Sham sleep feedback delivered via actigraphy biases daytime symptom reports in people with insomnia: Implications for insomnia disorder and wearable devices

BACKGROUND Wearable devices have been developed and implemented to improve data collection in remote health care and smart care. Wearable devices have the advantage of always being with individuals, enabling easy detection of their movements. In this study, we developed and implemented a smart-care system using smart clothing for persons with dementia and with hip fracture. We conducted a preliminary study to understand family caregivers’ and care receivers’ experiences of receiving a smart technology-assisted (STA) home-nursing care program. OBJECTIVE This paper reports the difficulties we encountered and strategies we developed during the feasibility phase of studies on the effectiveness of our STA home-nursing care program for persons with dementia and hip fracture. METHODS Our care model, a STA home-nursing care program for persons with dementia and those with hip fracture included a remote-monitoring system for elderly persons wearing smart clothing was used to facilitate family caregivers’ detection of elderly persons’ movements. These movements included getting up at night, staying in the bathroom for more than 30 minutes, not moving more than 2 hours during the day, leaving the house, and daily activities. Participants included 13 families with 5 patients with hip fracture and 7 with dementia. Research nurses documented the difficulties they encountered during the process. RESULTS Difficulties encountered in this smart-care study were categorized into problems setting up the smart-care environment, problems running the system, and problems with participant acceptance/adherence. These difficulties caused participants to drop out, the system to not function or delayed function, inability to collect data, extra costs of manpower, and financial burden. Strategies to deal with these problems are also reported. CONCLUSIONS During the implementation of smart care at home for persons with dementia or hip fracture, different aspects of difficulties were found and strategies were taken. The findings of this study can provide a reference for future implementation of similar smart-home devices.

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Healthcare Body Sensor Networks and Smart Wearable Devices in Internet of Medical Things

American Journal of Medical Research ◽

10.22381/ajmr71202010 ◽

2020 ◽

Vol 7 (1) ◽

pp. 67 ◽

Cited By ~ 1

Keyword(s):

Sensor Networks ◽

Wearable Devices ◽

Body Sensor Networks ◽

Internet Of Medical Things ◽

Smart Wearable

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Interoception, categorization, and symptom perception

10.1093/oso/9780198811930.003.0011 ◽

2018 ◽

Author(s):

Omer Van den Bergh ◽

Nadia Zacharioudakis ◽

Sibylle Petersen

Keyword(s):

Decision Making ◽

Medical Practice ◽

Disease Model ◽

Clinical Implications ◽

Symptom Perception ◽

Symptom Reports ◽

The Relationship ◽

Accurate Reflection

Medical practice and the disease model importantly rely on the accuracy assumption of symptom perception: patients’ symptom reports are a direct and accurate reflection of physiological dysfunction. This implies that symptoms can be used as a read-out of dysfunction and that remedying the dysfunction removes the symptoms. While this assumption is viable in many instances of disease, the relationship between symptoms and physiological dysfunction is highly variable and, in a substantial number of cases, completely absent. This chapter considers symptom perception as a form of unconscious inferential somatic decision-making that compellingly produces consciously experienced symptoms. At a mechanistic level, this perspective removes the categorical distinction between symptoms that are closely associated with physiological dysfunction and those that are not. In addition, it brings symptom perception in accordance with general theories of perception. Some clinical implications to understand and treat symptoms poorly related to physiological dysfunction are discussed.

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Overcoming the Privacy Challenges of Wearable Devices

Proceedings of the 18th Annual International Conference on Digital Government Research - dg.o '17 ◽

10.1145/3085228.3085254 ◽

2017 ◽

Cited By ~ 1

Author(s):

Loni Hagen

Keyword(s):

Wearable Devices

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Comparisons of physical activity and sedentary behavior between owners and non-owners of commercial wearable devices

Perspectives in Public Health ◽

10.1177/1757913921989389 ◽

2021 ◽

Vol 141 (2) ◽

pp. 89-96

Author(s):

Hsin-Yen Yen ◽

Hao-Yun Huang

Keyword(s):

Physical Activity ◽

Sleep Quality ◽

Sedentary Behavior ◽

Sedentary Time ◽

Short Form ◽

Wearable Devices ◽

Wearable Device ◽

World Health ◽

World Health Organization Quality ◽

Quality Of Life Scale

Aims: Wearable devices are a new strategy for promoting physical activity in a free-living condition that utilizes self-monitoring, self-awareness, and self-determination. The main purpose of this study was to explore health benefits of commercial wearable devices by comparing physical activity, sedentary time, sleep quality, and other health outcomes between individuals who used and those that did not use commercial wearable devices. Methods: The research design was a cross-sectional study using an Internet survey in Taiwan. Self-administered questionnaires included the International Physical Activity Questionnaire–Short Form, Pittsburgh Sleep Quality Index, Health-Promoting Lifestyle Profile, and World Health Organization Quality-of-Life Scale. Results: In total, 781 participants were recruited, including 50% who were users of wearable devices and 50% non-users in the most recent 3 months. Primary outcomes revealed that wearable device users had significantly higher self-reported walking, moderate physical activity, and total physical activity, and significantly lower sedentary time than non-users. Wearable device users had significantly better sleep quality than non-users. Conclusion: Wearable devices inspire users’ motivation, engagement, and interest in physical activity through habit formation. Wearable devices are recommended to increase physical activity and decrease sedentary behavior for promoting good health.

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765 Anxiety and sleep in Generalized Anxiety Disorder with and without Insomnia Disorder

SLEEP ◽

10.1093/sleep/zsab072.762 ◽

2021 ◽

Vol 44 (Supplement_2) ◽

pp. A298-A298

Author(s):

Augustus Kram Mendelsohn ◽

Carolina Daffre ◽

Katelyn Oliver ◽

Jeehye Seo ◽

Natasha Lasko ◽

...

Keyword(s):

Anxiety Disorder ◽

Generalized Anxiety Disorder ◽

Anxiety Sensitivity ◽

Slow Wave Sleep ◽

Stress Test ◽

Generalized Anxiety ◽

Poor Sleep ◽

Sensitivity Index ◽

Somatic Anxiety ◽

Insomnia Disorder

Abstract Introduction Insomnia Disorder (ID) elevates risk of incident anxiety disorders and vice versa. We examined whether ID and poor sleep are associated with greater self-reported anxiety in persons with Generalized Anxiety Disorder (GAD). Methods Twenty-one participants with GAD and ID (GAD+/ID+) having Insomnia Severity Index (ISI) scores ≥ 13 (mean 17.8, SD 3.6) and 14 with GAD but not ID (GAD+/ID-) having ISI scores ≤ 12 (mean 6.4, SD 3.4) completed 14 days of actigraphy and sleep diaries as well as a night of ambulatory polysomnography (PSG) following an acclimation night. Participants completed the Pittsburgh Sleep Quality Index (PSQI), the State-Trait Inventory for Cognitive and Somatic Anxiety (STICSA-T/C, -T/S), the Ford Insomnia Response to Stress Test (FIRST), the Penn State Worry Questionnaire (PSWQ), and the Anxiety Sensitivity Index (ASI). Differences in self-reported anxiety (STICSA, ASI, PSWQ) between GAD+/ID+ and GAD+/ID- were analyzed using t-tests. Relationships of anxiety with retrospective (PSQI, FIRST, ISI), longitudinal (actigraphy, diaries) and physiological (PSG) sleep variables were analyzed using simple regression. Results GAD+/ID+ versus GAD+/ID- participants showed trends toward higher anxiety on the PSWQ (p=0.075), ASI (p=0.072) and STICSA-T/S (p=0.078). PSQI scores were positively associated with STICSA-T/S, (R=0.417, p=0.018, N=32). Greater insomnia reactivity (FIRST) was associated with increased worry on the PSWQ (R=0.352, p=0.044, N=33). STICSA-T/C was negatively associated with mean diary (R= -0.440, p=0.015, N=30) and actigraph (R= -0.517, p=0.01, N=24) total sleep time (TST). Actigraph mean TST trended toward lower PSWQ (R= -0.376, p=0.058, N=26) while actigraph mean sleep efficiency (SE) trended toward lesser STICSA-T/C (R= -0.397, p=0.058). Greater REM% was associated with greater STICSA-T/C (R=0.613, p=0.0005, N=28) and STICSA-T/S (R=0.516, p=0.005), a relationship also seen in GAD+/ID+ alone (p=0.03 and 0.015 respectively, N=16). Slow Wave Sleep% (SWS%) was not associated with lesser STICSA-T/S across both groups (p=0.14) but was so in GAD+/ID+ (R= -0.539, p=0.031, N=16). Conclusion GAD+/ID+ versus GAD+/ID-, show greater worry, anxiety sensitivity and somatic anxiety. In GAD, shorter and poorer quality sleep measured retrospectively or averaged longitudinally, as well as greater REM%, are associated with greater somatic and cognitive anxiety. Among those with ID, greater SWS% is associated with less somatic anxiety. Support (if any) R21MH115279, R01MH109638

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