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Telemedicine and mobile health (mHealth) apps have emerged as powerful tools in health care, offering convenient access to services and empowering participants in managing their health. Among populations with chronic and progressive disease such as multiple sclerosis (MS), mHealth apps hold promise for enhancing self-management and care. To be used in clinical practice, the validity and usability of mHealth tools should be tested. The most commonly used method for assessing the usability of electronic technologies are questionnaires. This study aimed to translate and validate the English version of the mHealth App Usability Questionnaire into Italian (ita-MAUQ) in a sample of people with MS. The 18-item mHealth App Usability Questionnaire was forward- and back-translated from English into Italian by an expert panel, following scientific guidelines for translation and cross-cultural adaptation. The ita-MAUQ (patient version for stand-alone apps) comprises 3 subscales, which are ease of use, interface and satisfaction, and usefulness. After interacting with DIGICOG-MS (Digital Assessment of Cognitive Impairment in Multiple Sclerosis), a novel mHealth app for cognitive self-assessment in MS, people completed the ita-MAUQ and the System Usability Scale, included to test construct validity of the translated questionnaire. Confirmatory factor analysis, internal consistency, test-retest reliability, and construct validity were assessed. Known-groups validity was examined based on disability levels as indicated by the Expanded Disability Status Scale (EDSS) score and gender. In total, 116 people with MS (female n=74; mean age 47.2, SD 14 years; mean EDSS 3.32, SD 1.72) were enrolled. The ita-MAUQ demonstrated acceptable model fit, good internal consistency (Cronbach α=0.92), and moderate test-retest reliability (intraclass coefficient correlation 0.84). Spearman coefficients revealed significant correlations between the ita-MAUQ total score; the ease of use (5 items), interface and satisfaction (7 items), and usefulness subscales; and the System Usability Scale (all P values <.05). Known-group analysis found no difference between people with MS with mild and moderate EDSS (all P values >.05), suggesting that ambulation ability, mainly detected by the EDSS, did not affect the ita-MAUQ scores. Interestingly, a statistical difference between female and male participants concerning the ease of use ita-MAUQ subscale was found (P=.02). The ita-MAUQ demonstrated high reliability and validity and it might be used to evaluate the usability, utility, and acceptability of mHealth apps in people with MS.

The Mobile Application Rating Scale (MARS) provides a reliable method to assess the quality of mobile health (mHealth) apps. However, training and expertise in mHealth and the relevant health field is required to administer it. This study describes the development and reliability testing of an end-user version of the MARS (uMARS). The MARS was simplified and piloted with 13 young people to create the uMARS. The internal consistency and test-retest reliability of the uMARS was then examined in a second sample of 164 young people participating in a randomized controlled trial of a mHealth app. App ratings were collected using the uMARS at 1-, 3,- and 6-month follow up. The uMARS had excellent internal consistency (alpha = .90), with high individual alphas for all subscales. The total score and subscales had good test-retest reliability over both 1-2 months and 3 months. The uMARS is a simple tool that can be reliably used by end-users to assess the quality of mHealth apps.

Background: The System Usability Scale (SUS) is a widely used scale that has been used to quantify the usability of many software and hardware products. However, the SUS was not specifically designed to evaluate mobile apps, or in particular digital health apps (DHAs). Objective: The aim of this study was to examine whether the widely used SUS distribution for benchmarking (mean 68, SD 12.5) can be used to reliably assess the usability of DHAs. Methods: A search of the literature was performed using the ACM Digital Library, IEEE Xplore, CORE, PubMed, and Google Scholar databases to identify SUS scores related to the usability of DHAs for meta-analysis. This study included papers that published the SUS scores of the evaluated DHAs from 2011 to 2021 to get a 10-year representation. In total, 117 SUS scores for 114 DHAs were identified. R Studio and the R programming language were used to model the DHA SUS distribution, with a 1-sample, 2-tailed t test used to compare this distribution with the standard SUS distribution. Results: The mean SUS score when all the collected apps were included was 76.64 (SD 15.12); however, this distribution exhibited asymmetrical skewness (–0.52) and was not normally distributed according to Shapiro-Wilk test (P=.002). The mean SUS score for “physical activity” apps was 83.28 (SD 12.39) and drove the skewness. Hence, the mean SUS score for all collected apps excluding “physical activity” apps was 68.05 (SD 14.05). A 1-sample, 2-tailed t test indicated that this health app SUS distribution was not statistically significantly different from the standard SUS distribution (P=.98). Conclusions: This study concludes that the SUS and the widely accepted benchmark of a mean SUS score of 68 (SD 12.5) are suitable for evaluating the usability of DHAs. We speculate as to why physical activity apps received higher SUS scores than expected. A template for reporting mean SUS scores to facilitate meta-analysis is proposed, together with future work that could be done to further examine the SUS benchmark scores for DHAs.

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.

Mobile health (mHealth) interventions can produce both intended and unintended effects. Examining these unintended effects helps create a more complete and objective understanding of mHealth interventions and can reduce potential harm to participants. Existing studies on the unintended effects, which were published several years ago, tend to have either a general focus on health IT or a specific focus on health care providers, thereby excluding other key stakeholders (eg, patients and community health workers). Additionally, these studies did not systematically outline the causes of the unintended effects or strategies for their prevention. To address this gap, this systematic review, guided by the ecological framework, aims to systematically identify the unintended effects of mHealth interventions, create a typology for them, investigate the reasons for their occurrence, describe how they were detected, and propose ways to prevent or lessen them. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a systematic review was performed to examine the unintended effects of health interventions that use mobile technology. A total of 15 papers were included in the review. An ecological typology of mHealth intervention unintended effects (mHUE) was developed, which includes 26 distinct effects (eg, silencing and boomerang). The majority of these unintended effects (n=20) occur at the individual level and span physical or behavioral (n=7), psychological (n=8), cognitive (n=4), and financial (n=1) domains. Three effects occur at the interpersonal level and another 3 at the community or institutional level. Most of the identified effects (n=22) were negative. Potential causes for these effects include the improper use of mHealth technology, poorly designed interventions, the application of unsuitable intervention mechanisms, or a misalignment between the intended outcomes and the sociocultural context. Strategies and recommendations (eg, considering the context such as cultural norms) were suggested to help prevent or reduce the unintended effects. The unintended effects detailed in the mHUE typology were heterogenous and context-dependent. These effects can influence individuals across different domains and also affect unintended people within the ecological system. As most of the unintended effects are negative, if they are not monitored, mHealth interventions designed to empower participants could paradoxically disempower them (eg, decreasing self-efficacy for disease management, undermining patient control, and engagement). The mHUE typology, together with the proposed recommendations and strategies, can be used as a guide to enhance the planning, design, implementation, and postimplementation evaluation on mHealth interventions. Future research should concentrate on understanding the specific mechanisms behind these unintended effects.

Globally, the use of mobile health (mHealth) apps or interventions has increased. Robust synthesis of existing systematic reviews on mHealth apps may offer useful insights to guide maternal health clinicians and policy makers. This systematic review aims to assess the effectiveness or impact of mHealth apps on maternal health care delivery globally. We systematically searched Scopus, Web of Science (Core Collection), MEDLINE or PubMed, CINAHL, and Cochrane Database of Systematic Reviews using a predeveloped search strategy. The quality of the reviews was independently assessed by 3 reviewers, while study selection was done by 2 independent raters. We presented a narrative synthesis of the findings, highlighting the specific mHealth apps, where they are implemented, and their effectiveness or outcomes toward various maternal conditions. A total of 2527 documents were retrieved, out of which 16 documents were included in the review. Most mHealth apps were implemented by sending SMS text messages with mobile phones. mHealth interventions were most effective in 5 areas: maternal anxiety and depression, diabetes in pregnancy, gestational weight management, maternal health care use, behavioral modification toward smoking cessation, and controlling substance use during pregnancy. We noted that mHealth interventions for maternal health care are skewed toward high-income countries (13/16, 81%). The effectiveness of mHealth apps for maternity health care has drawn attention in research and practice recently. The study showed that research on mHealth apps and their use dominate in high-income countries. As a result, it is imperative that low- and middle-income countries intensify their commitment to these apps for maternal health care, in terms of use and research. PROSPERO CRD42022365179; https://tinyurl.com/e5yxyx77.

Successful eHealth applications require careful assessment to ensure their ease of use, usefulness, and user satisfaction. Responsive web applications are eHealth tools that operate on any internet-enabled device across all browsers. Psychometrically valid assessment tools are essential for effectively evaluating these applications, yet no validated eHealth questionnaire exists for assessing their usability and user satisfaction in Mexico. The objective of this study is to adapt the mHealth App Usability Questionnaire (MAUQ) for responsive web application assessment in Mexico and validate adapted Mx-MAUQ content, construct validity, internal consistency, and its ability to distinguish between patient subgroups. We conducted a psychometric validation study of Mx-MAUQ with women aged 20 to 75 diagnosed with stage I-III breast cancer who had begun neoadjuvant or adjuvant treatment within the last six weeks and used the responsive \"OncoMama App\" for 1 month. The study excluded women with stage IV breast cancer, illiterate women, and those with blindness, cognitive disability, or severe depression. Participants were recruited from oncology services at 4 hospitals belonging to the Mexican Institute of Social Security between August 2023 and November 2024. The study involved translating and adapting the MAUQ while evaluating its content through expert panels and cognitive interviews with women. The Mx-MAUQ construct was assessed through exploratory factor analysis (EFA), internal consistency via Cronbach α, and Mx-MAUQ's capacity to distinguish between subgroups of patients with breast cancer using the Wilcoxon rank sum test. A total of 210 women participated, with 75.2% (n=158) aged 60 or younger and 64.3% (n=135) having high school education. The expert panel granted all Mx-MAUQ items a content validity index (CVI) above 0.7. Experts have found that the MAUQ questions are general enough to be relevant not only to mobile apps or specific medical conditions but also to a variety of digital platforms, including responsive web applications and different health conditions. The cognitive interviews revealed 3 unclear terms in the questionnaire; consequently, we defined \"application interface\" and changed \"social settings\" to \"social environments\" and \"manage my health\" to \"take care of my health.\" EFA identified 2 factors explaining 91.6% of the variance and retaining all items. The first factor, \"Ease of Use,\" consists of 9 items and has a Cronbach α of .94. The second factor, \"Satisfaction, Usefulness, and System Information Arrangement,\" includes 12 items and has a Cronbach α of .97. Women with higher education levels scored significantly higher for both factors, as well as the overall Mx-MAUQ score, than those with lower educational attainment. Mx-MAUQ showed satisfactory psychometric properties based on EFA, internal consistency, and discriminant analysis, making it a suitable tool for a comprehensive assessment of the usability of interactive web-based eHealth applications for women with breast cancer in Mexico.

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.

Despite the potential of digital adherence technologies to support patient-centered monitoring for tuberculosis (TB), there is limited research on incorporating indirect and direct adherence monitoring or assessing patients' experiences with these technologies. The TB Treatment Support Tools (TB-TST) includes a comprehensive mobile app for patients and health care providers and a direct adherence metabolite test to report and monitor adherence. This paper describes the iterative refinement process of the TB-TST intervention. To refine the TB-TST intervention, we used an iterative approach involving multiple embedded mixed methods studies guided by the Information Systems Research framework and Design Thinking Process. Embedded studies included a randomized controlled pilot study, interviews, usability testing, and surveys with patients and experts to inform ongoing refinements. The project consisted of interface evaluation, high-level system design, and iterative redesign. The TB-TST intervention was refined through 3 iterative phases. In Phase 1, based on feedback from pilot study participants and 4 experts in TB, improvements included an in-app discussion board, submission confirmations, and enhanced account recovery. Cultural adaptation was based on Hofstede's dimensions. Phase 2 involved 4 Directed Research Groups and 19 stakeholders to redesign user flows, simplify reporting, and transition the app to a progressive web app, improving device compatibility. Phase 3 included usability testing cycles with 48 participants (26 patients and 22 health care professionals), yielding high satisfaction scores: patient app Mobile Health App Usability Questionnaire, mean 5.96 (SD 0.46); provider mobile dashboard IT Usability Evaluation Scale scores ranged from 5.83 to 6.23 out of 7, and optimization of interface and dashboard. Refinements included larger icons, streamlined onboarding, symptom summary enhancements, and a new cohort-level adherence graph. These modifications improved navigation, usability, and remote monitoring for patients with TB and providers in preparation for a multisite clinical trial. Combining multiple methods guided by the Information Systems Research framework and elements of the Design Thinking Process can help researchers and developers leverage the strengths of mixed methods iterative designs to create highly personalized and effective digital health interventions.