Evidence map›Paper›PMID 30139369›Full record

ArticleSubstance abuse treatment, prevention, and policy2018

How broad are state physician health program descriptions of physician impairment?

Nicholas D Lawson, J Wesley Boyd

Abstract read
In one paragraph

Article in Substance abuse treatment, prevention, and policy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Health conditions that impact fitness-to-practice in physicians: a scoping review.International journal for quality in health care : journal of the International Society for Quality in Health Care · 2025
    Article
  2. 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

2 authors.

Nicholas D LawsonGeorgetown University Law Center, 600 New Jersey Ave NW, Washington, DC, 20001, USA. nick.d.lawson@gmail.com.ORCID 0000-0003-3333-0922
J Wesley BoydDepartment of Psychiatry, Cambridge Health Alliance/Harvard Medical School, 26 Central St, Somerville, MA, 02143, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPhysician health program websites in 23 states provide many descriptions of possible physician impairment. This study sought to determine whether these descriptions are so broad that almost everyone might potentially be suspected of being impaired given these descriptions.

methodsThe authors randomly selected 25 descriptions of impairment and then presented them anonymously online to members of the general population in full-time employment through Amazon's Mechanical Turk (N = 199). Half of the respondents randomly received a narrowly worded version, and half received a broadly worded version of the survey questions.

resultsIn the narrowly worded version of the survey, 70.9% of respondents endorsed at least one description of impairment, and 59.2% endorsed more than one. In the broadly phrased version, 96.9% endorsed at least one description, and 95.8% endorsed more than one. These respondents endorsed a median of 10 out of 25 (40%) descriptions.

conclusionsThese findings call into question whether these descriptions really identify persons with poor performance or who pose a high risk of substantial, imminent harm to self or others in the workplace. They also demonstrate the extent to which these descriptions could potentially be misapplied and brand almost anyone as impaired.

Indexed as

Program DevelopmentHealth ServicesHumansInternetPhysician ImpairmentPublic OpinionAddictionAmericans with Disabilities ActCoercionDiscriminationPhysician health programPhysician impairmentPhysician suicideStigmaSubstance use disorderWell-beingWellness

Identifiers

PMID30139369
PMCPMC6107949

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.