Impact and Mechanisms of Cognitive Behavioural Therapy for Insomnia on Fatigue among Cancer Survivors: A Secondary Analysis of a Randomized Controlled Trial
Bibliographic record
Abstract
STUDY OBJECTIVES: Cancer-related fatigue is one of the most common symptoms in cancer survivors. Cognitive behavioral therapy for insomnia (CBT-I) can improve fatigue, but mechanisms are unclear. This secondary analysis of a randomized controlled trial evaluated whether CBT-I led to a significant improvement in fatigue, accounting for change in comorbid symptoms of insomnia, perceived cognitive impairment (PCI), anxiety, and depression. The parent study evaluated the impacts of CBT-I on PCI and insomnia. METHODS: Cancer survivors with insomnia and PCI were randomized to CBT-I or sleep-self-monitoring waitlist control. Fatigue was measured using the Multidimensional Fatigue Symptom Inventory-Short Form at pre-, mid-, and post-treatment. Significant improvement in fatigue was defined as a reduction of >10.79 points. Insomnia, PCI, anxiety, and depression symptoms were assessed. A linear mixed model evaluated whether CBT-I improved fatigue after adjusting for comorbidities. Mediation analyses examined whether change in comorbidities accounted for the effect of CBT-I on fatigue. RESULTS: The sample consisted of 132 cancer survivors (77% female, Mage = 60.12 years, 41% breast cancer). There was a significant group-by-time interaction on fatigue, p < .001, with the CBT-I group experiencing a 20.6-point reduction in fatigue compared to 3.7 points in the control. Improvements in fatigue were fully accounted for by improvements in the comorbidities with change in insomnia accounting for 45.3% of the effect observed in fatigue. CONCLUSIONS: CBT-I resulted in significant improvement in fatigue, and these effects were largely accounted for by changes in insomnia. CBT-I is a robust intervention with efficacy for improving fatigue among cancer survivors. CLINICAL TRIAL INFORMATION: Online Treatment of Cognitive Impairment and Insomnia in Cancer Survivors, https://clinicaltrials.gov/study/NCT04026048?term=NCT04026048&rank=1, ClinicalTrials.gov ID: NCT04026048.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".