Evidence map›Paper›PMID 28634909›Full record

Observational studyJournal of general internal medicine2017

Categorical Risk Perception Drives Variability in Antibiotic Prescribing in the Emergency Department: A Mixed Methods Observational Study.

Eili Y Klein, Elena M Martinez, Larissa May, Mustapha Saheed, Valerie Reyna, David A Broniatowski

Open access · bronzeAbstract readMulticenter StudyObservational Study
In one paragraph

Observational study in Journal of general internal medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
5.7field-weighted citation impact, top 3% of its field
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

33 citing papers in PubMed, 63 citations in OpenAlex.

  1. Trial
  2. Determinants of Physicians' Referrals for Suspected Cancer Given a Risk-Prediction Algorithm: Linking Signal Detection and Fuzzy Trace Theory.Medical decision making : an international journal of the Society for Medical Decision Making · 2026
    Article
  3. Article
  4. Article
  5. Shifting the antibiotic rhetoric in children from 'just in case' to 'disclose the risk': Has the time come?Journal of the Association of Medical Microbiology and Infectious Disease Canada = Journal officiel de l'Association pour la microbiologie medicale et l'infectiologie Canada · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Supporting Health and Medical Decision Making: Findings and Insights from Fuzzy-Trace Theory.Medical decision making : an international journal of the Society for Medical Decision Making · 2022
    Article
  11. Article
  12. Viruses, Vaccines, and COVID-19: Explaining and Improving Risky Decision-making.Journal of applied research in memory and cognition · 2021
    Article
  13. Article
  14. Review
  15. A scientific theory of gist communication and misinformation resistance, with implications for health, education, and policy.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Review
  16. Article
  17. To illuminate and motivate: A fuzzy-trace model of the spread of information online.Computational and mathematical organization theory · 2020
    Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 5 institutions in 1 country.

Eili Y KleinDepartment of Emergency Medicine, Johns Hopkins School of Medicine, 5801 Smith Avenue, Suite 3220, Office 265, Davis Building, Baltimore, MD, 21209, USA. eklein@jhu.edu.
Elena M MartinezCenter for Disease Dynamics, Economics & Policy, Washington, DC, USA.
Larissa MayDepartment of Emergency Medicine, University of California, Davis, Sacramento, CA, USA.
Mustapha SaheedDepartment of Emergency Medicine, Johns Hopkins School of Medicine, 5801 Smith Avenue, Suite 3220, Office 265, Davis Building, Baltimore, MD, 21209, USA.
Valerie ReynaHuman Neuroscience Institute, Center for Behavioral Economics and Decision Research and Human Neuroscience Institute, Cornell University, Ithaca, NY, USA.
David A BroniatowskiDepartment of Engineering Management and Systems Engineering, The George Washington University, Washington, DC, USA.
Johns Hopkins University · USCenter for Disease Dynamics, Economics & Policy · USDecision Research · USGeorge Washington University · USUniversity of California, Davis · US

Funding

Supplementing Survey-Based Analyses of Group Vaccination Narratives and Behaviors Using Social MediaR01GM114771 · NIGMS · GEORGE WASHINGTON UNIVERSITY · PI BRONIATOWSKI, DAVID ANDRE, QUINN, SANDRA CROUSE · 2015 to 2019
$1.6M
NIGMS NIH HHS R01 GM114771
6 · The paper itself

Abstract

backgroundAdherence to evidence-based antibiotic therapy guidelines for treatment of upper respiratory tract infections (URIs) varies widely among clinicians. Understanding this variability is key for reducing inappropriate prescribing.

objectiveTo measure how emergency department (ED) clinicians' perceptions of antibiotic prescribing risks affect their decision-making.

designClinician survey based on fuzzy-trace theory, a theory of medical decision-making, combined with retrospective data on prescribing outcomes for URI/pneumonia visits in two EDs. The survey predicts the categorical meanings, or gists, that individuals derive from given information.

participantsED physicians, residents, and physician assistants (PAs) who completed surveys and treated patients with URI/pneumonia diagnoses between August 2014 and December 2015. MAIN MEASURES: Gists derived from survey responses and their association with rates of antibiotic prescribing per visit. KEY

resultsOf 4474 URI/pneumonia visits, 2874 (64.2%) had an antibiotic prescription. However, prescribing rates varied from 7% to 91% for the 69 clinicians surveyed (65.2% response rate). Clinicians who framed therapy-prescribing decisions as a categorical choice between continued illness and possibly beneficial treatment ("why not take a risk?" gist, which assumes antibiotic therapy is essentially harmless) had higher rates of prescribing (OR 1.28 [95% CI, 1.06-1.54]). Greater agreement with the "antibiotics may be harmful" gist was associated with lower prescribing rates (OR 0.81 [95% CI, 0.67-0.98]).

conclusionsOur results indicate that clinicians who perceive prescribing as a categorical choice between patients remaining ill or possibly improving from therapy are more likely to prescribe antibiotics. However, this strategy assumes that antibiotics are essentially harmless. Clinicians who framed decision-making as a choice between potential harms from therapy and continued patient illness (e.g., increased appreciation of potential harms) had lower prescribing rates. These results suggest that interventions to reduce inappropriate prescribing should emphasize the non-negligible possibility of serious side effects.

Indexed as

Drug PrescriptionsPerceptionAnti-Bacterial AgentsClinical Decision-MakingDrug Resistance, Multiple, BacterialEmergency Service, HospitalFemaleHumansInappropriate PrescribingMaleRisk FactorsSurveys and QuestionnairesAnti-Bacterial Agentsantibiotic resistancedrivers of decision-makingfuzzy-trace theorygist of antibiotic therapynon-negligible risks of unnecessary antibiotics

Identifiers

PMID28634909
PMCPMC5602760
OpenAlexW2627315765

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.