ArticleDrug and alcohol dependence2025
Words matter: Stigmatizing language in medical records of individuals electing medication for opioid use disorder.
Article in Drug and alcohol dependence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
backgroundThere has been a concerted effort to minimize the use of stigmatizing language in healthcare settings; however, its prevalence in health record documentation remains high. This study examined clinicians' stigmatizing and patients' self-stigmatizing language in medical records for patients electing medication for opioid use disorder in two settings, office-based opioid treatment and opioid treatment programs.
methodsIn this retrospective cohort study, data were extracted from health records for a distributed provider network serving publicly funded patients in Texas. Patients seeking medication treatment for opioid use disorder between December 2020 and November 2021 were included. Using a natural language processing algorithm to review open text fields in the health records, we identified the prevalence of stigmatizing language identified in the National Institute on Drug Abuse's "Words Matter" tool.
resultsThe analytic sample included 1391 patients (63.8 % White, 27.5 % Hispanic, 40.5 % female, M
conclusionsFindings suggest that a patient's sociodemographic background influences the stigmatizing language their clinicians use while treatment setting influences both provider and self-stigmatizing language. Additional research is needed to explore whether differences in stigmatizing language contributes to differential treatment outcomes seen in different opioid treatment settings.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.