ArticleJMIR human factors2025
Exploring Mental Health Content Moderation and Well-Being Tools on Social Media Platforms: Walkthrough Analysis.
Article in JMIR human factors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSocial networking site (SNS) users may experience mental health difficulties themselves or engage with mental health-related content on these platforms. While SNSs use moderation systems and user tools to limit harmful content availability, concerns persist regarding the implementation and effectiveness of these methods.
objectiveThis study aimed to use an ethnographic walkthrough method to critically evaluate 4 SNSs-Instagram, TikTok, Tumblr, and Tellmi.
methodsWalkthrough methods were used to identify and analyze mental health content moderation and safety and well-being resources of SNS platforms. We completed systematic checklists for each of the SNS platforms and then used thematic analysis to interpret the data.
resultsFindings highlighted both successes and challenges in balancing user safety and content moderation across platforms. While varied mental health resources were available on platforms, several issues emerged, including redundancy of information, broken links, and a lack of non-US-centric resources. In addition, despite the presence of several self-moderation tool options, there was insufficient evidence of user education and testing around these features, potentially limiting their effectiveness. Platforms also faced difficulties addressing harmful mental health content due to unclear language around what was allowed or disallowed. This was especially evident in the management of mental health-related terminology, where the emergence of "algospeak," where users adopt alternative codewords or phrases to avoid having content removed or banned by moderation systems, highlighted how users easily bypass platform censorship. Furthermore, platforms did not detail support for reporters or reportees of mental health-related content, leaving users susceptible.
conclusionsOur study resulted in the production of preliminary recommendations for platforms regarding potential mental health content moderation and well-being procedures and tools. We also emphasized the need for more inclusive user-centered design, feedback, and research to improve SNS safety and moderation features.
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.