Seeking mental health information and support online: experiences and perspectives of young people receiving treatment for first‐episode psychosis
Bibliographic record
Abstract
AIM: Limited knowledge exists on youth mental health service users' experiences and perspectives of seeking mental health information, services and support online. Such information is important for developing online resources that are tailored to the needs of youth with different types of mental health concerns. The purpose of this study was to better understand the experiences and perspectives of young people receiving treatment for first-episode psychosis (FEP) on using web-based and mobile technologies for accessing mental health information, services and support. METHODS: A qualitative approach using focus group methods was used. Seventeen participants between the ages of 21 and 35 were recruited from a specialized early intervention program for psychosis. A thematic analysis was conducted. RESULTS: The results are organized under three related themes: striving towards a better understanding of the illness and treatment; encountering multiple issues with accessing information online; and valuing online mental health information and support. The majority of participants described online activities related to information and support, rather than specific types of mental health services or interventions. CONCLUSIONS: Youth receiving treatment for FEP value accessing mental health information and support online; however, they encounter several challenges in this regard. The findings can inform the development of online resources and strategies that meet the needs of service users. This study also highlights the importance for mental healthcare professionals to address the topic of online mental health information and support seeking within the context of providing services to young people.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".