Racial and socioeconomic disparities in patient experience of clinician empathy: a protocol for systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Clinician empathy is a vital component of high-quality healthcare. Healthcare disparities may reflect a societal lack of empathy for disadvantaged persons in general, and recent research suggests that socioeconomic disparities exist in patient satisfaction with clinicians. However, it is currently unclear if there are disparities in patient experience of empathy from clinicians. Our objective is to systematically analyse the scientific literature to test the hypothesis that racial and socioeconomic status (SES) disparities exist in patient-reported experience of clinician empathy. METHODS AND ANALYSIS: In accordance with published methodological guidelines for conducting a systematic review, we will analyse studies reporting patient assessment of clinician empathy using the Consultation and Relational Empathy (CARE) measure, which to date is the most commonly used and well-validated methodology in clinical research for measuring clinician empathy from the patient's perspective. We will use a standardised data collection template and assess study quality (risk of bias) using the Newcastle-Ottawa Scale. We will abstract data for the CARE measure stratified by race and SES, and we will contact the corresponding authors to obtain stratified data by race/SES if not reported in the original manuscript. Where appropriate, we will pool the data and perform quantitative meta-analysis to test if non-white (compared to white) patients and low SES (compared to high SES) patients report lower scores for clinician empathy. ETHICS AND DISSEMINATION: No individual patient-level data will be collected and thus the proposed systematic review does not require ethical approval. This systematic review will test if racial and SES differences exist in patient experience of clinician empathy, and will inform future research to help promote healthcare equity. PROSPERO REGISTRATION NUMBER: CRD42019142809.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.089 | 0.145 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.023 | 0.031 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.061 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".