BACKGROUND: Hypertension management apps (HMAs) can be effective in controlling blood pressure, but their actual impact is often suboptimal. Establishing a user satisfaction evaluation indicator system for HMAs can assist app developers in enhancing app design and functionality, while also helping users identify apps that best meet their needs. This approach aims to improve the overall effectiveness of app usage.
OBJECTIVE: This study aims to systematically collect data on HMAs and their user reviews in the United States and China. It analyzes app usage patterns and functional characteristics, identifies factors influencing user satisfaction from existing research, and develops a satisfaction evaluation indicator system to provide more accurate recommendations for improving user satisfaction.
METHODS: We conducted a descriptive statistical analysis to assess the development status of HMAs in both countries and applied the task-technology fit model to evaluate whether the app functionalities align with business needs. We separately summarized the factors influencing user satisfaction in both countries from previous research, utilized the analytic hierarchy process to develop an evaluation indicator system for HMA user satisfaction, and calculated satisfaction levels. Based on these findings, we propose improvements to enhance app functionality and user satisfaction.
RESULTS: In terms of current development status, there were fewer HMAs and user reviews in China compared with the United States. Regarding app functional availability, fewer than 5% (4/91) of the apps achieved a demand fulfillment rate exceeding 80% (8/10). Overall, user satisfaction in both countries was low.
CONCLUSIONS: In the United States, user satisfaction was lowest for advertising distribution, data synchronization, and reliability. By contrast, Chinese apps need improvements in cost efficiency and compatibility.

This study examines the factors influencing users\' intention to continue using mobile medical apps within the framework of the Unified Theory of Acceptance and Use of Technology (UTAUT) model. Through a combination of questionnaire surveys and interviews, the research finds that doctor-patient trust, Performance Expectancy (PE), social influence, and facilitating conditions significantly impact users\' intention to utilize mobile medical apps. Furthermore, the study reveals the moderating effect of doctor-patient trust on social influence, indicating an increased trust level during the epidemic, attributed to positive media coverage, complimentary medical services, and risk-sharing initiatives. These results provide valuable insights for the field of internet healthcare, COVID-19 response strategies, health information management, and the advancement of digital health technologies, spotlighting the pivotal roles of trust, PE, and social influence in fostering sustained engagement with mobile health apps.

OBJECTIVE: China\'s healthcare system is being burdened by the increasing prevalence of chronic diseases. Therefore, this study investigated the health service requirements of mobile health applications (mHealth apps) users in Hangzhou, China. This study aimed to propose suggestions and theoretical references to improve mHealth apps and promote their development, thereby meeting public medical and health needs and creating an efficient medical service system.
METHODS: We constructed a model of health service demands using a literature review, network survey, and semi-structured interviews. We analyzed the demand attributes using the Kano model and Better-Worse index and obtained the priority ranking of demands.
RESULTS: The results revealed 25 demand elements in four dimensions: must-be (M), one-dimensional (O), attractive (A), and indifferent (I) requirements. The findings suggest that mHealth app developers can optimize health services by categorizing and managing health services, focusing on middle-aged users, enhancing the professionalism of health service providers, and improving the feedback mechanism.
CONCLUSIONS: Studies on mHealth apps user demands, particularly on health service needs, remain scarce. This study employed a mixed-methods approach, integrating both qualitative and quantitative research techniques, to establish a priority ranking of user health service needs for mHealth apps. The study offers recommendations and theoretical references to optimize and improve mHealth app services.
CONCLUSIONS: Construct a better health service requirements model for mHealth app users.Obtain the prioritization of demand elements in the model.Propose some management suggestions to improve mHealth apps.

Mobile health applications (mHealth apps) have surged in popularity for their role in promoting knowledge exchange and providing emotional support among health consumers. However, this enhanced social connectivity via these apps has led to an escalation in privacy breaches, potentially hindering user engagement. Drawing upon the communication privacy management theory, this study proposes a moderated mediation model to link social privacy concerns to user engagement in mHealth apps. An online survey involving 1149 mHealth app users was conducted in China to empirically validate the proposed model. Results indicated that social privacy concerns were negatively related to user engagement in mHealth apps, and perceived privacy of the app partially mediated this relationship. Moreover, perceived control positively moderated the indirect relationship between social privacy concerns and user engagement via perceived privacy. Specifically, the negative impact of social privacy concerns on perceived privacy was mitigated for users who reported higher levels of perceived control, indicating that when users feel more in control of their personal data, they are less affected by concerns over social privacy. Theoretically, this study has the potential to help scholars understand user engagement in mHealth apps from a privacy management perspective. Practically, the results of this study could assist mobile app providers and health professionals in devising evidence-based strategies to enhance social engagement and promote effective and sustainable use of mHealth apps among health consumers.

BACKGROUND: Mobile technologies are increasingly being used in health care and public health practice for patient communication, monitoring, and education. Mobile health (mHealth) tools have also been used to facilitate adherence to chronic musculoskeletal pain (CMP) management, which is critical to achieving improved pain outcomes, quality of life, and cost-effective health care.
OBJECTIVE: The aim of this systematic review was to evaluate the 25-year trend of the literature on the adherence, usability, feasibility, and acceptability of mHealth interventions in CMP management among patients and health care providers.
METHODS: We searched the PubMed, Cochrane CENTRAL, MEDLINE, EMBASE, and Web of Science databases for studies assessing the role of mHealth in CMP management from January 1999 to December 2023. Outcomes of interest included the effect of mHealth interventions on patient adherence; pain-specific clinical outcomes after the intervention; and the usability, feasibility, and acceptability of mHealth tools and platforms in chronic pain management among target end users.
RESULTS: A total of 89 articles (26,429 participants) were included in the systematic review. Mobile apps were the most commonly used mHealth tools (78/89, 88%) among the included studies, followed by mobile app plus monitor (5/89, 6%), mobile app plus wearable sensor (4/89, 4%), and web-based mobile app plus monitor (1/89, 1%). Usability, feasibility, and acceptability or patient preferences for mHealth interventions were assessed in 26% (23/89) of the studies and observed to be generally high. Overall, 30% (27/89) of the studies used a randomized controlled trial (RCT), cohort, or pilot design to assess the impact of the mHealth intervention on patients\' adherence, with significant improvements (all P<.05) observed in 93% (25/27) of these studies. Significant (judged at P<.05) between-group differences were reported in 27 of the 29 (93%) RCTs that measured the effect of mHealth on CMP-specific clinical outcomes.
CONCLUSIONS: There is great potential for mHealth tools to better facilitate adherence to CMP management, and the current evidence supporting their effectiveness is generally high. Further research should focus on the cost-effectiveness of mHealth interventions for better incorporating these tools into health care practices.
BACKGROUND: International Prospective Register of Systematic Reviews (PROSPERO) CRD42024524634; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=524634.

BACKGROUND: Postpartum depression (PPD) has received widespread attention. Shenzhen has been running a large-scale program for PPD since 2013. The program requires mothers to self-assess when applying information technology to PPD screening beginning in 2021. The purpose of this study was to conduct a longitudinal analysis of the impact of mHealth apps on the health-seeking behaviors of PPD patients.
METHODS: Longitudinal data from districts in the Shenzhen Maternal and Child Health Management Information System (MCHMIS) for ten years was used in this study. Referral success rate (RSR, successful referrals to designated hospitals as a percentage of needed referrals) was used to assess health-seeking behavior. Trend χ2 tests were used to assess the overall trend of change after the implementation of mHealth in ten districts in Shenzhen. Interrupted Time Series Analysis (ITSA) was employed to assess the role of the mHealth app in changing patient health-seeking behaviors.
RESULTS: For the results of the trend χ2 tests, the ten districts of Shenzhen showed an upward trend. For the ITSA results, different results were shown between districts. Nanshan district, Longhua district, and Longgang district all demonstrated an upward trend in the first-year application of the mHealth app. Nanshan district and Longgang district both exhibited an upward trend in terms of sustained effects.
CONCLUSIONS: There is a difference in the performance of the mHealth app across the ten districts. The results show that the three districts with better health resource allocation, Nanshan, Longgang, and Longhua districts, demonstrated more significant mHealth app improvements. The mHealth app\'s functions, management systems, and health resource allocation may be potential factors in the results. This suggests that when leveraging mHealth applications, the first step is to focus on macro-level area resource allocation measures. Secondly, there should be effective process design and strict regulatory measures. Finally, there should also be appropriate means of publicity.

BACKGROUND: The paucity of evidence on longitudinal and consecutive recordings of physical activity (PA) and blood pressure (BP) under real-life conditions and their relationships is a vital research gap that needs to be addressed.
OBJECTIVE: This study aims to (1) investigate the short-term relationship between device-measured step volume and BP; (2) explore the joint effects of step volume and variability on BP; and (3) examine whether the association patterns between PA and BP varied across sex, hypertension status, and chronic condition status.
METHODS: This study used PA data of a prospective cohort of 3070 community-dwelling older adults derived from a mobile health app. Daily step counts, as a proxy of step volume, were derived from wearable devices between 2018 and 2022 and categorized into tertiles (low, medium, and high). Step variability was assessed using the SD of daily step counts. Consecutive daily step count recordings within 0 to 6 days preceding each BP measurement were analyzed. Generalized estimation equation models were used to estimate the individual and joint associations of daily step volume and variability with BP. Stratified analyses by sex, the presence of hypertension, and the number of morbidities were further conducted.
RESULTS: A total of 3070 participants, with a median age of 72 (IQR 67-77) years and 71.37% (2191/3070) women, were included. Participants walked a median of 7580 (IQR 4972-10,653) steps and 5523 (IQR 3590-7820) meters per day for a total of 592,597 person-days of PA monitoring. Our results showed that higher levels of daily step volume were associated with lower BP (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure). Compared with participants with low step volume (daily step counts <6000/d) and irregular steps, participants with high step volume (≥9500/d) and regular steps showed the strongest decrease in systolic BP (-1.69 mm Hg, 95% CI -2.2 to -1.18), while participants with medium step volume (6000/d to <9500/d) and regular steps were associated with the lowest diastolic BP (-1.067 mm Hg, 95% CI -1.379 to -0.755). Subgroup analyses indicated generally greater effects on women, individuals with normal BP, and those with only 1 chronic disease, but the effect pattern was varied and heterogeneous between participants with different characteristics.
CONCLUSIONS: Increased step volume demonstrated a substantial protective effect on BP among older adults with chronic conditions. Furthermore, the beneficial association between step volume and BP was enhanced by regular steps, suggesting potential synergistic protective effects of both increased step volume and step regularity. Targeting both step volume and variability through PA interventions may yield greater benefits in BP control, particularly among participants with hypertension and a higher chronic disease burden.

UNASSIGNED: Postoperative recovery in patients with cancer is a complex process that influences quality of life, functional recovery, and mental well-being. Smartphone app-based interventions have emerged as potential tools for improving various aspects of health and well-being in cancer patients. However, the existing literature lacks a consensus on the efficacy of these interventions, leading to conflicting outcomes.
UNASSIGNED: We searched multiple databases, including PubMed, Web of Science, Cochrane Library, Scopus, EMBASE, and MEDLINE Complete (EBSCO). We exclusively selected randomized controlled trials meeting the inclusion criteria for our systematic review and meta-analysis. Utilizing a random-effects model, we derived the pooled effect size estimates for the meta-analysis. Where applicable, we calculated the pooled standardized mean difference (SMD) with 95% confidence interval (CI). The Cochrane Collaboration tool (Cochrane ROB) was used to evaluate bias in randomized trials. The primary outcome was the quality of life. The secondary outcomes were psychological symptoms, health conditions, satisfaction, and self-efficacy.
UNASSIGNED: Of 731 screened articles, 15 were included, comprising 1,831 participants. Our meta-analysis revealed that app-based interventions potentially improved quality of life (SMD =  -0.58, 95% CI -1.00 to -0.16), alleviated psychological symptoms (SMD =  -0.43, 95% CI -0.72,-0.15; p = .003), and enhanced self-efficacy (SMD = 0.90, 95% CI 0.26 to 1.53; p  =  0.001). However, there was no statistically significant effect on satisfaction (SMD = 1.25, 95% CI-1.06 to 3.57; p  =  0.23).
UNASSIGNED: Our findings suggest that mobile health apps hold promise in improving the well-being of cancer patients after surgery by enhancing their quality of life, health status, and self-efficacy, while also reducing anxiety and depression.
Many smartphone apps focus on managing health, particularly for activities such as exercise and preventing diseases such as obesity, diabetes, and mental health; however, there is a noticeable absence of specialized health management apps tailored for cancer patients after surgery. Smartphone app-based interventions have the potential to enhance quality of life, health status, self-efficacy, and decrease feelings of anxiety and depression in adult cancer patients after surgery.

UNASSIGNED: Gestational diabetes mellitus (GDM) can increase the risk of adverse outcomes for both mothers and infants. Preventive interventions can effectively assist pregnant women suffering from GDM. At present, pregnant women are unaware of the importance of preventing GDM, and they possess a low level of self-management ability. Recently, mHealth technology has been used worldwide. Therefore, developing a mobile health app for GDM prevention could potentially help pregnant women reduce the risk of GDM.
UNASSIGNED: To design and develop a mobile application, evaluate its acceptance, and understand the users\'using experience and suggestions, thus providing a valid tool to assist pregnant women at risk of GDM in enhancing their self-management ability and preventing GDM.
UNASSIGNED: An evidence-based GDM prevent app (Better pregnancy) was developed using user-centered design methods, following the health belief model, and incorporating GDM risk prediction. A convenient sampling method was employed from June to August 2022 to select 102 pregnant women at risk of GDM for the pilot study. After a week, the app\'s acceptability was evaluated using an application acceptance questionnaire, and we updated the app based on the feedback from the women. We used SPSS 26.0 for data analysis.
UNASSIGNED: The application offers various functionalities, including GDM risk prediction, health management plan, behavior management, health information, personalized guidance and consultation, peer support, family support, and other functions. In total, 102 pregnant women consented to participate in the study, achieving a retention rate of 98%; however, 2% (n = 2) withdrew. The Better pregnancy app\'s average acceptability score is 4.07 out of 5. Additionally, participants offered several suggestions aimed at enhancing the application.
UNASSIGNED: The Better pregnancy app developed in this study can serve as an auxiliary management tool for the prevention of GDM, providing a foundation for subsequent randomized controlled trials.

OBJECTIVE: This study aimed to evaluate the current situation of Chinese mobile apps for hypertension management and explore patients\' real requirements for app use, providing a theoretical basis for the future improvement of hypertension apps.
METHODS: We reviewed hypertension management apps from mobile app platforms, and summarized their functional characteristics. In addition, we conducted an online survey among 1000 hypertensive patients, collected valid responses, and analyzed the feedback data.
RESULTS: Forty hypertension management apps were analyzed, with 72.5% offering no more than six functions, indicating limited coverage of advanced and comprehensive functionalities. Among the 934 valid survey responses, patients emphasized four main functions in apps for hypertension management: long-term dynamic blood pressure monitoring, scientific lifestyle management, strict medication management and systematic health knowledge delivering.
CONCLUSIONS: The existing hypertension management apps mainly serve as \"Digital Health\" tools with unclear clinical efficacy. The future development of these apps lies in how they transition to \"Digital Therapeutics\" solutions to better meet patients\' needs and provide clear clinical advantages.