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Medication adherence is crucial for managing chronic conditions. Mobile apps may have the potential, through a wide variety of features, to support and improve medication adherence. The purpose of this systematic review was to evaluate the effectiveness of mobile apps in promoting medication adherence for patients managing chronic conditions. MEDLINE (Ovid), Embase (Ovid), and Cochrane Central Register of Controlled Trials databases were searched for randomized controlled trials (RCTs) evaluating the effectiveness of mobile app interventions in improving medication adherence in patients with chronic conditions. Study design and app features were qualitatively described. Meta-analyses were performed on studies, grouped by medication adherence measurement scale, on the mean differences in medication adherence scores between intervention and control groups, using random effects models. If baseline medication adherence data were available, a difference in differences meta-analysis with a random effects model was also conducted. Bias assessment was conducted using the Cochrane Risk of Bias tool. This review included 14 RCTs published between 2014 and 2022, with sample sizes between 57 and 412 participants and the length of interventions ranging from 30 days to 12 months. A range of patient populations was evaluated, including those with Parkinson disease, coronary heart disease, psoriasis, and hypertension, with hypertension being the most common condition. All 14 studies reported that app interventions improved medication adherence, and 10 RCTs demonstrated statistically significant improvement in medication adherence. Three separate sets of meta-analyses, categorized by the medication adherence measurement scales, were conducted on the mean difference between medication adherence scores between the control and intervention groups: the 8-item Morisky Medication Adherence Scale (MMAS-8; 0.57, 95% CI 0.33-0.80; P<.001, I2=0%, τ2=0, P value for heterogeneity test=.94), 4-item Morisky Medication Adherence Scale (MMAS-4; 0.15, 95% CI -0.12 to 0.42; P=.28, I2=0%, τ2=0, P value for heterogeneity test=.54) and a percentage medication adherence scale (18.85, 95% CI 2.17-35.53; P=.03, I2=63%, τ2=94.89, P value for heterogeneity test=.10). Additionally, with available baseline adherence scores, difference in differences meta-analyses were conducted for studies using the MMAS-8 scale (0.38, 95% CI 0.15-0.62; P=.001, I2=0%, τ2=0, P value for heterogeneity test=.51) and for studies using the MMAS-4 scale (0.55, 95% CI 0.17 to 0.93; P=.005, I2=33%, τ2=0.03, P value for heterogeneity test=.22). The meta-analysis of the MMAS-8 scale, percentage medication adherence scale, and both difference-in-differences meta-analyses demonstrated that app-based interventions improved medication adherence. From the studies included in this review, mobile apps, designed for a wide variety of chronic conditions with a range of features, were shown to improve medication adherence and may be a tool to successfully manage chronic conditions.

Knee osteoarthritis (knee OA) is a heterogeneous condition characterized by chronic pain, stiffness, and fatigue that fluctuate rapidly over time. Traditional clinical assessments provide only static diagnoses of disease severity, failing to capture the dynamic, day-to-day symptom variability that impacts patient quality of life. While wearable technologies offer the potential for continuous, high-frequency monitoring, previous reviews have examined general technological interventions for knee OA management, yet they lack a specific synthesis of technologies for symptom monitoring. This scoping review aims to synthesize current research on sensor technologies used for the continuous monitoring of knee OA symptoms in free-living or simulated daily environments. Specifically, the review seeks to: (1) map sensor modalities to specific symptom domains (biomechanical, physiological, and behavioral); (2) evaluate the alignment between objective sensor metrics and patient-reported outcome measures (PROMs); and (3) identify gaps in current monitoring paradigms. A systematic literature search was conducted across PubMed, Embase, Web of Science, and IEEE Xplore. The review followed the PRISMA-ScR guidelines. Eligibility criteria included studies involving participants with knee OA, utilizing wearable or portable sensors capable of continuous monitoring (e.g., Inertial measurement units(IMUs), electrocardiography (ECG), and assessing clinical symptoms (e.g., pain, fatigue, stiffness). Studies relying solely on stationary laboratory equipment (e.g., force plates) without a portable component were excluded to ensure relevance to real-world applicability. Data were extracted regarding sensor types, sampling frequencies, monitored symptoms, and the statistical association between objective features and subjective symptom severity (key findings). A total of 16 studies met the inclusion criteria. The summary constructed from the results revealed a distinct technological saturation: the majority of studies (n=6) utilized IMUs to quantify biomechanical deficits (e.g., gait asymmetry, range of motion), which showed robust correlations with functional limitations. In contrast, there was a notable scarcity of research utilizing physiological sensors (e.g., electrocardiography, bioimpedance) to monitor systemic symptoms. Crucially, findings highlighted a significant discrepancy between subjective and objective data, particularly in sleep monitoring, where poor self-reported sleep quality predicted pain exacerbations despite stable objective actigraphy metrics. Furthermore, most systems operated as passive data loggers, with a lack of integration into active feedback loops. Unlike previous reviews focused solely on biomechanics, this study innovatively maps the use of sensors across a multidimensional symptom spectrum, revealing a critical gap in the monitoring of fatigue and physiological stress. The findings suggest that current sensor applications are limited by a lack of integration with subjective patient experiences. Real-world implementation requires a hybrid monitoring paradigm that combines the ecological validity of wearable sensors with the clinical relevance of patient-reported outcomes. This approach paves the way for Digital Phenotyping and active feedback systems, offering a personalized strategy for managing the complex symptom burden of knee OA.

Pulmonary rehabilitation (PR) is a cornerstone of chronic obstructive pulmonary disease (COPD) management; however, access to traditional center-based PR (CBPR) remains limited. Digital and remote models, collectively termed pulmonary telerehabilitation (Tele-PR), have increasingly been used, but their heterogeneity in technology use, supervision, and interaction mode may influence effectiveness and sustainability. This systematic review and meta-analysis aimed to compare the effectiveness and adherence of Tele-PR with those of CBPR in adults with COPD while systematically evaluating the impacts of supervision intensity and delivery models on key clinical outcomes. This review followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 and PRISMA-S (Preferred Reporting Items for Systematic reviews and Meta-Analyses literature search extension) guidelines. PubMed, Embase, the Cochrane Library, and the Web of Science were searched from inception to December 10, 2025, to identify randomized controlled trials comparing Tele-PR or home-based PR (HBPR) with CBPR in adults with COPD. Random effects meta-analyses were conducted using the Hartung-Knapp-Sidik-Jonkman method. Between-study heterogeneity was assessed using τ², I², and 95% prediction intervals. Risk of bias was evaluated with the Cochrane Risk of Bias 2 tool, and certainty of evidence was graded using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) approach. Seventeen randomized controlled trials involving 1658 participants were included. After intervention, Tele-PR and CBPR showed comparable average effects on exercise capacity by 6-minute walk distance (k=9; n=950, 57.3%; mean difference -5.37 m, 95% CI -15.68 to 4.95; P=.26; τ²=103.97; I²=28.2%; 95% prediction intervals=-32.73 to 22.27). Although pooled effects were not statistically significant, substantial heterogeneity was observed across remote delivery models. Subgroup analyses linked digitally supported, synchronously supervised Tele-PR to less between-study variance across several outcomes, indicating greater consistency in treatment effects across different settings while revealing that low-technology HBPR yielded more variable outcomes, particularly in symptom burden. At long-term follow-up (≥6 mo), between-group differences in functional and symptom outcomes diminished, and short-term gains in exercise capacity did not consistently translate into increased daily physical activity. Certainty of evidence ranged from moderate to very low, mainly downgraded for performance bias, inconsistency across intervention models, and imprecision. Tele-PR may achieve short-term clinical outcomes comparable to CBPR. Distinct from prior reviews, we stratified remote programs by delivery models and supervision, identifying digitally supported Tele-PR and low-technology HBPR as 2 clinically distinct paradigms with differing consistency of effects. We further propose a structured \"supervision gradient\" to interpret model-dependent variability in effects across Tele-PR approaches, providing a context-sensitive framework for evidence-informed, model-specific implementation. Future remote rehabilitation should integrate real-time professional supervision and long-term behavioral maintenance to sustain benefits. Tele-PR may be particularly valuable for expanding PR access, while CBPR remains essential for patients requiring close in-person supervision or complex multidisciplinary care.

Pulmonary rehabilitation (PR) is a cornerstone for the management of chronic obstructive pulmonary disease (COPD), yet global uptake remains low due to geographic and resource barriers. Digital health technologies, specifically smartphone apps, offer a promising platform for delivering accessible home-based PR. In addition, music-assisted interventions not only offer unique physiological and psychological benefits but may also serve as an innovative approach to enhancing patient engagement and improving the effectiveness of rehabilitation in home settings. This study aimed to evaluate the effectiveness of a smartphone app-based, music-facilitated multicomponent PR program (integrating rhythm-guided walking [RW] and singing) for improving exercise capacity and other clinical outcomes in patients with COPD compared with usual care (UC). This 3-arm, parallel-group, multicenter randomized controlled trial included 70 participants in China. Participants were randomized into a multimodule training (MT) group, which included a multicomponent PR program integrating RW and singing training (n=25); a RW group, which included RW training (n=23); or a UC group (n=22). The MT and RW groups received 12-week asynchronous home-based training via a smartphone app, and all arms received structured patient education. The primary outcome was the distance achieved in the incremental shuttle walking test (ISWT) at 12 weeks. The secondary outcomes included dyspnea, quality of life, and pulmonary function. The modified intention-to-treat principle was used to analyze the 70 study patients. At 12 weeks, the ISWT distance was significantly greater in the MT group than in the UC group (mean difference [MD] 56.35 m, 95% CI 6.66-106.04 m; P=.03; Cohen d=0.30). Significant improvements were observed in the MT group compared with the UC group in the modified Medical Research Council dyspnea scale (mMRC) score (MD -0.44, 95% CI -0.80 to -0.08; P=.02), COPD Assessment Test score (MD -3.23, 95% CI -6.18 to -0.29; P=.03), Hospital Anxiety and Depression Scale-anxiety subscale score (MD -2.31, 95% CI -3.99 to -0.63; P=.008), and inspiratory capacity (MD 15.98% predicted, 95% CI 4.76 to 27.21; P=.01). However, no significant differences were found between the RW and UC groups in primary or secondary outcomes. Compared with RW, MT was significantly better at decreasing the mMRC score (P=.03). The findings of this study demonstrate that our smartphone app-based music-facilitated multicomponent PR program (including tempo-guided walking and singing) caused clinically meaningful improvements in exercise capacity among patients with COPD compared to UC. Moreover, secondary outcomes, including dyspnea, quality of life, psychological status, and inspiratory capacity, showed better improvements with MT than with UC.

Digital health technology (DHT) plays an increasingly vital role in managing chronic diseases by enabling patients to actively manage their health. These tools have been shown to improve self-management and adherence to medical advice. However, for DHT to be fully effective, patients with chronic conditions must be digitally literate. The eHealth Literacy Scale (eHEALS), an 8‑item tool with scores ranging from 8 to 40, was developed to assess individuals' perceived ability to find, evaluate, and apply digital health information. Assessing patients' digital health literacy (DHL) and understanding the factors influencing it are essential for improving the accessibility and usability of health resources. This study aimed to assess DHL in patients with diabetes mellitus (DM), hypertension, and rheumatoid arthritis (RA) through a systematic review and meta‑analysis using eHEALS. We sought to determine average DHL scores, examine demographic and socioeconomic factors influencing DHL, and explore its impact on disease management to inform future strategies for enhancing DHL and improving chronic disease outcomes. Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we conducted a systematic review across 7 databases (PubMed, SCOPUS, Embase, ERIC, CINAHL, Library Literature and Information Science Index, and Google Scholar) from inception to August 14, 2022, with an updated search in October 2024. Eligible studies included adults (≥18 years) with DM, hypertension, or RA who reported DHL data using eHEALS (8-40) and were original research published in English. Exclusion criteria included studies involving participants younger than 18 years, reviews, meta‑analyses, studies not addressing the target diseases, or non‑English publications. Study quality was evaluated using the Newcastle‑Ottawa Scale (NOS). Eight studies involving 2527 participants were included. The pooled mean eHEALS score was 27.03 (95% CI 25.08-28.98), indicating high overall DHL. Stratified by disease, scores were higher for DM (27.79) and hypertension (28.48) but lower for RA (24.74). Quality assessment indicated a high standard of included studies. Factors influencing DHL included age, education, employment, and perception of the internet as a health resource. Due to the limited number of studies, meta‑regression analysis could not be performed. DHL is critical for individuals with chronic conditions, empowering them to make informed decisions and manage their health effectively. However, the scarcity of studies limits comprehensive analysis of DHL determinants. While the internet offers abundant health information, unequal DHL and health skills remain barriers. More inclusive research is needed to fully understand DHL's impact on health outcomes and mitigate disparities, ensuring equitable access to digital health resources and improving disease management.

With the widespread use of the internet and mobile devices, eHealth literacy promotion is critical for medical equity. Mobile health (mHealth) serves as a pivotal tool for enhancing eHealth literacy by providing accessible, interactive platforms for health information engagement. However, the evidence regarding the effectiveness of mHealth interventions on eHealth literacy among patients with chronic diseases remains inconclusive. This study aimed to evaluate the effectiveness of mHealth interventions on eHealth literacy among patients with chronic diseases based on randomized controlled trials (RCTs) and summarize supportive evidence from quasi-experimental and qualitative studies. A comprehensive search strategy was developed, and 8 electronic databases were systematically searched for studies published up to February 12, 2026. Patients with chronic diseases were included based on predefined inclusion criteria. The Cochrane risk of bias 2 tool for RCTs and the ROBINS-I tool for quasi-experimental studies were used to assess the risk of bias. Given the anticipated substantial heterogeneity among the studies included, we used a random-effects model based on the Hartung-Knapp-Sidik-Jonkman method to pool effect sizes. A narrative and quantitative synthesis of the findings was provided where appropriate. A total of 15 studies were included in this review, including 6 RCTs, 5 quasi-experimental studies, and 4 qualitative studies, involving a total of 2884 patients with chronic diseases. Meta-analyses of RCTs suggested that mHealth interventions could improve eHealth literacy, with a pooled mean effect size of standardized mean difference (SMD)=1. 19 (95% CI 0.14-2.23; P=.03; I²=97.75%; PI [prediction interval]=-2.68 to 5.05). Subgroup analyses by intervention targets showed that interventions on targets with specific disease produced larger mean effects (SMD=1.61; 95% CI 0.16-3.06; PI=-5.40 to 8.63), while interventions targeting the population with general chronic diseases produced smaller effects (SMD=0.36; 95% CI 0-0. 73; PI=-0. 21 to 0. 94). Analysis by intervention duration subgroup showed that the combined effect of studies with intervention duration <3 months was statistically significant (SMD=0.61; 95% CI 0.09-1.13; I²=88.04%; PI=-5.72 to 6.95); while the combined effect of studies with intervention duration ≥3 months was not statistically significant. Taking into account bias and the risk of GRADE (Grading of Recommendations, Assessment, Development, and Evaluation), the certainty of RCT evidence was moderate, and the certainty of quasi-experimental evidence was low. mHealth interventions could improve eHealth literacy among patients with chronic diseases on average. By using prediction intervals, this study reveals that the effectiveness of mHealth interventions is highly context-dependent and closely linked to implementation factors. Advancing beyond prior work, this study centers on eHealth literacy as a core outcome and integrates multiple types of evidence. Meanwhile, this finding emphasizes the need for evidence-based intervention programs and more rigorous implementation of intervention designs in future research.

About 1 in 2 patients with knee osteoarthritis (OA) receives a referral or recommendation for exercise. Digital health applications could counteract this undersupply. We aimed to investigate the effectiveness of a 12-week self-directed mobile health exercise intervention (re.flex) when used in addition to usual care compared to a control group receiving usual care only on pain reduction and improvement in physical function in patients with knee OA. This monocentric, 2-arm, randomized controlled parallel-group trial included patients from Germany with moderate to severe knee OA. Participants were mainly recruited via newspapers. Randomization was 1:1 into an intervention group (re.flex+usual care) and a control group (usual care) using computer-generated blocks. Participants were unmasked to group assignment. The re.flex group conducted a 12-week self-directed app-based and sensor-assisted exercise program with 3 sessions per week in addition to usual care. Primary outcomes were OA-specific knee pain and physical function (using the subscales pain and activities in daily living of the Knee Osteoarthritis Outcome Score, 0-100) at 3 months. Secondary outcomes included adherence and safety. Multiple imputation was used to account for missing data. Intervention effects were calculated using a baseline-adjusted analyses of covariance (ANCOVA). Bonferroni correction with an alpha level of .025 was applied. Between January 25, 2023, and August 11, 2023, a total of 195 participants were enrolled. Of them, 98 participants were allocated to re.flex, and 97 participants to usual care. The primary analysis included 194 participants. The mean age was 61.9 (SD 7.7) years, and the majority were female (132/194, 68%). Pain reduction was significantly larger in re.flex than in usual care, with an adjusted mean difference between study groups of 4.8 (95% CI 0.7-8.9; P=.02; Cohen d=0.35) points. Improvement in physical function was not statistically significant (beta coefficient [β]=3.9 points, 95% CI 0.0-7.9, P=.049). A total of 12 adverse events were linked to re.flex, none of which were serious. Participants adhered to 77% (2705/3528) of all scheduled exercise sessions. The self-directed sensor-based mobile health exercise intervention re.flex demonstrates superiority over usual care for pain reduction and justifies this kind of intervention as an alternative exercise delivery mode for patients with knee OA.

Despite the growing amount of patients who underwent coronary artery bypass grafting (CABG) in low- and middle-income countries like China, their glucose control was suboptimal, likely due to poor adherence to healthy lifestyles and preventive medications. Mobile health tools facilitating secondary prevention seem promising, but evidence focusing on this high-risk population is scarce. This study aimed to evaluate the significance of mobile health tools in long-term glycemic management for post-CABG patients with comorbid diabetes mellitus. GUIDEME (glycemic control using mini program-based intervention in patients with diabetes undergoing coronary artery bypass to promote self-management) is a multicenter, open-label, closed-user group, randomized controlled trial, in which 1066 patients with diabetes who had recently undergone CABG were enrolled and allocated into 2 groups. Patients in the control group received conventional health education before discharge, whereas those in the intervention group additionally received automatic delivery of bite-sized health education and medication reminders through a smartphone app during the 6 months after discharge. The primary end point was a change in glycosylated hemoglobin (HbA1c) from baseline to 6 months. Among the 1066 eligible participants enrolled, a total of 1038 (97.4%) had completed the follow-up, while 1000 (93.8%) had 6-month HbA1c results available. Although only 79 (14.9%) patients in the intervention group were defined as active users, a greater reduction of HbA1c in the intervention group was observed (adjusted between-group mean difference -0.13, 95% CI -0.25 to -0.01; P=.04). The intervention group also had a high proportion of good medication adherence (96.1% vs 93.2%, P=.04). There was no difference between the 2 groups regarding the secondary end points. Health education and medication reminders based on smartphone app achieved a statistically significant but modest between-group difference in HbA1c, the clinical relevance of which remains uncertain.

Digital health interventions, especially mobile apps, have become instrumental in helping women at risk of polycystic ovary syndrome (PCOS), increasing their understanding of the condition, improving self-care, and fostering empowerment. However, their rapid proliferation has brought about significant challenges regarding quality assessment and evidence-based determination. Therefore, establishing reliable quality assessment methods is essential to assist patients with PCOS in identifying effective and trustworthy mobile health tools. This study was designed to assess the content and quality of mobile apps developed for patients with PCOS using the Mobile App Rating Scale (MARS) to provide insights into their strengths, limitations, and areas needing improvement. In this descriptive-analytical study conducted in June 2024, a comprehensive search was performed to identify English and Persian mobile apps related to PCOS through the Café Bazaar and Google Play Store platforms, using both direct search methods and auxiliary tools such as AppAgg and AppBrain. Two trained reviewers (AR and NN) independently reviewed the apps using the MARS tool. The interrater reliability was measured using the intraclass correlation coefficient test. The quality of each app was scored across 4 dimensions: engagement, functionality, aesthetics, and information quality. Of the initial 199 apps identified, 15 met the inclusion criteria after screening and updates. The interrater agreement rate was 85%, which is considered acceptable. The apps' overall quality was sufficient, as assessed using the MARS, with a mean score of 3.6 (SD 0.52) of 5. Functionality and aesthetics emerged as the highest-scoring dimensions, highlighting user-friendliness and visual appeal (n=10). In contrast, engagement following information quality received the lowest average score, indicating limited interactivity and gaps in providing evidence-based information. The Ask PCOS app achieved the highest overall score, performing exceptionally well in subjective quality (4.75) and app-specific quality (4.33), reflecting its strong capacity to positively impact users' knowledge, attitudes, and behaviors related to PCOS. Uvi Health and Ask PCOS scored highest in engagement (4.2), while PCOS & PCOD Diet & Remedies led in functionality (5), and Uvi Health topped aesthetics (5). The findings revealed that even though many available PCOS-related apps demonstrate strengths in technical performance and design, critical limitations persist regarding user engagement and the credibility of the information provided. The predominance of commercially affiliated apps without academic or clinical oversight was identified as a key contributing factor to these shortcomings. These results underscore the need for future app development to incorporate more user-engaging features, reliable evidence-based content, and personalization strategies to enhance user engagement and support effective PCOS self-management. Addressing these limitations and leveraging the capabilities of existing mobile devices are essential steps toward improving the overall quality and impact of mobile health interventions for individuals with PCOS.

The incidence of end-stage renal disease continues to rise annually, with dialysis currently serving as the primary replacement therapy. The effectiveness of dialysis treatment and patients' quality of life are highly dependent on their self-management. Mobile health (mHealth), which provides real-time medical support through portable devices, has become an essential tool for assisting patients undergoing dialysis in optimizing their self-management. This study aimed to systematically explore the core elements of self-management in patients undergoing dialysis and clarify the primary applications of mHealth, including types of mHealth, relevant theories and models, mHealth-based interventions, and evaluation indicators. This study was guided by Arksey and O'Malley's methodology, PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews), and PRISMA-S (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Literature Search Extension). Databases, such as PubMed, Embase, CINAHL, PsycINFO, and Web of Science, were systematically searched from January 2010 until October 2025. The participants included in this study were patients undergoing dialysis, and the study design must incorporate quantitative research. Published protocols, reviews, editorials, conference papers, books, and non-English studies were excluded. The Mixed Methods Appraisal Tool was used to evaluate the quality of the included studies. Quantitative studies were extracted, mapped, and summarized. The results were collated and synthesized using a structured spreadsheet. Out of 1483 relevant studies, this scoping review ultimately selected 34 studies involving 2068 patients undergoing dialysis. Self-management among patients undergoing dialysis in this study included 6 major areas, including self-monitoring, diet and fluid management, medication management, disease-related knowledge, exercise management, and psychological management. Most studies used a single app (n=22) for management of patients undergoing dialysis, followed by 2 or more online interventions (n=6) and a remote patient monitoring system (n=3). The mHealth-based interventions in this study focused on self-monitoring, dietary and fluid management, and medication management. The transtheoretical model and stages of change (n=5), self-efficacy theory (n=4), and social cognitive theory (n=4) were the most commonly used theories. Among the evaluation indicators, interdialytic weight gain (n=12), serum potassium (n=14), serum phosphorus (n=20), and serum albumin (n=14) were the most commonly used objective indicators. Subjective indicators were assessed using scales, primarily covering adherence (n=17), self-efficacy (n=14), quality of life (n=12), knowledge (n=9), and diet and nutrition (n=9). Although mHealth holds promise for improving self-management and outcomes among patients undergoing dialysis, there remains significant room for advancement. Future research in this field should focus on enhancing adaptive software development, deeply integrating artificial intelligence technologies, addressing the needs of special populations, and establishing a standardized self-management evaluation system. Our findings not only provide a theoretical framework for optimizing clinical management strategies for patients undergoing dialysis but also offer targeted guidance and practical insights for the subsequent development of apps.