mHealth最新文献

{"title":"Maintained effectiveness of a smartphone-based chatbot coach (BalanceUP) for mental well-being in headache sufferers: preliminary findings from a single-arm 6-month follow-up study.","authors":"Sandra Ulrich, Hansjörg Künzli, Viktor Zuber, Tobias Kowatsch, Andreas R Gantenbein","doi":"10.21037/mhealth-25-9","DOIUrl":"10.21037/mhealth-25-9","url":null,"abstract":"<p><strong>Background: </strong>Behavioral interventions delivered by smartphones have been proven effective in improving physical and mental well-being in clinical and non-clinical samples. However, it remains unclear whether improvements are sustained after intervention completion. This single-arm study evaluated the sustained effectiveness of BalanceUP, a smartphone-based coaching intervention delivered by a conversational agent (CA), for people suffering from frequent headaches.</p><p><strong>Methods: </strong>Following a randomized controlled trial, where an intervention group was compared with a waitlist control group, this within-group comparison examined follow-up results of all participants who participated in the coaching program. Measurements were taken pre-, post-, and 6 months after intervention start. Changes in the primary outcome mental well-being [Patient Health Questionnaire Anxiety and Depression Scale (PHQ-ADS)] and secondary outcomes (psychosomatic symptoms, stress, headache-related self-efficacy, intention to change behavior, presentism, absenteeism, pain coping) were analyzed using repeated measure analysis of variance (ANOVA) and Cohen's d. Additionally, baseline predictors of improvement were explored.</p><p><strong>Results: </strong>Of 179 headache sufferers who started coaching [mean age 39.2 years, standard deviation (SD) 11.8 years; 157/179, 87.7% women], 117 (65.4%) completed the intervention and 67 (36.3%) provided 6-month follow-up data. Improvements in mental well-being were maintained at follow-up with a medium effect size (Cohen d=-0.54). Secondary outcomes also showed sustained improvements with effects ranging from small to medium (d=-0.24 to 0.70), including depression, anxiety, somatic symptoms, perceived stress, headache management self-efficacy, application of behavior change techniques, absenteeism/presentism, as well as pain coping skills. Higher baseline stress and presenteeism were associated with greater improvements in well-being.</p><p><strong>Conclusions: </strong>These preliminary findings suggest the potential for CA-delivered coaching to support improvements in mental well-being and psychological functioning over time. However, the uncontrolled study design, attrition at follow-up, and other methodological limitations require cautious interpretation of the findings. More methodologically robust controlled studies are essential to establish the sustained effectiveness of digital behavioral interventions before drawing definitive conclusions.</p>","PeriodicalId":74181,"journal":{"name":"mHealth","volume":"11 ","pages":"49"},"PeriodicalIF":2.2,"publicationDate":"2025-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12594013/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145484129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The dynamics of eating behaviors and eating environment in college students: discrepancies between app-tracked dietary intake and self-perceived food consumption.","authors":"Y Alicia Hong, Jo-Vivian Yu, Hong Xue, Gang Zhou, Lawrence J Cheskin","doi":"10.21037/mhealth-24-102","DOIUrl":"10.21037/mhealth-24-102","url":null,"abstract":"<p><strong>Background: </strong>People's eating behaviors are affected by their eating environment, particularly who they eat with and where they eat. This relationship is more pronounced in young adults whose behaviors are more likely to be influenced by their environment, but data were limited from this population. This study aims to examine the relationship between dietary intake and eating environment in young adults, and to compare dietary intake logged in a mobile app with self-perceived food consumption reported in daily surveys.</p><p><strong>Methods: </strong>A total of 41 American college students aged 18 to 25 years, from diverse racial and ethnic backgrounds, participated. They logged dietary intake using Nutritionix, a dietary tracking app, and completed daily surveys documenting their eating behaviors, environment, and mood and stress levels. Over 4 weeks, 3,168 eating occasions were logged. Data were analyzed using multilevel mixed-effect models.</p><p><strong>Results: </strong>App data showed participants consumed more calories when eating with two or more companions and in formal dining settings compared to eating alone or at home. Conversely, participants reported that they ate less in these social and formal settings in daily surveys. Significant gender differences were observed with males consuming more calories in social settings and females underreporting intake in formal dining environments. Other factors affecting eating behaviors included body mass index (BMI), mood, and stress levels.</p><p><strong>Conclusions: </strong>This study quantifies the relationship between dietary intake and eating environment using data from a mobile app and daily surveys. It highlights the significant impact of individual, interpersonal, and environmental factors on young adults' dietary behaviors, and underscores the need for personalized and context-sensitive interventions. Attention should be given to discrepancies between app-logged and survey-reported dietary intake when designing dietary interventions.</p>","PeriodicalId":74181,"journal":{"name":"mHealth","volume":"11 ","pages":"47"},"PeriodicalIF":2.2,"publicationDate":"2025-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12593974/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145484180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Micro-randomized pilot trial of an app-based smoking urge reduction intervention for young adults.","authors":"Johannes Thrul, Janardan Devkota, Josef Hamoud, Joseph J C Waring, Amanda Luken, Jasmin Jiuying Han, Felix Naughton, Vadim Zipunnikov, Tamar Mendelson, Carl Latkin, Meghan Moran, David Epstein, Michael R Desjardins","doi":"10.21037/mhealth-25-17","DOIUrl":"10.21037/mhealth-25-17","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Cigarette smoking remains the leading preventable cause of illness and death in the United States and young adults are a priority population. This study aimed to investigate the feasibility of conducting a pilot micro-randomized trial (MRT) among young adults, using smartphone messages to reduce smoking urges in high-risk situations and combining Ecological Momentary Assessments (EMA) and geofence-based delivery.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Participants were recruited online and completed surveys on Qualtrics and an EMA app to report smoking situations over 14 days (assessment phase). Assessment phase data were used to generate individual risk profiles [by combining timestamps, Global Positioning System (GPS), and self-reported data] with the highest likelihood of smoking for each participant. We used geofencing to generate geospatial buffers around these high-risk locations and intervention messages were triggered when a mobile device entered a geofence during specific time windows. In the following 30-day intervention phase, participants were prompted to complete up to 3 geofence-triggered EMAs daily. Each geofence-triggered EMA was followed by an intervention message and the type of message (distraction, acceptance, control) was randomized at each time point (within-subject). Urge level was the primary proximal outcome assessed in a follow-up EMA up to 15 minutes after message delivery. Analyses investigated the feasibility of study procedures, including geofence triggers, within-subject randomization, EMA survey completion rates, and smoking urge reports before and after message delivery. Cigarette smoking cessation and reduction outcomes at 45-day follow-up were also investigated.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 8 participants were included in analyses (mean age 26.3 years; 50% male; 37.5% non-Hispanic White). In the assessment phase, participants completed between 4 and 51 real-time smoking reports. At least 2 geofences were created per participant, with a maximum of 9 geofences for one participant. In the intervention phase, between 11 and 90 geofence EMAs were triggered per participant. Compliance with EMAs was high (90.1% of geofence-triggered, 93.9% of follow-up EMAs). Within-subject randomization was successful and urge ratings declined from pre- to post-message assessments for control (k=98; mean difference =0.20), acceptance (k=99, mean difference =0.36) and distraction messages (k=94, mean difference =0.37). At 45-day follow-up, 1 participant (12.5%) reported no cigarette smoking during the past 7 days and abstinence was confirmed remotely using saliva cotinine testing. Half of participants (n=4, 50%) reduced their number of cigarettes per day (CPD) from baseline to follow-up by 50% or more. Findings also demonstrated the need for robust prevention of fraudulent research participant enrollment, as 10 participants were excluded due to GPS locations outside of the United States.&lt;/p&gt;&lt;p&gt;&lt;st","PeriodicalId":74181,"journal":{"name":"mHealth","volume":"11 ","pages":"59"},"PeriodicalIF":2.2,"publicationDate":"2025-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12593977/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145484192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Caregiver inclusion influence on adolescent acceptance and engagement of an mHealth app, a randomized controlled trial.","authors":"Nicole Henry, Emma Montgomery, Parijat Ghosh, K Taylor Bosworth, Crystal Lim, Jaya Ghosh, Mihail Popescu, Kimberly Kimchi, Congyu Guo, Jamie Smith, Amy Braddock","doi":"10.21037/mhealth-24-97","DOIUrl":"10.21037/mhealth-24-97","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Adolescent obesity has become a major health concern. As adolescent obesity rates continue to rise, mobile health applications (mHealth apps) may play a unique role in reversing these trends by promoting positive health behavior change. The inclusion of adult caregivers in mHealth lifestyle interventions has been shown to be effective in young children, yet this aspect has not been well studied or described in adolescent populations. The aim of our study was to (I) determine whether adolescents find it acceptable to include caregivers in their mHealth lifestyle interventions; (II) evaluate whether caregiver engagement in mHealth lifestyle interventions is positively correlated with adolescent CommitFit mHealth app engagement based on their logging; and (III) explore whether including caregivers in adolescent mHealth lifestyle interventions increases the adolescent's self-perceived motivation to improve their health behavior.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;In this 4-month parallel randomized controlled trial (RCT), 30 dyads of caregivers (n=30) and their adolescents (n=30) were randomized into three study arms: CommitFit, CommitFit$, and waitlist control. Both intervention arms were given access to the novel CommitFit app which uses gamification and behavior economics to promote positive health behavior. The CommitFit app allows users to earn points and compete on a leaderboard by setting and logging health behavior goals. The CommitFit$ group also received money per point that was earned in the app. Dyads were encouraged to form a family team and compete on a team leaderboard. At baseline, 90 days, and 120 days, study participants completed surveys to assess their motivations to use the CommitFit app. Participant use of the app was tracked over time with the use of analytic software developed by the research team.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;All participants that were randomized were analyzed. Adolescents responded favorably to caregiver inclusion with an overall score of 71.9 out of 100. Caregiver app engagement was shown to be positively correlated with adolescent app engagement (r=0.65, P=0.002). However, caregiver inclusion had a marginal impact on adolescent motivation to achieve goals with a score of 51.8 out of 100. Additionally, adolescents at baseline did not consider caregivers to be a strong motivator for health behavior change with a score of 0.62 out of 3.00, although a significant difference at 120 days was shown between the CommitFit study arm and the control group (1.10/3.00 &lt;i&gt;vs.&lt;/i&gt; 0.20/3.00) (P=0.01).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Adolescents may be willing to use mHealth apps that partners with their caregivers. Additionally, increased parental involvement in adolescent mHealth lifestyle interventions may increase adolescent motivation and use of the mHealth app, and has the potential to increase the effectiveness of the mHealth intervention. However, adolescents do not perceive car","PeriodicalId":74181,"journal":{"name":"mHealth","volume":"11 ","pages":"57"},"PeriodicalIF":2.2,"publicationDate":"2025-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12594025/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145484030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A mobile health-based alcohol reduction intervention and its usability among persons with Human Immunodeficiency Virus in Uganda.","authors":"Julian Adong, Robin Fatch, Naomi Sanyu, Anita Katusiime, Nneka I Emenyonu, Winnie R Muyindike, Judith A Hahn","doi":"10.21037/mhealth-25-25","DOIUrl":"10.21037/mhealth-25-25","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Human Immunodeficiency Virus (HIV) and alcohol use are widespread in sub-Saharan Africa (sSA), negatively impacting the continuum of HIV care, from prevention and testing to treatment outcomes. Reducing alcohol consumption among people with HIV (PWH) is therefore a public health priority. Most alcohol reduction strategies require in-person interactions and can be challenging during pandemics and social unrest, which are common in sSA. Mobile Health (mHealth) interventions may offer a more accessible reduction counselling, an accessible alternative to, or may augment, in-person interventions. However, the usability of these mHealth interventions in the target population should be assessed before implementation. This analysis evaluates usability of an mHealth intervention (automated booster sessions) to augment in-person alcohol use reduction counselling and examines its association with booster intervention uptake among PWH who self-reported unhealthy alcohol use.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We analyzed data from PWH who participated in an alcohol reduction counselling intervention. Participants were PWH who self-reported unhealthy alcohol use in the prior 3 months by the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C positive; ≥3 women, ≥4 men). We analyzed data from one of the intervention arms, called the technology booster study arm. In this arm, participants received an in-person counselling intervention that was augmented by technology-based boosters delivered over 3 months. These boosters were delivered via interactive voice response (IVR) or short message service (SMS) text messages, based on participant preference. Usability of the IVR and SMS sessions was assessed at 6 months using the Systems Usability Scale (SUS). Booster intervention uptake, the outcome variable for this analysis, was defined as the percentage of booster sessions during the intervention period in which the participant successfully entered a personal identification number (PIN) needed to start the session. Multivariable linear regression (adjusting for sex, age, being literate, social desirability, and baseline high-risk alcohol use) was conducted to examine the relationship between usability and booster intervention uptake.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Of the 86 participants randomized to the technology arm, 35% were female, with a median age of 40 years [interquartile range (IQR): 32-47]. Fifty-six (65%) chose to receive IVR calls, while 30 (35%) chose SMS; the median booster intervention uptake was 73% (IQR: 53-83). The median SUS score (out of 100) was 90 (IQR: 85-90). SUS score and being literate were associated with booster intervention uptake [adjusted β =0.65, 95% confidence interval (CI): 0.02-1.29, P=0.04, and β =21.33, 95% CI: 7.65-35.01, reduction counselling, an 0.01, respectively].&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;In this analysis of usability and booster intervention uptake among PWH using an mHea","PeriodicalId":74181,"journal":{"name":"mHealth","volume":"11 ","pages":"62"},"PeriodicalIF":2.2,"publicationDate":"2025-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12594019/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145483873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors associated with intention to use an educative mHealth application among high-risk target groups in health prevention.","authors":"Peter Bickmann, Ingo Froböse, Christopher Grieben","doi":"10.21037/mhealth-25-29","DOIUrl":"10.21037/mhealth-25-29","url":null,"abstract":"<p><strong>Background: </strong>An unhealthy and sedentary lifestyle is widespread in industrialized countries, increasing chronic disease risks and potentially leading to a systemic crisis in nursing and elder care. Mobile health (mHealth) applications offer a promising solution by promoting health literacy and supporting holistic, health-oriented lifestyles. However, little is known about the factors influencing the intended use of such applications among individuals with an urgent need for preventive action. This study therefore aims to investigate behavioral intention (BI) to use a chatbot-based mHealth application designed to enhance health literacy and support balanced approaches to physical activity, nutrition, and stress management. Specifically, it seeks to identify key determinants influencing intention to use the application among individuals with high prevention needs, in order to inform the design of engaging and sustainable digital health interventions.</p><p><strong>Methods: </strong>A quantitative survey design based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model was applied to examine determinants of BI to use the Digital Health Companion (DHC), a chatbot-based mHealth application. The model variables included performance expectancy (PE), hedonic motivation (HM), social influence (SI), effort expectancy (EE), and facilitating conditions (FC). In addition, potential moderating effects of age, gender, prior mHealth experience, educational status, and health literacy were assessed using supplementary questionnaires.</p><p><strong>Results: </strong>Data from 105 participants (58 female; 38.4 years) with need for action in the area of physical activity, nutrition, or stress management were analyzed. Results indicate that PE and HM significantly influence BI (P<0.001), while SI shows the least influence (P=0.26) as well as the lowest score overall and therefore has the highest potential to strengthen BI as social functions were enhanced. Factors such as age, gender, prior experience with mHealth applications, or educational status did not influence BI.</p><p><strong>Conclusions: </strong>These findings underscore the need for engaging, user-friendly mHealth applications that motivate preventive health measures, reducing future care dependency. Users must be convinced of the personal health benefits (PE) of the application and experience a certain degree of enjoyment (HM) while using it. The integration of social features however, especially in cooperation with health insurance companies, is restricted by stringent data protection regulations.</p>","PeriodicalId":74181,"journal":{"name":"mHealth","volume":"11 ","pages":"45"},"PeriodicalIF":2.2,"publicationDate":"2025-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12594022/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145484106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Participant evaluation of MOMitor™-a smartphone-based application that monitors postpartum mental and physical health status.","authors":"Deepthi S Varma, Amie J Goodin, Tianze Jiao, Julia Yang, Tony S Wen, Kay Roussos-Ross","doi":"10.21037/mhealth-25-6","DOIUrl":"10.21037/mhealth-25-6","url":null,"abstract":"<p><strong>Background: </strong>MOMitor™ is a mobile app using ecological momentary assessment (EMA) developed and piloted in a large, quaternary care health-system. The purpose of MOMitor™ app is to monitor real-time mood, cesarean incision for symptoms of infection, hypertension, and diabetes in postpartum women. The MOMitor™ triggers alerts for clinic staff when predetermined thresholds are crossed based on survey responses. This prompts nurse-led follow-up and necessary clinical actions. This study aims to analyze exit surveys from all MOMitor™ participants at the end of the 6-week postpartum intervention during the app's 1-year beta testing phase. The objectives of this multi-method study were to explore the user (postpartum women's) satisfaction with the MOMitor™ app, perceived benefit, and challenges encountered during the use.</p><p><strong>Methods: </strong>We enrolled 535 women in a 6-week study using the MOMitor™ app, which involved downloading and using the app postpartum. Participants received an exit survey via email, with reminders, and completed it electronically through research electronic data capture (REDCap). The survey included multiple-choice and open-ended questions to assess user (postpartum women's) experience, app utility, and suggested improvements. Responses were collected electronically through REDCap; statistical analysis was performed using SAS version 9.4 to examine the association between monitored conditions and app compliance and usefulness. Content analysis of open-ended responses identified themes of satisfaction and challenges with the app, providing valuable insights into user (postpartum women's) experience and app functionality.</p><p><strong>Results: </strong>The overall response rate to the exit survey was 49.4%. A total of 190/535 participants reported opening the app. 91.4% of participants who opened the app reported receiving 38 notifications, and 84% completing assessments most or every time. A significant proportion of respondents also utilized mood tracking (75%), nurse contact (46.9%), and clinician discussions (21.9%). The qualitative data showed that the benefits of the MOMitor™ app as its ability to give support in symptom monitoring, ease of reaching clinicians when needed, helpful notifications for task reminders, and the convenience of having an easy-to-use app always accessible on their phones. Further, challenges with the MOMitor™ apps were unfriendly interface, short response times, frequent update requirements, the need to keep the app open in the background, and a visually unappealing design.</p><p><strong>Conclusions: </strong>This feasibility study indicates that mobile apps like MOMitor™, using EMA, can be a useful tool for monitoring postpartum women's health, but may not be universally adopted due to varying levels of engagement and participation. Enhanced patient-clinician communication and self-monitoring benefits of MOMitor™ were valued and accepted by the participants.</p>","PeriodicalId":74181,"journal":{"name":"mHealth","volume":"11 ","pages":"46"},"PeriodicalIF":2.2,"publicationDate":"2025-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12593978/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145484156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Survival analysis for predicting fitness app user churn.","authors":"Monika Zakrzewska, Oscar Bastidas-Jossa, Amaia Mendez-Zorrilla, Joel Montane, Begoña Garcia-Zapirain","doi":"10.21037/mhealth-25-15","DOIUrl":"10.21037/mhealth-25-15","url":null,"abstract":"<p><strong>Background: </strong>Fitness applications are increasingly used to support physical activity and promote healthier lifestyles. However, maintaining long-term engagement remains a major challenge, as many users discontinue app use within weeks. While churn prediction has been studied in fitness centers or other industries, research on digital fitness apps is still limited and often relies on static models such as logistic regression. To address this gap, this study analyses user churn in fitness apps using survival analysis techniques to identify factors contributing to drop out, aiming to improve user engagement and retention strategies. The study objective is to assess the suitability of survival analysis for predicting user churn times in fitness applications.</p><p><strong>Methods: </strong>The study analyzed data from 3,034 users of the Mammoth Hunters fitness application. Three distinct time-range approaches were employed for survival analysis, each paired with two censoring methods. Kaplan-Meier estimates assessed user dropout probabilities over time, supplemented by parametric survival models and cure fraction models. Model performance was evaluated using mean absolute error, Akaike Information Criterion (AIC), concordance index, and Cox-Snell residuals.</p><p><strong>Results: </strong>Significant differences in retention were observed for multiple variables such as gender, activity level, training frequency, and body fat percentage (P=0.004) across all approaches. Men, older users, and those with higher training frequency showed longer engagement, while sedentary users and women disengaged earlier. LogNormal parametric models achieved the best predictive performance with mean absolute errors of 1.02, 1.94, and 3.32 weeks across time approaches. Cure models indicated that only a small fraction of users would remain engaged indefinitely.</p><p><strong>Conclusions: </strong>This study highlights key factors driving user churn in the Mammoth Hunters fitness app, offering insights to help developers reduce dropout rates, enhance engagement, and improve user retention. Applying advanced survival and cure models can improve personalization, reduce dropout rates, and support sustainable health outcomes through digital fitness platforms.</p>","PeriodicalId":74181,"journal":{"name":"mHealth","volume":"11 ","pages":"64"},"PeriodicalIF":3.3,"publicationDate":"2025-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12593983/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145484179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analyzing motivation for tele-exercise in adult fitness app users.","authors":"Andrea Fuente-Vidal, Ricardo Blanco, Roger Prat, Javier Jerez-Roig, Ana Sofía Fernandes-Ribeiro, Joel Montane, Juan Manuel Arribas-Marin","doi":"10.21037/mhealth-25-11","DOIUrl":"10.21037/mhealth-25-11","url":null,"abstract":"<p><strong>Background: </strong>Tele-exercise-using mobile apps or digital platforms-has expanded access to guided physical activity, potentially contributing to public health. The motivational mechanisms that drive individuals to use mobile fitness apps may differ from more traditional forms of exercise and remain limited. Given that motivation undeniably plays a role in the uptake and maintenance of exercise, this study aims to provide insight into the motivational regulation of tele-exercise users, based on the self-determination theory.</p><p><strong>Methods: </strong>An <i>ad hoc</i> scale was developed. Exploratory (EFA) and confirmatory factor analyses (CFA) were conducted to assess the psychometric properties of the scale. Data were inferentially analysed using the Mann-Whitney <i>U</i> test, Kruskal-Wallis test, and Bonferroni <i>post hoc</i> tests.</p><p><strong>Results: </strong>The <i>ad hoc</i> scale showed adequate consistency indices with reliability values ≥0.83, for all (i.e., intrinsic, identified, introjected) motivation dimensions. CFA confirmed the factor structure, with loads >0.51, and composite reliabilities 0.54 to 0.74, for each factor. Construct validity was proven adequate through adjustment of indices tests [Comparative Fit Index (CFI) =0.990; Tucker & Lewis Index (TLI) =0.976, root mean square error of approximation (RMSEA) =0.058]. Statistically significant differences were found relative to sex, previous activity level and fitness goal, for some but not all motivation types (n=753). No statistically significant differences were found for motivation, relative to age.</p><p><strong>Conclusions: </strong>The common understanding that intrinsic motivation is desirable for sustained behavior change may need to be reinterpreted for the field of leisure-time, tele-exercise. These findings provide new insights into how motivation varies among fitness app users and suggest that digital interventions may benefit from reframing motivational strategies to better support exercise adherence.</p>","PeriodicalId":74181,"journal":{"name":"mHealth","volume":"11 ","pages":"50"},"PeriodicalIF":2.2,"publicationDate":"2025-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12594010/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145483964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association between smartphone glances during application-based navigation and pedestrian navigation performance: a real-world experimental study.","authors":"Suguru Shimokihara, Takayuki Tabira, Yuriko Ikeda, Michio Maruta, Gwanghee Han, Taishiro Kamasaki, Yuma Hidaka, Yoshihiko Akasaki, Wataru Kukizaki, Yusuke Kumura","doi":"10.21037/mhealth-25-33","DOIUrl":"10.21037/mhealth-25-33","url":null,"abstract":"<p><strong>Background: </strong>The percentage of people owning smartphones is rapidly increasing due to the digitalization of modern society. Among the smartphone's features, route guidance using navigation applications establishes spontaneous and independent outdoor mobility, and can potentially support people's health. Despite some known concerns regarding smartphone use while walking, navigation performance and eye-tracking behavior while walking with navigation applications in real-world environments are unclear. This study aimed to investigate the association between gaze behavior, particularly glancing at smartphones, and navigation performance among adult users of navigation applications while walking.</p><p><strong>Methods: </strong>This cross-sectional experimental study involved 33 healthy adults aged 20 years and older (20-81 years, 66.7% female) not requiring assistance with walking or activities of daily living. A route navigation task (RNT) of approximately 1,300 m was performed in a real outdoor environment. The participants were required to complete the route as quickly as possible, following the instructions of the navigation application. Simultaneously, the fixation time, number of fixations, number of saccades, total saccade angle, and number of glances at the smartphone were recorded using a wearable eye-tracking device. After checking the distribution of the obtained outcomes and performing correlation analysis, a generalized linear model (GLM) was created to investigate the relationship between the number of glances at the smartphone and the participants' navigation performance and gaze behavior. To confirm the validity of the estimates for each GLM, a bootstrap sample of 2,000 iterations was used to evaluate the estimates.</p><p><strong>Results: </strong>Correlation analysis showed that the number of stops and route errors were moderately and positively correlated with the number of times participants glanced at their smartphones (P<0.05). In the original GLM, the number of stops and route errors showed a significant positive association with the number of glances at the smartphone (P<0.05). This significant positive relationship persisted even after examining the bootstrap sample.</p><p><strong>Conclusions: </strong>In healthy adults, frequent screen glances while walking with a navigation application may interfere with navigation performance. Establishing an alternative navigation system that does not rely on screen-checking may help pedestrians move more efficiently and safely.</p>","PeriodicalId":74181,"journal":{"name":"mHealth","volume":"11 ","pages":"63"},"PeriodicalIF":2.2,"publicationDate":"2025-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12594009/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145484090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}