Parenting styles in caregivers of children with Autism Spectrum Disorder and effects of service dogs
Bibliographic record
Abstract
Objective Parents of children with Autism Spectrum Disorder (ASD) have parenting styles that differ from parents of typically developing children. Integration of a service dog (SD) at home has been demonstrated as having multiple effects within families of children with ASD. Our aims were to investigate if (a) specific parenting styles can be identified during parents’ interactions with their child with ASD using ethological methods, and (b) integration of a SD have an effect on these styles. Methods Behavioural coding was performed on videos recorded at home by 20 parents of 6-12-years old children with ASD before SD integration. Parents were asked to record themselves and their child while making a puzzle. 14 parents performed a second similar recording 3-6 months after SD integration. Data were analysed using Principal Component Analysis, Hierarchical Cluster Analysis and non-parametric tests. Results Three parenting styles emerged: Parents Involved in the Task (PIT), Parents Relaxed in the Interaction (PRI), and Parents Disengaged from the Interaction (PDI). PIT were characterised as more controlling and verbally focused on the activity. PRI were less controlling and talk about things other than the activity. The same applied to PDI, except that they were less warm in their interactions. Analysis performed after SD integration revealed that these groups also diverged in the evolution of certain behaviours. Conclusion This study is the first to demonstrate that behavioural observations can highlight different parenting styles in caregivers of children with ASD, and that the integration of a SD has effects on these styles, with variation according to parents’ style prior to SD integration. Indeed, a decrease in activity control behaviours was observed in parents with an initial profile characterise by higher expression of such behaviours (i.e., PIT), while an increase of those behaviours was observed in parents initially with an initial profile characterise by a weaker expression of such behaviours (i.e., PRI). Interestingly, the last profile characterized by less engagement in the interaction and activity (i.e., PDI) did not seem to show significant changes.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".