Understanding the Role of Formal and Informal Support Resources for Parents of Children with Autism Spectrum Disorder
Bibliographic record
Abstract
This research examines the extent to which parents of children with autism spectrum disorder (ASD) perceive support resources to be available, accessible, and/or effective in supporting their needs. A focus on the impact of the COVID-19 pandemic in the availability and effectiveness of service delivery is included. A total of 35 parents in Ontario, Canada with a child aged 6–17 with ASD completed an online survey responding to questions about involvement in ASD services, use of formal and informal supports, important support needs, which needs were being met, and perceptions of unmet needs, all which were thematically analysed. The analysis demonstrates that parents experience multiple barriers in accessing supports, particularly from formal sources. Further, the barriers were heightened during the pandemic particularly in relation to the multiple role responsibilities that parents had to take on due to a discontinuity of support provision. Most of these parents put their own support needs aside to focus on their child, with the support their child receives directly relating to the ability to attend to their own needs. Parents identified challenges related to uncertain funding, limits of a one-size-fits-all model of support, and lengthy waitlists. Recommendations for family-centred care and the need for service coordinators to work with families to assist in navigating the complex support system are provided.
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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 | 0.011 |
| 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 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".