Exploring the Decisional needs of Parents with Children with ADHD and Disruptive and Aggressive Behaviour.
Bibliographic record
Abstract
OBJECTIVE: The aim of this qualitative study was to explore the decisional needs of parents of children with ADHD and disruptive and aggressive behaviour to inform the creation of a patient decision aid. METHOD: A one-day meeting of researchers, community advocacy partners, and 11 parents of children (age range eight to 21) with aggressive and disruptive behaviour associated with a diagnosis of Attention Deficit Hyperactivity Disorder (ADHD), Oppositional Defiant Disorder or Conduct Disorder was held. This meeting consisted of a two-hour educational session on the assessment and management of aggressive and disruptive behaviour in children and patient decision aids, followed by two concurrent focus groups to determine the decisional needs of parents. NVivo11 software was used for the organization of the data. RESULTS: The results outline the broad themes and subthemes that emerged from the thematic analysis. These themes and subthemes include (a) decisional needs - treatment options and where to begin, availability, effectiveness of different treatment options, side effects, time, depth of information provided; (b) decision aid formats, and (c) accessibility - language, involvement of children, and dissemination. CONCLUSION: The themes generated from the focus groups suggest that a patient decision aid for parents with children with ADHD and disruptive and aggressive behaviour should follow the general recommendations for best practices for the creation of patient decision aids. Specific information on the regional availability of non-medical treatments will be especially helpful for parents to navigate services and service providers. Consideration should be given as to how the concept of values clarification is introduced to families.
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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 | 0.011 | 0.026 |
| 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 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".