A qualitative examination of the factors related to the development and maintenance of insomnia in cancer survivors
Bibliographic record
Abstract
OBJECTIVE: Insomnia is underrecognized and inadequately managed, with close to 60% of cancer survivors experiencing insomnia at some point in the treatment trajectory. The objective of this study was to further understand predisposing, precipitating, and perpetuating factors in the development and maintenance of insomnia in cancer survivors. METHOD: A heterogeneous sample of 63 patients who had completed active treatment was recruited. Participants were required to have a score >7 on the Insomnia Severity Index and meet the diagnostic criteria for insomnia disorder. Open-ended, semistructured interviews were conducted to elicit participants' experiences with sleep problems. An a priori set of codes and a set of codes that emerged from the data were used to analyze the data. RESULT: The mean age of the sample was 60.5 years, with 30% identifying as non-white and 59% reporting their sex as female. The cancer types represented were heterogeneous with the two most common being breast (30%) and prostate (21%). Participants described an inherited risk for insomnia, anxious temperament, and insufficient ability to relax as predisposing factors. Respondents were split as to whether they classified their cancer diagnosis as the precipitating factor for their insomnia. Participants reported several behaviors that are known to perpetuate problems with sleep including napping, using back-lit electronics before bed, and poor sleep hygiene. One of the most prominent themes identified was the use of sleeping medications. Participants reported that they were reluctant to take medication but felt that it was the only option to treat their insomnia and that it was encouraged by their doctors. SIGNIFICANCE OF RESULTS: Insomnia is a prevalent, but highly treatable, disorder in cancer survivors. Patients and provider education is needed to change individual and organizational behaviors that contribute to the development and maintenance of insomnia and increase access to evidence-based nonpharmacological interventions.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".