Tag: nevin manimala

JMIR Mhealth Uhealth. 2026 Feb 11;14:e74071. doi: 10.2196/74071.

ABSTRACT

BACKGROUND: Wearable devices enable the remote collection of health parameters, supporting the outpatient care plans recommended by the World Health Organization to manage chronic diseases. While disease-specific monitoring is accurate, a comprehensive analysis of wearables across various chronic diseases helps to standardize remote patient monitoring systems.

OBJECTIVE: This review aimed to identify wearables for remote monitoring of chronic diseases, focusing on (1) wearable devices, (2) sensor types, (3) health parameters, (4) body locations, and (5) medical applications.

METHODS: We developed a search strategy and conducted searches across three databases: PubMed, Web of Science, and Scopus. After reviewing 1160 articles, we selected 61 that addressed cardiovascular, cancer, neurological, metabolic, respiratory, and other diseases. We created a data analysis method based on our 5 objectives to organize the articles for a comprehensive analysis.

RESULTS: From the 61 articles, 39 (64%) used wearable bands such as smartwatches, wristbands, armbands, and straps to monitor chronic diseases. Wearable devices commonly included various sensor types, such as accelerometers (n=39, 64%), photoplethysmographic sensors (n=18, 30%), biopotential meters (n=17, 28%), pressure meters (n=11, 18%), and thermometers (n=9, 15%). These sensors collected diverse health parameters, including acceleration (n=39, 64%), heart rate (n=24, 39%), body temperature (n=9, 15%), blood pressure (n=8, 13%), and peripheral oxygen saturation (n=7, 11%). Common sensor body locations were the wrist, followed by the upper arm and the chest. The medical applications of wearable devices were neurological (n=21, 34%) and cardiovascular diseases (n=15, 25%). Additionally, researchers applied wearable devices for wellness and lifestyle monitoring (n=39, 64%), mainly for activity (n=39, 100%) and sleep (n=10, 26%).

CONCLUSIONS: This review underscores that wearable devices primarily function as bands, commonly worn on the wrist, to monitor chronic diseases. These devices collect data on acceleration, heart rate, body temperature, blood pressure, and peripheral oxygen saturation, with a focus on neurological and cardiovascular diseases. Our findings provide a foundational road map for designing generalized remote patient monitoring systems to manage multimorbidity and support standardized terminology for interoperability across digital health systems. To translate this into practice, we recommend that future research prioritize pragmatic clinical trials with medically certified devices.

PMID:41671558 | DOI:10.2196/74071

JMIR Cancer. 2026 Feb 11;12:e69525. doi: 10.2196/69525.

ABSTRACT

BACKGROUND: Mobile health (mHealth) represents a promising instrument for optimizing symptom management and important lifestyle strategies that enhance self-care and the quality of health care for patients with cancer. The ALIBIRD mHealth platform is a digital health solution specifically designed for the telemonitoring of oncology patients, fostering patient empowerment and supporting clinical decision-making.

OBJECTIVE: The primary objective of this study was to evaluate the patient experience with the ALIBIRD platform. In addition, the study aimed to assess clinical outcomes, particularly in symptom management, nutritional status, and lifestyle, using patient-reported outcome measures (PROMs).

METHODS: The evaluation was conducted over a 30-week period in patients with advanced lung cancer receiving active treatment. Outcome variables included usability, patient experience, symptom burden, lifestyle behaviors (diet, physical activity, and sleep), nutritional status, PROMs, and system-generated clinical alerts. Through the mobile app, patients reported symptoms and completed integrated REDCap (Research Electronic Data Capture) questionnaires assessing lifestyle behaviors and PROMs, while receiving personalized recommendations informed by nutrigenetic and gut microbiota assessments. Daily activity and sleep data were automatically captured using the Fitbit Inspire wearable. Clinicians remotely monitored patient data using a web-based dashboard and performed clinical actions when required, including phone calls, therapeutic adjustments, referrals, and appointment rescheduling. Statistical analysis included descriptive summaries and pre-post comparisons of clinical and patient-reported outcomes.

RESULTS: Out of 20 patients recruited for the study, 14 completed the intervention. The System Usability Scale yielded a score of 90, indicating high usability. Among the 14 completers, adherence to scheduled questionnaires ranged from 94% to 100% for several instruments, and wearable-based monitoring ranged from 66% to 96% across visits. Overall, the ALIBIRD platform collected and processed 3589 patient-reported outcomes related to physical activity, 3468 related to sleep, 679 on-demand symptom entries, and 1524 completed questionnaires. Clinically, 143 alerts were resolved within an average of 2.05 days, resulting in 2 referrals to emergency rooms and 2 early detections of disease progressions. Furthermore, more than 2100 personalized recommendations contributed to a 21% (3/14 patients) increase in adherence to the Mediterranean diet and a 14% (2/14 patients) increase in moderate physical activity.

CONCLUSIONS: The evaluation of the ALIBIRD implementation yielded promising results in that it facilitated the adoption of healthier lifestyle habits while enhancing health self-management among oncology patients. The ALIBIRD mHealth platform emerges as an effective digital health tool that enables closer monitoring of patients and thereby more informed clinical decision-making.

PMID:41671557 | DOI:10.2196/69525

JMIR Mhealth Uhealth. 2026 Feb 11;14:e73651. doi: 10.2196/73651.

ABSTRACT

BACKGROUND: Driven by technological advancements, the proliferation of mobile sports and health apps has revolutionized health management by improving efficiency, cost-effectiveness, and accessibility. While the widespread adoption of these platforms has transformed public health practices and social well-being in China, emerging evidence suggests that inadequacies in their privacy policies may compromise personal information (PI) protection.

OBJECTIVE: This study aimed to conduct a systematic evaluation of privacy policy compliance among 286 mobile sports and health apps in the Chinese Mainland, benchmarking them against the Personal Information Protection Law and associated PI regulatory guidelines.

METHODS: This study develops a privacy policy compliance indicator scale based on the information life cycle and the legal framework for PI protection in the Chinese Mainland. This scale consists of 5 level 1 indicators and 37 level 2 indicators that assess the privacy policy compliance.

RESULTS: The privacy policy compliance of 286 sports and health apps generally performed worse, with only a minimal number (n=11, 3.8%) of apps scoring above 90 points (rated as excellent), nearly half (n=121, 42.3%) of apps scored below 60 points (rated as unqualified). Among the 5 level 1 evaluation indicators for privacy compliance in sports and health apps, the compliance rate for PI collection (mean 74%, SD 25.8%) is the highest, while the compliance rate for PI storage (mean 53.5%, SD 28.4%) is the lowest. The compliance rates for privacy policies across the remaining 3 level 1 evaluation indicators, such as PI usage (mean 54.2%, SD 24.4%), PI entrusted processing, sharing, transferring, and disclosing (mean 62.2%, SD 19.8%), and PI security and feedback (mean 61.7%, SD 21.3%), fall around 60%. Out of 37, 17 level 2 evaluation indicators show a compliance rate below 60%. The compliance rate with privacy policies for 5 level 2 evaluation indicators is exceptionally high, including collection subject (mean 97.2%, SD 16.5%), collection type (mean 99%, SD 10.2%), collection purpose (mean 96.2%, SD 19.3%), reasons for sharing, transferring, and disclosing PI (mean 91.6%, SD 27.8%), and feedback channel (mean 93.4%, SD 24.9%). Notably, 3 indicators exhibit compliance rates below 20%, including sensitive information storage (mean 14%, SD 34.7%), constraints of automatic decision-making (mean 9.4%, SD 29.3%), and deceased user rule (mean 5.2%, SD 22.3%). Authorization for sensitive information (mean 29.4%, SD 45.6%) lagged behind general information (mean 83.6%, SD 37.1%).

CONCLUSIONS: Although some apps have established commendable policies, there are gaps that compromise the efficacy of PI protection. Considering this, this paper proposes targeted actions for 3 stakeholders: users, regulators, and legislators. Only through coordinated action can the app ecosystem close the compliance gaps, reduce PI protection risks, and restore user trust in digital services.

PMID:41671556 | DOI:10.2196/73651

J Med Internet Res. 2026 Feb 11;28:e83075. doi: 10.2196/83075.

ABSTRACT

BACKGROUND: Mobile health (mHealth) technologies can improve hypertension self-management, yet real-world adoption remains limited and unequally distributed.

OBJECTIVE: This study aimed to characterize the profiles, usage patterns, and engagement of active users of a hypertension self-management app (Hypertension.APP) in Germany, with a focus on user engagement and potential digital divides.

METHODS: We conducted a cross-sectional online survey among adult users of Hypertension.APP in Germany between January and September 2023. An 88-item questionnaire assessed app usage patterns, perceived utility, integration into clinical care, sociodemographic and clinical data, and digital health literacy (eHealth Literacy Scale; scores 16-40). Digital health literacy was categorized as low (16-23.99), moderate (24-31.99), or high (32-40). Descriptive statistics and univariable ordinal logistic regression were used to explore associations between sociodemographic and clinical variables and app usage frequency.

RESULTS: Of 254 respondents, the mean age was 53.6 years, and 54.3% (138/254) were male. A total of 44.5% (113/254) had a university or technical college degree, and 44.5% (113/254) reported a monthly net income higher than €2500 (US $2950). Most participants (224/254, 88.2%) reported access to at least two digital devices. Overall, 88.2% (224/254) had moderate or high digital health literacy (eHealth Literacy Scale ≥24). App engagement was high: 80.7% (205/254) reported using the app at least weekly, and 52.4% (133/254) reported using the app to prepare for medical visits. However, only 20.1% (51/254) reported that the app was formally integrated into their medical care, and 11.8% (30/254) indicated that medication had been adjusted based on app data. In univariable ordinal logistic regression analyses, higher education, longer duration of hypertension, and living in a small town (5000-20,000 inhabitants) were associated with more frequent app use, whereas systolic blood pressure of 140 mm Hg or higher was associated with less frequent use. Digital health literacy was not clearly associated with app usage frequency among current users.

CONCLUSIONS: Users of this hypertension self-management app were predominantly well-educated, digitally literate individuals with established hypertension, reinforcing concerns about a persistent digital divide. While app usability and engagement were high, formal clinical integration remained limited. Simply making an app available is insufficient; strategies to promote equitable access, strengthen clinical integration, and support patients with lower digital health literacy are needed for mHealth to contribute effectively to hypertension management.

PMID:41671553 | DOI:10.2196/83075

Am J Public Health. 2026 Mar;116(3):368-371. doi: 10.2105/AJPH.2025.308325.

ABSTRACT

Objectives. To determine the completeness of providers’ COVID-19 vaccine reporting to the Georgia Registry of Immunization Transactions and Services between October 1, 2023, and December 31, 2023. Methods. We performed active, population, and laboratory surveillance in metropolitan Atlanta, Georgia, to identify all residents hospitalized with COVID-19. We selected a subset of patients by using age-stratified random sampling. We telephoned patients or their proxies, pharmacies, and primary care physicians to verify vaccination status and obtain date of unrecorded vaccination (if applicable) for cases without recorded vaccination on or after September 1, 2023. Results. In the 8-county metro Atlanta catchment area, 2165 patients were hospitalized for COVID-19 during the study period, with 135 patients sampled for full chart reviews. Eighty-six patients required follow-up calls, resulting in 525 telephone calls and approximately 120 person-hours. From follow-up, we identified only 1 vaccine dose not in the registry. Conclusions. The registry is relatively reliable for obtaining information on COVID-19 vaccination status for patients in metropolitan Atlanta. Additional follow-up does not elucidate additional information. (Am J Public Health. 2026;116(3):368-371. https://doi.org/10.2105/AJPH.2025.308325).

PMID:41671540 | DOI:10.2105/AJPH.2025.308325

Am J Public Health. 2026 Mar;116(3):295-297. doi: 10.2105/AJPH.2026.308403.

NO ABSTRACT

PMID:41671538 | DOI:10.2105/AJPH.2026.308403

Neurology. 2026 Mar 10;106(5):e214674. doi: 10.1212/WNL.0000000000214674. Epub 2026 Feb 11.

ABSTRACT

BACKGROUND AND OBJECTIVES: Traumatic brain injury (TBI) is a leading cause of long-term disability in working-age populations. Return to work is a key marker of recovery, yet most studies assess it as binary at fixed time points. We aimed to estimate transition probabilities to and from work disability during 5 years after TBI and how injury severity and preinjury sociodemographic and medical factors influence these probabilities.

METHODS: We conducted a nationwide matched cohort study in Sweden using linked registers. Individuals aged 21-60 years with a TBI diagnosis between 2005 and 2016 were compared with up to 10 matched non-TBI individuals. TBI severity was proxied by care characteristics: TBI A (emergency visit or ≤2 days), TBI B (≥3 days), and TBI C (neurosurgery). Transition probabilities to and from work disability (>14 days sickness absence) were estimated with multistate models. Sociodemographic and medical factors were assessed with Cox regression.

RESULTS: The cohort included 98,256 individuals with TBI and 981,191 matched non-TBI individuals (median age 39 years; 43% women). Transition probabilities to work disability were higher in all TBI groups: at 30 days, 5.5% (95% CI 5.4-5.7) for TBI A, 29% (28.0-30.7) for TBI B, and 43% (38.2-47.3) for TBI C, vs 0.5% (0.5-0.6) in non-TBI; at 5 years, 7.1% (7.0-7.3), 10.9% (10.2-11.7), and 12.9% (10.7-15.7), vs 4.0% (4.0-4.1). In TBI A and B, higher probability was predicted by older age (TBI A hazard ratio 1.23, 95% CI 1.20-1.26; TBI B 1.34, 1.21-1.48), female sex (TBI A 1.59, 1.56-1.62; TBI B 1.35, 1.26-1.44), and psychiatric disorders (TBI A 1.34, 1.30-1.39; TBI B 1.28, 1.11-1.48), while higher education (TBI A 0.83, 0.81-0.86) and city residence (TBI A 0.92, 0.90-0.95; TBI B 0.88, 0.80-0.95) were protective. In TBI C, only older age remained significant (1.59, 1.17-2.14).

DISCUSSION: TBI was associated with persistently elevated transition probabilities to work disability across all severity groups, with early peaks in TBI B and C and a delayed increase in TBI A, influenced by sociodemographic and medical factors. However, the lack of standardized severity grading limits comparison with other studies. Still, these results suggest TBI increases long-term risk of work disability, supporting sustained individualized rehabilitation.

PMID:41671521 | DOI:10.1212/WNL.0000000000214674

JMIR Hum Factors. 2026 Feb 11;13:e77167. doi: 10.2196/77167.

ABSTRACT

BACKGROUND: The widespread use of digital technologies has raised growing concerns about their impact on mental health. While self-regulation has been proposed as a protective factor, little is known about how distinct psychological profiles based on self-regulatory and technology use patterns relate to psychological distress. Person-centered approaches, such as latent profile analysis, may offer deeper insights, particularly in underrepresented populations.

OBJECTIVE: This study aimed to identify latent psychological profiles based on self-regulation, nomophobia (fear of being without a phone), and problematic use of the internet and social media (defined by behavioral symptoms), to examine their associations with general psychological distress and the presence of emotional symptoms in a Colombian sample. Additionally, the predictive roles of age and gender in class membership were explored.

METHODS: Participants were recruited through a convenience sampling strategy aimed at ensuring heterogeneity of the sample in terms of age and gender. A total of 453 participants aged 12 to 57 years (mean 21.03, SD 8.41 years; 257/453, 56.7% female) completed validated measures of self-regulation (Abbreviated Self-Regulation Questionnaire), nomophobia (Nomophobia Questionnaire), internet and social media use (MULTICAGE-TIC, a multidomain screening questionnaire based on the CAGE framework), and psychological distress (General Health Questionnaire-12). Latent profile analysis was conducted using standardized scores of continuous variables. Model fit was assessed using the Bayesian information criterion, entropy, and bootstrapped likelihood ratio test. Differences in psychological distress scores across latent classes were examined through variance analysis (ANOVA) and regression models. A multinomial logistic regression tested the predictive value of age and gender for class membership.

RESULTS: The optimal solution revealed 4 distinct latent profiles (entropy=0.85). Class 1 showed high self-regulation and low problematic technology use, displaying the lowest psychological distress scores. Class 2 presented moderate levels across all indicators but the highest level of psychological distress. Classes 3 and 4 showed mixed patterns. Class 3 (higher information and communication technology [ICT] use and lower self-regulation) exhibited lower distress than class 2, whereas class 4 (younger individuals with low self-regulation and moderately high ICT use) showed higher distress than class 3. Psychological distress differed significantly across profiles (ANOVA, P<.001). Age and gender predicted class membership. Older males were more likely to belong to class 1, and younger females were more likely to be classified into classes 3 and 4.

CONCLUSIONS: Latent profile analysis identified distinct configurations of digital behavior, self-regulation, and psychological distress. Self-regulation consistently differentiated profiles with lower distress scores, suggesting its relevance for understanding how individuals manage ICT use. These findings support the value of person-centered approaches to characterize heterogeneous patterns of technology-related behaviors. The study provides evidence from a Spanish-speaking sample, offering a novel perspective on psychological distress and problematic technology use in contexts that remain underrepresented in the literature.

PMID:41671506 | DOI:10.2196/77167

JMIR Form Res. 2026 Feb 11;10:e67800. doi: 10.2196/67800.

ABSTRACT

BACKGROUND: Digital health interventions (DHIs) can extend the reach of disease prevention interventions; however, few are evidence-based, theoretically grounded, or developed for high-risk youth and families. Co-design approaches engage end users in the design and development of the DHI, which can lead to increased accessibility and engagement.

OBJECTIVE: This study aimed to describe the adaptation of an evidence-based diabetes prevention program for remote, digital delivery.

METHODS: The adaptation of the in-person intervention was guided by a modified Inclusive Digital Health Intervention Design to Promote Health Equity framework and conducted in collaboration with Hispanic adolescents (n=23) with obesity (BMI ≥95th percentile) and their parents (n=15). Focus groups identified digital, health education, and support needs. An expert and community panel assisted in developing solutions based on these findings. A sample content session with a food tasting experience was created and reviewed by participants. The research team subsequently built a digital platform to host the content. Participants assessed the usability of the platform, including the ease of use, design components, and technical issues. A second meeting of the expert panel provided recommendations for further refinement and feedback.

RESULTS: Findings from focus groups indicated that most participants (31/36, 86.1%) reported stable internet access and multiple digital devices. With regard to format, a few parents (2/9, 22.2%) preferred synchronous content sessions, while most youth and parents favored asynchronous sessions (7/9, 77.8%) lasting 40 to 60 minutes. Health education needs included interactive content, healthy recipes, and the ability to ask questions. Experts suggested offering asynchronous sessions with monthly synchronous meetings to meet both parent and youth needs. After viewing a sample session, families found the content easy to understand and mostly engaging, with (17/21) 81% participating in the food tasting activity and all participants reporting that the activity was feasible. Experts recommended using a more conversational, interactive teaching style to improve the content and using a food box with nonperishable items to increase the ease of food tasting activities. While the digital platform was functional and easy to use, families highlighted the need for larger font and icon sizes, easier navigation, and better color contrasts. On the basis of this feedback, experts advised creating tutorial videos and an orientation session for platform training. The content and platform will continue to be refined before further evaluation in a 12-week feasibility pilot study.

CONCLUSIONS: The use of a co-design approach provided opportunities to make content more interactive and engaging and to increase the ease of use of the digital platform. Describing the adaptation process using a guiding framework in collaboration with the focus population will inform future studies aiming to adapt evidence-based interventions to a digital platform.

PMID:41671476 | DOI:10.2196/67800

JMIR Res Protoc. 2026 Feb 11;15:e80243. doi: 10.2196/80243.

ABSTRACT

BACKGROUND: Autism spectrum disorder (ASD) represents a significant public health challenge characterized by persistent social communication deficits and restricted, repetitive patterns of behavior. Current interventions show limited efficacy, particularly for core symptoms. Repetitive transcranial magnetic stimulation (rTMS) and auditory integration training (AIT) have independently demonstrated promise in addressing neurophysiological abnormalities associated with ASD.

OBJECTIVE: This study aims to evaluate the clinical efficacy of a combined rTMS and AIT intervention compared to rTMS alone and sham stimulation in children with ASD.

METHODS: This is a randomized, sham-controlled trial that will recruit 80 children aged 2 to 6 years with a confirmed ASD diagnosis. The randomization of the first 8 participants in this study used a 1:1:1 ratio. To more effectively test the core hypothesis (ie, the efficacy of the combined intervention), greater statistical power will be concentrated on the intervention group (rTMS+AIT), and the randomization ratio was ultimately adjusted to 2:1:1-specifically, (1) rTMS combined with AIT (n=40), (2) rTMS alone (n=20), or (3) sham rTMS (n=20). Primary outcome measures include the Autism Behavior Checklist and Childhood Autism Rating Scale. Secondary outcomes are the Strengths and Difficulties Questionnaire and Repetitive Behavior Scale-Revised. Assessments will be conducted at baseline, an interim time point, and immediately after the intervention. Data will be analyzed using SPSS (version 25.0; IBM Corp).

RESULTS: This study has received funding, with data collection commencing in April 2024. Due to the small initial sample size of 8 participants (5 male and 3 female), no formal statistical comparisons of baseline characteristics between groups have been conducted at this time. It is anticipated that the rTMS combined with AIT intervention will exhibit superior efficacy compared to rTMS only.

CONCLUSIONS: This will be the first sham-controlled trial to systematically investigate the potential synergistic effects of a combined rTMS and AIT intervention in children with ASD. The results will provide valuable insights into the neurotherapeutic potential of this combined approach and contribute to the development of evidence-based interventions for ASD.

PMID:41671470 | DOI:10.2196/80243