AI Article Synopsis
- The study analyzed 351 women who underwent treatment for various cancers to understand the prevalence and predictors of sleep issues among them.
- Most participants (59%) experienced significant sleep disturbances, with various factors like younger age and having a partner linked to better sleep outcomes, while higher pain disability led to worse sleep.
- The findings highlight the need for targeted sleep intervention strategies for cancer survivors, using identified predictors to tailor support.
Article Abstract
Purpose: Using a discrete dataset from the Women's Wellness after Cancer Program (WWACP), we examine the prevalence and predictors of self-reported sleep problems in women previously treated for cancer.
Methods: Participants were 351 women (M = 53.2, SD = 8.8) from the WWACP who had completed surgery, chemotherapy and/or radiotherapy for breast, gynaecological or blood cancers within the previous 24 months. Sleep problems were measured using the Pittsburgh Sleep Quality Index (PSQI). Baseline data (i.e. prior to intervention randomisation) were analysed.
Results: Most women (59%) reported clinically significant sleep disturbance (PSQI > 5), 40% reported insufficient sleep duration (< 7 h), 38% self-reported poor sleep quality and 28% reported poor habitual sleep efficiency (sleep efficiency < 75%). Fewer psychological and vasomotor climacteric symptoms, age < 45 years and having a partner were associated with reduced odds (AOR < 1) of sleep problems. Higher levels of pain-related disability, and an intermediate compared to 'high' level of education, were associated with increased odds (AOR > 1) of sleep problems.
Conclusions: These findings confirm previous studies that have found a high prevalence of sleep problems in women previously treated for cancer. A range of sociodemographic, climacteric and pain-related factors were associated with sleep problems in this study.
Implications For Cancer Survivors: Targeted interventions to improve sleep quality after cancer treatment should be explored in this population. Predictors identified in this study could inform intervention targeting and development.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11082004 | PMC |
| http://dx.doi.org/10.1007/s11764-023-01346-9 | DOI Listing |
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