Bibliographic record
Abstract
Parents of children with autism living in rural communities often face barriers to navigating support systems, contributing to increased stress and disconnection. This mixed-methods study examines the impact of a strength-based, positive psychology framework on parental efficacy and confidence. Eight parents of autistic children from rural communities in British Columbia participated in a six-session online learning series designed and facilitated by a graduate student who is also a parent of a teen with autism. Sessions were delivered via Zoom to mitigate the geographic distances of northern rural areas. Participants learned how to identify and foster their child’s development using strength-based parenting strategies. The study addressed the research questions: How can strength-based parenting strategies and an appreciative inquiry framework enhance parental efficacy, empowerment, and growth-oriented practices for families raising a child (REN) with autism? Is online an effective method to deliver parenting sessions for families in rural communities? How does a facilitator’s critical reflection and their intersection of professional and personal experience support compassionate and equitable participant practice? Data was collected using pre-session, post-session and 3-month retention surveys, incorporating both Likert-scale and open-ended questions. Findings support parental confidence and self-efficacy, despite the vulnerability participants shared. The facilitator’s reflective practice and shared lived experience enhanced participant engagement and trust. This study contributes to the growing literature on strength-based, family-centered interventions and offers implications for scalable, community-informed support for families in underserved regions.
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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 | 0.002 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".