Helping Parents with Mental Illnesses and their Children: A Call for Family-Focused Mental Health Care
Bibliographic record
Abstract
<h4></h4> <p>Recent statistics indicate that nearly one quarter of American adults have been diagnosed with a mental illness (Egan &amp; Asher, 2005). This means many of these adults are parents affected by a mental illness while trying to raise their children. Nurses in many health care settings, particularly pediatrics, public health, schools, emergency rooms, and mental health, often see the damaging influence of parental mental illness on children. As the largest number of health care providers, nurses can make a significant contribution to improving the plight of these families. This is because nurses understand and have a holistic view of family function. Due to the nature of their education and expertise, nurses are in a unique position to not only offer clinical interventions but also act as bridges in connecting these families to social service agencies and family and community support networks.</p>
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".