2022
DOI: 10.2196/32557
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Digital Health Technologies for Long-term Self-management of Osteoporosis: Systematic Review and Meta-analysis

Abstract: Background Osteoporosis is the fourth most common chronic disease worldwide. The adoption of preventative measures and effective self-management interventions can help improve bone health. Mobile health (mHealth) technologies can play a key role in the care and self-management of patients with osteoporosis. Objective This study presents a systematic review and meta-analysis of the currently available mHealth apps targeting osteoporosis self-management, … Show more

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Cited by 38 publications
(18 citation statements)
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“…This study aimed to analyze the impact of face-to-face supervision sessions on the effectiveness of self-management therapeutic exercise programs in patients with chronic LBP. Although there are several studies investigating the utility of mHealth in chronic conditions for improving the communication between patients and health professionals, collecting and monitoring changes over the time or as a treatment option [ 35 , 36 , 37 , 38 ], limited evidence is available for this specific population and exercise-based interventions.…”
Section: Discussionmentioning
confidence: 99%
“…This study aimed to analyze the impact of face-to-face supervision sessions on the effectiveness of self-management therapeutic exercise programs in patients with chronic LBP. Although there are several studies investigating the utility of mHealth in chronic conditions for improving the communication between patients and health professionals, collecting and monitoring changes over the time or as a treatment option [ 35 , 36 , 37 , 38 ], limited evidence is available for this specific population and exercise-based interventions.…”
Section: Discussionmentioning
confidence: 99%
“…AffECt has the potential for improving the performance of emotion recognition systems in various domains where the EC recognition is important; for example, in personalized healthcare [62], human-computer interaction [18], and education [63].…”
Section: Extended Perspectives Of Affectmentioning
confidence: 99%
“…We also performed a self-assessment of quality on reviewed articles based on 5 criteria; that is, test environment, prototype quality, feasibility test, sensor calibration, and versatility of the smart helmet (Textbox 1). Each criterion was scored from 1 to 3, and the sum of scores ranged from 5 to 15, as prior studies used this kind of scoring to provide an overview of the quality of the papers reviewed [32][33][34][35]. This idea of assessment scores originated from the work of Suri et al [32], AtheroPoint's artificial intelligence-based Bias-AP(ai)Bias-for detecting a risk of bias in the study selection process.…”
Section: Content Analysis and Study Quality Assessmentmentioning
confidence: 99%