The impact of autism services on mothers' psychological wellbeing
Bibliographic record
Abstract
BACKGROUND: Families with a child diagnosed with autism spectrum disorder (ASD) often utilize a variety of professional services. The provision of these services has many potential benefits for families; however, these services also place demands on parents, particularly mothers, to access, navigate and participate. Little is known about how involvement with these services and service systems influences the psychological wellbeing of mothers of children diagnosed with ASD. We examined the relationship between professional services and psychological wellbeing for mothers of children diagnosed with ASD. METHODS: Mothers (n = 119) of children (mean child age 10.1 years; range 2-24 years) diagnosed with ASD anonymously completed a comprehensive survey. The survey included data related to maternal psychological wellbeing, professional services received and perceptions of these services, and child, mother and household characteristics. RESULTS: Regression analyses revealed that maternal psychological wellbeing was positively associated with the perceived continuity of services, and negatively associated with the number of professionals involved. Child and maternal age, and household income were also statistically significant predictors of maternal psychological wellbeing. CONCLUSIONS: The study findings draw attention to the potentially negative impact of systems-level challenges, especially fragmentation of services, on maternal psychological wellbeing, despite positive front-line services. In particular, our data suggest that psychological wellbeing among mothers of children with ASD may vary more as a function of service system variables than practitioner-level or child-level variables.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 |
| 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 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".