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Record W4407305741 · doi:10.1007/s10803-025-06725-y

Caregiver Satisfaction with Anxiety Treatment for Autistic Youth: A Mixed Methods Examination

2025· article· en· W4407305741 on OpenAlexafffund
Lesley A. Norris, Jonathan Rabner, Marika Marklin, Margaret E. Crane, Kathrin Renschler, Emma Jenkins, Joshua Kemp, Eric A. Storch, Jeffrey J. Wood, Connor M. Kerns, Adam B. Lewin, Brent J. Small, Philip C. Kendall

Bibliographic record

VenueJournal of Autism and Developmental Disorders · 2025
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversity of British Columbia
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Mental HealthIntellectual and Developmental Disabilities Research CenterNational Institutes of HealthInternational OCD FoundationMichael Smith Health Research BCBrainsWay
KeywordsAutismAnxietyPsychologyClinical psychologyThematic analysisRandomized controlled trialCoping (psychology)Psychological interventionPsychiatryMedicineQualitative research

Abstract

fetched live from OpenAlex

For Cognitive Behavioral Therapy to best meet the specific needs of autistic youth with co-occurring anxiety and to continue to grow as a sustainable treatment option, it is important to incorporate caregiver perspectives and feedback. Data were drawn from a randomized controlled trial and included 148 caregivers of autistic youth (ages 7-13 years, M = 9.89, SD = 1.79; 23% female; 77.7% White) with co-occurring anxiety disorders randomized to one of two active treatment conditions (Coping Cat, n = 72, or Behavioral Interventions for Anxiety in Children with Autism [BIACA], n = 76). A systematic inductive thematic analysis was used to code open-ended parent responses on the Consumer Satisfaction Questionnaire to identify what caregivers of autistic children with co-occurring anxiety liked most and least about their child's treatment. Satisfaction with treatment was high (M = 64.98, SD = 5.48). Caregivers' most-liked treatment features across treatments included (a) tools and coping skills, (b) therapeutic alliance, (c) caregiver support and involvement, (d) personalized treatment, and (e) treatment efficacy. Least-liked features of treatment and family participation included (a) the commute to the clinic, (b) treatment length, (c) commitment required at home, (d) questionnaires, and (e) scheduling. Treatment responders endorsed therapeutic alliance more frequently. Caregivers in BIACA endorsed caregiver support and involvement at higher rates, in addition to commitment required at home. Caregiver responses indicated a preference for more sessions and highlighted the importance of balancing need for caregiver involvement in treatment while reducing caregiver burden.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.950
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.326
Teacher spread0.298 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations0
Published2025
Admission routes2
Has abstractyes

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