Evidence map›Paper›PMID 33912649›Full record

ArticleSSM - population health2021

The asymmetries of the biopsychosocial model of depression in lay discourses - Topic modelling online depression forums.

Renáta Németh, Domonkos Sik, Eszter Katona

Abstract read
In one paragraph

Article in SSM - population health, 2021. 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

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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.

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4 · The record

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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.

Renáta NémethELTE Eötvös Loránd University of Budapest, Faculty of Social Sciences, Research Center for Computational Social Science, Budapest, Pázmány Péter Sétány 1/a, 1117, Hungary.
Domonkos SikELTE Eötvös Loránd University of Budapest, Faculty of Social Sciences, Research Center for Computational Social Science, Budapest, Pázmány Péter Sétány 1/a, 1117, Hungary.
Eszter KatonaELTE Eötvös Loránd University of Budapest, Faculty of Social Sciences, Research Center for Computational Social Science, Budapest, Pázmány Péter Sétány 1/a, 1117, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOne of the most comprehensive approaches to depression is the biopsychosocial model. From this wider perspective, social sciences have criticized the reductionist biomedical discourse, which has been dominating expert discourses for a long time. As these discourses determine the horizon of attributions and interventions, their lay interpretation plays a central role in the coping with depression.

methodsIn order to map these patterns, online depression forums are analyzed with natural language processing methods, where computational tools are complemented with a qualitative approach. Latent Dirichlet Allocation topic model of depression-related posts from the most popular English-speaking online health discussion forums (N = ~70 000) reveals the monolog (attributions and self-disclosures) and interactive (consultations and quasi-therapeutic interactions) patterns.

resultsFollowing the evaluation of various models 18 topics were differentiated:

conclusionsBiomedical discourse is underrepresented in lay discussions, while psychological discourse plays an overall dominant role. Even if actors are initially aware of the social mechanisms contributing to depression, they neglect these factors when it comes to considering the countermeasures.

Indexed as

Biopsychosocial modelDepressionLatent dirichlet allocationNatural language processingOnline forumTopic model

Identifiers

PMID33912649
PMCPMC8066842

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.