0861 Does Cognitive Behavioral Therapy for Insomnia Reduce Productivity Loss in Cancer Survivors with Cognitive Impairment?
Bibliographic record
Abstract
Abstract Introduction Insomnia and perceived cognitive impairments (PCI) affect 1 in 4 cancer survivors and negatively affects work productivity. This study explores the impact of cognitive behavioral therapy for insomnia (CBT-I) on work presenteeism and absenteeism in cancer survivors with comorbid insomnia and PCI. Methods A sub-sample of 42 Atlantic Canadian survivors with insomnia disorder and PCI who were currently working for pay were analyzed as part of a larger randomized clinical trial. Participants completed 7 virtual sessions of CBT-I. The Work Productivity and Activity Impairment Index Specific Health Problem Questionnaire (WPAI: SHP) was administered pre-and post-treatment. Absenteeism was defined as the percentage of time absent from work, while presenteeism was defined as the extent to which health problems affected productivity at work in the past 7 days. Costs were calculated by the human capital method. Significant changes in productivity loss were defined at ≥15% or 20% change in absenteeism and presenteeism, respectively. Descriptive statistics and paired samples t-tests were used to measure changes in productivity following treatment. Average net benefit was calculated by subtracting the average treatment cost from average treatment benefits after 1 year to reflect cost savings after CBT-I. The cost of treatment was estimated in terms of average cost per session and lost time at work. Results Participants (76% Female) were, on average, 50.4 years old with 16.6 years of education. Breast cancer was the most reported cancer type (43%). Overall rates of presenteeism were significantly lower at post-treatment (p=<.001, d=0.55), with 52.4% reporting significant reductions. Absenteeism rates from pre- to post-treatment were not significant (p=.11, d=0.20). Reduced productivity loss post-treatment was associated with an average savings of CAD$10,979/person/year. Average net benefits for the first-year post-treatment equaled CAD$9348/person. Conclusion CBT-I can improve work productivity in cancer survivors. Investments to increase and provide access to evidence-based treatment may lead to significant savings for individuals and businesses. Support (if any) Dr. Sheila Garland is supported by a Canadian Cancer Society Emerging Scholar Award (Survivorship) (grant #707146). This project was funded through a grant from the Canadian Institutes of Health Research (CIHR) (grant number: PJT 162428) and the Beatrice Hunter Cancer Research Institute.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".