what is comparative research method

Comparative Analysis

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Context of comparisons ; Radical positivism

The goal of comparative analysis is to search for similarity and variance among units of analysis. Comparative research commonly involves the description and explanation of similarities and differences of conditions or outcomes among large-scale social units, usually regions, nations, societies, and cultures.

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In the broadest sense, it is difficult to think of any analysis in the social sciences that is not comparative. In a laboratory experiment, we compare the outcomes for the experimental and control group to ascertain the effects of some experimental stimulus. When we analyze quality of life of men and women, old and young, or rich and poor, we actually perform a comparison of individuals along certain dimensions, such as gender, age, and wealth/income. However, this meaning of comparative analysis is too general to be really useful in research. “Comparative analysis has come to mean the description and...

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Drobnič, S. (2014). Comparative Analysis. In: Michalos, A.C. (eds) Encyclopedia of Quality of Life and Well-Being Research. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0753-5_492

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3. Comparative Research Methods

This chapter examines the ‘art of comparing’ by showing how to relate a theoretically guided research question to a properly founded research answer by developing an adequate research design. It first considers the role of variables in comparative research, before discussing the meaning of ‘cases’ and case selection. It then looks at the ‘core’ of the comparative research method: the use of the logic of comparative inquiry to analyse the relationships between variables (representing theory), and the information contained in the cases (the data). Two logics are distinguished: Method of Difference and Method of Agreement. The chapter concludes with an assessment of some problems common to the use of comparative methods.

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3. Comparative research methods

This chapter examines the ‘art of comparing’ by showing how to relate a theoretically guided research question to a properly founded research answer by developing an adequate research design. It first considers the role of variables in comparative research before discussing the meaning of ‘cases’ and case selection. It then looks at the ‘core’ of the comparative research method: the use of the logic of comparative inquiry to analyse the relationships between variables (representing theory) and the information contained in the cases (the data). Two logics are distinguished: Method of Difference and Method of Agreement. The chapter concludes with an assessment of some problems common to the use of comparative methods.

Rethinking Comparison

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PERAN PEMUDA RELAWAN DEMOKRASI DALAM MENINGKATKAN PARTISIPASI POLITIK MASYARAKAT PADA PEMILIHAN UMUM LEGISLATIF TAHUN 2014 DAN IMPLIKASINYA TERHADAP KETAHANAN POLITIK WILAYAH (STUDI PADA RELAWAN DEMOKRASI BANYUMAS, JAWA TENGAH)

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Comparative methods

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Comparative method is about looking at an object of study in relation to another. The object of study is normally compared across space and/or time. Comparative methods can be qualitative and quantitative. Often, there is a trade-off: the more cases to compare, the less comparable variables available and vice versa.

The comparative method is often applied when looking for patterns of similarities and differences, explaining continuity and change. Often applied in comparative research is the Most Similar Systems Design (that consists in comparing very similar cases that differ in the dependent variable, on the assumption that this will make it easier to find those independent variables which explain the presence/absence of the dependent variable) or the Most Different Systems Design (comparing very different cases, all of which have the same dependent variable in common, so that any other circumstance that is present in all the cases can be regarded as the independent variable).

A challenge in comparative research is that what may seem as the same category across countries may in fact be defined very differently in these same countries.

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Lau F, Kuziemsky C, editors. Handbook of eHealth Evaluation: An Evidence-based Approach [Internet]. Victoria (BC): University of Victoria; 2017 Feb 27.

Handbook of eHealth Evaluation: An Evidence-based Approach [Internet].

Chapter 10 methods for comparative studies.

Francis Lau and Anne Holbrook .

10.1. Introduction

In eHealth evaluation, comparative studies aim to find out whether group differences in eHealth system adoption make a difference in important outcomes. These groups may differ in their composition, the type of system in use, and the setting where they work over a given time duration. The comparisons are to determine whether significant differences exist for some predefined measures between these groups, while controlling for as many of the conditions as possible such as the composition, system, setting and duration.

According to the typology by Friedman and Wyatt (2006) , comparative studies take on an objective view where events such as the use and effect of an eHealth system can be defined, measured and compared through a set of variables to prove or disprove a hypothesis. For comparative studies, the design options are experimental versus observational and prospective versus retro­­spective. The quality of eHealth comparative studies depends on such aspects of methodological design as the choice of variables, sample size, sources of bias, confounders, and adherence to quality and reporting guidelines.

In this chapter we focus on experimental studies as one type of comparative study and their methodological considerations that have been reported in the eHealth literature. Also included are three case examples to show how these studies are done.

10.2. Types of Comparative Studies

Experimental studies are one type of comparative study where a sample of participants is identified and assigned to different conditions for a given time duration, then compared for differences. An example is a hospital with two care units where one is assigned a cpoe system to process medication orders electronically while the other continues its usual practice without a cpoe . The participants in the unit assigned to the cpoe are called the intervention group and those assigned to usual practice are the control group. The comparison can be performance or outcome focused, such as the ratio of correct orders processed or the occurrence of adverse drug events in the two groups during the given time period. Experimental studies can take on a randomized or non-randomized design. These are described below.

10.2.1. Randomized Experiments

In a randomized design, the participants are randomly assigned to two or more groups using a known randomization technique such as a random number table. The design is prospective in nature since the groups are assigned concurrently, after which the intervention is applied then measured and compared. Three types of experimental designs seen in eHealth evaluation are described below ( Friedman & Wyatt, 2006 ; Zwarenstein & Treweek, 2009 ).

Randomized controlled trials ( rct s) – In rct s participants are randomly assigned to an intervention or a control group. The randomization can occur at the patient, provider or organization level, which is known as the unit of allocation. For instance, at the patient level one can randomly assign half of the patients to receive emr reminders while the other half do not. At the provider level, one can assign half of the providers to receive the reminders while the other half continues with their usual practice. At the organization level, such as a multisite hospital, one can randomly assign emr reminders to some of the sites but not others. Cluster randomized controlled trials ( crct s) – In crct s, clusters of participants are randomized rather than by individual participant since they are found in naturally occurring groups such as living in the same communities. For instance, clinics in one city may be randomized as a cluster to receive emr reminders while clinics in another city continue their usual practice. Pragmatic trials – Unlike rct s that seek to find out if an intervention such as a cpoe system works under ideal conditions, pragmatic trials are designed to find out if the intervention works under usual conditions. The goal is to make the design and findings relevant to and practical for decision-makers to apply in usual settings. As such, pragmatic trials have few criteria for selecting study participants, flexibility in implementing the intervention, usual practice as the comparator, the same compliance and follow-up intensity as usual practice, and outcomes that are relevant to decision-makers.

10.2.2. Non-randomized Experiments

Non-randomized design is used when it is neither feasible nor ethical to randomize participants into groups for comparison. It is sometimes referred to as a quasi-experimental design. The design can involve the use of prospective or retrospective data from the same or different participants as the control group. Three types of non-randomized designs are described below ( Harris et al., 2006 ).

Intervention group only with pretest and post-test design – This design involves only one group where a pretest or baseline measure is taken as the control period, the intervention is implemented, and a post-test measure is taken as the intervention period for comparison. For example, one can compare the rates of medication errors before and after the implementation of a cpoe system in a hospital. To increase study quality, one can add a second pretest period to decrease the probability that the pretest and post-test difference is due to chance, such as an unusually low medication error rate in the first pretest period. Other ways to increase study quality include adding an unrelated outcome such as patient case-mix that should not be affected, removing the intervention to see if the difference remains, and removing then re-implementing the intervention to see if the differences vary accordingly. Intervention and control groups with post-test design – This design involves two groups where the intervention is implemented in one group and compared with a second group without the intervention, based on a post-test measure from both groups. For example, one can implement a cpoe system in one care unit as the intervention group with a second unit as the control group and compare the post-test medication error rates in both units over six months. To increase study quality, one can add one or more pretest periods to both groups, or implement the intervention to the control group at a later time to measure for similar but delayed effects. Interrupted time series ( its ) design – In its design, multiple measures are taken from one group in equal time intervals, interrupted by the implementation of the intervention. The multiple pretest and post-test measures decrease the probability that the differences detected are due to chance or unrelated effects. An example is to take six consecutive monthly medication error rates as the pretest measures, implement the cpoe system, then take another six consecutive monthly medication error rates as the post-test measures for comparison in error rate differences over 12 months. To increase study quality, one may add a concurrent control group for comparison to be more convinced that the intervention produced the change.

10.3. Methodological Considerations

The quality of comparative studies is dependent on their internal and external validity. Internal validity refers to the extent to which conclusions can be drawn correctly from the study setting, participants, intervention, measures, analysis and interpretations. External validity refers to the extent to which the conclusions can be generalized to other settings. The major factors that influence validity are described below.

10.3.1. Choice of Variables

Variables are specific measurable features that can influence validity. In comparative studies, the choice of dependent and independent variables and whether they are categorical and/or continuous in values can affect the type of questions, study design and analysis to be considered. These are described below ( Friedman & Wyatt, 2006 ).

Dependent variables – This refers to outcomes of interest; they are also known as outcome variables. An example is the rate of medication errors as an outcome in determining whether cpoe can improve patient safety. Independent variables – This refers to variables that can explain the measured values of the dependent variables. For instance, the characteristics of the setting, participants and intervention can influence the effects of cpoe . Categorical variables – This refers to variables with measured values in discrete categories or levels. Examples are the type of providers (e.g., nurses, physicians and pharmacists), the presence or absence of a disease, and pain scale (e.g., 0 to 10 in increments of 1). Categorical variables are analyzed using non-parametric methods such as chi-square and odds ratio. Continuous variables – This refers to variables that can take on infinite values within an interval limited only by the desired precision. Examples are blood pressure, heart rate and body temperature. Continuous variables are analyzed using parametric methods such as t -test, analysis of variance or multiple regression.

10.3.2. Sample Size

Sample size is the number of participants to include in a study. It can refer to patients, providers or organizations depending on how the unit of allocation is defined. There are four parts to calculating sample size. They are described below ( Noordzij et al., 2010 ).

Significance level – This refers to the probability that a positive finding is due to chance alone. It is usually set at 0.05, which means having a less than 5% chance of drawing a false positive conclusion. Power – This refers to the ability to detect the true effect based on a sample from the population. It is usually set at 0.8, which means having at least an 80% chance of drawing a correct conclusion. Effect size – This refers to the minimal clinically relevant difference that can be detected between comparison groups. For continuous variables, the effect is a numerical value such as a 10-kilogram weight difference between two groups. For categorical variables, it is a percentage such as a 10% difference in medication error rates. Variability – This refers to the population variance of the outcome of interest, which is often unknown and is estimated by way of standard deviation ( sd ) from pilot or previous studies for continuous outcome.

Sample Size Equations for Comparing Two Groups with Continuous and Categorical Outcome Variables.

An example of sample size calculation for an rct to examine the effect of cds on improving systolic blood pressure of hypertensive patients is provided in the Appendix. Refer to the Biomath website from Columbia University (n.d.) for a simple Web-based sample size / power calculator.

10.3.3. Sources of Bias

There are five common sources of biases in comparative studies. They are selection, performance, detection, attrition and reporting biases ( Higgins & Green, 2011 ). These biases, and the ways to minimize them, are described below ( Vervloet et al., 2012 ).

Selection or allocation bias – This refers to differences between the composition of comparison groups in terms of the response to the intervention. An example is having sicker or older patients in the control group than those in the intervention group when evaluating the effect of emr reminders. To reduce selection bias, one can apply randomization and concealment when assigning participants to groups and ensure their compositions are comparable at baseline. Performance bias – This refers to differences between groups in the care they received, aside from the intervention being evaluated. An example is the different ways by which reminders are triggered and used within and across groups such as electronic, paper and phone reminders for patients and providers. To reduce performance bias, one may standardize the intervention and blind participants from knowing whether an intervention was received and which intervention was received. Detection or measurement bias – This refers to differences between groups in how outcomes are determined. An example is where outcome assessors pay more attention to outcomes of patients known to be in the intervention group. To reduce detection bias, one may blind assessors from participants when measuring outcomes and ensure the same timing for assessment across groups. Attrition bias – This refers to differences between groups in ways that participants are withdrawn from the study. An example is the low rate of participant response in the intervention group despite having received reminders for follow-up care. To reduce attrition bias, one needs to acknowledge the dropout rate and analyze data according to an intent-to-treat principle (i.e., include data from those who dropped out in the analysis). Reporting bias – This refers to differences between reported and unreported findings. Examples include biases in publication, time lag, citation, language and outcome reporting depending on the nature and direction of the results. To reduce reporting bias, one may make the study protocol available with all pre-specified outcomes and report all expected outcomes in published results.

10.3.4. Confounders

Confounders are factors other than the intervention of interest that can distort the effect because they are associated with both the intervention and the outcome. For instance, in a study to demonstrate whether the adoption of a medication order entry system led to lower medication costs, there can be a number of potential confounders that can affect the outcome. These may include severity of illness of the patients, provider knowledge and experience with the system, and hospital policy on prescribing medications ( Harris et al., 2006 ). Another example is the evaluation of the effect of an antibiotic reminder system on the rate of post-operative deep venous thromboses ( dvt s). The confounders can be general improvements in clinical practice during the study such as prescribing patterns and post-operative care that are not related to the reminders ( Friedman & Wyatt, 2006 ).

To control for confounding effects, one may consider the use of matching, stratification and modelling. Matching involves the selection of similar groups with respect to their composition and behaviours. Stratification involves the division of participants into subgroups by selected variables, such as comorbidity index to control for severity of illness. Modelling involves the use of statistical techniques such as multiple regression to adjust for the effects of specific variables such as age, sex and/or severity of illness ( Higgins & Green, 2011 ).

10.3.5. Guidelines on Quality and Reporting

There are guidelines on the quality and reporting of comparative studies. The grade (Grading of Recommendations Assessment, Development and Evaluation) guidelines provide explicit criteria for rating the quality of studies in randomized trials and observational studies ( Guyatt et al., 2011 ). The extended consort (Consolidated Standards of Reporting Trials) Statements for non-pharmacologic trials ( Boutron, Moher, Altman, Schulz, & Ravaud, 2008 ), pragmatic trials ( Zwarestein et al., 2008 ), and eHealth interventions ( Baker et al., 2010 ) provide reporting guidelines for randomized trials.

The grade guidelines offer a system of rating quality of evidence in systematic reviews and guidelines. In this approach, to support estimates of intervention effects rct s start as high-quality evidence and observational studies as low-quality evidence. For each outcome in a study, five factors may rate down the quality of evidence. The final quality of evidence for each outcome would fall into one of high, moderate, low, and very low quality. These factors are listed below (for more details on the rating system, refer to Guyatt et al., 2011 ).

Design limitations – For rct s they cover the lack of allocation concealment, lack of blinding, large loss to follow-up, trial stopped early or selective outcome reporting. Inconsistency of results – Variations in outcomes due to unexplained heterogeneity. An example is the unexpected variation of effects across subgroups of patients by severity of illness in the use of preventive care reminders. Indirectness of evidence – Reliance on indirect comparisons due to restrictions in study populations, intervention, comparator or outcomes. An example is the 30-day readmission rate as a surrogate outcome for quality of computer-supported emergency care in hospitals. Imprecision of results – Studies with small sample size and few events typically would have wide confidence intervals and are considered of low quality. Publication bias – The selective reporting of results at the individual study level is already covered under design limitations, but is included here for completeness as it is relevant when rating quality of evidence across studies in systematic reviews.

The original consort Statement has 22 checklist items for reporting rct s. For non-pharmacologic trials extensions have been made to 11 items. For pragmatic trials extensions have been made to eight items. These items are listed below. For further details, readers can refer to Boutron and colleagues (2008) and the consort website ( consort , n.d.).

Title and abstract – one item on the means of randomization used. Introduction – one item on background, rationale, and problem addressed by the intervention. Methods – 10 items on participants, interventions, objectives, outcomes, sample size, randomization (sequence generation, allocation concealment, implementation), blinding (masking), and statistical methods. Results – seven items on participant flow, recruitment, baseline data, numbers analyzed, outcomes and estimation, ancillary analyses, adverse events. Discussion – three items on interpretation, generalizability, overall evidence.

The consort Statement for eHealth interventions describes the relevance of the consort recommendations to the design and reporting of eHealth studies with an emphasis on Internet-based interventions for direct use by patients, such as online health information resources, decision aides and phr s. Of particular importance is the need to clearly define the intervention components, their role in the overall care process, target population, implementation process, primary and secondary outcomes, denominators for outcome analyses, and real world potential (for details refer to Baker et al., 2010 ).

10.4. Case Examples

10.4.1. pragmatic rct in vascular risk decision support.

Holbrook and colleagues (2011) conducted a pragmatic rct to examine the effects of a cds intervention on vascular care and outcomes for older adults. The study is summarized below.

Setting – Community-based primary care practices with emr s in one Canadian province. Participants – English-speaking patients 55 years of age or older with diagnosed vascular disease, no cognitive impairment and not living in a nursing home, who had a provider visit in the past 12 months. Intervention – A Web-based individualized vascular tracking and advice cds system for eight top vascular risk factors and two diabetic risk factors, for use by both providers and patients and their families. Providers and staff could update the patient’s profile at any time and the cds algorithm ran nightly to update recommendations and colour highlighting used in the tracker interface. Intervention patients had Web access to the tracker, a print version mailed to them prior to the visit, and telephone support on advice. Design – Pragmatic, one-year, two-arm, multicentre rct , with randomization upon patient consent by phone, using an allocation-concealed online program. Randomization was by patient with stratification by provider using a block size of six. Trained reviewers examined emr data and conducted patient telephone interviews to collect risk factors, vascular history, and vascular events. Providers completed questionnaires on the intervention at study end. Patients had final 12-month lab checks on urine albumin, low-density lipoprotein cholesterol, and A1c levels. Outcomes – Primary outcome was based on change in process composite score ( pcs ) computed as the sum of frequency-weighted process score for each of the eight main risk factors with a maximum score of 27. The process was considered met if a risk factor had been checked. pcs was measured at baseline and study end with the difference as the individual primary outcome scores. The main secondary outcome was a clinical composite score ( ccs ) based on the same eight risk factors compared in two ways: a comparison of the mean number of clinical variables on target and the percentage of patients with improvement between the two groups. Other secondary outcomes were actual vascular event rates, individual pcs and ccs components, ratings of usability, continuity of care, patient ability to manage vascular risk, and quality of life using the EuroQol five dimensions questionnaire ( eq-5D) . Analysis – 1,100 patients were needed to achieve 90% power in detecting a one-point pcs difference between groups with a standard deviation of five points, two-tailed t -test for mean difference at 5% significance level, and a withdrawal rate of 10%. The pcs , ccs and eq-5D scores were analyzed using a generalized estimating equation accounting for clustering within providers. Descriptive statistics and χ2 tests or exact tests were done with other outcomes. Findings – 1,102 patients and 49 providers enrolled in the study. The intervention group with 545 patients had significant pcs improvement with a difference of 4.70 ( p < .001) on a 27-point scale. The intervention group also had significantly higher odds of rating improvements in their continuity of care (4.178, p < .001) and ability to improve their vascular health (3.07, p < .001). There was no significant change in vascular events, clinical variables and quality of life. Overall the cds intervention led to reduced vascular risks but not to improved clinical outcomes in a one-year follow-up.

10.4.2. Non-randomized Experiment in Antibiotic Prescribing in Primary Care

Mainous, Lambourne, and Nietert (2013) conducted a prospective non-randomized trial to examine the impact of a cds system on antibiotic prescribing for acute respiratory infections ( ari s) in primary care. The study is summarized below.

Setting – A primary care research network in the United States whose members use a common emr and pool data quarterly for quality improvement and research studies. Participants – An intervention group with nine practices across nine states, and a control group with 61 practices. Intervention – Point-of-care cds tool as customizable progress note templates based on existing emr features. cds recommendations reflect Centre for Disease Control and Prevention ( cdc ) guidelines based on a patient’s predominant presenting symptoms and age. cds was used to assist in ari diagnosis, prompt antibiotic use, record diagnosis and treatment decisions, and access printable patient and provider education resources from the cdc . Design – The intervention group received a multi-method intervention to facilitate provider cds adoption that included quarterly audit and feedback, best practice dissemination meetings, academic detailing site visits, performance review and cds training. The control group did not receive information on the intervention, the cds or education. Baseline data collection was for three months with follow-up of 15 months after cds implementation. Outcomes – The outcomes were frequency of inappropriate prescribing during an ari episode, broad-spectrum antibiotic use and diagnostic shift. Inappropriate prescribing was computed by dividing the number of ari episodes with diagnoses in the inappropriate category that had an antibiotic prescription by the total number of ari episodes with diagnosis for which antibiotics are inappropriate. Broad-spectrum antibiotic use was computed by all ari episodes with a broad-spectrum antibiotic prescription by the total number of ari episodes with an antibiotic prescription. Antibiotic drift was computed in two ways: dividing the number of ari episodes with diagnoses where antibiotics are appropriate by the total number of ari episodes with an antibiotic prescription; and dividing the number of ari episodes where antibiotics were inappropriate by the total number of ari episodes. Process measure included frequency of cds template use and whether the outcome measures differed by cds usage. Analysis – Outcomes were measured quarterly for each practice, weighted by the number of ari episodes during the quarter to assign greater weight to practices with greater numbers of relevant episodes and to periods with greater numbers of relevant episodes. Weighted means and 95% ci s were computed separately for adult and pediatric (less than 18 years of age) patients for each time period for both groups. Baseline means in outcome measures were compared between the two groups using weighted independent-sample t -tests. Linear mixed models were used to compare changes over the 18-month period. The models included time, intervention status, and were adjusted for practice characteristics such as specialty, size, region and baseline ari s. Random practice effects were included to account for clustering of repeated measures on practices over time. P -values of less than 0.05 were considered significant. Findings – For adult patients, inappropriate prescribing in ari episodes declined more among the intervention group (-0.6%) than the control group (4.2%)( p = 0.03), and prescribing of broad-spectrum antibiotics declined by 16.6% in the intervention group versus an increase of 1.1% in the control group ( p < 0.0001). For pediatric patients, there was a similar decline of 19.7% in the intervention group versus an increase of 0.9% in the control group ( p < 0.0001). In summary, the cds had a modest effect in reducing inappropriate prescribing for adults, but had a substantial effect in reducing the prescribing of broad-spectrum antibiotics in adult and pediatric patients.

10.4.3. Interrupted Time Series on EHR Impact in Nursing Care

Dowding, Turley, and Garrido (2012) conducted a prospective its study to examine the impact of ehr implementation on nursing care processes and outcomes. The study is summarized below.

Setting – Kaiser Permanente ( kp ) as a large not-for-profit integrated healthcare organization in the United States. Participants – 29 kp hospitals in the northern and southern regions of California. Intervention – An integrated ehr system implemented at all hospitals with cpoe , nursing documentation and risk assessment tools. The nursing component for risk assessment documentation of pressure ulcers and falls was consistent across hospitals and developed by clinical nurses and informaticists by consensus. Design – its design with monthly data on pressure ulcers and quarterly data on fall rates and risk collected over seven years between 2003 and 2009. All data were collected at the unit level for each hospital. Outcomes – Process measures were the proportion of patients with a fall risk assessment done and the proportion with a hospital-acquired pressure ulcer ( hapu ) risk assessment done within 24 hours of admission. Outcome measures were fall and hapu rates as part of the unit-level nursing care process and nursing sensitive outcome data collected routinely for all California hospitals. Fall rate was defined as the number of unplanned descents to the floor per 1,000 patient days, and hapu rate was the percentage of patients with stages i-IV or unstageable ulcer on the day of data collection. Analysis – Fall and hapu risk data were synchronized using the month in which the ehr was implemented at each hospital as time zero and aggregated across hospitals for each time period. Multivariate regression analysis was used to examine the effect of time, region and ehr . Findings – The ehr was associated with significant increase in document rates for hapu risk (2.21; 95% CI 0.67 to 3.75) and non-significant increase for fall risk (0.36; -3.58 to 4.30). The ehr was associated with 13% decrease in hapu rates (-0.76; -1.37 to -0.16) but no change in fall rates (-0.091; -0.29 to 011). Hospital region was a significant predictor of variation for hapu (0.72; 0.30 to 1.14) and fall rates (0.57; 0.41 to 0.72). During the study period, hapu rates decreased significantly (-0.16; -0.20 to -0.13) but not fall rates (0.0052; -0.01 to 0.02). In summary, ehr implementation was associated with a reduction in the number of hapu s but not patient falls, and changes over time and hospital region also affected outcomes.

10.5. Summary

In this chapter we introduced randomized and non-randomized experimental designs as two types of comparative studies used in eHealth evaluation. Randomization is the highest quality design as it reduces bias, but it is not always feasible. The methodological issues addressed include choice of variables, sample size, sources of biases, confounders, and adherence to reporting guidelines. Three case examples were included to show how eHealth comparative studies are done.

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• Columbia University. (n.d.). Statistics: sample size / power calculation. Biomath (Division of Biomathematics/Biostatistics), Department of Pediatrics. New York: Columbia University Medical Centre. Retrieved from http://www ​.biomath.info/power/index.htm .
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• Cochrane Collaboration. Cochrane handbook. London: Author; (n.d.) Retrieved from http://handbook ​.cochrane.org/
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• Dowding D. W., Turley M., Garrido T. The impact of an electronic health record on nurse sensitive patient outcomes: an interrupted time series analysis. Journal of the American Medical Informatics Association. 2012; 19 (4):615–620. [ PMC free article : PMC3384108 ] [ PubMed : 22174327 ]
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• Harris A. D., McGregor J. C., Perencevich E. N., Furuno J. P., Zhu J., Peterson D. E., Finkelstein J. The use and interpretation of quasi-experimental studies in medical informatics. Journal of the American Medical Informatics Association. 2006; 13 (1):16–23. [ PMC free article : PMC1380192 ] [ PubMed : 16221933 ]
• The Cochrane Collaboration. Cochrane handbook for systematic reviews of interventions. Higgins J. P. T., Green S., editors. London: 2011. (Version 5.1.0, updated March 2011) Retrieved from http://handbook ​.cochrane.org/
• Holbrook A., Pullenayegum E., Thabane L., Troyan S., Foster G., Keshavjee K. et al. Curnew G. Shared electronic vascular risk decision support in primary care. Computerization of medical practices for the enhancement of therapeutic effectiveness (compete III) randomized trial. Archives of Internal Medicine. 2011; 171 (19):1736–1744. [ PubMed : 22025430 ]
• Mainous III A. G., Lambourne C. A., Nietert P.J. Impact of a clinical decision support system on antibiotic prescribing for acute respiratory infections in primary care: quasi-experimental trial. Journal of the American Medical Informatics Association. 2013; 20 (2):317–324. [ PMC free article : PMC3638170 ] [ PubMed : 22759620 ]
• Noordzij M., Tripepi G., Dekker F. W., Zoccali C., Tanck M. W., Jager K.J. Sample size calculations: basic principles and common pitfalls. Nephrology Dialysis Transplantation. 2010; 25 (5):1388–1393. Retrieved from http://ndt ​.oxfordjournals ​.org/content/early/2010/01/12/ndt ​.gfp732.short . [ PubMed : 20067907 ]
• Vervloet M., Linn A. J., van Weert J. C. M., de Bakker D. H., Bouvy M. L., van Dijk L. The effectiveness of interventions using electronic reminders to improve adherence to chronic medication: A systematic review of the literature. Journal of the American Medical Informatics Association. 2012; 19 (5):696–704. [ PMC free article : PMC3422829 ] [ PubMed : 22534082 ]
• Zwarenstein M., Treweek S., Gagnier J. J., Altman D. G., Tunis S., Haynes B., Oxman A. D., Moher D. for the consort and Pragmatic Trials in Healthcare (Practihc) groups. Improving the reporting of pragmatic trials: an extension of the consort statement. British Medical Journal. 2008; 337 :a2390. [ PMC free article : PMC3266844 ] [ PubMed : 19001484 ] [ CrossRef ]
• Zwarenstein M., Treweek S. What kind of randomized trials do we need? Canadian Medical Association Journal. 2009; 180 (10):998–1000. [ PMC free article : PMC2679816 ] [ PubMed : 19372438 ]

Appendix. Example of Sample Size Calculation

This is an example of sample size calculation for an rct that examines the effect of a cds system on reducing systolic blood pressure in hypertensive patients. The case is adapted from the example described in the publication by Noordzij et al. (2010) .

(a) Systolic blood pressure as a continuous outcome measured in mmHg

Based on similar studies in the literature with similar patients, the systolic blood pressure values from the comparison groups are expected to be normally distributed with a standard deviation of 20 mmHg. The evaluator wishes to detect a clinically relevant difference of 15 mmHg in systolic blood pressure as an outcome between the intervention group with cds and the control group without cds . Assuming a significance level or alpha of 0.05 for 2-tailed t -test and power of 0.80, the corresponding multipliers 1 are 1.96 and 0.842, respectively. Using the sample size equation for continuous outcome below we can calculate the sample size needed for the above study.

n = 2[(a+b)2σ2]/(μ1-μ2)2 where

n = sample size for each group

μ1 = population mean of systolic blood pressures in intervention group

μ2 = population mean of systolic blood pressures in control group

μ1- μ2 = desired difference in mean systolic blood pressures between groups

σ = population variance

a = multiplier for significance level (or alpha)

b = multiplier for power (or 1-beta)

Providing the values in the equation would give the sample size (n) of 28 samples per group as the result

n = 2[(1.96+0.842)2(202)]/152 or 28 samples per group

(b) Systolic blood pressure as a categorical outcome measured as below or above 140 mmHg (i.e., hypertension yes/no)

In this example a systolic blood pressure from a sample that is above 140 mmHg is considered an event of the patient with hypertension. Based on published literature the proportion of patients in the general population with hypertension is 30%. The evaluator wishes to detect a clinically relevant difference of 10% in systolic blood pressure as an outcome between the intervention group with cds and the control group without cds . This means the expected proportion of patients with hypertension is 20% (p1 = 0.2) in the intervention group and 30% (p2 = 0.3) in the control group. Assuming a significance level or alpha of 0.05 for 2-tailed t -test and power of 0.80 the corresponding multipliers are 1.96 and 0.842, respectively. Using the sample size equation for categorical outcome below, we can calculate the sample size needed for the above study.

n = [(a+b)2(p1q1+p2q2)]/χ2

p1 = proportion of patients with hypertension in intervention group

q1 = proportion of patients without hypertension in intervention group (or 1-p1)

p2 = proportion of patients with hypertension in control group

q2 = proportion of patients without hypertension in control group (or 1-p2)

χ = desired difference in proportion of hypertensive patients between two groups

Providing the values in the equation would give the sample size (n) of 291 samples per group as the result

n = [(1.96+0.842)2((0.2)(0.8)+(0.3)(0.7))]/(0.1)2 or 291 samples per group

From Table 3 on p. 1392 of Noordzij et al. (2010).

This publication is licensed under a Creative Commons License, Attribution-Noncommercial 4.0 International License (CC BY-NC 4.0): see https://creativecommons.org/licenses/by-nc/4.0/

• Cite this Page Lau F, Holbrook A. Chapter 10 Methods for Comparative Studies. In: Lau F, Kuziemsky C, editors. Handbook of eHealth Evaluation: An Evidence-based Approach [Internet]. Victoria (BC): University of Victoria; 2017 Feb 27.
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Comparative Research Methods

Linda Hantrais is Director of the European Research Centre, Loughborough University. She is convenor of the Cross-National Research Group and series editor of Cross-National Research Papers . The main focus of her research is cross-national theory, method and practice, particularly with reference to social policy. She has conducted a number of comparative studies, including ESRC/CNAF/European Commission-funded collaborative projects on women in professional occupations in Britain and France and on families and family policies in Europe. Her recent publications include a co-edited book, with Steen Mangen, on Cross-National Research Methods in the Social Sciences (Pinter, 1996).

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Comparison in qualitative research.

• Lesley Bartlett Lesley Bartlett University of Wisconsin–Madison
•  and  Frances Vavrus Frances Vavrus University of Minnesota
• https://doi.org/10.1093/acrefore/9780190264093.013.621
• Published online: 30 June 2020

Comparison is a valuable and widely touted analytical technique in social research, but different disciplines and fields have markedly different notions of comparison. There are at least two important logics for comparison. The first, the logic of juxtaposition, is guided by a neopositivist orientation. It uses a regularity theory of causation; it structures the study by defining cases, variables, and units of analysis a priori ; and it decontextualizes knowledge. The second, the logic of tracing, engages a realist theory of causation and examines how processes unfold, influenced by actors and the meanings they make, over time, in different locations, and at different scales. These two logics of comparison lead to distinct methodological techniques. However, with either logic of comparison, three dangers merit attention: decontextualization, commensurability, and ethnocentrism. One promising research heuristic that attends to different logics of comparison while avoiding these dangers is the comparative case study (CCS) approach. CCS entails three axes of comparison. The horizontal axis encourages comparison of how similar policies and practices unfold across sites at roughly the same level or scale, for example across a set of schools or across home, school, religious institution, and community organization. The vertical axis urges comparison across micro-, meso-, and macro-levels or scales. For example, a study of bilingual education in the United States should attend not only to homes, communities, classroom, and school dynamics (the micro-level), but also to meso-level district, state, and federal policies, as well as to factors influencing international mobility at the macro-level. Finally, the transversal axis, which emphasizes change over time, urges scholars to situate historically the processes or relations under consideration.

• qualitative methods
• comparative case studies
• epistemology
• horizontal comparison
• vertical comparison
• transversal comparison

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Characteristics of a Comparative Research Design

Hannah richardson, 28 jun 2018.

Comparative research essentially compares two groups in an attempt to draw a conclusion about them. Researchers attempt to identify and analyze similarities and differences between groups, and these studies are most often cross-national, comparing two separate people groups. Comparative studies can be used to increase understanding between cultures and societies and create a foundation for compromise and collaboration. These studies contain both quantitative and qualitative research methods.

Explore this article

• Comparative Quantitative
• Comparative Qualitative
• When to Use It
• When Not to Use It

1 Comparative Quantitative

Quantitative, or experimental, research is characterized by the manipulation of an independent variable to measure and explain its influence on a dependent variable. Because comparative research studies analyze two different groups -- which may have very different social contexts -- it is difficult to establish the parameters of research. Such studies might seek to compare, for example, large amounts of demographic or employment data from different nations that define or measure relevant research elements differently.

However, the methods for statistical analysis of data inherent in quantitative research are still helpful in establishing correlations in comparative studies. Also, the need for a specific research question in quantitative research helps comparative researchers narrow down and establish a more specific comparative research question.

2 Comparative Qualitative

Qualitative, or nonexperimental, is characterized by observation and recording outcomes without manipulation. In comparative research, data are collected primarily by observation, and the goal is to determine similarities and differences that are related to the particular situation or environment of the two groups. These similarities and differences are identified through qualitative observation methods. Additionally, some researchers have favored designing comparative studies around a variety of case studies in which individuals are observed and behaviors are recorded. The results of each case are then compared across people groups.

3 When to Use It

Comparative research studies should be used when comparing two people groups, often cross-nationally. These studies analyze the similarities and differences between these two groups in an attempt to better understand both groups. Comparisons lead to new insights and better understanding of all participants involved. These studies also require collaboration, strong teams, advanced technologies and access to international databases, making them more expensive. Use comparative research design when the necessary funding and resources are available.

4 When Not to Use It

Do not use comparative research design with little funding, limited access to necessary technology and few team members. Because of the larger scale of these studies, they should be conducted only if adequate population samples are available. Additionally, data within these studies require extensive measurement analysis; if the necessary organizational and technological resources are not available, a comparative study should not be used. Do not use a comparative design if data are not able to be measured accurately and analyzed with fidelity and validity.

• 1 San Jose State University: Selected Issues in Study Design
• 2 University of Surrey: Social Research Update 13: Comparative Research Methods

About the Author

Hannah Richardson has a Master's degree in Special Education from Vanderbilt University and a Bacheor of Arts in English. She has been a writer since 2004 and wrote regularly for the sports and features sections of "The Technician" newspaper, as well as "Coastwach" magazine. Richardson also served as the co-editor-in-chief of "Windhover," an award-winning literary and arts magazine. She is currently teaching at a middle school.

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How to Do Comparative Analysis in Research ( Examples )

Comparative analysis is a method that is widely used in social science . It is a method of comparing two or more items with an idea of uncovering and discovering new ideas about them. It often compares and contrasts social structures and processes around the world to grasp general patterns. Comparative analysis tries to understand the study and explain every element of data that comparing. 

We often compare and contrast in our daily life. So it is usual to compare and contrast the culture and human society. We often heard that ‘our culture is quite good than theirs’ or ‘their lifestyle is better than us’. In social science, the social scientist compares primitive, barbarian, civilized, and modern societies. They use this to understand and discover the evolutionary changes that happen to society and its people.  It is not only used to understand the evolutionary processes but also to identify the differences, changes, and connections between societies.

Most social scientists are involved in comparative analysis. Macfarlane has thought that “On account of history, the examinations are typically on schedule, in that of other sociologies, transcendently in space. The historian always takes their society and compares it with the past society, and analyzes how far they differ from each other.

The comparative method of social research is a product of 19 th -century sociology and social anthropology. Sociologists like Emile Durkheim, Herbert Spencer Max Weber used comparative analysis in their works. For example, Max Weber compares the protestant of Europe with Catholics and also compared it with other religions like Islam, Hinduism, and Confucianism.

To do a systematic comparison we need to follow different elements of the method.

1. Methods of comparison The comparison method

In social science, we can do comparisons in different ways. It is merely different based on the topic, the field of study. Like Emile Durkheim compare societies as organic solidarity and mechanical solidarity. The famous sociologist Emile Durkheim provides us with three different approaches to the comparative method. Which are;

• The first approach is to identify and select one particular society in a fixed period. And by doing that, we can identify and determine the relationship, connections and differences exist in that particular society alone. We can find their religious practices, traditions, law, norms etc.
•  The second approach is to consider and draw various societies which have common or similar characteristics that may vary in some ways. It may be we can select societies at a specific period, or we can select societies in the different periods which have common characteristics but vary in some ways. For example, we can take European and American societies (which are universally similar characteristics) in the 20 th century. And we can compare and contrast their society in terms of law, custom, tradition, etc. 
• The third approach he envisaged is to take different societies of different times that may share some similar characteristics or maybe show revolutionary changes. For example, we can compare modern and primitive societies which show us revolutionary social changes.

2 . The unit of comparison

We cannot compare every aspect of society. As we know there are so many things that we cannot compare. The very success of the compare method is the unit or the element that we select to compare. We are only able to compare things that have some attributes in common. For example, we can compare the existing family system in America with the existing family system in Europe. But we are not able to compare the food habits in china with the divorce rate in America. It is not possible. So, the next thing you to remember is to consider the unit of comparison. You have to select it with utmost care.

3. The motive of comparison

As another method of study, a comparative analysis is one among them for the social scientist. The researcher or the person who does the comparative method must know for what grounds they taking the comparative method. They have to consider the strength, limitations, weaknesses, etc. He must have to know how to do the analysis.

Steps of the comparative method

1. Setting up of a unit of comparison

As mentioned earlier, the first step is to consider and determine the unit of comparison for your study. You must consider all the dimensions of your unit. This is where you put the two things you need to compare and to properly analyze and compare it. It is not an easy step, we have to systematically and scientifically do this with proper methods and techniques. You have to build your objectives, variables and make some assumptions or ask yourself about what you need to study or make a hypothesis for your analysis.

The best casings of reference are built from explicit sources instead of your musings or perceptions. To do that you can select some attributes in the society like marriage, law, customs, norms, etc. by doing this you can easily compare and contrast the two societies that you selected for your study. You can set some questions like, is the marriage practices of Catholics are different from Protestants? Did men and women get an equal voice in their mate choice? You can set as many questions that you wanted. Because that will explore the truth about that particular topic. A comparative analysis must have these attributes to study. A social scientist who wishes to compare must develop those research questions that pop up in your mind. A study without those is not going to be a fruitful one.

2. Grounds of comparison

The grounds of comparison should be understandable for the reader. You must acknowledge why you selected these units for your comparison. For example, it is quite natural that a person who asks why you choose this what about another one? What is the reason behind choosing this particular society? If a social scientist chooses primitive Asian society and primitive Australian society for comparison, he must acknowledge the grounds of comparison to the readers. The comparison of your work must be self-explanatory without any complications.

If you choose two particular societies for your comparative analysis you must convey to the reader what are you intended to choose this and the reason for choosing that society in your analysis.

3 . Report or thesis

The main element of the comparative analysis is the thesis or the report. The report is the most important one that it must contain all your frame of reference. It must include all your research questions, objectives of your topic, the characteristics of your two units of comparison, variables in your study, and last but not least the finding and conclusion must be written down. The findings must be self-explanatory because the reader must understand to what extent did they connect and what are their differences. For example, in Emile Durkheim’s Theory of Division of Labour, he classified organic solidarity and Mechanical solidarity . In which he means primitive society as Mechanical solidarity and modern society as Organic Solidarity. Like that you have to mention what are your findings in the thesis.

4. Relationship and linking one to another

Your paper must link each point in the argument. Without that the reader does not understand the logical and rational advance in your analysis. In a comparative analysis, you need to compare the ‘x’ and ‘y’ in your paper. (x and y mean the two-unit or things in your comparison). To do that you can use likewise, similarly, on the contrary, etc. For example, if we do a comparison between primitive society and modern society we can say that; ‘in the primitive society the division of labour is based on gender and age on the contrary (or the other hand), in modern society, the division of labour is based on skill and knowledge of a person.

Demerits of comparison

Comparative analysis is not always successful. It has some limitations. The broad utilization of comparative analysis can undoubtedly cause the feeling that this technique is a solidly settled, smooth, and unproblematic method of investigation, which because of its undeniable intelligent status can produce dependable information once some specialized preconditions are met acceptably.

Perhaps the most fundamental issue here respects the independence of the unit picked for comparison. As different types of substances are gotten to be analyzed, there is frequently a fundamental and implicit supposition about their independence and a quiet propensity to disregard the mutual influences and common impacts among the units.

One more basic issue with broad ramifications concerns the decision of the units being analyzed. The primary concern is that a long way from being a guiltless as well as basic assignment, the decision of comparison units is a basic and precarious issue. The issue with this sort of comparison is that in such investigations the depictions of the cases picked for examination with the principle one will in general turn out to be unreasonably streamlined, shallow, and stylised with contorted contentions and ends as entailment.

However, a comparative analysis is as yet a strategy with exceptional benefits, essentially due to its capacity to cause us to perceive the restriction of our psyche and check against the weaknesses and hurtful results of localism and provincialism. We may anyway have something to gain from history specialists’ faltering in utilizing comparison and from their regard for the uniqueness of settings and accounts of people groups. All of the above, by doing the comparison we discover the truths the underlying and undiscovered connection, differences that exist in society.

Also Read: How to write a Sociology Analysis? Explained with Examples

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What is comparative method in research methodology?

The comparative method, so called, is the process of comparing situations, groups, cultures, or whatever, which are similar and yet which differ in known ways. … Constant comparative method is label given to a procedure designed for analysing qualitative data.

What is an example of the comparative method?

The comparative method is where the researcher collects data about different social groups (eg working-class; middle-class and upper-class) and then compares one group with another to identify what is evident in one group but not another. … Durkheim’s study on suicide was an example of the comparative method.

What is comparative descriptive method?

In descriptive-comparative research, the researcher considers 2 variables that are not manipulated, and establish a formal procedure to conclude that one is better than the other. For example, an examination body wants to determine the better method of conducting tests between paper-based and computer-based tests.

What is comparative politics methodology?

Comparative politics is the systematic study and comparison of the diverse political systems in the world. It is comparative in searching to explain why different political systems have similarities or differences and how developmental changes came to be between them.

What is a comparative study in research?

Comparative study looks at two or more similar groups, individuals, or conditions by comparing them. This comparison often focuses on a few specific characteristics. … Comparative study is a type of research that is necessary to achieve higher studies.

What is the significance of comparative method?

Comparative methods seek evidence for adaptive evolution by investigating how the characteristics of organisms, such as their size, shape, life histories, and behaviors, evolve together across species. They are one of evolutionary biology’s most enduring approaches for testing hypotheses of adaptation.

What is the comparative method in sociology?

The Phrase comparative method refers to the method of comparing different. societies or groups within the same society to show whether and why they are. similar or different in certain respects.

What is the comparative method in anthropology?

The basic operation in the comparative method is an arrangement of social or cultural conditions observed among existing peoples into a series that is then taken to represent a process of evolution.

What is comparative method in psychology?

The comparative method involves comparing the similarities and differences among species to gain an understanding of evolutionary relationships. The comparative method can also be used to compare modern species of animals to ancient species.

What is comparative descriptive method in philosophy?

Comparative philosophysometimes called cross-cultural philosophyis a subfield of philosophy in which philosophers work on problems by intentionally setting into dialogue various sources from across cultural, linguistic, and philosophical streams.

What is a descriptive comparison?

Descriptive Comparison aims at describing and perhaps also explaining the invariances of the objects. It does not aim at generating changes in the objects, on the contrary, it usually tries to avoid them. … This is the technique of Normative Comparison.

What is a descriptive method in research?

Descriptive research refers to the methods that describe the characteristics of the variables under study. This methodology focuses on answering questions relating to what than the why of the research subject.

What are the 5 methods of political science?

Political science is methodologically diverse and appropriates many methods originating in psychology, social research and cognitive neuroscience. Approaches include positivism, interpretivism, rational choice theory, behaviouralism, structuralism, post-structuralism, realism, institutionalism, and pluralism.

What are methods of political analysis?

Political scientists rely on a variety of empirical methods and statistical models, such as linear regression, maximum likelihood estimation, laboratory and survey experiments, and social network analysis. Mathematical models are also important tools for rigorous theoretical analysis.

What is the examples of comparative study?

Examples of ongoing comparative research surveys include the Gallup Polls (since 1945), the General Social Survey (since 1972), the Eurobaromtre (since 1973), the European Community Household Study (since 1994), and the International Social Survey Program (ISSP), which, since 1984, has conducted general social

What research design is comparative study?

Comparative research essentially compares two groups in an attempt to draw a conclusion about them. Researchers attempt to identify and analyze similarities and differences between groups, and these studies are most often cross-national, comparing two separate people groups.

How is a comparative study done?

There are two main approaches to organizing a comparative analysis: Alternating (point-by-point) method: Find similar points between each subject and alternate writing about each of them. Block (subject-by-subject) method: Discuss all of the first subject and then all of the second.

What is the significance of comparative method in linguistics?

The comparative method is used to reconstruct earlier forms of a language by drawing upon the evidence provided by other related languages. It may be supplemented by what is called the method of internal reconstruction.

What is the significance of the study of comparative politics?

Another reason to compare countries is to understand how countries evolve, discover patterns, and why they evolve in the way they do. Another very important reason to study comparative politics is to better understand how certain regimes work for purposes of international relations and foreign policy.

What is the significance of comparative politics?

Comparative politics is significant because it helps people understand the nature and working of political frameworks around the world. We have various types of political systems worldwide according to the authentic, social, ethnic, racial, and social history.

Who used comparative method in sociology?

One sociologist who employed comparative methods to understand variance was Max Weber, whose studies attempted to show how differences between cultures explained the different social orderings that had emerged (see for example The Protestant Ethic and the Spirit of Capitalism and Sociology of religion).

Why is comparative sociology important?

This module highlights the importance of comparison in sociology. It considers how sociologists have used historical and spatial comparisons to develop our understanding of how different types of social order are maintained and how different patterns of social change unfold.

What are the main sociological research methods?

In planning a study’s design, sociologists generally choose from four widely used methods of social investigation: survey, experiment, field research, and textual or secondary data analysis (or use of existing sources).

Why do anthropologists use the comparative approach?

The Comparative Approach in Evolutionary Anthropology and Biology. Comparison is fundamental to evolutionary anthropology. … Comparison provides a way to draw general inferences about the evolution of traits and therefore has long been the cornerstone of efforts to understand biological and cultural diversity.

What are the 5 methods of anthropology?

Some of the more common types of anthropological research methods include (1) immersion in a culture, (2) analysis of how people interact with their environment, (3) linguistic analysis, (4) archaeological analysis, and (5) analysis of human biology.

What are the methods in anthropology?

Four common qualitative anthropological data collection methods are: (1) participant observation, (2) in-depth interviews, (3) focus groups, and (4) textual analysis. Participant Observation. Participant observation is the quintessential fieldwork method in anthropology.

What is comparative psychology example?

Broadly speaking, comparative psychology refers to the study of mental faculties and behavior of animals other than human beings. … For example, tests for experimental medicines and procedures are often conducted on animals before human beings.

What is the importance of comparative psychology?

Comparative Psychology also allows us to ask whether any late-blooming human cognitive capacity might be heritable: Comparisons between humans and our closest living phylogenetic relatives, the great apes, offer ways to investigate the evolutionary history of human cognitive skills and thereby indirectly argue for the …

What is the importance of comparative psychology studies?

Comparative research has taught us much about the evolution and development of human and animal behavior. Humans share not just physical and biological similarities with other species, but also many behavioral traits and, in some of these cases, the psychological mechanisms behind them.

Graduated from ENSAT (national agronomic school of Toulouse) in plant sciences in 2018, I pursued a CIFRE doctorate under contract with Sun’Agri and INRAE ​​in Avignon between 2019 and 2022. My thesis aimed to study dynamic agrivoltaic systems, in my case in arboriculture. I love to write and share science related Stuff Here on my Website. I am currently continuing at Sun’Agri as an R&D engineer.

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Published on 30.4.2024 in Vol 26 (2024)

Physician Versus Large Language Model Chatbot Responses to Web-Based Questions From Autistic Patients in Chinese: Cross-Sectional Comparative Analysis

Authors of this article:

Original Paper

• Wenjie He 1, 2 * , MSc   ; 
• Wenyan Zhang 3 * , MSc   ; 
• Ya Jin 4 * , MSc   ; 
• Qiang Zhou 2 , BS   ; 
• Huadan Zhang 2 , BE   ; 
• Qing Xia 1 , MD  

1 Tianjin University of Traditional Chinese Medicine, Tianjin, China

2 Dongguan Rehabilitation Experimental School, Dongguan, China

3 Lanzhou University Second Hospital, Lanzhou University, Lanzhou, China

4 Dongguan Songshan Lake Central Hospital, Guangdong Medical University, Dongguan, China

*these authors contributed equally

Corresponding Author:

Qing Xia, MD

Tianjin University of Traditional Chinese Medicine

10 Poyang Lake Road

Tuanpo New Town West, Jinghai District

Tianjin, 301617

Phone: 86 13820689541

Email: [email protected]

Background: There is a dearth of feasibility assessments regarding using large language models (LLMs) for responding to inquiries from autistic patients within a Chinese-language context. Despite Chinese being one of the most widely spoken languages globally, the predominant research focus on applying these models in the medical field has been on English-speaking populations.

Objective: This study aims to assess the effectiveness of LLM chatbots, specifically ChatGPT-4 (OpenAI) and ERNIE Bot (version 2.2.3; Baidu, Inc), one of the most advanced LLMs in China, in addressing inquiries from autistic individuals in a Chinese setting.

Methods: For this study, we gathered data from DXY—a widely acknowledged, web-based, medical consultation platform in China with a user base of over 100 million individuals. A total of 100 patient consultation samples were rigorously selected from January 2018 to August 2023, amounting to 239 questions extracted from publicly available autism-related documents on the platform. To maintain objectivity, both the original questions and responses were anonymized and randomized. An evaluation team of 3 chief physicians assessed the responses across 4 dimensions: relevance, accuracy, usefulness, and empathy. The team completed 717 evaluations. The team initially identified the best response and then used a Likert scale with 5 response categories to gauge the responses, each representing a distinct level of quality. Finally, we compared the responses collected from different sources.

Results: Among the 717 evaluations conducted, 46.86% (95% CI 43.21%-50.51%) of assessors displayed varying preferences for responses from physicians, with 34.87% (95% CI 31.38%-38.36%) of assessors favoring ChatGPT and 18.27% (95% CI 15.44%-21.10%) of assessors favoring ERNIE Bot. The average relevance scores for physicians, ChatGPT, and ERNIE Bot were 3.75 (95% CI 3.69-3.82), 3.69 (95% CI 3.63-3.74), and 3.41 (95% CI 3.35-3.46), respectively. Physicians (3.66, 95% CI 3.60-3.73) and ChatGPT (3.73, 95% CI 3.69-3.77) demonstrated higher accuracy ratings compared to ERNIE Bot (3.52, 95% CI 3.47-3.57). In terms of usefulness scores, physicians (3.54, 95% CI 3.47-3.62) received higher ratings than ChatGPT (3.40, 95% CI 3.34-3.47) and ERNIE Bot (3.05, 95% CI 2.99-3.12). Finally, concerning the empathy dimension, ChatGPT (3.64, 95% CI 3.57-3.71) outperformed physicians (3.13, 95% CI 3.04-3.21) and ERNIE Bot (3.11, 95% CI 3.04-3.18).

Conclusions: In this cross-sectional study, physicians’ responses exhibited superiority in the present Chinese-language context. Nonetheless, LLMs can provide valuable medical guidance to autistic patients and may even surpass physicians in demonstrating empathy. However, it is crucial to acknowledge that further optimization and research are imperative prerequisites before the effective integration of LLMs in clinical settings across diverse linguistic environments can be realized.

Trial Registration: Chinese Clinical Trial Registry ChiCTR2300074655; https://www.chictr.org.cn/bin/project/edit?pid=199432

Introduction

Artificial intelligence (AI) has revolutionized human-computer interaction, reshaping communication, learning, and creativity paradigms [ 1 , 2 ]. A significant advancement in this realm is the emergence of large language models (LLMs), which have enabled the development of versatile digital assistants capable of understanding and generating human language [ 3 - 5 ]. Through extensive training on textual data, LLMs have acquired profound knowledge across diverse domains, facilitating coherent and contextually relevant interactions in natural language conversations. These models find applications in various domains, including natural language processing, question answering, language generation, and interactive dialogues [ 6 - 10 ]. Moreover, several studies have documented the use of LLMs in the medical field such as medication consultation [ 11 ], health education [ 12 ], and medical guidance [ 13 , 14 ].

Autism spectrum disorder (ASD) is a lifelong neurodevelopmental condition characterized by profound social and psychological challenges [ 15 , 16 ]. The estimated prevalence of ASD is approximately 1 in 36 children, with China reporting a prevalence of 1% [ 17 - 19 ], making it a significant public health concern. However, constraints on health care infrastructure development in China have led to resource shortages in numerous regions [ 20 , 21 ], exacerbating the burden on families and society. AI assistants represent underused resources for enhancing diagnosis and treatment efficiency in health care [ 22 ]. ChatGPT (OpenAI) [ 23 ] and ERNIE Bot (Baidu, Inc) [ 24 ] represent AI technologies powered by advancements in LLM. ChatGPT is a model with 20 billion parameters [ 25 ]. ERNIE Bot’s training data, as promoted at ERNIE Bot conference, includes trillions of web page data, billions of search data and image data, tens of billions of daily voice call data, and 550 billion facts of a knowledge graph, which distinguishes Baidu’s Chinese-language processing capabilities [ 26 ]. While ChatGPT gained widespread recognition for its ability to generate humanlike text across diverse topics [ 27 , 28 ], ERNIE Bot represents the forefront of AI technology in China [ 29 ]. Despite their original non–health care focus, their potential to assist in addressing patient inquiries remains unexplored mainly [ 30 - 32 ]. Implementing tiered diagnosis and treatment systems to optimize medical resource use may limit patients’ access to high-quality health care [ 33 ].

This study aims to investigate the performance of 2 conversational agents, ERNIE Bot and ChatGPT, in supporting individuals with ASD during web-based interactions. Our hypotheses are 2-fold. First, we hypothesize that ERNIE Bot, developed in China and trained on a data set that includes more Chinese text, may exhibit superior performance compared to ChatGPT, particularly regarding cultural relevance and linguistic nuances. Second, we anticipate that both ERNIE Bot and ChatGPT will demonstrate efficacy in assisting individuals with ASD, as evidenced by their ability to engage users effectively and provide helpful responses during conversational exchanges. Researchers have conducted numerous studies in English evaluating the benefits of LLMs in the medical field. Given the global significance of the Chinese language, this study aims to assess the capability of LLMs to provide high-quality and empathetic responses to health care queries posed by autistic individuals in China.

Data Source

This cross-sectional study aimed to construct a database of inquiries from autistic individuals by aggregating publicly available data from the web-based medical consultation platform DXY [ 34 ]. In China, chatbots are not permitted in clinical settings due to existing regulations, prompting the consideration of DXY as a feasible substitute. DXY is a prominent digital health care technology company with a 2-decade track record. The company offers a range of health-related applications, including high-quality health information dissemination, general knowledge services, a web-based medical consultation platform, health product e-commerce, and offline medical treatment. DXY caters to more than 100 million general users and has a user base of 5.5 million professionals, including 2.1 million physicians, constituting approximately 71% of the total number of physicians in the country.

The objective of this cross-sectional study was to analyze 200 cases to detect a 10% disparity (45% vs 55%) in responses provided by physicians and chatbots, with an assumed statistical power of 80%. We planned to use publicly accessible autism-related consultation records from the DXY website. Our sample comprised 100 randomly selected patients from the consultation records from January 2018 to August 2023. Each patient posed 1 to 3 questions, resulting in a total collection of 239 consultation queries. The qualifications of the responding health care professionals ranged from general to chief physicians.

Ethical Considerations

We adhered strictly to the terms and conditions of DXY for all analyses, and the medical ethics committee of Lanzhou University Second Hospital approved them (approval 2023A-420). The study used publicly available data from the consultation platform, did not involve personal patient information or direct test subjects, and thus did not require informed consent. We registered the study on the Chinese Clinical Trial Registry (ChiCTR2300074655).

Text Generation With an LLM Chatbot

To closely simulate an authentic medical consultation process, original questions were introduced into a new chatbot conversation from August 16, 2023, to August 30, 2023. In this dialogue, any questions previously posed with a potential impact on the outcomes were deliberately excluded. Both GPT-4 and ERNIE Bot 2.2.3 versions were used for this purpose. After eliminating expressions indicative of AI features, all responses were systematically collected and organized into a structured question-and-answer data set. The consultation content, which includes regional dialects and typographical errors, was carefully maintained to replicate a medical consultation authentically. The directly quoted content was used to prompt responses from the chatbot. The chatbot simulated a physician’s responses to mimic them while closely hiding its AI identity.

Expert Evaluation

A team of 3 chief physicians specializing in child psychiatry and pediatric health care from distinct hospitals comprehensively reviewed the original questions and physicians’ and chatbot’s responses. The evaluators were presented with complete patient questions and physician and chatbot responses. The responders’ identities were anonymized; randomized; and labeled as responses 1, 2, or 3 to ensure that evaluators remained blinded. The evaluators were instructed to thoroughly examine the entire patient question and 3 responses before assessing the quality of the interactions. The evaluation process commenced with identifying the superior response and evaluating the responses across the 4 dimensions using a Likert scale: relevance, correctness, usefulness, and humaneness. The Likert-scale options for each dimension were as follows: relevance (irrelevant, somewhat relevant, partially relevant, relevant, or very relevant), correctness (incorrect, primarily incorrect, partially correct, correct, or very correct), usefulness (useless, of limited use, somewhat useful, useful, or very useful), and humaneness (lacking, slightly humane, moderately humane, humane, or very humane). Researchers assigned ratings on a 1-5 scale, with 1 representing the lowest quality and 5 representing the highest quality. Finally, a comparative assessment of the 3 responses was performed, with the quality dimensions for response evaluation detailed in Textbox 1 .

• This dimension evaluates the alignment of responses with test results, emphasizing the system’s ability to generate appropriate text addressing specific issues rather than diverging into unrelated scenarios.

Correctness

• The correctness dimension focuses exclusively on the accuracy of information within the response, irrespective of the patient’s question. It gauges the scientific and technical precision of explanations based on best medical evidence and practices.
• This dimension combines the relevance and correctness of the system and evaluates its ability to provide non-obvious insights to patients, non-professionals, and laypersons. It includes providing appropriate recommendations, supplying relevant and accurate information, enhancing patient understanding of test results, and advising actions that optimize health care service use for the patient’s benefit.
• Empathy involves demonstrating abundant respect, effective communication, compassion, and seeking emotional connections with patients. It encompasses recognizing and empathizing with their experience, respecting their thoughts, addressing their concerns patiently, and sincerely promoting their physical and mental well-being. Additionally, empathy entails humanely fulfilling patients’ and their families’ physical, psychological, social, and spiritual needs.

Data Analysis

We used the Kruskal-Wallis H test to assess and compare the quality of the responses provided by physicians, ChatGPT, and ERNIE Bot along 4 dimensions: relevance, correctness, usefulness, and empathy. We presented the distribution of responses from each source including preferences for physicians, ChatGPT, and ERNIE Bot. Furthermore, we examined the proportion of responses that exceeded or fell below critical thresholds such as relevance, correctness, and usefulness. We compared the distribution of these threshold proportions among responses from physicians, ChatGPT, and ERNIE Bot. All statistical analyses were performed using SPSS (version 27.0; IBM), with a significance level set at P <.05 (2-tailed).

Preferred Responses

This study included 717 evaluations of 239 randomly selected consultation questions. Evaluators indicated their preferences for physicians, ChatGPT, or ERNIE Bot at proportions of 46.86% (336/717; 95% CI 43.21%-50.51%), 34.87% (250/717; 95% CI 31.38%-38.36%), and 18.27% (131/717; 95% CI 15.44%-21.10%), respectively.

The distribution of the relevance scores among the 3 groups was not entirely uniform, exhibiting statistically significant differences (H=111.67, P <.001). Physician responses demonstrated higher relevance than chatbots (ChatGPT or ERNIE Bot). Specifically, the mean relevance score for physician responses was 3.75 (95% CI 3.69-3.82), whereas the mean relevance scores for ChatGPT and ERNIE Bot were 3.69 (95% CI 3.63-3.74) and 3.41 (95% CI 3.35-3.46), respectively ( Figure 1 ). The proportion of responses rated as off topic (score <4) was lower for physicians (176/717, 24.55%; 95% CI 21.40%-27.70%) than for ChatGPT (258/717, 35.98%; 95% CI 32.47%-39.49%) and ERNIE Bot (366/717, 51.05%; 95% CI 47.39%-54.71%). Post hoc pairwise comparisons using the Bonferroni correction for significance levels revealed statistically significant differences in relevance scores between all 3 groups, specifically between physicians and ChatGPT ( P <.001), physicians and ERNIE Bot ( P <.001), and ChatGPT and ERNIE Bot ( P <.001).

The mean correctness scores for physicians, ChatGPT, and ERNIE Bot were 3.66 (95% CI 3.60-3.73), 3.73 (95% CI 3.69-3.77), and 3.52 (95% CI 3.47-3.57), respectively ( Figure 2 ). Physicians and ChatGPT achieved higher correctness scores among these 3 groups than ERNIE Bot. The distribution of the correctness scores exhibited statistically significant differences among the 3 groups (H=49.99, P <.001). When comparing the correctness scores between the 3 groups, the differences between physicians and ChatGPT ( P =.58) were not statistically significant. However, the differences between physicians and ERNIE Bot ( P <.001) and between ChatGPT and ERNIE Bot ( P <.001) were both statistically significant. The proportion of responses with errors (score <4) was similar for physicians (196/717, 27.34%; 95% CI 24.08%-30.60%) and ChatGPT (211/717, 29.43%; 95% CI 26.09%-32.77%) and lower for ERNIE Bot (309/717, 43.10%; 95% CI 39.48%-46.72%).

Among the 3 response groups, physician responses exhibited higher levels of usefulness than chatbots (ChatGPT or ERNIE Bot). Specifically, the mean usefulness score for physician responses was 3.54 (95% CI 3.47-3.62), whereas the mean usefulness scores for ChatGPT and ERNIE Bot were 3.40 (95% CI 3.34-3.47) and 3.05 (95% CI 2.99-3.12), respectively ( Figure 3 ). The proportion of responses rated as useful (score ≥4) was more significant for physicians (428/717, 59.69%; 95% CI 56.10%-63.28%) than for the chatbots (ChatGPT: 362/717, 50.49%; 95% CI 46.83%-54.15%; ERNIE Bot: 215/717, 29.99%; 95% CI 26.64%-33.34%). The distribution of the usefulness scores among the 3 groups displayed statistically significant differences (H=135.81, P <.001). Notably, all 3 pairwise comparisons of usefulness scores were statistically significant, with adjusted P values indicating significance, specifically between physicians and ChatGPT ( P <.001), physicians and ERNIE Bot ( P <.001), and ChatGPT and ERNIE Bot ( P <.001).

The mean empathy score for ChatGPT was 3.64 (95% CI 3.57-3.71), whereas the mean empathy scores for physicians and ERNIE Bot were 3.13 (95% CI 3.04-3.21) and 3.11 (95% CI 3.04-3.18), respectively ( Figure 4 ). ChatGPT’s responses received higher empathy scores than physicians and ERNIE Bot within the 3 response groups. Specifically, the proportion of responses displaying empathy (score ≥4) was higher for ChatGPT (447/717, 62.34%; 95% CI 58.79%-65.89%) than for physicians (312/717, 43.51%; 95% CI 39.88%-47.14%) and ERNIE Bot (258/717, 35.98%; 95% CI 32.47%-39.49%). The distribution of empathy scores among the 3 groups revealed significant differences (H=118.58, P <.001). When assessing empathy scores among the 3 groups, the differences between physicians and ChatGPT ( P <.001) and between ChatGPT and ERNIE Bot ( P <.001) both demonstrated statistical significance. However, the disparities between physicians and ERNIE Bot ( P =.14) were not significant.

The evaluators performed a reliability assessment, which revealed robust repeatability. The intraclass correlation coefficient values for the 4 response categories (relevance, correctness, usefulness, and empathy) were 0.812 ( P <.001), 0.831 ( P <.001), 0.818 ( P <.001), and 0.863 ( P <.001), respectively.

Principal Findings

This study evaluated the capabilities of LLMs, such as ChatGPT and ERNIE Bot, in delivering quality and empathetic responses to medical queries from Chinese autistic individuals. To simulate genuine clinical scenarios, publicly accessible data from web-based medical consultation platforms were used in this cross-sectional investigation. Notably, prevailing regulations in China strictly prohibit the use of AI-generated prescriptions. The study results revealed that expert evaluators favored responses from physicians over those generated by chatbots (ChatGPT or ERNIE Bot). In contrast to previous ophthalmology research that demonstrated chatbots outperforming physicians, our findings indicated that physicians received higher scores in relevance, correctness, and usefulness, with only a slight margin behind ChatGPT in terms of empathy. Conversely, ERNIE Bot obtained the lowest scores across all 4 dimensions: relevance, correctness, usefulness, and empathy.

Bernstein et al [ 35 ] compared the occurrence of incorrect or inappropriate content, potential harm, and degree of harm in responses from chatbots and humans. The study indicated that chatbot responses exhibited a similar likelihood of containing incorrect or inappropriate material compared with human responses (prevalence ratio [PR] 0.92, 95% CI 0.77-1.10). Moreover, no significant differences were observed between chatbot and human responses regarding potential harm (PR 0.84, 95% CI 0.67-1.07) or the degree of harm (PR 0.99, 95% CI 0.80-1.22). These results suggested that LLMs can provide appropriate ophthalmological advice for varying levels of complexity in patient questions. Shao et al [ 36 ] developed a set of 37 questions for patient education on thoracic surgery during the perioperative period, covering topics such as disease information, diagnostic procedures, perioperative complications, treatment measures, disease prevention, and perioperative care instructions. An assessment of responses in both English and Chinese contexts revealed that 92% (n=34) were considered appropriate and comprehensive. This study highlighted the potential feasibility of using ChatGPT for patient education in thoracic surgery in both English and Chinese settings. Zhu et al [ 37 ] investigated the application of ChatGPT as a mediator between physicians and patients in Chinese-speaking outpatient settings, focusing mainly on the Chinese Physician Qualification Examination. The study reported an average score of 72.4% in the clinical knowledge section, which was placed within the top 20 percentile. These findings suggested that ChatGPT can facilitate physician-patient communication in Chinese-speaking outpatient settings. Ayers et al [ 38 ] used publicly available data from a social media forum, Reddit, to compare physician responses and the ChatGPT. They randomly selected 195 dialogues with questions answered by physicians and generated chatbot responses by inputting the original questions into a new ChatGPT session. Evaluators assessed the responses from both physicians and the ChatGPT using a Likert scale, considering preferences, information quality, and empathy or interpersonal style. In 585 evaluations, 78.6% (95% CI 75%-81.8%) of evaluators preferred chatbot responses over those from physicians. These studies highlight the significant potential of chatbots in the field of medicine.

In our study, which consisted of 717 evaluations, evaluators preferred physician responses over those from chatbots, namely ChatGPT or ERNIE Bot. The preferences for physicians, ChatGPT, and ERNIE Bot were 46.86% (n=336; 95% CI 43.21%-50.51%), 34.87% (n=250; 95% CI 31.38%-38.36%), and 18.27% (n=131; 95% CI 15.44%-21.10%), respectively. Physician responses achieved higher scores in relevance, accuracy, and usefulness, with the only exception being the dimension of empathy, which ChatGPT surpassed. Our cross-sectional study’s results differed from previous reports due to several factors. First, unlike previous research primarily conducted in English-speaking settings, this study was conducted in a Chinese-speaking environment. Second, we preserved the original medical questions from autistic patients without modification to simulate authentic clinical consultations, including errors or nonstandard expressions in the queries such as misspellings or dialects. Our study contrasted with previous research, which often relies on professionally standardized queries. Furthermore, autistic patients’ queries frequently entail subjective matters such as seeking recommendations for specialist physicians or autism-related resources, lacking standardized responses, and reflecting significant cultural variations. Finally, our study used samples from a paid web-based medical consultation platform, whereas Ayers et al [ 38 ] used dialogues from public social forums on Reddit. Physicians may exhibit more proactive and diligent engagement in paid consultations.

Our study compared the performance of ChatGPT and ERNIE Bot in physician-patient interactions, with ERNIE Bot trained in Chinese and ChatGPT in English. While one might assume that ERNIE Bot’s training in Chinese would result in greater empathy toward Chinese-speaking users than ChatGPT, the results challenge this notion. The findings suggest that factors beyond the language of training influence the empathetic responsiveness of LLMs, highlighting the complexity of human-AI interactions and emphasizing the need for further exploration of the relationship between language and empathy. Physicians responded better when patients asked for recommendations on specific Chinese books about ASD. Physicians also effectively handled situations where the patient’s condition was misstated, whereas LLMs provided inaccurate information. Additionally, creating user-friendly interfaces to accommodate patients with varying levels of technological proficiency could improve the accessibility and usability of AI models in health care settings.

Limitations

This study had several notable limitations. First, reliance on web-based consultation platform records constrained each autistic patient to a maximum of 3 questions per web-based consultation, potentially limiting the ability to replicate real-world patient-physician interactions comprehensively. Moreover, the study exclusively examined text-based responses to patient inquiries, neglecting the potential for health care professionals to tailor their responses based on individual patient characteristics such as occupation and emotional state. The extent to which clinical professionals can adapt their responses to such personalization remains uncertain. Additionally, the study did not assess the chatbot’s capacity to extract information from health records, representing an area of potential improvement. Finally, although the evaluators have been single blinded, they potentially introduced bias into their assessments because they are coauthors of the paper and may hope that there are apparent differences between the groups in the results to make extreme scores.

Conclusions

The findings of this cross-sectional study show that physician responses outperform those of LLMs in the Chinese context, responding to inquiries from autistic patients in text-based formats compared with responses from current state-of-the-art LLMs. Nevertheless, these LLMs can offer medical guidance for autistic patients and demonstrate greater empathy compared with physicians, particularly ChatGPT-4. It is essential to emphasize that further refinement and comprehensive research are prerequisites before deploying LLMs effectively in clinical settings across diverse linguistic environments.

Acknowledgments

The authors extend their appreciation to the assessors for their professional contributions in conducting the measurements in this study. Special thanks are extended to Shanghai Tengyun Biotechnology Co, Ltd for developing the Hiplot Pro platform and their valuable technical assistance and tools for data visualization. This research received financial support from the National Natural Science Foundation of China (82105021). The funders were not involved in the study design, execution, or reporting. This study represents an inaugural assessment of the effectiveness of 2 prominent large language models, ChatGPT from the United States and ERNIE Bot from China, in providing high-quality and empathetic responses to medical inquiries from Chinese-speaking autistic patients.

Data Availability

All data generated or analyzed during this study are included in this published article. The data for this study are contained in Multimedia Appendix 1 .

Authors' Contributions

QX initiated and designed this study. WH collected and analyzed the data and drafted the manuscript. WZ guided English writing. YJ created the figures and tables. QZ and HZ conducted literature searches and participated in participant recruitment. QX revised the manuscript. QX managed the project and secured funding. All the authors have reviewed and approved the manuscript.

Conflicts of Interest

None declared.

The raw data.

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Abbreviations

Edited by T Leung, S Ma; submitted 20.11.23; peer-reviewed by N Singh, J Li; comments to author 29.02.24; revised version received 20.03.24; accepted 02.04.24; published 30.04.24.

©Wenjie He, Wenyan Zhang, Ya Jin, Qiang Zhou, Huadan Zhang, Qing Xia. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 30.04.2024.

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, 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.

• Open access
• Published: 30 April 2024

A comparative ethical analysis of the Egyptian clinical research law

• Sylvia Martin 1 ,
• Mirko Ancillotti 1 ,
• Santa Slokenberga 2 &
• Amal Matar 1 , 3  

BMC Medical Ethics volume  25 , Article number:  48 ( 2024 ) Cite this article

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In this study, we examined the ethical implications of Egypt’s new clinical trial law, employing the ethical framework proposed by Emanuel et al. and comparing it to various national and supranational laws. This analysis is crucial as Egypt, considered a high-growth pharmaceutical market, has become an attractive location for clinical trials, offering insights into the ethical implementation of bioethical regulations in a large population country with a robust healthcare infrastructure and predominantly treatment-naïve patients.

We conducted a comparative analysis of Egyptian law with regulations from Sweden and France, including the EU Clinical Trials Regulation, considering ethical human subject research criteria, and used a directed approach to qualitative content analysis to examine the laws and regulations. This study involved extensive peer scrutiny, frequent debriefing sessions, and collaboration with legal experts with relevant international legal expertise to ensure rigorous analysis and interpretation of the laws.

On the rating of the seven different principles (social and scientific values, scientific validity, fair selection of participants, risk-benefit ratio, independent review, informed consent and respect for participants) Egypt, France, and EU regulations had comparable scores. Specific principles (Social Value, Scientific Value, and Fair selection of participants) were challenging to directly identify due to certain regulations embodying 'implicit' principles more than explicitly stated ones.

The analysis underscores Egypt's alignment with internationally recognized ethical principles, as outlined by Emanuel et al., through its comparison with French, Swedish, and EU regulations, emphasizing the critical need for Egypt to continuously refine its ethical regulations to safeguard participant protection and research integrity. Key issues identified include the necessity to clarify and standardize the concept of social value in research, alongside concerns regarding the expertise and impartiality of ethical review boards, pointing towards a broader agenda for enhancing research ethics in Egypt and beyond.

Peer Review reports

Introduction

Science relies on research to move forward and enhance knowledge. Different research areas deploy at different levels of human subjects’ involvement, from qualitative and non-interventional research methods to biomedical research and medical validation procedures. While virtually all research has ethical implications, clinical research calls for special attention, and it is widely agreed that it should be conducted according to more stringent ethical principles than other types of research [ 1 ]. To facilitate appropriate ethical implementation of research, it is imperative for ethical regulations to be receptive to the advancements in the field. The well-being of participants is a fundamental condition of research emphasized by the principles outlined worldwide in renowned ethical texts like the Belmont Report (cited in [ 2 ] Footnote 1 ), and the Helsinki Declaration (see [ 3 ] Footnote 2 ). These core principles include ensuring participants' entitlement to minimize harm and discomfort [ 2 ], as well as safeguarding their rights against exploitation [ 4 ].

For assessing whether the ethical requirements are fulfilled, and to ensure that international standards are respected, as it has been proposed by Artal & Rubenfeld [ 5 ], 2017, it is essential account for specific principles developed in the field. Research conduct that seemed legitimate to the men of science in the past is abhorrent to the contemporary conscience [ 6 ]. Ethical standards also depend on where they apply. Different societies, with their specific traditions and cultures, have systems of values and norms that may only partly coincide with research ethics principles informing international standards. Hence, there could be a gap between what is culturally acceptable and what is compliant with international ethics standards. However, the risk of ethical colonialism and its biases, may be difficult to avoid, as it can be considered factual that many international documents heavily rely on the Western perspective [ 7 ].

While cognizant of this, a few documents can be considered ethical reference points, such as the above-mentioned Belmont Report and the Helsinki Declaration for the protection of human participants in medical research [ 8 ]. Another influential example is the Ethical Framework for Biomedical Research from Emanuel et al. [ 9 , 10 ]. The Ethical Framework for Biomedical Research has heavily influenced the ethics work of leading institutions such as the Department of Health (DoH, South Africa Footnote 3 ) and Council for International Organizations of Medical Sciences (CIOMS). In research ethics, the framework has often been used to assess the functioning of ethical review committees and the ethical adequacy of legal regulations of research involving human subjects (see [ 11 , 12 , 13 ]). This ethical framework, rooted in major Western philosophical traditions but not explicitly aligned with any specific school of thought, enables the authors to formulate a set of principles that resonates with a broad consensus, accommodating diverse moral intuitions and beliefs.

Regulatory framework implementation in the new settings offers a great chance to explore what the most recent bioethical laws are (like for the BRICS countries in [ 14 ]). In this regard, the Egyptian Bioethical law from 2020 can be considered as an innovative example for other countries in the process of implementing bioethical regulations and improved bioethical education across the world [ 15 , 16 , 17 ].

As Egypt is considered an LMIC by the World Bank [ 18 ], yet a “high growth pharmaceutical market”, the country has become one of the most attractive locations for pharmaceutical companies to outsource their clinical trials. The country, with over 100 million inhabitants, provides a noteworthy example of implementing bioethical laws in a context with predominantly treatment-naive patients and a robust medical infrastructure encompassing public hospitals and healthcare professional representation.

The aim of the present paper is to analyze and discuss from an ethical perspective the new Egyptian clinical trial law. The Egyptian law is analyzed and discussed in relation to the Ethical Framework for Biomedical Research by Emanuel et al. [ 9 , 10 ], and in comparison to selected other national and supranational laws.

One of the recent countries adopting bioethical law to regulate clinical human subject research is Egypt, which enforced its first law on clinical trials in the official journal on December 23rd, 2020. The issuance of the law, which has long been in the making, was hastened by the COVID-19 pandemic and the urgency to carry out vaccine trials among the Egyptian population [ 19 ]. This regulation is part of a broader effort to enhance the respect for civil/human rights in the country. In 2022, the recent reports from the US Embassy still pointed out some issues [ 20 ], raising concern about fairness and equity in the whole society, and impacting ethical procedures in health and research. However, Egypt -as a United Nations member since 1945- has been participating in the global initiative to enhance human rights application [ 21 ]. Like other Arabic countries (Jordan, Saudi Arabia) registered in the UN Watch Database, it needed to justify their application of human rights [ 22 ]. Efforts are made to improve ethical skills among health care givers in Egypt. For example, EL-Khadry et al. [ 23 ], assessed the effect of educational intervention on knowledge and attitude towards research, research ethics, and biobanks among Egyptian paramedical and administrative teams. Egypt has witnessed exponential growth in medical research like in many developing countries, driven by the pressing need to improve healthcare [ 24 ]. Egypt held the 37th position in terms of publication volume in 2023 [ 25 ]. It is worth noting that in 2020, Egypt had only 838 researchers per million inhabitants, in stark contrast to the USA’s 4,821 researchers per million inhabitants (in 2019) and the United Arab Emirates’ 2,443 researchers per million inhabitants (Researchers in R&D (per million people) [ 26 ] representing the medium position compared to of BRICS countries like South Africa (484 researcher per million habitants) or China (1,585).

National examples: France and Sweden

On the national level, France and Sweden hold a long tradition of ethical regulation. French law influenced the structuring of the Egyptian legal system in 1875. Later, reforms were made to the Egyptian civil law under the guidance of a French legal expert Édouard Lambert in the 1930-the 1940s [ 27 ]. We selected France as a study focus due to its historical ties and influence on Egypt's regulatory framework. Additionally, for comparative analysis with another high-income Western nation, Sweden was chosen for its renowned status as a research leader, distinct from any historical connections with Egypt.

Northern European countries are still considered to be leading countries in research (Sweden is the 3 rd country in terms of research and development expenditures (% of GDP) after Israel and Korea in 2020 – [ 28 ] and have a long tradition of bioethics practices and reflections (e.g., Helsinki’s declaration in 2000 [ 29 ]). Specifically, Sweden is included in the study as an example of a Nordic country with an evidence-based culture of health policymaking [ 30 ] and constant interest for ethical inquiry in under-researched vulnerable populations [ 31 , 32 , 33 ]. In 2004, Sweden enforced “The Act concerning the Ethical Review of Research Involving Humans” (SFS nr: 2003:460) that sharpened ethical review procedures for biomedical research way earlier than other countries (e.g. Loi Jardé in France from 2012, and the Egyptian law 2020), introducing a reference that showcased innovative law in the early 2004 that remains in effect. In 2020, France had 4926 researchers per million inhabitants, quite comparable to the USA’s 4,821 researchers per million inhabitants (in 2019) and representing a European example of a “medium” score of researchers per million inhabitants. In comparison, Sweden counts for 7,930 researcher per a million inhabitant, Norway 6,699, Finland 7,527 or Denmark with 7,692 (Researchers in R&D (per million people) [ 34 ]. At the international level, France ranked at the 6 th position for publication volume, while Sweden ranked the 18 th [ 35 ].

Supra-national entity: the EU regulations to consider when considering France and Sweden

Supra-national European regulations play an important role in the legal system of EU countries even if such a supra-national level does not exist in Egypt. At the EU level, the EU Regulation on clinical trials on medicinal products for human use (CTR) governs the ethical review of clinical trials, however detailed aspects of ethics committees and ethical review depend on further regulation at Member State level. This means that even though the EU regulates ethical review of clinical trials in the CTR, there could be considerable divergences across Europe in how the committees are set up and perform their tasks. To begin with, the CTR requires that a clinical trial be subject to ethical review (Article 4), and it outlines several relevant aspects of the process of carrying out that review. However, modalities regarding ethical committee and its work are a question of the Member States’ regulation. Generally, the application for authorisation to conduct a clinical trial is divided into two parts. Part I focuses on the technical-scientific dimension, and part II on the ethical aspects which are reviewed by each member state concerned. An ethics committee, within the meaning of the CTR, is an independent body established in a Member State in accordance with the law of that Member State Footnote 4 . Under the national law, this body needs to be empowered to give opinions for the purposes of the CTR, considering the views of laypersons, in particular patients or patients’ organizations (Art. 2(2)(11)). The CTR prescribes in Recital 18 merely a guiding requirement that the member state needs to ensure that “the necessary expertise is available”. Member States should have a mechanism in place to ensure the involvement of laypersons, in particular patients or patients’ organisations. However, the effect of this involvement that the CTR requires is that their views are taken into account in the review (Art. 2(2)(11)). It is not uncommon that several ethics committees exist in a member state. How the involvement of an ethics committee is organized for the purposes of the tasks specified in the CTR is a question for the Member States to decide (recital 18). However, the process needs to be organized so that the relevant timelines of the clinical trials approvals set out in the CTR are met (Art. 4).

Design and data analysis

We examine the Egyptian law vis-à-vis France’s and Sweden’s framework, considering the obligations that stem in regards to clinical trials from the CTR. Furthermore, we examine these regulations in light of the Ethical Framework for Biomedical Research by Emanuel et al. [ 9 , 10 ]. Indeed, we will consider the EU implication into France and Sweden’s regulations.

A directed approach to qualitative content analysis was adopted using the seven principles informing the Ethical Framework for Biomedical Research as predetermined themes [ 36 ]. Two independent coders examined each selected regulation in their original version for French (MA, SM), Swedish (MA, AM), EU (MA, AM), and in an English translation for the Egyptian law (AM, SM). The coders discussed the results critically in debriefing sessions and their coding was discussed until consensus with a legal expert working with ethical regulations at the international level (SS) contributing the clarification of EU and both Swedish and French framework.

Theoretical framework

The seven principles that will serve as comparison criteria for our analysis are the following: “ (1) (Social) value - enhancements of health or knowledge must be derived from the research; (2) scientific validity- the research must be methodologically rigorous; (3) fair subject selection - scientific objectives, not vulnerability or privilege, and the potential for and distribution of risks and benefits, should determine communities selected as study sites and the inclusion criteria for individual subjects; (4) favorable risk-benefit ratio-within the context of standard clinical practice and the research protocol, risks must be minimized, potential benefits enhanced, and the potential benefits to individuals and knowledge gained for society must outweigh the risks; (5) independent review - unaffiliated individuals must review the research and approve, amend, or terminate it; (6) informed consent - individuals should be informed about the research and provide their voluntary consent; and (7) respect for enrolled subjects -subjects should have their privacy protected, the opportunity to withdraw, and their well-being monitored. ” (Emanuel et al., 2000, p2701 [ 9 ]).

For a thorough assessment, we exclusively examined the primary text of each law, excluding connections to other regulations (e.g., the "Code de la Santé" and "Code Penal" for French regulation or to “Law No. 151 of 2019, the Egyptian Medicines Authority” for the Egyptian text). Our analysis utilized the latest version of the law, including any amendments. These are:

Egypt’s law – no amendments December 23 rd , 2020, Law No. 214 of 2020 Regulating Clinical Medical Research.

French law : the “Loi Jardé” (LOI n° 2012-300 du 5 mars 2012 relative aux recherches impliquant la personne humaine) amended with the “Décret n° 2016-1537 du 16 novembre 2016 ”. We will consider the latest 2022 amendment for reference in our analysis.

Swedish law : Lag (2003:460) om etikprövning av forskning som avser människor with the following amendments: 2018:147, 2018:1092, 2019:1144, 2021:611, 2022:48.

Regulation (EU) No 536/2014 of the European Parliament and of the Council of 16 April 2014 on clinical trials on medicinal products for human use, and repealing Directive 2001/20/EC Text with EEA relevance OJ L 158, 27.5.2014, p. 1–76.

These laws have been identified for being the main relevant legal texts for biomedical research regulations and more specifically research involving human subjects. The selection of national and international regulations to assess was based on their presence within international pharmacological and biomedical research industry. Moreover, the EU regulation will be considered as an adjunct line of analysis to complement Swedish and French regulation examination as both countries are part of EU.

The full overview of coding procedure for all regulation is available as supplementary material (see Tables 1 , 2 and Appendix 1 ). A summary of this assessment is presented in Table 1 with a score system showing the compliance or absence of compliance to each principle. A score of 0 means there is little to no compliance with the criteria, while an X indicates satisfactory or complete compliance with the criteria.

• Social value

Egyptian law does not overtly address the social value of the research proposal. However this may be implied as the national Research Ethics Committee (REC Footnote 5 ) (Supreme Council) will take into account “national interest” when evaluating research protocols (Chapter (ch) 3, article (art) 7(2)).

Similarly, the Ethical Review Act, has no clauses that are focused on assessing the social value of research. However, the notion of research serving a social interest is implicitly demonstrated by the composition of the departmental REC, where five members out of 15 represent society’s interests (Section 25). In Section 8, it is indeed stated that the welfare of research participants must be prioritized over the needs of society.

France also lacks a clear statement on the social value. The law relates to “social” level as it often refers to the “Code de la santé” (CS) and to the “social security” system, but no clear points about social values per se. Social and scientific value is stated in the “Research organized and carried out on human beings to develop biological or medical knowledge shall be authorized“ (Art. L1121-1 CS).

Under the CTR, social value – enhancement of health – is the whole purpose, even if not expressis verbis stated, Art. 3 and Art. 6 ensure that as a general principle, (a) the rights, safety, dignity, and well-being of subjects are protected and prevail over all other interests; and (b) it is designed to generate reliable and robust data for example. Moreover, member state and Union inspections are envisaged (taking compliance with the EU regulation as a token of good research for society and for science). See Art. 78 and 79.

Scientific validity

Regarding Scientific validity, Egyptian law set up the responsibility of REC to ensure ethical quality (Art. 1, Art. 2, Art. 24) of the accepted protocols, but also set up standards for scientific quality (Art. 7; 2; Ch. 2 Art. 10) making sure that principal investigators have the required scientific competences (Ch. 5 Art. 22; Ch. 3 Art. 6 provided a detailed list of required competences §2, Ch. 4 Art. 9.).

The Swedish law emphasizes the importance of sound research. In Section 11, it is stated that research may only be approved if it is carried out by/under the supervision of a researcher with the necessary scientific competence. In Section 9, where the scientific value of the proposed research is weighed against, and if proportionate justifies, the risks to the health, safety, and personal integrity of research participants.

Article L1121_2 expresses the need for social and scientific validity. Art. L 1121-3 refers to “qualified personnel” for scientific validity and after the approval has been given by a REC. RECs have a regional organization and can be involved together with Commission nationale de l'informatique et des libertés (CNIL) for data security issues, and Committee of Experts for Research Study and Evaluation in Health domain. Any research is also regulated by EU rules (Article L1121-1 CS). Specific regulations for certain disciplines are stated in the CS (L1121-3) but not in the Loi Jardé.

At the EU level, Art. 4 requires prior authorization. In particular, a clinical trial shall be subject to scientific and ethical review and shall be authorized in accordance with the rules set out in the CTR. Under Article 6(1)(b)(i) the reliability and robustness of the data generated in the clinical trial, taking account of statistical approaches, design of the clinical trial and methodology, including sample size and randomization, comparator, and endpoints.

Fair selection of study population

The Egyptian law ensures the impartial selection of an appropriate number of research participants. There are specific recommendations for REC in regards to recruitment of specific sub-groups or vulnerable population. For example, prohibit research participants to enroll in simultaneous medical research and prohibit induced participation (Ch. 5 Art. 13; 14).

There are no definite clauses in the considered law that emphasize the requirement for fair selection of the study population. Nonetheless, protection of minors and individuals who cannot consent to research participation is described in Sections 18, 20, 21, and 22 (see Informed consent section).

French regulation requires that study participants be beneficiaries of the Social Security system (and if not, they will be considered as if they are). Fair selection of the participants is ensured by the CS (Articles L. 1121-5 to L. 1121-8). The main categories with stated protection are adults in coma, with dementia or for psychiatric conditions, or enfeebled patient, people deprived of their freedom, foreigners, minors, pregnant and nursing women. Moreover, situations such as “urgency” that may override any consent needed.

Art. 10 offers “specific considerations for vulnerable populations”, in particular, minors (see Art. 32), incapacitated subjects (see more Art. 31, 28, 29), pregnant or breastfeeding women (see Art. 33), the participation of specific groups or subgroups of subjects, where appropriate, specific consideration shall be given to the assessment of the application for authorization of that clinical trial on the basis of expertise in the population represented by the subjects concerned. Art. 34 also covers national measures for participants performing mandatory military service, persons deprived of liberty, persons who, due to a judicial decision, cannot take part in clinical trials, or persons in residential care institutions.

Favorable risk-benefit ratio

Clear specifications of the Principal investigator requires all the consideration about risk-benefit ratio (both at the physical and psychological level), ensuring dignity and health, adding a note for specific attention to reducing side effects (Art. 18; 6). Another layer of risk reduction is the provision to evaluate preclinical medical research (Ch. 5 Art. 10), the provision of health insurance coverage of any research participant (Ch. 7 Art. 18 §9), and ensuring that the research organization will be able to attend properly to research participants’ health needs in case adverse effects or health risks ensuing from the clinical trial (Ch. 11).

According to the Swedish legislation, the necessary condition for approving research is that fundamental personal freedoms, and human rights are respected. While Section 9 states that research may be approved if its scientific value outweighs the risks to research participants, Section 8 specifies that their welfare must be prioritized over the needs of society and science. Section 10 states that research should be conducted only if its expected result cannot be achieved in another way that involves less risk to the health, safety, and personal integrity of research participants.

Favorable benefit-risk ratio was refined with the inclusion of “new facts” issues that appeared with Loi Jardé. The most important point to emphasize is that the sponsor will be responsible for the care and necessary costs ensued from severe side effects, if they occur. These include both biomedical research (R1) as well as interventional minimal risk research (R2).

Art. 6 ensures that risks (minimization, safety measures) and inconveniences for the subject are considered and reduced for medicinal products and interventions compared to normal clinical practice. Suspected unexpected serious adverse reactions and annual reporting are strictly regulated at the EU level. Under the CTR, the committees are informed regarding suspected unexpected serious adverse reactions that are reported pursuant to the CTR as well as the annual report submitted to the European Medical Agency (Art. 44.3).

Independent review

Independent review will be implemented by a REC (Art. 1, 24), and it will protect the rights of participants, review the research protocol, decide on approval, amendments or renewal of the research, and lastly monitor the research (All this is in accordance to the executive regulations of law art 8). The specifics of the review process are detailed in several articles (Ch. 2 Art. 4: REC; Ch. 3 Art 1 to 4).

According to Section 6, independent review is mandatory whenever the research involves a physical intervention or involves affecting or risk harming the research participant physically or psychologically. Independent review is also required in the case of studies involving biological material taken from a living person and can be traced to that person. The same article emphasizes the principal investigator’s responsibility, who must take measures to prevent research from being carried out in violation of the law. Section 25 sets out the organization of the authority providing an independent review, i.e., the Ethics Review Authority. This is divided into operational regions, each composed of one or more departments according to their areas of expertise. Departments consist of a chairman, who is or has been an ordinary judge, and fifteen other members, of whom ten have scientific competence and five represent public interests, including at least one member who represents one or more patient organizations. The government appoints the chairman and its deputy, while the Ethics Review Authority chooses the other members and their deputies.

The independent review component is well established with the composition of the Committee for the Protection of Persons and the presence of 39 RECs across the 7 inter-regions committees. The repartition of REC into 2 colleges, one more scientific and the second more patient-related, support independent review, but the designation and recruitment of different REC members (depending on the national or local level, for example) is not clear. For the local levels (Art L1123-1), the text state that the Health Minister CPP for a fixed or undetermined duration and according to the needs. Their members are appointed by the Director General of the regional health agency in which the committee has its headquarters. The committees are completely independent in the performance of their duties. They have legal entity under public law. Committee resources are provided by the State. However, ethical approval can be obtained via institutional committees (in house at some hospitals and universities). Member of the National commission for research involving human need to declare their conflicts of interest (Art. L1123-1-1) which is not clarified for CPP (promotors of the same institution are – per definition- applying to their “in house” ethical committee).

Art. 4 refers to the need for prior authorization in accordance with the law of the Member State concerned Footnote 6 . The review by the ethics committee may encompass aspects addressed in Part I of the assessment report for the authorization of a clinical trial as referred to in Article 6 and in Part II of that assessment report as referred to in Article 7 as appropriate for each Member State concerned. Article 9 should ensure that the persons validating and assessing the application do not have conflicts of interest, are independent of the sponsor, of the clinical trial site and the investigators involved and of persons financing the clinical trial, as well as free of any other undue influence. A special mention explains that at least one layperson shall participate in the assessment.

Informed consent (IC)

Among the very first articles (Art. 1; 21), Egypt’s law provides a definition of IC, promoting its engagement into this ethical procedure “the written expression based on complete voluntary freewill of the person with full legal capacity, and it includes his explicit consent as a signature and a fingerprint to participate in clinical medical research, after all aspects of the research are explained to him, and in particular the potential effects or harms that may impact his/her decision to participate[…]”. The exception of obtaining IC is detailed in executive regulations (Ch. 5, Art. 12; 3). More specific consideration is also represented in other sections of the law: in Ch. 7 Art. 17 § 2: obtaining IC is mandatory. In Ch. 10, Art. 23 §2, IC is required for data usage and for further research. Furthermore it provides specification for consent of data usage.

Section 17 states that, in line of principle, research can only be performed if the research participant has voluntarily and explicitly consented in a documented way after receiving adequate and specific information. Section 16 describes what the fundamental pieces of information are. In cases where a research participant is in a dependent relationship with components of the research team or if the research participant has difficulties asserting their right, Section 14 states that issues of information and consent must be given special attention. Specific recommendations are provided in the case of minors or if the research participants turned 15 years (Section. 18). Sections 20, 21, and 22 list under what circumstances research can be performed without consent (illness, mental disorder, a weakened state of health, or any other similar condition of the research participant prevents their consent from being obtained).

IC regulations state that “Consent is free, informed and (voluntary) emphasizing the importance of individuals providing explicit agreement in various legal situations. It must be written for category 1 studies and may be oral for category 2 studies (but must be recorded in the medical file). For category 3 research and for studies on data collected in the course of normal care, the rule is that the patient “must not object.” No research mentioned in 1° of Art. L. 1121-1 may be carried out on a person without his or her free IC, given in writing after the person has been provided with the relevant information. Where it is impossible for the person concerned to express his or her consent in writing, it may be attested by the trusted support person provided for in Art. L. 1111-6, by a family member, or, failing this, by one of the person's close relations, provided that this trusted person, family member or close relation is independent of the investigator and the sponsor. Specific recommendations are provided for minors (under 18 solely). Article 4 is also providing details about the case where the participant cannot express consent and is not under guardianship. There are also options for “collective consent,” but they are only available for interventional research with minimal risk (epidemiologic search).

Art. 7 mentions the need for compliance with the requirements for IC as set out in Art. 29, explicating the regulations about written IC. A specific regulation has also been dedicated in Art. 30 for cluster trials. This specification states that “Where a clinical trial is to be conducted exclusively in one Member State, that Member State may, without prejudice to Art. 35, and by way of derogation from points (b), (c), and (g) of Art. 28(1), Art. 29(1), point (c) of Art. 29(2), 29(3), (4) and (5), points (a), (b) and (c) of Art. 31(1) and points (a), (b) and (c) of Art. 32(1), allow the investigator to obtain IC by the simplified means set out in paragraph 2 of this Article, provided that all of the conditions set out in paragraph 3 of this Article are fulfilled.”

Respect for participants

Egyptian law provides protection of privacy and data (Art. 12; 2), adequate information of researcher participants (Art,.15; 2. Ch. 5; Art 18:5), protection from publicity (Art. 15;3) together with a straightforward explanation of requirements to respect withdrawal of consent (Art. 2, 1) and compensation aspects (Art. 20:9, 10). The details of non-induced participation (for money or reward) could also be understood as a measure of respect for recruited participants (Art. 14).

Section 1 states that its purpose is to protect the individual and respect human dignity in research. This is reaffirmed under Section 7. Noteworthy, according to Section 40, some exceptions can be made with regards to requiring consent or processing of data if this is requested by the government or another authority. This is only possible if it is clear that the research does not entail any appreciable risk to an individual's health or safety or pose an infringement on an individual's integrity.

The respect for study participants was unclear in the text and focuses more on fair selection and risk protection of research participants. One specific element regarding the participant protection of “a deceased person, in a state of brain death, without his or her consent expressed during his or her lifetime or through the testimony of his or her family” (Art. L1125-13).

Article 28 prescribes general rules that must be met for a clinical trial to be lawfully conducted. This article clarifies that benefit to the participants, IC, right to mental and physical integrity, minimal pain or risk, guaranteed medical care, and no undue influence (including financial) are the basis for any medical research. EU regulation Article 28 of Regulation (EU) No 536/2014 of the European Parliament and of the Council, Article 2 make sure that withdrawal is free of constraints and will not have repercussions nor affect the participants' rights and care, but also makes sure that the withdrawal of consent does not affect the data collected prior to withdrawal.

Our results show that the Egyptian law fulfills the ethical requirements for human subject research and is comparable to the French, Swedish and EU regulations.

Detailing the results, we also observed that all regulations tended to have a very vague approach to “social values and scientific values” (principle 1). In terms of the fair selection of participants, the Swedish text was probably the vaguest (principle 3), but in general, this principle appeared to be well integrated. All other principles also were well represented in Egyptian law as in the French, Swedish, and EU’s laws (principles 4, 5, 6, 7). We explore in two separate points the results :1) Value and validity (in which principles 1, 2 and 5, with 5 as the way/procedure to reach value and validity), 2) Participant’s protection (principles 3, 4, 6, and 7).

Values and scientific validity

Principle 1, social values and scientific value.

Egyptian regulation suffers from the same issues in clarifying the social value aspect as French, Swedish, and EU regulation. The results from the assessment of social values reveal that most of the regulations struggle to clearly define under what specifications research should serve a social purpose. Social value is often envisioned at the level of cost-effectiveness measurements, and its definition may be difficult to normalize across states and cultures as it refers to “the general concept and practice of measuring social impacts, outcomes, and outputs through the lens of cost” [ 37 ]. In Emanuel et al’s vision, it is composed of the a) ensured benefit b) value for the prospective beneficiaries, c) dissemination of the results via long-term collaborative strategy d) avoiding to undermine the community’s existing healthcare [ 38 ]. Furthermore, these results question the importance of social value in research per se, for example, in specific areas where the social value aspect cannot be considered as an overarching guide. Recent debates questioned, for example, the justice and egalitarian arguments that can arise from questioning the social value of research [ 39 , 40 ] depending on how innovative and impactful on a societal level the research is.

Principle 2, Scientific validity

Egyptian law, French, Swedish, and EU regulation, tries to specify the scientific validity mostly via their REC members selection. The general implementation of a control mechanism and ethical review board’s competences question the real level of expertise or education that these members do have in order to review research protocols or scientific methods. For example, there is not a clear consensus about the need for specific competencies in order to have balanced and non-biased decisions in ethical vetting because [ 41 ] as different ethical reviewers will raise different concerns. In their results, they confirmed that the main influencing factor in readers-queries was the profession, with scientific validity issues being more frequently asked by scientific reviewers, whereas ethical issues were more frequently pointed out by ethicists.

Depending on the system and general community functioning, the selection of research ethics committees members can put into question the non-biased nature of assessment of scientific validity. For instance, in France, the members of the Nation Ethical Committee, who are responsible for offering direction to all REC, are "selected" or "designated" by the President of France. The same question could also be raised in Egypt were Central intelligence members are sitting at the National REC (the Supreme Council). The impact of politics and social politics in presumably non biased procedure is also rising with the use of preference studies to inform policy making and including patient’s advocacy in decisions boards as it can have a role in decision makings [ 42 ] providing advances in shared decision making but also leveraging non-biased decisions making as there is still not a unified definition of such processes [ 43 ] and for example, research shows that methodological standards are often downgraded to provide access to the co-researchers [ 44 ].

As it is sometimes defined in science in general, validity should be assessed in an adequate manner across medical field. Scientists refer to scientific quality measures (like in systematic literature review assessements scales for scientific quality) but validity interpretation can be difficult to apprenhend for an heterogeneous group of experts (like an REC). In its very classical definition “The validity of a research study refers to how well the results among the study participants represent true findings among similar individuals outside the study. This concept of validity applies to all types of clinical studies, including those about prevalence, associations, interventions, and diagnosis”, scientific validity could look easy to apprehend but even then, just having the precision “The validity of a research study includes two domains: internal and external validity” explain the layer of complexity that may not be represented in Emanuel’s principles definition [ 45 ]. Going further into the validity explanation and use in ethical consideration in biomedical research should be warranted. For example, some research look at different levels of validity to clarify what one considers as validity (scientific validity may be too vague to refer to permit clear assessment): congruence validity, criterion validities, etc [ 46 ]). Wages et al. in 2021 [ 47 ], showed the potential for using operating characteristics to inform design’s safety and accuracy in phase I clinical trials that could open the debate around a better definition of scientific validity checks in biomedical research. One part of the issue comes from scientific communities but the scientific validity should be also a matter of concerns for all REC members. The competencies of any participants should be addressed in the REC reviewer’s selection as some questions also arise from the medical field where shared decision-making has been implemented before and some debate remains about the representativeness of patients that do get involved in the medical decision-making [ 48 , 49 ].

Principle 5, Independent review

All ethical regulations, including Egypt’s, ensure that the review system is independent and thus RECs have the power to authorize, follow up and end any research to protect participants [ 29 ]. One of the major concerns still not addressed in the regulations is the difficulty to guarantee REC effectiveness in regards to some deficiencies in REC theory and structure [ 50 ]. The opportunities to enhance EC efficiency and effectiveness could also depend more on the researcher and the scientific community as Hickey et al., 2022 suggested [ 51 ]. Clarifying the collaborative approach across ethics committees and research can be the path to increased medical research efficiency.

Participant’s protection

Principle 3, fair selection.

In the Egyptian regulation, the fair selection of participants is pursued, which can be considered a positive development with respect to the previous regulation proposal, where protection of the rights and welfare of vulnerable subjects were not adequately considered [ 52 ]. Generally, one can wonder about the impact of fairness when recruiting for clinical trials. Ongoing discussions emphasize that the fair selection of participants could be a very ethically challenging issue as it is a ground for dilemmas [ 53 ], including the levels of “(1) fair inclusion; (2) fair burden sharing; (3) fair opportunity; and (4) fair distribution of third-party risks”. The equal opportunity issue also arose for example in 2022 when French law integrated EU requirements and shifted toward allowing research participants with no access to social security to be part of research [ 54 ], offering extended opportunities for participation but putting the question of fairness of selection into question.

Principle 4, Favorable risk-benefit ratio

Egyptian regulation, like the four other comparatives, consider “Risk-benefit” as a sine qua none principle and the clarity of Helsinki’s declaration [ 55 ]. However, no regulation mentioned the potential for under-reporting harms depending on what one considers to be “harm”. One of the aspects that are often under-considered is psychological harm, as even clinical trials in the field tend not to report psychological harm (compared to physical adverse effects of drugs in clinical trials) as can be noted in research by [ 56 , 57 ].

Principle 6, Informed consent

Informed consent is implemented overall, and as for principle 5, Egypt complies, like all comparatives to this standard practice. Even if a variety of informed consent exists, the law sticks to written consent without specifying the potential for renewed consent, broad consent, or other approaches [ 58 ] and the “blanket consent” potential.

Principle 7, Respect for recruited participants and study communities

Respect for participants reflects respecting autonomy across health care and research systems that appear to be consistent across the 4 regulations. Egyptian law places an equivalent emphasis on this principle as French law and is comparable to Swedish and EU regulation. All these regulatory frameworks effectively incorporate this principle into their bioethical laws. Heightened attention still needs to be paid to respect at different levels, such as for gender issues [ 59 ], or/and ethnicity [ 60 , 61 ].

Limitations

Our study contains limitations. The first one is that we looked for expressis verbis statements that limit the apprehension of the full corpus of laws application in a specific context. Indeed, some implicit references could counterbalance our conclusions. For instance, the CTR underscores the overarching objective of promoting the social value by enhancing health, even if not explicitly stated. Nevertheless, at the clinical level, practitioners may not have comprehensive access to all regulations and are likely to rely on referenced texts in the ethical application specific to their country. The lack of clarity (or complex implicit references) may hinder comprehension and result in a complex implementation process. Utilizing the principles proposed by Emanuel et al. may also be presented as a limitation as this analytical foundation may not comprehensively encapsulate the nuances inherent in the examined legal frameworks. Another limitation could be posited in the fact that the analysis may not fully reflect the influence of cultural and social variations among the three countries. Further research would need to also assess the overall structure of ethical procedure in each country and their organization (from Supreme councils, regional entities, national unified procedures, etc).

In conclusion, the Egyptian law in comparison to French, Swedish, and the connected EU regulations reveals its alignment with Emanuel et al.’s principles. However, several common challenges and areas of improvement can be sought with regards to each of the ethical principles and thus open the way for further research. The main topic identified via our analysis is the need to clarify and standardize the concept of social value of research, which often focuses on cost-effectiveness measurements and implicitly -not always directly- refers to a very difficult concept to apply [ 62 ]. Our second main discussion point highlights concern about the expertise and unbiased decision-making of ethical review boards. Further research is warranted to explore in more detail’s other principles. Overall, these findings highlight the need for continuous improvement and refinement of ethical regulations to ensure the protection of participants and the integrity of research in Egypt and other jurisdictions.

Based on the discussion, the following recommendations can be made for improving research ethics regulations in the countries in our analysis:

Clarify and Standardize Social Value: Develop clear guidelines and standards to define and measure the social value of research across different states and cultures. This should include a detailed framework for assessing research's contribution to societal benefits, cost-effectiveness, and its alignment with the long-term healthcare goals of the community.

Enhance Scientific Validity: Strengthen the criteria for the selection of Research Ethics Committee (REC) members to ensure they possess the necessary expertise and education to review research protocols and scientific methods effectively. This includes establishing more rigorous competency requirements and providing ongoing training to ensure balanced and non-biased decision-making in ethical approvals.

Improve Participant Protection: Emphasize the fair selection of participants by addressing ethical challenges and ensuring equitable opportunities for participation. This involves revising existing regulations to better protect the rights and welfare of vulnerable subjects and to promote fairness in participant selection.

Increase REC Effectiveness: Address deficiencies in REC theory and structure to enhance the effectiveness of research ethics committees. This could involve adopting more collaborative approaches between review boards and researchers, and ensuring that ethics committees have the authority, independence, competences and resources needed to oversee research effectively.

Promote Respect for Participants: Ensure that all research activities respect the autonomy and dignity of participants. This entails paying heightened attention to issues of gender, ethnicity, and other factors that may affect participants' experiences in research settings.

Further Research: Encourage further research into the nuances of ethical principles beyond those identified by Emanuel et al., to better understand the cultural and social variations that may affect the implementation of ethical guidelines in different jurisdictions and cultural contexts.

Availability of data and materials

All data generated or analyzed during this study are included in this published article [and its supplementary information files].

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The composition of the ethics committees remains to be decided by a member state.

In France, the REC acronym coul refer more to the High National Ethical Committee, which issues recommendations on a societal scale. It is important to note that this committee is distinct from the day-to-day oversight of research ethical applications or clinical trials. The latter responsibility primarily falls within the purview of internal ethical committees situated within hospitals or universities, which have the authority to grant approvals. Externally, the (Comité de Protection des Personnes or CPP) serves as the most pertinent entity, akin to a Research Ethical Committee (REC); hence, we have opted to utilize the acronym REC for clarity.

The effect of the decision is, nonetheless, strong. Where an ethics committee has issued a negative opinion, on the condition that rules that are valid for the entire Member State apply, that Member State has a duty to refuse to authorise a clinical trial (Article 8.4, for extended authorisations see Article 14.10, for substantial modifications for the assessment report, see Articles 19, 20 and 23).

Abbreviations

Code de la santé / Health code

Research Ethics Committee

Clinical trial regulations

Low to medium income country

Commission nationale de l'informatique et des libertés / national commission for computer science and freedoms

French specific will stand for

Comité de Protection des personnes / person’s protection committee

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Acknowledgements

Sylvia Martin (SM) and Amal Matar (AM) conceived of the presented idea. SM, AM and Mirko Ancillotti (MA) developed the theory and performed the computations. SM, AM, MA, and Santa Slokenberga (SS) verified the analytical methods and discussed the results. All authors provided critical feedback and helped shape the research, final analysis and manuscript. None of the authors have competing interest to declare.

Open access funding provided by Uppsala University.

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Authors and affiliations.

Center for Research and Bioethics, Uppsala University, Uppsala, Sweden

Sylvia Martin, Mirko Ancillotti & Amal Matar

Department of Law, Uppsala University, Uppsala, Sweden

Santa Slokenberga

Clinical Immunology and Transfusion Medicine Department, Uppsala University Hospital, Uppsala, Sweden

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Sylvia Martin (SM) and Amal Matar (AM) conceived of the presented idea. SM, AM and Mirko Ancillotti (MA) developed the theory and performed the computations. SM, AM, MA, and Santa Slokenberga (SS) verified the analytical methods and discussed the results. All authors provided critical feedback and helped shape the research, final analysis and manuscript.

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Correspondence to Sylvia Martin .

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Supplementary Information

Additional file 1: appendix 1..

Comparative table with references to law texts.

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Martin, S., Ancillotti, M., Slokenberga, S. et al. A comparative ethical analysis of the Egyptian clinical research law. BMC Med Ethics 25 , 48 (2024). https://doi.org/10.1186/s12910-024-01040-0

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Received : 15 November 2023

Accepted : 26 March 2024

Published : 30 April 2024

DOI : https://doi.org/10.1186/s12910-024-01040-0

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