Cognitive Behavioral Therapy Using a Mobile Application Synchronizable With Wearable Devices for Insomnia Treatment: A Pilot Study

Kang, Seung-Gul; Kang, Jae Myeong; Cho, Seong Jin; Ko, Kwang Pil; Lee, Yu Jin; Lee, Heon Jeong; Winkelman, John W.

doi:10.5664/jcsm.6564

Cited by 44 publications

(43 citation statements)

References 18 publications

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“…The researchers found that those who used mobile apps and stress algorithm were more likely to complete their goals and demonstrated reduced stress and anger compared with the control group. It can be inferred from the results that the SMSR integrated with CBT and the SRL strategy helped enhance users’ cognition of sleep hygiene; this finding is consistent with that reported in another study [ 33 ], showing that CBT integrated with mobile apps would be a positive treatment for patients with insomnia. On the other hand, this study also found that users could gain benefits by using the SRL strategy integrated with a mobile app, no matter whether they were using wearable devices or not; this implies that the guidance provided in the self-monitoring process could help users be aware of their own situations and, hence, improve their sleep quality.…”

Section: Discussionsupporting

confidence: 89%

A Mobile Sleep-Management Learning System for Improving Students’ Sleeping Habits by Integrating a Self-Regulated Learning Strategy: Randomized Controlled Trial

Liu

Kuo

2018

JMIR Mhealth Uhealth

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BackgroundInsomnia can significantly affect students’ learning performance. Researchers have indicated the importance and challenge of coping with insomnia using nondrug treatments, such as cognitive behavioral therapy (CBT) for insomnia. However, it is easy for the traditional CBT for insomnia to be interrupted owing to the overly lengthy period of sleep therapy. Self-regulated learning (SRL) strategies are known to be an effective approach for helping students improve their time management, as well as their ability to set learning goals and adopt learning strategies.ObjectiveThe objective of this study was to propose a mobile sleep-management learning system integrated with SRL strategies and CBT.MethodsA total of 18 undergraduate students from a university in northern Taiwan participated in the 2-week experiment of using this sleep-management system.ResultsThe experimental results showed that the proposed approach was useful and easy for students to use. In addition, the number of students with insomnia significantly decreased; that is, the proposed approach could help students improve their sleep quality and cultivate better sleeping habits, which is important for them to enhance their learning efficiency.ConclusionsWith the assistance of this proposed approach, students can plan their daily life by setting goals, applying strategies, monitoring their life habits process, and modifying strategies to cultivate good learning and healthy lifestyle habits.Trial RegistrationGovernment Research Bulletin MOST104-3011-E038-001; https://www.grb.gov.tw/search/planDetail? id=11568383&docId=467988 (Archived by WebCite at http://www.webcitation.org/73MnPHNri)

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Section: Discussionsupporting

confidence: 89%

A Mobile Sleep-Management Learning System for Improving Students’ Sleeping Habits by Integrating a Self-Regulated Learning Strategy: Randomized Controlled Trial

Liu

Kuo

2018

JMIR Mhealth Uhealth

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“…There were two studies that focused on both physical activity and sleep, one in an employee wellness program, [53] one in college students [56]. One study reported on a pilot study of CBT for insomnia using a mobile application paired with a wearable device [54]. The results of the intervention studies were variable.…”

Section: Resultsmentioning

confidence: 99%

Feeling validated yet? A scoping review of the use of consumer-targeted wearable and mobile technology to measure and improve sleep

Baron

Duffecy

Berendsen

et al. 2018

Sleep Medicine Reviews

136

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The objectives of this review were to evaluate the use of consumer-targeted wearable and mobile sleep monitoring technology, identify gaps in the literature and determine the potential for use in behavioral interventions. We undertook a scoping review of studies conducted in adult populations using consumer-targeted wearable technology or mobile devices designed to measure and/or improve sleep. After screening for inclusion/exclusion criteria, data were extracted from the articles by two co-authors. Articles included in the search were using wearable or mobile technology to estimate or evaluate sleep, published in English and conducted in adult populations. Our search returned 3897 articles and 43 met our inclusion criteria. Results indicated that the majority of studies focused on validating technology to measure sleep (n = 23) or were observational studies (n = 10). Few studies were used to identify sleep disorders (n = 2), evaluate response to interventions (n = 3) or deliver interventions (n = 5). In conclusion, the use of consumer-targeted wearable and mobile sleep monitoring technology has largely focused on validation of devices and applications compared with polysomnography (PSG) but opportunities exist for observational research and for delivery of behavioral interventions. Multidisciplinary research is needed to determine the uses of these technologies in interventions as well as the use in more diverse populations including sleep disorders and other patient populations.

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“…CBT-I coach is a central place to track sleep habits, provide tools (e.g., relaxation breathing, guided imagery), and encourage positive reinforcement. 8 As insomnia is multifactorial, appropriate management of comorbid medical illness should be emphasized. In particular, obstructive sleep apnea, pain disorders, mood disorders, substance use disorders, and nocturia should all be treated effectively.…”

Section: Nonpharmacologic Treatmentmentioning

confidence: 99%

Updates in insomnia diagnosis and treatment

Bragg

Benich²,

Christian

et al. 2019

Int J Psychiatry Med

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Introduction Insomnia is the most commonly reported sleep disorder and remains undertreated in many patients. New changes to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, have changed the way insomnia is diagnosed. In patients who suffer from insomnia, a number of available treatment options exist including both behavioral therapy and medications. Literature Review: First line therapy for insomnia should always include behavioral modifications such as sleep hygiene and insomnia-oriented cognitive behavioral therapy. In patients deemed to need pharmacotherapy, first line medications include nonbenzodiazepine hypnotics (i.e., z-drugs) and antidepressants depending on the patients’ needs and comorbidities. The risk of next day impairment, parasomnias, and central nervous system depression are some of the most feared side effects with z-drugs. Second line drug therapy includes melatonin and suvorexant. Several concerns exist for suvorexant similar to other insomnia medications, but melatonin remains one of the safest medication alternatives. Other medication options such as benzodiazepines, antihistamines, and antipsychotics should rarely be used because of weak effectiveness data or serious safety concerns. Discussion The most appropriate treatment plan needs to be tailored to meet the needs of individual patients. Many patient factors (e.g., age, other comorbidities, specific problems with sleep) need to be considered before prescribing drug therapy for patients suffering from insomnia. Medications with the best evidence and fewest safety concerns should be prioritized when clinicians work with patients to determine the most appropriate treatment plan. Conclusions Nondrug treatment should be the emphasis for managing insomnia, but several options exist for patients needing multimodal therapy to improve their symptoms and maximize their quality of life. Z-drugs and antidepressants are first line medications options, but other options may be considered when tailored to individual patients. Medications should only be used intermittently and short term until nondrug treatments help to change a patient’s sleep routine.

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Cognitive Behavioral Therapy Using a Mobile Application Synchronizable With Wearable Devices for Insomnia Treatment: A Pilot Study

Cited by 44 publications

References 18 publications

A Mobile Sleep-Management Learning System for Improving Students’ Sleeping Habits by Integrating a Self-Regulated Learning Strategy: Randomized Controlled Trial

A Mobile Sleep-Management Learning System for Improving Students’ Sleeping Habits by Integrating a Self-Regulated Learning Strategy: Randomized Controlled Trial

Feeling validated yet? A scoping review of the use of consumer-targeted wearable and mobile technology to measure and improve sleep

Updates in insomnia diagnosis and treatment

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