among the 14 cases with multifocal IOL implantation, pre-laser VF-14-CN scores were lower compared to those with monofocal IOLs. Post-laser posterior capsulotomy, patients reported a marked improvement in self-perceived symptoms. The OQAS functioned as an objective assessment metric for the laser treatment of early stage PCO. In cases involving multifocal IOL implantation, the visual disturbance caused by PCO was more pronounced, underscoring the significance of OSI as a valuable guide for laser treatment in these patients.

Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.

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Box plot of OSI and…

Box plot of OSI and BCVA in eyes with early PCO. It showed…

The change in BCVA before…

The change in BCVA before and after laser capsulotomy procedure. The average BCVA…

The change in OSI before…

The change in OSI before and after laser capsulotomy procedure. The OSI decreased…

The change in VF-14 before…

The change in VF-14 before and after laser capsulotomy procedure. The VF-14 scores…

• Awasthi N, Guo S, Wagner BJ. Posterior capsular opacification: a problem reduced but not yet eradicated. Arch Ophthalmol. 2009;127:555–62. - PubMed
• Lundqvist B, Mönestam E. Ten-year longitudinal visual function and Nd: YAG laser capsulotomy rates in patients less than 65 years at cataract surgery. Am J Ophthalmol. 2010;149:238–44.e1. - PubMed
• Javaloy J, Rivera E, Montalbán R, et al. . Diffractive trifocal pseudophakic intraocular lenses in high myopic eyes: 2-year assessment after implantation. Graefes Arch Clin Exp Ophthalmol. 2019;257:1331–9. - PubMed
• Bai H, Li H, Zheng S, Sun L, Wu X. Nd:YAG capsulotomy rates with two multifocal intraocular lenses. Int J Gen Med. 2021;14:8975–80. - PMC - PubMed
• Artal P, Benito A, Pérez GM, et al. . An objective scatter index based on double-pass retinal images of a point source to classify cataracts. PLoS One. 2011;6:e16823. - PMC - PubMed

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• Open access
• Published: 27 August 2024

Mindfulness intervention, homogeneous medical concept, and concentrated solution nursing for colorectal cancer patients: a retrospective study

• Yaning Feng 1   na1 ,
• Kuanlei Wang 2 ,
• Jianchun Fan 3   na1 ,
• Xueliang Wu 4 , 5 ,
• Tian Li 6 &
• Zhili Yang 4 , 7  

BMC Cancer volume  24 , Article number:  1055 ( 2024 ) Cite this article

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We aim to explore the differences of the psychological distress of postoperative chemotherapy patients with colorectal cancer between mindfulness intervention combined with homogeneous medical concepts and mindfulness intervention only.

One hundred patients with colorectal cancer undergoing chemotherapy after surgery from Sep 2020 to Sep 2022 were enrolled and divided into active control group (Solution centered nursing interventions; homogenized medical and nursing professional teams; dedicated personnel responsible for “admission notices”; Regular follow-up after discharge) and mindfulness group (homogeneous medical concept + and concentrated solution + Mindfulness intervention) with 50 cases in each group according to different nursing methods.

After nursing, the physical function, emotional function, cognitive function, and social function of the patients in the mindfulness group were significantly higher than those in the active control group. However, the overall life and economic difficulties of the patients in the mindfulness group were significantly lower than those in the active control group ( P  < 0.05). After nursing, the observation score, description score, action score, intrinsic experience score, non-judgment score and non-reaction score of the mindfulness group were significantly higher than those of the active control group ( P  < 0.05).

The implementation of mindfulness intervention in colorectal cancer patients undergoing chemotherapy can alleviate the patients’ negative emotions, improve the level of mindfulness, and improve the quality of life of patients.

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Introduction

Colorectal cancer is one of the common tumor diseases caused by the digestive tract system, which mainly presents symptoms such as local abdominal pain, blood in the stool, anemia and weight loss [ 1 ]. According to relevant research reports, the morbidity and mortality of colorectal cancer patients in my country rank third and fourth among many cancer diseases, and the patients are obviously younger [ 2 , 3 ]. At present, radiotherapy and chemotherapy are an important auxiliary means for the treatment of colorectal cancer. They can lead to increased physical and psychological stress, and cause patients The quality of sleep decreases, and the difficult emotions such as fear, depression, and anxiety are aggravated [ 4 ].

In recent years, the homogeneous medical concept nursing model has been widely advocated by hospitals. Homogeneous healthcare refers to a group of individuals who have identified similar patterns of medical resource utilization, treatment sequences, prognosis, and care trajectories [ 5 ]. The solution-focused mode is characterized by fully respecting individual resources and potential, and emphasizing that the focus of problem-solving is on the positive aspects of people [ 6 ]. Previous studies have found that the solution-focused model can help improve the psychological function and quality of life of patients [ 7 ]. The concentrated nursing model is a rehabilitation nursing measure covering the patient’s psychology, sports and life, and its starting point is health education. However, the current clinical nursing mode of homogeneous medical concept combined with focused solution mode lacks the ability to perceive the patient’s physiological state and enhance the patient’s sense of self-control [ 8 ]. As research progresses, positive thinking interventions can be used to increase the level of positive thinking in patients. It is a meditation practice that evaluates the subconscious mind to find out the level of stress that the patient perceives, thus ensuring that the patient remains in a more normal state under stress. Positive thinking intervention therapy can significantly reduce patients’ fear of disease and a series of difficult emotions after gastrointestinal surgery. Subsequently, it has been shown to reduce patients’ psychological and physical health, thereby improving their quality of life and significantly increasing their sense of well-being. Positive thinking therapy can help patients to increase their level of positive thinking and thus continuously improve their physical and psychological health.

According to related studies, colorectal cancer patients have obvious anxiety and depression, and the severity of the disease is increasing [ 9 ]. The contradiction between the disease and the psychological problems caused by colorectal cancer is becoming more and more tense, which in turn leads to the lower level of mindfulness and quality of life in patients with colorectal cancer, which gradually affects their living standards [ 10 ]. The mindfulness intervention is a stress reduction therapy that originated from meditation and is guided by Zen concepts to help patients relieve pain and anxiety. Studies have shown that in addition to conventional care and psychological care measures, mindfulness interventions can effectively reduce difficult emotions and improve quality of life in patients with colorectal pain [ 11 ].

Materials and methods

Research subject.

The medical records of 100 patients with colorectal cancer undergoing chemotherapy after surgery from Sep 2020 to Sep 2022 were selected as the retrospective research objects, and divided into an active control group and an mindfulness group with 50 cases in each group according to different nursing methods. All patients underwent the intervention during hospitalization and discharge, over a period of 5 weeks. Patients were followed up weekly after discharge from hospital for the intervention. We have de-identified all patient details. All authors have signed informed consent forms. The reporting of this study conforms to CONSORT guidelines [ 12 ].

Inclusion criteria: (1) Patients were informed about this study and agreed to participate in this research; (2) 70 ≥ Age ≥ 18 years; (3) Patients were diagnosed with colorectal cancer by pathological examination; (4) There were no organ lesions in patients with stage I and Stage II partial colorectal resection; (5) Have a certain ability to read and write, and have a certain understanding of colorectal cancer. (6) Be able to understand the essence of this experiment and actively cooperate with it.

Exclusion criteria: (1) Those who refused to accept the questionnaire; (2) Those with other primary cancers, or those with other serious diseases who could not be treated by radical surgery; (3) Those with a history of mental illness or mental retardation: (4) The family requested that the patient not be informed of the actual condition.

Homogeneous medical concept combined with focused solution nursing

Among them, the active control group implemented the concept of homogeneous medical care combined with solution-focused nursing, namely: (1) Solution-focused nursing intervention: Describe the problem: The responsible nurse guides the patient to describe the main problems at present. Build feasible goals: Encourage patients to think about the goals they want to achieve in the treatment process. Discuss success stories: Discuss past success stories with patients, let patients realize that stoma is not so scary. Implement feedback: Encourage and praise the daily changes of the beneficiaries. Evaluate the effect: Evaluate the patient’s results and actively improve in the next step. (2) Form a homogeneous medical and nursing professional team: members include medical staff in colorectal surgery and oncology surgery, and the selected personnel are senior nurses and physicians in the department. Before the nursing work is carried out, conduct unified training. After hospitalization, activate the homogeneous medical mode immediately, inform the patient of the precautions for dietary activities, and inform the patient that a series of encouragement measures after admission will be the responsibility of the attending physician. (3) In-hospital stage: After the patient is admitted to the hospital, the responsible nurse informs them of the “Admission Notice”.

The responsible nurse and the attending doctor participate in the ward round, Consultation, treatment plan formulation, surgical arrangement, pathological discussion and other medical activities, comprehensively understand the actual condition of the patients in charge, give timely feedback on difficult problems in the treatment process, and improve the implementation. In addition, pay attention to ease the patient’s psychological state, continuously encourage the patient, help enhance their confidence in treatment, and establish a correct attitude towards the disease. Take behavioral interventions for the bad mood of the thinker, such as arranging the thinker to do progressive muscle relaxation training in the recovery room with light music, and gradually relax the muscles of the whole body through deep breathing, once a day in the morning and evening, 20 min/time, the training time can be appropriately extended 3 days before the operation. During the operation, the vital indicators of the patients were strictly observed and anti-infection measures were taken. On the first day after the operation, the responsible nurse asked the stoma specialist nurse to conduct on-site teaching during the consultation, so that they could master the skills of cutting, pasting and replacing the ostomy bag, and observe the main points of the stoma. Learn to observe the color change of the stoma mucosa, manage and prevent stoma complications; during the nursing process, the medical staff should give enough respect and encouragement to the patients, so as to reduce the patient’s postoperative stigma and enhance the confidence in treatment 3 to 14 days after operation, according to the patient’s recovery, give corresponding dietary guidance, supplement nutrition, encourage patients to get out of bed early, and increase the time and scope of activities. (4) After discharge: within 48 h after the patient is discharged from the hospital, the responsible nurse and the attending doctor will complete the telephone follow-up of the patient. Provide professional guidance. One month after discharge from the hospital to the stoma outpatient follow-up, targeted re-interventions were carried out. The nursing time of patients in both groups was 6 months after the confirmed enrollment.

• Mindfulness intervention

The mindfulness group implemented mindfulness intervention, namely: mindfulness intervention therapy is a group training therapy on the first coupling of cancer and psychology, which in turn continuously improves the physical and psychological condition of the patient, thus continuously rebuilding the patient’s perception of the disease and its management. The 50 patients in the mindfulness group were divided into 7 groups, 6 of which had 7 patients in each group and the remaining group had 8 patients. The patients in each group were given mindfulness intervention care sequentially from Monday to Monday for 2.5 to 3 h each time, once a week for 5 weeks. In our study, the administration process was mainly influenced by the new crown epidemic, which was adjusted to a weekly group therapy session and a different theme each week, with a continuous intervention for patients for 5 weeks, with the weekly intervention taking place on Tuesdays at 4 p.m. The main intervention length was 2–2.5 h. It was conducted in two groups, and the next cycle of rehabilitation was generally not allowed until the end of the previous cycle, for a total intervention time of 2 months. In our study, instructional manuals and teaching videos were distributed to the administered patients before the start of the sessions, mainly to facilitate the patients to be able to perform white me training by learning, and the frequency and duration of weekly training were recorded on the memo sheet. To be able to keep the patients with colorectal cancer able to continue their rehabilitation training, we studied the use of online and offline instruction to educate the patients. In addition, the health care staff will distribute group training homework to patients with colorectal cancer online every week, and will follow up on the patients’ training results and provide one-on-one professional answers to their feelings and questions.

Week 1: the background, current situation and attitude of mindfulness colorectal cancer rehabilitation were introduced, and instruction manuals and exercise record cards were issued. Introduce yourself, set up a WeChat group, and introduce mindfulness breathing to learn and cultivate mindfulness. Week 2: Discuss mindfulness breathing, the group exchanged experiences from last week’s practice, and shared knowledge about cancer and stress, as well as the psychological problems caused by changes in the personal image and orientation of colorectal cancer patients. Week 3: Discuss new findings in body scan assignments, the impact of colorectal cancer patients on physical fatigue and pain; stretching teaching of gentle yoga, taking into account the patient’s physical disability, the practice follows the principle of moderation Week 4: Discuss the problems of yoga practice and Experience, tell the typical jade stress response and conscious stress response to cancer stress events. Tell stories in life, troubled stories in your mind and mental state, introduce mindfulness walking, and explore the relationship between walking movement and emotions. Week 5: Discuss the problem of mindfulness walking, share relevant experiences, explain the relationship between sleep, fatigue, physical pain, and emotions, and discuss experiences and findings in cancer coping. Review, discuss the mindfulness journey, how to deal with fear of cancer recurrence, emphasize mindfulness healing as a means of having health, and provide online resources.

Observation indicators

Quality of life score: EORTCQLQ-C30 V3.0 Chinese version developed by European Organization for Research and Treatment of Cancer, EORTC. The scale contains 30 items in 15 areas, including 5 functional areas: physical function (items 1–5), cognitive function (items 20, 25), emotional function (items 21–24) and social function (questions 26–27), three symptom areas, fatigue, nausea and vomiting, pain, 6 individual symptoms (including dyspnea, loss of appetite, quality of life, constipation, diarrhea, and financial difficulties), and 1 general health area. The overall health status is divided into 7 grades from 1 to 7. 1 means “very poor”, 7 means “very good”, and the rest of the items are divided into 4 grades, 1 means “never”, 2 means “somewhat”, 3 for “something” and 4 for “very much”. The scoring method of the scale: the scores of the items included in each field are added up and divided by the number of items included to obtain the rough score of the field. And the better the quality of life, the higher the symptom domain score, indicating that the more symptoms or problems, the worse the patient’s quality of life. At present, the scale has been translated into 43 languages, including Chinese, and is widely used in various countries and regions in the world. The Five-Factor Mindfulness Scale (FFMQ) [ 13 ]: measures the level of mindfulness of patients. The scale has 39 items, and each item is scored on a five-point scale (1 = not at all, 2 = less, 3 = somewhat), 4 = very agree, 5 = complete agreement), the score interval is [39,195], the higher the score, the higher the level of mindfulness. The severity of difficult emotions mainly evaluates two kinds of difficult emotions, namely anxiety and depression, and the evaluation time is before and after nursing. The scale used to assess anxiety is the Hamilton Anxiety Scale (HAMA) [ 14 ], with a cut-off value of 7 points. A score below 7 indicates that the patient has no anxiety, while a score over 7 indicates that the patient has anxiety, and the higher the score. High indicates more severe anxiety. The Hamilton Depression Scale (HAMD) [ 15 ] was used to evaluate depression. A score below 7 indicates that the patient does not have depression, while a score over 7 indicates that the patient has depression, and the higher the score, the more severe the patient’s depression.

Statistical analysis

The sample size calculation formula for multiple rate comparisons was used. The sample size was calculated according to the formula: N = Z 2 ×[P× (1-P)]/E 2 . Where N is the sample size; Z is the statistic, and when the confidence is 95%, Z = 1.96; When the confidence is 90%, Z = 1.64; E is the error value; P is the probability value; Thirty samples is the minimum sample size for a quantitative study. All data were entered using Epidata, and SPSS 28.0 was used for statistical processing. Independent samples t test was used for measurement data expressed as mean ± standard deviation (X ± SD), and χ 2 test was used for count data expressed as percentage (%). Statistical P  < 0.05 is significant.

General data analysis

The gender, average age, body mass index and educational level of the two groups of patients were compared by t test and chi-square test, and there was no statistical significance ( P  > 0.05). See Table  1 .

Quality of life score comparison

Before nursing, there was no significant difference in the quality of life scores between the two groups ( P  > 0.05). After nursing, the physical function score, emotional function score, cognitive function score, and social function score of the mindfulness group were significantly higher than those of the active control group, but the economic difficulty score of the mindfulness group was significantly lower than that of the active control group, which was statistically significant. ( P  < 0.05). See Fig.  1 .

Comparison of quality of life scores. For the quality of life score data in our study, all data were entered using Epidata, and SPSS 28.0 was used for statistical processing of the data, and the measurement data expressed as mean ± standard deviation (± SD) were tested by independent samples t test The results showed that before nursing, there was no significant difference in the quality of life scores between the two groups ( P  > 0.05). ( A ) The physical function score of the mindfulness group and the active control group after nursing. ( B ) The emotional function score of the mindfulness group and the active control group after nursing. ( C ) The cognitive function score of the mindfulness group and the active control group after nursing. ( D ) The social function scores of the mindfulness group and the active control group after nursing. ( E ) The Financial Hardship scores of the mindfulness group and the active control group after nursing. There were statistical significance (* P  < 0.05)

Comparison of mindfulness levels

Before nursing, there was no significant difference in the level of mindfulness between the two groups ( P  > 0.05). After nursing, the observation score, descriptive score, action score, intrinsic experience score, non-judgment score, and non-reaction score of the mindfulness group were significantly higher than those of the active control group, and the difference was statistically significant ( P  < 0.05). See Fig.  2 .

Comparison of mindfulness levels. For the mindfulness level data in our study, Epidata was used to enter all data, SPSS 28.0 was used to perform statistical processing, and the measurement data expressed as mean ± standard deviation (± SD) was tested by independent samples t test. Results It was found that before nursing, there was no significant difference in the level of mindfulness between the two groups ( P  > 0.05). The sex score was significantly higher than that of the active control group, and the difference was statistically significant ( P  < 0.05). ( A ) The observation score of the mindfulness group and the active control group after nursing. ( B ) The descriptive score of the mindfulness group and the active control group after nursing. ( C ) The action score of the mindfulness group and the active control group after nursing. ( D ) The non-judgmental scores of the mindfulness group and the active control group after nursing. ( E ) The non-responsiveness scores of the mindfulness group and the active control group after nursing. There were statistical significance (** P  < 0.05)

Bad mood comparison

The independent sample t-test analysis of the two groups of patients showed that there was no significant difference in the difficult emotions between the two groups before nursing ( P  > 0.05). After nursing, the HAMA score and HAMD score of the mindfulness group were significantly lower than those of the active control group, and statistics showed that the difference was statistically significant ( P  < 0.05). See Fig.  3 .

Comparison of bad mood. For the bad mood data in our study, Epidata was used to input all the data, SPSS 28.0 was used to perform statistical processing on the data, and the measurement data expressed as mean ± standard deviation used an independent sample t test. The results showed that the two groups of the independent sample t-test analysis showed that there was no significant difference in the difficult emotions of the two groups of patients before nursing ( P  > 0.05). ( A ) The HAMA score of the mindfulness group and the active control group after nursing. ( B ) The HAMD score of the mindfulness group and the active control group after nursing. There were statistical significance (*** P  < 0.05)

Main interpretation

Mindfulness therapy is a meditation method founded by Zen Buddhism that pays attention to the moment, does not judge, and is aware [ 16 ].Mindfulness therapy mainly allows patients to use various mindfulness trainings such as sitting, scanning, meditation, etc., so that the patient can achieve emotional regulation through making people more conscious about their emotions and reactivity when facing stress and be able to choose a more conscious response [ 17 ]. Mindfulness does never talk about control emotions. Mindfulness therapy is a kind of psychotherapy and a meditation method, which has become one of the main methods for the treatment of mental illness in China [ 18 ]. The subsequent development of this technology has fallen into a bottleneck period due to insufficient theoretical basis for exposure and unclear therapeutic mechanism. But with the deepening of research [ 19 ]. By introducing the etiology theory, method and technical theoretical basis of mindfulness therapy, it is found that attachment and breaking of attachment can keep the body away from mental illness and achieve true health and happiness, which significantly improves the precision and science of mindfulness therapy [ 20 ]. At present, mindfulness therapy is widely used in many fields, such as psychological efficacy, physiological efficacy, clinical efficacy and so on. Therefore, our study aims to provide a theoretical basis for our research through the discussion of mindfulness therapy.

Neoplasms remain the main cause of death worldwide [ 21 , 22 , 23 , 24 ]. The quality of life of colorectal cancer patients undergoing chemotherapy has an important relationship with adverse factors such as anxiety and depression, and the adverse factors and quality of life also affect each other. The main reasons for the occurrence of difficult emotions in colorectal cancer chemotherapy patients include: colorectal cancer chemotherapy patients need to face the threat of individual life, and at the same time need to accept the reality of self-image damage, especially younger patients are particularly prone to anxiety, depression, difficult emotions such as anxiety [ 25 ]. Chemotherapy requires a lot of costs for patients, and the beneficiaries are worried that the excessive treatment costs will increase the financial burden of the family, and they will also worry that their own disease will affect the harmony of the family [ 26 ].

Clinical implications

Our study found that after nursing, the physical function, emotional function, cognitive function, and social function of the patients in the mindfulness group were significantly higher than those in the active control group. However, the overall life and economic difficulties of the patients in the mindfulness group were significantly lower than those in the active control group. Statistical significance. After nursing, the HAMA score and HAMD score of the mindfulness group were significantly lower than those of the active control group, and statistics showed that the difference was statistically significant. We found that mindfulness intervention can reduce negative emotions, improve level of mindfulness, and quality of life of patients undergoing chemotherapy after colorectal cancer. It shows that mindfulness intervention can effectively reduce postoperative anxiety and depression in patients with colorectal cancer, which may be because mindfulness intervention improves patients’ concentration and ability to resist stressful events through specific methods such as breathing awareness, sitting meditation and walking meditation, increase patient tolerance for adverse events and reduce patient sensitivity to difficult emotions. The reasons for the analysis are as follows: mindfulness intervention does not allow patients to avoid difficult emotions, but allows patients to truly perceive the existence of difficult emotions and accept their own difficult emotions, and then people become more able to tolerant of difficult emotions and the negative reactions when they appear [ 27 ]. This has positive implications for alleviating the automatic emotional responses generated by negative beliefs, thereby improving patients’ sleep quality and solving physiological problems [ 28 ]. Long-term mental awareness connections can even alter the parenchymal structure of the brain, improving the cortical areas of the right anterior lobe and right anterior limbic system, which are important for regulating mood and memory in patients, reducing the automated emotions generated by negative beliefs reaction [ 29 ]. This also shows that mindfulness intervention is of great significance for affecting the physiological susceptibility of individuals to difficult emotions, thereby improving the negative emotions in patients with colorectal cancer chemotherapy, and improving the quality of sleep and life of patients [ 30 ]. Mindfulness intervention is more in line with the trend of modern medical development, focusing on cultivating patients’ awareness of correct cognition of diseases, and cultivating patients to use scientific methods to regulate their own emotions and behavior [ 31 ]. In order to improve the patient’s psychological coping ability, cultivate the patient’s health awareness and healthy behavior, improve the patient’s coping ability and psychological status, and improve the patient’s quality of life as a whole [ 32 ].

Our study found that the observation score, descriptive score, action score, intrinsic experience score, non-judgment score, and non-reactivity score of the mindfulness group after nursing were significantly higher than those of the active control group, and statistics showed that the difference was statistically significant. The main reason is that colorectal cancer patients have a certain fear of their disease, and feel very helpless about the gradual decline in their living standards and quality in the future. The high economic burden caused by the family, etc., eventually leads the patient to be in a state of mental stress with high tension and excessive anxiety, which gradually makes the mindfulness of colorectal cancer patients in a lower state [ 33 ]. The awareness-action score in the mindfulness level is the highest, while the non-judgmental score for inner experience is the lowest, mainly because colorectal cancer patients are more cooperative with medical staff in the treatment process [ 34 ]. Moreover, this cognitive behavior will have a higher positive effect on the patients in the next stage of treatment, thus making the colorectal cancer patients’ awareness behavior at a higher level [ 35 ]. Andrew et al. [ 36 ] conducted a 4-week randomized controlled study on 68 patients and found that compared with the active control group, the increase in awkward symptoms in the mindfulness group was significantly reduced at week 8. Although the results suggested that mindfulness was not superior to the active control group in alleviating psychological distress, both treatments had partial improvement in depression. Mindfulness intervention is reliable and acceptable. Compared to our study, different populations included in the study, varying levels of acceptance of mindfulness interventions by patients, and cultural differences will lead to varying degrees of bias in the results. The clinical sample size of this study is small, and the region and patient population are relatively limited. We will need to conduct large sample multicenter clinical studies for verification in the future. However, after the colorectal cancer patients came forward, they recurred, mainly because the patients lacked effective medical care during the actual healing process, and the patients failed to effectively implement the rehabilitation-related methods explained by the medical staff after being discharged from the hospital. In the actual operation process, there will be a certain degree of fear and resistance, which leads to a low level of the patient’s non-judgmental dimension score [ 37 ].

Study limitations

Our study is affected by objective conditions, and our study has certain shortcomings that need to be further improved and supplemented. In addition, our study only conducted a preliminary qualitative and quantitative study on the level of positive thinking, health beliefs and self-management efficacy of some patients before and after the intervention. The study explored the effect of positive self-management efficacy of colorectal cancer patients, with the aim of bridging the lack of systematic and rigorous theoretical support for positive thinking therapy, so as to provide healing tools for clinical treatment of colorectal cancer patients, and then better provide treatment services for colorectal cancer patients.

In conclusion, mindfulness intervention in patients undergoing chemotherapy after colorectal cancer can reduce their negative emotions, improve the level of mindfulness, and improve the quality of life of patients.

Data availability

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Acknowledgements

This project was supported by the Medjaden Academy & Research Foundation for Young Scientists (Grant No. MJA202306056).

Hebei Provincial Health and Family Planning Commission medical science research project (20200597).

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Yaning Feng and Jianchun Fan contributed equally to this work.

Authors and Affiliations

Physical Examination Center, The First Affiliated Hospital of Hebei North University, Zhangjiakou, 075000, China

Yaning Feng

Hospital Office, The First Affiliated Hospital of Hebei North University, Zhangjiakou, 075000, China

Kuanlei Wang

Graduate School, Hebei North University, Zhangjiakou, 075000, China

Jianchun Fan

Department of General Surgery, The First Affiliated Hospital of Hebei North University, 12 Changqing Rd, Zhangjiakou, 075000, China

Xueliang Wu & Zhili Yang

Tumor Research Institute, The First Affiliated Hospital of Hebei North University, Zhangjiakou, 075000, China

Xueliang Wu

School of Basic Medicine, Fourth Military Medical University, Xi’an, 710032, China

Department of Anorectal Surgery, Xinchang Country People’s Hospital, 117 Gushan Middle Road, Xinchang, Zhejiang Province, 312500, China

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Yaning Feng performed the statistical analyses and wrote the manuscript. Kuanlei Wang, Jianchun Fan completed all the data entry and provided assistance for the data analysis. Xueliang Wu designed and wrote the study protocol and reviewed the manuscript. Yaning Feng participated the revision of this manuscript. Xueliang Wu participated in manuscript revision. Tian Li offered many constructive opinions on this study and provided a critical revision of the manuscript for important intellectual content. All authors contributed to and approved the final manuscript.

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Feng, Y., Wang, K., Fan, J. et al. Mindfulness intervention, homogeneous medical concept, and concentrated solution nursing for colorectal cancer patients: a retrospective study. BMC Cancer 24 , 1055 (2024). https://doi.org/10.1186/s12885-024-12508-y

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Solid health care waste management practice in Ethiopia, a convergent mixed method study

• Yeshanew Ayele Tiruneh 1 ,
• L. M. Modiba 2 &
• S. M. Zuma 2  

BMC Health Services Research volume  24 , Article number:  985 ( 2024 ) Cite this article

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Metrics details

Introduction

Healthcare waste is any waste generated by healthcare facilities that is considered potentially hazardous to health. Solid healthcare waste is categorized into infectious and non-infectious wastes. Infectious waste is material suspected of containing pathogens and potentially causing disease. Non-infectious waste includes wastes that have not been in contact with infectious agents, hazardous chemicals, or radioactive substances, similar to household waste, i.e. plastic, papers and leftover foods.

This study aimed to investigate solid healthcare waste management practices and develop guidelines to improve solid healthcare waste management practices in Ethiopia. The setting was all health facilities found in Hossaena town.

A mixed-method study design was used. For the qualitative phase of this study, eight FGDs were conducted from 4 government health facilities, one FGD from each private health facility (which is 37 in number), and forty-five FGDs were conducted. Four FGDs were executed with cleaners; another four were only health care providers because using homogeneous groups promotes discussion. The remaining 37 FGDs in private health facilities were mixed from health professionals and cleaners because of the number of workers in the private facilities. For the quantitative phase, all health facilities and health facility workers who have direct contact with healthcare waste management practice participated in this study. Both qualitative and quantitative study participants were taken from the health facilities found in Hossaena town.

Seventeen (3.1%) health facility workers have hand washing facilities. Three hundred ninety-two (72.6%) of the participants agree on the availability of one or more personal protective equipment (PPE) in the facility ‘‘ the reason for the absence of some of the PPEs, like boots and goggles, and the shortage of disposable gloves owes to cost inflation from time to time and sometimes absent from the market’’ . The observational finding shows that colour-coded waste bins are available in 23 (9.6%) rooms. 90% of the sharp containers were reusable, and 100% of the waste storage bins were plastic buckets that were easily cleanable. In 40 (97.56%) health facilities, infectious wastes were collected daily from the waste generation areas to the final disposal points. Two hundred seventy-one (50.2%) of the respondents were satisfied or agreed that satisfactory procedures are available in case of an accident. Only 220 (40.8%) respondents were vaccinated for the Hepatitis B virus.

Hand washing facilities, personal protective equipment and preventive vaccinations are not readily available for health workers. Solid waste segregation practices are poor and showed that solid waste management practices (SWMP) are below the acceptable level.

Peer Review reports

Healthcare waste (HCW) encompasses all types of waste generated while providing health-related services, spanning activities such as diagnosis, immunization, treatment, and research. It constitutes a diverse array of materials, each presenting potential hazards to health and the environment. Within the realm of HCW, one finds secretions and excretions from humans, cultures, and waste containing a stock of infectious agents. Discarded plastic materials contaminated with blood or other bodily fluids, pathological wastes, and discarded medical equipment are classified as healthcare waste. Sharps, including needles, scalpels, and other waste materials generated during any healthcare service provision, are also considered potentially hazardous to health [ 1 ].

Healthcare waste in solid form (HCW) is commonly divided into two primary groups: infectious and non-infectious. The existence of pathogens in concentrations identifies infectious waste or amounts significant enough to induce diseases in vulnerable hosts [ 1 ] If healthcare facility waste is free from any combination with infectious agents, nearly 85% is categorized as non-hazardous waste, exhibiting characteristics similar to conventional solid waste found in households [ 2 ]. World Health Organization (WHO) recommends that appropriate colour-coded waste receptacles be available in all medical and other waste-producing areas [ 3 ].

Solid waste produced in the course of healthcare activities carries a higher potential for infection and injury than any other type of waste. Improper disposal of sharps waste increases the risk of disease transmission among health facility workers and general populations [ 1 ]. Inadequate and inappropriate handling of healthcare waste may have serious public health consequences and a significant environmental impact. The World Health Organization (2014) guidelines also include the following guidance for hand washing and the use of alcohol-based hand rubs: Wash hands before starting work, before entering an operating theatre, before eating, after touching contaminated objects, after using a toilet, and in all cases where hands are visibly soiled [ 4 ].

Among the infectious waste category, sharps waste is the most hazardous waste because of its ability to puncture the skin and cause infection [ 3 ]. Accidents or occurrences, such as near misses, spills, container damage, improper waste segregation, and incidents involving sharps, must be reported promptly to the waste management officer or an assigned representative [ 5 ].

Africa is facing a growing waste management crisis. While the volumes of waste generated in Africa are relatively small compared to developed regions, the mismanagement of waste in Africa already impacts human and environmental health. Infectious waste management has always remained a neglected public health problem in developing countries, resulting in a high burden of environmental pollution affecting the general masses. In Ethiopia, there is no updated separate regulation specific to healthcare waste management in the country to enforce the proper management of solid HCW [ 6 ].

In Ethiopia, like other developing countries, healthcare waste segregation practice was not given attention and did not meet the minimum HCWM standards, and it is still not jumped from paper. Previous study reveals that healthcare waste generation rates are significantly higher than the World Health Organization threshold, which ranges from 29.5–53.12% [ 7 , 8 ]. In Meneilk II Hospital, the proportion of infectious waste was 53.73%, and in the southern and northern parts of Ethiopia, it was 34.3 and 53%, respectively. Generally, this figure shows a value 3 to 4 times greater than the threshold value recommended by the World Health Organization [ 7 ].

Except for sharp wastes, segregation practice was poor, and all solid wastes were collected without respecting the colour-coded waste disposal system [ 9 ]. The median waste generation rate was found to vary from 0.361- 0.669 kg/patient/day, comprising 58.69% non-hazardous and 41.31% hazardous wastes. The amount of waste generated increased as the number of patients flow increased. Public hospitals generated a high proportion of total healthcare waste (59.22%) in comparison with private hospitals (40.48) [ 10 ]. The primary SHCW treatment and disposal mechanism was incineration, open burning, burring into unprotected pits and open dumping on municipal dumping sites as well as in the hospital backyard. Carelessness, negligence of the health workers, patients and cleaners, and poor commitment of the facility leaders were among the major causes of poor HCWM practice in Ethiopia [ 9 ]. This study aimed to investigate solid healthcare waste management practices and develop guidelines to improve solid healthcare waste management practices in Ethiopia.

The setting for this study was all health facilities found in Hossaena town, which is situated 232 kms from the capital city of Ethiopia, Addis Ababa, and 165 kms from the regional municipality of Hawasa. The health facilities found in the town were one university hospital, one private surgical centre, three government health centres, 17 medium clinics, and 19 small clinics were available in the city and; health facility workers who have direct contact with generating and disposal of HCW and those who are responsible as a manager of health facilities found in Hossaena town are the study settings. All health facilities except drug stores and health facility workers who have direct contact with healthcare waste generation participated in this study.

A mixed-method study design was used. For the quantitative part of this study, all healthcare workers who have direct contact with healthcare waste management practice participated in this study, and one focus group discussion from each health facility was used. Both of the study participants were taken from the same population. All health facility workers who have a role in healthcare waste management practice were included in the quantitative part of this study. The qualitative data collection phase used open-ended interviews, focus group discussions, and visual material analysis like posters and written materials. All FGDs were conducted by the principal investigator, one moderator, and one note-taker, and it took 50 to 75 min. 4–6 participants participated in each FGD.

According to Elizabeth (2018: 5), cited by Creswell and Plano (2007: 147), the mixed method is one of the research designs with philosophical assumptions as well as methods of inquiry. As a method, it focuses on collecting, analyzing, and mixing both quantitative and qualitative data in a single study. As a methodology, it involves philosophical assumptions guiding the direction of the collection and analysis and combining qualitative and quantitative approaches in many phases of the research project. The central premise is that using qualitative and quantitative approaches together provides a better understanding of the research problems than either approach alone.

The critical assumption of the concurrent mixed methods approach in this study is that quantitative and qualitative data provide different types of information, often detailed views of participants’ solid waste management practice qualitatively and scores on instruments quantitatively, and together, they yield results that should be the same. In this approach, the researcher collected quantitative and qualitative data almost simultaneously and analyzed them separately to cross-validate or compare whether the findings were similar or different between the qualitative and quantitative information. Concurrent approaches to the data collection process are less time-consuming than other types of mixed methods studies because both data collection processes are conducted on time and at the same visit to the field [ 11 ].

Data collection

The data collection involves collecting both quantitative and qualitative data simultaneously. The quantitative phase of this study assessed three components. Health care waste segregation practice, the availability of waste segregation equipment for HCW segregation, temporary storage facilities, transportation for final disposal, and disposal facilities data were collected using a structured questionnaire and observation of HCW generation. Recycling or re-using practice, waste treatment, the availability of the HCWM committee, and training data were collected.

Qualitative data collection

The qualitative phase of the data collection for this study was employed by using focus group discussions and semi-structured interviews about SHCWMP. Two focus group discussions (FGD) from each health facility were conducted in the government health facilities, one at the administrative level and one at the technical worker level, and one FGD was conducted for all private health facilities because of the number of available health facility workers. Each focus group has 4–6 individuals.

In this study, the qualitative and the quantitative data provide different information, and it is suitable for this study to compare and contrast the findings of the two results to obtain the best understanding of this research problem.

Quantitative data collection

The quantitative data were entered into Epi data version 3.1 to minimize the data entry mistakes and exported to the statistical package for social science SPSS window version 27.0 for analysis. A numeric value was assigned to each response in a database, cleaning the data, recoding, establishing a codebook, and visually inspecting the trends to check whether the data were typically distributed.

Data analysis

Data were analyzed quantitatively by using relevant statistical tools, such as SPSS. Descriptive statistics and the Pearson correlation test were used for the bivariate associations and analysis of variance (ANOVA) to compare the HCW generation rate between private and government health facilities and between clinics, health centres and hospitals in the town. Normality tests were performed to determine whether the sample data were drawn from a normally distributed population.

The Shapiro–Wilk normality tests were used to calculate a test statistic based on the sample data and compare it to critical values. The Shapiro–Wilk test is a statistical test used to assess whether a given sample comes from a normally distributed population. The P value greater than the significance level of 0.05 fails to reject the null hypothesis. It concludes that there is not enough evidence to suggest that the data does not follow the normal distribution. Visual inspection of a histogram, Q-Q plot, and P-P plot (probability-probability plot) was assessed.

Bivariate (correlation) analysis assessed the relationships between independent and dependent variables. Then, multiple linear regression analysis was used to establish the simple correlation matrices between different variables for investigating the strength relationships of the study variables in the analysis. In most variables, percentages and means were used to report the findings with a 95% confidence interval. Open-ended responses and focused group findings were undertaken by quantifying and coding the data to provide a thematic narrative explanation.

Appropriate and scientific care was taken to maintain the data quality before, during, and after data collection by preparing the proper data collection tools, pretesting the data collection tools, providing training for data collectors, and proper data entry practice. Data were cleaned on a daily basis during data collection practice, during data entry, and before analysis of its completeness and consistency.

Data analysis in a concurrent design consists of three phases. First, analyze the quantitative database in terms of statistical results. Second, analyze the qualitative database by coding the data and collapsing the codes into broad themes. Third comes the mixed-method data analysis. This is the analysis that consists of integrating the two databases. This integration consists of merging the results from both the qualitative and the quantitative findings.

Descriptive analysis was conducted to describe and summarise the data obtained from the samples used for this study. Reliability statistics for constructs, means and modes of each item, frequencies and percentage distributions, chi-square test of association, and correlations (Spearman rho) were used to portray the respondents’ responses.

All patient care-providing health facilities were included in this study, and the generation rate of healthcare waste and composition assessed the practice of segregation, collection, transportation, and disposal system was observed quantitatively using adopted and adapted structured questionnaires. To ensure representativeness, various levels of health facilities like hospitals, health centres, medium clinics, small clinics and surgical centres were considered from the town. All levels of health facilities are diagnosing, providing first aid services and treating patients accordingly.

The hospital and surgical centre found in the town provide advanced surgical service, inpatient service and food for the patients that other health facilities do not. The HCW generation rate was proportional to the number of patients who visited the health facilities and the type of service provided. The highest number of patients who visited the health facilities was in NEMMCSH; the service provided was diverse, and the waste generation rate was higher than that of other health facilities. About 272, 18, 15, 17, and 20 average patients visited the health facilities daily in NEMMCSH: government health centres, medium clinics, small clinics, and surgical centres. Paper and cardboard (141.65 kg), leftover food (81.71 kg), and contaminated gloves (42.96 kg) are the leading HCWs generated per day.

A total of 556 individual respondents from sampled health facilities were interviewed to complete the questionnaire. The total number of filled questionnaires was 540 (97.1) from individuals representing these 41 health facilities.

The principal investigator observed the availability of handwashing facilities near SHCW generation sites. 17(3.1%) of health facility workers had hand washing facilities near the health care waste generation and disposal site. Furthermore,10 (3.87%), 2 (2.1%), 2 (2.53%), 2 (2.1%), 1 (6.6%) of health facility workers had the facility of hand washing near the health care waste generation site in Nigist Eleni Mohamed Memorial Comprehensive Specialized Hospital (NEMMCSH), government health centres, medium clinics, small clinics, and surgical centre respectively. This finding was nearly the same as the study findings conducted in Myanmar; the availability of hand washing facilities near the solid health care waste generation was absent in all service areas [ 12 ]. The observational result was convergent with the response of facility workers’ response regarding the availabilities of hand washing facilities near to the solid health care waste generation sites.

The observational result was concurrent with the response of facility workers regarding the availability of hand-washing facilities near the solid health care waste generation sites.

The availability of personal protective equipment (PPE) was checked in this study. Three hundred ninety-two (72.6%) of the respondents agree on the facility’s availability of one or more personal protective equipment (PPE). The availability of PPEs in different levels of health facilities shows 392 (72.6%), 212 (82.2%), 56 (58.9%), 52 (65.8%), 60 (65.2%), 12 (75%) health facility workers in NEMMCSH, government health centres, medium clinics, small clinics, and surgical centres respectively agree to the presence of personal protective equipment in their department. The analysis further shows that the availability of masks for healthcare workers was above the mean in NEMMCSH and surgical centres.

Focus group participants indicated that health facilities did not volunteer to supply Personal protective equipment (PPEs) for the cleaning staff.

“We cannot purchase PPE by ourselves because of the salary paid for the cleaning staff.”

Cost inflation and the high cost of purchasing PPEs like gloves and boots are complained about by all (41) health facility owners.

“the reason for the absence of some of the PPEs like boots, goggles, and shortage of disposable gloves are owing to cost inflation from time to time and sometimes absent from the market is the reason why we do not supply PPE to our workers.”

Using essential personal protective equipment (PPEs) based on the risk (if the risk is a splash of blood or body fluid, use a mask and goggles; if the risk is on foot, use appropriate shoes) is recommended by the World Health Organization [ 13 ]. The mean availability of gloves in health facilities was 343 (63.5% (95% CI: 59.3–67.4). Private health institutions are better at providing gloves for their workers, 67.1%, 72.8%, and 62.5% in medium clinics, small clinics, and surgical centres, respectively, which is above the mean.

Research participants agree that.

‘‘ there is a shortage of gloves to give service in Nigist Eleni Mohamed Memorial Comprehensive Specialized Hospital (NEMMCSH) and government health centres .’’

Masks are the most available personal protective equipment for health facility workers compared to others. 65.4%, 55.6%, and 38% of the staff are available with gloves, plastic aprons and boots, respectively.

The mean availability of masks, heavy-duty gloves, boots, and aprons was 71.1%, 65.4%, 38%, and 44.4% in the study health facilities. Health facility workers were asked about the availability of different personal protective equipment, and 38% of the respondents agreed with the presence of boots in the facility. Still, the qualitative observational findings of this study show that all health facility workers have no shoes or footwear during solid health care waste management practice.

SHCW segregation practice was checked by observing the availability of SHCW collection bins in each patient care room. Only 4 (1.7%) of the room’s SHCW bins are collected segregated (non-infectious wastes segregated in black bins and infectious wastes segregated in yellow bins) based on the World Health Organization standard. Colour-coded waste bins, black for non-infectious and yellow for infectious wastes, were available in 23 (9.6%) rooms. 90% of the sharp containers were reusable, and 100% of the waste storage bins were plastic buckets that were easily cleanable. Only 6.7% of the waste bins were pedal operated and adequately covered, and the rest were fully opened, or a tiny hole was prepared on the container’s cover. All of the healthcare waste disposal bins in each health facility and at all service areas were away from the arm’s reach distance of the waste generation places, and this is contrary to World Health Organization SHCWM guidelines [ 13 ]. The observation result reveals that the reason for the above result was that medication trolleys were not used during medication or while healthcare providers provided any health services to patients.

Most medical wastes are incinerated. Burning solid and regulated medical waste generated by health care creates many problems. Medical waste incinerators emit toxic air pollutants and ash residues that are the primary source of environmental dioxins. Public concerns about incinerator emissions and the creation of federal regulations for medical waste incinerators are causing many healthcare facilities to rethink their choices in medical waste treatment. Health Care Without Harm [ 14 ], states that non-incineration treatment technologies are a growing and developing field. The U.S. National Academy of Science 2000 argued that the emission of pollutants during incineration is a potential risk to human health, and living or working near an incineration facility can have social, economic, and psychological effects [ 15 ].

The incineration of solid healthcare waste technology has been accepted and adopted as an effective method in Ethiopia. Incineration of healthcare waste can produce secondary waste and pollutants if the treatment facilities are not appropriately constructed, designed, and operated. It can be one of the significant sources of toxic substances, such as polychlorinated dibenzo-dioxins/dibenzofurans (PCDD/ PCDF), polyvinyl chloride (PVC), hexachlorobenzenes and polychlorinated biphenyls, and dioxins and furans that are known as hazardous pollutants. These pollutants may have undesirable environmental impacts on human and animal health, such as liver failure and cancer [ 15 , 16 ].

All government health facilities (4 in number) used incineration to dispose of solid waste. 88.4% and 100% of the wastes are incinerated in WUNEMMCSH and government health centres. This finding contradicts the study findings in the United States of America and Malaysia, in which 49–60% and 59–60 were incinerated, respectively, and the rest were treated using other technologies [ 15 , 16 ].

World Health Organization (2014:45) highlighted those critical elements of the appropriate operation of incinerators include effective waste reduction and waste segregation, placing incinerators away from populated areas, satisfactory engineered design, construction following appropriate dimensional plans, proper operation, periodic maintenance, and staff training and management are mandatory.

Solid waste collection times should be fixed and appropriate to the quantity of waste produced in each area of the health care facility. General waste should not be collected simultaneously or in the same trolley as infectious or hazardous wastes. The collection should be done daily for most wastes, with collection timed to match the pattern of waste generation during the day [ 13 ].

SHCW segregation practices were observed for 240 rooms in 41 health facilities that provide health services in the town. In government health centres, medium clinics, small clinics, and surgical centres, SHCW segregation practice was not based on the World Health Organization standard. All types of solid waste were collected in a single container near the generation area, and there were no colour-coded SHCW storage dust bins. Still, in NEMMCSH, in most of the service areas, colour-coded waste bins are available, and the segregation practice was not based on the standard. Only 3 (10%) of the dust bins collected the appropriate wastes according to the World Health Organization standard, and the rest were mixed with infectious and non-infectious SHCW.

Table 1 below shows health facility managers were asked about healthcare waste segregation practices, and 9 (22%) of the facility leaders responded that there is an appropriate solid healthcare waste segregation practice in their health facilities. Still, during observation, only 4 (1.7%) of the rooms in two (4.87%) of the facilities, SHCW bins collected the segregated wastes (non-infectious wastes segregated at the black bin and infectious wastes segregated at yellow bin) based on the world health organization standard. The findings of this study show there is a poor segregation practice, and all kinds of solid wastes are collected together.

In 40 (97.56%) health facilities, infectious wastes were collected daily from the waste generation areas to the final disposal points. During observation in one of the study health facilities, infectious wastes were not collected daily and left for days. Utility gloves, boots, and aprons are not available for cleaning staff to collect and transport solid healthcare wastes in all study health facilities. 29.26% of the facilities’ cleaning staff have a face mask, and 36.5% of the facilities remove waste bins from the service area when 3/4 full, and the rest were not removed or replaced with new ones. There is a separate container only in 2 health facilities for infectious and non-infectious waste segregation practice, and the rest were segregated and collected using single and non-colour coded containers.

At all of the facilities in the study area, SHCW was transported from the service areas to the disposal site were transported manually by carrying the collection container and there is no trolley for transportation. This finding was contrary to the study findings conducted in India, which show segregated waste from the generation site was being transported through the chute to the carts placed at various points on the hospital premises by skilled sanitary workers [ 17 ].

Only 2 out of 41 health facilities have temporary solid waste storage points at the facility. One of the temporary storage places was clean, and the other needed to be properly cleaned and unsightly. Two (100%) of the temporary storage areas are not fenced and have no restriction to an authorized person. Temporary storage areas are available only in two health facilities that are away from the service provision areas.

Observational findings revealed that pre-treatment of SHCW before disposal was not practised at all study health facilities. 95% of the facilities have no water supply for hand washing during and after solid healthcare waste generation, collection, and disposal.

The United States Agency estimated sharp injuries from medical wastes to health professionals and sanitary service personnel for toxic substances and disease registry. Most of the injuries are caused during the recapping of hypodermic needles before disposal into sharps containers [ 13 ]. Nearly half of the respondents, 245 (51.5%), are recapping needles after providing an injection to the patient. Recapping was more practised in NEMMCSH and surgical centres, which is 57.5% and 57.5%, respectively. In government health centres, medium clinics, and surgical centres, the recapping of used needles was practised below the mean, which is 47.9%, 48, and 43.8%, respectively. This finding was reasonable compared to the study findings of Doylo et al. [ 18 ] in western Ethiopia, where 91% of the health workers are recapping needles after injection [ 18 ]. The research finding shows that there is no significant association P-value of 0.82 between the training and recapping of needles after injection.

Focus group participants ’ response for appropriate SHCWMP regarding patients ’ and visitors ’ lack of knowledge on SHCW segregation practice

“The personal responsibilities of patients and visitors on solid HCW disposal should be explained to help appropriate safe waste management practice and maintain good hygiene .” “Providing waste management training and creating awareness are the two aspects of improving SHCW segregation practice.” “Training upgrades and creates awareness on hygiene for all workers.”

Sharp waste collection practices were observed in 240 rooms in the study health facilities, and 9.2% of the rooms used disposable sharp containers.

Sixty per cent (60%), 13.3%, 8.24%, and 15.71% of the sharps containers in NEMMCSH, government health centres, medium clinics, and small clinics, respectively, were using disposable sharps containers; sharps were disposed together with the sharps container, and surgical centre was using reusable sharp collection container. All disposable sharps containers in medium and small clinics used non-puncture-resistant or simple packaging carton boxes. 60% and 13.3% of the disposable sharps containers in NEMMCSH and the government health centre use purposefully manufactured disposable safety boxes.

Needle sticks injury reporting and occurrence

A total of 70 injuries were reported to the health facility manager in the last one year, and 44 of the injuries were reported by health professionals. The rest of the injuries were reported by supportive staff. These injuries were reported from 35 health facilities, and the remaining six health facilities did not report any cases of injury related to work; see Tables 2 and 3 below.

Accidents or incidents, including near misses, spillages, damaged containers, inappropriate segregation, and any incidents involving sharps, should be reported to the waste-management officer. Accidental contamination must be notified using a standard-format document. The cause of the accident or incident should be investigated by the waste-management officer (in case of waste) or another responsible officer, who should also take action to prevent a recurrence [ 13 ]. Two hundred seventy-one (50.2% (CI: 45.7–54.6) of the respondents agree that satisfactory procedures are available in case of an accident, while the remaining 269 (49.8%( CI: 45.4–54.3) of respondents do not agree on the availability of satisfactory procedures in case of an accident, see Table  4 below. The availability of satisfactory procedures in case of an accident is above the mean in medium clinics, which is 60.8%. 132(24.4%) of the staff are pricked by needle stick injury while providing health services. Nearly half of the respondents, 269 (49.8%), who have been exposed to needle stick injury do not get satisfactory procedures after being pricked by a needle, and those who have not been stung by a needle stick injury for the last year. 204 (37.8%) disagree with the presence of satisfactory procedures in the case of a needle stick injury. In NEMMCSH, 30.2% of the research participants were pricked by needle stick injury within one year of period, and 48.8% of those who were stung by needle stick injuries did not agree upon the presence of satisfactory procedures in case of needle stick injuries in the study hospital. 17.9% and 49.5%, 24.1% and 60.8%, 7.6% and 50% of the respondents are pricked by needle sticks, and they disagree on the availability of satisfactory procedures in case of accidents, respectively, in government health centres, medium clinics, small clinics, and surgical centre respectively.

One hundred seventy-seven (32.7% (CI:29.1–37) respondents were exposed to needle stick injury while working in the current health facilities. One hundred three (58.1%) and 26 (32.9%) needle stick injuries were reported from WUNEMMCSH and medium clinics, which is above the mean. One hundred thirty-two(24.7% (95%CI:20.7–28.1) of the respondents are exposed to needle stick injury within one year of the period. Seventy-eight(30.2%), 17 (17.9%), 19 (24.1%), 15 (16.3%), 3 (18.8%) of the staff are injured by needle sticks from NEMMCSH, government health centres, medium clinics, small clinics, and surgical centre staffs respectively within one year of service.

The mean availabilities of satisfactory procedures in case of accidents were 321 (59.4% (CI:55.4–63.7). Out of this, 13.7% of the staff is injured by needle sticks within one year before the survey. Except in NEMMCSH, the mean availabilities of satisfactory procedures were above the mean, which is 50%, 60%, 77.2%, 66.3%, and 81.3% in NEMMCSH, government health centres, medium clinics, small clinics, and surgical centres respectively.

Table 5 below shows that Hepatitis B, COVID-19, and tetanus toxoid vaccinations are the responses of the research participants to an open-ended question on which vaccine they took. The finding shows that 220 (40.8%) of the respondents were vaccinated to prevent themselves from health facility-acquired infection. One hundred fifty-six (70.9%) of the respondents are vaccinated to avoid themselves from Hep B infection. Fifty-nine (26%0.8) of the respondents were vaccinated to protect themselves from two diseases that are Hep B and COVID-19.

Appropriate health care waste management practice was assessed by using 12 questions: availability of colour-coded waste bins, foot-operated dust bins, elbow or foot-operated hand washing basin, personal protective equipment, training, role and responsibility of the worker, the presence of satisfactory procedures in case of an accident, incinerator, vaccination, guideline, onsite treatment, and the availability of poster. The mean of appropriate healthcare waste management practice was 55.58%. The mean of solid health care waste management practice based on the level of health facilities was summed and divided into 12 variables to get each health facility’s level of waste management practice. 64.9%, 45.58%, 49%, 46.9%, and 51.8% are the mean appropriate health care waste management practices in NEMMCSH, government health centres, medium clinics, small clinics, and surgical centres, respectively. In NEMMCSH, the practice of solid healthcare waste management shows above the mean, and the rest was below the mean of solid healthcare waste management practice.

Healthcare waste treatment and disposal practice

Solid waste treatment before disposal was not practised at all study health facilities. There is an incineration practice at all of the study health facilities, and the World Health Organization 2014 recommended three types of incineration practice for solid health care waste management: dual-chamber starved-air incinerators, multiple chamber incinerators, and rotary kilns incinerators. Single-chamber, drum, and brick incinerators do not meet the best available technique requirements of the Stockholm Convention guidelines [ 13 ]. The findings of this study show that none of the incinerators found in the study health facilities meet the minimum standards of solid healthcare waste incineration practice, and they need an air inlet to facilitate combustion. Eleven (26.82%) of the health facilities have an ash pit to dispose of burned SHCW; the majority, 30 (73.17%), dispose of the incinerated ash and burned needles in the municipal waste disposal site. In one out of 11 health facilities with an ash pit, one of the incinerators was built on the ash pit, and the incinerated ashes were disposed of in the ash pit directly. Pre-treatment of SHCW before disposal was not practised at all health facilities; see Table  6 below.

All government health facilities use incineration to dispose of solid waste. 88.4% and 100% of the solid wastes are incinerated in WUNEMMCS Hospital and government health centres, respectively. This finding was not similar to the other studies because other technologies like autoclave microwave and incineration were used for 59–60% of the waste [ 15 ]. Forty-one (100%) of the study facilities were using incinerators, and only 5 (12.19%) of the incinerators were constructed by using brick and more or less promising than others for incinerating the generated solid wastes without considering the emitting gases into the atmosphere and the residue chemicals and minerals in the ashes.

Research participants’ understanding of the environmental friendliness of health care waste management practice was assessed, and the result shows that more than half, 312(57%) of the research participants do not agree on the environmental friendliness of the waste disposal practices in the health facilities. The most disagreement regarding environmental friendliness was observed in NEMMCSH; 100 (38.8%) of the participants only agreed the practice was environmentally friendly of the service. Forty-four (46.3%), 37 (46.8%), 40 (43.5%), and 7 (43.8%) of the participants agree on the environmental friendliness of healthcare waste management practice in government health centres, medium clinics, small clinics, and surgical centres, respectively.

One hundred twenty-five (48.4%) and 39(42.4%) staff are trained in solid health care waste management practice in NEMMCSH and small clinic staff, respectively; this result shows above the mean. Twenty-seven (28.4%), 30 (38%), and 4 (25%) of the staff are trained in health care waste management practice in Government health centres, medium clinics, and surgical centres, respectively. The training has been significantly associated with needle stick injury, and the more trained staff are, the less exposed to needle stick injury. One hundred ninety-six (36.4%) of the participants answered yes to the question about the availability of trainers in the institution. 43.8% of the NEMMCSH staff agreed on the availability of trainers on solid health care waste management, which is above the mean, and 26.3%, 31.6%, 31.5%, and 25% for the government health centres, medium clinics, small clinics, and surgical centre respectively, which is below the mean.

Trained health professionals are more compliant with SHCWM standards, and the self-reported study findings of this study show that 41.7% (95%CI:37.7–46) of the research participants are trained in health care waste management practice. This finding was higher compared to the study findings of Sahiledengle in 2019 in the southeast of Ethiopia, shows 13.0% of healthcare workers received training related to HCWM in the past one year preceding the study period and significantly lower when compared to the study findings in Egypt which is 71% of the study participants were trained on SHCWM [ 8 , 19 , 20 ].

Three out of four government health facility leaders, 17 (45.94%) of private health facility leaders/owners of the clinic and 141 FGD participants complain about the absence of some PPEs like boots and aprons to protect themselves from infectious agents.

‘ ‘Masks, disposable gloves, and changing gowns are a critical shortage at all health facilities.’’

Cleaners in private health facilities are more exposed to infectious agents because of the absence of personal protective equipment. Except for the cleaning staff working in the private surgical centre, all cleaning staff 40 (97.56) of the health facilities complain about the absence of changing gowns and the fact that there are no boots in the facilities.

Cost inflation and the high cost of purchasing PPEs like gloves and boots are complained by all of (41) the health facility owners and the reason for the absence of some of the PPEs like boots, goggles, and shortage of disposable gloves. Sometimes, absence from the market is the reason why we do not supply PPE to our workers.

Thirty-four (82.92%) of the facility leaders are forwarded, and there is a high expense and even unavailability of some of the PPEs, which are the reasons for not providing PPEs for the workers.

‘‘Medical equipment and consumables importers and whole sellers are selective for importing health supplies, and because of a small number of importers in the country and specifically, in the locality, we can’t get materials used for health care waste management practice even disposable gloves. ’’

One of the facility leaders from a private clinic forwarded that before the advent of COVID-19 -19) personal protective equipment was more or less chip-and-get without difficulty. Still, after the advent of the first Japanese COVID-19 patient in Ethiopia, people outside the health facilities collect PPEs like gloves and masks and storing privately in their homes.

‘‘PPEs were getting expensive and unavailable in the market. Incinerator construction materials cost inflation, and the ownership of the facility building are other problems for private health facilities to construct standard incinerators.’’

For all of the focus group discussion participants except in NEMMCSH and two private health facilities, covered and foot-operated dust bins were absent or in a critical shortage compared to the needed ones.

‘‘ Waste bins are open and not colour-coded. The practice attracts flies and other insects. Empty waste bins are replaced without cleaning and disinfecting by using chlorine solution.’’ “HCW containers are not colour-coded, but we are trying to label infectious and non-infectious in Amharic languages.”

Another issue raised during focus group discussions is incineration is not the final disposal method. It needs additional disposal sites, lacks technology, is costly to construct a brick incinerator, lacks knowledge for health facility workers, shortage of man powers /cleaners, absence of environmental health professionals in health centres and all private clinics, and continues exposure to the staff for needle stick injury, foully smell, human scavengers, unsightly, fire hazard, and lack of water supply in the town are the major teams that FGD participants raise and forwarded the above issue as a problem to improve SHCWMP.

Focus group participants, during the discussion, raised issues that could be more comfortable managing SHCWs properly in their institution. Two of the 37 private health facilities are working in their own compound, and the remaining 35 are rented; because of this, they have difficulty constructing incinerators and ash removal pits and are not confident about investing in SHCWM systems. Staff negligence and involuntary abiding by the rules of the facilities were raised by four of the government health facilities, and it was difficult to punish those who violated the healthcare waste management rules because the health facility leaders were not giving appropriate attention to the problem.

Focus group participants forwarded recommendations on which interventions can improve the management of SHCW, and recommendations are summarised as follows:

“PPE should be available in quality and quantity for all health facility workers who have direct contact with SHCW.” “Scientific-based waste management technologies should be availed for health facilities.” “Continuous induction HCW management training should be provided to the workers. Law enforcement should be strengthened.” “Communal HCW management sites should be availed, especially for private health facilities.” “HCWM committee should be strengthened.” “Non-infectious wastes should be collected communally and transported to the municipal SHCW disposal places.” “Leaders should be knowledgeable on the SHCWM system and supervise the practice continuously.” “Patient and client should be oriented daily about HCW segregation practice.” “Regulatory bodies should supervise the health facilities before commencing and periodically between services .”

The above are the themes that FGD participants discussed and forwarded for the future improvements of SHAWMP in the study areas.

Lack of water supply in the town

Other issues raised during FGDs were health facilities’ lack of water supply. World Health Organization (2014: 89) highlights that water supply for the appropriate waste management system should be mandatory at any time in all health service delivery points.

Thirty-nine (95.12%) of the health facilities complain about the absence of water supply to improve HCW management practices and infection prevention and control practices in the facilities.

“We get water once per week, and most of the time, the water is available at night, and if we are not fetching as scheduled, we can’t get water the whole week”.

In this research, only those who have direct contact have participated in this study, and 434 (80.4%) of the respondents agree they have roles and responsibilities for appropriate solid health care waste management practice. The rest, 19.6%, do not agree with their commitment to manage health care wastes properly, even though they are responsible. Health facility workers in NEMMCSH and medium clinics know their responsibilities better than others, and their results show above the mean. 84.5%, 74.5%, 81%, 73.9% and 75% in NEMMCSH, Government health centres, medium clinics, small clinics, and surgical centres, respectively.

Establishing a policy and a legal framework, training personnel, and raising public awareness are essential elements of successful healthcare waste management. A policy can be viewed as a blueprint that drives decision-making at a political level and should mobilize government effort and resources to create the conditions to make changes in healthcare facilities. Three hundred and seventy-four (69.3%) of the respondents agree with the presence of any solid healthcare waste management policy in Ethiopia. The more knowledge above the mean (72.9%) on the presence of the policy is reported from NEMMCSH.

Self-reported level of knowledge on what to do in case of an accident revealed that 438 (81.1% CI: 77.6–84.3%) of the respondents knew what to do in case of an accident. Government health centre staff and medium clinic staff’s knowledge about what to do in case of an accident was above the mean (88.4% and 82.3%), respectively, and the rest were below the mean. The action performed after an occupational accident revealed that 56 (35.7%) of the respondents did nothing after any exposure to an accident. Out of 56 respondents who have done nothing after exposure, 47 (83.92%) of the respondents answered yes to their knowledge about what to do in case of an accident. Out of 157 respondents who have been exposed to occupational accidents, only 59 (37.6%) of the respondents performed the appropriate measures, 18 (11.5%), 9 (5.7%), 26 (16.6%), 6 (3.8%) of the respondents are taking prophylaxis, linked to the incident officer, consult the available doctors near to the department, and test the status of the patient (source of infection) respectively and the rest were not performing the scientific measures, that is only practising one of the following practices washing the affected part, squeezing the affected part to remove blood, cleaning the affected part with alcohol.

Health facility workers’ understanding of solid health care waste management practices was assessed by asking whether the current SHCWM practice needs improvement. Four hundred forty-nine (83.1%) health facility workers are unsatisfied with the current solid waste management practice at the different health facility levels, and they recommend changing it to a scientific one. 82.6%, 87.4%, 89.9%, 75%, and 81.3% of the respondents are uncomfortable or need to improve solid health care waste management practices in NEMMCSH, government health centres, medium clinics, small clinics, and surgical centres, respectively.

Lack of safety box, lack of colour-coded waste bins, lack of training, and no problems are the responses to the question problems encountered in managing SHCWMP. Two Hundred and Fifty (46.92%) and 232 (42.96%) of the respondents recommend the availability of safety boxes and training, respectively.

Four or 9.8% of the facilities have infection prevention and control (IPC) teams in the study health facilities. This finding differed from the study in Pakistan, where thirty per cent (30%) of the study hospitals had HCWM or infection control teams [ 21 ]. This study’s findings were similar to those conducted in Pakistan by Khan et al. [ 21 ], which confirmed that the teams were almost absent at the secondary and primary healthcare levels [ 20 ].

The availability of health care waste management policy report reveals that 69.3% (95% CI: 65.4–73) of the staff are aware of the presence of solid health care waste management policy in the institution. Availability of health care waste management policy was 188 (72.9%), 66 (69.5%), 53 (677.1%), 57 (62%), 10 (62.5%) in NEMMCSH, Government health centres, medium clinics, small clinics, and surgical centre respectively. Healthcare waste management policy availability was above the mean in NEMMCSH and government health centres; see Table  6 below.

Open-ended responses on the SHCWM practice of health facility workers were collected using the prepared interview guide, and the responses were analyzed using thematic analysis. All the answered questions were tallied on the paper and exported to Excel software for thematic analysis.

The study participants recommend.

“appropriate segregation practice at the point of generation” "health facility must avail all the necessary supplies that used for SHCWMP, punishment for those violating the rule of SHCWMP",

“waste management technologies should be included in solid waste management guidelines, and enforcement should be strengthened.”

The availability of written national or adopted/adapted SHCWM policies was observed at all study health facilities. Twenty eight (11.66%) of the rooms have either a poster or a written document of the national policy document. However, all staff working in the observed rooms have yet to see the inside content of the policy. The presence of the policy alone cannot bring change to SHCWMP. This finding shows that the presence of policy in the institution was reasonable compared to the study findings in Menelik II hospital in Addis Ababa, showing that HCWM regulations and any applicable facility-based policy and strategy were not found [ 22 ]. The findings of this study were less compared to the study findings in Pakistan; 41% of the health facilities had the policy document or internal rules for the HCWM [ 21 ].

Focus group participants have forwarded recommendations on which interventions can improve the management of SHCW, and recommendations are summarised as follows.

‘‘Supplies should be available in quality and quantity for all health facility workers with direct contact with SHCW. Scientific-based waste management technologies should be available for health facilities. Continues and induction health care waste management training should be provided to the workers. Law enforcement should be strengthened. Community healthcare waste management sites should be available, especially for private health facilities. HCWM committee should be strengthened. Non-infectious wastes should be collected communally and transported to the municipal SHCW disposal places. Leaders should be knowledgeable about the SHCWM system and supervise the practice continuously. Patients and clients should be oriented daily about health care waste segregation practices. Regulatory bodies should supervise the health facilities before commencing and periodically in between the service are the themes those FGD participants discussed and forward for the future improvements of SHCWMP in the study areas.’’

The availability of PPEs in different levels of health facilities shows 392 (72.6%), 212 (82.2%), 56 (58.9%), 52 (65.8%), 60 (65.2%), 12 (75%) health facility workers in NEMMCSH, government health centres, medium clinics, small clinics, and surgical centres respectively agree to the presence of personal protective equipment in their department. The availability of PPEs in this study was nearly two-fold when compared to the study findings in Myanmar, where 37.6% of the staff have PPEs [ 12 ].

The mean availability of masks, heavy-duty gloves, boots, and aprons was 71.1%, 65.4%, 38%, and 44.4% in the study health facilities. This finding shows masks are less available in the study health facilities compared to other studies. The availability of utility gloves, boots, and plastic aprons is good in this study compared to the study conducted by Banstola, D in Pokhara Sub-Metropolitan City [ 23 ].

The findings of this study show there is a poor segregation practice, and all kinds of solid wastes were collected together. This finding was similar to the study findings conducted in Addis Ababa, Ethiopia, by Debere et al. [ 24 ] and contrary to the study findings conducted in Nepal and India, which shows 50% and 65–75% of the surveyed health facilities were practising proper waste segregation systems at the point of generation without mixing general wastes with hazardous wastes respectively [ 9 , 17 ].

Ninety percent of private health facilities collect and transport SHCW generated in every service area and transport it to the disposal place by the collection container (no separate container to collect and transport the waste to the final disposal site). This finding was similar to the study findings of Debre Markos’s town [ 25 ]. At all of the facilities in the study area, SHCW was transported from the service areas to the disposal site manually by carrying the collection container, and there was no trolley for transportation. This finding was contrary to the study findings conducted in India, which show segregated waste from the generation site was being transported through the chute to the carts placed at various points on the hospital premises by skilled sanitary workers [ 17 ].

Observational findings revealed that pre-treatment of SHCW before disposal was not practised at all study health facilities. This study was contrary to the findings of Pullishery et al. [ 26 ], conducted in Mangalore, India, which depicted pre-treatment of the waste in 46% of the hospitals [ 26 ]. 95% of the facilities have no water supply for handwashing during and after solid healthcare waste generation, collection, and disposal. This finding was contrary to the study findings in Pakistan hospitals, which show all health facilities have an adequate water supply near the health care waste management sites [ 27 ].

Questionnaire data collection tools show that 129 (23.8%) of the staff needle stick injuries have occurred on health facility workers within one year of the period before the data collection. This finding was slightly smaller than the study findings of Deress et al. [ 25 ] in Debre Markos town, North East Ethiopia, where 30.9% of the workers had been exposed to needle stick injury one year prior to the study [ 25 ]. Reported and registered needle stick injuries in health facilities are less reported, and only 70 (54.2%) of the injuries are reported to the health facilities. This finding shows an underestimation of the risk and the problem, which was supported by the study conducted in Menilik II hospitals in Addis Ababa [ 22 ]. 50%, 33.4%, 48%, 52%, and 62.5% of needle stick injuries were not reported in NEMMCSH, Government health centres, medium clinics, small clinics, and surgical centres, respectively, to the health facility manager.

Nearly 1/3 (177 or 32.7%) of the staff are exposed to needle stick injuries. Needle stick injuries in health facilities are less reported, and only 73 (41.24%) of the injuries are reported to the health facilities within 12 months of the data collection. This finding is slightly higher than the study finding of Deress et al. [ 25 ] in Debere Markos, Ethiopia, in which 23.3% of the study participants had encountered needle stick/sharps injuries preceding 12 months of the data collection period [ 25 ].

Seventy-three injuries were reported to the health facility manager in the last one year, 44 of the injuries were reported by health professionals, and the rest were reported by supportive staff. These injuries were reported from 35(85.3%) health facilities; the remaining six have no report. These study findings were better than the findings of Khan et al. [ 21 ], in which one-third of the facilities had a reporting system for an incident, and almost the same percentage of the facilities had post-exposure procedures in both public and private sectors [ 21 ].

Within one year of the study period, 129 (23.88%) needle stick injuries occurred. However, needle stick injuries in health facilities are less reported, and only 70 (39.5%) of the injuries are reported to the health facilities. These findings were reasonable compared to the study findings of the southwest region of Cameroon, in which 50.9% (110/216) of all participants had at least one occupational exposure [ 28 , 29 ]. This result report shows a very high exposure to needle stick injury compared to the study findings in Brazil, which shows 6.1% of the research participants were injured [ 27 ].

The finding shows that 220 (40.8%) of the respondents were vaccinated to prevent themselves from health facility-acquired infection. One Hundred Fifty-six (70.9%) of the respondents are vaccinated in order to avoid themselves from Hep B infection. Fifty-nine (26%0.8) of the respondents were vaccinated to protect themselves from two diseases that are Hep B and COVID-19. This finding was nearly the same as the study findings of Deress et al. [ 7 ],in Ethiopia, 30.7% were vaccinated, and very low compared to the study findings of Qadir et al. [ 30 ] in Pakistan and Saha & Bhattacharjya India which is 66.67% and 66.17% respectively [ 25 , 30 , 31 ].

The incineration of solid healthcare waste technology has been accepted and adopted as an effective method in Ethiopia. These pollutants may have undesirable environmental impacts on human and animal health, such as liver failure and cancer [ 15 , 16 ]. All government health facilities use incineration to dispose of solid waste. 88.4% and 100% of the wastes are incinerated in WUNEMMCSH and government health centres, respectively. This finding contradicts the study findings in the United States of America and Malaysia, which are 49–60% and 59–60 are incinerated, respectively, and the rest are treated using other technologies [ 15 , 16 ].

All study health facilities used a brick or barrel type of incinerator. The incinerators found in the study health facilities need to meet the minimum standards of solid health care waste incineration practice. These findings were similar to the study findings of Nepal and Pakistan [ 32 ]. The health care waste treatment system in health facilities was found to be very unsystematic and unscientific, which cannot guarantee that there is no risk to the environment and public health, as well as safety for personnel involved in health care waste treatment. Most incinerators are not properly operated and maintained, resulting in poor performance.

All government health facilities use incineration to dispose of solid waste. All the generated sharp wastes are incinerated using brick or barrel incinerators, as shown in Fig.  1 above. This finding was consistent with the findings of Veilla and Samwel [ 33 ], who depicted that sharp waste generation is the same as sharps waste incinerated [ 33 ]. All brick incinerators were constructed without appropriate air inlets to facilitate combustion except in NEMMCSH, which is built at a 4-m height. These findings were similar to the findings of Tadese and Kumie at Addis Ababa [ 34 ].

Barrel and brick incinerators used in private clinic

Strengths and limitations

This is a mixed-method study; both qualitative and quantitative study design, data collection and analysis techniques were used to understand the problem better. The setting for this study was one town, which is found in the southern part of the country. It only represents some of the country’s health facilities, and it is difficult to generalize the findings to other hospitals and health centres. Another limitation of this study was that private drug stores and private pharmacies were not incorporated.

Conclusions

In the study, health facilities’ foot-operated solid waste dust bins are not available for healthcare workers and patients to dispose of the generated wastes. Health facility managers in government and private health institutions should pay more attention to the availability of colour-coded dust bins. Most containers are opened, and insects and rodents can access them anytime. Some of them are even closed (not foot-operated), leading to contamination of hands when trying to open them.

Healthcare waste management training is mandatory for appropriate healthcare waste disposal. Healthcare-associated exposure should be appropriately managed, and infection prevention and control training should be provided to all staff working in the health facilities.

Availability of data and materials

The authors declare that data for this work are available upon request to the first author.

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Acknowledgements

The authors are grateful to the health facility leaders and ethical committees of the hospitals for their permission. The authors acknowledge the cooperation of the health facility workers who participated in this study.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Dr. Yeshanew Ayele Tiruneh is a researcher of this study; the principal investigator does all the proposal preparation, methodology, data collection, result and discussion, and manuscript writing. Professor LM Modiba and Dr. SM Zuma are supervisors for this study. They participated in the topic selection and modification to the final manuscript preparation by commenting on and correcting the study. Finally, the three authors read and approved the final version of the manuscript and agreed to submit the manuscript for publication.

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Tiruneh, Y.A., Modiba, L.M. & Zuma, S.M. Solid health care waste management practice in Ethiopia, a convergent mixed method study. BMC Health Serv Res 24 , 985 (2024). https://doi.org/10.1186/s12913-024-11444-8

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Received : 05 March 2023

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DOI : https://doi.org/10.1186/s12913-024-11444-8

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