Cited by 27Health Literacy and Information AccessibilityMedia Influence and HealthInnovative Human-Technology Interaction

Vicarious Interactions in Online Support Communities: The Roles of Visual Anonymity and Social Identification

Open access
Dai, Yue (Nancy), Shi, Jingyuan·2022·Journal of Computer-Mediated Communication

Abstract

Online information seekers often do not actively post or engage in interactions with others, inviting research on how passive users of online communities benefit from the information they see. Based on the social identity model of deindividuation effects model (SIDE) and social identity theory, we proposed and tested the idea that observers of a supportive interaction online could relate to the observed support seeker based on their shared gender and, in turn, become vicariously influenced by the support provider’s message to the support seeker. An experiment using a sample of young adults (N = 326) in the United States provided support to the proposition. Furthermore, the outcomes of the vicarious interaction were qualified by the genders of the observed interactants and enhanced by the lack of profile photos. The findings advance the understandings of vicarious interaction in online context and guide the design of online communities to promote mental well-being. Lay Summary Ample evidence shows that people benefit tremendously from participating in online health support communities, but less is understood about how people who do not actively participate in interactions benefit from these communities. We conducted an online experiment using a sample of young adults in the United States. The results showed that females, compared with males, are more likely to be persuaded to seek professional counseling for mental health issues from observing a supportive conversation online. The persuasive effect of reading supportive interactions was enhanced when female participants shared the same gender with the observed support seeker and when the observed interactants had no profile photos.

Integrity signals

Registry

Crossref · 10.1093/jcmc/zmac006

Cites

52 of 52 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Dai, Y. (., & Shi, J.
Affiliations
  • Department of Media and Communication, City University of Hong Kong, Hong Kong
  • Hong Kong Baptist University (HK)
Venue
Journal of Computer-Mediated Communication
Published
2022-03-23
Volume
27
Issue
3
ISSN
1083-6101 (ISSN-L)
OpenAlex
W4213142182
Cited by
27
References
52
Citations by year
2026: 5 · 2025: 10 · 2024: 6 · 2023: 5 · 2022: 1
FWCI
6.32
Type
journal article
Language
en
Open access
Locations
  • Journal of Computer-Mediated Communication (publishedVersion, cc-by)
  • CityU Scholars (submittedVersion, cc-by)
Funders
  • Department of Media and Communication, City University of Hong Kong (9618015)
  • City University of Hong Kong
  • Hong Kong Baptist University
Topics
  • Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
  • Social Sciences › Arts and Humanities › Literature and Literary Theory › Media Influence and Health
  • Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
Keywords
online support groups, social identification, gender similarity, deindividuation, persuasiveness, mental health help-seeking, professional counseling, profile pictures, young adults

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review