Evidence map›Paper›PMID 29636316›Full record

ArticleJournal of medical Internet research2018

Harnessing Reddit to Understand the Written-Communication Challenges Experienced by Individuals With Mental Health Disorders: Analysis of Texts From Mental Health Communities.

Albert Park, Mike Conway

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

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  19. Mental Health Severity Detection from Psychological Forum Data using Domain-Specific Unlabelled Data.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2020
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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

2 authors.

Albert ParkDepartment of Biomedical Informatics, School of Medicine, University of Utah, Salt Lake City, UT, United States.ORCID 0000-0002-2419-0131
Mike ConwayDepartment of Biomedical Informatics, School of Medicine, University of Utah, Salt Lake City, UT, United States.ORCID 0000-0002-3209-8108

Funding

UNIVERSITY OF UTAH MEDICAL INFORMATICS TRAININGT15LM007124 · NLM · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Karen Louise Eilbeck · 1997 to 2026
$22.0M
Utilizing social media as a resource for mental health surveillanceR00LM011393 · NLM · UNIVERSITY OF UTAH · PI CONWAY, MICHAEL AMBROSE · 2014 to 2016
$667k
Utilizing social media as a resource for mental health surveillanceK99LM011393 · NLM · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CONWAY, MICHAEL AMBROSE · 2013 to 2013
$83k
NLM NIH HHS K99 LM011393NLM NIH HHS R00 LM011393NLM NIH HHS T15 LM007124
6 · The paper itself

Abstract

backgroundMental disorders such as depression, bipolar disorder, and schizophrenia are common, incapacitating, and have the potential to be fatal. Despite the prevalence and gravity of mental disorders, our knowledge concerning everyday challenges associated with them is relatively limited. One of the most studied deficits related to everyday challenges is language impairment, yet we do not know how mental disorders can impact common forms of written communication, for example, social media.

objectiveThe aims of this study were to investigate written communication challenges manifest in online mental health communities focusing on depression, bipolar disorder, and schizophrenia, as well as the impact of participating in these online mental health communities on written communication. As the control, we selected three online health communities focusing on positive emotion, exercising, and weight management.

methodsWe examined lexical diversity and readability, both important features for measuring the quality of writing. We used four well-established readability metrics that consider word frequencies and syntactic complexity to measure writers' written communication ability. We then measured the lexical diversity by calculating the percentage of unique words in posts. To compare lexical diversity and readability among communities, we first applied pairwise independent sample t tests, followed by P value adjustments using the prespecified Hommel procedure to adjust for multiple comparison. To measure the changes, we applied linear least squares regression to the readability and lexical diversity scores against the interaction sequence for each member, followed by pairwise independent sample t tests and P value adjustments. Given the large sample of members, we also report effect sizes and 95% CIs for the pairwise comparisons.

resultsOn average, members of depression, bipolar disorder, and schizophrenia communities showed indications of difficulty expressing their ideas compared with three other online health communities. Our results also suggest that participating in these platforms has the potential to improve members' written communication. For example, members of all three mental health communities showed statistically significant improvement in both lexical diversity and readability compared with members of the OHC focusing on positive emotion.

conclusionsWe provide new insights into the written communication challenges faced by individuals suffering from depression, bipolar disorder, and schizophrenia. A comparison with three other online health communities suggests that written communication in mental health communities is significantly more difficult to read, while also consisting of a significantly less diverse lexicon. We contribute practical suggestions for utilizing our findings in Web-based communication settings to enhance members' communicative experience. We consider these findings to be an important step toward understanding and addressing everyday written communication challenges among individuals suffering from mental disorders.

Indexed as

CommunicationComprehensionFemaleHumansMaleMental HealthSocial MediaText Messagingbipolarbipolar and related disordersbipolar disordercommunications mediacommunity networksconsumer health informationdepressiondepressive disorderdepressive disorder, majorinformaticsinformation sciencemental healthpsychosocial support systemschizophreniaschizophrenia spectrum and other psychotic disordersschizotypal personality disorderself-help groupssocial support

Identifiers

PMID29636316
PMCPMC5915669

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LicenceCC BY
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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.