MétaCan
Menu
Back to cohort
Record W2112574927 · doi:10.1080/15402002.2012.700662

Determinants of Success for Computerized Cognitive Behavior Therapy: Examination of an Insomnia Program

2013· article· en· W2112574927 on OpenAlex
Norah Vincent, Kate Walsh, Samantha Lewycky

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBehavioral Sleep Medicine · 2013
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversity of ManitobaManitoba Health
FundersUniversity of Manitoba
KeywordsInsomniaComorbidityCognitive behavioral therapy for insomniaRandomized controlled trialClinical psychologyPsychologyCognitive behavioral therapyChronic insomniaCognitionPsychiatryPhysical therapyMedicineSleep disorderInternal medicine

Abstract

fetched live from OpenAlex

This study evaluated plausible moderators of outcome in a 6-week computerized treatment for insomnia. Using secondary data from two randomized controlled trials, participants were 228 adults with chronic insomnia. Participants received computerized treatment from their homes. Outcomes were assessed using a sleep diary, as well as several standardized self-report scales. Using linear mixed models with SPSS, treatment was largely robust to comorbid conditions, education, age, and gender. Results showed that psychiatric comorbidity and education moderated the impact of treatment on fatigue and that sleep symptom comorbidity moderated the impact of treatment on maladaptive attitudes about sleep. Implications of these findings are that more widespread use of computerized treatment for insomnia may be warranted.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.051
GPT teacher head0.394
Teacher spread0.344 · 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