https://mhealth.jmir.org/issue/feed 2024-01-05T10:15:04-05:00 JMIR Publications editor@jmir.org Open Journal Systems Unless stated otherwise, all articles are open-access distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work ("first published in JMIR mHealth and uHealth...") is properly cited with original URL and bibliographic citation information. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included. JMIR mhealth and uhealth is a new journal focussing on mobile and ubiquitous health technologies, including smartphones, augmented reality (Google Glasses), intelligent domestic devices, implantable devices, and other technologies designed to maintain health and improve life. https://mhealth.jmir.org/2026/1/e90345 2026-09-08T16:15:13-04:00 Thomas Roussel Elodie Benhaim Louis Perrard Benoit Merat Shamir Vally Remi Girerd Pierre Deharo Louis-Marie Desroche École Numérique de Cardiologie

Background: Mobile health (mHealth) and online video are increasingly central to cardiology education and point-of-care decision support. However, little is known about how simple design choices, such as mobile-first web layouts and captioned videos, translate into real-world practice across countries with different income levels. Objective: This exploratory ecological study used routinely collected, cross-platform learning analytics from a francophone cardiology mHealth initiative to (1) describe how mobile web access and caption-enabled YouTube viewing varied across World Bank income groups and (2) examine whether greater reliance on mobile access was associated with poorer engagement on the website or on YouTube. Methods: We analyzed country-level analytics from the École Numérique de Cardiologie (ENC; Saint-Denis) mobile-optimized website and its companion YouTube channel (YouTube, LLC [Google LLC]) over a two-year window (September 2023 to September 2025). Countries were grouped as high-, middle-, or low-income (World Bank, three-level classification). Country-level metrics included mobile device session share; website bounce rate; time on page; and YouTube average view duration, audience retention, and intentional views. Caption-related and demographic YouTube metrics were available only as income-group aggregates and were therefore reported descriptively as between-group contrasts; country-level inferential analyses were restricted to country-level variables. Reporting followed the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist. Results: Thirty-four countries contributed data: 13/34 (38%) high-income, 14/34 (41%) middle-income, and 7/34 (21%) low-income. Caption-enabled watch time was 18.8% in high-income countries (HICs), compared with 38.7% in middle-income countries (MICs) and 60.9% in low-income countries (LICs), representing a caption equity gap (CEG) of 42.1% between low- and high-income settings. Median website mobile share rose with decreasing income (36.5%, 63.3%, and 81.4%, respectively; Jonckheere-Terpstra .01). Across income groups, higher caption-enabled watch time coincided with a higher share of intentional views. At the country level, greater reliance on mobile access was not associated with higher bounce rate or shorter time on page, and Spearman correlations between mobile share and YouTube engagement metrics were small and nonsignificant (all |ρ|≤0.28; all ≥.18). Conclusions: In this multicountry, francophone, mHealth learning analytics case study, mobile web access and captioned video were used most intensively in lower-income settings, and greater reliance on mobile access was not associated with measurable penalties in basic engagement metrics. These findings support treating mobile-optimized design and systematic captioning as core, low-cost, access-supporting features for equitable digital cardiology education. They also suggest that routinely collected platform indicators can serve as practical equity-monitoring signals for global mHealth initiatives, while underscoring that engagement metrics are not direct measures of learning or behavior change.

2026-09-08T16:15:13-04:00 https://mhealth.jmir.org/2026/1/e72435 2026-09-08T15:45:14-04:00 Sisi Li Lik Hang Lincoln Lo Chiu Yi Charlie Lau Megan Lam Meanne Chan

Background: Work-related stress has been widely associated with an increased risk of various mental disorders and poor mental well-being. The fast-growing mobile health services industry has provided new opportunities for workplace mental health. Objective: This randomized controlled trial examined the effectiveness of (Neurum Limited), a smartphone-based intervention tool featuring ecological momentary assessments and interventions that aims to reduce workplace stress in real-time and real-world settings. Methods: A total of 201 working adults were recruited for a 4-week smartphone-based intervention that incorporated cognitive behavioral therapy, mindfulness exercises, and self-regulation exercises delivered on . A simple randomization procedure was used. Participants in the intervention group were encouraged to log mood journals, complete mental health exercises, and provide user feedback whenever applicable. The key outcome was measured by the Depression, Anxiety, and Stress Scale-21 items (DASS-21; Cronbach α=0.87). Results: The intervention group consisted of 102 participants, while the control group consisted of 99 participants. More participants dropped out from the intervention group (n=21) than from the control group (n=2; =18.259; <.001). The final sample consisted of 178 participants (male: 85/178, 47.8%; female: 93/178, 52.2%; mean age of 34.65, SD 7.67 y). Analyses revealed that after the 4-week intervention, the DASS-21 scores decreased in the intervention group (mean difference [MD]=14.518) but increased in the control group (MD=3.319; =59.358, <.001; =0.252). This effect was largely led by stress reduction (=64.679, <.001; for the intervention group, MD=6.692, while for the control group, MD=2.000). On average, participants completed 6.27 (SD 9.4) exercises and provided 9.74 (SD 18.2) mood journal logs, with a daily engagement of 4.95 (SD 6.89) minutes. However, the associations between the changes in DASS-21 scores and the numbers of exercises or mood journal logs did not reach statistical significance. Conclusions: This study primarily established the effectiveness of in alleviating depression, anxiety, and stress symptoms in noninstitutionalized working adults, with a satisfactory user retention rate. Despite potential health-related culture differences, contributed to evidence-based digital health in nonclinical settings for timely needs and general accessibility as an alternative to traditional, face-to-face, and high-cost mental health services. Future directions involving a personalized approach in online mental health services were discussed. Trial Registration: Chinese Clinical Trial Registry ChiCTR2600131522; https://tinyurl.com/mpdrfdvx

2026-09-08T15:45:14-04:00 https://mhealth.jmir.org/2026/1/e81290 2026-09-08T15:15:07-04:00 Jimikaye Courtney Genevieve Dunton

Intensive longitudinal data (ILD) include frequent and dense repeated measures captured over acute timescales (eg, every second, hour, or day) that are used to investigate within-person processes both within and across days. ILD are collected via wearable sensor data, ecological momentary assessments, or daily diaries and provide unique insights into within-person processes under ecologically valid conditions that can strengthen understanding of temporal relationships among variables and potential causal processes, while also informing the development of just-in-time adaptive interventions. Advancements in mobile and sensor technology have facilitated an explosion of ILD studies that have outpaced formal training in ILD study design. When designing ILD studies, researchers need to make careful decisions about the frequency (ie, how often) and timing (ie, when) of measurements. Decisions about the frequency and timing of measurement are influenced by issues such as variability across individuals and constructs, the purpose of the assessment, concerns about recall biases, saliency, or missing information, and participant needs. The interpretation of study results, causal inferences, and the predictive value of ILD are also impacted by decisions related to the timing of assessments, temporal lags between measures, how a “day” is defined, and data aggregation choices. Due to the increased interest in and adoption of ILD studies, and a lack of formal training, researchers can benefit from guidance on how to design ILD studies. Therefore, this paper aims to provide practical guidance to researchers on how to plan ILD studies using a step-by-step decision-making tutorial with applied health behavior research examples examining phenomena (eg, physical activity and alcohol use) that vary over acute time scales.

2026-09-08T15:15:07-04:00 https://mhealth.jmir.org/2026/1/e104264 2026-09-03T15:30:14-04:00 Soo-Hwan Byun Sung-Woon On Byong-Eun Yang Sung-Ah Che Sang-Min Yi Yongjin Park Yeolib Kim Sang-Yoon Park

Background: Temporomandibular disorders (TMDs) are common chronic conditions involving orofacial pain and functional limitations. Digital therapeutics (DTx) have demonstrated efficacy in TMD management; yet, the behavioral and clinical mechanisms underlying treatment response remain poorly characterized, particularly whether behavioral modification or DTx engagement intensity drives therapeutic benefit. Objective: This study aimed to investigate the behavioral mechanisms, responder profiles, and moderators of clinical response to a DTx intervention for TMD through a post hoc analysis integrating self-reported, server-derived, and clinician-rated outcome measures. Methods: We performed a post hoc secondary analysis of a multicenter, double-blind, sham-controlled randomized superiority trial conducted at 2 tertiary care centers in South Korea. The per-protocol cohort comprised 93 participants (DTx: n=44; sham: n=49). Five complementary analyses were applied: responder logistic regression at ≥30%, ≥50%, and ≥70% Visual Analog Scale (VAS) pain-reduction thresholds; subgroup comparison by Oral Behaviors Checklist (OBC) modifier status; causal mediation analysis using the potential outcomes framework with bootstrap CIs; week-4 sensitivity analysis; and moderator analysis testing the treatment×Patient Health Questionnaire-4 (PHQ-4) interaction on VAS change. Results: DTx assignment was consistently associated with clinically meaningful pain reduction across all 3 responder thresholds (adjusted odds ratios [ORs] 5.39, 95% CI 1.72‐16.94 at ≥30%; 3.21, 95% CI 1.14‐8.99 at ≥50%; and 3.45, 95% CI 1.12‐10.63 at ≥70%; all <.05). Mediation analysis suggested that approximately 29.1% of the total VAS treatment effect may be transmitted via OBC-defined behavioral modification (natural indirect effect −6.91 mm; 95% CI −13.23 to −0.58; =.03), with the mediated proportion rising from 19.6% to 30.2% as responder thresholds became more stringent. Participants with OBC modifiers achieved substantially greater pain reduction than nonmodifiers (−45.71 vs −22.61 mm; difference −23.11; 95% CI −36.97 to −9.24; <.01) despite no significant differences in any objective DTx engagement metric. Treatment ORs were 33%‐42% higher at week 4 than at the 6-week end point (week-4 ORs 7.15, 95% CI 2.39‐21.32 at ≥30%; 4.48, 95% CI 1.68‐11.94 at ≥50%; and 4.91, 95% CI 1.74‐13.87 at ≥70%), suggesting that week 4 may be a candidate time point for future adaptive protocols. Baseline psychological distress (PHQ-4 ≥3) appeared to moderate the treatment response (interaction β=−19.63; 95% CI −37.86 to −1.39; =.04). Conclusions: Sham-controlled randomized trials in TMD that empirically differentiate behavioral realization from digital engagement volume remain scarce. Behavioral modification, rather than engagement volume, appears to be an important pathway associated with DTx efficacy and may mediate approximately 29% of the pain-reduction effect under exploratory causal assumptions. This advances mechanism-based evaluation of DTx beyond engagement-based surrogates. Week 4 may represent a promising candidate for future adaptive protocols, and baseline psychological distress may warrant investigation for precision patient selection. These preliminary findings should be corroborated by future prospective studies and further mechanistic investigations. Trial Registration: Clinical Research Information Service KCT0009493; https://tinyurl.com/w5huy4zn

2026-09-03T15:30:14-04:00 https://mhealth.jmir.org/2026/1/e93912 2026-09-03T12:15:12-04:00 Tonghui Xu Summer Chavez Ben King Gonzalo Ramirez-Pulido Chinedum O Ojinnaka Daniel Osayi Valery Kounga Omolola E Adepoju

Background: Delays in completing cancer screening diminish the preventive benefits of early detection, particularly among women receiving care in Federally Qualified Health Centers (FQHCs). Although many patients receive SMS reminders and complete screening, less is known about how quickly they complete testing or which patient-level and structural factors are associated with delays. Objective: This study examined factors associated with time to cancer screening completion among women aged 50 years or older who received SMS reminders and completed screening across a large FQHC network in Texas. The study also compared time to completion across three cancer screening tests: human papillomavirus (HPV) or the Papanicolaou test (hereinafter “Pap test”), mammography, and the fecal immunochemical test (FIT) or Cologuard screening. Methods: We conducted a secondary data analysis using electronic health record (EHR) data from a 56-clinic FQHC network in Texas. The initial cohort included 1803 women aged 50 years or older who (1) were overdue for HPV or Pap testing, mammography, or FIT or Cologuard screening, and (2) received at least three SMS reminders. Of those, 551 completed the screening and constituted the analytic cohort for this study. The outcome was the number of days from the initial SMS reminder to documented completion of the overdue screening test in the EHR. Kaplan-Meier methods were used to estimate time to completion by screening modality. A multivariable Cox proportional hazards model assessed associations of screening modality, sociodemographic, and clinical characteristics, and self-reported health-related social needs with the rate of screening completion. Results: Overall, 40.8% (n=212) of patients overdue for HPV or Pap testing completed their screening, while 21.1% (n=138) of those overdue for mammography and 32.1% (n=201) of those overdue for FIT or Cologuard screening completed their respective screening. Median time to completion was 72.5 (95% CI 64‐86) days for HPV or Pap screening and 52.0 days for both mammography (95% CI 43‐64) and FIT or Cologuard screening (95% CI 52‐53). In the adjusted model, screening completion was faster for FIT or Cologuard screening (hazard ratio [HR] 1.65, 95% CI 1.34‐2.05) and mammography (HR 1.41, 95% CI 1.11‐1.78) than for HPV or Pap screening. Patient-reported transportation limitation was associated with slower screening completion (HR 0.74, 95% CI 0.55‐0.99). Conclusions: These findings demonstrate meaningful variation in both the completion and timeliness of overdue cancer screening across screening modalities. Although HPV or Pap testing had the highest overall completion rate, time to completion was significantly shorter for mammography and FIT or Cologuard screening. The association between transportation limitations and delayed screening further underscores the influence of access-related barriers on timely preventive care. This suggests that efforts to improve cancer screening should extend beyond patient outreach to incorporate modality-specific strategies and interventions that address structural barriers to screening completion.

2026-09-03T12:15:12-04:00 https://mhealth.jmir.org/2026/1/e92981 2026-09-02T12:00:03-04:00 Benjamin Lalani Gabriela Siew Yllka Valdez Aliyah Shehadeh Daniel Zade Kristin Riekert Nestoras Mathioudakis AI-DPP Study Group

<strong>Background:</strong> Prediabetes is highly prevalent and increasing globally, yet lifestyle interventions remain underused. AI-driven mobile health (mHealth) tools can help scale diabetes prevention efforts, but the key factors driving their success are not well understood. <strong>Objective:</strong> This post hoc secondary analysis of a randomized controlled trial (RCT) aimed to characterize the most valued features and the role of user engagement in outcomes of a fully automated mHealth intervention for diabetes prevention. <strong>Methods:</strong> Data from 151 participants with prediabetes and overweight or obesity who were assigned to an AI-based diabetes prevention program (Sweetch) in a parent RCT (NCT05056376) were analyzed. Engagement (defined as the total number of days the app was used) was categorized into tertiles (low, medium, and high). Baseline characteristics were compared across engagement groups using ANOVA, Kruskal-Wallis, and chi-square tests, and regression models assessed the association between engagement and achievement of diabetes risk reduction outcomes (≥5% weight loss, ≥4% weight loss with ≥150 min/week of physical activity, or ≥0.2 percentage point reduction in hemoglobin A_1c [HbA_1c] at 12 months). Perceived usefulness of intervention features was surveyed at 12 months. <strong>Results:</strong> Median engagement was 98 (IQR 34-232) days. Older age (<i>P</i>&lt;.001) and lower baseline BMI (<i>P</i>=.04) were significantly associated with higher engagement. Compared with low engagement, high engagement was associated with greater odds of achieving the composite diabetes risk reduction outcome (odds ratio [OR] 2.59, 95% CI 1.11-6.01; <i>P</i>=.03), ≥5% weight loss (OR 3.31, 95% CI 1.16-9.42; <i>P</i>=.03), and ≥0.2 percentage point reduction in HbA_1c (OR 3.57, 95% CI 1.19-10.75; <i>P</i>=.02). Participants most frequently rated weight tracking, physical activity tracking, and the digital body weight scale as the features that were most helpful for achieving their health goals. <strong>Conclusions:</strong> Higher engagement with an AI-driven intervention requiring no human intervention was associated with improved diabetes risk reduction. Contrary to concerns about lower digital literacy, older adults engaged with the intervention more than younger adults. Features related to weight and physical activity tracking were most valued by patients in the program. <strong>Trial Registration:</strong> ClinicalTrials.gov NCT05056376; https://clinicaltrials.gov/study/NCT05056376

2026-09-02T12:00:03-04:00 https://mhealth.jmir.org/2026/1/e108495 2026-09-01T16:00:03-04:00 Minyue Sun Fuyou Tang Luo min Shiyu Wen Shuang Wang Huiping Jiang 2026-09-01T16:00:03-04:00 https://mhealth.jmir.org/2026/1/e91407 2026-09-01T15:00:18-04:00 Yan Lin Yingchun Zeng Kaining Chen Zongcun Chen Caihua Ye Ying Zhou Qiwei Zhou Chengying Yu Vivien Xi Wu Samuel Seidu Bin Li Xinjun Jiang

Background: Digital interventions offer scalable alternatives to traditional face-to-face diabetes education, but often face challenges related to inconsistent clinical effectiveness, and declining user engagement. However, whether a digital structured education program integrated with behavioral nudge tools can improve metabolic, behavioral, and psychological outcomes in adults with type 2 diabetes remains unclear. Objective: This study aimed to evaluate the effectiveness of a digital structured education program integrated with behavioral nudge tools in improving metabolic, behavioral, and psychological outcomes among adults with type 2 diabetes. Methods: This multicenter randomized controlled trial was conducted in the endocrinology departments of 4 hospitals in China. Adults with type 2 diabetes were randomly assigned to an intervention group receiving a digital structured education program integrated with behavioral nudge tools (n=146) or a control group receiving standard digital diabetes education (n=147). Assessments were conducted at baseline and 12-week follow-up. The primary outcome was hemoglobin A (HbA) at 12 weeks, adjusted for baseline HbA, and study center. Secondary outcomes included fasting blood glucose (FBG), weight, BMI, waist circumference, blood pressure, lipid profiles, self-management behaviors, self-efficacy, and habit strength. Results: Among 293 participants (mean age 49.19, SD 10.02 y), 287 (97.9%) completed follow-up. At 12 weeks, the intervention group demonstrated significantly greater improvements than the control group in HbA (adjusted mean difference −0.38%, 95% CI −0.68% to −0.09%; .01), FBG (adjusted mean difference −0.75, 95% CI −1.27 to −0.44 mmol/L; <.001), weight (adjusted mean difference −0.84, 95% CI −1.61 to −0.07 kg; .03), BMI (adjusted mean difference −0.38, 95% CI −0.65 to −0.11 kg/m²; .01), systolic blood pressure (adjusted mean difference −2.71, 95% CI −4.62 to −0.79 mm Hg; .01), diastolic blood pressure (adjusted mean difference −2.92, 95% CI −4.47 to −1.37 mm Hg; <.001), and total cholesterol (adjusted mean difference −0.27, 95% CI −0.48 to −0.05 mmol/L; .02). The intervention was also associated with significantly greater improvements in self-management behaviors, self-efficacy, and habit strength (all <.05). Conclusions: Digital structured education integrated with behavioral nudge tools improved metabolic outcomes and strengthened psychological and behavioral determinants of self-management among adults with type 2 diabetes over a 12-week period. These findings suggest that a digital structured education program integrated with behavioral nudge tools may enhance diabetes self-management beyond standard digital diabetes education. Further studies with longer follow-up and real-world implementation are warranted to evaluate the sustainability, generalizability, and long-term clinical impact of this integrated intervention. Trial Registration: Chinese Clinical Trial Registry ChiCTR2400082373; https://tinyurl.com/3djbnt36

2026-09-01T15:00:18-04:00 https://mhealth.jmir.org/2026/1/e91274 2026-09-01T14:00:17-04:00 Atsushi Inaba Kensuke Shinmura Shozo Osera Takahiro Yamada Hiroaki Kon Maki Kanazawa Naoki Sugimura Yasushi Sano Hiroko Hosaka Toshio Uraoka Daiki Sato Yusuke Yoda Hiroyuki Takamaru Yutaka Saito Toshihiko Gocho Atsushi Katagiri Kazuhisa Yamaguchi Takahisa Matsuda Atsuki Imai Hitomi Fujimoto Hiroki Matsuzaki Nobuyoshi Takeshita Masashi Wakabayashi Hiroaki Ikematsu Tomonori Yano

Background: Optimal bowel preparation (BP) is crucial for a successful colonoscopy. Although multiple factors influence BP quality, including patient adherence to laxatives and dietary instructions, the stool state during BP should be properly evaluated to perform a colonoscopy of sufficient quality. Therefore, we developed a smartphone app to evaluate a patient’s stool state during BP and a viewer to enable real-time monitoring by medical staff. Objective: This study aimed to assess the feasibility of performing colonoscopies of appropriate quality using the app-and-viewer system. Methods: This prospective observational study was conducted between November 2022 and December 2023, involving patients scheduled for colonoscopy at 10 Japanese institutions, comprising 6 tertiary hospitals, 3 regional general hospitals, and 1 community-based clinic. Patients who (1) underwent a colonoscopy at participating institutions, (2) were aged between 20 and 70 years, and (3) owned smartphones compatible with Android or iOS were included in the study. The patients downloaded the app on their smartphones and captured images of their stools during BP, while the medical staff reviewed the evaluation of the stools by the app via the viewer system. The primary end point was defined as the proportion of patients with a Boston Bowel Preparation Scale (BBPS) score of ≥6 among those who successfully used the app. Secondary end points included mean BBPS score, rate of an excellent BBPS score (≥8), adenoma detection rate, cecal intubation rate, and withdrawal time in negative colonoscopy. Additionally, we evaluated the usability of the app, medical staff workload burden with the app, and viewer usage via questionnaire surveys. Results: A total of 343 patients were enrolled, and 326 were ultimately included in the analysis. Overall, 99.1% (323/326, 95% CI 97.3%-99.8%) of the patients achieved the primary end point. The mean BBPS score was 8.5 (SD 1.0), and the proportion of excellent BBPS scores was 87.4% (285/326). The adenoma detection rate, cecal intubation rate, and mean withdrawal time in negative colonoscopy were 46.9% (153/326, 95% CI 41.4%-52.5%), 99.7% (325/326, 95% CI 98.3%-99.9%), and 10.7 (SD 5.9) minutes, respectively. In the questionnaire survey, 98.5% (321/326) of the patients reported that the tutorial was easy to understand, 96.0% (313/326) found stool image capture easy, and 87.8% (286/326) reported reduced anxiety regarding BP. Furthermore, 90.5% (295/326) of the patients indicated that they would like to use the app again for future colonoscopies. Among medical staff, 92.5% (62/67) considered the viewer system necessary, 89.6% (60/67) found it easy to use, and 89.6% (60/67) reported a reduction in workload burden. Conclusions: AI-based stool state assessment using the app and the viewer during BP was feasible across diverse BP methods and clinical environments. Favorable BP outcomes and high usability among patients and medical staff support the potential use of this approach in real-world colonoscopy practice.

2026-09-01T14:00:17-04:00 https://mhealth.jmir.org/2026/1/e93989 2026-09-01T13:30:13-04:00 Raffaella Dobrina Chiara De Vita Laura Brunelli Giulia Galvani Margherita Dal Cin Manuela Giangreco Milena Ciampechini Silvana Schreiber Giada Ferrari Paola Di Rocco Sara Zaccariotto Maria Lucrezia Saija Ilaria del Giorno Sara Zanchiello Anja Starec Andrea Cassone

Background: Pediatric ear, nose, and throat (ENT) surgery is common, but generates perioperative anxiety for caregivers and distress in children. Limited time for perioperative education and reliance on unverified online information can reduce family preparedness and increase stress. Few studies have evaluated co-designed mobile health (mHealth) apps to support and engage families in the perioperative ENT journey. Objective: This study aimed to compare caregiver anxiety between an mHealth app-supported care pathway and standard supportive and educational care alone in the perioperative ENT context. Secondary objectives explored between-group differences in caregiver anxiety at follow-up, family preparation, child distress, and social-impact indicators. Methods: A 2-arm, parallel-group, open-label randomized controlled trial (RCT) enrolled caregivers of children undergoing ENT surgery (tonsillectomy, adenoidectomy, tympanostomy tube insertion). The intervention was an mHealth app co-designed through a user-centered participatory approach and developed following Schnall and colleagues’ Information Systems Research Framework, with content based on caregivers’ informational needs. RCT participants were recruited at the hospital during their presurgery visit, when a health care provider introduced the study and provided instructions on how to use the app. No additional human support was scheduled thereafter. A sample size of 180 participants (90 per group) was estimated to detect the expected between-group difference in caregiver anxiety. Participants were randomly assigned in a 1:1 ratio to app use or standard care alone. The primary outcome was the between-group difference in caregiver state anxiety (State-Trait Anxiety Inventory [STAI-Y]). Secondary outcomes included between-group differences in child distress (modified version of the Yale Preoperative Anxiety Scale [mYPAS]), child preparation for surgery, family preparation for hospital admission and surgery, and social impact indicators. Outcomes were assessed online through questionnaires, which included both self-reported measures and evaluations completed by a nurse on the day of surgery. App engagement metrics were also collected. Reporting followed the CONSORT-EHEALTH (Consolidated Standards of Reporting Trials of Electronic and Mobile Health Applications and Online Telehealth) guidelines. Results: The study enrolled 227 caregivers, with 111 allocated to the control group (CG) and 116 to the experimental group (EG), achieving the target sample size. No statistically significant differences were observed between the groups for the primary or secondary outcomes (all >.05). In the EG, 75% (n=87) of the participants accessed at least 1 item of in-app content. Higher baseline anxiety was linked to lower app use (ρ=–0.22, 95% CI –0.39 to –0.04; =.02), while greater use was linked to lower child distress (ρ=–0.23, 95% CI –0.40 to –0.04; =.02). Conclusions: Although the hypotheses were not confirmed, these findings provide valuable insights for future perioperative mHealth research. The lack of effectiveness may reflect limited exposure to the intervention, outcome selection and timing, and contextual factors such as caregivers’ independent information-seeking. These findings support a greater focus on implementation processes and on identifying the caregivers most likely to benefit from mHealth-supported education. Trial Registration: Clinicaltrials.gov NCT05460689; https://clinicaltrials.gov/study/NCT05460689 International Registered Report Identifier (IRRID): RR2-10.1186/s13063-023-07376-z

2026-09-01T13:30:13-04:00