Youth perceptions of positive mental health
Bibliographic record
Abstract
Introduction Positive mental health underpins individual well-being and occupational participation. Internationally, youth mental health services are expanding to include interventions that promote positive mental health and prevent mental illness, to reduce the growing burden of disease caused by mental illness across the lifespan. Policy initiatives have increased the funding of early intervention initiatives, and evidence is required to inform changes in practice. Method This study aimed to explore youths’ perceptions of positive mental health. An interpretive descriptive qualitative study design was utilized, which involved purposive sampling to recruit three adolescent community mental health service users. Data were collected using the digital storytelling method within a series of three individual interviews. The Canadian Model of Occupational Performance and Engagement was used as a lens to guide thematic analysis. Findings Five main themes emerged, including: Components of spirituality; Occupational factors; Aspirations; Social influences; and Challenges and barriers. Positive mental health was developed through experiences with adversity, primarily mental illness, and being able to increase adequate coping strategies and resilience. Spirituality was expressed through experiences with identity formation and positive mental health was linked with a strong sense of self, being able to accept oneself and embracing one’s identity. Equally important were aspirations and hope, engagement in leisure occupations, role models and positive relationships with family and friends. Conclusion Using the Canadian Model of Occupational Performance and Engagement, personal, occupational and environment factors were demonstrated as being important in how youth perceive positive mental health, with spirituality being particularly influential. Further exploration of positive mental health for adolescents is required to inform policy and practice for community youth mental health services, and more broadly for preventative public health campaigns. Research, such as through the use of digital storytelling method, should actively engage young people in developing definitions, to ensure that they are meaningful to youth and that services understand their unique developmental needs.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".