Associations between dimensions of mental health literacy and adolescent help‐seeking intentions
Bibliographic record
Abstract
BACKGROUND: The majority of long-term mental health problems begin during adolescence. Low mental health literacy (MHL) may impede help-seeking for these problems. Although MHL is a multidimensional construct and adolescent help-seeking can be through formal and informal means, little is known about how dimensions of MHL influence these help-seeking intentions. This study examines associations between dimensions of MHL and formal and informal help-seeking intentions among adolescents. It also investigates whether informal help-seeking mediates the association between dimensions of MHL and formal help-seeking, and whether these associations are moderated by gender. METHODS: A cross-sectional survey including measures of MHL, and help-seeking intentions was distributed to participants in 10 schools (12-17 years) across Scotland (n = 734). Data were analysed using Confirmatory Factor Analyses (CFA) and Structural Equation Modelling (SEM). RESULTS: Confirmatory Factor Analyses identified two distinct dimensions of MHL: ability to identify a mental health problem, and knowledge of treatment efficacy. Only knowledge of treatment efficacy was associated with increased intention to seek formal and informal help. Ability to identify a mental health problem was negatively associated with both forms of help-seeking intentions. Informal help-seeking mediated the association between both forms of MHL and formal help-seeking. Gender did not moderate the associations between MHL and help-seeking. CONCLUSIONS: Care should be taken when providing MHL interventions to ensure that adaptive forms of MHL are promoted. Future research should investigate possible mechanisms by which discrete forms of MHL influence adolescent help-seeking as well as investigating other potential moderators of MHL and help-seeking, such as stigma.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".