This paper is in the following e-collection/theme issue:

Peer-to-Peer Support and Online Communities (592)

Published on in Vol 19, No 2 (2017): February

Demographic and Indication-Specific Characteristics Have Limited Association With Social Network Engagement: Evidence From 24,954 Members of Four Health Care Support Groups

Demographic and Indication-Specific Characteristics Have Limited Association With Social Network Engagement: Evidence From 24,954 Members of Four Health Care Support Groups

Demographic and Indication-Specific Characteristics Have Limited Association With Social Network Engagement: Evidence From 24,954 Members of Four Health Care Support Groups

Authors of this article:

Trevor van Mierlo1, 2 Author Orcid Image ;   Xinlong Li3 Author Orcid Image ;   Douglas Hyatt3 Author Orcid Image ;   Andrew T Ching3 Author Orcid Image
Article Authors Cited by (10) Tweetations (18) Metrics

Journals

  1. Geramita E, Herbeck Belnap B, Abebe K, Rothenberger S, Rotondi A, Rollman B. The Association Between Increased Levels of Patient Engagement With an Internet Support Group and Improved Mental Health Outcomes at 6-Month Follow-Up: Post-Hoc Analyses From a Randomized Controlled Trial. Journal of Medical Internet Research 2018;20(7):e10402 View
  2. Feldhege J, Moessner M, Bauer S. Who says what? Content and participation characteristics in an online depression community. Journal of Affective Disorders 2020;263:521 View
  3. Gopalsamy R, Semenov A, Pasiliao E, McIntosh S, Nikolaev A. Engagement as a Driver of Growth of Online Health Forums: Observational Study. Journal of Medical Internet Research 2017;19(8):e304 View
  4. Sieverink F, Kelders S, Poel M, van Gemert-Pijnen L. Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data. JMIR Research Protocols 2017;6(8):e156 View
  5. Joglekar S, Sastry N, Coulson N, Taylor S, Patel A, Duschinsky R, Anand A, Jameson Evans M, Griffiths C, Sheikh A, Panzarasa P, De Simoni A. How Online Communities of People With Long-Term Conditions Function and Evolve: Network Analysis of the Structure and Dynamics of the Asthma UK and British Lung Foundation Online Communities. Journal of Medical Internet Research 2018;20(7):e238 View
  6. Taylor J, Pagliari C. Mining social media data: How are research sponsors and researchers addressing the ethical challenges?. Research Ethics 2018;14(2):1 View
  7. Myneni S, Lewis B, Singh T, Paiva K, Kim S, Cebula A, Villanueva G, Wang J. Diabetes Self-Management in the Age of Social Media: Large-Scale Analysis of Peer Interactions Using Semiautomated Methods. JMIR Medical Informatics 2020;8(6):e18441 View
  8. Skaczkowski G, van der Kruk S, Loxton S, Hughes-Barton D, Howell C, Turnbull D, Jensen N, Smout M, Gunn K. Web-Based Interventions to Help Australian Adults Address Depression, Anxiety, Suicidal Ideation, and General Mental Well-being: Scoping Review. JMIR Mental Health 2022;9(2):e31018 View
  9. Rondina R, van Mierlo T, Fournier R. Testing Behavioral Nudges and Prompts in Digital Courses for the Self-guided Treatment of Depression and Anxiety: Protocol for a 3-Arm Randomized Controlled Trial. JMIR Research Protocols 2022;11(8):e37231 View
  10. van Mierlo T, Rondina R, Fournier R. Nudges and Prompts Increase Engagement in Self-Guided Digital Health Treatment for Depression and Anxiety: Results From a 3-Arm Randomized Controlled Trial. JMIR Formative Research 2024;8:e52558 View