Testing the Impact of the #chatsafe Intervention on Young People’s Ability to Communicate Safely About Suicide on Social Media: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Suicide is the leading cause of death among Australians. One commonly cited explanation is the impact of social media, in particular, the ways in which young people use social media to communicate about their own experiences and their exposure to suicide-related content posted by others. Guidelines designed to assist mainstream media to safely report about suicide are widespread. Until recently, no guidelines existed that targeted social media or young people. In response, we developed the #chatsafe guidelines and a supporting social media campaign, which together make up the #chatsafe intervention. The intervention was tested in a pilot study with positive results. However, the study was limited by the lack of a control group. OBJECTIVE: The aim of this study is to assess the impact of the #chatsafe social media intervention on young people's safety and confidence when communicating on the web about suicide. METHODS: The study employs a pragmatic, parallel, superiority randomized controlled design. It will be conducted in accordance with the Consolidated Standards of Reporting Trials statement over 18 months. Participants will be 400 young people aged 16-25 years (200 per arm). Participants will be recruited via social media advertising and assessed at 3 time points: time 1-baseline; time 2-8-week postintervention commencement; and time 3-4-week postintervention. They will be asked to complete a weekly survey to monitor safety and evaluate each piece of social media content. The intervention comprises an 8-week social media campaign including social media posts shared on public Instagram profiles. The intervention group will receive the #chatsafe suicide prevention content and the control group will receive sexual health content. Both groups will receive 24 pieces of content delivered to their mobile phones via text message. The primary outcome is safety when communicating on the web about suicide, as measured via the purpose-designed #chatsafe online safety questionnaire. Additional outcomes include willingness to intervene against suicide, internet self-efficacy, safety, and acceptability. RESULTS: The study was funded in November 2020, approved by the University of Melbourne Human Research Ethics Committee on October 7, 2022, and prospectively registered with the Australian New Zealand Clinical Trials registry. Trial recruitment began in November 2022 and study completion is anticipated by June 2024. CONCLUSIONS: This will be the first randomized controlled trial internationally to test the impact of a social media intervention designed to equip young people to communicate safely on the web about suicide. Given the rising rates of youth suicide in Australia and the acceptability of social media among young people, incorporating social media-based interventions into the suicide prevention landscape is an obvious next step. This intervention, if effective, could also be extended internationally, thereby improving web-based safety for young people not just in Australia but globally. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12622001397707; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=384318. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/44300.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.057 | 0.055 |
| Meta-epidemiology (narrow) | 0.008 | 0.005 |
| Meta-epidemiology (broad) | 0.014 | 0.010 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.077 | 0.013 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".