Parents perceptions of school nurses roles: The impact of communication on students with autism spectrum disorder
Bibliographic record
Abstract
This qualitative study used the nursing grounding theory to describe parents' experiences working with school nurses to elevate their child’s healthcare. Seventeen interviews were conducted with parents/primary caregivers (P/PCG) who had children with autism spectrum disorder (ASD; ages six to ten). Through centering parents’ voices, the investigators were able to identify gaps in P/CG understanding of their school nurses’ roles through thematic analyses. We found that P/CG lacked the understanding of school nurses' roles and how school nurses could aid their child’s healthcare. The oversight of school nurses contributed to miscommunication, which constrained the relationship between the parent and the school nurse. These findings provide insight into the importance of enhancing communication between the parents of children with ASD and school nurses and was the catalyst to why this article was written. When healthcare professionals provide clarity and expertise to parents as to their respective roles, incorporate perspective-taking, and tailor their approaches based on their concerns, it may enhance parents’ experiences with their school nurses. In addition, school nurses should consider various routes of engaging parents so they have a deeper understanding of their responsibilities in enhancing the healthcare of children with ASD.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| 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".