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Record W4293027757 · doi:10.1007/s10567-022-00409-0

A Systematic Review of Therapeutic Process Factors in Mental Health Treatment for Autistic Youth

2022· review· en· W4293027757 on OpenAlexafffund
Carly Albaum, Nisha Vashi, Yvonne Bohr, Jonathan A. Weiss

Bibliographic record

VenueClinical Child and Family Psychology Review · 2022
Typereview
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsYork University
FundersCanadian Institutes of Health ResearchYork University
KeywordsPsychosocialMental healthPsychologyPsychological interventionClinical psychologyPopulationProcess (computing)PsychotherapistPsychiatryMedicine

Abstract

fetched live from OpenAlex

Understanding the role of therapeutic process factors in treatment change may prove useful for discerning why some autistic youth benefit from psychosocial interventions that target emotional and psychological aspects of mental health, while others do not. The aim of the current study was to synthesize what is currently known about therapeutic process factors in mental health treatment of emotional and psychological challenges for autistic youth, regarding how process factors have been measured in past research, and the relation between process factors and treatment outcome. A systematic review of the literature was conducted to narratively synthesize all articles published up until June 2021. Methodological quality of included studies was appraised. Twenty-five studies met inclusion criteria. Process factors assessed across studies included relational factors; treatment expectations, readiness, and satisfaction; and treatment engagement from youth and their parents. Process-outcome associations were reported for a limited number of constructs. There is a limited, albeit growing, body of high-quality research evaluating the role of process factors in the treatment of mental health issues for autistic youth. Future research should continue to examine process factors in relation to treatment outcome, and validate measures to accurately capture process-related constructs in mental health treatment for this population. Greater understanding of therapy processes can lead to developing evidence-informed strategies that clinicians can implement to promote positive expectations, relationships, and engagement.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.298
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0090.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.352
GPT teacher head0.542
Teacher spread0.190 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations10
Published2022
Admission routes2
Has abstractyes

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