Evidence map›Paper›PMID 36845987›Full record

ArticleDrug and alcohol dependence reports2022

Examining stigma relating to substance use and contextual factors in social media discussions.

Annie T Chen, Shana Johnny, Mike Conway

Abstract read
In one paragraph

Article in Drug and alcohol dependence reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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

3 authors.

Annie T ChenUniversity of Washington School of Medicine, Biomedical Informatics and Medical Education, Box 358047, 850 Republican St., Seattle, WA 98109, United States.
Shana JohnnyUniversity of Washington School of Nursing, Box 357260, Seattle, WA 98195, United States.
Mike ConwayUniversity of Utah, Department of Biomedical Informatics, 421 Wakara Way #140, Salt Lake City, UT 84108, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Stigma associated with substance use can have severe negative consequences for physical and mental health and serve as a barrier to treatment. Yet, research on stigma processes and stigma reduction interventions is limited. Aim: We use a social media dataset to examine: 1) the nature of stigma-related experience related to substance use; and 2) salient affective and temporal factors in the use of three substances: alcohol, cannabis, and opioids. Methods: We harvested several years of data pertaining to three substances - alcohol, cannabis, and opioids - from Reddit, a popular social networking platform. For Part I, we selected posts based on stigma-related keywords, performed content analysis, and rendered word clouds to examine the nature of stigma associated with these substances. In Part II, we employed natural language processing in conjunction with hierarchical clustering and visualization to explore temporal and affective factors. Results: In Part I, internalized stigma was most commonly exhibited. Anticipated and enacted stigma were less common in posts relating to cannabis compared to the other two substances. Work, home, and school were important contexts in which stigma was observed. Part II showed that temporal markers were prominent; post authors shared stories of substance use journeys, and timelines of their experience with quitting and withdrawals. Shame, sadness, anxiety, and fear were common, with shame being more prominent in alcohol-related posts. Conclusion: Our findings highlight the importance of contextual factors in substance use recovery and stigma reduction and offer directions for future interventions.

Indexed as

AffectAlcoholCannabisContextual factorsOpioidsSocial mediaStigma

Identifiers

PMID36845987
PMCPMC9948814

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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.