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Record W4283777458 · doi:10.1177/13623613221106400

Clinician factors related to the delivery of psychotherapy for autistic youth and youth with attention-deficit hyperactivity disorder

2022· article· en· W4283777458 on OpenAlexafffundabout
Flora Roudbarani, Paula Tablon Modica, Brenna B. Maddox, Yvonne Bohr, Jonathan A. Weiss

Bibliographic record

VenueAutism · 2022
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsYork University
FundersYork University
KeywordsPsychologyMental healthContext (archaeology)AnxietyClinical psychologyPsychiatryAutismAttention deficit hyperactivity disorderCognitionPsychotherapist

Abstract

fetched live from OpenAlex

Autistic children and adolescents are more likely than non-autistic youth to experience mental health problems, such as anxiety or depression, but less likely to receive psychotherapy to address these concerns. Recent research indicates that clinician factors, such as knowledge, attitudes, confidence and beliefs, can impact their decisions to provide care, though this work has primarily focused on adults or within the context of one kind of treatment (cognitive behaviour therapy). The current study examined psychological predictors (e.g. attitudes and confidence) of clinicians’ intention to deliver psychotherapy to autistic youth and those with attention-deficit hyperactivity disorder. Participants included 611 clinicians across publicly funded agencies in Ontario, Canada. Multiple mediation analyses revealed that clinician knowledge on mental health-related topics (e.g. core symptoms, developing treatment plans and identifying progress towards treatment goals) was associated with intention to treat autistic clients or clients with attention-deficit hyperactivity disorder, and normative pressures and attitudes partially mediated this association. Clinicians felt less likely to treat autistic clients than clients with attention-deficit hyperactivity disorder, partly because of differences in attitudes, normative pressures and knowledge. This research suggests that targeted training around autism and mental health care may be a useful initiative for agency staff. Lay abstract Autistic children and youth often experience mental health problems, such as anxiety, depression and behavioural challenges. Although there are therapy programmes that have been found helpful in reducing these issues, such as cognitive behaviour therapy, autistic children often struggle to receive adequate mental health care. Clinicians’ knowledge, attitudes, confidence and beliefs about treating mental health problems in autistic people may be related to their choices in providing psychotherapy. Across Ontario, Canada, 611 mental health clinicians, working in publicly funded agencies, completed an online survey about their experiences and opinions on delivering therapy for autistic clients compared to those with attention-deficit hyperactivity disorder. Clinician knowledge was associated with their intention to treat autistic clients or clients with attention-deficit hyperactivity disorder, partly because of their attitudes and the social pressures or values they felt. Clinicians reported feeling less intent on providing therapy to autistic youth compared to youth with attention-deficit hyperactivity disorder because of differences in their attitudes, social pressures and knowledge. This research can inform the training and educational initiatives for mental health practitioners.

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)0.003
metaresearch head score (Gemma)0.020
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 score0.289
Threshold uncertainty score0.575

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.041
GPT teacher head0.309
Teacher spread0.268 · 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".

Quick stats

Citations9
Published2022
Admission routes3
Has abstractyes

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