Prospective Rates, Longitudinal Associations, and Factors Associated With Comorbid Insomnia Symptoms and Perceived Cognitive Impairment
Bibliographic record
Abstract
BACKGROUND: Insomnia and cognitive impairment are both common conditions experienced by people diagnosed with cancer. Individually, these conditions have negative impacts on functioning, but the combined burden has yet to be evaluated. The purpose of this research was to estimate rates of comorbid insomnia and perceived cognitive impairments, examine the longitudinal associations between these two conditions, and identify demographic and clinical factors associated with reporting both insomnia and perceived cognitive impairment. METHODS: In this secondary analysis, a heterogeneous sample of 962 patients completed the Insomnia Severity Index (ISI) and the Cognitive Failures Questionnaire (CFQ) at the time of their cancer surgery (baseline; T1) and then again at 2 (T2), 6 (T3), 10 (T4), 14 (T5), and 18 (T6) months. Correlations and partial correlations, controlling for age and education level, were computed at each time point to assess the relationship between ISI and CFQ scores. Cross-lagged correlations assessed associations between ISI and CFQ scores over time. Proportions of patients with comorbid insomnia and cognitive impairments were calculated and logistic regressions investigated changes over time in these proportions. ANOVAs, logistic regressions, ordinal regressions, and multinomial regressions were used to identify risk factors of having comorbid insomnia and cognitive difficulties. RESULTS: Significant and bidirectional correlations between ISI and CFQ scores were observed at each time point and over time. The proportion of patients having both clinical levels of insomnia and perceived cognitive difficulties ranged from 18.73 to 25.84% across time points and this proportion was significantly greater at T1 and T2 than T4, T5, and T6. Participants who reported comorbid insomnia and cognitive impairment were more likely to be younger, female, not currently working, currently receiving chemotherapy, with clinical levels depression and anxiety, and using antidepressants or anxiolytics. CONCLUSION: Comorbid insomnia and perceived cognitive impairment affects around one in five patients and is more frequent at the beginning of the cancer care trajectory. The relationship between insomnia and cognitive impairment appears to be bidirectional. Insomnia may represent an important patient level vulnerability that when identified and treated can improve perception of cognitive function.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".