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Record W3031604068 · doi:10.1093/sleep/zsaa056.1180

1186 Developing And Testing A Web-based Provider Training For Cognitive Behavioral Therapy Of Insomnia

2020· article· en· W3031604068 on OpenAlexaff
Daniel J. Taylor, Brian E. Bunnell, Casey D. Calhoun, Kristi E. Pruiksma, Jessica R. Dietch, Sophie Wardle‐Pinkston, Melissa E. Milanak, Alyssa A. Rheingold, Richard O. Simmons, Arlin V. Peterson, Charles M. Morin, Kenneth J. Ruggiero, William Brim, Diana C. Dolan, Allison K. Wilkerson

Bibliographic record

VenueSLEEP · 2020
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsUsabilityCognitive trainingMoodCognitionInsomniaRandomized controlled trialMedicineCognitive behavioral therapyClinical psychologyPsychologyPsychiatryComputer science

Abstract

fetched live from OpenAlex

Abstract Introduction Chronic insomnia is a common, debilitating disorder and a risk factor for significant medical morbidity, mental health problems, and workplace difficulties. Cognitive behavioral therapy for insomnia (CBT-I) is the gold standard treatment for insomnia. However, few providers are trained in CBT-I, in part due to a bottleneck in training availability and the time and cost associated with current training platforms. To address this training deficit, our team developed and evaluated CBTIweb.org, a web-based provider training course for CBT-I. Methods Feedback from alpha- and beta-testing of CBTIweb.org was collected and used to optimize course content and functionality. Then, a comparison study was conducted in which licensed providers were randomized to complete either the online CBTIweb.org course (n=21) or an in-person CBT-I training (n=23). During all phases of development, providers completed a Computer System Usability Questionnaire (CSUQ), investigator-developed website usability and content questionnaires, and pre/post-training competency assessments. Results Independent samples t-tests indicated significant improvements in CSUQ, and website usability and content questionnaires responses from alpha- to beta-testing (all ps < .05). Linear mixed-effects modeling revealed significant within-subject increases in knowledge acquisition (F(34.7) = 65.4, p < 0.001; baseline = 69% correct, post-training = 92% correct) when collapsed across in-person and web-based groups. The interaction group by time interaction was non-significant (F(34.7) = 1.7, p = 0.204), indicating similar gains in knowledge (i.e., equivalence) between the in-person and the CBTIweb.org training formats. Conclusion Alpha and beta testers of CBTIweb.org reported high levels of satisfaction while also noting areas for improvement, which were used to update the site. Findings suggest the final CBTIweb.org product successfully trained clinicians compared to an in-person workshop, given knowledge acquisition improvements. CBTIweb.org is an efficient and effective training platform for clinicians to gain knowledge and competence in the most effective treatment for insomnia. Support W81XWH-17-1-0165

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.963
Threshold uncertainty score0.374

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.262
GPT teacher head0.437
Teacher spread0.176 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations1
Published2020
Admission routes1
Has abstractyes

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