Models of case management for working with young children: Implications for mental health nurses
Bibliographic record
Abstract
The care of children with behavioural disorders/mental illnesses is an important and emerging role for mental health nurses. Unfortunately, there is little evidence on which to base their practice. Children, because of their rapid emotional, physical, and cognitive development, and their dependence on their families, need special consideration in their mental health care. The limited evidence available indicates that this special consideration should include a focus, not only on the child, but also on the parents and social and school networks of the child. Evidence from the adult literature indicates the most effective case management models are the ones in which the case manager offers as many services as possible, including talking therapies. This also seems to be true when working with children. Mental health nurses, because of their background and commitment to holistic care, are ideally suited to offer this type of service. However, mental health nurses have not been good at articulating what they do. This can limit the recognition of the contribution they make and their opportunities.
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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 | 0.054 | 0.068 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.012 | 0.011 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".