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Record W4390078898 · doi:10.1017/s1355617723002916

87 Suitability of the I-InTERACT-North Parenting Program for families with autistic children

2023· article· en· W4390078898 on OpenAlexaffabout
Rachael E. Lyon, Rivka Green, Angela Deotto, Giulia F. Fabiano, Elizabeth Kelley, Evdokia Anagnostou, Rob Nicolson, Shari L. Wade, Tricia S. Williams

Bibliographic record

VenueJournal of the International Neuropsychological Society · 2023
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsWestern UniversityHolland Bloorview Kids Rehabilitation HospitalQueen's UniversityHospital for Sick ChildrenYork University
Fundersnot available
KeywordsPsychologyAutismIntervention (counseling)Clinical psychologyAutism spectrum disorderThematic analysisPsychiatryDevelopmental psychologyMedicineQualitative research

Abstract

fetched live from OpenAlex

Objective: I-InTERACT-North is a stepped-care telepsychological parenting intervention designed to promote positive parenting skills and improve child behaviour. Initially developed for children with traumatic brain injury, our pilot study has shown efficacy in increasing positive parenting skills and reducing problem behaviours for children with early brain injury (e.g., stroke, encephalopathy). Recently, the program has expanded to include children with neurodevelopmental disorders, including Autism Spectrum Disorder. Although positive parenting programs (e.g., Parent-Child Interaction Therapy) can be effective for autistic children, it is unknown whether the goals most important to these families can be addressed with IInTERACT-North program. An examination of suitability and preliminary efficacy was conducted. Participants and Methods: Parent participants of autistic children between 3 and 9 years (n= 20) were recruited from the neonatal, neurology, psychiatry, or cardiology clinics at The Hospital for Sick Children and the Province of Ontario Neurodevelopmental Disorders (POND) Network. Top problems, as reported by parents at baseline, were analyzed qualitatively through a cross-case analysis procedure in order to identify common themes and facilitate generalizations surrounding concerning behaviours. Parent-reported intensity of their children’s top problem behaviours on a scale from 1 (“not a problem”) to 8 (“huge problem”) were quantified. To explore preliminary program efficacy, t-tests were used to compare pre- and post-intervention problems and intensity on the Eyberg Child Behavior Inventory (ECBI) (n=16). Results: A total of 56 top problem data units were examined, with convergent thematic coding on 53 of 56 (94.6% inter-coder reliability). Four prevalent, high-agreement themes were retained: emotion dysregulation (19; 33.9%), non-compliance (12; 21.4%), sibling conflict (7; 12.5%), and inattention and hyperactivity (7; 12.5%). Average problem intensity for these themes ranged from 5.85 to 6.53 (where 8 is greatest impairment) with emotion dysregulation having the highest intensity (6.53) compared to the others. Scores on the ECBI were lower post-intervention (Intensity scale: M= 59.06, SD= 8.1; Problem scale: M= 60.69, SD= 11.5) compared to pre-intervention (Intensity scale: M= 61.19, SD= 10.4; Problem scale: M= 64.31, SD= 11.7), but small sample size precluded detecting statistical significance (p’s = .16 and .07, respectively). Conclusions: Thematic analysis of top problems identified by parents of autistic children suggested that concerns were transdiagnostic in nature, and represent common treatment targets of the I-InTERACTNorth program. Though challenging behaviours related to restricted interests or repetitive behaviours may exist in our sample, parental behavioural goals appeared to align with the types of concerns traditionally raised by participants of the program, supporting a transdiagnostic approach. Preliminary data point to positive treatment outcomes in these families.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.047
GPT teacher head0.373
Teacher spread0.326 · 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 designObservational
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".

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Citations0
Published2023
Admission routes2
Has abstractyes

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