Sleep advances : a journal of the Sleep Research Society最新文献

{"title":"Are there lingering effects of Daylight-Saving Time on sleep and health estimates of an Australian population?","authors":"Reece J Kemp, Robert J Adams, Jenny Haycock, Leon C Lack","doi":"10.1093/sleepadvances/zpag009","DOIUrl":"10.1093/sleepadvances/zpag009","url":null,"abstract":"<p><p>Research has examined acute sleep effects at the immediate transition onto Daylight-Saving Time (DST), culminating in a sentiment that it should be abolished. These effects could be theorized to continue well-into the DST period. The current article aimed to address this gap, investigating the effect of DST on sleep during the middle-late stages (2-4 and 6 months) of the DST period. A retrospective, cross-sectional design was used to compare subjective data of two nationwide surveys of the Australian population; one population-representative sample, and a convenience sample of those with chronic Insomnia. Respondents were categorized based on whether they were from a DST state or permanent Standard Time (ST) state. We then compared sleep behavior and tendencies in sleep health between DST and ST states. Overall, both samples consistently demonstrated that those from DST states tended to go to bed later and, particularly, rise at later clock times than those from ST states. Importantly, despite a delay in the timing of sleep we found no differences in reported Total Sleep Time nor Sleep Onset Latency; and no sign of impairment on any related health estimates. Very few sleep health variables reached significance (<i>p</i> < .05), and the vast majority of them suggested those from DST states were <i>less</i> impaired than their ST counterparts. We have found no evidence of impairment associated with DST well-into the DST period. Future studies should measure sleep and associated daytime functioning longitudinally and objectively to accurately assess the possible duration of any potential acute DST effect.</p>","PeriodicalId":74808,"journal":{"name":"Sleep advances : a journal of the Sleep Research Society","volume":"7 1","pages":"zpag009"},"PeriodicalIF":0.0,"publicationDate":"2026-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13016940/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147523017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association between cannabis use and insomnia symptoms among veterans with chronic pain.","authors":"Jonathan E Elliott, Daniel Schriemer, Hannah Flegal, Natassja Pal, Meike Niederhausen, Travis I Lovejoy, Steven K Dobscha, Benjamin J Morasco","doi":"10.1093/sleepadvances/zpag026","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpag026","url":null,"abstract":"<p><strong>Study objectives: </strong>Insomnia and chronic pain commonly co-occur, with Veterans more likely to experience both compared to the general population. As opioid prescribing practices change, there is growing interest in the use of cannabis for pain management and insomnia yet little data evaluating these potential associations.</p><p><strong>Methods: </strong>405 Veterans recruited nationally who were prescribed long-term opioid therapy for chronic pain and had a positive urine drug screen for THC in the month prior were enrolled. Participants were stratified into \"none\" (n = 118), \"mild\" (n = 140), and \"moderate/severe\" (n = 147) insomnia groups via the Insomnia Severity Index. THC consumption over the prior ~3-6 months was determined from nail samples, assayed for Carboxy-THC (pg/mg) via liquid gas chromatography/mass spectroscopy.</p><p><strong>Results: </strong>Bivariate analyses compared demographic and clinical factors based on insomnia severity classifications. Relative to patients without impaired sleep, those classified as having mild insomnia had significantly worse pain interference, anxiety, depression, and PTSD symptom severity. These relationships were further amplified in the moderate/severe sleep impairment group, which also reported significantly greater pain intensity. However, no group differences were found related to Carboxy-THC concentration, reflecting previous consumption characteristics. Multivariable linear regression examined variables associated with insomnia severity; PTSD, depression, and pain interference were associated with insomnia, with no effect of cannabis consumption.</p><p><strong>Conclusions: </strong>These findings suggest that in a sample of Veterans prescribed long-term opioid therapy with past month cannabis use, THC consumption may not be associated with insomnia symptoms. Future research should examine a possible threshold effect of cannabis dose on insomnia symptoms.</p>","PeriodicalId":74808,"journal":{"name":"Sleep advances : a journal of the Sleep Research Society","volume":"7 2","pages":"zpag026"},"PeriodicalIF":0.0,"publicationDate":"2026-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13147453/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147847248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A user's introduction to an algorithmic method to identify space-time profiles of sleep slow oscillations: dataset constraints, case-use examples, and open-source code.","authors":"Ali Snedden, Sara C Mednick, Paola Malerba","doi":"10.1093/sleepadvances/zpag024","DOIUrl":"10.1093/sleepadvances/zpag024","url":null,"abstract":"<p><p>Studies of sleep slow oscillations (SOs, 0.5-1.5 Hz) have emphasized their importance for cognition and health, and their variable spatial organization. We have introduced a data-driven method to analyze SOs as events that differentiate in their space-time co-emergence on the electrode manifold. This approach has identified properties of SO organization that are relevant to function, and that can change in clinical populations. In this work, we share a software and user manual that will allow the sleep research community to leverage our method directly in their own datasets. The work formalizes which dataset properties are necessary to deploy our method in terms of number of participants (<i>N</i>) and count of electrodes (<i>E</i>), and share parameterization strategies. We applied our algorithm to two datasets of nighttime sleep in healthy adults: Set1 (<i>N</i> = 22, <i>E</i> = 58) and Set2 (<i>N</i> = 34, <i>E</i> = 24). Roles of <i>E</i> and <i>N</i> values were tested by down-sampling electrodes to 24 and 8 channels, reflecting standard caps, and by randomly selecting subsets of participants. Early vs complete nighttime sleep was evaluated by truncating sets to 90 min after the first detected SO. Clustering outputs from tests were compared to original dataset outputs. Successful identification of SO profiles was evaluated with an index of similarity to ideal centroid masks. We found that identification of SO profiles required at least 22 participants and at least a 24 head-electrode montage, whereas 8 head-electrodes configurations, typical of clinically acquired sleep, were not sufficient. Furthermore, early nighttime sleep was sufficient for successful identification of SO profiles.</p>","PeriodicalId":74808,"journal":{"name":"Sleep advances : a journal of the Sleep Research Society","volume":"7 1","pages":"zpag024"},"PeriodicalIF":0.0,"publicationDate":"2026-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13034924/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147596693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using consumer sleep trackers for sleep extension interventions: retention, adherence, and user experiences.","authors":"Eliza Taylor, Mary Takgbajouah, Jennifer Duffecy, Minsun Park, Sirimon Reutrakul, Pamela Martyn-Nemeth, Kelly Glazer Baron","doi":"10.1093/sleepadvances/zpag025","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpag025","url":null,"abstract":"<p><strong>Study objectives: </strong>Consumer sleep trackers (CSTs) can provide insights into sleep behaviors for behavioral interventions. This study aimed to describe the implementation, adherence, and participant perceptions of CSTs across two behavioral sleep extension studies: Study 1, the Sleep Technology Intervention to Target Cardiometabolic Health and Study 2, the Sleep Optimization for Type 1 Diabetes.</p><p><strong>Methods: </strong>Both studies employed randomized controlled trial designs. Participants were provided with CSTs and engaged in structured coaching sessions via Zoom or phone, supplemented with sleep education materials. Adherence was measured by the number of days with sleep data recorded during the intervention periods (8 weeks for Study 1, 12 weeks for Study 2). Participant feedback was collected through end-of-study surveys that included open-ended questions with free text answers to assess usability, satisfaction, and perceived impact of CSTs. Open-ended feedback was analyzed using reflexive thematic analysis.</p><p><strong>Results: </strong>Study 1 enrolled 60 participants, and Study 2 enrolled 73 participants. Adherence was 89% and 86% and retention was 100% and 86%, respectively. Open-ended feedback revealed three themes: positive aspects of device use, negative aspects of device use, and device usability and data interactions. Participants found the CST helpful for motivation and goal tracking. However, technical issues, discomfort, and emotional responses to sleep data were noted as barriers.</p><p><strong>Conclusions: </strong>CSTs, when paired with personalized coaching and support, can effectively be used to promote participant engagement in sleep behavior change studies. Continued research is essential to refine wearable technology interventions to maximize their impact on health behavior modification.This article is part of the Consumer Sleep Technology Special Collection.</p>","PeriodicalId":74808,"journal":{"name":"Sleep advances : a journal of the Sleep Research Society","volume":"7 2","pages":"zpag025"},"PeriodicalIF":0.0,"publicationDate":"2026-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13116327/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147791866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ACCESS-OSA: a randomized controlled trial for accurate, accessible, and cost-effective screening solutions for obstructive sleep apnoea: study protocol.","authors":"Jack Manners, Maddy Roch, Lucia Pinilla, Robert J Adams, Barbara Toson, Ching Li Chai-Coetzer, Billingsley Kaambwa, Maree Barnes, Bastien Lechat, Kelly A Loffler, Alison White, Warren R Ruehland, Mark E Howard, Andrew Vakulin, Aeneas Yeo, Simon Proctor, Duc Phuc Nguyen, Jeremy Mercer, Alicia Hoberg, Laura Bandick, Melinda L Jackson, Amy S Jordan, Anna Ridgers, Sonya Johnston, Thomas Altree, Suzanne Curyer, Tom J Churchward, Julie Tolson, Alun Stevens, Danny J Eckert, Peter Catcheside, Sutapa Mukherjee","doi":"10.1093/sleepadvances/zpag023","DOIUrl":"10.1093/sleepadvances/zpag023","url":null,"abstract":"<p><p>Obstructive sleep apnoea (OSA) is common and burdensome, yet current diagnostic pathways remain costly and often misclassify patients. Single-night polysomnography (PSG), the diagnostic gold standard, fails to capture night-to-night variability in severity, is difficult to access and costly. Emerging technologies enable multi-night in-home evaluation, but robust comparative evidence regarding accuracy and cost-effectiveness is lacking. This study will evaluate (a) the diagnostic accuracy of three multi-night in-home devices versus conventional single night PSG; (b) the patient and signal characteristics that optimize diagnostic performance; and (c) the cost-effectiveness of these pathways for clinical implementation. We will conduct a three-arm randomized diagnostic strategy trial (n = 500) enrolling adults referred for suspected OSA over a recruitment period of several years from July 2025. All participants will undergo both conventional single-night PSG and multi-night assessment with an under-mattress sensor, oximetry ring, and forehead EEG device. Participants will be randomized to one of three diagnostic pathways, determining the order in which sleep physicians interpret test results. Sleep physicians will provide sequential diagnostic decisions at each stage, and a blinded expert panel will determine consensus diagnoses. The primary outcome is diagnostic accuracy of each pathway compared with consensus diagnosis. Secondary outcomes include cost-effectiveness, patient-reported acceptability, clinical confidence, self-reported long-term symptoms, and health and quality of life outcomes over 12 months follow-up. Findings will provide definitive evidence for whether simplified and accessible multi-night testing can improve accuracy and cost-effectiveness of OSA diagnosis in routine care.</p>","PeriodicalId":74808,"journal":{"name":"Sleep advances : a journal of the Sleep Research Society","volume":"7 1","pages":"zpag023"},"PeriodicalIF":0.0,"publicationDate":"2026-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13025067/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147576817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of a rule-based natural language processing algorithm to extract sleep information in pediatric primary care patients with a sleep diagnosis.","authors":"Joseph W Sirrianni, Ariana Calloway, Syed-Amad Hussain, Hongfang Liu, Christopher W Bartlett, Mattina A Davenport","doi":"10.1093/sleepadvances/zpag014","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpag014","url":null,"abstract":"<p><strong>Study objectives: </strong>The current study employed natural language processing (NLP) to capture multidimensional and transdiagnostic information in pediatric clinical notes. We present a novel, low-resource sleep vocabulary that can be applied to notes to identify pediatric sleep-related mentions automatically.</p><p><strong>Methods: </strong>Using a combination of existing medical sleep ontologies, interviews with clinicians, and examination of clinical note narratives, we develop a novel vocabulary of pediatric sleep-related terms and phrases that covers both technical terms, abbreviations, and colloquial keywords used in describing pediatric sleep health. We compare our vocabulary against a set of manually annotated clinical notes to determine the effectiveness of our vocabulary for identifying notes with pediatric sleep-related mentions.</p><p><strong>Results: </strong>Our vocabulary was able to correctly identify clinical notes with pediatric sleep-related mentions with a recall of 0.992 and a precision of 0.852. Most false positives occurred in notes that either explicitly stated no sleep issues or contained text unrelated to patient sleep health (e.g. medication side effects). Among the text spans annotated as sleep-related mentions, 77.1% include at least one keyword from our vocabulary.</p><p><strong>Conclusions: </strong>Our vocabulary showed excellent performance for identifying pediatric sleep-related mentions at the clinical note level and decent performance for identifying the specific text containing patient mentions. Our low-resource vocabulary, which can be deployed in almost any compute environment, can serve as an identifying first pass over clinical notes to identify which notes or note sections should be further processed by more advanced models or manual annotation review to identify more narrow mentions.</p>","PeriodicalId":74808,"journal":{"name":"Sleep advances : a journal of the Sleep Research Society","volume":"7 1","pages":"zpag014"},"PeriodicalIF":0.0,"publicationDate":"2026-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12920604/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147273518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Patient-reported outcome measures in central disorders of hypersomnolence: consensus of a sleep consortium/RARE-X expert working group.","authors":"Karmen Trzupek, Claire Wylds-Wright, Cynthia Kuan, Lindsay Jesteadt","doi":"10.1093/sleepadvances/zpag021","DOIUrl":"https://doi.org/10.1093/sleepadvances/zpag021","url":null,"abstract":"<p><p>Central disorders of hypersomnolence (CDoH), including the primary hypersomnolence disorders of narcolepsy type 1 (NT1), narcolepsy type 2 (NT2), idiopathic hypersomnia (IH), and Kleine-Levin syndrome (KLS), as well as secondary hypersomnolence disorders, represent an underdiagnosed and under-treated population. Continuing advancements in understanding and treating CDoH rely on an understanding of the patient and caregiver experience. To address this need, a community-led, patient-owned online research study was launched by the nonprofit organizations Sleep Consortium and Global Genes, using the RARE-X research platform. An expert working group of stakeholders with expertise in hypersomnolence disorders, including clinicians, therapy developers, and patient advocates, was convened to identify key patient- and caregiver-reported clinical outcome measures essential for evaluating CDoH symptoms and impacts. These clinical outcome measures have been implemented as part of an online direct-to-patient study. The measures chosen by the Sleep Consortium Expert Working Group are presented here with the hope of supporting the standardization of clinical outcome assessments being used in CDoH research, especially for primary hypersomnolence disorders.</p>","PeriodicalId":74808,"journal":{"name":"Sleep advances : a journal of the Sleep Research Society","volume":"7 1","pages":"zpag021"},"PeriodicalIF":0.0,"publicationDate":"2026-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12978642/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147446262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Functional analysis of bedtime procrastination in individuals with clinical insomnia: a behavior for digital emotional regulation?","authors":"Yeji Lee, Huisu Jeon, Sooyeon Suh","doi":"10.1093/sleepadvances/zpag019","DOIUrl":"10.1093/sleepadvances/zpag019","url":null,"abstract":"<p><p>Bedtime procrastination (BP) has been identified as a significant factor contributing to poor sleep health. While previous studies have examined its behavioral and psychological correlates, its functional role in individuals with clinical insomnia remains unclear. This study aims to investigate the primary functions of BP in individuals with insomnia and examine its relationship with smartphone use. A total of 80 young adults (mean age 22.3 ± 2.4 years, 80% female) with clinical insomnia participated in the study. BP, insomnia severity, and emotion regulation were assessed using self-report questionnaires. Additionally, sleep patterns were monitored using a daily sleep diary and actigraphy. A structured interview using functional analysis was conducted to analyze the individual functions of BP, classifying responses into seven categories based on antecedents, behaviors, and consequences. Participants spent an average of 95.9 (<i>SD</i> = 38.3) minutes per day using their smartphones in the 3 h before bedtime. Most participants used their phones every day during this window (78.8%). The most common functions of BP were emotion regulation (49.3%), reward (14.3%), and sleep induction (10.7%). In addition, adaptive emotion regulation strategies significantly moderated the relationship between BP and smartphone use in the 3 h before bedtime (<i>β</i> = 0.34, 95% CI = [0.02-0.23]). Our findings suggest that for individuals with clinical insomnia, BP, which is largely driven by smartphone use, can serve as a tool for emotion regulation. Interventions targeting BP should incorporate strategies considering individual functions of BP, rather than merely restricting media use.</p>","PeriodicalId":74808,"journal":{"name":"Sleep advances : a journal of the Sleep Research Society","volume":"7 1","pages":"zpag019"},"PeriodicalIF":0.0,"publicationDate":"2026-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13025074/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147576867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Slow wave electroencephalogram spectral properties during adaptation of a new light dark cycle in cynomolgus monkeys.","authors":"Ruitong Jiang, Julian Low, Martha H Vitaterna, Karrie Fitzpatrick, Douglas J Weber, Darcy M Griffin","doi":"10.1093/sleepadvances/zpag020","DOIUrl":"10.1093/sleepadvances/zpag020","url":null,"abstract":"<p><strong>Study objectives: </strong>Shifts in the light-dark cycle (L:D cycle) often trigger phase shifts in physiological data related to the sleep-wake cycle. Slow wave activity (delta) indicates sleep pressure and intensity. This study examines how delta power adapts to shifts in L:D cycle and the temporal dynamics of its coupling with rest-activity rhythms during re-entrainment.</p><p><strong>Methods: </strong>We collected electroencephalogram (EEG) and accelerometer data from three non-human primates during baseline and shifted (8-h delayed light-on) conditions. We derived delta power (0.5 ~ 4 Hz) using Fast Fourier Transform. To quantify changes in delta power dynamics following L:D cycle shifts, we calculated diurnal differences in delta power, per cent variance explained by time-of-day, circadian coupling with physical activity, and delta power activity transitions timing.</p><p><strong>Results: </strong>In both conditions, delta power exhibited a robust 24-h periodicity, and a significant portion of the variance (57.61% ± 6.99%) could be explained by time of day. We found an early transition of delta power in the first 2 days of the shifted condition, followed by realignment to the light-off time within 3 days after the shift. We used coherence analysis to reveal strong coupling between delta power and locomotor activity, with a consistent anti-phase relationship across baseline and phase shifted conditions.</p><p><strong>Conclusions: </strong>Our findings demonstrate that delta power adapts rapidly to environmental phase shifts while maintaining circadian rhythmicity and stable coordination with rest-activity rhythms. Here, we provide new insight into how neural and behavioral states remain aligned during circadian disruptions in a diurnal species.</p>","PeriodicalId":74808,"journal":{"name":"Sleep advances : a journal of the Sleep Research Society","volume":"7 1","pages":"zpag020"},"PeriodicalIF":0.0,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13025076/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147576809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Measuring sleep disturbance in advanced cancer using the brief Pittsburgh sleep quality index (bPSQI).","authors":"Craig Gouldthorpe, Andrew Davies","doi":"10.1093/sleepadvances/zpag018","DOIUrl":"10.1093/sleepadvances/zpag018","url":null,"abstract":"<p><p>Sleep disturbance is common among patients with cancer and is linked to significant morbidity, poorer quality of life and reduced survival in this population. The Pittsburgh Sleep Quality Index (PSQI) can identify poor sleep quality in this population, although a higher threshold value may be required compared to the general population. The brief PSQI (bPSQI), consisting of six of the original 19 items, offers a quicker and simpler tool. The bPSQI has demonstrated comparable accuracy in identifying poor sleep in the general population but remains unexplored in patients with advanced cancer. This observational study of 65 patients with advanced cancer reiterates the prevalence of sleep disturbance, demonstrates good internal consistency of the bPSQI and notes higher bPSQI scores with increasing subjective sleep-related distress. Although significant associations were noted between the bPSQI global score, individual bPSQI item scores and single-item sleep disturbance questions, the study cautions against the use of single-item questions in detecting sleep problems. Discrepancies were noted between subjective and objective sleep assessments. The findings support a higher threshold value for identifying poor sleep quality using the bPSQI. Although limited by a small sample size, the findings emphasize the need for further validation of the bPSQI in this population and to ensure that assessment methods align with research aims.</p>","PeriodicalId":74808,"journal":{"name":"Sleep advances : a journal of the Sleep Research Society","volume":"7 1","pages":"zpag018"},"PeriodicalIF":0.0,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13034921/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147596680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}