quantitative research characteristics pdf

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. 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-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

Quantitative Research Methods: Meaning and Characteristics

What are quantitative research methods? What is its definition, when are these research methods used, and what are its characteristics?

This article defines quantitative research methods and lists seven characteristics of quantitative research that discriminate these research methods from qualitative research approaches.

Table of Contents

When to use quantitative or qualitative research.

The methods used by researchers may either be quantitative or qualitative . The decision to select the method largely depends on the researcher’s judgment and the nature of the research topic . Some research topics are better studied using quantitative methods, while others are more appropriately explored using qualitative methods.

Read More : Qualitative Study Design: A Comprehensive Guide

Recently, many researchers use both methods, thereby the era of using mixed methods in research arose as a more desirable and encompassing approach to understanding phenomena. Qualitative methods may be used to explore a phenomenon and identify factors for a quantitative study. Or, a quantitative study may identify research areas that require the application of qualitative methods to provide an in-depth understanding of the phenomenon at hand or when the use of quantitative methods is insufficient to answer questions that relate to human behavior such as feelings, values, and beliefs.

J. Pizarro has already described qualitative research in this site, so this article focuses on quantitative methods, its meaning and characteristics.

What are quantitative research methods?

Quantitative research methods are those research methods that use numbers as its basis for making generalizations about a phenomenon. It emphasizes numerical data analysis using computational techniques like multiple regression analysis to analyze the relationship between multiple factors like age, sex, educational attainment, and academic performance.

The numbers used in statistical analysis originate from objective scales of measurement of the units of analysis called variables . Four types of measurement scale exist namely nominal, ordinal, ratio, and interval (see 4 Statistical Scales of Measurement ).

The data that will serve as the basis for explaining a phenomenon, therefore, can be gathered through surveys . Such surveys use instruments that require numerical inputs or direct measurements of parameters that characterize the subject of investigation (e.g. pH, dissolved oxygen, salinity, turbidity, and conductivity to measure water quality).

These numbers will then be analyzed using the appropriate statistical application software to unravel significant relationships or differences between variables. The output serves as the basis for making the conclusions and generalizations of the study after a thorough discussion has been made.

Read more : How to write the results and discussion

7 Characteristics of Quantitative Research Methods

Seven characteristics discriminate qualitative methods of research from qualitative ones. I enumerate the characteristics of quantitative research methods in the following list.

1. Contain Measurable Variables

Data gathering instruments contain items that solicit measurable characteristics of the population. These measurable characteristics are referred to as the variables of the study , such as age, the number of children, educational status, and economic status.

2. Use Standardized Research Instruments

The data collection instruments include questionnaires, polls, or surveys. Standardized, pre-tested instruments guide data collection, thus ensuring the accuracy, reliability and validity of data . Pre-testing helps identify areas in the research instruments that need revisions. It makes sure that respondents provide the expected answers or satisfy the intent of the researcher to meet the research objectives .

3. Assume a Normal Population Distribution

For more reliable data analysis of quantitative data, a normal population distribution curve is preferred over a non-normal distribution. This requires a large population, the numbers of which depend on how the characteristics of the population vary. This requires adherence to the principle of random sampling to avoid researcher bias in interpreting the results that defeat the purpose of the research.

4. Present Data in Tables, Graphs, or Figures

The data obtained using quantitative methods are organized using tables, graphs, or figures that merge large numbers of data to show trends, relationships, or differences among variables. This fosters understanding of the readers or clients of the research investigation.

5. Use Repeatable Method

Researchers can repeat the quantitative method to verify or confirm the findings in another setting. This reinforces the validity of groundbreaking discoveries or findings, thus eliminating the possibility of spurious or erroneous conclusions.

6. Can Predict Outcomes

Quantitative models or formula derived from data analysis can predict outcomes. If-then scenarios can be constructed using complex mathematical computations with the aid of digital computers or computer-controlled robots commonly referred to as artificial intelligence or AI.

Read More : How to Write an Article with AI: A Quick Guide

7. Use Measuring Devices

Advanced digital or electronic instruments are used to measure or gather quantitative data from the field. The instruments ensure an objective and accurate collection of data provided that these are calibrated. Calibration means that the instruments used by the researcher matches the measurements of a reference instrument that is considered a standard.

The characteristics of quantitative research methods listed in this article make this research approach popular among researchers. Using qualitative research methods, however, is appropriate on issues or problems that need not require quantification or exploratory in nature .

University of Southern California (2015). Quantitative methods. Retrieved on 3 January, 2015 from http://goo.gl/GMiwt

© 2015 January 3 P. A. Regoniel updated : 2020 October 26

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Dr. Regoniel, a faculty member of the graduate school, served as consultant to various environmental research and development projects covering issues and concerns on climate change, coral reef resources and management, economic valuation of environmental and natural resources, mining, and waste management and pollution. He has extensive experience on applied statistics, systems modelling and analysis, an avid practitioner of LaTeX, and a multidisciplinary web developer. He leverages pioneering AI-powered content creation tools to produce unique and comprehensive articles in this website.

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Quantitative Research

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• First Online: 13 January 2019
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• Leigh A. Wilson 2 , 3  

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Quantitative research methods are concerned with the planning, design, and implementation of strategies to collect and analyze data. Descartes, the seventeenth-century philosopher, suggested that how the results are achieved is often more important than the results themselves, as the journey taken along the research path is a journey of discovery. High-quality quantitative research is characterized by the attention given to the methods and the reliability of the tools used to collect the data. The ability to critique research in a systematic way is an essential component of a health professional’s role in order to deliver high quality, evidence-based healthcare. This chapter is intended to provide a simple overview of the way new researchers and health practitioners can understand and employ quantitative methods. The chapter offers practical, realistic guidance in a learner-friendly way and uses a logical sequence to understand the process of hypothesis development, study design, data collection and handling, and finally data analysis and interpretation.

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Wilson LA, Black DA. Health, science research and research methods. Sydney: McGraw Hill; 2013.

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Differential attainment in assessment of postgraduate surgical trainees: a scoping review

• Rebecca L. Jones 1 , 2 ,
• Suwimol Prusmetikul 1 , 3 &
• Sarah Whitehorn 1  

BMC Medical Education volume  24 , Article number:  597 ( 2024 ) Cite this article

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Introduction

Solving disparities in assessments is crucial to a successful surgical training programme. The first step in levelling these inequalities is recognising in what contexts they occur, and what protected characteristics are potentially implicated.

This scoping review was based on Arksey & O’Malley’s guiding principles. OVID and Embase were used to identify articles, which were then screened by three reviewers.

From an initial 358 articles, 53 reported on the presence of differential attainment in postgraduate surgical assessments. The majority were quantitative studies (77.4%), using retrospective designs. 11.3% were qualitative. Differential attainment affects a varied range of protected characteristics. The characteristics most likely to be investigated were gender (85%), ethnicity (37%) and socioeconomic background (7.5%). Evidence of inequalities are present in many types of assessment, including: academic achievements, assessments of progression in training, workplace-based assessments, logs of surgical experience and tests of technical skills.

Attainment gaps have been demonstrated in many types of assessment, including supposedly “objective” written assessments and at revalidation. Further research is necessary to delineate the most effective methods to eliminate bias in higher surgical training. Surgical curriculum providers should be informed by the available literature on inequalities in surgical training, as well as other neighbouring specialties such as medicine or general practice, when designing assessments and considering how to mitigate for potential causes of differential attainment.

Peer Review reports

Diversity in the surgical workforce has been a hot topic for the last 10 years, increasing in traction following the BlackLivesMatter movement in 2016 [ 1 ]. In the UK this culminated in publication of the Kennedy report in 2021 [ 2 ]. Before this the focus was principally on gender imbalance in surgery, with the 2010 Surgical Workforce report only reporting gender percentages by speciality, with no comment on racial profile, sexuality distribution, disability occurrence, or socioeconomic background [ 3 ].

Gender is not the only protected characteristic deserving of equity in surgery; many groups find themselves at a disadvantage during postgraduate surgical examinations [ 4 ] and at revalidation [ 5 ]. This phenomenon is termed ‘differential attainment’ (DA), in which disparities in educational outcomes, progression rates, or achievements between groups with protected characteristics occur [ 4 ]. This may be due to the assessors’ subconscious bias, or a deficit in training and education before assessment.

One of the four pillars of medical ethics is “justice”, emphasising that healthcare should be provided in a fair, equitable, and ethical manner, benefiting all individuals and promoting the well-being of society as a whole. This applies not only to our patients but also to our colleagues; training should be provided in a fair, equitable, and ethical manner, benefiting all. By applying the principle of justice to surgical trainees, we can create an environment that is supportive, inclusive, and conducive to professional growth and well-being.

A diverse consultant body is crucial for providing high-quality healthcare to a diverse patient population. It has been shown that patients are happier when cared for by a doctor with the same ethnic background [ 6 ]. Takeshita et al. [ 6 ] proposed this is due to a greater likelihood of mutual understanding of cultural values, beliefs, and preferences and is therefore more likely to cultivate a trusting relationship, leading to accurate diagnosis, treatment adherence and improved patient understanding. As such, ensuring that all trainees are justly educated and assessed throughout their training may contribute to improving patient care by diversifying the consultant body.

Surgery is well known to have its own specific culture, language, and social rules which are unique even within the world of medicine [ 7 , 8 ]. Through training, graduates develop into surgeons, distinct from other physicians and practitioners [ 9 ]. As such, research conducted in other medical domains is not automatically applicable to surgery, and behavioural interventions focused on reducing or eliminating bias in training need to be tailored specifically to surgical settings.

Consequently, it’s important that the surgical community asks the questions:

Does DA exist in postgraduate surgical training, and to what extent?

Why does DA occur?

What groups or assessments are under-researched?

How can we apply this knowledge, or acquire new knowledge, to provide equity for trainees?

The following scoping review hopes to provide the surgical community with robust answers for future of surgical training.

Aims and research question

The aim of this scoping review is to understand the breadth of research about the presence of DA in postgraduate surgical education and to determine themes pertaining to causes of inequalities. A scoping review was chosen to provide a means to map the available literature, including published peer-reviewed primary research and grey literature.

Following the methodological framework set out by Arksey and O’Malley [ 10 ], our research was intended to characterise the literature addressing DA in HST, including Ophthalmology, Obstetrics & Gynaecology (O&G). We included literature from English-language speaking countries, including the UK and USA.

Search strategy

We used search terms tailored to our target population characteristics (e.g., gender, ethnicity), concept (i.e., DA) and context (i.e., assessment in postgraduate surgical education). Medline and Embase were searched with the assistance of a research librarian, with addition of synonyms. This was conducted in May 2023, and was exported to Microsoft Excel for further review. The reference lists of included articles were also searched to find any relevant data sources that had yet to be considered. In addition, to identify grey literature, a search was performed for the term “differential attainment” and “disparity” on the relevant stakeholders’ websites (See supplemental Table 1 for full listing). Stakeholders were included on the basis of their involvement in governance or training of surgical trainees.

Study selection

To start we excluded conference abstracts that were subsequently published as full papers to avoid duplications ( n  = 337). After an initial screen by title to exclude obviously irrelevant articles, articles were filtered to meet our inclusion and exclusion criteria (Table  1 ). The remaining articles ( n  = 47) were then reviewed in their entirety, with the addition of five reports found in grey literature. Following the screening process, 45 studies were recruited for scoping review (Fig.  1 ).

Charting the data

The extracted data included literature title, authors, year of publication, country of study, study design, population characteristic, case number, context, type of assessment, research question and main findings (Appendix 1). Extraction was performed initially by a single author and then subsequently by a second author to ensure thorough review. Group discussion was conducted in case of any disagreements. As charting occurred, papers were discovered within reference lists of included studies which were eligible for inclusion; these were assimilated into the data charting table and included in the data extraction ( n  = 8).

Collating, summarizing and reporting the results

The included studies were not formally assessed in their quality or risk of bias, consistent with a scoping review approach [ 10 ]. However, group discussion was conducted during charting to aid argumentation and identify themes and trends.

We conducted a descriptive numerical summary to describe the characteristics of included studies. Then thematic analysis was implemented to examine key details and organise the attainment quality and population characteristics based on their description. The coding of themes was an iterative process and involved discussion between authors, to identify and refine codes to group into themes.

We categorised the main themes as gender, ethnicity, country of graduation, individual and family background in education, socioeconomic background, age, and disability. The number of articles in each theme is demonstrated in Table  2 . Data was reviewed and organised into subtopics based on assessment types included: academic achievement (e.g., MRCS, FRCS), assessments for progression (e.g., ARCP), workplace-based assessment (e.g., EPA, feedback), surgical experience (e.g., case volume), and technical skills (e.g., visuo-spatial tasks).

PRISMA flow diagram

44 articles defined the number of included participants (89,399 participants in total; range of participants across individual studies 16–34,755). Two articles reported the number of included studies for their meta-analysis (18 and 63 included articles respectively). Two reports from grey literature did not define the number of participants they included in their analysis. The characteristics of the included articles are displayed in Table  2 .

Growth in published literature on differential attainment over the past 40 years

Academic achievement

In the American Board of Surgery Certifying Exam (ABSCE), Maker [ 11 ] found there to be no significant differences in terms of gender when comparing those who passed on their first attempt and those who did not in general surgery training, a finding supported by Ong et al. [ 12 ]. Pico et al. [ 13 ] reported that in Orthopaedic training, Orthopaedic In-Training Examination (OITE) and American Board of Orthopaedic Surgery (ABOS) Part 1 scores were similar between genders, but that female trainees took more attempts in order to pass. In the UK, two studies reported significantly lower Membership of the Royal College of Surgeons (MRCS) pass rates for female trainees compared to males [ 4 , 14 ]. However, Robinson et al. [ 15 ] presented no significant gender differences in MRCS success rates. A study assessing Fellowship of the Royal College of Surgeons (FRCS) examination results found no significant gender disparities in pass rates [ 16 ]. In MRCOG examination, no significant gender differences were found in Part 1 scores, but women had higher pass rates and scores in Part 2 [ 17 ].

Assessment for Progression

ARCP is the annual process of revalidation that UK doctors must perform to progress through training. A satisfactory progress outcome (“outcome 1”) allows trainees to advance through to the next training year, whereas non-satisfactory outcomes (“2–5”) suggest inadequate progress and recommends solutions, such as further time in training or being released from the training programme. Two studies reported that women received 60% more non-satisfactory outcomes than men [ 16 , 18 ]. In contrast, in O&G men had higher non-satisfactory ARCP outcomes without explicit reasons for this given [ 19 ].

Regarding Milestone evaluations based from the US Accreditation Council for Graduate Medical Education (ACGME), Anderson et al. [ 20 ] reported men had higher ratings of knowledge of diseases at postgraduate year 5 (PGY-5), while women had lower mean score achievements. This was similar to another study finding that men and women had similar competencies at PGY-1 to 3, and that it was only at PGY-5 that women were evaluated lower than men [ 21 ]. However, Kwasny et al. [ 22 ] found no difference in trainers’ ratings between genders, but women self-rated themselves lower. Salles et al. [ 23 ] demonstrated significant improvement in scoring in women following a value-affirmation intervention, while this intervention did not affect men.

Workplace-based Assessment

Galvin et al. [ 24 ] reported better evaluation scores from nurses for PGY-2 male trainees, while females received fewer positive and more negative comments. Gerull et al. [ 25 ] demonstrated men received compliments with superlatives or standout words, whereas women were more likely to receive compliments with mitigating phrases (e.g., excellent vs. quite competent).

Hayward et al. [ 26 ] investigated assessment of attributes of clinical performance (ethics, judgement, technical skills, knowledge and interpersonal skills) and found similar scoring between genders.

Several authors have studied autonomy given to trainees in theatre [ 27 , 28 , 29 , 30 , 31 ]. Two groups found no difference in level of granted autonomy between genders but that women rated lower perceived autonomy on self-evaluation [ 27 , 28 ]. Other studies found that assessors consistently gave female trainees lower autonomy ratings, but only in one paper was this replicated in lower performance scores [ 29 , 30 , 31 ].

Padilla et al. [ 32 ] reported no difference in entrustable professional activity assessment (EPA) levels between genders, yet women rated themselves much lower, which they regarded as evidence of imposter syndrome amongst female trainees. Cooney et al. [ 33 ] found that male trainers scored EPAs for women significantly lower than men, while female trainers rated both genders similarly. Conversely, Roshan et al. [ 34 ] found that male assessors were more positive in feedback comments to female trainees than male trainees, whereas they also found that comments from female assessors were comparable for each gender.

Surgical Experience

Gong et al. [ 35 ] found significantly fewer cataract operations were performed by women in ophthalmology residency programmes, which they suggested could be due to trainers being more likely to give cases to male trainees. Female trainees also participated in fewer robotic colorectal procedures, with less operative time on the robotic console afforded [ 36 ]. Similarly, a systematic review highlighted female trainees in various specialties performed fewer cases per week and potentially had limited access to training facilities [ 37 ]. Eruchalu et al. [ 38 ] found that female trainees performed fewer cases, that is, until gender parity was reached, after which case logs were equivalent.

Technical skills

Antonoff et al. [ 39 ] found higher scores for men in coronary anastomosis skills, with women receiving more “fail” assessments. Dill-Macky et al. [ 40 ] analysed laparoscopic skill assessment using blinded videos of trainees and unblinded assessments. While there was no difference in blinded scores between genders, when comparing blinded and unblinded scores individually, assessors were less likely to agree on the scores of women compared to men. However, another study about laparoscopic skills by Skjold-Ødegaard et al. [ 41 ] reported higher performance scores in female residents, particularly when rated by women. The lowest score was shown in male trainees rated by men. While some studies showed disparities in assessment, several studies reported no difference in technical skill assessments (arthroscopic, knot tying, and suturing skills) between genders [ 42 , 43 , 44 , 45 , 46 ].

Several studies investigated trainees’ abilities to complete isolated tasks associated with surgical skills. In laparoscopic tasks, men were initially more skilful in peg transfer and intracorporeal knot tying than women. Following training, the performance was not different between genders [ 47 ]. A study on microsurgical skills reported better initial visual-spatial and perceptual ability in men, while women had better fine motor psychomotor ability. However, these differences were not significant, and all trainees improved significantly after training [ 48 ]. A study by Milam et al. [ 49 ] revealed men performed better in mental rotation tasks and women outperformed in working memory. They hypothesised that female trainees would experience stereotype threat, fear of being reduced to a stereotype, which would impair their performance. They found no evidence of stereotype threat influencing female performance, disproving their hypothesis, a finding supported by Myers et al. [ 50 ].

Ethnicity and country of graduation

Most papers reported ethnicity and country of graduation concurrently, for example grouping trainees as White UK graduates (WUKG), Black and minority ethnicity UK graduates (BME UKG), and international medical graduates (IMG). Therefore, these areas will be addressed together in the following section.

When assessing the likelihood of passing American Board of Surgery (ABS) examinations on first attempt, Yeo et al. [ 51 ] found that White trainees were more likely than non-White. They found that the influence of ethnicity was more significant in the end-of-training certifying exam than in the start-of-training qualifying exam. This finding was corroborated in a study of both the OITE and ABOS certifying exam, suggesting widening inequalities during training [ 52 ].

Two UK-based studies reported significantly higher MRCS pass rates in White trainees compared to BMEs [ 4 , 14 ]. BMEs were less likely to pass MRCS Part A and B, though this was not true for Part A when variations in socioeconomic background were corrected for [ 14 ]. However, Robinson et al. [ 53 ] found no difference in MRCS pass rates based on ethnicity. Another study by Robinson et al. [ 15 ] demonstrated similar pass rates between WUKGs and BME UKGs, but IMGs had significantly lower pass rates than all UKGs. The FRCS pass rates of WUKGs, BME UKGs and IMGs were 76.9%, 52.9%, and 53.9%, respectively, though these percentages were not statistically significantly different [ 16 ].

There was no difference in MRCOG results based on ethnicity, but higher success rates were found in UKGs [ 19 ]. In FRCOphth, WUKGs had a pass rate of 70%, higher than other groups of trainees, with a pass rate of only 45% for White IMGs [ 52 ].

By gathering data from training programmes reporting little to no DA due to ethnicity, Roe et al. [ 54 ] were able to provide a list of factors they felt were protective against DA, such as having supportive supervisors and developing peer networks.

Assessment for progression

RCOphth [ 55 ] found higher rates of satisfactory ARCP outcomes for WUKGs compared to BME UKGs, followed by IMGs. RCOG [ 19 ] discovered higher rates of non-satisfactory ARCP outcomes from non-UK graduates, particularly amongst BMEs and those from the European Economic Area (EEA). Tiffin et al. [ 56 ] considered the difference in experience between UK graduates and UK nationals whose primary medical qualification was gained outside of the UK, and found that the latter were more likely to receive a non-satisfactory ARCP outcome, even when compared to non-UK nationals.

Woolf et al. [ 57 ] explored reasons behind DA by conducting interview studies with trainees. They investigated trainees’ perceptions of fairness in evaluation and found that trainees felt relationships developed with colleagues who gave feedback could affect ARCP results, and might be challenging for BME UKGs and IMGs who have less in common with their trainers.

Workplace-based assessment

Brooks et al. [ 58 ] surveyed the prevalence of microaggressions against Black orthopaedic surgeons during assessment and found 87% of participants experienced some level of racial discrimination during workplace-based performance feedback. Black women reported having more racially focused and devaluing statements from their seniors than men.

Surgical experience

Eruchalu et al. [ 38 ] found that white trainees performed more major surgical cases and more cases as a supervisor than did their BME counterparts.

Dill-Macky et al. [ 40 ] reported no significant difference in laparoscopic surgery assessments between ethnicities.

Individual and family background in education

Two studies [ 4 , 16 ] concentrated on educational background, considering factors such as parental occupation and attendance of a fee-paying school. MRCS part A pass rate was significantly higher for trainees for whom Medicine was their first Degree, those with university-educated parents, higher POLAR (Participation In Local Areas classification group) quintile, and those from fee-paying schools. Higher part B pass rate was associated with graduating from non-Graduate Entry Medicine programmes and parents with managerial or professional occupations [ 4 ]. Trainees with higher degrees were associated with an almost fivefold increase in FRCS success and seven times more scientific publications than their counterparts [ 16 ].

Socioeconomic background

Two studies used Index of Multiple Deprivation quintile, the official measure of relative deprivation in England based on geographical areas for grading socioeconomic level. The area was defined at the time of medical school application. Deprivation quintiles (DQ) were calculated, ranging from DQ1 (most deprived) to DQ5 (least deprived) [ 4 , 14 ].

Trainees with history of less deprivation were associated with higher MRCS part A pass rate. More success in part B was associated with history of no requirement for income support and less deprived areas [ 4 ]. Trainees from DQ1 and DQ2 had lower pass rates and higher number of attempts to pass [ 14 ]. A general trend of better outcomes in examination was found from O&G trainees in less deprived quintiles [ 19 ].

Trainees from DQ1 and DQ2 received significantly more non-satisfactory ARCP outcomes (24.4%) than DQ4 and DQ5 (14.2%) [ 14 ].

Trainees who graduated at age less than 29 years old were more likely to pass MRCS than their counterparts [ 4 ].

Authors [ 18 , 56 ] found that older trainees received more non-satisfactory ARCP outcomes. Likewise, there was higher percentage of non-satisfactory ARCP outcomes in O&G trainees aged over 45 compared with those aged 25–29 regardless of gender [ 19 ].

Trainees with disability had significantly lower pass rates in MRCS part A compared to candidates without disability. However, the difference was not significant for part B [ 59 ].

What have we learnt from the literature?

It is heartening to note the recent increase in interest in DA (27 studies in the last 4 years, compared to 26 in the preceding 40) (Fig.  2 ). The vast majority (77%) of studies are quantitative, based in the US or UK (89%), focus on gender (85%) and relate to clinical assessments (51%) rather than examination results. Therefore, the surgical community has invested primarily in researching the experience of women in the USA and UK.

Interestingly, a report by RCOG [ 19 ] showed that men were more likely to receive non-satisfactory ARCP outcomes than women, and a study by Rushd et al. [ 17 ] found that women were more likely to pass part 2 of MRCOG than men. This may be because within O&G men are the “out-group” (a social group or category characterised by marginalisation or exclusion by the dominant cultural group) as 75% of O&G trainees are female [ 60 ].

This contrasts with other specialities in which men are the in-group and women are seen to underperform. Outside of O&G, in comparison to men, women are less likely to pass MRCS [ 4 , 14 ], receive satisfactory ARCP outcome [ 16 , 18 ], or receive positive feedback [ 24 ], whilst not performing the same number of procedures as men [ 34 , 35 ]. This often leads to poor self-confidence in women [ 32 ], which can then worsen performance [ 21 ].

It proves difficult to comment on DA for many groups due to a lack of evidence. The current research suggests that being older, having a disability, graduate entry to medicine, low parental education, and living in a lower socioeconomic area at the time of entering medical school are all associated with lower MRCS pass rates. Being older and having a lower socioeconomic background are also associated with non-satisfactory ARCP outcomes, slowing progression through training.

These characteristics may provide a compounding negative effect – for example having a previous degree will automatically make a trainee older, and living in a lower socioeconomic area makes it more likely their parents will have a non-professional job and not hold a higher degree. When multiple protected characteristics interact to produce a compounded negative effect for a person, it is often referred to as “intersectional discrimination” or “intersectionality” [ 61 ]. This is a concept which remains underrepresented in the current literature.

The literature is not yet in agreement over the presence of DA due to ethnicity. There are many studies that report perceived discrimination, however the data for exam and clinical assessment outcomes is equivocal. This may be due to the fluctuating nature of in-groups and out-groups, and multiple intersecting characteristics. Despite this, the lived experience of BME surgeons should not be ignored and requires further investigation.

What are the gaps in the literature?

The overwhelming majority of literature exploring DA addresses issues of gender, ethnicity or country of medical qualification. Whilst bias related to these characteristics is crucial to recognise, studies into other protected characteristics are few and far between. The only paper on disability reported striking differences in attainment between disabled and non-disabled registrars [ 59 ]. There has also been increased awareness about neurodiversity amongst doctors and yet an exploration into the experience of neurodiverse surgeons and their progress through training has yet to be published [ 62 ].

The implications of being LGBTQ + in surgical training have not been recognised nor formally addressed in the literature. Promisingly, the experiences of LGBTQ + medical students have been recognised at an undergraduate level, so one can hope that this will be translated into postgraduate education [ 63 , 64 ]. While this is deeply entwined with experiences of gender discrimination, it is an important characteristic that the surgical community would benefit from addressing, along with disability. To a lesser extent, the effect of socioeconomic background and age have also been overlooked.

Characterising trainees for the purpose of research

Ethnicity is deeply personal, self-defined, and may change over time as personal identity evolves, and therefore arbitrarily grouping diverse ethnic backgrounds is unlikely to capture an accurate representation of experiences. There are levels of discrimination even within minority groups; colourism in India means dark-skinned Indians will experience more discrimination than light-skinned Indians, even from those within in their own ethnic group [ 65 ]. Therefore, although the studies included in the scoping review accepted self-definitions of ethnicity, this is likely not enough to fully capture the nuances of bias and discrimination present in society. For example, Ellis et al. [ 4 ] grouped participants as “White”, “Mixed”, “Asian”, “Black” and “Other”, however they could have also assigned a skin tone value such as the NIS Skin Colour Scale [ 66 ], thus providing more detail.

Ethnicity is more than genetic heritage; it is also cultural expression. The experience of an IMG in UK postgraduate training will differ from that of a UKG, an Indian UKG who grew up in India, and an Indian UKG who grew up in the UK. These are important distinctions which are noted in the literature (e.g. by Woolf et al., 2016 [ 57 ]) however some do not distinguish between ethnicity and graduate status [ 15 ] and none delve into an individual’s cultural expression (e.g., clothing choice) and how this affects the perception of their assessors.

Reasons for DA

Despite the recognition of inequalities in all specialties of surgery, there is a paucity of data explicitly addressing why DA occurs. Reasons behind the phenomenon must be explored to enable change and eliminate biases. Qualitative research is more attuned to capturing the complexities of DA through observation or interview-based studies. Currently most published data is quantitative, and relies on performance metrics to demonstrate the presence of DA while ignoring the causes. Promisingly, there are a gradually increasing number of qualitative, predominantly interview-based, studies (Fig.  2 ).

To create a map of DA in all its guises, an analysis of the themes reported to be contributory to its development is helpful. In our review of the literature, four themes have been identified:

Training culture

In higher surgical training, for there to be equality in outcomes, there needs to be equity in opportunities. Ellis et al. [ 4 ] recognised that variation in training experiences, such as accessibility of supportive peers and senior role models, can have implications on attainment. Trainees would benefit from targeted support at times of transition, such as induction or at examinations, and it may be that currently the needs of certain groups are being met before others, reinforcing differential attainment [ 4 ].

Experience of assessment

Most literature in DA relates to the presence (or lack of) an attainment gap in assessments, such as ARCP or MRCS. It is assumed that these assessments of trainee development are objective and free of bias, and indeed several authors have described a lack of bias in these high-stakes examinations (e.g., Ong et al., 2019 [ 12 ]; Robinson et al., 2019 [ 53 ]). However, in some populations, such as disabled trainees, there are differences in attainment [ 59 ]. This is demonstrated despite legislation requiring professional bodies to make reasonable adjustments to examinations for disabled candidates, such as additional time, text formatting amendments, or wheelchair-accessible venues [ 67 ]. Therefore it would be beneficial to investigate the implementation of these adjustments across higher surgical examinations and identify any deficits.

Social networks

Relationships between colleagues may influence DA in multiple ways. Several studies identified that a lack of a relatable and inspiring mentor may explain why female or BME doctors fail to excel in surgery [ 4 , 55 ]. Certain groups may receive preferential treatment due to their perceived familiarity to seniors [ 35 ]. Robinson et al. [ 15 ] recognised that peer-to-peer relationships were also implicated in professional development, and the lack thereof could lead to poor learning outcomes. Therefore, a non-discriminatory culture and inclusion of trainees within the social network of training is posited as beneficial.

Personal characteristics

Finally, personal factors directly related to protected characteristics have been suggested as a cause of DA. For example, IMGs may perform worse in examinations due to language barriers, and those from disadvantaged backgrounds may have less opportunity to attend expensive courses [ 14 , 16 ]. Although it is impossible to exclude these innate deficits from training, we may mitigate their influence by recognising their presence and providing solutions.

The causes of DA may also be grouped into three levels, as described by Regan de Bere et al. [ 68 ]: macro (the implications of high-level policy), meso (focusing on institutional or working environments) and micro (the influence of individual factors). This can intersect with the four themes identified above, as training culture can be enshrined at both an institutional and individual level, influencing decisions that relate to opportunities for trainees, or at a macro level, such as in the decisions made on nationwide recruitment processes. These three levels can be used to more deeply explore each of the four themes to enrich the discovery of causes of DA.

Discussions outside of surgery

Authors in General Practice (e.g., Unwin et al., 2019 [ 69 ]; Pattinson et al., 2019 [ 70 ]), postgraduate medical training (e.g., Andrews, Chartash, and Hay, 2021 [ 71 ]), and undergraduate medical education (e.g., Yeates et al., 2017 [ 72 ]; Woolf et al., 2013 [ 73 ]) have published more extensively in the aetiology of DA. A study by Hope et al. [ 74 ] evaluating the bias present in MRCP exams used differential item functioning to identify individual questions which demonstrated an attainment gap between male and female and Caucasian and non-Caucasian medical trainees. Conclusions drawn about MRCP Part 1 examinations may be generalisable to MRCS Part A or FRCOphth Part 1: they are all multiple-choice examinations testing applied basic science and usually taken within the first few years of postgraduate training. Therefore it is advisable that differential item functioning should also be applied to these examinations. However, it is possible that findings in some subspecialities may not be generalisable to others, as training environments can vary profoundly. The RCOphth [ 55 ] reported that in 2021, 53% of ophthalmic trainees identified as male, whereas in Orthopaedics 85% identified as male, suggesting different training environments [ 5 ]. It is useful to identify commonalities of DA between surgical specialties and in the wider scope of medical training.

Limitations of our paper

Firstly, whilst aiming to provide a review focussed on the experience of surgical trainees, four papers contained data about either non-surgical trainees or medical students. It is difficult to draw out the surgeons from this data and therefore it is possible that there are issues with generalisability. Furthermore, we did not consider the background of each paper’s authors, as their own lived experience of attainment gap could form the lens through which they commented on surgical education, colouring their interpretation. Despite intending to include as many protected characteristics as possible, inevitably there will be lived experiences missed. Lastly, the experience of surgical trainees outside of the English-speaking world were omitted. No studies were found that originated outside of Europe or North America and therefore the presence or characteristics of DA outside of this area cannot be assumed.

Experiences of inequality in surgical assessment are prevalent in all surgical subspecialities. In order to further investigate DA, researchers should ensure all protected characteristics are considered - and how these interact - to gain insight into intersectionality. Given the paucity of current evidence, particular focus should be given to the implications of disability, and specifically neurodiversity, in progress through training as they are yet to be explored in depth. In defining protected characteristics, future authors should be explicit and should avoid generalisation of cultural backgrounds to allow authentic appreciation of attainment gap. Few authors have considered the driving forces between bias in assessment and DA, and therefore qualitative studies should be prioritised to uncover causes for and protective factors against DA. Once these influences have been identified, educational designers can develop new assessment methods that ensure equity across surgical trainees.

Data availability

All data provided during this study are included in the supplementary information files.

Abbreviations

Accreditation Council for Graduate Medical Education

American Board of Orthopaedic Surgery

American Board of Surgery

American Board of Surgery Certifying Exam

Annual Review of Competence Progression

Black, Asian, and Minority Ethnicity

Council on Resident Education in Obstetrics and Gynecology

Differential Attainment

Deprivation Quintile

European Economic Area

Entrustable Professional Activities

Fellowship of The Royal College of Ophthalmologists

Fellow of the Royal College of Surgeons

General Medical Council

Higher Surgical Training

International Medical Graduate

In-Training Evaluation Report

Member of the Royal College of Obstetricians and Gynaecologists

Member of the Royal College of Physicians

Member of the Royal College of Surgeons

Obstetrics and Gynaecology

Orthopaedic In-Training Examination

Participation In Local Areas

Postgraduate Year

The Royal College of Ophthalmologists

The Royal College of Obstetricians and Gynaecologists

The Royal College of Surgeons of England

United Kingdom Graduate

White United Kingdom Graduate

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Rebecca L. Jones, Suwimol Prusmetikul & Sarah Whitehorn

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RJ, SP and SW conceived the study. RJ carried out the search. RJ, SP and SW reviewed and appraised articles. RJ, SP and SW extracted data and synthesized results from articles. RJ, SP and SW prepared the original draft of the manuscript. RJ and SP prepared Figs. 1 and 2. All authors reviewed and edited the manuscript and agreed to the final version.

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Jones, R.L., Prusmetikul, S. & Whitehorn, S. Differential attainment in assessment of postgraduate surgical trainees: a scoping review. BMC Med Educ 24 , 597 (2024). https://doi.org/10.1186/s12909-024-05580-2

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DOI : https://doi.org/10.1186/s12909-024-05580-2

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