Evidence map›Paper›PMID 28320692›Full record

ArticleJournal of medical Internet research2017

Longitudinal Changes in Psychological States in Online Health Community Members: Understanding the Long-Term Effects of Participating in an Online Depression Community.

Albert Park, Mike Conway

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
13.9field-weighted citation impact, top 1% of its field
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

38 citing papers in PubMed, 101 citations in OpenAlex.

  1. Article
  2. Article
  3. Endometriosis Communities on Reddit: Quantitative Analysis.Journal of medical Internet research · 2025
    Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Emotional Contagion in the Online Depression Community.Healthcare (Basel, Switzerland) · 2021
    Article
  18. Article
  19. What Happens When People with Depression Gather Online?International journal of environmental research and public health · 2021
    Article
  20. 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 at 1 institution in 1 country.

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
University of Utah · US

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

backgroundMajor depression is a serious challenge at both the individual and population levels. Although online health communities have shown the potential to reduce the symptoms of depression, emotional contagion theory suggests that negative emotion can spread within a community, and prolonged interactions with other depressed individuals has potential to worsen the symptoms of depression.

objectiveThe goals of our study were to investigate longitudinal changes in psychological states that are manifested through linguistic changes in depression community members who are interacting with other depressed individuals.

methodsWe examined emotion-related language usages using the Linguistic Inquiry and Word Count (LIWC) program for each member of a depression community from Reddit. To measure the changes, we applied linear least-squares regression to the LIWC scores against the interaction sequence for each member. We measured the differences in linguistic changes against three online health communities focusing on positive emotion, diabetes, and irritable bowel syndrome.

resultsOn average, members of an online depression community showed improvement in 9 of 10 prespecified linguistic dimensions: "positive emotion," "negative emotion," "anxiety," "anger," "sadness," "first person singular," "negation," "swear words," and "death." Moreover, these members improved either significantly or at least as much as members of other online health communities.

conclusionsWe provide new insights into the impact of prolonged participation in an online depression community and highlight the positive emotion change in members. The findings of this study should be interpreted with caution, because participating in an online depression community is not the sole factor for improvement or worsening of depressive symptoms. Still, the consistent statistical results including comparative analyses with different communities could indicate that the emotion-related language usage of depression community members are improving either significantly or at least as much as members of other online communities. On the basis of these findings, we contribute practical suggestions for designing online depression communities to enhance psychosocial benefit gains for members. We consider these results to be an important step toward a better understanding of the impact of prolonged participation in an online depression community, in addition to providing insights into the long-term psychosocial well-being of members.

Indexed as

InternetSocial MediaAdultCommunity NetworksDepressionFemaleHumansLinguisticsLongitudinal StudiesMajor Depressive DisorderMaleMental HealthSocial Networkingcommunications mediacommunity networksconsumer health informationdepressioninformaticsinformation sciencemental healthpsychosocial support systemself-help groupssocial support

Identifiers

PMID28320692
PMCPMC5379019
OpenAlexW2603861002

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.