An Interpretive Description of Nurses’ Perspectives on Rural Child and Youth Mental Health and Substance Use Care
Bibliographic record
Abstract
Mental health and substance use (MHSU) disorders are the primary contributors to disability among children and youth, often with an early age of onset. Rural communities face added challenges in accessing care. Nurses may be a key professional support for rural children and youth needing MHSU care, but there is a gap in the literature about nurses' roles in this practice area. This interpretive descriptive study explored the insights of rural nurses regarding MHSU care for children and youth in community practice settings in British Columbia, Canada. Semi-structured interviews were conducted with eleven rural nurses who were either MHSU specialists or generalists with MHSU as part of their practice. Reflexive thematic analysis and interpretive description were used to analyse the data. Three key themes were constructed: (1) children and youth's mental health was tethered to the rural and remote context; (2) MHSU care was more than just MHSU treatment; and (3) the essential components of rural child and youth MHSU nursing practice. Early intervention and rural-centric approaches may support rural children and youth. By supporting rural nurses, MHSU care for children and youth can be enhanced.
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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 | 0.019 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.016 | 0.025 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| 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".