Barriers and Facilitators Associated with the Management of Aggressive and Disruptive Behaviour in Children: A Qualitative Study with Pediatricians.
Bibliographic record
Abstract
BACKGROUND: Aggressive and disruptive behaviours are frequently observed in children. Short-term use of antipsychotics with monitoring for adverse effects is recommended when first-line interventions fail (e.g. psychosocial therapies and psychostimulants for ADHD). This study aimed to understand the barriers and facilitators to behavioural change for the management of aggressive and disruptive behaviours by pediatricians. METHODS: This was a qualitative study with twenty community-based pediatricians. An interview guide was developed to elicit beliefs associated with practice behaviours. We used thematic content analysis with the Theoretical Domains Framework to inform knowledge translation interventions, by helping to determine what behavioural barriers and facilitators to practice exist. Key domains which influenced behaviour were identified by evaluating the frequency of beliefs across interviews, conflicting beliefs, and the strength of beliefs impacting behaviour. RESULTS: Pediatricians described evaluating the impact of aggressive and disruptive behaviours, attempting to determine their cause, and using an approach that prioritized psychosocial therapies and psychostimulants. Pediatricians reported that antipsychotics were effective but that they experienced anxiety about harms, and there was a need to accept the adverse effects as a trade-off for improved function. Discontinuing antipsychotics was problematic. Despite awareness of antipsychotic-induced movement disorders and metabolic effects, there were limitations in physician skills, knowledge and resources and social influences that were a barrier to routine implementation of recommended monitoring procedures. CONCLUSIONS: This study identifies barriers and facilitators to evidence-based practice that can be used for knowledge translation interventions to ensure a high standard of care for children prescribed antipsychotics.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".