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.
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.
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
38 citing papers in PubMed, 101 citations in OpenAlex.
- Hierarchy and hope: Exploring AI's role in medicine through a thematic analysis of online discourse.PLOS digital health · 2026Article
- Discrete mathematical network analysis bridging clinical vocabulary and patient discourse in interstitial cystitis/bladder pain syndrome online communications.Scientific reports · 2025Article
- Endometriosis Communities on Reddit: Quantitative Analysis.Journal of medical Internet research · 2025Article
- Exploring the Use of Social Media for Medical Problem Solving by Analyzing the Subreddit r/medical_advice: Quantitative Analysis.JMIR infodemiology · 2025Article
- Changing Conversations: The Rise of Gender and Sexuality Discourse on Reddit.Archives of sexual behavior · 2025Article
- How developments in natural language processing help us in understanding human behaviour.Nature human behaviour · 2024Review
- Investigating Older Adults' Use of a Socially Assistive Robot via Time Series Clustering and User Profiling: Descriptive Analysis Study.JMIR formative research · 2024Article
- Predicting negative attitudes towards suicide in social media texts: prediction model development and validation study.Frontiers in public health · 2024Article
- Leveraging stylometry analysis to identify unique characteristics of peer support user groups in online mental health forums.Scientific reports · 2023Article
- Posting patterns in peer online support forums and their associations with emotions and mood in bipolar disorder: Exploratory analysis.PloS one · 2023Article
- Resilience in Web-Based Mental Health Communities: Building a Resilience Dictionary With Semiautomatic Text Analysis.JMIR formative research · 2022Article
- Exploring Users' Health Behavior Changes in Online Health Communities: Heuristic-Systematic Perspective Study.International journal of environmental research and public health · 2022Article
- Tweets Related to Motivation and Physical Activity for Obesity-Related Behavior Change: Descriptive Analysis.Journal of medical Internet research · 2022Article
- Do Informational and Emotional Elements Differ between Online Psychological and Physiological Disease Communities in China? A Comparative Study of Depression and Diabetes.International journal of environmental research and public health · 2022Article
- Article
- Studies of Depression and Anxiety Using Reddit as a Data Source: Scoping Review.JMIR mental health · 2021Article
- Emotional Contagion in the Online Depression Community.Healthcare (Basel, Switzerland) · 2021Article
- Determining the prevalence of cannabis, tobacco, and vaping device mentions in online communities using natural language processing.Drug and alcohol dependence · 2021Article
- What Happens When People with Depression Gather Online?International journal of environmental research and public health · 2021Article
- A Newly Developed Online Peer Support Community for Depression (Depression Connect): Qualitative Study.Journal of medical Internet research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
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
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.