Young People Seeking Help Online for Mental Health: Cross-Sectional Survey Study
Bibliographic record
Abstract
BACKGROUND: Young people are particularly vulnerable to experiencing mental health difficulties, but very few seek treatment or help during this time. Online help-seeking may offer an additional domain where young people can seek aid for mental health difficulties, yet our current understanding of how young people seek help online is limited. OBJECTIVE: This was an exploratory study which aimed to investigate the online help-seeking behaviors and preferences of young people. METHODS: This study made use of an anonymous online survey. Young people aged 18-25, living in Ireland, were recruited through social media ads on Twitter and Facebook and participated in the survey. RESULTS: A total of 1308 respondents completed the survey. Many of the respondents (80.66%; 1055/1308) indicated that they would use their mobile phone to look online for help for a personal or emotional concern. When looking for help online, 82.57% (1080/1308) of participants made use of an Internet search, while 57.03% (746/1308) made use of a health website. When asked about their satisfaction with these resources, 36.94% (399/1080) indicated that they were satisfied or very satisfied with an Internet search while 49.33% (368/746) indicated that they were satisfied or very satisfied with a health website. When asked about credibility, health websites were found to be the most trustworthy, with 39.45% (516/1308) indicating that they found them to be trustworthy or very trustworthy. Most of the respondents (82.95%; 1085/1308) indicated that a health service logo was an important indicator of credibility, as was an endorsement by schools and colleges (54.97%; 719/1308). Important facilitators of online help-seeking included the anonymity and confidentiality offered by the Internet, with 80% (1046/1308) of the sample indicating that it influenced their decision a lot or quite a lot. A noted barrier was being uncertain whether information on an online resource was reliable, with 55.96% (732/1308) of the respondents indicating that this influenced their decision a lot or quite a lot. CONCLUSIONS: Findings from this survey suggest that young people are engaging with web-based mental health resources to assist them with their mental health concerns. However, levels of satisfaction with the available resources vary. Young people are engaging in strategies to assign credibility to web-based resources, however, uncertainty around their reliability is a significant barrier to online help-seeking.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".