Is a Video-Based Cognitive Behavioral Therapy for Insomnia as Efficacious as a Professionally Administered Treatment in Breast Cancer? Results of a Randomized Controlled Trial
Bibliographic record
Abstract
STUDY OBJECTIVE: To assess the short-term efficacy of a video-based cognitive behavioral therapy for insomnia (CBT-I) as compared to a professionally administered CBT-I and to a no-treatment group. DESIGN: Randomized controlled trial. SETTING: Radio-oncology department of a public hospital affiliated with Université Laval (CHU de Québec). PARTICIPANTS: Two hundred forty-two women with breast cancer who had received radiation therapy in the past 18 mo and who had insomnia symptoms or were using hypnotic medications were randomized to: (1) professionally administered CBT-I (PCBT-I; n = 81); (2) video-based CBT-I (VCBT-I; n = 80); and (3) no treatment (CTL; n = 81). INTERVENTIONS: PCBT-I composed of six weekly, individual sessions of approximately 50 min; VCBT-I composed of a 60-min animated video + six booklets. MEASUREMENT AND RESULTS: Insomnia Severity Index (ISI) total score and sleep parameters derived from a daily sleep diary and actigraphy, collected at pretreatment and posttreatment. PCBT-I and VCBT-I were associated with significantly greater sleep improvements, assessed subjectively, as compared to CTL. However, relative to VCBT-I, PCBT-I was associated with significantly greater improvements of insomnia severity, early morning awakenings, depression, fatigue, and dysfunctional beliefs about sleep. The remission rates of insomnia (ISI < 8) were significantly greater in PCBT-I as compared to VCBT-I (71.3% versus 44.3%, P < 0.005). CONCLUSIONS: A self-administered cognitive behavioral therapy for insomnia (CBT-I) using a video format appears to be a valuable treatment option, but face-to-face sessions remain the optimal format for administering CBT-I efficaciously in patients with breast cancer. Self-help interventions for insomnia may constitute an appropriate entry level as part of a stepped care model. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT00674830. CITATION: Savard J, Ivers H, Savard MH, Morin CM. Is a video-based cognitive behavioral therapy for insomnia as efficacious as a professionally administered treatment in breast cancer? Results of 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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".