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  mHealth for Wellness, Behavior Change...

  May 2, 2024

  Efficacy of the Flo App in Improving Health Literacy, Menstrual and General Health, and Well-Being in Women: Pilot Randomized Controlled Trial

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  Authors List:

  • Adam C Cunningham  
  • Carley Prentice  
  • Kimberly Peven  
  • Aidan Wickham  
  • Ryan Bamford  
  • Tara Radovic  
  • Anna Klepchukova  
  • Maria Fomina  
  • Katja Cunningham  
  • Sarah Hill  
  • Liisa Hantsoo  
  • Jennifer Payne  
  • Liudmila Zhaunova  
  • Sonia Ponzo  

  Abstract:

  Background: Reproductive health literacy and menstrual health awareness play a crucial role in ensuring the health and well-being of women and people who menstruate. Further, awareness of one’s own menstrual cycle patterns and associated symptoms can help individuals identify and manage conditions of the menstrual cycle such as premenstrual syndrome (PMS) and premenstrual dysphoric disorder (PMDD). Digital health products, and specifically menstrual health apps, have the potential to effect positive change due to their scalability and ease of access. Objective: The primary aim of this study was to measure the efficacy of a menstrual and reproductive health app, Flo, in improving health literacy and health and well-being outcomes in menstruating individuals with and without PMS and PMDD. Further, we explored the possibility that the use of the Flo app could positively influence feelings around reproductive health management and communication about health, menstrual cycle stigma, unplanned pregnancies, quality of life, work productivity, absenteeism, and body image. Methods: We conducted 2 pilot, 3-month, unblinded, 2-armed, remote randomized controlled trials on the effects of using the Flo app in a sample of US-based (1) individuals who track their cycles (n=321) or (2) individuals who track their cycles and are affected by PMS or PMDD (n=117). Results: The findings revealed significant improvements at the end of the study period compared to baseline for our primary outcomes of health literacy (cycle tracking: D̄=1.11; t₃₁₁=5.73, P<.001; PMS or PMDD: D̄=1.20; t₁₁₅=3.76, P<.001) and menstrual health awareness (D̄=3.97; t₃₁₁=7.71, P<.001), health and well-being (D̄=3.44; t₃₁₁=5.94, P<.001), and PMS or PMDD symptoms burden (D̄=–7.08; t₁₁₅=–5.44, P<.001). Improvements were also observed for our secondary outcomes of feelings of control and management over health (D̄=1.01; t₃₁₁=5.08, P<.001), communication about health (D̄=0.93; t₃₁₁=2.41, P=.002), menstrual cycle stigma (D̄=–0.61; t₃₁₁=–2.73, P=.007), and fear of unplanned pregnancies (D̄=–0.22; t₃₁₁=–2.11, P=.04) for those who track their cycles, as well as absenteeism from work and education due to PMS or PMDD (D̄=–1.67; t₁₄₄=–2.49, P=.01). Conclusions: These pilot randomized controlled trials demonstrate that the use of the Flo app improves menstrual health literacy and awareness, general health and well-being, and PMS or PMDD symptom burden. Considering the widespread use and affordability of the Flo app, these findings show promise for filling important gaps in current health care provisioning such as improving menstrual knowledge and health. Trial Registration: OSF Registries osf.io/pcgw7; https://osf.io/pcgw7 ; OSF Registries osf.io/ry8vq; https://osf.io/ry8vq

  • JMIR Mhealth Uhealth 2024;12(1):e54124

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  Wearable Devices and Sensors

  May 2, 2024

  Harnessing Consumer Wearable Digital Biomarkers for Individualized Recognition of Postpartum Depression Using the All of Us Research Program Data Set:...

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  Authors List:

  • Eric Hurwitz  
  • Zachary Butzin-Dozier  
  • Hiral Master  
  • Shawn T O'Neil  
  • Anita Walden  
  • Michelle Holko  
  • Rena C Patel  
  • Melissa A Haendel  

  Abstract:

  Background: Postpartum depression (PPD) poses a significant maternal health challenge. The current approach to detecting PPD relies on in-person postpartum visits, which contributes to underdiagnosis. Furthermore, recognizing PPD symptoms can be challenging. Therefore, we explored the potential of using digital biomarkers from consumer wearables for PPD recognition. Objective: The main goal of this study was to showcase the viability of using machine learning (ML) and digital biomarkers related to heart rate, physical activity, and energy expenditure derived from consumer-grade wearables for the recognition of PPD. Methods: Using the All of Us Research Program Registered Tier v6 data set, we performed computational phenotyping of women with and without PPD following childbirth. Intraindividual ML models were developed using digital biomarkers from Fitbit to discern between prepregnancy, pregnancy, postpartum without depression, and postpartum with depression (ie, PPD diagnosis) periods. Models were built using generalized linear models, random forest, support vector machine, and k-nearest neighbor algorithms and evaluated using the κ statistic and multiclass area under the receiver operating characteristic curve (mAUC) to determine the algorithm with the best performance. The specificity of our individualized ML approach was confirmed in a cohort of women who gave birth and did not experience PPD. Moreover, we assessed the impact of a previous history of depression on model performance. We determined the variable importance for predicting the PPD period using Shapley additive explanations and confirmed the results using a permutation approach. Finally, we compared our individualized ML methodology against a traditional cohort-based ML model for PPD recognition and compared model performance using sensitivity, specificity, precision, recall, and F₁-score. Results: Patient cohorts of women with valid Fitbit data who gave birth included <20 with PPD and 39 without PPD. Our results demonstrated that intraindividual models using digital biomarkers discerned among prepregnancy, pregnancy, postpartum without depression, and postpartum with depression (ie, PPD diagnosis) periods, with random forest (mAUC=0.85; κ=0.80) models outperforming generalized linear models (mAUC=0.82; κ=0.74), support vector machine (mAUC=0.75; κ=0.72), and k-nearest neighbor (mAUC=0.74; κ=0.62). Model performance decreased in women without PPD, illustrating the method’s specificity. Previous depression history did not impact the efficacy of the model for PPD recognition. Moreover, we found that the most predictive biomarker of PPD was calories burned during the basal metabolic rate. Finally, individualized models surpassed the performance of a conventional cohort-based model for PPD detection. Conclusions: This research establishes consumer wearables as a promising tool for PPD identification and highlights personalized ML approaches, which could transform early disease detection strategies.

  • JMIR Mhealth Uhealth 2024;12(1):e54622

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  mHealth for Rehabilitation

  May 2, 2024

  Rehabilitation Applications Based on Behavioral Therapy for People With Knee Osteoarthritis: Systematic Review

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  Authors List:

  • Dian Zhu  
  • Jianan Zhao  
  • Mingxuan Wang  
  • Bochen Cao  
  • Wenhui Zhang  
  • Yunlong Li  
  • Chenqi Zhang  
  • Ting Han  

  Abstract:

  Background: The development of digital applications based on behavioral therapies to support patients with knee osteoarthritis (KOA) has attracted increasing attention in the field of rehabilitation. This paper presents a systematic review of research on digital applications based on behavioral therapies for people with KOA. Objective: This review aims to describe the characteristics of relevant digital applications, with a special focus on the current state of behavioral therapies, digital interaction technologies, and user participation in design. The secondary aim is to summarize intervention outcomes and user evaluations of digital applications. Methods: A systematic literature search was conducted using the keywords “Knee Osteoarthritis,” “Behavior Therapy,” and “Digitization” in the following databases (from January 2013 to July 2023): Web of Science, Embase, Science Direct, Ovid, and PubMed. The Mixed Methods Assessment Tool (MMAT) was used to assess the quality of evidence. Two researchers independently screened and extracted the data. Results: A total of 36 studies met the inclusion criteria and were further analyzed. Behavioral change techniques (BCTs) and cognitive behavioral therapy (CBT) were frequently combined when developing digital applications. The most prevalent areas were goals and planning (n=31) and repetition and substitution (n=27), which were frequently used to develop physical activity (PA) goals and adherence. The most prevalent combination strategy was app/website plus SMS text message/telephone/email (n=12), which has tremendous potential. This area of application design offers notable advantages, primarily manifesting in pain mitigation (n=24), reduction of physical dysfunction (n=21), and augmentation of PA levels (n=12). Additionally, when formulating design strategies, it is imperative to consider the perspectives of stakeholders, especially in response to the identified shortcomings in application design elucidated within the study. Conclusions: The results demonstrate that “goals and planning” and “repetition and substitution” are frequently used to develop PA goals and PA behavior adherence. The most prevalent combination strategy was app/website plus SMS text message/telephone/email, which has tremendous potential. Moreover, incorporating several stakeholders in the design and development stages might enhance user experience, considering the distinct variations in their requirements. To improve the efficacy and availability of digital applications, we have several proposals. First, comprehensive care for patients should be ensured by integrating multiple behavioral therapies that encompass various aspects of the rehabilitation process, such as rehabilitation exercises and status monitoring. Second, therapists could benefit from more precise recommendations by incorporating additional intelligent algorithms to analyze patient data. Third, the implementation scope should be expanded from the home environment to a broader social community rehabilitation setting.

  • JMIR Mhealth Uhealth 2024;12(1):e53798

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  Wearables and MHealth Reviews

  May 1, 2024

  Cross-Cutting mHealth Behavior Change Techniques to Support Treatment Adherence and Self-Management of Complex Medical Conditions: Systematic Review

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  Authors List:

  • Cyd K Eaton  
  • Emma McWilliams  
  • Dana Yablon  
  • Irem Kesim  
  • Renee Ge  
  • Karissa Mirus  
  • Takeera Sconiers  
  • Alfred Donkoh  
  • Melanie Lawrence  
  • Cynthia George  
  • Mary Leigh Morrison  
  • Emily Muther  
  • Gabriela R Oates  
  • Meghana Sathe  
  • Gregory S Sawicki  
  • Carolyn Snell  
  • Kristin Riekert  

  Abstract:

  Background: Mobile health (mHealth) interventions have immense potential to support disease self-management for people with complex medical conditions following treatment regimens that involve taking medicine and other self-management activities. However, there is no consensus on what discrete behavior change techniques should be used in an effective adherence and self-management promoting mHealth solution for any chronic illness. Reviewing the extant literature to identify effective, cross-cutting behavior change techniques in mHealth interventions for adherence and self-management promotion could help accelerate the development, evaluation, and dissemination of behavior change interventions with potential generalizability across complex medical conditions. Objective: To identify cross-cutting mHealth-based behavior change techniques to incorporate in effective mHealth adherence and self-management interventions for people with complex medical conditions by systematically reviewing the literature across chronic medical conditions with similar adherence and self-management demands. Methods: A registered systematic review was conducted to identify published evaluations of mHealth adherence and self-management interventions for chronic medical conditions with complex adherence and self-management demands. Methodological characteristics and behavior change techniques in each study were extracted using a standard data collection form. Results: 122 studies were reviewed; the majority involved people with type 2 diabetes (n=28/122, 23%), asthma (n=27/122, 22%), and type 1 diabetes (n=19/122, 16%). mHealth interventions rated as having a positive outcome on adherence/self-management used more behavior change techniques (M=4.95, SD=2.56) compared to interventions with no impact on outcomes (M=3.57, SD=1.95) or used >1 outcome measure or analytic approach (M=3.90, SD=1.93; P=.02). The following behavior change techniques were associated with positive outcomes: Self-monitoring outcomes of behavior (39/59, 66%), feedback on outcomes of behavior (34/59, 58%), self-monitoring of behavior (34/59, 58%), feedback on behavior (29/59, 49%), credible source (24/59, 41%), and goal setting (behavior; 14/59, 24%). In adult-only samples, prompts/cues were associated with positive outcomes (34/45, 76%). In adolescent/young adult samples, information about health consequences (1/4, 25%), problem-solving (1/4, 25%), and material reward-behavior (2/4, 50%) were associated with positive outcomes. In interventions explicitly targeting taking medicine, prompts/cues (25/33, 76%) and credible source (13/33, 39%) were associated with positive outcomes. In interventions focused on self-management and other adherence targets, instruction on how to perform the behavior (8/26, 31%), goal setting (behavior; 8/26, 31%)), and action planning (5/26, 19%) were associated with positive outcomes. Conclusions: To support adherence and self-management in people with complex medical conditions, mHealth tools should purposefully incorporate effective and developmentally appropriate behavior change techniques. A cross-cutting approach to behavior change technique selection could accelerate the development of much needed mHealth interventions for target populations, though mHealth intervention developers should continue to consider the unique needs of the target population when designing these tools. Clinical Trial: PROSPERO International prospective register of systematic reviews CRD42021224407; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=224407

  • JMIR Mhealth Uhealth 2024;12(1):e49024

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  Textile Sensors and Smart Textiles

  May 1, 2024

  Monitoring Adolescent and Young Adult Patients With Cancer via a Smart T-Shirt: Prospective, Single-Cohort, Mixed Methods Feasibility Study (OncoSmartShirt...

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  Authors List:

  • Emma Balch Steen-Olsen  
  • Helle Pappot  
  • Maiken Hjerming  
  • Signe Hanghoej  
  • Cecilie Holländer-Mieritz  

  Abstract:

  Background: Wearables measuring vital parameters can be potential tools for monitoring patients at home during cancer treatment. One type of wearable is a smart t-shirt with embedded sensors. Initially, the smart t-shirts were designed to aid athletes in their performance analysis but with an ambition to be a supportive tool in health care. In general, the knowledge of the use of wearables for symptom monitoring during cancer treatment is limited, and consensus and awareness about compliance or adherence are sparse. Objective: The aim of this study was to evaluate the adherence and patient experience of using a smart t-shirt for home monitoring of biometric sensor data in adolescents and young adults (AYA) undergoing cancer treatment during a two-week period. Methods Methods: The study was a prospective, single-cohort, mixed-method feasibility study. Inclusion criteria were patients ≥18-39 years receiving treatment at Copenhagen University Hospital, Rigshospitalet, D.K. Consenting patients were asked to wear the ChronolifeTM smart t-shirt for a period of two weeks. The smart t-shirt has multiple sensors and electrodes, which engender six measurements: ECG, thoracic and abdominal respiration, thoracic impedance, physical activity (steps), and skin temperature. The primary endpoint was adherence, defined as wear time > 8 hours/day. The patient experience was investigated in individual semi-structured telephone interviews and a paper questionnaire. Results: Ten patients were included. Wear time >8 h/d during the study period (14 days) varied between 0-6 days, mean 2 days. Three patients had a mean wear time >8 h/d during their days with data registration. Days with any data registration were 0-10, mean 6.4 days. The thematic analysis of interviews pointed to three main themes: 1) The smart t-shirt is cool but does not fit cancer patients; 2) The technology limits the use of the smart t-shirt; and 3) Monitoring of data increases the safety feeling. Results from the questionnaire showed that the patients generally had confidence in the device. Conclusions: Although the primary endpoint was not reached, the patients’ experience using the smart t-shirt led to the knowledge that patients acknowledged the need for new technologies for improved supportive care in cancer. The patients were positive when asked to wear the smart t-shirt. However, technical and practical challenges in using the device led to low adherence. Although wearables might have a potential for home monitoring, the present technology is immature for clinical use.

  • JMIR Mhealth Uhealth 2024;12(1):e50620

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  Wearables and MHealth Reviews

  Apr 30, 2024

  Effectiveness of mHealth App–Based Interventions for Increasing Physical Activity and Improving Physical Fitness in Children and Adolescents: Systematic...

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  Authors List:

  • Jun-Wei Wang  
  • Zhicheng Zhu  
  • Zhang Shuling  
  • Jia Fan  
  • Yu Jin  
  • Zhan-Le Gao  
  • Wan-Di Chen  
  • Xue Li  

  Abstract:

  Background: The COVID-19 pandemic has significantly reduced physical activity (PA) levels and increased sedentary behavior (SB), which can lead to worsening physical fitness (PF). Children and adolescents may benefit from mobile health (mHealth) apps to increase PA and improve PF. However, the effectiveness of mHealth app–based interventions and potential moderators in this population are not yet fully understood. Objective: This study aims to review and analyze the effectiveness of mHealth app–based interventions in promoting PA and improving PF and identify potential moderators of the efficacy of mHealth app–based interventions in children and adolescents. Methods: We searched for randomized controlled trials (RCTs) published in the PubMed, Web of Science, EBSCO, and Cochrane Library databases until December 25, 2023, to conduct this meta-analysis. We included articles with intervention groups that investigated the effects of mHealth-based apps on PA and PF among children and adolescents. Due to high heterogeneity, a meta-analysis was conducted using a random effects model. The Cochrane Risk of Bias Assessment Tool was used to evaluate the risk of bias. Subgroup analysis and meta-regression analyses were performed to identify potential influences impacting effect sizes. Results: We included 28 RCTs with a total of 5643 participants. In general, the risk of bias of included studies was low. Our findings showed that mHealth app–based interventions significantly increased total PA (TPA; standardized mean difference [SMD] 0.29, 95% CI 0.13-0.45; P<.001), reduced SB (SMD –0.97, 95% CI –1.67 to –0.28; P=.006) and BMI (weighted mean difference –0.31 kg/m², 95% CI –0.60 to –0.01 kg/m²; P=.12), and improved muscle strength (SMD 1.97, 95% CI 0.09-3.86; P=.04) and agility (SMD –0.35, 95% CI –0.61 to –0.10; P=.006). However, mHealth app–based interventions insignificantly affected moderate to vigorous PA (MVPA; SMD 0.11, 95% CI –0.04 to 0.25; P<.001), waist circumference (weighted mean difference 0.38 cm, 95% CI –1.28 to 2.04 cm; P=.65), muscular power (SMD 0.01, 95% CI –0.08 to 0.10; P=.81), cardiorespiratory fitness (SMD –0.20, 95% CI –0.45 to 0.05; P=.11), muscular endurance (SMD 0.47, 95% CI –0.08 to 1.02; P=.10), and flexibility (SMD 0.09, 95% CI –0.23 to 0.41; P=.58). Subgroup analyses and meta-regression showed that intervention duration was associated with TPA and MVPA, and age and types of intervention was associated with BMI. Conclusions: Our meta-analysis suggests that mHealth app–based interventions may yield small-to-large beneficial effects on TPA, SB, BMI, agility, and muscle strength in children and adolescents. Furthermore, age and intervention duration may correlate with the higher effectiveness of mHealth app–based interventions. However, due to the limited number and quality of included studies, the aforementioned conclusions require validation through additional high-quality research. Trial Registration: PROSPERO CRD42023426532; https://tinyurl.com/25jm4kmf

  • JMIR Mhealth Uhealth 2024;12(1):e51478

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  Use and User Demographics of mHealth

  Apr 29, 2024

  Use of Electronic Patient Messaging by Pregnant Patients Receiving Prenatal Care at an Academic Health System: Retrospective Cohort Study

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  Authors List:

  • Kai Holder  
  • Joe Feinglass  
  • Charlotte Niznik  
  • Lynn M Yee  

  Abstract:

  Background: Use of electronic medical record (EMR) patient portal messaging has rarely been studied in maternity care. Objective: This study aimed to estimate changes in patient portal use and intensity in prenatal care before and during the pandemic period. Methods: In this study, patients seen for prenatal care at a large academic medical center were categorized by the number of secure messages sent during pregnancy as non-users, infrequent (5), moderate (6-14), or frequent (15). Monthly portal use intensity rates were computed over 43 months from 2018-2021 before to after the COVID pandemic shutdown. A logistic regression model was estimated to identify patient sociodemographic and clinical subgroups with the highest portal non-use. Results: Among 12,380 patients, 21.7% never used the portal, and 21.6%, 30.3%, and 26.4% were infrequent, moderate, and frequent users, respectively. Portal use and intensity increased significantly over the study period, particularly after the pandemic. However, non-Hispanic Black, Hispanic, non-English-speaking, and Medicaid-insured patients continued to have significantly lower likelihoods of portal use. Patients with pre-existing comorbidities, hypertensive disorders of pregnancy, diabetes, and a history of mental health conditions were all significantly associated with higher portal use and intensity. Conclusions: Reducing disparities in messaging use will require outreach and assistance to low use patient groups, including education addressing health literacy and encouraging appropriate and effective use of messaging.

  • JMIR Mhealth Uhealth 2024;12(1):e51637

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  mHealth for Wellness, Behavior Change...

  Apr 26, 2024

  An mHealth Intervention Promoting Physical Activity and Healthy Eating in a Family Setting (SMARTFAMILY): Randomized Controlled Trial

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  Authors List:

  • Kathrin Wunsch  
  • Janis Fiedler  
  • Sebastian Hubenschmid  
  • Harald Reiterer  
  • Britta Renner  
  • Alexander Woll  

  Abstract:

  Background: Numerous smartphone apps are targeting physical activity (PA) and healthy eating (HE), but empirical evidence on their effectiveness for the initialization and maintenance of behavior change, especially in children and adolescents, is still limited. Social settings influence individual behavior; therefore, core settings such as the family need to be considered when designing mobile health (mHealth) apps. Objective: The purpose of this study was to evaluate the effectiveness of a theory- and evidence-based mHealth intervention (called SMARTFAMILY [SF]) targeting PA and HE in a collective family–based setting. Methods: A smartphone app based on behavior change theories and techniques was developed, implemented, and evaluated with a cluster randomized controlled trial in a collective family setting. Baseline (t₀) and postintervention (t₁) measurements included PA (self-reported and accelerometry) and HE measurements (self-reported fruit and vegetable intake) as primary outcomes. Secondary outcomes (self-reported) were intrinsic motivation, behavior-specific self-efficacy, and the family health climate. Between t₀ and t₁, families of the intervention group (IG) used the SF app individually and collaboratively for 3 consecutive weeks, whereas families in the control group (CG) received no treatment. Four weeks following t₁, a follow-up assessment (t₂) was completed by participants, consisting of all questionnaire items to assess the stability of the intervention effects. Multilevel analyses were implemented in R (R Foundation for Statistical Computing) to acknowledge the hierarchical structure of persons (level 1) clustered in families (level 2). Results: Overall, 48 families (CG: n=22, 46%, with 68 participants and IG: n=26, 54%, with 88 participants) were recruited for the study. Two families (CG: n=1, 2%, with 4 participants and IG: n=1, 2%, with 4 participants) chose to drop out of the study owing to personal reasons before t₀. Overall, no evidence for meaningful and statistically significant increases in PA and HE levels of the intervention were observed in our physically active study participants (all P>.30). Conclusions: Despite incorporating behavior change techniques rooted in family life and psychological theories, the SF intervention did not yield significant increases in PA and HE levels among the participants. The results of the study were mainly limited by the physically active participants and the large age range of children and adolescents. Enhancing intervention effectiveness may involve incorporating health literacy, just-in-time adaptive interventions, and more advanced features in future app development. Further research is needed to better understand intervention engagement and tailor mHealth interventions to individuals for enhanced effectiveness in primary prevention efforts. Trial Registration: German Clinical Trials Register DRKS00010415; https://drks.de/search/en/trial/DRKS00010415

  • JMIR Mhealth Uhealth 2024;12(1):e51201

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  mHealth for Patient Education

  Apr 24, 2024

  Effects of a Planned Web-Based Educational Intervention Based on the Health Belief Model for Patients With Ischemic Stroke in Promoting Secondary Prevention...

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  Authors List:

  • Zhuo Liu  
  • Xin Sun  
  • Zhen-Ni Guo  
  • Ye Sun  
  • Yi Yang  
  • Xiuli Yan  

  Abstract:

  Background: Some common modified vascular risk factors remain poorly controlled among stroke survivors, and educational programs may help improve these conditions. Objective: This study aimed to evaluate the effect of planned online educational intervention based on the health belief model (HBM) for promoting secondary prevention in ischemic stroke patients. Methods: An evaluation-blinded quasi-experimental trial with a historical control group was conducted. Patients admitted from March to June 2020 were assigned to the historical control group, and patients admitted between July to October 2020 were assigned to the intervention group. The control group received routine health management. The intervention group received six additional sessions based on the HBM via Tencent Meeting, an audio and video conferencing application within 3 months after discharge. Sessions were held every two weeks with each lasting approximately 40 min, and conducted in small groups, with 8～10 people in each group. The primary outcomes were changes in blood pressure (BP), low-density lipoprotein cholesterol (LDL-C), haemoglobin A1c (HbA1c), and the proportion of patients achieving the treatment target. The secondary outcomes were medication adherence and disability assessed with Morisky medicine adherence scale and modified Rankin scale, respectively. Results: In total, 315 first-ever stroke patients were analyzed. More patients in the intervention group had controlled BP (41.9% vs. 28.4%, adjusted odds ratio [aOR]: 1.93, P=.012), LDL-C (83.1% vs. 67.7%, aOR: 2.66, P=.001), and HbA1c (91.9% vs. 83.9%, aOR: 3.37, P=.035), and a significant decrease post-intervention in the systolic BP (adjusted β = -3.94, P=.021), LDL-C (adjusted β = -0.21, P=.008), and HbA1c (adjusted β = -0.27, P<.001) compared with control groups. Significant between-group differences were observed in medication adherence (79.4% vs. 63.2%, aOR: 2.31, P=.002), but not in favourable functional outcomes. Conclusions: An online education program based on HBM may be more effective than the current methods used to educate stroke patients on optimal vascular risk factors and medication adherence. Clinical Trial: The study protocol was registered in the Chinese Clinical Trial Registry (ChiCTR2000040804).

  • JMIR Mhealth Uhealth 2024;12(1):e44463

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  mHealth for Symptom and Disease...

  Apr 22, 2024

  Effectiveness of an Interactive mHealth App (EVITE) in Improving Lifestyle After a Coronary Event: Randomized Controlled Trial

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  Authors List:

  • María Ángeles Bernal-Jiménez  
  • German Calle  
  • Alejandro Gutiérrez Barrios  
  • Livia Luciana Gheorghe  
  • Celia Cruz-Cobo  
  • Nuria Trujillo-Garrido  
  • Amelia Rodríguez-Martín  
  • Josep A Tur  
  • Rafael Vázquez-García  
  • María José Santi-Cano  

  Abstract:

  Background: Coronary heart disease is one of the leading causes of mortality worldwide. Secondary prevention is essential, as it reduces the risk of further coronary events. Mobile health (mHealth) technology could become a useful tool to improve lifestyles. Objective: This study aimed to evaluate the effect of an mHealth intervention on people with coronary heart disease who received percutaneous coronary intervention. Improvements in lifestyle regarding diet, physical activity, and smoking; level of knowledge of a healthy lifestyle and the control of cardiovascular risk factors (CVRFs); and therapeutic adherence and quality of life were analyzed. Methods: This was a randomized controlled trial with a parallel group design assigned 1:1 to either an intervention involving a smartphone app (mHealth group) or to standard health care (control group). The app was used for setting aims, the self-monitoring of lifestyle and CVRFs using measurements and records, educating people with access to information on their screens about healthy lifestyles and adhering to treatment, and giving motivation through feedback about achievements and aspects to improve. Both groups were assessed after 9 months. The primary outcome variables were adherence to the Mediterranean diet, frequency of food consumed, patient-reported physical activity, smoking, knowledge of healthy lifestyles and the control of CVRFs, adherence to treatment, quality of life, well-being, and satisfaction. Results: The study analyzed 128 patients, 67 in the mHealth group and 61 in the control group; most were male (92/128, 71.9%), with a mean age of 59.49 (SD 8.97) years. Significant improvements were observed in the mHealth group compared with the control group regarding adherence to the Mediterranean diet (mean 11.83, SD 1.74 points vs mean 10.14, SD 2.02 points; P<.001), frequency of food consumption, patient-reported physical activity (mean 619.14, SD 318.21 min/week vs mean 471.70, SD 261.43 min/week; P=.007), giving up smoking (25/67, 75% vs 11/61, 42%; P=.01), level of knowledge of healthy lifestyles and the control of CVRFs (mean 118.70, SD 2.65 points vs mean 111.25, SD 9.05 points; P<.001), and the physical component of the quality of life 12-item Short Form survey (SF-12; mean 45.80, SD 10.79 points vs mean 41.40, SD 10.78 points; P=.02). Overall satisfaction was higher in the mHealth group (mean 48.22, SD 3.89 vs mean 46.00, SD 4.82 points; P=.002) and app satisfaction and usability were high (mean 44.38, SD 6.18 out of 50 points and mean 95.22, SD 7.37 out of 100). Conclusions: The EVITE app was effective in improving the lifestyle of patients in terms of adherence to the Mediterranean diet, frequency of healthy food consumption, physical activity, giving up smoking, knowledge of healthy lifestyles and controlling CVRFs, quality of life, and overall satisfaction. The app satisfaction and usability were excellent. Trial Registration: Clinicaltrials.gov NCT04118504; https://clinicaltrials.gov/study/NCT04118504

  • JMIR Mhealth Uhealth 2024;12(1):e48756

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  Evaluation and Research Methodology...

  Apr 15, 2024

  Tailored Prompting to Improve Adherence to Image-Based Dietary Assessment: Mixed Methods Study

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  Authors List:

  • Lachlan Lee  
  • Rosemary Hall  
  • James Stanley  
  • Jeremy Krebs  

  Abstract:

  Background: Accurately assessing an individual’s diet is vital in the management of personal nutrition and in the study of the effect of diet on health. Despite its importance, the tools available for dietary assessment remain either too imprecise, expensive, or burdensome for clinical or research use. Image-based methods offer a potential new tool to improve the reliability and accessibility of dietary assessment. Though promising, image-based methods are sensitive to adherence, as images cannot be captured from meals that have already been consumed. Adherence to image-based methods may be improved with appropriately timed prompting via text message. Objective: This study aimed to quantitatively examine the effect of prompt timing on adherence to an image-based dietary record, and qualitatively explore the participant experience of dietary assessment in order to inform the design of a novel image-based dietary assessment tool. Methods: This study used a randomised cross-over design to examine the intra-individual effect of three prompt settings on the number of images captured in a image-based dietary record. The prompt settings were control, where no prompts were sent; standard, where prompts were sent at 7:15 AM, 11:15 AM, and 5:15 PM for every participant; and tailored, where prompt timing was tailored to habitual meal times for each participant. Participants completed a text-based dietary record at baseline to determine the timing of tailored prompts. Participants were randomised to one of six study sequences, each with a unique order of the three prompt settings, with each three-day image-based dietary record separated by a wash-out period of at least seven days. The qualitative component comprised semi-structured interviews and questionnaires exploring the experience of dietary assessment. Results: Thirty seven people were recruited and 30 participants, (11 male, 19 female; mean (SD) age 30 (10.8) years), completed all image-based dietary records. Image rate increased by 0.83 images per day in the standard setting compared to control (P=.23) and increased by 1.78 images per day in the tailored setting compared to control (P=<.001). Sixty two percent of participants preferred to use the image-based dietary record versus the text-based dietary record but reported method-specific challenges with each method, particularly the inability to record via image after a meal had been consumed. Conclusions: Tailored prompting improves adherence to image-based dietary assessment. Future image-based dietary assessment tools should use tailored prompting and offer both image-based and written input options to improve record completeness.

  • JMIR Mhealth Uhealth 2024;12(1):e52074

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  Wearables and MHealth Reviews

  Apr 15, 2024

  mHealth-Based Gamification Interventions Among Men Who Have Sex With Men in the HIV Prevention and Care Continuum: Systematic Review and Meta-Analysis

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  Authors List:

  • Qianqian Luo  
  • Yue Zhang  
  • Wei Wang  
  • Tianyu Cui  
  • Tianying Li  

  Abstract:

  Background: Past few years has witnessed a burgeoning interest in applying gamification to promote desired health behaviors. However, little is known about the effectiveness of such applications in Human Immunodeficiency Virus (HIV) prevention and care continuum among men who have sex with men (MSM). Objective: To summarize and evaluate research on the effectiveness of gamification on HIV prevention and care continuum, including HIV testing promotion, condomless anal sex (CAS) reduction, uptake and adherence in pre-exposure prophylaxis (PrEP), post-exposure prophylaxis (PEP), and antiretroviral therapy (ART). Methods: We comprehensively searched PubMed, Embase, the Cochrane Library, Web of Science, Scopus, the Journal of Medical Internet Research and its sister journals for studies published in English and Chinese from inception to January 2024. Eligible studies were included when they used gamified interventions with an active or inactive control group and assessed at least one of the following outcomes: HIV testing, CAS, uptake and adherence of PrEP, PEP, and ART. During the meta-analysis, a random-effects model was applied. Two reviewers independently assessed the quality and risk of bias of each included study. Results: The systematic review identified 26 studies, including 10 randomized controlled trials (RCTs). The results indicated that gamified digital interventions had been applied to various HIV outcomes, such as HIV testing, CAS, PrEP uptake and adherence, PEP uptake, and ART adherence. Most of the studies were conducted in the USA (19/26, 73%). The most frequently used game component was gaining points, followed by challenges. The meta-analysis showed gamification interventions could reduce the number of CAS acts at the 3-month follow-up (Two RCTs, IRR=0.62, 95%CI: 0.44-0.88). The meta-analysis also suggested an effective but non-statistically significant effect of PrEP adherence at 3-month follow up (three RCTs, RR=1.16, 95%CI: 0.96, 1.38) and 6-month follow up (Four RCTs, RR=1.28, 95%CI: 0.89, 1.84). Only one pilot RCT was designed to evaluate the effectiveness of a gamified app in promoting HIV testing and PrEP uptake. No RCT was conducted to evaluate the effect of the gamified digital intervention on PEP uptake and adherence, and ART initiation among MSM. Conclusions: Our findings suggest the short-term effect of gamified digital interventions on lowering the number of CAS in MSM. Further well-powered studies are still needed to evaluate the effect of the gamified digital intervention on HIV testing, PrEP uptake, PEP initiation and adherence, and ART initiation in MSM. Clinical Trial: PROSPERO CRD42023392193; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=392193

  • JMIR Mhealth Uhealth 2024;12(1):e49509

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