Effect of TikTok on Self-Harm and Suicidal Behavior in the Adolescent Population: Protocol for a Systematic Review
Bibliographic record
Abstract
BACKGROUND: Social media use among adolescents and young adults has increased exponentially over the last decade, with TikTok being one of the most popular platforms. In Spain, 61% of adolescents use TikTok, spending an average of 1.5 hours daily on the app. This phenomenon coincides with an alarming increase in the prevalence of self-harm and suicidal behavior among adolescents and young adults. Moreover, suicidal behavior is one of the leading causes of morbidity and mortality in this age group. OBJECTIVE: The primary aim of this study is to evaluate the existing evidence on the association of TikTok use with self-harm and suicidal behavior in the adolescent population. METHODS: This systematic review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines to ensure transparency, rigor, and reproducibility. Original studies that evaluate the impact of TikTok use on self-harm and suicidal behavior will be selected. The primary outcome will be the occurrence and prevalence of self-harm and suicidal behavior related to TikTok use among adolescents and young adults. Health science literature databases, including PubMed/MEDLINE, Cochrane, Web of Science, PsycINFO, and Scopus, will be searched. Two researchers will independently select studies that meet the predefined eligibility criteria, and they will extract data from each included study. The risk of bias and methodological quality of the included studies will be assessed using the Risk of Bias in Non-Randomized Studies of Interventions and Joanna Briggs Institute tools, respectively. The methodological characteristics, association measures, and qualitative conclusions of the reviewed studies will be analyzed, and a descriptive synthesis will be presented through tables and graphs. RESULTS: This systematic review formally began in July 2025, although it has been planned since September 2024. The final systematic review will be performed and reported according to this protocol and the PRISMA guidelines. Initially, the search returned 6126 records, and 3664 records are currently being screened for eligibility. Data from the final included studies will be extracted, collated, and analyzed. The risk of bias and quality of evidence will be determined. A narrative synthesis will be used to summarize the results of the systematic review. When possible, statistical analyses will be presented using graphs and figures. The final systematic review is expected to be published in December 2025. CONCLUSIONS: This systematic review will help to better understand the relationship between TikTok use and self-harm and suicidal behavior among adolescents and young adults. Our findings may support future research, recommendations, and policies in this field, emphasizing the need to incorporate the digital environment as a key factor in adolescent mental health. TRIAL REGISTRATION: Open Science Framework MX5CJ; https://osf.io/MX5CJ. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/78600.
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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 | 0.071 | 0.076 |
| Meta-epidemiology (narrow) | 0.007 | 0.006 |
| Meta-epidemiology (broad) | 0.022 | 0.024 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.080 | 0.010 |
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".