Engaging families in research to determine health literacy needs related to the use of second-generation antipsychotics in children and adolescents.
Bibliographic record
Abstract
OBJECTIVES: We sought to engage parents and caregivers in research to understand their health literacy needs related to the use of second-generation antipsychotic medications (SGAs) in children and youth. METHODS: Two focus groups with a total of 14 participants were conducted in two distinct geographical regions of British Columbia. RESULTS: Participants expressed that they had numerous questions about the medications but had few reliable resources available to them. They currently obtain information from a wide variety of sources including: psychiatrists, pharmacy print-outs, pediatricians, other parents, the Internet, and books. They expressed a preference for information to be initially delivered verbally, on a 'one-to-one' basis by their medical professional (preferably psychiatrist, psychologist, pediatrician), and then supplemented by accessible, written- and video-reference materials that would also be available online from a single reputable source (e.g., BC Children's Hospital). The weight gain and other potential metabolic side effects were of great concern to parents. Educational resources that address healthy nutrition and promotion of physical activity need to address the specific issues that parents looking after children with mental health concerns face. CONCLUSIONS: Families are key partners in the management and treatment of child and adolescent psychiatric disorders. The findings from this study support the value of including the "family" voice in developing educational strategies related to medications such as SGAs.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".