A randomized controlled trial of cognitive behavioral therapy and bright light therapy for insomnia and fatigue during breast cancer treatment: SleepCaRe trial.
Bibliographic record
Abstract
12009 Background: Women on chemotherapy for breast cancer (BC) report high levels of insomnia and fatigue. This trial aimed to test the main effects of Cognitive Behavioral Therapy for Insomnia (CBT-I) and Bright Light Therapy (BLT) on insomnia and fatigue symptoms. Methods: This multi-center, randomized, controlled, 2 x 2 factorial, superiority, trial enrolled 219 women receiving cytotoxic chemotherapy for any stage BC. Interventions were: (1) neither CBT-I nor BLT (sleep hygiene education; SHE), (2) BLT, (3) CBT-I, and (4) BLT+CBT-I. The 6-week interventions included one telehealth, 1:1 session followed by emails and a mid-treatment call. Assessments occurred at baseline, 3 and 6 weeks. Dual primary outcomes were the insomnia severity index (ISI) and PROMIS Fatigue. Intention-to-treat analyses were latent growth models. Effect sizes are standardized mean differences (SMDs). Results: Mean age was 50.7y and 24% had metastatic cancer. At baseline, average ISI was 13.24 (SD = 5.48; sub-threshold insomnia), and fatigue was 59.57 (SD = 7.91; moderate fatigue). 88% (n = 198) completed the telehealth session. 75% (n = 165) reported post-treatment outcomes. ISI and fatigue decreased in all conditions (see Table). CBT-I improved ISI (mean difference = -2.03; p = .001; SMD = -0.37), but BLT did not (mean difference = -1.09; p = .082; SMD = -0.20). Neither intervention affected fatigue (SMDs -0.06 to -0.07; p > 0.60). There was no BLTxCBT-I interaction for ISI nor fatigue ( p > 0.50). Conclusions: In patients receiving chemotherapy for BC, brief CBT-I can improve insomnia but not fatigue symptoms. BLT did not improve insomnia or fatigue. We found no evidence of an interaction between BLT and CBT-I. During chemotherapy, fatigue may not be responsive to brief sleep and circadian-oriented treatments. Clinical trial information: ACTRN12620001133921 . Between group (main effects) and within group (change). ISI [95% CI] P, SMD Fatigue [95% CI] P, SMD Main Effects BLT -1.09 [-2.31, 0.14] p = .082, SMD = -0.20 -0.49 [-2.87, 1.88] p = .68, SMD = -0.06 CBT-I -2.03 [-3.25, -0.81] p = .001, SMD = -0.37 -0.54 [-2.92, 1.83] p = .65, SMD = -0.07 Change: 0–6 weeks SHE -3.41 [-4.65, -2.17] p < .001, SMD = -0.62 -3.75 [-6.16, -1.34] p = .002, SMD = -0.47 BLT -4.89 [-6.12, -3.66] p < .001, SMD = -0.89 -3.75 [-6.13, -1.37] p = .002, SMD = -0.47 CBT-I -5.83 [-7.12, -4.54] p < .001, SMD = -1.06 -3.80 [-6.30, -1.31] p = .003, SMD = -0.48 CBT-I+BLT -6.53 [-7.88, -5.18] p < .001, SMD = -1.19 -4.79 [-7.44, -2.14] p < .001, SMD = -0.61
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".