Help-Seeking Behaviors of Transition-Aged Youth for Mental Health Concerns: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Transition-aged youth are particularly vulnerable to mental health problems, yet they are one of the least likely demographic groups to seek help. OBJECTIVE: The aim of this study is to explore the influences on and patterns in help-seeking for mental health concerns among transition-aged youth who attend postsecondary schools in Canada. METHODS: A qualitative research design was used, involving 12 semistructured focus groups with transition-aged youth (17-29 years) who attended postsecondary schools in Canada. A thematic analysis was conducted to code the transcripts and develop themes. RESULTS: Four main themes and subthemes regarding the process and experience of help-seeking were generated: (1) the influence of formal service providers (accessibility and experiences), (2) the influence of social factors (system navigation and stigma), (3) the influence of health literacy (symptom recognition, acting on symptoms, digital tools and the internet, and mental health awareness campaigns), and (4) the influence of low-intensity sources of support, namely, self-help. CONCLUSIONS: Transition-aged youth seek help for mental health problems in different ways. Despite efforts to improve access to mental health services, transition-aged youth continue to face barriers to accessing these services, especially formal sources of support. The factors identified in this study that either hinder or facilitate help-seeking have pragmatic implications for developing help-seeking interventions and delivering mental health services for this population. In addition to other facilitators, family physicians are an important resource in the help-seeking process. Furthermore, digital help-seeking tools have unique characteristics that may make them an important source of support for transition-aged youth.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".