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Record W4400866786 · doi:10.1177/07067437241261933

Comparing the Efficacy of Electronically Delivered Cognitive Behavioral Therapy (e-CBT) to Weekly Online Mental Health Check-Ins for Generalized Anxiety Disorder—A Randomized Controlled Trial: Comparaison de l'efficacité de la thérapie cognitivo-comportementale délivrée par voie électronique (e-TCC) aux contrôles hebdomadaires en ligne de santé mentale pour le trouble d'anxiété généralisée - un essai randomisé contrôlé

2024· article· en· W4400866786 on OpenAlexaffvenue
Melinaz Barati Chermahini, Jazmin Eadie, Anika Agarwal, Callum Stephenson, Niloufar Malakouti, Niloofar Nikjoo, Jasleen Jagayat, Vineeth Jarabana, Amirhossein Shirazi, Anchan Kumar, Tessa Gizzarelli, Gilmar Gutiérrez, Ferwa Khan, C. B. Patel, Megan Yang, Mohsen Omrani, Nazanin Alavi

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2024
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsOptech (Canada)Queen's University
Fundersnot available
KeywordsGeneralized anxiety disorderAnxietyRandomized controlled trialWorryPsychological interventionMental healthCognitive behavioral therapyIrritabilityCognitive therapyPsychologyPsychiatryClinical psychologyCognitionMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Generalized anxiety disorder (GAD) is a prevalent anxiety disorder characterized by uncontrollable worry, trouble sleeping, muscle tension, and irritability. Cognitive behavioural therapy (CBT) is one of the first-line treatments that has demonstrated high efficacy in reducing symptoms of anxiety. Electronically delivered CBT (e-CBT) has been a promising adaptation of in-person treatment, showing comparable efficacy with increased accessibility and scalability. Finding further scalable interventions that can offer benefits to patients requiring less intensive interventions can allow for better resource allocation. Some studies have indicated that weekly check-ins can also lead to improvements in GAD symptoms. However, there is a lack of research exploring the potential benefits of online check-ins for patients with GAD. OBJECTIVE: This study aims to investigate the effects of weekly online asynchronous check-ins on patients diagnosed with GAD and compare it with a group receiving e-CBT. METHODS: check-in = 51) with GAD were randomized into either an e-CBT or a mental health check-in program for 12 weeks. Participants in the e-CBT program completed pre-designed modules and homework assignments through a secure online delivery platform where they received personalized feedback from a trained care provider. Participants in the mental health check-in condition had weekly asynchronous messaging communication with a care provider where they were asked structured questions with a different weekly theme to encourage conversation. RESULTS: Both treatments demonstrated statistically significant reductions in GAD-7-item questionnaire (GAD-7) scores over time, but when comparing the groups there was no significant difference between the treatments. The number of participants who dropped out and baseline scores on all questionnaires were comparable for both groups. CONCLUSIONS: The findings support the effectiveness of e-CBT and mental health check-ins for the treatment of GAD. PLAIN LANGUAGE SUMMARY TITLE: Comparing the Effectiveness of Electronically Delivered Therapy (e-CBT) to Weekly Online Mental Health Check-ins for Generalized Anxiety Disorder-A Randomized Controlled Trial.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.025
GPT teacher head0.374
Teacher spread0.349 · 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 designRandomized 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

Citations8
Published2024
Admission routes2
Has abstractyes

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