Mental health of transitional aged youth in Nicaragua: Perceptions and experiences of educators
Bibliographic record
Abstract
Mental illnesses contribute to a large proportion of the disease burden in children and adolescents in low and middle-income countries (LMICs). There is limited research completed in LMICs about paediatric mental health, particularly related to youth. School is a place where many adolescents first seek mental health support. This study examined how educators in Nicaragua view youth mental health and how mental health can be supported in LMIC schools. Focus groups were completed with teachers serving youth from a variety of socioeconomic settings within León, Nicaragua. The study was completed from an Interpretivist theoretical paradigm and coding of qualitative data was completed consistent with Constructivist Grounded Theory. Educators described their roles in as detecting mental health problems and liasing with other supports; they noted barriers as cross-sector integration and social challenges. Educators felt that youth would be better served by improving integration of care, addressing structural factors, and providing more teacher supports. A model for addressing youth mental health in LMICs could include a stepped-care approach with schools providing preventative programming as well as developing within school referral strategies for youth with higher needs. There may be a role for the use of community health promoters.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".