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

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      , PhD 1 , , , MBA 1 , , PhD 1
      (Reviewer), (Reviewer)
      JMIR mHealth and uHealth
      JMIR Publications
      cognitive behavioral therapy, insomnia, mobile phone, self-regulated learning

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          Abstract

          Background

          Insomnia 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.

          Objective

          The objective of this study was to propose a mobile sleep-management learning system integrated with SRL strategies and CBT.

          Methods

          A total of 18 undergraduate students from a university in northern Taiwan participated in the 2-week experiment of using this sleep-management system.

          Results

          The 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.

          Conclusions

          With 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 Registration

          Government 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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          Most cited references29

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          Becoming a Self-Regulated Learner: An Overview

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            Sleep and sleep disorders in older adults.

            A common but significant change associated with aging is a profound disruption to the daily sleep-wake cycle. It has been estimated that as many as 50% of older adults complain about difficulty initiating or maintaining sleep. Poor sleep results in increased risk of significant morbidity and mortality. Moreover, in younger adults, compromised sleep has been shown to have a consistent effect on cognitive function, which may suggest that sleep problems contribute to the cognitive changes that accompany older age. The multifactorial nature of variables affecting sleep in old age cannot be overstated. Changes in sleep have been thought to reflect normal developmental processes, which can be further compromised by sleep disturbances secondary to medical or psychiatric diseases (e.g., chronic pain, dementia, depression), a primary sleep disorder that can itself be age-related (e.g., Sleep Disordered Breathing and Periodic Limb Movements During Sleep), or some combination of any of these factors. Given that changes in sleep quality and quantity in later life have implications for quality of life and level of functioning, it is imperative to distinguish the normal age-related sleep changes from those originating from pathological processes.
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              Is Open Access

              mHealth 2.0: Experiences, Possibilities, and Perspectives

              With more than 1 billion users having access to mobile broadband Internet and a rapidly growing mobile app market, all stakeholders involved have high hopes that this technology may improve health care. Expectations range from overcoming structural barriers to access in low-income countries to more effective, interactive treatment of chronic conditions. Before medical health practice supported by mobile devices ("mHealth") can scale up, a number of challenges need to be adequately addressed. From a psychological perspective, high attrition rates, digital divide of society, and intellectual capabilities of the users are key issues when implementing such technologies. Furthermore, apps addressing behavior change often lack a comprehensive concept, which is essential for an ongoing impact. From a clinical point of view, there is insufficient evidence to allow scaling up of mHealth interventions. In addition, new concepts are required to assess the efficacy and efficiency of interventions. Regarding technology interoperability, open standards and low-energy wireless protocols appear to be vital for successful implementation. There is an ongoing discussion in how far health care-related apps require a conformity assessment and how to best communicate quality standards to consumers. "Apps Peer-Review" and standard reporting via an "App synopsis" appear to be promising approaches to increase transparency for end users. With respect to development, more emphasis must be placed on context analysis to identify what generic functions of mobile information technology best meet the needs of stakeholders involved. Hence, interdisciplinary alliances and collaborative strategies are vital to achieve sustainable growth for "mHealth 2.0," the next generation mobile technology to support patient care.
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                Author and article information

                Contributors
                Journal
                JMIR Mhealth Uhealth
                JMIR Mhealth Uhealth
                JMU
                JMIR mHealth and uHealth
                JMIR Publications (Toronto, Canada )
                2291-5222
                October 2018
                29 October 2018
                : 6
                : 10
                : e11557
                Affiliations
                [1 ] Department of Computer Science and Information Management School of Business Soochow University Taipei Taiwan
                Author notes
                Corresponding Author: Hui-Chun Chu carolhcchu@ 123456gmail.com
                Author information
                http://orcid.org/0000-0002-3131-4673
                http://orcid.org/0000-0002-5000-0354
                http://orcid.org/0000-0001-9311-6464
                Article
                v6i10e11557
                10.2196/11557
                6239866
                30373729
                0bc82d23-b749-4fe1-a29f-eaef79051fa9
                ©Hui-Chun Chu, Yi-Meng Liu, Fan-Ray Kuo. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 29.10.2018.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mhealth and uhealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/.as well as this copyright and license information must be included.

                History
                : 11 July 2018
                : 1 August 2018
                : 10 August 2018
                : 13 August 2018
                Categories
                Original Paper
                Original Paper

                cognitive behavioral therapy,insomnia,mobile phone,self-regulated learning

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