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Record W7034401775

Therapeutic Process Factors in Mental Health Treatment for Autistic Youth

2023· other· en· W7034401775 on OpenAlexaff

Bibliographic record

VenueYork University Digital Library (York University) · 2023
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicMollusks and Parasites Studies
Canadian institutionsYork University
Fundersnot available
KeywordsPsychosocialMental healthPsychological interventionIntervention (counseling)AllianceTherapeutic relationshipCognitionObservational study
DOInot available

Abstract

fetched live from OpenAlex

Psychosocial interventions can be beneficial for addressing mental health challenges for some autistic youth, but a sizeable portion of youth who take part in mental health treatment do not demonstrate clinically meaningful improvement. Examining therapeutic process factors may provide insight as to why some youth benefit from treatment, while others do not. The current research aimed to evaluate the role of various therapeutic process factors in mental health treatment for autistic children and adolescents through two studies. \n\nThe first study involved a systematic review and a narrative synthesis of the literature on how therapeutic process factors have been measured and the association with treatment outcome following psychosocial intervention addressing mental health challenges for autistic youth. 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. \n\nThe second study examined indicators of child engagement in relation to treatment outcome for autistic children who participated in cognitive behaviour therapy for emotion regulation. Indicators of child engagement included observational ratings of in-session involvement, and therapist ratings of therapeutic alliance between therapist and child and homework completion. Each indicator of engagement was measured at early, middle, and late stages of therapy. After controlling for pre-treatment scores, in-session involvement significantly predicted some aspects of post-treatment emotion regulation, whereas therapeutic relationship and homework completion did not. \n\nThis dissertation addresses key gaps in research on mental health treatment for autistic youth by providing a detailed summary on what is currently known about therapeutic process factors and process-outcome associations in psychotherapy, and offers original findings that highlight the importance of child in-session involvement for therapeutic success. Research should continue to focus on relatively well-examined factors, such as therapeutic alliance, and explore factors that are less understood, such as client beliefs about treatment and parent involvement. Clinicians working with autistic clients should actively strive to form therapeutic alliance with youth and parents, and support positive treatment engagement for the full duration of therapy to enhance the likelihood of successful outcomes.

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)0.005
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.211
Teacher spread0.170 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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