1030 An Exploration of the Impact of Cognitive Behavioural Therapy of Insomnia (CBT-I) on Perceived Cognitive Impairment in Breast Cancer Survivors
Bibliographic record
Abstract
Abstract Introduction Insomnia and cognitive impairment are prevalent and persistent symptoms in cancer survivors. Cognitive Behavior Therapy is effective for improving insomnia and comorbid symptoms in cancer survivors but there are very few empirically supported treatments that can improve cognitive impairment. This feasibility study explored the impact of CBT-I on perceived cognitive impairment in breast cancer survivors. Methods We enrolled 10 early stage breast cancer survivors with insomnia disorder and perceived cognitive impairment. Participants received 7 individual sessions of CBT-I over the course of 8 weeks and completed the Insomnia Severity Index (ISI), the Functional Assessment of Cancer Therapy - Cognitive Function (FACT-Cog) questionnaires and The Hospital Anxiety and Depression Scale (HADS) at baseline and post-treatment. Paired samples t-tests were used to assess change over time. Results The sample was predominantly diagnosed with stage II breast cancer (60%). Women were an average age of 50.8 (SD 6.84) and 18.2 (SD 3.62) years of education. CBT-I significantly reduced insomnia severity [19.4 to 7.1; t(9)= 6.56, p < .001] and improved perceived cognitive impairment [t(9)= -3.55, p < .01], perceived cognitive ability [t(9)= -2.87, p < .05], quality of life [t(9)= -3.14, p < .05], and overall subjective cognitive function [t(9)= -3.67, p < .01]. Although participants began treatment with low levels of mood disturbance, CBT-I further decreased symptoms of anxiety (baseline: M= 10.10, SD= 4.34; post-treatment M= 8.20, SD= 3.91) and depression (baseline: M= 7.90, SD= 3.45; post-treatment M= 5.30, SD= 2.83), although not statistically significant. Conclusion This study suggests CBT-I may improve perceived cognitive impairment in cancer survivors, in addition to insomnia and mood. Future randomized controlled trials with larger samples and objective measurements of cognition are needed. Support Nyissa Walsh is a trainee in the Cancer Research Training Program of the Beatrice Hunter Cancer Research Institute (BHCRI). Dr. Sheila Garland is supported by a Scotiabank New Investigator Award from BHCRI.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".