Background: Knee osteoarthritis is a prevalent cause of disability among older adults, emphasizing the need for effective and accessible self-management strategies. Mobile app-based personalized exercise programs predominantly overcome the barriers associated with traditional approaches.
Objective: This study aimed to evaluate the feasibility and preliminary efficacy of a 6-week mobile app-based self-exercise program that incorporates a multimonitoring system, weekly progress tracking, and dynamic exercise adjustments used by physiotherapists, and compares them with those of a conventional paper-based self-exercise program in older patients with chronic knee osteoarthritis.
Methods: A total of 29 participants aged ≥60 years with chronic knee pain and radiographic evidence of osteoarthritis were randomized at a 2:1 ratio to either the intervention (19/29, 66%; mobile app-based program) or control (10/29, 34%; paper-based program) group. The mobile app delivered a personalized exercise program, which was tailored by physiotherapists based on remote monitoring of patient-reported symptoms. Feasibility outcomes included retention, adherence, and satisfaction rates, as well as safety. Preliminary clinical outcomes included changes from baseline to 6 weeks in the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) total score, Numeric Rating Scale (NRS) pain, and other functional measures.
Results: A total of 26 participants (n=16, 62% intervention and n=10, 38% control) completed the 6-week assessment, with retention rates of 84% and 100%, respectively. No adverse events were reported. Adherence was high in the intervention group, with 69% exercising ≥5 days per week and 88% reporting high satisfaction. The intervention group exhibited significant reductions in the WOMAC total score (median change -11.00, 95% CI -23.00 to -2.50; P=.01) and NRS pain score (mean change -2.12, 95% CI -3.13 to -1.11; P<.001).
Conclusions: The mobile app-based personalized exercise program was feasible, safe, and well-accepted among older patients with knee osteoarthritis. High adherence and satisfaction support the practicality of this approach, and preliminary improvements in pain and function suggest potential clinical benefit. A larger, adequately powered trial is warranted to confirm the effectiveness of digital self-exercise interventions for knee osteoarthritis management.
Background: The adoption of mobile health (mHealth) technologies among older adults remains significantly lower than in younger populations, despite their potential to promote healthier lifestyles and mitigate age-related health risks.
Objective: This study aims to explore the perspectives of retirement-age adults on mHealth interventions, identifying factors that influence their adoption, such as persuasive elements in the app design and psychological techniques.
Methods: A qualitative focus group study was conducted with 19 Spanish participants recruited from urban community settings in Madrid, Spain (mean age 61.5 years; 15/19, 79% women). Participants discussed their attitudes, barriers, and preferences for mHealth tools. Focus groups were recorded, transcribed, and coded using an iterative process to ensure rigorous data analysis. An abductive approach was followed, using the persuasive design principles framework and the behavior change techniques' taxonomy, and representing any theme outside those frameworks.
Results: Participants expressed generally positive attitudes toward mHealth tools, favoring intuitive, user-friendly designs that are minimally time-demanding. However, significant barriers also emerged, such as low digital literacy and concerns about technology dependence. Key design preferences (persuasive design principles) and psychological techniques (behavior change techniques) were deemed beneficial, with preferred features such as tailored and meaningful goal-setting, self-monitoring, positive feedback (eg, congratulating messages after achieving a goal; social rewards), and a moderated use of notifications and prompts. Participants also stressed the importance of age-appropriate recommendations (eg, suggested diets for their age and characteristics) and design (eg, accessible, easy-to-use interfaces and human-like communication). Additionally, some preferences appeared to be culturally grounded (eg, rejection of anglicisms and the desire for locally relevant content, such as suggested activities specific to Madrid). Social support mechanisms, such as group activities and peer interactions through mHealth, were seen as critical for fostering motivation and engagement.
Conclusions: mHealth interventions for this population should offer accessible and easy-to-use interfaces along with initial tutorials, facilitating an easy onboarding to overcome low digital literacy, thereby enhancing both usability and initial adoption. Furthermore, by providing meaningful, tailored content (eg, personalized diets and goals) and social features that foster peer connection (eg, user chats or organized activities), these tools may better support sustained engagement over time.
Background: Mobile visual acuity (VA) apps have emerged as valuable tools in both clinical and home settings, particularly in the context of expanding teleophthalmology. Despite the growing number of apps available to measure visual acuity, studies evaluating their overall quality, functionality, and clinical relevance are limited.
Objective: This study aimed to systematically evaluate the quality and features of mobile VA apps available on iOS and Android platforms using the clinically validated Mobile App Rating Scale (MARS).
Methods: A comprehensive search of the Google Play Store and Apple App Store was conducted between January 2024 and March 2024 using standardized search terms. Eligible apps included free, English-language VA testing tools not requiring external devices. App characteristics and features were extracted. Each app was independently evaluated by 2 trained reviewers using MARS, which rates engagement, functionality, aesthetics, information quality, and subjective quality on a 5-point scale.
Results: Of the 725 apps initially identified, 44 met the inclusion criteria, with 23 from the Google Play Store and 21 from the Apple App Store. The most common VA test optotypes used were Tumbling E (n=21; 48%), Snellen Chart (18/44; 41%), and Landolt C (n=14; 32%). Common supplemental features included color vision testing (n=20; 46%), astigmatism tests (n=13; 30%), Amsler grid (n=13; 30%), and contrast testing (n=12; 28%). The average MARS scores were comparable across platforms: 3.04 (SD 0.80) for Android and 3.02 (SD 0.84) for iOS. Functionality received the highest ratings (mean 3.65, SD 0.75 for Android; mean 3.71, SD 0.82 for iOS), while subjective quality received the lowest (mean 2.09, SD 1.01 for Android; mean 2.21, SD 1.01 for iOS). Few apps had undergone clinical validation. Only Apple App Store apps demonstrated significant correlations between MARS scores and app store star ratings.
Conclusions: VA apps exhibited considerable heterogeneity in quality, functionality, and clinical use. Total mean MARS scores were similar between the Google Play Store and the Apple App Store, suggesting that neither platform consistently offers superior app quality. While many apps are technically sound, low subjective-quality scores and a lack of clinical validation limit their current use in professional practice. These findings underscore the need for more rigorous app development and validation standards to improve their relevance and reliability in teleophthalmology.
Background: Approximately 1 out of 5 pregnant women develops depression. Internet-based cognitive behavioral therapy (iCBT) is an effective way to treat not only depression but also mild depressive symptoms or subthreshold depression. While numerous iCBT programs have been developed and tested through randomized controlled trials for various mental health conditions and specific populations, research on their effectiveness and application in the real world remains limited.
Objective: This study aimed to examine the effectiveness of a previously developed iCBT program implemented in an existing app for improving depressive symptoms among pregnant women in a real-world setting.
Methods: The previously developed iCBT program for preventing perinatal depression was already implemented in an existing app called Luna Luna Baby by MTI Ltd. The app aims to provide information to pregnant women about pregnancy and babies, and potential users can download it from the Japanese version of the Apple App Store or Google Play Store without any fee. The program does not require any additional fees. The log data stored on the app identified iCBT program users and nonusers, allowing us to conduct this retrospective cohort study. Data from September 2022 to September 2024 were extracted from the app after anonymous processing. The primary outcome was the score on the self-reported Edinburgh Postnatal Depression Scale (EPDS), which participants answer by themselves on the app. The exposure group was defined as completers of all 6 modules of the iCBT program. The nonexposure group was defined as users who did not use any module of the program and matched the baseline characteristics of the exposure group. The change in EPDS score before and after using the program was compared using effect sizes, and repeated 2-way ANOVA was conducted to test the difference between the exposure and nonexposure groups.
Results: Data from 119 women who completed the iCBT program and 448 pair-matched controls were selected. The average EPDS scores at baseline were 7.24 (SD 5.30) in the exposure group and 7.25 (SD 5.18) in the nonexposure group. After using the iCBT program, the group mean EPDS scores changed by -0.69 (SD 4.92) and +0.99 (SD 5.56) over time in the exposure and nonexposure groups, respectively (Cohen d=0.31, 95% CI 0.11-0.51). The repeated 2-way ANOVA showed statistical significance in the interaction terms between the groups and the measurement time points (P=.04).
Conclusions: The previously developed iCBT program showed a significant effect with a modest effect size on decreasing depressive symptoms among pregnant women in a real-world setting. Future research should attempt to minimize dropouts and increase participation in the program.
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