JMIR mHealth and uHealth最新文献

Background: Wearable sensor technologies such as inertial measurement units, smartwatches, and multisensor systems have emerged as valuable tools in clinical and real-world health monitoring. These devices enable continuous, noninvasive tracking of gait, mobility, and functional health across diverse populations. However, challenges remain in sensor placement standardization, data processing consistency, and real-world validation.

Objective: This systematic review aimed to evaluate recent literature on the clinical and research applications of wearable sensors. Specifically, it investigated how these technologies are used to assess mobility, predict disease risk, and support rehabilitation. It also identified limitations and proposed future research directions.

Methods: This review was conducted according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We searched the PubMed, Scopus, and Web of Science databases up to March 9, 2025. Inclusion criteria focused on studies using wearable sensors in clinical or real-world environments. A total of 30 eligible studies were identified for qualitative synthesis. Data extracted included study design, population characteristics, sensor type and placement, machine learning algorithms, and clinical outcomes.

Results: Of the included studies, 43% (13/30) were observational, 27% (8/30) were experimental, and 10% (3/30) were randomized controlled trials. Inertial measurement unit-based sensors were used in 67% (20/30) of the studies, with wrist-worn devices being the most common (13/20, 65%). Machine learning techniques were frequently applied, with random forest (6/30, 20%) and deep learning (5/30, 17%) models predominating. Clinical applications spanned Parkinson disease, stroke, multiple sclerosis, and frailty, with several studies (4/30, 13%) reporting high predictive accuracy for fall risk and mobility decline (area under the receiver operating characteristic curve up to 0.97).

Conclusions: Wearable sensors show strong potential for mobility monitoring, disease risk assessment, and rehabilitation tracking in clinical and real-world settings. However, challenges remain in standardizing sensor protocols and data analysis. Future research should focus on large-scale, longitudinal studies; harmonized machine learning pipelines; and integration with cloud-based health systems to improve scalability and clinical translation.

Unlabelled: Shoulder pain is prevalent in people living with spinal cord injury. Technology and digital rehabilitation tools are increasingly available, but this has not yet included the provision of a self-guided exercise intervention focused on managing shoulder pain for people living with spinal cord injury. We drew on the person-based approach (PBA) to intervention development to design a Shoulder Pain Intervention delivered over the interNet (SPIN) to address this gap. However, in preparation for the design process, we found very few published examples of how the PBA had been operationalized. The aim of this paper is to provide a detailed explanation of our approach and how we operationalized the PBA in the design of SPIN to maximize relevance and engagement. Our design process followed the key PBA steps, combining additional evidence and theoretical components. Each step ensured that guiding principles were formulated and followed to maximize the probability that SPIN would be fit for purpose. We followed 3 steps: (1) we drew on themes from preparatory research (existing and primary) to identify the key behavioral issues, needs and challenges, and existing features to form the basis of SPIN design; (2) we formatted guiding principles that included articulating specific design objectives to provide a framework to identify system requirements; and (3) we selected and refined intervention features using existing literature, behavioral theory, and tools such as the "Behaviour Change Wheel." We have designed SPIN by incorporating a deep understanding of the users' needs and best available evidence to maximize engagement and positive outcomes. In this paper, we have made clear how we operationalized the PBA phases, including how existing evidence, theory, tools, and methods were leveraged to support the PBA process. In explicating our process, we have provided a blueprint to guide future researchers using this approach.

Background: While there is growing evidence demonstrating the usefulness of integrating social features within mobile health approaches, little research has explored how African American women use mobile platforms to facilitate physical activity within the context of a group-based physical activity intervention.

Objective: The primary aim of this study was to qualitatively describe how African American women used private group messaging boards on the Fitbit mobile app (eg, the type of social and motivational strategies) during a 10-week group-based physical activity intervention. The secondary aim of this study was to quantitatively test whether greater engagement on the Fitbit mobile app (number of posts per week) was associated with greater daily physical activity (ie, steps and total minutes of physical activity) across 10 weeks.

Methods: Data were collected from 54 African American women who participated in the Together Everyone Achieves More Physical Activity trial (mean age 51.57, SD 13.89 y). Participants completed weekly in-person group sessions, set group-based weekly physical activity goals, and used the Fitbit mobile app for ongoing group communication and support, including posting in a private group. This study used a QUAN-qual mixed methods design to describe how participants used the private group messaging boards on the Fitbit mobile app and to evaluate whether engagement on the Fitbit app was associated with greater physical activity (ie, steps and total minutes of physical activity) across the 10-week intervention.

Results: The mean number of posts per week ranged from 1.79 (SD 2.95) in week 1 to 1.11 (SD 2.49) in week 10, with a maximum of 5.06 (SD 7.62) posts in week 5. A thematic content analysis revealed that the private groups reflected numerous topics, including motivational strategies, cognitive strategies, group strategies, informal positive communication, and sharing pictures. The quantitative analyses revealed that participants who posted at least once per week engaged in more steps (P=.006) and total minutes of physical activity (P=.02).

Conclusions: Participants engaged in ongoing social support, positive communication, and vicarious learning through the Fitbit app, suggesting several important directions for future research, including potential interpersonal mechanisms and best practices for enhancing social support and physical activity among African American women.

Background: Digital therapeutics represents a promising approach to support the management of hypertension. Rural regions in China face substantial challenges in hypertension prevention and management. Given the rapid growth in use of the internet and mobile technologies, particularly smartphones, we developed a user-friendly WeChat mini-program "E-controlled pressure (eKongya)" to assist village physicians in managing patients with hypertension.

Objective: This trial aimed to investigate the efficacy of digital interventions for blood pressure (BP) control in patients with hypertension.

Methods: This open-label cluster-randomized controlled study was conducted in 8 villages in China. Individuals with systolic BP (SBP) ≥140 mm Hg or diastolic BP (DBP) ≥90 mm Hg were recruited. Eight villages were randomly assigned in a 1:1 ratio to the digital intervention group or control group. The primary end point was the hypertension control rate at 24 weeks among the study participants. The secondary end points were the changes in mean SBP and DBP from baseline to 24 weeks. All analyses were performed using the full analysis set.

Results: Between June and July 2024, a total of 95 participants were enrolled and allocated to the digital intervention group (n=48, 51%) or the control group (n=47, 49%). After 24 weeks, data were available from 87 (92%) participants, and the mean age was 63.8 (SD 9.7) years, with 48% (n=42) being female participants. The digital intervention group (25/44, 57%) had a higher percentage of participants with controlled BP compared to the control group (21/43, 49%), although this difference was not statistically significant (P=.60). Logistic regression analysis showed that the digital interventions did not significantly increase the hypertension control rate (odds ratio 0.73, 95% CI 0.31-1.69; P=.46). In the intervention group, SBP decreased from 158.0 (SD 18.4) mm Hg at baseline to 137.5 (SD 13.0) mm Hg at 24 weeks and DBP decreased from 93.8 (SD 10.3) mm Hg to 85.3 (SD 11.6) mm Hg. In the control group during that same period, SBP decreased from 161.1 (SD 18.2) mm Hg to 139.6 (SD 13.2) mm Hg, and DBP decreased from 99.2 (SD 9.2) mm Hg to 83.4 (SD 12.1) mm Hg. After adjusting for baseline SBP or DBP, the mean change from baseline to 24 weeks was comparable between the digital intervention and control groups for both SBP (between-group difference -1.6, 95% CI -7.2 to 3.9; P=.56) and DBP (between-group difference 3.3, 95% CI -1.8 to 8.5; P=.21). No major program-related safety events occurred up to 24 weeks.

Conclusions: Our study demonstrated that the digital interventions increased the hypertension control rate in rural areas, although this improvement was not statistically significant. Nevertheless, providing convenient BP measurements and health education to these patients notably enhanced hypertension control rates.

Background: Heart failure (HF) is a major healthcare challenge in the United States, with approximately 900,000 older adults hospitalized annually. Gaps in self-management, including unrecognized worsening symptoms and failure to adhere to dietary sodium restriction, can reduce quality of life and precipitate hospital admissions. Existing mHealth approaches to HF self-management have produced mixed results, highlighting the need for innovative strategies to improve post-discharge outcomes in at-risk patients.

Objective: The ManageHF trial aimed to evaluate the effectiveness of two just-in-time adaptive interventions (JITAIs) delivered via a mobile application to enhance HF self-management. The interventions focused on symptom recognition and lower dietary sodium restriction, with the goal of reducing readmissions and improving HRQOL over a 12-week period.

Methods: The trial was a 2x2 factorial, double-blind, randomized controlled study conducted across several U.S. institutions. Participants recently hospitalized for acute HF were randomized into four groups: both interventions, either intervention alone, or an active control. The primary outcome was a composite measure assessing time to all-cause death, time to first HF readmission, and HRQOL changes, using the Minnesota Living with Heart Failure Questionnaire (MLHFQ).

Results: Recruitment was hindered by the COVID-19 pandemic, leading to the early discontinuation of the trial. Of 62 participants enrolled, 43 completed the study. Participants were diverse, with a mean age of 55 years; 32% were female, and 55% were Black or African American. Most had HF with reduced ejection fraction . However, due to the early termination and small sample size, the ability to detect statistically significant differences was limited.

Conclusions: The ManageHF trial highlighted the potential of mobile health technology to support HF management, particularly in enhancing HRQOL. Future studies employing more effective recruitment and retention strategies are crucial for establishing the efficacy of these interventions with greater certainty.

Clinicaltrial:

Background: Mobile apps are powerful tools for promoting and sustaining healthy behaviors, including supporting diverse recovery pathways from substance use, including alcohol use disorder. Indeed, prior research strongly supports the notion that social connection through mobile platforms, supplemented by an in-person interaction, is vital in helping individuals strengthen their recovery and improve overall well-being and mental health. However, research into the digital footprints of mobile app users, as a strategy to assess app usage experiences in a recovery context, is lacking.

Objective: This study utilizes a dataset from The Phoenix app, a social media platform specifically designed for individuals impacted by substance use, including those in or seeking recovery, to identify core uses of the app, including how it is leveraged by members from a thematic and emotional valence context.

Methods: We applied natural language processing and deep learning methods to analyze a random sample of 19,685 posts. Analyses included the Bidirectional Encoder Representation from Transformers topic modeling tool to generate themes and a Valence Aware Dictionary and Sentiment Reasoner sentiment analysis to approximate emotional tone and mood from posts ranging from highly negative (-0.99) to highly positive (0.99).

Results: After removing duplicate and nonsensical posts, we retained a final sample size of 17,617 posts. Bidirectional Encoder Representation from Transformers topic modeling tool identified 10 topics (coherence score=0.48) within 2 overarching themes: (1) those related to engaging app members through in-person and online interactions (7 topics) and (2) as a forum to discuss more serious topics pertaining to substance use and mental health recovery (3 topics). Overall, the topics revealed a distinct and recurring theme of community support. Valence Aware Dictionary and Sentiment Reasoner sentiment analysis was 0.44 (SD 0.42), indicating highly positive posts, with only 429 (2.4%) being highly negative.

Conclusions: The study findings broadly show positive uses of The Phoenix app as a tool for social connections and community among people in recovery from substance use. With the high positive sentiment of posts, the app was distinct from other social media platforms (eg, X, Reddit, Facebook), which often feature a mix of highly positive and highly negative posts. Additional research is needed to confirm these results using a larger dataset and with comparative analysis of other recovery forums to contribute to the understanding of social media's role and function in changing health-related behaviors.