Parent engagement in autism-related care: a qualitative grounded theory study
Bibliographic record
Abstract
Parents of children with autism assume substantial responsibility for navigating intervention to address autism-related concerns, including involvement in therapy. Little is known, from the perspective of these parents, regarding how to best engage and support them in this navigating process as it evolves over the child’s development. In this article, we present findings from a large qualitative study that investigated how parents of children with autism navigate intervention, to construct an in-depth theoretical account of how this group comes to be engaged in individual-level care. Using grounded theory methods and a symbolic interactionist framework, we analyzed select documents and 45 intensive interviews conducted with 32 mothers and 9 expert professionals from urban and rural regions of Ontario, Canada. Parent-defined concerns are the central impetus for the core process of navigating intervention, labeled using parents’ language making your own way. We describe how this process is analogous to engaging in care. Four meaning-making processes – defining concerns, informing the self, seeing what is involved, and adapting emotionally – all interacting in an ongoing fashion, together account for parents’ evolving readiness and motivation for taking action to navigate intervention. We illustrate how parents’ readiness and motivation for navigating intervention (and thus for engagement) evolves over a generalized trajectory, according to three highly overlapping processes experienced by most parents: coming to understand their child has autism, going into high gear, and easing off. These findings indicate multiple empirical conditions and factors affecting engagement that service planners and professionals will likely want to consider when seeking parent involvement as a means to improve outcomes in autism. Additionally, theoretical aspects are relevant to the developing understanding of how healthcare consumers in general become engaged in individual care, with implications for patient-centered care.
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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 | 0.032 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".