Evidence map›Paper›PMID 39688867›Full record

ArticleJAMA network open2024

Biased Language in Simulated Handoffs and Clinician Recall and Attitudes.

Austin Wesevich, Erica Langan, Ilona Fridman, Sonya Patel-Nguyen, Monica E Peek, Victoria Parente

Abstract read
In one paragraph

Article in JAMA network open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Chronic pain in the aging adult with sickle cell disease.Frontiers in pain research (Lausanne, Switzerland) · 2026
    Review
  5. A Hand to Hold.Journal of general internal medicine · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Austin WesevichSection of Hematology/Oncology, Department of Medicine, The University of Chicago, Chicago, Illinois.
Erica LanganDuke University, Durham, North Carolina.
Ilona FridmanCenter for Discovery and Innovation, Hackensack Meridian Health, Hackensack, New Jersey.
Sonya Patel-NguyenDivision of Hospital Medicine, Department of Medicine, Duke University, Durham, North Carolina.
Monica E PeekSection of General Internal Medicine, Department of Medicine, The University of Chicago, Chicago, Illinois.
Victoria ParenteDivision of Hospital Medicine, Department of Pediatrics, Duke University, Durham, North Carolina.

Funding

BASIC RESEARCH TRAINING IN MEDICAL ONCOLOGYT32CA009566 · NCI · UNIVERSITY OF CHICAGO · PI OLUFUNMILAYO F. OLOPADE · 1987 to 2026
$10.5M
NCI NIH HHS T32 CA009566
6 · The paper itself

Abstract

Importance: Poor-quality handoffs can lead to medical errors when transitioning patient care. Biased language within handoffs may contribute to errors and lead to disparities in health care delivery. Objective: To compare clinical information recall accuracy and attitudes toward patients among trainees in paired cases of biased vs neutral language in simulated handoffs. Design, Setting, and Participants: Surveys administered from April 29 to June 15 and from July 20 to October 10, 2023, included 3 simulated verbal handoffs, randomized between biased and neutral, and measured clinical information recall, attitudes toward patients, and key takeaways after each handoff. Participants included residents in internal medicine, pediatrics, and internal medicine-pediatrics and senior medical students at 2 academic medical centers in different geographic regions of the US. Data were analyzed from November 2023 to June 2024. Exposures: Each participant received 3 handoffs that were based on real handoffs about Black patients at 1 academic center. These handoffs were each randomized to either a biased or neutral version. Biased handoffs had 1 of 3 types of bias: stereotype, blame, or doubt. The order of handoff presentation was also randomized. Internal medicine and pediatrics residents received slightly different surveys, tailored for their specialty. Internal medicine-pediatrics residents received the pediatric survey. Medical students were randomly assigned the survey type. Main Outcomes and Measures: Each handoff was followed by a clinical information recall question, an adapted version of the Provider Attitudes Toward Sickle Cell Patients Scale (PASS), and 3 free-response takeaways. Results: Of 748 trainees contacted, 169 participants (142 residents and 27 medical students) completed the survey (23% overall response rate), distributed across institutions, residency programs, and years of training (95 female [56%]; mean [SD] age, 28.6 [2.3] years). Participants who received handoffs with blame-based bias had less accurate information recall than those who received neutral handoffs (77% vs 93%; P = .005). Those who reported bias as a key takeaway of the handoff had lower clinical information recall accuracy than those who did not (85% vs 93%; P = .01). Participants had less positive attitudes toward patients per PASS scores after receiving biased compared with neutral handoffs (mean scores, 22.9 [3.3] vs 25.2 [2.7]; P < .001). More positive attitudes toward patients were associated with higher clinical information recall accuracy (odds ratio, 1.12; 95% CI, 1.02-1.22). Conclusions and Relevance: In this survey study of residents and medical students, biased handoffs impeded accurate transfer of key clinical information and decreased empathy, potentially endangering patients and worsening health disparities. Handoff standardization is critical to addressing racial bias and improving patient safety.

Indexed as

Internship and ResidencyPatient HandoffAdultAttitude of Health PersonnelBiasFemaleHumansInternal MedicineLanguageMaleMental RecallPediatricsStudents, MedicalSurveys and Questionnaires

Identifiers

PMID39688867
PMCPMC11653120

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.