The impact of <scp>COVID</scp>‐19 on the mental health and wellbeing of caregivers of autistic children and youth: A scoping review
Bibliographic record
Abstract
Caregivers and families of autistic people have experienced stress and increase in demands due to the COVID-19 pandemic that may have long-term negative consequences for both their own and their children's mental health. A scoping review was conducted to identify pandemic related demands experienced by caregivers and families of autistic children and youth. The review also consolidated information on coping strategies and parenting-related guidelines that have emerged to help parents meet these demands. Search strategies were approved by a research librarian and were conducted in peer-reviewed and gray literature databases between May 2020 and February 2021. Additional resources were solicited through author networks and social media. All articles were published between December 2019 and February 2021. Article summaries were charted, and a thematic analysis was conducted with confirmation of findings with our knowledge users. Twenty-three published articles and 14 pieces of gray literature were included in the review. The majority of articles characterized and highlighted the increase in demands on caregivers of autistic children and youth during the pandemic globally. Both quantitative and qualitative studies suggest that parents have experienced an increase in stress and mental health-related symptoms during lockdown measures. Findings suggest that families are employing coping strategies, but there no evidence-based supports were identified. The review highlighted the potential long-term impact of prolonged exposure to increasing demands on the mental health and wellbeing of caregivers and families of autistic people, and pointed to a need for the rapid development and evaluation of flexible and timely support programs. LAY SUMMARY: Caregivers and families of autistic children and youth have faced increased demands due to pandemic-related lockdown measures. We reviewed the literature to outline sources of stress, links to their influence on caregiver mental health, and if support programs have emerged to help them. Our findings suggest a number of demands have increased caregivers' risk to mental health challenges, and their potential impact on family wellbeing. Ongoing development of evidence-based supports of all families of autistic children and youth are needed.
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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 | 0.008 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".