Online Peer-to-Peer Support for Young People With Mental Health Problems: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Adolescence and early adulthood are critical periods for the development of mental disorders. Online peer-to-peer communication is popular among young people and may improve mental health by providing social support. Previous systematic reviews have targeted Internet support groups for adults with mental health problems, including depression. However, there have been no systematic reviews examining the effectiveness of online peer-to-peer support in improving the mental health of adolescents and young adults. OBJECTIVE: The aim of this review was to systematically identify available evidence for the effectiveness of online peer-to peer support for young people with mental health problems. METHODS: The PubMed, PsycInfo, and Cochrane databases were searched using keywords and Medical Subject Headings (MeSH) terms. Retrieved abstracts (n=3934) were double screened and coded. Studies were included if they (1) investigated an online peer-to-peer interaction, (2) the interaction discussed topics related to mental health, (3) the age range of the sample was between 12 to 25 years, and (4) the study evaluated the effectiveness of the peer-to-peer interaction. RESULTS: Six studies satisfied the inclusion criteria for the current review. The studies targeted a range of mental health problems including depression and anxiety (n=2), general psychological problems (n=1), eating disorders (n=1), and substance use (tobacco) (n=2). The majority of studies investigated Internet support groups (n=4), and the remaining studies focused on virtual reality chat sessions (n=2). In almost all studies (n=5), the peer support intervention was moderated by health professionals, researchers or consumers. Studies employed a range of study designs including randomized controlled trials (n=3), pre-post studies (n=2) and one randomized trial. Overall, two of the randomized controlled trials were associated with a significant positive outcome in comparison to the control group at post-intervention. In the remaining four studies, peer-to-peer support was not found to be effective. CONCLUSIONS: This systematic review identified an overall lack of high-quality studies examining online peer-to-peer support for young people. Given that peer support is frequently used as an adjunct to Internet interventions for a variety of mental health conditions, there is an urgent need to determine the effectiveness of peer support alone as an active intervention.
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 | 0.008 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".