Parent Outcomes Following Participation in Cognitive Behavior Therapy for Autistic Children in a Community Setting: Parent Mental Health, Mindful Parenting, and Parenting Practices
Bibliographic record
Abstract
Parents of autistic children are at a higher risk for mental health problems, including anxiety, depression, and stress. Cognitive behavior therapy (CBT) that targets children's emotion regulation may have an indirect influence on parent outcomes, especially if they play a supporting role in their child's intervention. However, most CBT interventions have been carried out in highly controlled research settings and there are a few studies that examined parental outcomes after participating in autistic child-focused CBT within a community setting. The current study examined parent outcomes (i.e., mental health problems, mindful parenting, and parenting practices) following a community-based CBT program with concurrent parent involvement for autistic children, as well as associations between changes in parent and child outcomes (i.e., autism symptoms and emotion dysregulation). Participants included 77 parent-child dyads across seven community organizations in Ontario, Canada. Parents reported improved mindful parenting and positive parenting practices post-intervention, and no significant changes in their mental health. Multiple mediation analyses revealed that positive changes in parent outcomes (i.e., mindful parenting and parenting practices) were associated with positive changes in child emotion regulation. These positive changes in parenting practices mediated the relationship between mindful parenting and child emotion regulation. Results suggest that participating in community-based CBT is mutually beneficial for autistic children and their parents, particularly in improving parenting behaviors.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".