scholarly journals Internet-based Individualized Cognitive Behavioral Therapy for Shift Work Sleep Disorder (Empowered by Wellbeing Prediction): A Pilot Study Protocol (Preprint)

2020 ◽  
Author(s):  
Asami Ito-Masui ◽  
Eiji Kawamoto ◽  
Ryota Sakamoto ◽  
Akane Sano ◽  
Eishi Motomura ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cognitive Behavioral Therapy ◽  
Sleep Disorder ◽  
Shift Work ◽  
Behavioral Therapy ◽  
Phase 1 ◽  
Cognitive Behavioral ◽  
Biometric Data ◽  
Shift Workers ◽  
Shift Work Sleep Disorder

BACKGROUND Shift work sleep disorders (SWSDs) are associated with the high turnover rates of nurses, and are considered a major medical safety issue. However, initial management can be hampered by insufficient awareness. In recent years, it has become possible to visualize, collect and analyze the work-life balance of healthcare workers with irregular sleeping and working habits by using wearable sensors that can continuously monitor biometric data under real life settings. In addition, internet-based cognitive behavioral therapy for psychiatric disorders has been shown to be effective. Application of wearable sensors and machine learning may potentially enhance the beneficial effects of internet-based cognitive behavioral therapy. OBJECTIVE In this study, we aim to develop and evaluate the effect of a new Internet-based cognitive behavioral therapy for shift work sleep disorder (iCBTS). This system includes current methods, such as medical sleep advice, as well as machine learning wellbeing prediction to improve sleep durations of shift workers and prevent declines in their wellbeing. METHODS This study consists of two phases: (1) preliminary data collection and machine learning for wellbeing prediction; (2) intervention and evaluation of iCBTS for shift work sleep disorder. Shift workers in the ICU at Mie University will wear a wearable sensor that collects biometric data and answer daily questionnaires regarding their wellbeing. Next, they will be provided with an iCBTS app for 4 weeks. Sleep and wellbeing measurements between baseline and the intervention period will then be compared. RESULTS Recruitment for phase 1 ended in October 2019. Recruitment for phase 2 is scheduled to start in October 2020. Preliminary results are expected to be available by summer 2021. CONCLUSIONS iCBTS empowered with wellbeing prediction is expected to improve the sleep durations of shift workers, thereby enhancing their overall well-being. Findings of this study will reveal the potential of this system for improving sleep disorders among shift workers. CLINICALTRIAL UMIN clinical trials registry (phase 1: UMIN 000036122, phase 2: UMIN000040547)

MP91-06 INCREASED RISK OF HYPOGONADAL SYMPTOMS IN SHIFT WORKERS WITH SHIFT WORK SLEEP DISORDER

2017 ◽  
Vol 197 (4S) ◽  
Author(s):  
Will Kirby ◽  
Adithya Balasubramanian ◽  
Javier Santiago ◽  
Mark Hockenberry ◽  
David Skutt ◽  
...  
Keyword(s):  
Sleep Disorder ◽  
Shift Work ◽  
Shift Workers ◽  
Shift Work Sleep Disorder ◽  
Increased Risk

Increased Risk of Hypogonadal Symptoms in Shift Workers With Shift Work Sleep Disorder

Urology ◽  
2020 ◽  
Vol 138 ◽  
pp. 52-59 ◽  
Author(s):  
Adithya Balasubramanian ◽  
Taylor P. Kohn ◽  
Javier E. Santiago ◽  
John T. Sigalos ◽  
E. Will Kirby ◽  
...  
Keyword(s):  
Sleep Disorder ◽  
Shift Work ◽  
Shift Workers ◽  
Shift Work Sleep Disorder ◽  
Increased Risk

scholarly journals Anonymous online cognitive behavioral therapy for sleep disorders in shift workers—a study protocol for a randomized controlled trial

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Lukas Retzer ◽  
Monika Feil ◽  
Richard Reindl ◽  
Kneginja Richter ◽  
Robert Lehmann ◽  
...  
Keyword(s):  
Cognitive Behavioral Therapy ◽  
Behavioral Therapy ◽  
Intervention Group ◽  
Online Intervention ◽  
Waiting List ◽  
Cognitive Behavioral ◽  
Control Group ◽  
Shift Workers ◽  
Face To Face ◽  
Randomized Controlled

Abstract Background Many shift workers suffer from sleep issues, which negatively affect quality of life and performance. Scientifically evaluated, structured programs for prevention and treatment are scarce. We developed an anonymous online cognitive behavioral therapy for insomnia (CBT-I) program. After successful completion of a feasibility study, we now start this prospective, randomized, controlled superiority trial to compare outcomes of two parallel groups, namely an intervention group and a waiting-list control-group. Additionally, we will compare these outcomes to those of a face-to-face CBT-I outpatient sample. Methods Collaborating companies will offer our anonymous online intervention to their shift-working employees. Company physicians and counseling services will screen those interested for inclusion and exclusion criteria. Participants will receive access to our online service, where they will complete psychometric assessment and receive random assignment to either the intervention group or the waiting-list control group. Participants and providers will be aware of the group assignment. We aim to allocate at least N = 60 participants to the trial. The intervention consists of psychoeducation, sleep restriction, stimulus control, relaxation techniques, and individual feedback delivered via four e-mail contacts. During the intervention, as well as during the waiting period, participants will fill out weekly sleep diaries. Immediately after completion of the program, the post-intervention assessment takes place. Participants in the control group will be able to participate in the program after all study assessments. To recruit an additional sample, collaborating outpatient sleep clinics will provide six sessions of standard face-to-face CBT-I to an ad hoc sample of shift working patients. We expect both the online and the face-to-face CBT-I interventions to have beneficial effects compared to the control group on the following primary outcomes: self-reported symptoms of depression and insomnia, sleep quality, and daytime sleepiness. Conclusions The online intervention allows shift workers to follow a CBT-I program independently of their working schedule and location. Forthcoming results might contribute to further improvement of prevention and therapy of sleep issues in shift workers. Trial registration German Clinical Trials Register DRKS DRKS00017777. Registered on 14 January 2020—retrospectively registered.

Preoperative cognitive–behavioral therapy for reducing pain catastrophizing and improving pain outcomes after total knee replacement: a randomized clinical trial

2021 ◽  
pp. rapm-2020-102258
Author(s):  
Asokumar Buvanendran ◽  
Amanda C Sremac ◽  
Patricia A Merriman ◽  
Craig J Della Valle ◽  
John W Burns ◽  
...  
Keyword(s):  
Cognitive Behavioral Therapy ◽  
Pain Catastrophizing ◽  
Behavioral Therapy ◽  
Phase 1 ◽  
Cognitive Behavioral ◽  
Womac Pain ◽  
Phase 2 ◽  
Pain Subscale ◽  
Pain Outcomes ◽  
Total Knee

IntroductionCognitive–behavioral therapy (CBT) can reduce preoperative pain catastrophizing and may improve postsurgical pain outcomes. We hypothesized that CBT would reduce pain catastrophizing more than no-CBT controls and result in improved pain outcomes.MethodsThe study was a randomized controlled trial of patients undergoing elective total knee arthroplasty between January 2013 and March 2020. In phase 1, the change in pain catastrophizing scores (PCS) among 4-week or 8-week telehealth, 4-week in person and no-CBT sessions was compared in 80 patients with a PCS >16. In phase 2, the proportion of subjects that achieved a 3-month decrease in Western Ontario and McMaster Universities Osteoarthritis (WOMAC) pain subscale >4 following 4-week telehealth CBT with no-CBT controls were compared in 80 subjects.ResultsIn phase 1, 4-week telehealth CBT had the highest completion rate 17/20 (85%), demonstrated an adjusted median reduction in PCS of −9 (95% CI −1 to −14, p<0.01) compared with no-CBT and was non-inferior to 8-week telehealth CBT at a margin of 2 (p=0.02). In phase 2, 29 of 35 (83%) in the 4-week telehealth CBT and 26 of 33 (79%) subjects in the no-CBT demonstrated a decrease in the WOMAC pain subscale >4 at 3 months, difference 4% (95% CI −18% to 26%, p=0.48), despite a median decrease in the PCS for the 4-week CBT and no-CBT group of −6 (−10 to −2, p=0.02).ConclusionsOur findings demonstrate that CBT interventions delivered prior to surgery in person or via telehealth can reduced PCS scores; however, this reduction did not lead to improved 3-month pain outcomes.Trial registration numberClinicalTrials.gov (NCT 01772329, registration date 21 January 2013).

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