JMIR mHealth and uHealth最新文献

{"title":"Barriers and Facilitators in Implementing a Telemonitoring Application for Patients With Chronic Kidney Disease and Health Professionals: Ancillary Implementation Study of the NeLLY (New Health e-Link in the Lyon Region) Stepped-Wedge Randomized Controlled Trial.","authors":"Marion Delvallée, Abdallah Guerraoui, Lucas Tchetgnia, Jean-Pierre Grangier, Nassira Amamra, Anne-Laure Camarroque, Julie Haesebaert, Agnès Caillette-Beaudoin","doi":"10.2196/50014","DOIUrl":"10.2196/50014","url":null,"abstract":"<p><strong>Background: </strong>The use of telemonitoring to manage renal function in patients with chronic kidney disease (CKD) is recommended by health authorities. However, despite these recommendations, the adoption of telemonitoring by both health care professionals and patients faces numerous challenges.</p><p><strong>Objective: </strong>This study aims to identify barriers and facilitators in the implementation of a telemonitoring program for patients with CKD, as perceived by health care professionals and patients, and to explore factors associated with the adoption of the program. This study serves as a process evaluation conducted alongside the cost-effectiveness NeLLY (New Health e-Link in the Lyon Region) trial.</p><p><strong>Methods: </strong>A mixed methods approach combining a quantitative questionnaire and semistructured interviews was conducted among nurses, nephrologists, and patients with stages 3 and 4 CKD across 10 renal care centers in France that have implemented telemonitoring. The Technology Acceptance Model (TAM) and the Consolidated Framework for Implementation Research (CFIR) were used to design the questionnaires and interview guides. The dimensions investigated included ease of use, perceived usefulness, and intention to use (TAM), as well as characteristics of the intervention, local and general context, individual factors, and processes (CFIR). The adoption of telemonitoring was assessed based on the frequency with which patients connected to the telemonitoring device. Determinants of telemonitoring use were analyzed using nonparametric tests, specifically the Wilcoxon-Mann-Whitney and Kruskal-Wallis tests. Thematic analysis was conducted on the transcriptions of semistructured interviews. Both quantitative and qualitative results, including data from patients and professionals, were integrated to provide a comprehensive understanding of the factors associated with the use of remote monitoring in CKD.</p><p><strong>Results: </strong>A total of 42 professionals and 128 patients with CKD responded to our questionnaire. Among these, 11 professionals and 13 patients participated in interviews. Nurses, who were responsible for patient follow-up, regularly used telemonitoring (8/13, 62%, at least once a month), while nephrologists, who were responsible for prescribing it, were primarily occasional users (5/8, 63%, using it less than once a month). Among professionals, the main obstacles identified were the heavy workload generated by telemonitoring, lack of training, and insufficient support for nurses. Among the 128 patients, 46 (35.9%) reported using the application at least once a week. The main barriers for patients were issues related to computer use, as well as the lack of feedback and communication with health care professionals. The main facilitators identified by both professionals and patients for using telemonitoring were the empowerment of patients in managing their health and the reduction of the burden asso","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"13 ","pages":"e50014"},"PeriodicalIF":5.4,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11799818/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143023524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effectiveness of a Mobile Health Intervention (DOT Selfie) in Increasing Treatment Adherence Monitoring and Support for Patients With Tuberculosis in Uganda: Randomized Controlled Trial.","authors":"Juliet Nabbuye Sekandi, Esther Buregyeya, Sarah Zalwango, Damalie Nakkonde, Patrick Kaggwa, Trang Ho Thu Quach, David Asiimwe, Lynn Atuyambe, Kevin Dobbin","doi":"10.2196/57991","DOIUrl":"10.2196/57991","url":null,"abstract":"<p><strong>Background: </strong>Directly observed therapy (DOT) is the standard method for monitoring adherence to tuberculosis (TB) treatment. However, implementing DOT poses challenges for both patients and providers due to limited financial and human resources. Increasing evidence suggests that emerging digital adherence technologies, such as video directly observed therapy (VDOT), can serve as viable alternatives.</p><p><strong>Objective: </strong>This study aims to evaluate the effectiveness of VDOT compared with usual care directly observed therapy (UCDOT).</p><p><strong>Methods: </strong>Between July 2020 and October 2021, we conducted a 2-arm, parallel-group, open-label randomized trial with a 1:1 assignment to receive either the VDOT intervention (n=72) or UCDOT (n=72) for treatment adherence monitoring at public health clinics in Kampala, Uganda. Each group was further stratified to ensure equal numbers of males and females. Eligible patients were aged 18-65 years, had a confirmed diagnosis of TB, and were undergoing daily treatment. The VDOT group was provided with a smartphone equipped with an app, while the UCDOT group followed the routine monitoring practices outlined by the Uganda National TB Program. We tested the hypothesis that VDOT was more effective than UCDOT for monitoring medication adherence. The primary outcome was adherence, defined as having ≥80% of the expected doses observed during the 6-month treatment period. An intention-to-treat analysis was conducted, and multivariable logistic regression was used to estimate the effect of the intervention on adherence monitoring. Adjusted relative risk ratios and their corresponding 95% CIs are presented. Secondary outcomes included treatment completion, loss to follow-up, death, and reasons for missed videos in the intervention group.</p><p><strong>Results: </strong>The intention-to-treat analysis included 142 participants, with 2 excluded due to discontinuation of medication within the first week after enrollment. The median age of participants was 34 (IQR 26-45) years. The median fraction of expected doses observed (FEDO) was significantly higher in the VDOT group compared with the UCDOT group (100, IQR 80-100 vs 30, IQR 10-60, respectively; P<.001). When using a FEDO cutoff of ≥80% to define optimal adherence, 63 of 142 (44%) patients met the threshold, with a significant difference between the VDOT and UCDOT groups (56/71, 79% vs 7/71, 10%, P<.001). After adjusting for confounders, VDOT users were significantly more likely to achieve ≥80% of their expected doses observed compared with UCDOT users (adjusted risk ratio 8.4, 95% CI 4.16-17.0). The most common reasons for failing to submit videos of medication intake were an uncharged phone battery, forgetting to record videos during medication intake, and losing the smartphone.</p><p><strong>Conclusions: </strong>Enhanced VDOT was more effective than UCDOT in increasing adherence monitoring among patients with TB in Uganda. Th","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":" ","pages":"e57991"},"PeriodicalIF":5.4,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11783032/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142881741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Smoking Cessation Smartphone App for Nondaily Smoking With Telephone Onboarding: Proof-of-Concept Randomized Controlled Trial.","authors":"Bettina B Hoeppner, Kaitlyn R Siegel, Allison E Futter, Diadora Finley-Abboud, Alivia C Williamson, Christopher W Kahler, Elyse R Park, Susanne S Hoeppner","doi":"10.2196/53971","DOIUrl":"10.2196/53971","url":null,"abstract":"<p><strong>Background: </strong>Nondaily smoking is a widespread and increasingly prevalent pattern of use. To date, no effective treatment approach for nondaily smoking has been identified.</p><p><strong>Objective: </strong>This study aimed to conduct an unblinded randomized controlled trial to evaluate proof-of-concept markers of the Smiling instead of Smoking (SiS) app, a smartphone app for smoking cessation, designed specifically for people who smoke less than daily, within the framework of positive psychology.</p><p><strong>Methods: </strong>Overall, 226 adults who smoke less than daily were recruited on the web and asked to undertake a quit attempt while using assigned smoking cessation support materials. Participants were randomly assigned to 1 of 3 materials: the SiS smartphone app, the National Cancer Institute's smartphone app QuitGuide (QG), or the National Cancer Institute's smoking cessation brochure, \"Clearing the Air\" (CtA). All participants engaged in a 15-minute scripted onboarding phone call and were introduced to their support materials to use for the next 7 weeks. Follow-up self-assessment web surveys were sent 2, 6, 12, and 24 weeks after participants' initially chosen quit date (ie, 1 week after onboarding). The primary outcome for this study was self-efficacy to remain abstinent from smoking at treatment end. Secondary outcomes assessed treatment acceptability, treatment feasibility (eg, number of days of app use, time spent using app, and use of smoking cessation strategies), and secondary proof-of-concept efficacy outcomes (eg, positive affect, craving, and attitudes toward smoking). Smoking outcomes (ie, 30-day point prevalence abstinence and smoking reduction) were also assessed.</p><p><strong>Results: </strong>Results indicated a significant effect of treatment on the primary outcome, where SiS participants (n=80) reported higher self-efficacy to abstain from smoking at the end of treatment than the 2 control groups (QG: n=75; P=.02; Cohen d=0.40 and CtA: n=71; P=.007; Cohen d=0.50). This effect was also significant on both self-efficacy subscales (ie, internal cues and external cues) with effect sizes ranging from Cohen d=0.34 to 0.50 across the pairwise comparisons. The SiS app group also reported lower craving (QG: P=.005; Cohen d=-0.57 and CtA: P=.005; Cohen d=-0.57) and higher positive affect than QG (QG: P=.01; Cohen d=0.44 and CtA: P=.05; Cohen d=0.38); attitudes toward smoking were largely similar across groups. Treatment acceptability was comparable across groups (P values for all groups >.05; Cohen d range 0.06-0.23). Treatment feasibility measures indicated that participants used the SiS app on 33 out of 49 days, for 35 to 40 minutes per week, resulting in greater use of smoking cessation strategies than QG (QG: P=.04; Cohen d=0.38 and CtA: P=.16; Cohen d=0.24).</p><p><strong>Conclusions: </strong>These findings provide strong evidence for the conceptual underpinnings of the SiS app, and thereby provide comp","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"13 ","pages":"e53971"},"PeriodicalIF":5.4,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11780296/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143005381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Mobile App-Based Gratitude Intervention's Effect on Mental Well-Being in University Students: Randomized Controlled Trial.","authors":"Chloë Fuller, Silvia Marin-Dragu, Ravishankar Subramani Iyer, Sandra Melanie Meier","doi":"10.2196/53850","DOIUrl":"10.2196/53850","url":null,"abstract":"<p><strong>Background: </strong>Gratitude interventions are used to cultivate a sense of gratitude for life and others. There have been mixed results of the efficacy of gratitude interventions' effect on psychological well-being with a variety of populations and methodologies.</p><p><strong>Objectives: </strong>The objective of our study was to test the effectiveness of a gratitude intervention smartphone app on university students' psychological well-being.</p><p><strong>Methods: </strong>We used a randomized experimental design to test our objective. Participants were recruited undergraduate students from a web-based university study recruitment system. Participants completed 90 web-based survey questions on their emotional well-being and personality traits at the beginning and end of the 3-week research period. Their depression, anxiety, and stress levels were measured with the Depression, Anxiety, and Stress Scale (DASS-21). After the baseline survey, participants were randomly assigned to either the control or the intervention. Participants in the intervention group used both a fully automated mobile sensing app and a gratitude intervention mobile iOS smartphone app designed for youth users and based on previous gratitude interventions and exercises. The gratitude intervention app prompted users to complete daily gratitude exercises on the app including a gratitude journal, a gratitude photo book, an imagine exercise, a speech exercise, and meditation. Participants in the control group used only the mobile sensing app, which passively collected smartphone sensory data on mobility, screen time, sleep, and social interactions.</p><p><strong>Results: </strong>A total of 120 participants met the inclusion criteria, and 27 were lost to follow-up for a total of 41 participants in the intervention group and 52 in the control group providing complete data. Based on clinical cutoffs from the baseline assessment, 56 out of 120 participants were identified as being in a subsample with at least moderate baseline symptomatology. Participants in the subsample with at least moderate baseline symptomatology reported significantly lower symptoms of depression, anxiety, and stress postintervention (Cohen d=-0.68; P=.04) but not in the full sample with low baseline symptomatology (Cohen d=0.16; P=.46). The number of times the app was accessed was not correlated with changes in either the subsample (r=0.01; P=.98) or the full sample (r=-0.04; P=.79).</p><p><strong>Conclusions: </strong>University students experiencing moderate to severe distress can benefit from a gratitude intervention smartphone app to improve symptoms of depression, anxiety, and stress. The number of times the gratitude intervention app was used is not related to well-being outcomes. Clinicians could look at incorporating gratitude apps with other mental health treatments or for those waitlisted as a cost-effective and minimally guided option for university students experiencing psychologica","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"13 ","pages":"e53850"},"PeriodicalIF":5.4,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11749078/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142983510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"mHealth-Augmented Care for Reducing Depression Symptom Severity Among Patients With Chronic Pain: Exploratory, Retrospective Cohort Study.","authors":"Dan Holley, Amanda Brooks, Matthew Hartz, Sudhir Rao, Thomas Zaubler","doi":"10.2196/52764","DOIUrl":"10.2196/52764","url":null,"abstract":"<p><strong>Background: </strong>Depression and chronic pain are commonly comorbid, mutually reinforcing, and debilitating. Emerging approaches to mobile behavioral health care (mHealth) promise to improve outcomes for patients with comorbid depression and chronic pain by integrating with existing care models to bolster support and continuity between clinical visits; however, the evidence base supporting the use of mHealth to augment care for this patient population is limited.</p><p><strong>Objective: </strong>To develop an evidence base that sets the stage for future research, we aimed to explore the associations between changes in depression severity and various integrated care models, with and without mHealth augmentation, among patients with comorbid depression and nonmalignant chronic pain.</p><p><strong>Methods: </strong>Our team leveraged retrospective, real-world data from 3837 patients with comorbid depression and nonmalignant chronic pain who received integrated behavioral health care (IBH) at a subspecialty pain clinic. We analyzed one IBH-only, non-mHealth cohort (n=2765), an mHealth-augmented cohort (n=844), and a collaborative care (CoCM)+mHealth cohort (n=136), which were supported by the NeuroFlow mHealth platform, and a pre-CoCM mHealth cohort (n=92), which was supported by the mHealth platform for 3 months prior to beginning the chronic pain treatment. We evaluated changes in depression severity between treatment cohorts via longitudinal analyses of both clinician- and mHealth-administered Patient Health Questionnaire-9 (PHQ-9) assessments.</p><p><strong>Results: </strong>mHealth-augmented integrated care led to significantly greater proportions of patients reaching clinical benchmarks for reduction (725/844, 86% vs 2112/2765, 76%), response (689/844, 82% vs 2027/2765, 73%), and remission (629/844, 75% vs 1919/2765, 69%) compared with integrated care alone. Furthermore, hierarchical regression modeling revealed that patients who received mHealth-augmented psychiatric CoCM experienced the greatest sustained reductions in on-average depression severity compared with other cohorts, irrespective of clinical benchmarks. In addition, patients who engaged with an mHealth platform before entering CoCM experienced a 7.2% reduction in average depression severity before starting CoCM treatment.</p><p><strong>Conclusions: </strong>Our findings suggest that mHealth platforms have the potential to improve treatment outcomes for patients with comorbid chronic pain and depression by providing remote measurement-based care, tailored interventions, and improved continuity between appointments. Moreover, our study set the stage for further research, including randomized controlled trials to evaluate causal relationships between mHealth engagement and treatment outcomes in integrated care settings.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"13 ","pages":"e52764"},"PeriodicalIF":5.4,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11741195/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142970799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reliability and Accuracy of the Fitbit Charge 4 Photoplethysmography Heart Rate Sensor in Ecological Conditions: Validation Study.","authors":"Maxime Ceugniez, Hervé Devanne, Eric Hermand","doi":"10.2196/54871","DOIUrl":"10.2196/54871","url":null,"abstract":"<p><strong>Background: </strong>Wrist-worn photoplethysmography (PPG) sensors allow for continuous heart rate (HR) measurement without the inconveniences of wearing a chest belt. Although green light PPG technology reduces HR measurement motion artifacts, only a limited number of studies have investigated the reliability and accuracy of wearables in non-laboratory-controlled conditions with actual specific and various physical activity movements.</p><p><strong>Objective: </strong>The purpose of this study was to (1) assess the reliability and accuracy of the PPG-based HR sensor of the Fitbit Charge 4 (FC4) in ecological conditions and (2) quantify the potential variability caused by the nature of activities.</p><p><strong>Methods: </strong>We collected HR data from participants who performed badminton, tennis, orienteering running, running, cycling, and soccer while simultaneously wearing the FC4 and the Polar H10 chest belt (criterion sensor). Skin tone was assessed with the Fitzpatrick Skin Scale. Once data from the FC4 and criterion data were synchronized, accuracy and reliability analyses were performed, using intraclass correlation coefficients (ICCs), Lin concordance correlation coefficients (CCCs), mean absolute percentage errors (MAPEs), and Bland-Altman tests. A linear univariate model was also used to evaluate the effect of skin tone on bias. All analyses were stratified by activity and pooled activity types (racket sports and running sports).</p><p><strong>Results: </strong>A total of 77.5 hours of HR recordings from 26 participants (age: mean 21.1, SD 5.8 years) were analyzed. The highest reliability was found for running sports, with ICCs and CCCs of 0.90 and 0.99 for running and 0.80 and 0.93 for orienteering running, respectively, whereas the ICCs and CCCs were 0.37 and 0.78, 0.42 and 0.88, 0.65 and 0.97, and 0.49 and 0.81 for badminton, tennis, cycling, and soccer, respectively. We found the highest accuracy for running (bias: 0.1 beats per minute [bpm]; MAPE 1.2%, SD 4.6%) and the lowest for badminton (bias: -16.5 bpm; MAPE 16.2%, SD 14.4%) and soccer (bias: -16.5 bpm; MAPE 17.5%, SD 20.8%). Limit of agreement (LOA) width and artifact rate followed the same trend. No effect of skin tone was observed on bias.</p><p><strong>Conclusions: </strong>LOA width, bias, and MAPE results found for racket sports and soccer suggest a high sensitivity to motion artifacts for activities that involve \"sharp\" and random arm movements. In this study, we did not measure arm motion, which limits our results. However, whereas individuals might benefit from using the FC4 for casual training in aerobic sports, we cannot recommend the use of the FC4 for specific purposes requiring high reliability and accuracy, such as research purposes.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"13 ","pages":"e54871"},"PeriodicalIF":5.4,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11735015/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142949276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Text Messaging Versus Postal Reminders to Improve Participation in a Colorectal Cancer Screening Program: Randomized Controlled Trial.","authors":"Nuria Vives, Gemma Binefa, Noemie Travier, Albert Farre, Jon Aritz Panera, Berta Casas, Carmen Vidal, Gemma Ibáñez-Sanz, Montse Garcia","doi":"10.2196/64243","DOIUrl":"10.2196/64243","url":null,"abstract":"<p><strong>Background: </strong>Mobile phone SMS text message reminders have shown moderate effects in improving participation rates in ongoing colorectal cancer screening programs.</p><p><strong>Objective: </strong>This study aimed to assess the effectiveness of SMS text messages as a replacement for routine postal reminders in a fecal immunochemical test-based colorectal cancer screening program in Catalonia, Spain.</p><p><strong>Methods: </strong>We conducted a randomized controlled trial among individuals aged 50 to 69 years who were invited to screening but had not completed their fecal immunochemical test within 6 weeks. The intervention group (n=12,167) received an SMS text message reminder, while the control group (n=12,221) followed the standard procedure of receiving a reminder letter. The primary outcome was participation within 18 weeks of the invitation. The trial was stopped early, and a recovery strategy was implemented for nonparticipants in the intervention group. We performed a final analysis to evaluate the impact of the recovery strategy on the main outcome of the trial. Participation was assessed using a logistic regression model adjusting for potential confounders (sex, age, and deprivation score index) globally and by screening behavior.</p><p><strong>Results: </strong>The trial was discontinued early in September 2022 due to the results of the interim analysis. The interim analysis included 5570 individuals who had completed 18 weeks of follow-up (intention-to-treat). The SMS text message group had a participation rate of 17.2% (477/2781), whereas the control group had a participation rate of 21.9% (610/2789; odds ratio 0.71, 95% CI 0.62-0.82; P<.001). As a recovery strategy, 7591 (72.7%) out of 10,442 nonparticipants in the SMS text message group had an open screening episode and received a second reminder by letter, reaching a participation rate of 23% (1748/7591). The final analysis (N=24,388) showed a participation rate of 29.3% (3561/12,167) in the intervention group, which received 2 reminders, while the participation rate was 26.5% (3235/12,221) in the control group (odds ratio 1.16, 95% CI 1.09-1.23; P<.001).</p><p><strong>Conclusions: </strong>Replacing SMS text messages with reminder letters did not increase the participation rate but also led to a decline in participation among nonparticipants 6 weeks after the invitation. However, sending a second reminder by letter significantly increased participation rates among nonparticipants within 6 weeks in the SMS text message group compared with those who received 1 postal reminder (control group). Additional research is essential to determine the best timing and frequency of reminders to boost participation without being intrusive in their choice of participation.</p><p><strong>Trial registration: </strong>ClinicalTrials.gov NCT04343950; https://www.clinicaltrials.gov/study/NCT04343950.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"13 ","pages":"e64243"},"PeriodicalIF":5.4,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11736219/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142914799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Self-Management Support Apps for Spinal Cord Injury: Results of a Systematic Search in App Stores and Mobile App Rating Scale Evaluation.","authors":"Renaldo M Bernard, Vanessa Seijas, Micheal Davis, Anel Volkova, Nicola Diviani, Janina Lüscher, Carla Sabariego","doi":"10.2196/53677","DOIUrl":"10.2196/53677","url":null,"abstract":"<p><strong>Background: </strong>The use of mobile technology to meet health needs, widely referred to as mobile health (mHealth), has played a critical role in providing self-management support for chronic health conditions. However, despite its potential benefits, mHealth technologies such as self-management support apps for spinal cord injury (SCI) have received little research attention, and an understanding of their public availability is lacking. Therefore, an overview of these apps is needed to complement findings from the literature for a complete understanding of mHealth self-management support tools for SCI to support the selection and improvement of existing apps and the development of new ones.</p><p><strong>Objective: </strong>This study aimed to identify and describe quantity, quality, focus, strengths, and weaknesses of self-management support apps for SCI available on major mobile app digital distribution platforms.</p><p><strong>Methods: </strong>A systematic search of the Google Play Store and Apple App Store was conducted to identify and summarize apps for SCI that have been updated since 2017. A supplementary systematic literature review was conducted across 11 bibliographic databases to identify publications that provided more detailed descriptions of the identified apps than what is typically available in app stores. The data synthesis was guided by self-management tasks and skills taxonomies. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines informed the reporting.</p><p><strong>Results: </strong>The 13 apps included in the final synthesis were launched between 2013 and 2021, mostly originating in the United States, with availability in 72 countries and support for 14 languages. Most apps used the Android operating system (10/13, 77%), while 31% (4/13) used iOS. The identified apps mainly focused on activities of daily living, physical activity promotion, health literacy, and therapeutic exercise. All 3 self-management tasks (medical, role, and emotional management) and most self-management skills and support activities were supported by the apps. The mean Mobile App Rating Scale score was 3.86 (SD 0.54), indicating good overall quality. No publications were found describing these apps.</p><p><strong>Conclusions: </strong>Despite their good overall quality, as measured by the Mobile App Rating Scale assessment, the 13 identified apps, alone or combined, do not appear to offer a comprehensive self-management approach that incorporates theory-based strategies. Besides working to improve comprehensiveness, future research and practice should consider adopting new technologies, such as artificial intelligence, to enhance future self-management support apps for SCI. Furthermore, adopting new app development methods, such as low-code development platforms, could help reduce barriers to development, such as time, cost, and securing scarce expertise.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"12 ","pages":"e53677"},"PeriodicalIF":5.4,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11695972/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142864177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy of the mHealth App Intellect in Improving Subclinical Obsessive-Compulsive Disorder in University Students: Randomized Controlled Trial With a 4-Week Follow-Up.","authors":"Madeline Lee Yoon Li, Stephanie Lee Si Min, Oliver Sündermann","doi":"10.2196/63316","DOIUrl":"10.2196/63316","url":null,"abstract":"<p><strong>Background: </strong>Obsessive-compulsive disorder (OCD) is the third most prevalent mental health disorder in Singapore, with a high degree of burden and large treatment gaps. Self-guided programs on mobile apps are accessible and affordable interventions, with the potential to address subclinical OCD before symptoms escalate.</p><p><strong>Objective: </strong>This randomized controlled trial aimed to examine the efficacy of a self-guided OCD program on the mobile health (mHealth) app Intellect in improving subclinical OCD and maladaptive perfectionism (MP) as a potential moderator of this predicted relationship.</p><p><strong>Methods: </strong>University students (N=225) were randomly assigned to an 8-day, self-guided app program on OCD (intervention group) or cooperation (active control). Self-reported measures were obtained at baseline, after the program, and at a 4-week follow-up. The primary outcome measure was OCD symptom severity (Obsessive Compulsive Inventory-Revised [OCI-R]). Baseline MP was assessed as a potential moderator. Depression, anxiety, and stress (Depression Anxiety and Stress Scales-21) were controlled for during statistical analyses.</p><p><strong>Results: </strong>The final sample included 192 participants. The intervention group reported significantly lower OCI-R scores compared with the active control group after the intervention (partial eta-squared [η_p²]=0.031; P=.02) and at 4-week follow-up (η_p²=0.021; P=.044). A significant, weak positive correlation was found between MP and OCI-R levels at baseline (r=0.28; P<.001). MP was not found to moderate the relationship between condition and OCI-R scores at postintervention (P=.70) and at 4-week follow-up (P=.88).</p><p><strong>Conclusions: </strong>This study provides evidence that the self-guided OCD program on the Intellect app is effective in reducing subclinical OCD among university students in Singapore. Future studies should include longer follow-up durations and study MP as a moderator in a broader spectrum of OCD symptom severity.</p><p><strong>Trial registration: </strong>ClinicalTrials.gov NCT06202677; https://clinicaltrials.gov/study/NCT06202677.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"12 ","pages":"e63316"},"PeriodicalIF":5.4,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11686029/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142836483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Qualitative Evaluation of mHealth Implementation for Infectious Disease Care in Low- and Middle-Income Countries: Narrative Review.","authors":"Josephine Greenall-Ota, H Manisha Yapa, Greg J Fox, Joel Negin","doi":"10.2196/55189","DOIUrl":"10.2196/55189","url":null,"abstract":"<p><strong>Background: </strong>Mobile health (mHealth) interventions have the potential to improve health outcomes in low- and middle-income countries (LMICs) by aiding health workers to strengthen service delivery, as well as by helping patients and communities manage and prevent diseases. It is crucial to understand how best to implement mHealth within already burdened health services to maximally improve health outcomes and sustain the intervention in LMICs.</p><p><strong>Objective: </strong>We aimed to identify key barriers to and facilitators of the implementation of mHealth interventions for infectious diseases in LMICs, drawing on a health systems analysis framework.</p><p><strong>Methods: </strong>We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist to select qualitative or mixed methods studies reporting on determinants of already implemented infectious disease mHealth interventions in LMICs. We searched MEDLINE, Embase, PubMed, CINAHL, the Social Sciences Citation Index, and Global Health. We extracted characteristics of the mHealth interventions and implementation experiences, then conducted an analysis of determinants using the Tailored Implementation for Chronic Diseases framework.</p><p><strong>Results: </strong>We identified 10,494 titles for screening, among which 20 studies met our eligibility criteria. Of these, 9 studies examined mHealth smartphone apps and 11 examined SMS text messaging interventions. The interventions addressed HIV (n=7), malaria (n=4), tuberculosis (n=4), pneumonia (n=2), dengue (n=1), human papillomavirus (n=1), COVID-19 (n=1), and respiratory illnesses or childhood infectious diseases (n=2), with 2 studies addressing multiple diseases. Within these studies, 10 interventions were intended for use by health workers and the remainder targeted patients, at-risk individuals, or community members. Access to reliable technological resources, familiarity with technology, and training and support were key determinants of implementation. Additional themes included users forgetting to use the mHealth interventions and mHealth intervention designs affecting ease of use.</p><p><strong>Conclusions: </strong>Acceptance of the intervention and the capacity of existing health care system infrastructure and resources are 2 key factors affecting the implementation of mHealth interventions. Understanding the interaction between mHealth interventions, their implementation, and health systems will improve their uptake in LMICs.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"12 ","pages":"e55189"},"PeriodicalIF":5.4,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11660726/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142818061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}