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Record W3184165114 · doi:10.1177/13623613211034057

A balancing act: An interpretive description of healthcare providers’ and families’ perspective on the surgical experiences of children with autism spectrum disorder

2021· article· en· W3184165114 on OpenAlexafffund
Stephanie Snow, Isabel M. Smith, Margot Latimer, Emma Stirling-Cameron, Jennifer Fox, Jill Chorney

Bibliographic record

VenueAutism · 2021
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsDalhousie UniversityIzaak Walton Killam Health Centre
FundersCanadian Institutes of Health ResearchIWK Health Centre
KeywordsAutismPsychologyAutism spectrum disorderEmpathyPsychological interventionInterpersonal communicationAnxietyQualitative researchDevelopmental psychologyClinical psychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Children with an autism spectrum disorder (autism) are vulnerable to negative experiences within the surgical setting. This qualitative study used Interpretive Description. Individual interviews were conducted with 8 parents of children with autism who had recently undergone surgery, and 15 healthcare providers (HCPs) with experience caring for children with autism. Participants were asked open-ended questions on the approaches used to support children with autism around the time of surgery and their effectiveness, how the surgical experience could be improved, and the barriers and facilitators to potential improvements. Results yielded three main themes within an overarching metaphor of a balancing act. The first theme, finding your footing through an uncertain journey, described individual factors (e.g. anticipatory anxiety) that set the foundation for surgery-related experiences. The second theme, relationships can help to keep everyone steady, highlighted how interpersonal dynamics (e.g. collaboration and empathy) influence the experience. Finally, the systems shape the experience theme captured the impact of systemic factors (e.g. the hospital environment) on the balancing act. These findings enriched our understanding of how individual, interpersonal, and systemic factors influence the surgical experiences of children with autism, families, and HCPs. Insights gained from this study can be used to inform future interventions. Lay abstract Children with an autism spectrum disorder (autism) often have negative experiences within the surgical setting. We conducted individual interviews with 8 parents of children with autism who had recently undergone surgery, and 15 healthcare providers (HCPs) with experience caring for children with autism. We asked open-ended questions on the approaches used to support children with autism around the time of surgery, how effective they were, suggestions for improvement, and the barriers and facilitators to improvement. Three main themes emerged within an overarching metaphor of a balancing act. The first theme, finding your footing through an uncertain journey, described individual factors (e.g. anticipatory anxiety) that set the foundation for experiences. The second theme, relationships can help to keep everyone steady, highlighted how personal interactions (e.g. collaboration and empathy) influence the experience. Finally, the systems shape the experience theme captured how systemic factors (e.g. the hospital environment) affected the balancing act. These findings enriched our understanding of the surgical experiences of children with autism, families, and HCPs by demonstrating the importance of individual characteristics, relationships, and systemic factors. Future interventions should consider this complexity and intervene not just with children, but also their parents, healthcare providers, and in policy to improve experiences.

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 imitation

Not 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.

metaresearch head score (Codex)0.018
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.027
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0140.027
Scholarly communication0.0080.012
Open science0.0030.009
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.023
GPT teacher head0.324
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2021
Admission routes2
Has abstractyes

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