Investigating the experiences of families of young children diagnosed with autism spectrum disorder (ASD) with the use of social support services
Bibliographic record
Abstract
Previous studies have indicated that families of young children with Autism Spectrum Disorder (ASD) experience challenges caring for their children and that social support services have been found to help families cope or deal with some of these challenges (Hall & Graff, 2010; Ludlow, Skelly & Rohleder, 2012; Lytel, Lopez-Garcia & Stacey 2008). This study used a qualitative research methodology to investigate the experiences of families of young children diagnosed with ASD and accessing and utilizing social support services within an urban center in Newfoundland and Labrador (NL). Themes were derived from the data and commonalities across participants were explored. This study employed purposeful sampling as the method of participant selection. Parents or guardians of young children [preschool - grade 3] diagnosed with ASD and using social support services from various services providers were invited to participate. Open-ended interviews were used as the primary source of data and thematic analysis was used as the methodology to analyze the data. The findings suggested three overarching themes which included; suitability, barriers to access, and quality. Results from this study suggested that families with young children with ASD had both positive and negative experiences when accessing and utilizing social support services for their children with ASD.
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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".