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Record W2385404460 · doi:10.1016/j.janxdis.2016.05.006

Transdiagnostic Internet-delivered cognitive behaviour therapy in Canada: An open trial comparing results of a specialized online clinic and nonspecialized community clinics

2016· article· en· W2385404460 on OpenAlexafffundabout
Heather D. Hadjistavropoulos, Marcie Nugent, Nicole M. Alberts, Lauren Staples, Blake F. Dear, Nickolai Titov

Bibliographic record

VenueJournal of Anxiety Disorders · 2016
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsUniversity of Regina
FundersCanadian Institutes of Health ResearchSaskatchewan Health Research Foundation
KeywordsAnxietyPsychologyCognitionThe InternetDepression (economics)Clinical psychologyPsychiatryWorld Wide Web

Abstract

fetched live from OpenAlex

Effects of Internet-delivered cognitive behaviour therapy (ICBT) for anxiety and depression are not well understood when delivered in non-specialized as compared to specialized clinic settings. This open trial (n=458 patients) examined the benefits of transdiagnostic-ICBT when delivered in Canada by therapists (registered providers or graduate students) working in either a specialized online clinic or one of eight nonspecialized community clinics. Symptoms of depression and anxiety were assessed at pre-treatment, post-treatment and at 3-month follow-up. Completion rates and satisfaction were high. Significant and large reductions (effect sizes 1.17-1.31) were found on symptom measures. Completion rates, satisfaction levels and outcomes did not differ whether ICBT was delivered by therapists working in a specialized online clinic or nonspecialized community clinics. Differences were also not found between registered providers and graduate students, or therapists trained in psychology or another discipline. The findings support the public health potential of ICBT.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score0.900

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.106
GPT teacher head0.422
Teacher spread0.316 · 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 designNon-randomized trial
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

Citations108
Published2016
Admission routes3
Has abstractyes

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