Digital Health Interventions Targeting Psychological Health in Parents of Children With Autism Spectrum Disorder: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: Autism spectrum disorder (ASD) is a complex, incurable condition requiring lifelong care, often placing significant psychological strain on parents and emerging as a public health concern. While various interventions exist to enhance the psychological health of parents, the role of digital health interventions (DHIs) in this context remains underexplored. OBJECTIVE: This scoping review aims to systematically assess the availability of DHIs targeting the psychological health of parents of children with ASD and evaluate the effectiveness of these interventions in improving parental psychological health. METHODS: The review will include English-language studies published from inception to June 25, 2024, focusing on DHIs aimed at improving the psychological health of parents of children with ASD. Eligible studies will involve parents of children with ASD less than the age of 18 years, across various settings, and assess psychological health outcomes. A comprehensive search will be conducted across six databases: (1) CINAHL, (2) Ovid EMBASE, (3) Ovid Global Health, (4) Ovid MEDLINE, (5) Ovid PsycINFO, and (6) Web of Science. Studies will be screened and selected based on predefined eligibility criteria. Data extraction will include publication details, study design, participants' characteristics, intervention specifics, comparisons, psychological outcomes, and key findings. Results will be synthesized using descriptive statistics, charts, and narrative analysis. RESULTS: The initial keyword-based search, completed in June 2024, identified 5825 records, which were subsequently screened and analyzed. Screening and evidence synthesis were finalized in winter 2024, and the completed scoping review was submitted in December 2024. CONCLUSIONS: This study will provide a comprehensive overview of commonly used DHIs for supporting the psychological health of parents of children with ASD and their effectiveness. The findings will help identify research gaps, inform future studies and funding priorities, and contribute to the development of practice guidelines to enhance parental psychological health. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/68677.
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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 | 0.055 | 0.054 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.013 | 0.016 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.077 | 0.012 |
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".