Identify
Explore
Discover
Discuss
Summarise
Describe
Last, format your objectives into a numbered list. This is because when you write your thesis or dissertation, you will at times need to make reference to a specific research objective; structuring your research objectives in a numbered list will provide a clear way of doing this.
To bring all this together, let’s compare the first research objective in the previous example with the above guidance:
Research Objective:
1. Develop finite element models using explicit dynamics to mimic mallet blows during cup/shell insertion, initially using simplified experimentally validated foam models to represent the acetabulum.
Checking Against Recommended Approach:
Q: Is it specific? A: Yes, it is clear what the student intends to do (produce a finite element model), why they intend to do it (mimic cup/shell blows) and their parameters have been well-defined ( using simplified experimentally validated foam models to represent the acetabulum ).
Q: Is it measurable? A: Yes, it is clear that the research objective will be achieved once the finite element model is complete.
Q: Is it achievable? A: Yes, provided the student has access to a computer lab, modelling software and laboratory data.
Q: Is it relevant? A: Yes, mimicking impacts to a cup/shell is fundamental to the overall aim of understanding how they deform when impacted upon.
Q: Is it timebound? A: Yes, it is possible to create a limited-scope finite element model in a relatively short time, especially if you already have experience in modelling.
Q: Does it start with a verb? A: Yes, it starts with ‘develop’, which makes the intent of the objective immediately clear.
Q: Is it a numbered list? A: Yes, it is the first research objective in a list of eight.
1. making your research aim too broad.
Having a research aim too broad becomes very difficult to achieve. Normally, this occurs when a student develops their research aim before they have a good understanding of what they want to research. Remember that at the end of your project and during your viva defence , you will have to prove that you have achieved your research aims; if they are too broad, this will be an almost impossible task. In the early stages of your research project, your priority should be to narrow your study to a specific area. A good way to do this is to take the time to study existing literature, question their current approaches, findings and limitations, and consider whether there are any recurring gaps that could be investigated .
Note: Achieving a set of aims does not necessarily mean proving or disproving a theory or hypothesis, even if your research aim was to, but having done enough work to provide a useful and original insight into the principles that underlie your research aim.
Be realistic about what you can achieve in the time you have available. It is natural to want to set ambitious research objectives that require sophisticated data collection and analysis, but only completing this with six months before the end of your PhD registration period is not a worthwhile trade-off.
Each research objective should have its own purpose and distinct measurable outcome. To this effect, a common mistake is to form research objectives which have large amounts of overlap. This makes it difficult to determine when an objective is truly complete, and also presents challenges in estimating the duration of objectives when creating your project timeline. It also makes it difficult to structure your thesis into unique chapters, making it more challenging for you to write and for your audience to read.
Fortunately, this oversight can be easily avoided by using SMART objectives.
Hopefully, you now have a good idea of how to create an effective set of aims and objectives for your research project, whether it be a thesis, dissertation or research paper. While it may be tempting to dive directly into your research, spending time on getting your aims and objectives right will give your research clear direction. This won’t only reduce the likelihood of problems arising later down the line, but will also lead to a more thorough and coherent research project.
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Formulating research aim and objectives in an appropriate manner is one of the most important aspects of your thesis. This is because research aim and objectives determine the scope, depth and the overall direction of the research. Research question is the central question of the study that has to be answered on the basis of research findings.
Research aim emphasizes what needs to be achieved within the scope of the research, by the end of the research process. Achievement of research aim provides answer to the research question.
Research objectives divide research aim into several parts and address each part separately. Research aim specifies WHAT needs to be studied and research objectives comprise a number of steps that address HOW research aim will be achieved.
As a rule of dumb, there would be one research aim and several research objectives. Achievement of each research objective will lead to the achievement of the research aim.
Consider the following as an example:
Research title: Effects of organizational culture on business profitability: a case study of Virgin Atlantic
Research aim: To assess the effects of Virgin Atlantic organizational culture on business profitability
Following research objectives would facilitate the achievement of this aim:
Figure below illustrates additional examples in formulating research aims and objectives:
Formulation of research question, aim and objectives
Common mistakes in the formulation of research aim relate to the following:
1. Choosing the topic too broadly . This is the most common mistake. For example, a research title of “an analysis of leadership practices” can be classified as too broad because the title fails to answer the following questions:
a) Which aspects of leadership practices? Leadership has many aspects such as employee motivation, ethical behaviour, strategic planning, change management etc. An attempt to cover all of these aspects of organizational leadership within a single research will result in an unfocused and poor work.
b) An analysis of leadership practices in which country? Leadership practices tend to be different in various countries due to cross-cultural differences, legislations and a range of other region-specific factors. Therefore, a study of leadership practices needs to be country-specific.
c) Analysis of leadership practices in which company or industry? Similar to the point above, analysis of leadership practices needs to take into account industry-specific and/or company-specific differences, and there is no way to conduct a leadership research that relates to all industries and organizations in an equal manner.
Accordingly, as an example “a study into the impacts of ethical behaviour of a leader on the level of employee motivation in US healthcare sector” would be a more appropriate title than simply “An analysis of leadership practices”.
2. Setting an unrealistic aim . Formulation of a research aim that involves in-depth interviews with Apple strategic level management by an undergraduate level student can be specified as a bit over-ambitious. This is because securing an interview with Apple CEO Tim Cook or members of Apple Board of Directors might not be easy. This is an extreme example of course, but you got the idea. Instead, you may aim to interview the manager of your local Apple store and adopt a more feasible strategy to get your dissertation completed.
3. Choosing research methods incompatible with the timeframe available . Conducting interviews with 20 sample group members and collecting primary data through 2 focus groups when only three months left until submission of your dissertation can be very difficult, if not impossible. Accordingly, timeframe available need to be taken into account when formulating research aims and objectives and selecting research methods.
Moreover, research objectives need to be formulated according to SMART principle,
where the abbreviation stands for specific, measurable, achievable, realistic, and time-bound.
Study employee motivation of Coca-Cola | To study the impacts of management practices on the levels of employee motivation at Coca-Cola US by December 5, 2022
|
Analyze consumer behaviour in catering industry
| Analyzing changes in consumer behaviour in catering industry in the 21 century in the UK by March 1, 2022 |
Recommend Toyota Motor Corporation management on new market entry strategy
| Formulating recommendations to Toyota Motor Corporation management on the choice of appropriate strategy to enter Vietnam market by June 9, 2022
|
Analyze the impact of social media marketing on business
| Assessing impacts of integration of social media into marketing strategy on the level of brand awareness by March 30, 2022
|
Finding out about time management principles used by Accenture managers | Identifying main time-management strategies used by managers of Accenture France by December 1, 2022 |
Examples of SMART research objectives
At the conclusion part of your research project you will need to reflect on the level of achievement of research aims and objectives. In case your research aims and objectives are not fully achieved by the end of the study, you will need to discuss the reasons. These may include initial inappropriate formulation of research aims and objectives, effects of other variables that were not considered at the beginning of the research or changes in some circumstances during the research process.
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Research objectives refer to the definitive statements made by researchers at the beginning of a research project detailing exactly what a research project aims to achieve.
These objectives are explicit goals clearly and concisely projected by the researcher to present a clear intention or course of action for his or her qualitative or quantitative study.
Research objectives are typically nested under one overarching research aim. The objectives are the steps you’ll need to take in order to achieve the aim (see the examples below, for example, which demonstrate an aim followed by 3 objectives, which is what I recommend to my research students).
Research aim and research objectives are fundamental constituents of any study, fitting together like two pieces of the same puzzle.
The ‘research aim’ describes the overarching goal or purpose of the study (Kumar, 2019). This is usually a broad, high-level purpose statement, summing up the central question that the research intends to answer.
Example of an Overarching Research Aim:
“The aim of this study is to explore the impact of climate change on crop productivity.”
Comparatively, ‘research objectives’ are concrete goals that underpin the research aim, providing stepwise actions to achieve the aim.
Objectives break the primary aim into manageable, focused pieces, and are usually characterized as being more specific, measurable, achievable, relevant, and time-bound (SMART).
Examples of Specific Research Objectives:
1. “To examine the effects of rising temperatures on the yield of rice crops during the upcoming growth season.” 2. “To assess changes in rainfall patterns in major agricultural regions over the first decade of the twenty-first century (2000-2010).” 3. “To analyze the impact of changing weather patterns on crop diseases within the same timeframe.”
The distinction between these two terms, though subtle, is significant for successfully conducting a study. The research aim provides the study with direction, while the research objectives set the path to achieving this aim, thereby ensuring the study’s efficiency and effectiveness.
I usually recommend to my students that they use the SMART framework to create their research objectives.
SMART is an acronym standing for Specific, Measurable, Achievable, Relevant, and Time-bound. It provides a clear method of defining solid research objectives and helps students know where to start in writing their objectives (Locke & Latham, 2013).
Each element of this acronym adds a distinct dimension to the framework, aiding in the creation of comprehensive, well-delineated objectives.
Here is each step:
You’re not expected to fit every single element of the SMART framework in one objective, but across your objectives, try to touch on each of the five components.
1. Field: Psychology
Aim: To explore the impact of sleep deprivation on cognitive performance in college students.
2. Field: Environmental Science
Aim: To understand the effects of urban green spaces on human well-being in a metropolitan city.
3. Field: Technology
Aim: To investigate the influence of using social media on productivity in the workplace.
4. Field: Education
Aim: To examine the effectiveness of online vs traditional face-to-face learning on student engagement and achievement.
5. Field: Health
Aim: To determine the impact of a Mediterranean diet on cardiac health among adults over 50.
6. Field: Environmental Science
Aim: To analyze the impact of urban farming on community sustainability.
7. Field: Sociology
Aim: To investigate the influence of home offices on work-life balance during remote work.
8. Field: Economics
Aim: To evaluate the effects of minimum wage increases on small businesses.
9. Field: Education
Aim: To explore the role of extracurricular activities in promoting soft skills among high school students.
10. Field: Technology
Aim: To assess the impact of virtual reality (VR) technology on the tourism industry.
11. Field: Biochemistry
Aim: To examine the role of antioxidants in preventing cellular damage.
12. Field: Linguistics
Aim: To determine the influence of early exposure to multiple languages on cognitive development in children.
13. Field: Art History
Aim: To explore the impact of the Renaissance period on modern-day art trends.
14. Field: Cybersecurity
Aim: To assess the effectiveness of two-factor authentication (2FA) in preventing unauthorized system access.
15. Field: Cultural Studies
Aim: To analyze the role of music in cultural identity formation among ethnic minorities.
16. Field: Astronomy
Aim: To explore the impact of solar activity on satellite communication.
17. Field: Literature
Aim: To examine narrative techniques in contemporary graphic novels.
18. Field: Renewable Energy
Aim: To investigate the feasibility of solar energy as a primary renewable resource within urban areas.
19. Field: Sports Science
Aim: To evaluate the role of pre-game rituals in athlete performance.
20. Field: Ecology
Aim: To investigate the effects of urban noise pollution on bird populations.
21. Field: Food Science
Aim: To examine the influence of cooking methods on the nutritional value of vegetables.
The importance of research objectives cannot be overstated. In essence, these guideposts articulate what the researcher aims to discover, understand, or examine (Kothari, 2014).
When drafting research objectives, it’s essential to make them simple and comprehensible, specific to the point of being quantifiable where possible, achievable in a practical sense, relevant to the chosen research question, and time-constrained to ensure efficient progress (Kumar, 2019).
Remember that a good research objective is integral to the success of your project, offering a clear path forward for setting out a research design , and serving as the bedrock of your study plan. Each objective must distinctly address a different dimension of your research question or problem (Kothari, 2014). Always bear in mind that the ultimate purpose of your research objectives is to succinctly encapsulate your aims in the clearest way possible, facilitating a coherent, comprehensive and rational approach to your planned study, and furnishing a scientific roadmap for your journey into the depths of knowledge and research (Kumar, 2019).
Kothari, C.R (2014). Research Methodology: Methods and Techniques . New Delhi: New Age International.
Kumar, R. (2019). Research Methodology: A Step-by-Step Guide for Beginners .New York: SAGE Publications.
Doran, G. T. (1981). There’s a S.M.A.R.T. way to write management’s goals and objectives. Management review, 70 (11), 35-36.
Locke, E. A., & Latham, G. P. (2013). New Developments in Goal Setting and Task Performance . New York: Routledge.
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Patricia farrugia.
* Michael G. DeGroote School of Medicine, the
† Division of Orthopaedic Surgery and the
‡ Departments of Surgery and
§ Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, Ont
There is an increasing familiarity with the principles of evidence-based medicine in the surgical community. As surgeons become more aware of the hierarchy of evidence, grades of recommendations and the principles of critical appraisal, they develop an increasing familiarity with research design. Surgeons and clinicians are looking more and more to the literature and clinical trials to guide their practice; as such, it is becoming a responsibility of the clinical research community to attempt to answer questions that are not only well thought out but also clinically relevant. The development of the research question, including a supportive hypothesis and objectives, is a necessary key step in producing clinically relevant results to be used in evidence-based practice. A well-defined and specific research question is more likely to help guide us in making decisions about study design and population and subsequently what data will be collected and analyzed. 1
In this article, we discuss important considerations in the development of a research question and hypothesis and in defining objectives for research. By the end of this article, the reader will be able to appreciate the significance of constructing a good research question and developing hypotheses and research objectives for the successful design of a research study. The following article is divided into 3 sections: research question, research hypothesis and research objectives.
Interest in a particular topic usually begins the research process, but it is the familiarity with the subject that helps define an appropriate research question for a study. 1 Questions then arise out of a perceived knowledge deficit within a subject area or field of study. 2 Indeed, Haynes suggests that it is important to know “where the boundary between current knowledge and ignorance lies.” 1 The challenge in developing an appropriate research question is in determining which clinical uncertainties could or should be studied and also rationalizing the need for their investigation.
Increasing one’s knowledge about the subject of interest can be accomplished in many ways. Appropriate methods include systematically searching the literature, in-depth interviews and focus groups with patients (and proxies) and interviews with experts in the field. In addition, awareness of current trends and technological advances can assist with the development of research questions. 2 It is imperative to understand what has been studied about a topic to date in order to further the knowledge that has been previously gathered on a topic. Indeed, some granting institutions (e.g., Canadian Institute for Health Research) encourage applicants to conduct a systematic review of the available evidence if a recent review does not already exist and preferably a pilot or feasibility study before applying for a grant for a full trial.
In-depth knowledge about a subject may generate a number of questions. It then becomes necessary to ask whether these questions can be answered through one study or if more than one study needed. 1 Additional research questions can be developed, but several basic principles should be taken into consideration. 1 All questions, primary and secondary, should be developed at the beginning and planning stages of a study. Any additional questions should never compromise the primary question because it is the primary research question that forms the basis of the hypothesis and study objectives. It must be kept in mind that within the scope of one study, the presence of a number of research questions will affect and potentially increase the complexity of both the study design and subsequent statistical analyses, not to mention the actual feasibility of answering every question. 1 A sensible strategy is to establish a single primary research question around which to focus the study plan. 3 In a study, the primary research question should be clearly stated at the end of the introduction of the grant proposal, and it usually specifies the population to be studied, the intervention to be implemented and other circumstantial factors. 4
Hulley and colleagues 2 have suggested the use of the FINER criteria in the development of a good research question ( Box 1 ). The FINER criteria highlight useful points that may increase the chances of developing a successful research project. A good research question should specify the population of interest, be of interest to the scientific community and potentially to the public, have clinical relevance and further current knowledge in the field (and of course be compliant with the standards of ethical boards and national research standards).
Feasible | ||
Interesting | ||
Novel | ||
Ethical | ||
Relevant |
Adapted with permission from Wolters Kluwer Health. 2
Whereas the FINER criteria outline the important aspects of the question in general, a useful format to use in the development of a specific research question is the PICO format — consider the population (P) of interest, the intervention (I) being studied, the comparison (C) group (or to what is the intervention being compared) and the outcome of interest (O). 3 , 5 , 6 Often timing (T) is added to PICO ( Box 2 ) — that is, “Over what time frame will the study take place?” 1 The PICOT approach helps generate a question that aids in constructing the framework of the study and subsequently in protocol development by alluding to the inclusion and exclusion criteria and identifying the groups of patients to be included. Knowing the specific population of interest, intervention (and comparator) and outcome of interest may also help the researcher identify an appropriate outcome measurement tool. 7 The more defined the population of interest, and thus the more stringent the inclusion and exclusion criteria, the greater the effect on the interpretation and subsequent applicability and generalizability of the research findings. 1 , 2 A restricted study population (and exclusion criteria) may limit bias and increase the internal validity of the study; however, this approach will limit external validity of the study and, thus, the generalizability of the findings to the practical clinical setting. Conversely, a broadly defined study population and inclusion criteria may be representative of practical clinical practice but may increase bias and reduce the internal validity of the study.
Population (patients) | ||
Intervention (for intervention studies only) | ||
Comparison group | ||
Outcome of interest | ||
Time |
A poorly devised research question may affect the choice of study design, potentially lead to futile situations and, thus, hamper the chance of determining anything of clinical significance, which will then affect the potential for publication. Without devoting appropriate resources to developing the research question, the quality of the study and subsequent results may be compromised. During the initial stages of any research study, it is therefore imperative to formulate a research question that is both clinically relevant and answerable.
The primary research question should be driven by the hypothesis rather than the data. 1 , 2 That is, the research question and hypothesis should be developed before the start of the study. This sounds intuitive; however, if we take, for example, a database of information, it is potentially possible to perform multiple statistical comparisons of groups within the database to find a statistically significant association. This could then lead one to work backward from the data and develop the “question.” This is counterintuitive to the process because the question is asked specifically to then find the answer, thus collecting data along the way (i.e., in a prospective manner). Multiple statistical testing of associations from data previously collected could potentially lead to spuriously positive findings of association through chance alone. 2 Therefore, a good hypothesis must be based on a good research question at the start of a trial and, indeed, drive data collection for the study.
The research or clinical hypothesis is developed from the research question and then the main elements of the study — sampling strategy, intervention (if applicable), comparison and outcome variables — are summarized in a form that establishes the basis for testing, statistical and ultimately clinical significance. 3 For example, in a research study comparing computer-assisted acetabular component insertion versus freehand acetabular component placement in patients in need of total hip arthroplasty, the experimental group would be computer-assisted insertion and the control/conventional group would be free-hand placement. The investigative team would first state a research hypothesis. This could be expressed as a single outcome (e.g., computer-assisted acetabular component placement leads to improved functional outcome) or potentially as a complex/composite outcome; that is, more than one outcome (e.g., computer-assisted acetabular component placement leads to both improved radiographic cup placement and improved functional outcome).
However, when formally testing statistical significance, the hypothesis should be stated as a “null” hypothesis. 2 The purpose of hypothesis testing is to make an inference about the population of interest on the basis of a random sample taken from that population. The null hypothesis for the preceding research hypothesis then would be that there is no difference in mean functional outcome between the computer-assisted insertion and free-hand placement techniques. After forming the null hypothesis, the researchers would form an alternate hypothesis stating the nature of the difference, if it should appear. The alternate hypothesis would be that there is a difference in mean functional outcome between these techniques. At the end of the study, the null hypothesis is then tested statistically. If the findings of the study are not statistically significant (i.e., there is no difference in functional outcome between the groups in a statistical sense), we cannot reject the null hypothesis, whereas if the findings were significant, we can reject the null hypothesis and accept the alternate hypothesis (i.e., there is a difference in mean functional outcome between the study groups), errors in testing notwithstanding. In other words, hypothesis testing confirms or refutes the statement that the observed findings did not occur by chance alone but rather occurred because there was a true difference in outcomes between these surgical procedures. The concept of statistical hypothesis testing is complex, and the details are beyond the scope of this article.
Another important concept inherent in hypothesis testing is whether the hypotheses will be 1-sided or 2-sided. A 2-sided hypothesis states that there is a difference between the experimental group and the control group, but it does not specify in advance the expected direction of the difference. For example, we asked whether there is there an improvement in outcomes with computer-assisted surgery or whether the outcomes worse with computer-assisted surgery. We presented a 2-sided test in the above example because we did not specify the direction of the difference. A 1-sided hypothesis states a specific direction (e.g., there is an improvement in outcomes with computer-assisted surgery). A 2-sided hypothesis should be used unless there is a good justification for using a 1-sided hypothesis. As Bland and Atlman 8 stated, “One-sided hypothesis testing should never be used as a device to make a conventionally nonsignificant difference significant.”
The research hypothesis should be stated at the beginning of the study to guide the objectives for research. Whereas the investigators may state the hypothesis as being 1-sided (there is an improvement with treatment), the study and investigators must adhere to the concept of clinical equipoise. According to this principle, a clinical (or surgical) trial is ethical only if the expert community is uncertain about the relative therapeutic merits of the experimental and control groups being evaluated. 9 It means there must exist an honest and professional disagreement among expert clinicians about the preferred treatment. 9
Designing a research hypothesis is supported by a good research question and will influence the type of research design for the study. Acting on the principles of appropriate hypothesis development, the study can then confidently proceed to the development of the research objective.
The primary objective should be coupled with the hypothesis of the study. Study objectives define the specific aims of the study and should be clearly stated in the introduction of the research protocol. 7 From our previous example and using the investigative hypothesis that there is a difference in functional outcomes between computer-assisted acetabular component placement and free-hand placement, the primary objective can be stated as follows: this study will compare the functional outcomes of computer-assisted acetabular component insertion versus free-hand placement in patients undergoing total hip arthroplasty. Note that the study objective is an active statement about how the study is going to answer the specific research question. Objectives can (and often do) state exactly which outcome measures are going to be used within their statements. They are important because they not only help guide the development of the protocol and design of study but also play a role in sample size calculations and determining the power of the study. 7 These concepts will be discussed in other articles in this series.
From the surgeon’s point of view, it is important for the study objectives to be focused on outcomes that are important to patients and clinically relevant. For example, the most methodologically sound randomized controlled trial comparing 2 techniques of distal radial fixation would have little or no clinical impact if the primary objective was to determine the effect of treatment A as compared to treatment B on intraoperative fluoroscopy time. However, if the objective was to determine the effect of treatment A as compared to treatment B on patient functional outcome at 1 year, this would have a much more significant impact on clinical decision-making. Second, more meaningful surgeon–patient discussions could ensue, incorporating patient values and preferences with the results from this study. 6 , 7 It is the precise objective and what the investigator is trying to measure that is of clinical relevance in the practical setting.
The following is an example from the literature about the relation between the research question, hypothesis and study objectives:
Study: Warden SJ, Metcalf BR, Kiss ZS, et al. Low-intensity pulsed ultrasound for chronic patellar tendinopathy: a randomized, double-blind, placebo-controlled trial. Rheumatology 2008;47:467–71.
Research question: How does low-intensity pulsed ultrasound (LIPUS) compare with a placebo device in managing the symptoms of skeletally mature patients with patellar tendinopathy?
Research hypothesis: Pain levels are reduced in patients who receive daily active-LIPUS (treatment) for 12 weeks compared with individuals who receive inactive-LIPUS (placebo).
Objective: To investigate the clinical efficacy of LIPUS in the management of patellar tendinopathy symptoms.
The development of the research question is the most important aspect of a research project. A research project can fail if the objectives and hypothesis are poorly focused and underdeveloped. Useful tips for surgical researchers are provided in Box 3 . Designing and developing an appropriate and relevant research question, hypothesis and objectives can be a difficult task. The critical appraisal of the research question used in a study is vital to the application of the findings to clinical practice. Focusing resources, time and dedication to these 3 very important tasks will help to guide a successful research project, influence interpretation of the results and affect future publication efforts.
FINER = feasible, interesting, novel, ethical, relevant; PICOT = population (patients), intervention (for intervention studies only), comparison group, outcome of interest, time.
Competing interests: No funding was received in preparation of this paper. Dr. Bhandari was funded, in part, by a Canada Research Chair, McMaster University.
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Research in social science requires the collection of data in order to understand a phenomenon. This can be done in a number of ways, and will depend on the state of existing knowledge of the topic area. The researcher can:
Exploratory research is often done through observation and other methods such as interviews or surveys that allow the researcher to gather preliminary information.
Explanatory research, on the other hand, generally tests hypotheses about cause and effect relationships. Hypotheses are statements developed by the researcher that will be tested during the research. The distinction between exploratory and explanatory research is linked to the distinction between inductive and deductive research. Explanatory research tends to be deductive and exploratory research tends to be inductive. This is not always the case but, for simplicity, we shall not explore the exceptions here.
Descriptive research may support an explanatory or exploratory study. On its own, descriptive research is not sufficient for an academic project. Academic research is aimed at progressing current knowledge.
The perspective taken by the researcher also depends on whether the researcher believes that there is an objective world out there that can be objectively known; for example, profit can be viewed as an objective measure of business performance. Alternatively the researcher may believe that concepts such as ‘culture’, ‘motivation’, ‘leadership’, ‘performance’ result from human categorisation of the world and that their ‘meaning’ can change depending on the circumstances. For example, performance can mean different things to different people. For one it may refer to a hard measure such as levels of sales. For another it may include good relationships with customers. According to this latter view, a researcher can only take a subjective perspective because the nature of these concepts is the result of human processes. Subjective research generally refers to the subjective experiences of research participants and to the fact that the researcher’s perspective is embedded within the research process, rather than seen as fully detached from it.
On the other hand, objective research claims to describe a true and correct reality, which is independent of those involved in the research process. Although this is a simplified view of the way in which research can be approached, it is an important distinction to think about. Whether you think about your research topic in objective or subjective terms will determine the development of the research questions, the type of data collected, the methods of data collection and analysis you adopt and the conclusions that you draw. This is why it is important to consider your own perspective when planning your project.
Subjective research is generally referred to as phenomenological research. This is because it is concerned with the study of experiences from the perspective of an individual, and emphasises the importance of personal perspectives and interpretations. Subjective research is generally based on data derived from observations of events as they take place or from unstructured or semi-structured interviews. In unstructured interviews the questions emerged from the discussion between the interviewer and the interviewee. In semi-structured interviews the interviewer prepares an outline of the interview topics or general questions, adding more as needs emerged during the interview. Structured interviews include the full list of questions. Interviewers do not deviate from this list. Subjective research can also be based on examinations of documents. The researcher will attribute personal interpretations of the experiences and phenomena during the process of both collecting and analysing data. This approach is also referred to as interpretivist research. Interpretivists believe that in order to understand and explain specific management and HR situations, one needs to focus on the viewpoints, experiences, feelings and interpretations of the people involved in the specific situation.
Conversely, objective research tends to be modelled on the methods of the natural sciences such as experiments or large scale surveys. Objective research seeks to establish law-like generalisations which can be applied to the same phenomenon in different contexts. This perspective, which privileges objectivity, is called positivism and is based on data that can be subject to statistical analysis and generalisation. Positivist researchers use quantitative methodologies, which are based on measurement and numbers, to collect and analyse data. Interpretivists are more concerned with language and other forms of qualitative data, which are based on words or images. Having said that, researchers using objectivist and positivist assumptions sometimes use qualitative data while interpretivists sometimes use quantitative data. (Quantitative and qualitative methodologies will be discussed in more detail in the final part of this course.) The key is to understand the perspective you intend to adopt and realise the limitations and opportunities it offers. Table 1 compares and contrasts the perspectives of positivism and interpretivism.
Positivism (objective) | Interpretivism (subjective) |
---|---|
Regards the world as objectively ‘out there’, real and completely separate from human meaning-making. | Claims that the only world we can study is a world of meanings, represented in the signs and symbols that people use to think and to communicate. |
Asserts there is only one true, objective knowledge that transcends time and cultural location. | Accepts that there are multiple knowledges, and that knowledge is highly contingent on time and cultural location. |
Views knowledge as based on facts that are ‘out there in the world’ waiting to be discovered. | Views knowledge as constructed through people’s meaning-making. |
Asks of knowledge: | Asks of knowledge: |
Some textbooks include the realist perspective or discuss constructivism, but, for the purpose of your work-based project, you do not need to engage with these other perspectives. This course keeps the discussion of research perspectives to a basic level.
Search and identify two articles that are based on your research topic. Ideally you may want to identify one article based on quantitative and one based on qualitative methodologies.
Now answer the following questions:
This activity has helped you to distinguish between objective and subjective research by recognising the type of language and the different ways in which objectivists/positivists and subjectivists/interpretivists may formulate their research aims. It should also support the development of your personal preference on objective or subjective research.
Imagine you’re a student planning a vacation in a foreign country. You’re on a tight budget and need to draw…
Imagine you’re a student planning a vacation in a foreign country. You’re on a tight budget and need to draw up a pocket-friendly plan. Where do you begin? The first step is to do your research.
Before that, you make a mental list of your objectives—finding reasonably-priced hotels, traveling safely and finding ways of communicating with someone back home. These objectives help you focus sharply during your research and be aware of the finer details of your trip.
More often than not, research is a part of our daily lives. Whether it’s to pick a restaurant for your next birthday dinner or to prepare a presentation at work, good research is the foundation of effective learning. Read on to understand the meaning, importance and examples of research objectives.
What are the objectives of research, what goes into a research plan.
Research is a careful and detailed study of a particular problem or concern, using scientific methods. An in-depth analysis of information creates space for generating new questions, concepts and understandings. The main objective of research is to explore the unknown and unlock new possibilities. It’s an essential component of success.
Over the years, businesses have started emphasizing the need for research. You’ve probably noticed organizations hiring research managers and analysts. The primary purpose of business research is to determine the goals and opportunities of an organization. It’s critical in making business decisions and appropriately allocating available resources.
Here are a few benefits of research that’ll explain why it is a vital aspect of our professional lives:
One of the greatest benefits of research is to learn and gain a deeper understanding. The deeper you dig into a topic, the more well-versed you are. Furthermore, research has the power to help you build on any personal experience you have on the subject.
Research encourages you to discover the most recent information available. Updated information prevents you from falling behind and helps you present accurate information. You’re better equipped to develop ideas or talk about a topic when you’re armed with the latest inputs.
Research provides you with a good foundation upon which you can develop your thoughts and ideas. People take you more seriously when your suggestions are backed by research. You can speak with greater confidence because you know that the information is accurate.
Take any leading nonprofit organization, you’ll see how they have a strong research arm supported by real-life stories. Research also becomes the base upon which real-life connections and impact can be made. It even helps you communicate better with others and conveys why you’re pursuing something.
As we’ve already established, research is mostly about using existing information to create new ideas and opinions. In the process, it sparks curiosity as you’re encouraged to explore and gain deeper insights into a subject. Curiosity leads to higher levels of positivity and lower levels of anxiety.
Well-defined objectives of research are an essential component of successful research engagement. If you want to drive all aspects of your research methodology such as data collection, design, analysis and recommendation, you need to lay down the objectives of research methodology. In other words, the objectives of research should address the underlying purpose of investigation and analysis. It should outline the steps you’d take to achieve desirable outcomes. Research objectives help you stay focused and adjust your expectations as you progress.
The objectives of research should be closely related to the problem statement, giving way to specific and achievable goals. Here are the four types of research objectives for you to explore:
Also known as secondary objectives, general objectives provide a detailed view of the aim of a study. In other words, you get a general overview of what you want to achieve by the end of your study. For example, if you want to study an organization’s contribution to environmental sustainability, your general objective could be: a study of sustainable practices and the use of renewable energy by the organization.
Specific objectives define the primary aim of the study. Typically, general objectives provide the foundation for identifying specific objectives. In other words, when general objectives are broken down into smaller and logically connected objectives, they’re known as specific objectives. They help define the who, what, why, when and how aspects of your project. Once you identify the main objective of research, it’s easier to develop and pursue a plan of action.
Let’s take the example of ‘a study of an organization’s contribution to environmental sustainability’ again. The specific objectives will look like this:
To determine through history how the organization has changed its practices and adopted new solutions
To assess how the new practices, technology and strategies will contribute to the overall effectiveness
Once you’ve identified the objectives of research, it’s time to organize your thoughts and streamline your research goals. Here are a few effective tips to develop a powerful research plan and improve your business performance.
Your research objectives should be SMART—Specific, Measurable, Achievable, Realistic and Time-constrained. When you focus on utilizing available resources and setting realistic timeframes and milestones, it’s easier to prioritize objectives. Continuously track your progress and check whether you need to revise your expectations or targets. This way, you’re in greater control over the process.
Create a plan that’ll help you select appropriate methods to collect accurate information. A well-structured plan allows you to use logical and creative approaches towards problem-solving. The complexity of information and your skills are bound to influence your plan, which is why you need to make room for flexibility. The availability of resources will also play a big role in influencing your decisions.
After you’ve created a plan for the research process, make a list of the data you’re going to collect and the methods you’ll use. Not only will it help make sense of your insights but also keep track of your approach. The information you collect should be:
Logical, rigorous and objective
Can be reproduced by other people working on the same subject
Free of errors and highlighting necessary details
Current and updated
Includes everything required to support your argument/suggestions
Data analysis is the most crucial part of the process and there are many ways in which the information can be utilized. Four types of data analysis are often seen in a professional environment. While they may be divided into separate categories, they’re linked to each other.
The most commonly used data analysis, descriptive analysis simply summarizes past data. For example, Key Performance Indicators (KPIs) use descriptive analysis. It establishes certain benchmarks after studying how someone has been performing in the past.
The next step is to identify why something happened. Diagnostic analysis uses the information gathered through descriptive analysis and helps find the underlying causes of an outcome. For example, if a marketing initiative was successful, you deep-dive into the strategies that worked.
It attempts to answer ‘what’s likely to happen’. Predictive analysis makes use of past data to predict future outcomes. However, the accuracy of predictions depends on the quality of the data provided. Risk assessment is an ideal example of using predictive analysis.
The most sought-after type of data analysis, prescriptive analysis combines the insights of all of the previous analyses. It’s a huge organizational commitment as it requires plenty of effort and resources. A great example of prescriptive analysis is Artificial Intelligence (AI), which consumes large amounts of data. You need to be prepared to commit to this type of analysis.
Once you’ve collected and collated your data, it’s time to review it and draw accurate conclusions. Here are a few ways to improve the review process:
Identify the fundamental issues, opportunities and problems and make note of recurring trends if any
Make a list of your insights and check which is the most or the least common. In short, keep track of the frequency of each insight
Conduct a SWOT analysis and identify the strengths, weaknesses, opportunities and threats
Write down your conclusions and recommendations of the research
When we think about research, we often associate it with academicians and students. but the truth is research is for everybody who is willing to learn and enhance their knowledge. If you want to master the art of strategically upgrading your knowledge, Harappa Education’s Learning Expertly course has all the answers. Not only will it help you look at things from a fresh perspective but also show you how to acquire new information with greater efficiency. The Growth Mindset framework will teach you how to believe in your abilities to grow and improve. The Learning Transfer framework will help you apply your learnings from one context to another. Begin the journey of tactful learning and self-improvement today!
Explore Harappa Diaries to learn more about topics related to the THINK Habit such as Learning From Experience , Critical Thinking & What is Brainstorming to think clearly and rationally.
Published on 26.8.2024 in Vol 26 (2024)
Authors of this article:
1 Institute of Molecular Immunology, Klinikum Rechts der Isar, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
2 Institute of History and Ethics in Medicine, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
3 Department of Science, Technology and Society (STS), School of Social Sciences and Technology, Technical University of Munich, Munich, Germany
4 Institute of Philosophy, Multidisciplinary Center for Infectious Diseases, University of Bern, Bern, Switzerland
5 Institute for Biomedical Ethics, University of Basel, Basel, Switzerland
*these authors contributed equally
Bettina M Zimmermann, PhD
Institute of History and Ethics in Medicine
TUM School of Medicine and Health
Technical University of Munich
Ismaninger Str. 22
Munich, 81675
Phone: 49 89 4140 4041
Email: [email protected]
Background: Social media platforms are increasingly used to recruit patients for clinical studies. Yet, patients’ attitudes regarding social media recruitment are underexplored.
Objective: This mixed methods study aims to assess predictors of the acceptance of social media recruitment among patients with hepatitis B, a patient population that is considered particularly vulnerable in this context.
Methods: Using a mixed methods approach, the hypotheses for our survey were developed based on a qualitative interview study with 6 patients with hepatitis B and 30 multidisciplinary experts. Thematic analysis was applied to qualitative interview analysis. For the cross-sectional survey, we additionally recruited 195 patients with hepatitis B from 3 clinical centers in Germany. Adult patients capable of judgment with a hepatitis B diagnosis who understood German and visited 1 of the 3 study centers during the data collection period were eligible to participate. Data analysis was conducted using SPSS (version 28; IBM Corp), including descriptive statistics and regression analysis.
Results: On the basis of the qualitative interview analysis, we hypothesized that 6 factors were associated with acceptance of social media recruitment: using social media in the context of hepatitis B (hypothesis 1), digital literacy (hypothesis 2), interest in clinical studies (hypothesis 3), trust in nonmedical (hypothesis 4a) and medical (hypothesis 4b) information sources, perceiving the hepatitis B diagnosis as a secret (hypothesis 5a), attitudes toward data privacy in the social media context (hypothesis 5b), and perceived stigma (hypothesis 6). Regression analysis revealed that the higher the social media use for hepatitis B (hypothesis 1), the higher the interest in clinical studies (hypothesis 3), the more trust in nonmedical information sources (hypothesis 4a), and the less secrecy around a hepatitis B diagnosis (hypothesis 5a), the higher the acceptance of social media as a recruitment tool for clinical hepatitis B studies.
Conclusions: This mixed methods study provides the first quantitative insights into social media acceptance for clinical study recruitment among patients with hepatitis B. The study was limited to patients with hepatitis B in Germany but sets out to be a reference point for future studies assessing the attitudes toward and acceptance of social media recruitment for clinical studies. Such empirical inquiries can facilitate the work of researchers designing clinical studies as well as ethics review boards in balancing the risks and benefits of social media recruitment in a context-specific manner.
Benefits and risks of using social media recruitment for clinical studies.
Recruiting clinical study participants through social media has the potential to increase the recruitment accrual in a cost-effective way [ 1 ]. Consequently, social media recruitment has been increasingly applied for clinical studies, often in parallel with other recruitment strategies. However, social media recruitment still bears a host of challenges. First, maintaining a social media presence and community management can be resource intensive. Second, when used as a stand-alone recruiting method, it might yield a cohort of limited demographic representativeness. Finally, social media recruitment comes with ethical issues, particularly when used to recruit for clinical studies [ 2 ]. Because social media recruitment includes reaching potential research participants outside a clinical setting and in a public online space without direct personal contact, risks related to social stigma, privacy infringement, loss of trust, and psychological harm have been discussed [ 3 ]. To mitigate some of these risks, prioritizing investigator transparency and obtaining explicit consent when recruiting from others’ social network was suggested [ 4 ]. Yet, because the activities of social media platforms are primarily unregulated and partly belong to large global technology companies, activities conducted on social media, including study recruitment, can never be fully controlled by researchers or institutions. Remaining privacy-infringing risks include hidden data collection and profiling, particularly problematic for patients carrying vulnerable characteristics [ 5 ].
Early studies assessing social media recruitment for clinical studies focused on the effectiveness of the method. For example, Frandsen et al [ 3 ] used social media recruitment for a smoking cessation trial and compared their cohort recruited from a Facebook-based approach to cohorts resulting from other recruitment methods. They found no differences between the cohorts regarding socioeconomic or smoking characteristics, except that participants recruited via Facebook were significantly younger. Wisk et al [ 4 ] recruited college students with type 1 diabetes, a hard-to-reach population, using a variety of outreach channels, including social media. They found that Facebook was the most successful recruitment method. Guthrie et al [ 5 ] found that Facebook advertising was significantly cheaper than recruiting via mail. While these studies allow insights into the utility of social media recruitment from the perspective of researchers, studies assessing patients’ perspectives and attitudes toward social media for clinical study recruitment are lacking. This study aims to deliver first evidence on patient attitudes toward social media recruitment, focusing on patients with hepatitis B.
Patients with hepatitis B are a particularly interesting cohort to study acceptance for social media recruitment as the particularities of the disease exhibit potentially confounding factors for their attitudes toward social media recruitment. First, there is robust empirical evidence that patients with hepatitis B can be subject to social stigma [ 6 - 10 ]. Therefore, the risk of public exposure to hepatitis B diagnosis on social media renders them—and patients with other stigmatized traits and conditions—particularly vulnerable in the context of social media recruitment [ 11 ]. Second, hepatitis B in Europe is particularly prevalent in certain immigrant populations, which are at risk of being neglected for clinical studies due to language barriers and lack of health care access. Social media recruitment can help include patient populations who otherwise would be disregarded for clinical studies or are hard to reach [ 12 - 14 ].
However, the effectiveness of social media recruitment crucially hinges on technology acceptance. To date, the attitudes of patients regarding social media recruitment are underexplored. Addressing this gap, this mixed methods study assesses factors predicting the acceptance of social media recruitment among patients with hepatitis B. On the basis of qualitative individual interviews with 6 patients with hepatitis B and 30 multidisciplinary experts and a literature review, we hypothesized that general social media use (hypothesis 1), social media literacy (hypothesis 2), interest in clinical studies (hypothesis 3), trust (hypothesis 4), privacy needs (hypothesis 5), and perceived stigma (hypothesis 6) are associated with acceptance of social media recruitment.
This study is part of the European Union–funded international research consortium “TherVacB—A Therapeutic Vaccine to Cure Hepatitis B,” work package 6 (ethical, legal, and social aspects of social media recruitment). Using a mixed methods design, we first conducted an explorative qualitative multistakeholder interview study assessing the ethical, legal, social, and practical implications of social media recruitment for clinical studies [ 2 ]. The hypotheses investigated in this paper are based on these interviews and a conceptual literature review mapping the ethical implications of social media recruitment [ 11 ]. The reporting of this study followed the Strengthening the Reporting of Observational Studies in Epidemiology guidelines [ 15 ].
On the basis of preliminary statistical power analysis and pragmatic considerations of available study participants, we aimed for 200 responses in a recruitment period of 7 months. Due to administrative constraints, including the COVID-19 pandemic, the overall recruitment period was prolonged by 5 months (total recruitment period 12 months, June 4, 2022, to May 31, 2023), and the recruitment period varied among the recruiting clinics ( Multimedia Appendix 1 ).
Adult, German-speaking patients diagnosed with acute or chronic viral hepatitis B were recruited from 3 large university hospitals in Germany. We chose such a venue-based recruitment methodology because it is considered one of the best options to recruit representative samples from hard-to-reach populations [ 16 ]. The clinical staff was instructed to distribute the study information leaflet to every eligible patient in the study period, explaining the implications of the study and inviting them to fill out the questionnaire. To limit recruitment bias and enhance sample representativeness, study nurses were briefed to avoid self-selected restrictions in recruitment and, if possible, to give a questionnaire to every incoming patient with hepatitis B who understood German sufficiently well. However, because of the administrative burden of the clinical staff, only 30.4% (285/939) of the estimated eligible incoming patients received the questionnaire ( Multimedia Appendix 1 ). Because this low distribution number results from administrative burden in the clinic, we do not expect this to have a relevant impact on representativeness (refer to the Limitations subsection under the Discussion section). Completed questionnaires (207/285, 72.6% of the distributed questionnaires; Multimedia Appendix 1 ) were collected in the recruiting hospital and sent to the authors via mail.
The dependent variable (acceptance of social media recruitment) was constructed based on the Technology Acceptance Model [ 17 , 18 ], involving the dimensions of perceived usefulness; perceived ease of use, intentions, and problem awareness; and proved good internal consistency (Cronbach α=0.863). Possible predictors for social media recruitment acceptance were identified based on the abovementioned hypotheses and operationalized by, if possible, existing validated questionnaires. For 3 (33%) of the 9 independent variables, we used existing validated questionnaires that were found to be of excellent reliability: the social media literacy scale (14 items, Cronbach α=0.947) [ 19 ], the Berger HIV Stigma Scale for use among patients with hepatitis C virus (6 items, Cronbach α=0.931) [ 20 ], and the Privacy Attitude Questionnaire [ 21 ]. For the latter, we included a shortened version that covered the dimensions developed in the Privacy Attitude Questionnaire but targeted it toward the hepatitis B context. From these dimensions, 2 subscales were created: secrecy of hepatitis B diagnosis (2 items, Cronbach α=0.623) and data privacy needs regarding hepatitis B diagnosis (2 items, Cronbach α=0.587).
For the remaining variables, no validated tools existed. Hence, we developed new scales for each variable of interest. As indicated by internal consistency, these were of moderate, good, or excellent reliability: general social media use (8 items, Cronbach α=0.676), hepatitis B–related social media use (6 items, Cronbach α=0.906), interest in clinical studies (2 items, Cronbach α=0.895), and trust in information sources regarding hepatitis B (11 items, Cronbach α=0.905; 2 subscales were created: trust in medical information sources—4 items, Cronbach α=0.784 and trust in nonmedical information sources, ie, traditional media, social media, other patients, poster advertisements, etc—7 items, Cronbach α=0.881). In addition to these adapted and self-developed scales, we included 4 demographic variables in the regression model (age, gender, education, and mother tongue as an indicator of migration background). A preliminary version of the questionnaire was discussed with 3 experts from the fields of infectiology and bioethics and then adapted and shortened based on their comments. We then performed cognitive pretesting [ 22 ] with 6 patients with hepatitis B, leading to minor changes. The full questionnaire is provided in Multimedia Appendix 2 .
Using SPSS (version 28.0; IBM Corp), we (1) performed descriptive analyses, (2) determined independent factors associated with participants’ acceptance of social media as a recruitment tool for clinical hepatitis B studies through multiple linear regression analysis, and (3) performed additional exploratory bivariate analyses of hepatitis B–related stigma (ie, correlation, independent 2-tailed t test). The statistical significance level was set at P <.05. For multiple linear regression analysis, assumption checks were performed before the interpretation of the model ( Multimedia Appendix 3 ). For the scale measuring the frequency of social media use, missing values were replaced by “0” (ie, “never”), assuming that participants did not tick a box, as they did not know the respective social media platform. Overall, 71.3% (139/195) of the participants completed all items, resulting in 3.66% (478/13,065) missing values and 81% (54/67) incomplete variables.
For the linear regression analysis, theoretical considerations and hypotheses derived from our previous qualitative study determined predictor selection. In addition, the sample size or predictor ratio a priori determines variable selection for regression modeling. According to Harrell [ 23 ], a fitted regression model is likely to be reliable when p<m/10 or p<m/20 (average requirement: p<m/15), where p is the number of predictors and m is the sample size. Applying this requirement to our sample size (N=195) and having missing data, we preliminarily limited the number of included predictors to 11. The following 11 predictors were included in the regression model: general social media use, social media literacy, hepatitis B–related social media use, interest in clinical studies, trust in medical information sources regarding hepatitis B (dichotomized to meet assumption of linearity), trust in nonmedical information sources regarding hepatitis B, secrecy of hepatitis B (dichotomized to meet assumption of linearity), data privacy needs regarding hepatitis B (dichotomized to meet assumption of linearity), perceived stigma, age, and education. Assumptions checks for regression analyses are presented in Multimedia Appendix 3 .
For study consent, participants were asked to confirm having read and understood the study information and to consent to the study participation by checking a consent box at the beginning of the questionnaire. Only questionnaires with this box checked were included in the analysis (12/207, 5.8% of the questionnaires were excluded for that reason; Multimedia Appendix 1 ). The ethics committees from the Technical University of Munich (12/22-S-NP), Hannover Medical School (10368_BO_K_2022), and University Clinic Leipzig (189/22-lk) approved the study.
After conducting an in-depth literature review on the ethical and social challenges surrounding social media recruitment for clinical studies [ 11 ], we developed 2 semistructured interview guides, one targeted at patients with hepatitis B and the other targeted at multidisciplinary experts. On the basis of interviews with 6 patients that were triangulated with findings from 30 interviews with experts, we qualitatively assessed what factors could be associated with the acceptance of social media recruitment for clinical hepatitis B studies. On the basis of these findings, we derived hypotheses to be tested quantitatively in a survey among patients with hepatitis B in Germany ( Textbox 1 ).
Most of the patients we talked with were rejecting the idea of being recruited for a clinical hepatitis B study via social media. However, patients who were more actively involved in their own recruitment tended to have more accepting attitudes. For example, patients who described using social media as a tool for informing themselves about potential clinical studies related to their disease were less opposed to being recruited via the same channel. One patient included search engines in their definition of social media and mentioned the following:
You can also advertise on Google. That is quasi/I think it’s better if I [as a patient] search for a study. For example, I search for a study related to psoriasis and enter that term in Google—when the advertisement for a psoriasis study is then made so that it shows up as the first suggestion...I think that’s better because in these instances I’m already searching, so I take the first step, I search for the study. And then the study, or the advertisement must be done in such a way that I can find it. So, I take the first step and then I land on the study. [Patient 3]
Similarly, patients who joined shared interest groups, such as patient groups on Facebook, which gather people who deliberately want to share their own experiences with the disease and learn from others’ experiences, were more open toward the idea of being approached and recruited within such groups.
These insights indicate that patients who were already active on social media and found it useful for their personal disease management were more open to being recruited via social media. This led us to the following hypothesis: (H1) The more patients use social media (for hepatitis B), the higher their acceptance of using social media as a recruitment tool for clinical (hepatitis B) studies.
The patients we interviewed represented a variety of levels regarding social media literacy. While some patients have had very limited contact with social media, others were very active on social media. One patient even described social media content management as part of their daily job. Another had conducted a research web-based questionnaire for which they were recruiting on the web. Analyzing the interviewees’ accounts about their experience with social media, and partially their use habits, we found a scattered connection to social media recruitment acceptance: those who were considered to have higher digital literacy skills were, in some instances, likely to accept social media as a recruitment tool for clinical hepatitis B studies because they perceived other forms of recruitment as outdated:
I think we are living in a time that you have to use social media because if you don’t use it...sending a letter or put[ting it] in the newspaper, will not help you. [Patient 6]
On the other end of the spectrum, however, patients with very low digital literacy skills and relatedly very little reported use of social media, or digital media in general, in some instances had difficulties delimiting the concept of social media as such. Presumably, their less nuanced understanding of social media as a concept makes them less strictly opposed to being recruited for a clinical study via social media. One patient, for example, favored personal contact for study recruitment at first but then revised their statement and reported that being helped was even more important than personal contact:
Yes definitely. If it was something important it would be best if we met at a clinic, or I don’t know where this study is being done.... But even via Facebook or Messenger.... Yeah, actually never mind, I don’t care actually. [Patient 2]
While the interviews suggested a connection between the acceptance of social media recruitment for clinical hepatitis B studies and digital literacy, it remained unclear whether acceptance was higher with high or low digital literacy. Consequently, we formulated the nondirectional hypothesis that (H2) digital literacy is associated with social media acceptance (SMA).
Some participating patients expressed particularly high interest in participating in clinical studies about hepatitis B. One patient explained to us that they were “very, very happy to support studies” (patient 5), and another patient told us the following: “I actually want to help. So, that’s why I get in” (patient 6). Patients like this, who reported an increased willingness to participate in clinical studies in general, seemed more susceptible to social media as a recruitment tool, too.
Another patient perceived it as beneficial that online recruitment made them less dependent on their physician to refer them to the study:
I don’t know if my physician is even internet-savvy, he’s a bit older. And well, then I thought, I have to see for myself because I’m not sure how competent he is with such things. What I mean is, it would be nicer if I...could google for [a clinical trial], land on a platform, search for [relevant studies], see all the information and can get in touch right away and say: “Hey, I am interested in your study. I would like to participate.” Because in my case, the...specialists didn’t even know that this [study] existed.... That’s stupid and got me pretty upset.” [Patient 3]
None of the patients interviewed reported that they were generally against participation in clinical studies. This is likely a recruitment bias of this qualitative interview study, which made it difficult to interrogate if patients who are less accepting of clinical studies are also less accepting of social media recruitment. Yet, based on the apparent influence of this aspect in 2 (33%) of 6 patient interviews, we formulated the following hypothesis: (H3) The more patients are interested in clinical studies, the more they accept social media as a recruitment tool for clinical hepatitis B studies.
The role of trust in health care professionals, social media platforms, and other recruitment channels was a very salient aspect of all interviews. Illustrating this, one participating patient with hepatitis B stated the following as a reason for being against social media recruitment:
I just feel such a distrust of social media. Any information I share there, I’m not completely comfortable with/It’s just not a safe way for me to share information. [Patient 4]
Other patients were more open to social media recruitment if they knew the source of the advertisement and assigned relevant expertise to them:
It would be okay for me [if someone would contact me on social media to ask whether I would like to meet for a clinical study, as long as] the person is qualified in that direction and is well versed in this expertise. [Patient 2]
[R]ecruiting is normally working if the person that suggests it is a person that you trust or you know. So because she was a person I knew from [redacted], then I clicked the link and I got in. Normally we know, of course, that social media is also a trap for many, I don’t know, viruses and this kind of thing. So you don’t open everything if you don’t trust the link.... If I would see it on, I don’t know, social media and as we know, because you have these cookies that you accept, then immediately, they know that you have something or you are looking for some article. Then this kind of things will pop up. Again, it’s all about trusting links. I’m not sure how much I will get in something that is suggesting from just because I click on a link. [Patient 6]
More implicitly, another patient emphasized that the clinical setting was the place for them to discuss things in the context of hepatitis B, not social media:
This channel through the [clinic in Germany]... I have a very good opinion of the hospital and I have always been well taken care of there. That is the only channel through which I would talk about my condition and about my/yes. [Patient 1]
We analyze the aspect of trust in a separate publication (Willem, T, et al, unpublished data, January 2024) in detail and hypothesize the following: (H4) The more patients trust information sources, the higher their acceptance of social media recruitment. The hypothesis was operationalized for trust in medical information sources (H4a) and trust in nonmedical information sources (H4b).
A particular concern of most patients we spoke with was their privacy. Privacy is a multifaceted and complex concept, and we found that participants referred to different dimensions of privacy: (1) data privacy, defined as the general attitude toward protective measures that empower patients or users to make their own decisions about who can process their data for which purpose; and (2) privacy related to the perceived secrecy of the hepatitis B diagnosis.
First, regarding data privacy, several patients perceived recruitment via social media as dubious and suspected some form of data leakage or malicious data collection goals behind the reach outs. This view applied irrespectively to how they would be approached on social media (eg, advertisement banners in their social media timelines or personal contact requests via social media messengers by health care professionals). For example, a patient who reported on being in the process of decreasing their social media use to protect their privacy also said that if someone contacted them on social media regarding clinical study participation, they would “find that very strange, because [I] would ask [my]self, where did they get this information?” and reported that they would feel that this “would rob quite a lot of privacy” (patient 5). Another patient, who reported using WhatsApp as their only social media, explained that by saying that they “consider social media to be useful in some instances;” however, they continued, “It’s too risky for me with my private data and so much advertising. This, for me, trumps all advantages of social media recruitment” (patient 4).
Regarding the second privacy dimension, secrecy, several patients commented on their hepatitis B diagnosis being a very private, intimate matter:
This condition is in my most private, intimate sphere…. And you might be right, I never thought about it in this way, but [my avoiding engaging on social media regarding hepatitis B] may be related to the fact that content I pass on via WhatsApp can be passed on thousands of times with one click. [Patient 1]
One patient replied to a question regarding their attitude toward being contacted by a study center via social media that they “would find that difficult”. As a reason, this patient explained the following:
[T]hat’s just the problem: it ends up on social media. See, if someone writes: “Hey, I would like to ask you about your hepatitis B, whether you would participate in a study?” Then this information is out there on social media.... That’s why I had a very, very good feeling when my doctor approached me about [this interview study] and that it just went through the clinic. If she had said, “Look, someone is approaching you via social media,” or something, then I would have said no, right? Because I wouldn’t have wanted to, because these data/social media make money because they have data. They run the ads based on your data and what you type in there or what you say or whatever. And I don’t want that associated with my disease. [Patient 5]
These findings led us to the following hypothesis: (H5) The more patients value privacy, the lower their acceptance of using social media as a recruitment tool for clinical hepatitis B studies. The hypothesis was operationalized for secrecy (H5a) and data privacy (H5b).
Several interviewed patients with hepatitis B reported fear of being stigmatized if their social environment found out about their diagnosis as an important reason against social media recruitment. One patient, who mentioned that only their closest family members knew about their diagnosis, expressed fear that other people learning the diagnosis would lead to social exclusion:
A broken leg or surgery on the knee or hip. This is apparent to everyone. And everyone assumes that it will heal at some point and that there is no potential infectious danger from these people. Whereas in the case of infectious diseases, no one can assess that, and people get socially excluded very quickly.... And this is why I am so cautious with my data. [Patient 1]
A similar view was shared by patient 5. Another patient added that perception of stigma differed depending on the context:
I come from [Eastern European country], I have moved to Germany. So here the mentality is a little bit different. If you say to someone, I have Hepatitis, he is okay with it. He says: “Oh, is not a problem. Normally here we are vaccinated against it.” If you are going to [Eastern European country] and say: “I have Hepatitis B,” it’s like you have a huge disease that can just be taken by a handshake [laughs]. And so I think that’s why I’m going on the conservative site. [Patient 6]
The connection between the stigma connected to hepatitis B and the social media–connected perceived privacy risks established by several interview participants led us to the following hypothesis: (H6) The higher the perceived stigma of patients, the lower their acceptance of social media as a recruitment tool for clinical hepatitis B studies.
Participant characteristics.
A total number of 195 eligible questionnaires were included in the statistical analysis of the survey study. Table 1 displays the characteristics of the patients with hepatitis B who participated in the study: more than half of the participants (108/195, 55.4%) were aged between 30 and 49 years. Just above half (110/195, 56.4%) reported having lower educational degrees than Abitur (German equivalent to a high school degree). More than half of the participants (111/195, 56.9%) had another mother tongue than German (only). All participants had a chronic hepatitis B infection, as per the inclusion criterion of this study.
Characteristics | Participants, n (%) | ||
Male | 101 (51.8) | ||
Female | 88 (45.1) | ||
No answer | 6 (3.1) | ||
18-29 | 16 (8.2) | ||
30-39 | 50 (25.6) | ||
40-49 | 58 (29.7) | ||
50-59 | 38 (19.5) | ||
>60 | 24 (12.3) | ||
No answer | 9 (4.6) | ||
Yes | 71 (36.4) | ||
No | 110 (56.4) | ||
No answer | 14 (7.2) | ||
German | 101 (51.8) | ||
Other | 111 (56.9) | ||
No answer | 12 (6.2) |
The questionnaire included 7 scales that were measured through several items ( Table 2 and Multimedia Appendices 1 and 4 ).
The level of acceptance for social media recruitment was measured through the SMA scale, which was calculated based on 4 questionnaire items (P6.01 to P6.04; Multimedia Appendix 4 ). Each item was measured by a 5-point Likert scale, ranging from 0 (completely disagree) to 4 (completely agree). Items P6.01 (“Social media are well suited to make patients aware of studies on new hepatitis B treatments”) and P6.02 (“Social media increase the likelihood of success in hepatitis B clinical trials”) formed the subscale of the perceived usefulness of social media recruitment and received moderate agreement (P6.01: mean 1.99, SD 1.23; P6.02: mean 1.81, SD 1.12). Items P6.03 and P6.04 formed the SMA subscale on the perceived usefulness of social media recruitment. Item P6.03 (“I would be recruited via social media for a hepatitis B clinical trial”) received particularly low acceptance (mean 1.13, SD 1.13; Multimedia Appendix 4 ). P6.04 (I would use social media to learn about hepatitis B clinical trials) received a higher mean acceptance score than P6.03 (mean 1.58, SD 1.23; Multimedia Appendix 4 ).
The overall SMA score was calculated by summarizing the scores from items 6.01 to 6.04 and ranged from 0 (no acceptance) to 16 (full acceptance; mean 6.48, SD 3.03; Table 2 ). While 28.7% (56/195) of the respondents rejected social media recruitment with an SMA score of <5, only 10.2% (20/195) of the respondents accepted social media recruitment with an SMA score of >11 ( Table 3 ).
Valid, n (%) | Items, n (%) | Scale, median (range ) | Values, mean (SD) | |
General social media use | 195 (100) | 8 (15) | 11 (0-32) | 11.22 (6.51) |
Social media literacy (hypothesis 2) | 174 (89.2) | 14 (25) | 41 (0-56) | 37.58 (14.60) |
Hepatitis B–related social media use (hypothesis 1) | 181 (92.8) | 6 (11) | 3 (0-24) | 5.22 (5.61) |
Interest in clinical studies (hypothesis 3) | 187 (95.9) | 2 (4) | 6 (0-8) | 5.53 (2.45) |
Trust in medical information sources | 180 (92.3) | 4 (7) | 11 (0-16) | 10.27 (3.64) |
Trust in nonmedical information sources (hypothesis 4) | 175 (89.7) | 7 (13) | 8.5 (0-28) | 8.36 (5,76) |
Acceptance of social media recruitment (dependent variable) | 178 (91.3) | 4 (7) | 6 (0-16) | 6.48 (3.93) |
Secrecy (hypothesis 5a) | 185 (94.9) | 2 (4) | 2 (0-8) | 2.25 (2.09) |
Data privacy (hypothesis 5b) | 186 (95.4) | 2 (4) | 7 (0-8) | 6.25 (2.10) |
Perceived stigma (hypothesis 6) | 180 (92.3) | 6 (11) | 3.5 (0-24) | 5.52 (6.02) |
a Items were measured through a 5-point Likert scale, ranging from 0 (completely disagree) to 4 (completely agree).
Social media acceptance score | Responses, n (%) |
0 | 20 (10.3) |
1 | 4 (2.1) |
2 | 6 (3.1) |
3 | 8 (4.1) |
4 | 18 (9.2) |
5 | 14 (7.2) |
6 | 20 (10.3) |
7 | 20 (10.3) |
8 | 17 (8.7) |
9 | 12 (6.2) |
10 | 8 (4.1) |
11 | 11 (5.6) |
12 | 7 (3.6) |
13 | 7 (3.6) |
14 | 2 (1) |
15 | 1 (0.5) |
16 | 3 (1.5) |
Missing | 17 (8.7) |
Using multiple linear regression analyses, we evaluated the predictors of participants’ acceptance of social media as a recruitment tool for clinical hepatitis B studies. Testing the statistical significance of the overall model fit, the F test indicated that the predictors included in the model substantially contributed to the explanation of the dependent variable ( Table 4 ). Regression analysis revealed that social media use for hepatitis B, interest in clinical studies, trust in nonmedical information sources, and hepatitis B secrecy independently predicted acceptance of social media as a recruitment tool for clinical hepatitis B studies. More precisely, the higher the social media use for hepatitis B, the higher the interest in clinical studies, the more trust in nonmedical information sources, and the less secret hepatitis B, the higher the acceptance of social media as a recruitment tool for clinical hepatitis B studies ( Table 4 ).
Unstandardized coefficients B (SE) | β | test ( ) | value | Tolerance | VIF | |
Constant | 4.007 (1.935) | — | 2.071 (127) | .04 | — | — |
General social media use | 0.060 (0.051) | .098 | 1.175 (127) | .24 | .628 | 1.593 |
Social media literacy | –0.002 (0.025) | –.008 | –0.096 (127) | .92 | .600 | 1.668 |
Hepatitis B–related social media use | 0.279 (0.053) | .391 | 5.299 (127) | <.001 | .804 | 1.234 |
Interest clinical studies | 0.283 (0.127) | .171 | 2.217 (127) | .03 | .732 | 1.366 |
Trust medical information sources | –0.601 (0.683) | –.079 | –0.879 (127) | .38 | .546 | 1.830 |
Trust in nonmedical information sources | 0.252 (0.058) | .359 | 4.307 (127) | <.001 | .632 | 1.583 |
Secrecy | –1.299 (0.542) | –.171 | –2.399 (127) | .02 | .861 | 1.161 |
Data privacy | –0.765 (0.577) | –.099 | –1.326 (127) | .19 | .792 | 1.262 |
Perceived stigma | –0.003 (0.048) | –.004 | –0.057 (127) | .95 | .770 | 1.299 |
Age | –0.052 (0.028) | –.151 | –1.842 (127) | .07 | .648 | 1.543 |
Education | 0.770 (0.567) | .102 | 1.357 (127) | .18 | .782 | 1.278 |
a Overall model fit: F 11,127 =9.221, P <.001; R 2 =0.444; N=139.
b VIF: variance inflation factor.
c Not applicable.
We present the first empirical study investigating how adult patients with hepatitis B accept social media recruitment for clinical studies. Social media have been suggested to increase recruitment accrual, particularly for hard-to-reach populations [ 13 , 14 , 24 ]. Our study provides a more fine-grained contextualization of this potential. We find that acceptance of social media recruitment among patients with hepatitis B is associated with higher ongoing activity on social media with regard to hepatitis B (confirming H1), a generally high interest in participating in clinical studies for hepatitis B (confirming H3), and high trust recruitment channels outside the clinical setting (confirming H4a). Patients with these characteristics are, consequently, recruitable via social media under the assumptions that (1) patients are most effectively recruited via social media if they accept this channel as a recruitment method and (2) people who do not accept this recruitment channel should also not be recruited in this way.
Yet, 54 (27.7%) out of 195 participants reported an acceptance score of <5 and, thus, rejected being recruited via social media. Moreover, only 20 (10.3%) out of 195 participants reported an acceptance score >11, indicating high acceptance. These findings indicate that recruitment success via social media might be limited among patients with hepatitis B in Germany and underline the importance of using multiple recruitment channels to facilitate diversity and equitable health care access, particularly for patient groups considered vulnerable [ 11 ].
Contrary to what we had hypothesized, SMA was not associated with digital literacy (rejecting H2), data privacy needs (rejecting H5b), and perceived hepatitis B–related stigma (rejecting H6), although reported secrecy around hepatitis B diagnosis was a predictor (confirming H5a). Moreover, trust in medical information sources and demographic variables (age and education) as well as the overall frequency of using social media were not associated with SMA. The results for H2 and H4b are not surprising, as the preceding qualitative interviews did not explicitly indicate a linear connection between digital literacy and social media recruitment acceptance. Our study cannot exclude the possibility that there might be a potential nonlinear association, but another survey study also found that digital literacy did not directly affect the intention to use digital technology [ 25 ]. Furthermore, trust is a multifaceted concept [ 26 , 27 ], which is why the subjects of trust were split into medical information sources and other advertisement channels. Hence, it is not unexpected that trust in medical information sources is not associated with SMA.
The rejection of H5b (data privacy) was more surprising, particularly because the qualitative interviews indicated strong connections between data privacy and SMA. In addition, the scholarly debate around data privacy issues has been very salient: data ethicists have repeatedly emphasized the issues related to data privacy and transparency in the context of social media use in the research context [ 12 , 28 , 29 ]. In addition, the European General Data Protection Regulation emphasizes the transparent use of data and the rights of data subjects [ 30 ]. Moreover, various scandals (eg, related to the US presidential election in 2016 and the UK Brexit referendum) diminished users’ trust in social media platforms and increased awareness of data privacy in that context [ 31 , 32 ]. A recent population survey conducted in Germany, the United Kingdom, and the United States confirmed high levels of concern regarding data privacy in all included countries [ 33 ]. Given these public discussions about social media activities being problematic for data privacy, it is particularly astonishing that data privacy concerns (as operationalized in our study) were not predicting SMA. The findings align with discussions around the privacy paradox. It was confirmed in numerous studies that social media users display limited data protection behavior despite being concerned about their privacy [ 34 - 36 ]. In line with this, the aforementioned scandals have not resulted in a decline in Facebook users [ 37 , 38 ]. Other studies suggest a poor user awareness of online privacy [ 39 ] and fatigue in engaging with privacy-related risks [ 40 ]. It seems that the surveyed population with hepatitis B in Germany are also affected by this privacy paradox.
The rejection of H6 (association of stigma) was surprising, too, particularly because of the strong association between hepatitis B and stigma in other studies. An Indian survey study found that most surveyed patients with hepatitis B were subject to severe stigma and moderate to severe discrimination, with gender identification as men, unemployment, and illiteracy being predictors of discrimination [ 6 ]. Other survey studies from Australia, Turkey, and Serbia confirmed the presence of self-reported perception of stigma in 35% to 47% of patients with hepatitis B and 60% to 65% of patients with hepatitis C [ 10 , 41 , 42 ]. An Iranian qualitative study found that patients with hepatitis B conceptualized stigma as both extrinsic (eg, discrimination, public embarrassment, or blame) and intrinsic (eg, perceived rejection, social isolation, and frustration) [ 8 ]. Although this empirical evidence illustrates the relative importance of stigma in the context of hepatitis B, this did not predict patients’ acceptance of social media recruitment in our study. Instead, our findings suggest that the perceived secrecy of a hepatitis B diagnosis, which seems to be unrelated to the perception of stigma, is informative on social media recruitment acceptance. This indicates that perceptions of stigma in other stigmatized diseases (eg, sexually transmitted diseases, and psychiatric disorders) might not influence patient acceptance to be recruited via social media for clinical studies. However, empirical studies within these populations need to confirm this.
Our survey showed a relatively balanced representation of genders. This aligns with a German serological study from 2011, which indicated no statistically significant difference in the prevalence of acute or chronic hepatitis B infection in men and women [ 43 ]. In terms of age distribution, the survey study covered a diverse range of age groups, mirroring the distribution found in the German serological study [ 43 ]. On the basis of these observations, the survey sample overall is representative of the population with hepatitis B in Germany regarding gender and age.
However, it is essential to consider potential limitations and sources of bias. The recruitment strategy used, primarily relying on venue-based recruitment within a clinical setting, might introduce selection bias, as it may not fully capture the diverse population that may exist outside such settings. In addition, only 30.4% (285/939) of estimated incoming patients received the questionnaire, which might introduce an additional selection bias. We attempted to mitigate this by explicitly briefing the study nurses to avoid self-selection when distributing the survey. The low distribution rate has been mainly caused by administrative burden, resulting in weeks during which no questionnaires were distributed. Thus, we do not expect this to have a large impact on selection bias.
In addition, the study’s restriction to the German language may have impaired the accessibility of the questionnaire for participants who do not have German as their mother tongue. In addition, the exclusive focus on a German setting may limit the generalizability of the findings to a broader international context, potentially impacting the study’s external validity. Finally, it is important to note that we have shortened the questionnaire in comparison to its original length after discussion with clinical colleagues, who provided the feedback that the questionnaire was too long. As part of this shortening, some validated scales were replaced by self-developed scales, which may have implications for the comprehensiveness and depth of the data collected.
Consequently, the attitudes of patients in other medical conditions toward social media recruitment, and a comparison to the attitudes of patients with hepatitis B assessed in this study, should be subject to further research. Similarly, it will be important to study how the different social media platforms, their underlying logic, use patterns, and other factors might influence patients’ acceptance of social media recruitment over time.
This study provides the first quantitative data on the acceptance of social media as a recruitment channel for clinical studies. In the context of hepatitis B in Germany, acceptance of being recruited via social media was very limited. More than 1 (28.7%) in 4 participants rejected this recruitment channel. The study sets out to be a reference point for future studies assessing the attitudes and acceptance of social media recruitment for clinical studies. Such empirical inquiries can facilitate the work of researchers designing clinical studies as well as ethics review boards in balancing the risks and benefits of social media recruitment in a context-specific manner. Moreover, this study provides guidance for researchers considering using social media recruitment and ethics review boards judging such undertakings, by cautioning against the potentially low acceptance rates social media–based recruitment might yield for some patient populations. These should be weighed against the risks of social media recruitment for the target populations.
Similarly relevant for practice, the findings indicate that social media recruitment is particularly accepted in patient populations with high interest in participating in clinical studies. This is particularly the case for diseases with insufficient treatment options and historically neglected diseases with high unmet needs [ 44 ]. Using social media as a recruitment channel for studies targeting these patient groups might thus encounter higher acceptance levels than in this study. There was no statistically significant role associated with perceived stigma and data privacy needs among patients, suggesting that these concerns are unrelated to social media recruitment acceptance.
This study received funding from the European Union’s Horizon 2020 research and innovation program (848223; TherVacB). This publication reflects only the authors’ views, and the European Commission is not liable for any use that may be made of the information contained therein. The authors would like to thank all TherVacB clinical project partners who helped recruit for this study and provided feedback on the questionnaire for their kind collaboration. The authors would also like to thank all patients with hepatitis B who took the time to participate in the survey.
None declared.
Response rate information.
Questionnaire.
Assumptions checks for regression analyses.
Description of each item of the questionnaire.
social media acceptance |
Edited by A Mavragani; submitted 27.10.23; peer-reviewed by D Kukadiya, WB Lee; comments to author 26.02.24; revised version received 08.03.24; accepted 03.06.24; published 26.08.24.
©Theresa Willem, Bettina M Zimmermann, Nina Matthes, Michael Rost, Alena Buyx. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 26.08.2024.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
Article sidebar, article details, main article content, pre-conception alternative sex selection methods for non-medical reasons: bibliographic review, richard mogeni.
Objectives : This study aims to identify the various pre-conception alternative sex selection methods available, explain the scientific basis of the various sex selection methods and assess the factors influencing sex selection
Methods : I electronically searched various databases including; google scholar, PubMed, research gate and tandfonline and reviewed studies and reports written in English up to October 2022 from around the globe. The key words used in the search included; 'sex selection methods', 'pre-conception', 'nonmedical reasons', 'gender selection'. The findings were comprehensively compiled with respect to the type of method, time of use i.e. pre-conception, possible mechanism of action, merits and demerits of the method, success rate and general applicability for non-medical reasons.
Results : Following the electronic search 42 articles were found to have mentioned the key words including 'sex selection methods', 'pre- conception', 'non-medical reasons', 'gender selection'. The articles were reviewed and those found relevant to the study were included in this review. The alternative sex selection methods identified were either administered naturally (Whelan Method, Billings Ovulation Method, pre-conception diet, and gender selection kits such as GenSelect and Smart Stork, which rely on timing of intercourse, the vaginal environment, a selective diet and nutraceuticals) or artificially administered (sperm sorting or Ericsson’s method, Microsort, Preimplantation Genetic Diagnosis and Urobiologics PreGender test).
Conclusion : Given the desire by couples to select the sex of their offspring, there is a need to explore alternative sex selection methods through rigorous scientific process and regulate the process of sex selection for non-medical reasons.
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Home » Research Design – Types, Methods and Examples
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Definition:
Research design refers to the overall strategy or plan for conducting a research study. It outlines the methods and procedures that will be used to collect and analyze data, as well as the goals and objectives of the study. Research design is important because it guides the entire research process and ensures that the study is conducted in a systematic and rigorous manner.
Types of Research Design are as follows:
This type of research design is used to describe a phenomenon or situation. It involves collecting data through surveys, questionnaires, interviews, and observations. The aim of descriptive research is to provide an accurate and detailed portrayal of a particular group, event, or situation. It can be useful in identifying patterns, trends, and relationships in the data.
Correlational research design is used to determine if there is a relationship between two or more variables. This type of research design involves collecting data from participants and analyzing the relationship between the variables using statistical methods. The aim of correlational research is to identify the strength and direction of the relationship between the variables.
Experimental research design is used to investigate cause-and-effect relationships between variables. This type of research design involves manipulating one variable and measuring the effect on another variable. It usually involves randomly assigning participants to groups and manipulating an independent variable to determine its effect on a dependent variable. The aim of experimental research is to establish causality.
Quasi-experimental research design is similar to experimental research design, but it lacks one or more of the features of a true experiment. For example, there may not be random assignment to groups or a control group. This type of research design is used when it is not feasible or ethical to conduct a true experiment.
Case study research design is used to investigate a single case or a small number of cases in depth. It involves collecting data through various methods, such as interviews, observations, and document analysis. The aim of case study research is to provide an in-depth understanding of a particular case or situation.
Longitudinal research design is used to study changes in a particular phenomenon over time. It involves collecting data at multiple time points and analyzing the changes that occur. The aim of longitudinal research is to provide insights into the development, growth, or decline of a particular phenomenon over time.
The format of a research design typically includes the following sections:
An Example of Research Design could be:
Research question: Does the use of social media affect the academic performance of high school students?
Research design:
Writing a research design involves planning and outlining the methodology and approach that will be used to answer a research question or hypothesis. Here are some steps to help you write a research design:
Research design should be written before conducting any research study. It is an important planning phase that outlines the research methodology, data collection methods, and data analysis techniques that will be used to investigate a research question or problem. The research design helps to ensure that the research is conducted in a systematic and logical manner, and that the data collected is relevant and reliable.
Ideally, the research design should be developed as early as possible in the research process, before any data is collected. This allows the researcher to carefully consider the research question, identify the most appropriate research methodology, and plan the data collection and analysis procedures in advance. By doing so, the research can be conducted in a more efficient and effective manner, and the results are more likely to be valid and reliable.
The purpose of research design is to plan and structure a research study in a way that enables the researcher to achieve the desired research goals with accuracy, validity, and reliability. Research design is the blueprint or the framework for conducting a study that outlines the methods, procedures, techniques, and tools for data collection and analysis.
Some of the key purposes of research design include:
There are numerous applications of research design in various fields, some of which are:
Here are some advantages of research design:
Research Design | Research Methodology |
---|---|
The plan and structure for conducting research that outlines the procedures to be followed to collect and analyze data. | The set of principles, techniques, and tools used to carry out the research plan and achieve research objectives. |
Describes the overall approach and strategy used to conduct research, including the type of data to be collected, the sources of data, and the methods for collecting and analyzing data. | Refers to the techniques and methods used to gather, analyze and interpret data, including sampling techniques, data collection methods, and data analysis techniques. |
Helps to ensure that the research is conducted in a systematic, rigorous, and valid way, so that the results are reliable and can be used to make sound conclusions. | Includes a set of procedures and tools that enable researchers to collect and analyze data in a consistent and valid manner, regardless of the research design used. |
Common research designs include experimental, quasi-experimental, correlational, and descriptive studies. | Common research methodologies include qualitative, quantitative, and mixed-methods approaches. |
Determines the overall structure of the research project and sets the stage for the selection of appropriate research methodologies. | Guides the researcher in selecting the most appropriate research methods based on the research question, research design, and other contextual factors. |
Helps to ensure that the research project is feasible, relevant, and ethical. | Helps to ensure that the data collected is accurate, valid, and reliable, and that the research findings can be interpreted and generalized to the population of interest. |
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Why are research objectives important? Research objectives are important because they: Establish the scope and depth of your project: This helps you avoid unnecessary research. It also means that your research methods and conclusions can easily be evaluated.; Contribute to your research design: When you know what your objectives are, you have a clearer idea of what methods are most appropriate ...
Formulating research objectives has the following five steps, which could help researchers develop a clear objective: 8. Identify the research problem. Review past studies on subjects similar to your problem statement, that is, studies that use similar methods, variables, etc.
Research Objectives. Research objectives refer to the specific goals or aims of a research study. They provide a clear and concise description of what the researcher hopes to achieve by conducting the research.The objectives are typically based on the research questions and hypotheses formulated at the beginning of the study and are used to guide the research process.
Time-bound: Research objectives may have associated timelines or deadlines to indicate when the research aims should be accomplished. Research objectives help researchers stay focused on the purpose of their study and guide the development of research methods, data collection, and analysis. They also serve as a basis for evaluating the success ...
Research Objectives: Examples ... This is a well researched and superbly written article for learners of research methods at all levels in the research topic from conceptualization to research findings and conclusions. I highly recommend this material to university graduate students. As an instructor of advanced research methods for PhD ...
This step in your research journey is usually the first written method used to convey your research idea to your tutor. Therefore, aims and objectives should clearly convey your topic, academic foundation, and research design. In order to write effective research aims and objectives, researchers should consider all aspects of their proposed work.
Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes.2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed ...
Research objectives are clear, concise statements that outline what a research project aims to achieve. They guide the direction of the study, ensuring that researchers stay focused and organized. Properly formulated objectives help in identifying the scope of the research and the methods to be used.
The objectives provide a clear direction and purpose for the study, guiding the researcher in their data collection and analysis. Here are some tips on how to write effective research objective: 1. Be clear and specific. Research objective should be written in a clear and specific manner.
Developing your research methods is an integral part of your research design. When planning your methods, there are two key decisions you will make. ... in order to develop an approach that matches your objectives. Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys, ...
Summary. One of the most important aspects of a thesis, dissertation or research paper is the correct formulation of the aims and objectives. This is because your aims and objectives will establish the scope, depth and direction that your research will ultimately take. An effective set of aims and objectives will give your research focus and ...
Formulating research aim and objectives in an appropriate manner is one of the most important aspects of your thesis. This is because research aim and objectives determine the scope, depth and the overall direction of the research. Research question is the central question of the study that has to be answered on the basis of research findings.
Outline the main research questions and objectives; II. Research Design. Explain the research design chosen and why it is appropriate for the research question(s) and objectives ... Flexibility: Research methodology allows researchers to choose the most appropriate research methods and techniques based on the research question, ...
Examples of Specific Research Objectives: 1. "To examine the effects of rising temperatures on the yield of rice crops during the upcoming growth season.". 2. "To assess changes in rainfall patterns in major agricultural regions over the first decade of the twenty-first century (2000-2010).". 3.
The development of the research question, including a supportive hypothesis and objectives, is a necessary key step in producing clinically relevant results to be used in evidence-based practice. A well-defined and specific research question is more likely to help guide us in making decisions about study design and population and subsequently ...
Quantitative research methods are used to collect and analyze numerical data. This type of research is useful when the objective is to test a hypothesis, determine cause-and-effect relationships, and measure the prevalence of certain phenomena. Quantitative research methods include surveys, experiments, and secondary data analysis.
Conversely, objective research tends to be modelled on the methods of the natural sciences such as experiments or large scale surveys. Objective research seeks to establish law-like generalisations which can be applied to the same phenomenon in different contexts.
Many research projects contain more than one research objective. Typically, research objectives appear either in the introduction of a research proposal or between the introduction and the research question. Related: Types of Research Methods How to write research objectives Here are three simple steps that you can follow to identify and write ...
An in-depth analysis of information creates space for generating new questions, concepts and understandings. The main objective of research is to explore the unknown and unlock new possibilities. It's an essential component of success. Over the years, businesses have started emphasizing the need for research.
4. Propose a research study and justify the theory as well as the methodological decisions, including sampling and measurement. 5. Understand the importance of research ethics and integrate research ethics into the research process. 6. Be able to assess and critique a published journal article that uses one of the primary research methods in ...
Qualitative research involves the quality of data and aims to understand the explanations and motives for actions, and also the. way individuals perceive their experiences and the world around ...
Purpose/Objective: Small sample sizes are a common problem in disability research. Here, we show how Bayesian methods can be applied in small sample settings and the advantages that they provide. Method/Design: To illustrate, we provide a Bayesian analysis of employment status (employed vs. unemployed) for those with disability. Specifically, we apply empirically informed priors, based on ...
Background: Social media platforms are increasingly used to recruit patients for clinical studies. Yet, patients' attitudes regarding social media recruitment are underexplored. Objective: This mixed methods study aims to assess predictors of the acceptance of social media recruitment among patients with hepatitis B, a patient population that is considered particularly vulnerable in this ...
The objectives of research may vary depending on the field of study and the specific research question being investigated. However, some common objectives of research include: ... Research is critical in education to evaluate the effectiveness of teaching methods and programs, and to develop new approaches to learning. About the author ...
Objectives: This study aims to identify the various pre-conception alternative sex selection methods available, explain the scientific basis of the various sex selection methods and assess the factors influencing sex selection. Methods: I electronically searched various databases including; google scholar, PubMed, research gate and tandfonline and reviewed studies and reports written in ...
Objective: To describe the profile of Streptococcus pneumoniae, identify research gaps, and provide in-depth insights into various aspects related to the pathogen. Methods: Google Scholar, PubMed, and ScienceDirect were searched for all studies on the pneumococcus in Ghana that reported on specimen collected, population and sample size, carriage prevalence, incidence of pneumococcal diseases ...
Research Methods: This section describes the methods that will be used to collect and analyze data. It includes details about the study design, the sampling strategy, the data collection instruments, and the data analysis techniques. ... Clear objectives: The research design helps to clarify the objectives of the study, ...
Plan and track enterprise projects, gain visibility into capacity, ensure alignment to business objectives, monitor insights and results, and support data-driven decision-making. Make informed decisions and gather insights by building effective dashboards with user-friendly, visual tools.