Maeve M Pascoe, Alex R. Wollet, Julianie De La Cruz Minyety, Elizabeth Vera, Hope Miller, O. Celiku, H. Leeper, Kelly Fernandez, Jennifer Reyes, Demarrius Young, Alvina A. Acquaye-Mallory, Kendra A. Adegbesan, L. Boris, E. Burton, Claudia P Chambers, Anna Choi, E. Grajkowska, Tricia F. Kunst, Jason Levine, M. Panzer, M. Penas-Prado, V. Pillai, L. Polskin, Jing Wu, Mark R Gilbert, T. Mendoza, Amanda L King, Dorela D. Shuboni-Mulligan, Terri S Armstrong
{"title":"利用智能可穿戴设备和患者报告数据评估原发性脑肿瘤患者的睡眠情况:一项观察性研究的可行性和中期分析","authors":"Maeve M Pascoe, Alex R. Wollet, Julianie De La Cruz Minyety, Elizabeth Vera, Hope Miller, O. Celiku, H. Leeper, Kelly Fernandez, Jennifer Reyes, Demarrius Young, Alvina A. Acquaye-Mallory, Kendra A. Adegbesan, L. Boris, E. Burton, Claudia P Chambers, Anna Choi, E. Grajkowska, Tricia F. Kunst, Jason Levine, M. Panzer, M. Penas-Prado, V. Pillai, L. Polskin, Jing Wu, Mark R Gilbert, T. Mendoza, Amanda L King, Dorela D. Shuboni-Mulligan, Terri S Armstrong","doi":"10.1093/nop/npae048","DOIUrl":null,"url":null,"abstract":"\n \n \n Sleep-wake disturbances are common and disabling in primary brain tumor (PBT) patients but studies exploring longitudinal data are limited. This study investigates the feasibility and relationship between longitudinal patient-reported outcomes (PROs) and physiologic data collected via smart wearables.\n \n \n \n Fifty-four PBT patients ≥18 years wore Fitbit smart-wearable devices for 4 weeks, which captured physiologic sleep measures (e.g., total sleep time, wake after sleep onset (WASO)). They completed PROs (Sleep Hygiene Index, PROMIS Sleep-Related Impairment (SRI) and Sleep Disturbance (SD), Morningness-Eveningness Questionnaire (MEQ)) at baseline and 4 weeks. Smart wearable use feasibility (enrollment/attrition, data missingness), clinical characteristics, test consistency, PROs severity, and relationships between PROs and physiologic sleep measures were assessed.\n \n \n \n The majority (72%) wore their Fitbit for the entire study duration with 89% missing <3 days, no participant withdrawals, and 100% PRO completion. PROMIS SRI/SD and MEQ were all consistent/reliable (Cronbach’s alpha 0.74-0.92). Chronotype breakdown showed 39% morning, 56% intermediate, and only 6% evening types. Moderate-severe SD & SRI were reported in 13% and 17% at baseline, and with significant improvement in SD at 4 weeks (p=0.014). Fitbit-recorded measures showed a correlation at week 4 between WASO and SD (r=0.35, p=0.009) but not with SRI (r=0.24, p=0.08).\n \n \n \n Collecting sleep data with Fitbits is feasible, PROs are consistent/reliable, >10% of participants had SD and SRI that improved with smart wearable use, and SD was associated with WASO. The skewed chronotype distribution, risk and impact of sleep fragmentation mechanisms warrant further investigation.\n","PeriodicalId":19234,"journal":{"name":"Neuro-oncology practice","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessing Sleep in Primary Brain Tumor Patients using Smart Wearables and Patient-Reported Data: Feasibility and Interim Analysis of an Observational Study\",\"authors\":\"Maeve M Pascoe, Alex R. Wollet, Julianie De La Cruz Minyety, Elizabeth Vera, Hope Miller, O. Celiku, H. Leeper, Kelly Fernandez, Jennifer Reyes, Demarrius Young, Alvina A. Acquaye-Mallory, Kendra A. Adegbesan, L. Boris, E. Burton, Claudia P Chambers, Anna Choi, E. Grajkowska, Tricia F. Kunst, Jason Levine, M. Panzer, M. Penas-Prado, V. Pillai, L. Polskin, Jing Wu, Mark R Gilbert, T. Mendoza, Amanda L King, Dorela D. Shuboni-Mulligan, Terri S Armstrong\",\"doi\":\"10.1093/nop/npae048\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n \\n \\n Sleep-wake disturbances are common and disabling in primary brain tumor (PBT) patients but studies exploring longitudinal data are limited. This study investigates the feasibility and relationship between longitudinal patient-reported outcomes (PROs) and physiologic data collected via smart wearables.\\n \\n \\n \\n Fifty-four PBT patients ≥18 years wore Fitbit smart-wearable devices for 4 weeks, which captured physiologic sleep measures (e.g., total sleep time, wake after sleep onset (WASO)). They completed PROs (Sleep Hygiene Index, PROMIS Sleep-Related Impairment (SRI) and Sleep Disturbance (SD), Morningness-Eveningness Questionnaire (MEQ)) at baseline and 4 weeks. Smart wearable use feasibility (enrollment/attrition, data missingness), clinical characteristics, test consistency, PROs severity, and relationships between PROs and physiologic sleep measures were assessed.\\n \\n \\n \\n The majority (72%) wore their Fitbit for the entire study duration with 89% missing <3 days, no participant withdrawals, and 100% PRO completion. PROMIS SRI/SD and MEQ were all consistent/reliable (Cronbach’s alpha 0.74-0.92). Chronotype breakdown showed 39% morning, 56% intermediate, and only 6% evening types. Moderate-severe SD & SRI were reported in 13% and 17% at baseline, and with significant improvement in SD at 4 weeks (p=0.014). Fitbit-recorded measures showed a correlation at week 4 between WASO and SD (r=0.35, p=0.009) but not with SRI (r=0.24, p=0.08).\\n \\n \\n \\n Collecting sleep data with Fitbits is feasible, PROs are consistent/reliable, >10% of participants had SD and SRI that improved with smart wearable use, and SD was associated with WASO. The skewed chronotype distribution, risk and impact of sleep fragmentation mechanisms warrant further investigation.\\n\",\"PeriodicalId\":19234,\"journal\":{\"name\":\"Neuro-oncology practice\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-05-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neuro-oncology practice\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1093/nop/npae048\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neuro-oncology practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/nop/npae048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Assessing Sleep in Primary Brain Tumor Patients using Smart Wearables and Patient-Reported Data: Feasibility and Interim Analysis of an Observational Study
Sleep-wake disturbances are common and disabling in primary brain tumor (PBT) patients but studies exploring longitudinal data are limited. This study investigates the feasibility and relationship between longitudinal patient-reported outcomes (PROs) and physiologic data collected via smart wearables.
Fifty-four PBT patients ≥18 years wore Fitbit smart-wearable devices for 4 weeks, which captured physiologic sleep measures (e.g., total sleep time, wake after sleep onset (WASO)). They completed PROs (Sleep Hygiene Index, PROMIS Sleep-Related Impairment (SRI) and Sleep Disturbance (SD), Morningness-Eveningness Questionnaire (MEQ)) at baseline and 4 weeks. Smart wearable use feasibility (enrollment/attrition, data missingness), clinical characteristics, test consistency, PROs severity, and relationships between PROs and physiologic sleep measures were assessed.
The majority (72%) wore their Fitbit for the entire study duration with 89% missing <3 days, no participant withdrawals, and 100% PRO completion. PROMIS SRI/SD and MEQ were all consistent/reliable (Cronbach’s alpha 0.74-0.92). Chronotype breakdown showed 39% morning, 56% intermediate, and only 6% evening types. Moderate-severe SD & SRI were reported in 13% and 17% at baseline, and with significant improvement in SD at 4 weeks (p=0.014). Fitbit-recorded measures showed a correlation at week 4 between WASO and SD (r=0.35, p=0.009) but not with SRI (r=0.24, p=0.08).
Collecting sleep data with Fitbits is feasible, PROs are consistent/reliable, >10% of participants had SD and SRI that improved with smart wearable use, and SD was associated with WASO. The skewed chronotype distribution, risk and impact of sleep fragmentation mechanisms warrant further investigation.
期刊介绍:
Neuro-Oncology Practice focuses on the clinical aspects of the subspecialty for practicing clinicians and healthcare specialists from a variety of disciplines including physicians, nurses, physical/occupational therapists, neuropsychologists, and palliative care specialists, who have focused their careers on clinical patient care and who want to apply the latest treatment advances to their practice. These include: Applying new trial results to improve standards of patient care Translating scientific advances such as tumor molecular profiling and advanced imaging into clinical treatment decision making and personalized brain tumor therapies Raising awareness of basic, translational and clinical research in areas of symptom management, survivorship, neurocognitive function, end of life issues and caregiving