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Record W2980927173 · doi:10.1002/cpp.2404

Measuring therapeutic alliance in children with autism during cognitive behavior therapy

2019· article· en· W2980927173 on OpenAlexaff
Priscilla Burnham Riosa, Maria R. Khan, Jonathan A. Weiss

Bibliographic record

VenueClinical Psychology & Psychotherapy · 2019
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsYork UniversityBrock University
Fundersnot available
KeywordsAlliancePsychologyAutismIntervention (counseling)Clinical psychologyObservational studyPopulationCognitionCoding (social sciences)Developmental psychologyPsychotherapistPsychiatryMedicine

Abstract

fetched live from OpenAlex

Therapeutic alliance (TA), or the collaborative relationship between a therapist and client, has been shown to be an important component of intervention success. The objective of this study was to examine the psychometric properties of the Therapy Process Observational Coding System-Alliance Scale (TPOCS-A). The sample consisted of 20 children (19 males) ages 8 to 12 years with autism and their parents (15 mothers, 5 fathers), who completed a cognitive-behavioural intervention designed to improve children's emotion regulation skills. Two trained coders rated early, middle, and late parent and child alliance using the TPOCS-A after watching video recorded therapy sessions. Therapist-reported child involvement, alliance, and adherence were also assessed. Psychometric findings revealed that the TPOCS-A is a reliable and valid measure of therapeutic alliance for children with autism. The implications of examining TA in empirically supported treatments for this population are discussed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.168
GPT teacher head0.447
Teacher spread0.280 · 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; both teacher heads agree on what is shown here.

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".

Quick stats

Citations12
Published2019
Admission routes1
Has abstractyes

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