TY - JOUR AU - MacLeod, Lucy AU - Suruliraj, Banuchitra AU - Gall, Dominik AU - Bessenyei, Kitti AU - Hamm, Sara AU - Romkey, Isaac AU - Bagnell, Alexa AU - Mattheisen, Manuel AU - Muthukumaraswamy, Viswanath AU - Orji, Rita AU - Meier, Sandra PY - 2021/10/26 TI - A Mobile Sensing App to Monitor Youth Mental Health: Observational Pilot Study JO - JMIR Mhealth Uhealth SP - e20638 VL - 9 IS - 10 KW - mobile sensing KW - youth KW - psychiatry KW - feasibility KW - mobile phone N2 - Background: Internalizing disorders are the most common psychiatric problems observed among youth in Canada. Sadly, youth with internalizing disorders often avoid seeking clinical help and rarely receive adequate treatment. Current methods of assessing internalizing disorders usually rely on subjective symptom ratings, but internalizing symptoms are frequently underreported, which creates a barrier to the accurate assessment of these symptoms in youth. Therefore, novel assessment tools that use objective data need to be developed to meet the highest standards of reliability, feasibility, scalability, and affordability. Mobile sensing technologies, which unobtrusively record aspects of youth behaviors in their daily lives with the potential to make inferences about their mental health states, offer a possible method of addressing this assessment barrier. Objective: This study aims to explore whether passively collected smartphone sensor data can be used to predict internalizing symptoms among youth in Canada. Methods: In this study, the youth participants (N=122) completed self-report assessments of symptoms of anxiety, depression, and attention-deficit hyperactivity disorder. Next, the participants installed an app, which passively collected data about their mobility, screen time, sleep, and social interactions over 2 weeks. Then, we tested whether these passive sensor data could be used to predict internalizing symptoms among these youth participants. Results: More severe depressive symptoms correlated with more time spent stationary (r=0.293; P=.003), less mobility (r=0.271; P=.006), higher light intensity during the night (r=0.227; P=.02), and fewer outgoing calls (r=?0.244; P=.03). In contrast, more severe anxiety symptoms correlated with less time spent stationary (r=?0.249; P=.01) and greater mobility (r=0.234; P=.02). In addition, youths with higher anxiety scores spent more time on the screen (r=0.203; P=.049). Finally, adding passively collected smartphone sensor data to the prediction models of internalizing symptoms significantly improved their fit. Conclusions: Passively collected smartphone sensor data provide a useful way to monitor internalizing symptoms among youth. Although the results replicated findings from adult populations, to ensure clinical utility, they still need to be replicated in larger samples of youth. The work also highlights intervention opportunities via mobile technology to reduce the burden of internalizing symptoms early on. UR - https://mhealth.jmir.org/2021/10/e20638 UR - http://dx.doi.org/10.2196/20638 UR - http://www.ncbi.nlm.nih.gov/pubmed/34698650 ID - info:doi/10.2196/20638 ER - TY - JOUR AU - Zhao, Liuhong AU - Chen, Jingfen AU - Lan, Liuying AU - Deng, Ni AU - Liao, Yan AU - Yue, Liqun AU - Chen, Innie AU - Wen, Wu Shi AU - Xie, Ri-hua PY - 2021/10/7 TI - Effectiveness of Telehealth Interventions for Women With Postpartum Depression: Systematic Review and Meta-analysis JO - JMIR Mhealth Uhealth SP - e32544 VL - 9 IS - 10 KW - telehealth KW - postpartum depression KW - anxiety KW - meta-analysis N2 - Background: Postpartum depression (PPD) is a prevalent mental health problem with serious adverse consequences for affected women and their infants. Clinical trials have found that telehealth interventions for women with PPD result in increased accessibility and improved treatment effectiveness. However, no comprehensive synthesis of evidence from clinical trials by systematic review has been conducted. Objective: The aim of this study is to evaluate the effectiveness of telehealth interventions in reducing depressive symptoms and anxiety in women with PPD. To enhance the homogeneity and interpretability of the findings, this systematic review focuses on PPD measured by the Edinburgh Postnatal Depression Scale (EPDS). Methods: PubMed, The Cochrane Library, CINAHL, PsycINFO, CNKI, and Wanfang were electronically searched to identify randomized controlled trials (RCTs) on the effectiveness of telehealth interventions for women with PPD from inception to February 28, 2021. Data extraction and quality assessment were performed independently by two researchers. The quality of included studies was assessed using the Cochrane risk-of-bias tool, and meta-analysis was performed using RevMan 5.4 software. Results: Following the search, 9 RCTs with a total of 1958 women with PPD were included. The EPDS (mean difference=?2.99, 95% CI ?4.52 to ?1.46; P<.001) and anxiety (standardized mean difference=?0.39, 95% CI ?0.67 to ?0.12; P=.005) scores were significantly lower in the telehealth group compared with the control group. Significant subgroup differences were found in depressive symptoms according to the severity of PPD, telehealth technology, specific therapy, and follow-up time (P<.001). Conclusions: Telehealth interventions could effectively reduce the symptoms of depression and anxiety in women with PPD. However, better designed and more rigorous large-scale RCTs targeting specific therapies are needed to further explore the potential of telehealth interventions for PPD. Trial Registration: PROSPERO CRD42021258541; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=258541 UR - https://mhealth.jmir.org/2021/10/e32544 UR - http://dx.doi.org/10.2196/32544 UR - http://www.ncbi.nlm.nih.gov/pubmed/34617909 ID - info:doi/10.2196/32544 ER - TY - JOUR AU - Maliwichi, Priscilla AU - Chigona, Wallace AU - Sowon, Karen PY - 2021/10/6 TI - Appropriation of mHealth Interventions for Maternal Health Care in Sub-Saharan Africa: Hermeneutic Review JO - JMIR Mhealth Uhealth SP - e22653 VL - 9 IS - 10 KW - mHealth KW - appropriation KW - mobile phones KW - model of technology appropriation KW - maternal health KW - community of purpose KW - hermeneutic literature review N2 - Background: Many maternal clients from poorly resourced communities die from preventable pregnancy-related complications. The situation is especially grave in sub-Saharan Africa. Mobile health (mHealth) interventions have the potential to improve maternal health outcomes. mHealth interventions are used to encourage behavioral change for health care?seeking by maternal clients. However, the appropriation of such interventions among maternal health clients is not always guaranteed. Objective: This study aims to understand how maternal clients appropriate mHealth interventions and the factors that affect this appropriation. Methods: This study used a hermeneutic literature review informed by the model of technology appropriation. We used data from three mHealth case studies in sub-Saharan Africa: Mobile Technology for Community Health, MomConnect, and Chipatala Cha Pa Foni. We used the search and acquisition hermeneutic circle to identify and retrieve peer-reviewed and gray literature from the Web of Science, Google Scholar, Google, and PubMed. We selected 17 papers for analysis. We organized the findings using three levels of the appropriation process: adoption, adaptation, and integration. Results: This study found that several factors affected how maternal clients appropriated mHealth interventions. The study noted that it is paramount that mHealth designers and implementers should consider the context of mHealth interventions when designing and implementing interventions. However, the usefulness of an mHealth intervention may enhance how maternal health clients appropriate it. Furthermore, a community of purpose around the maternal client may be vital to the success of the mHealth intervention. Conclusions: The design and implementation of interventions have the potential to exacerbate inequalities within communities. To mitigate against inequalities during appropriation, it is recommended that communities of purpose be included in the design and implementation of maternal mHealth interventions. UR - https://mhealth.jmir.org/2021/10/e22653 UR - http://dx.doi.org/10.2196/22653 UR - http://www.ncbi.nlm.nih.gov/pubmed/34612835 ID - info:doi/10.2196/22653 ER - TY - JOUR AU - Jiang, Nan AU - Nguyen, Nam AU - Siman, Nina AU - Cleland, M. Charles AU - Nguyen, Trang AU - Doan, Thi Hue AU - Abroms, C. Lorien AU - Shelley, R. Donna PY - 2021/10/8 TI - Adaptation and Assessment of a Text Messaging Smoking Cessation Intervention in Vietnam: Pilot Randomized Controlled Trial JO - JMIR Mhealth Uhealth SP - e27478 VL - 9 IS - 10 KW - smoking cessation KW - text messaging KW - mHealth KW - mobile health KW - low- and middle-income country KW - smoking KW - developing countries KW - SMS KW - Vietnam N2 - Background: Text message (ie, short message service, SMS) smoking cessation interventions have demonstrated efficacy in high-income countries but are less well studied in low- and middle-income countries, including Vietnam. Objective: The goal of the research is to assess the feasibility, acceptability, and preliminary efficacy of a fully automated bidirectional SMS cessation intervention adapted for Vietnamese smokers. Methods: The study was conducted in 3 phases. In phase 1, we adapted the SMS library from US-based SMS cessation programs (ie, SmokefreeTXT and Text2Quit). The adaptation process consisted of 7 focus groups with 58 smokers to provide data on culturally relevant patterns of tobacco use and assess message preferences. In phase 2, we conducted a single-arm pilot test of the SMS intervention with 40 smokers followed by in-depth interviews with 10 participants to inform additional changes to the SMS library. In phase 3, we conducted a 2-arm pilot randomized controlled trial (RCT) with 100 smokers. Participants received either the SMS program (intervention; n=50) or weekly text assessment on smoking status (control; n=50). The 6-week SMS program consisted of a 2-week prequit period and a 4-week postquit period. Participants received 2 to 4 automated messages per day. The main outcomes were engagement and acceptability which were assessed at 6 weeks (end of intervention). We assessed biochemically confirmed smoking abstinence at 6 weeks and 12 weeks. Postintervention in-depth interviews explored user experiences among a random sample of 16 participants in the intervention arm. Results: Participants in both arms reported high levels of engagement and acceptability. Participants reported using the program for an average of 36.4 (SD 3.4) days for the intervention arm and 36.0 (SD 3.9) days for the control arm. Four of the 50 participants in the intervention arm (8%) reset the quit date and 19 (38%) texted the keyword TIPS. The majority of participants in both arms reported that they always or usually read the text messages. Compared to the control arm, a higher proportion of participants in the intervention arm reported being satisfied with the program (98% [49/50] vs 82% [41/50]). Biochemically verified abstinence was higher in the intervention arm at 6 weeks (20% [10/50] vs 2% [1/50]; P=.01), but the effect was not significant at 12 weeks (12% [6/50] vs 6% [3/50]; P=.49). In-depth interviews conducted after the RCT suggested additional modifications to enhance the program including tailoring the timing of messages, adding more opportunities to interact with the program, and placing a greater emphasis on messages that described the harms of smoking. Conclusions: The study supported the feasibility and acceptability of an SMS program adapted for Vietnamese smokers. Future studies need to assess whether, with additional modifications, the program is associated with prolonged abstinence. Trial Registration: ClinicalTrials.gov NCT03219541; https://clinicaltrials.gov/ct2/show/NCT03219541 UR - https://mhealth.jmir.org/2021/10/e27478 UR - http://dx.doi.org/10.2196/27478 UR - http://www.ncbi.nlm.nih.gov/pubmed/34623318 ID - info:doi/10.2196/27478 ER - TY - JOUR AU - Ogundaini, Oaikhena Oluwamayowa AU - de la Harpe, Retha AU - McLean, Nyx PY - 2021/10/13 TI - Integration of mHealth Information and Communication Technologies Into the Clinical Settings of Hospitals in Sub-Saharan Africa: Qualitative Study JO - JMIR Mhealth Uhealth SP - e26358 VL - 9 IS - 10 KW - mHealth KW - health care professionals KW - co-design KW - hospitals KW - ActAD model KW - work activity KW - Sub-Saharan Africa KW - referrals KW - VULA mobile app KW - WhatsApp KW - mobile phone N2 - Background: There is a rapid uptake of mobile-enabled technologies in lower- and upper-middle?income countries because of its portability, ability to reduce mobility, and facilitation of communication. However, there is limited empirical evidence on the usefulness of mobile health (mHealth) information and communication technologies (ICTs) to address constraints associated with the work activities of health care professionals at points of care in hospital settings. Objective: This study aims to explore opportunities for integrating mHealth ICTs into the work activities of health care professionals at points of care in clinical settings of hospitals in Sub-Saharan Africa. Thus, the research question is, ?How can mHealth ICTs be integrated into the work activities of health care professionals at points of care in hospital settings?? Methods: A qualitative approach was adopted to understand the work activities and points at which mHealth ICTs could be integrated to support health care professionals. The techniques of inquiry were semistructured interviews and co-design activities. These techniques were used to ensure the participation of frontline end users and determine how mHealth ICTs could be integrated into the point of care in hospital settings. Purposive and snowball sampling techniques were used to select tertiary hospitals and participants for this study from South Africa and Nigeria. A total of 19 participants, including physicians, nurses, and hospital managers, were engaged in the study. Ethical clearance was granted by the University research committee and the respective hospitals. The data collected were sorted and interpreted using thematic analysis and Activity Analysis and Development model. Results: The findings show that mHealth ICTs are suitable at points where health care professionals consult with patients in the hospital clinics, remote communication is needed, and management of referrals and report writing are required. It was inferred that mHealth ICTs could be negatively disruptive, and some participants perceived the use of mobile devices while engaging with patients as unprofessional. These findings were informed by the outcomes of the interplay between human attributes and technology capabilities during the transformation of the motives of work activity into the intended goal, which is enhanced service delivery. Conclusions: The opportunities to integrate mHealth ICTs into clinical settings depend on the inefficiencies of interaction moments experienced by health care professionals at points of care during patient consultation, remote communication, referrals, and report writing. Thus, the timeliness of mHealth ICTs to address constraints experienced by health care professionals during work activities should take into consideration the type of work activity and the contextual factors that may result in contradictions in relation to technology features. This study contributes toward the design of mHealth ICTs by industry vendors and its usability evaluation for the work activity outcomes of health care professionals. UR - https://mhealth.jmir.org/2021/10/e26358 UR - http://dx.doi.org/10.2196/26358 UR - http://www.ncbi.nlm.nih.gov/pubmed/34643540 ID - info:doi/10.2196/26358 ER - TY - JOUR AU - Lacour, Matthieu AU - Bloudeau, Laurie AU - Combescure, Christophe AU - Haddad, Kevin AU - Hugon, Florence AU - Suppan, Laurent AU - Rodieux, Frédérique AU - Lovis, Christian AU - Gervaix, Alain AU - Ehrler, Frédéric AU - Manzano, Sergio AU - Siebert, N. Johan AU - PY - 2021/10/7 TI - Impact of a Mobile App on Paramedics? Perceived and Physiologic Stress Response During Simulated Prehospital Pediatric Cardiopulmonary Resuscitation: Study Nested Within a Multicenter Randomized Controlled Trial JO - JMIR Mhealth Uhealth SP - e31748 VL - 9 IS - 10 KW - cardiopulmonary resuscitation KW - drugs KW - emergency medical services KW - medication errors KW - mobile health KW - mobile apps KW - out-of-hospital cardiac arrest KW - paramedics KW - pediatrics KW - State-Trait Anxiety Inventory KW - stress N2 - Background: Out-of-hospital cardiac arrests (OHCAs) are stressful, high-stake events that are associated with low survival rates. Acute stress experienced in this situation is associated with lower cardiopulmonary resuscitation performance in calculating drug dosages by emergency medical services. Children are particularly vulnerable to such errors. To date, no app has been validated to specifically support emergency drug preparation by paramedics through reducing the stress level of this procedure and medication errors. Objective: This study aims to determine the effectiveness of an evidence-based mobile app compared with that of the conventional preparation methods in reducing acute stress in paramedics at the psychological and physiological levels while safely preparing emergency drugs during simulated pediatric OHCA scenarios. Methods: In a parent, multicenter, randomized controlled trial of 14 emergency medical services, perceived and physiologic stress of advanced paramedics with drug preparation autonomy was assessed during a 20-minute, standardized, fully video-recorded, and highly realistic pediatric OHCA scenario in an 18-month-old child. The primary outcome was participants? self-reported psychological stress perceived during sequential preparations of 4 intravenous emergency drugs (epinephrine, midazolam, 10% dextrose, and sodium bicarbonate) with the support of the PedAMINES (Pediatric Accurate Medication in Emergency Situations) app designed to help pediatric drug preparation (intervention) or conventional methods (control). The State-Trait Anxiety Inventory and Visual Analog Scale questionnaires were used to measure perceived stress. The secondary outcome was physiologic stress, measured by a single continuous measurement of the participants? heart rate with optical photoplethysmography. Results: From September 3, 2019, to January 21, 2020, 150 advanced paramedics underwent randomization. A total of 74 participants were assigned to the mobile app (intervention group), and 76 did not use the app (control group). A total of 600 drug doses were prepared. Higher State-Trait Anxiety Inventory?perceived stress increase from baseline was observed during the scenario using the conventional methods (mean 35.4, SD 8.2 to mean 49.8, SD 13.2; a 41.3%, 35.0 increase) than when using the app (mean 36.1, SD 8.1 to mean 39.0, SD 8.4; a 12.3%, 29.0 increase). This revealed a 30.1% (95% CI 20.5%-39.8%; P<.001) lower relative change in stress response in participants who used the app. On the Visual Analog Scale questionnaire, participants in the control group reported a higher increase in stress at the peak of the scenario (mean 7.1, SD 1.8 vs mean 6.4, SD 1.9; difference: ?0.8, 95% CI ?1.3 to ?0.2; P=.005). Increase in heart rate during the scenario and over the 4 drugs was not different between the 2 groups. Conclusions: Compared with the conventional method, dedicated mobile apps can reduce acute perceived stress during the preparation of emergency drugs in the prehospital setting during critical situations. These findings can help advance the development and evaluation of mobile apps for OHCA management and should be encouraged. Trial Registration: ClinicalTrials.gov NCT03921346; https://clinicaltrials.gov/ct2/show/NCT03921346 International Registered Report Identifier (IRRID): RR2-10.1186/s13063-019-3726-4 UR - https://mhealth.jmir.org/2021/10/e31748 UR - http://dx.doi.org/10.2196/31748 UR - http://www.ncbi.nlm.nih.gov/pubmed/34617916 ID - info:doi/10.2196/31748 ER - TY - JOUR AU - Chen, Hung-Chang AU - Tzeng, Shin-Shi AU - Hsiao, Yen-Chang AU - Chen, Ruei-Feng AU - Hung, Erh-Chien AU - Lee, K. Oscar PY - 2021/10/8 TI - Smartphone-Based Artificial Intelligence?Assisted Prediction for Eyelid Measurements: Algorithm Development and Observational Validation Study JO - JMIR Mhealth Uhealth SP - e32444 VL - 9 IS - 10 KW - artificial intelligence KW - AI KW - deep learning KW - margin reflex distance 1 KW - margin reflex distance 2 KW - levator muscle function KW - smartphone KW - measurement KW - eye KW - prediction KW - processing KW - limit KW - image KW - algorithm KW - observational N2 - Background: Margin reflex distance 1 (MRD1), margin reflex distance 2 (MRD2), and levator muscle function (LF) are crucial metrics for ptosis evaluation and management. However, manual measurements of MRD1, MRD2, and LF are time-consuming, subjective, and prone to human error. Smartphone-based artificial intelligence (AI) image processing is a potential solution to overcome these limitations. Objective: We propose the first smartphone-based AI-assisted image processing algorithm for MRD1, MRD2, and LF measurements. Methods: This observational study included 822 eyes of 411 volunteers aged over 18 years from August 1, 2020, to April 30, 2021. Six orbital photographs (bilateral primary gaze, up-gaze, and down-gaze) were taken using a smartphone (iPhone 11 Pro Max). The gold-standard measurements and normalized eye photographs were obtained from these orbital photographs and compiled using AI-assisted software to create MRD1, MRD2, and LF models. Results: The Pearson correlation coefficients between the gold-standard measurements and the predicted values obtained with the MRD1 and MRD2 models were excellent (r=0.91 and 0.88, respectively) and that obtained with the LF model was good (r=0.73). The intraclass correlation coefficient demonstrated excellent agreement between the gold-standard measurements and the values predicted by the MRD1 and MRD2 models (0.90 and 0.84, respectively), and substantial agreement with the LF model (0.69). The mean absolute errors were 0.35 mm, 0.37 mm, and 1.06 mm for the MRD1, MRD2, and LF models, respectively. The 95% limits of agreement were ?0.94 to 0.94 mm for the MRD1 model, ?0.92 to 1.03 mm for the MRD2 model, and ?0.63 to 2.53 mm for the LF model. Conclusions: We developed the first smartphone-based AI-assisted image processing algorithm for eyelid measurements. MRD1, MRD2, and LF measures can be taken in a quick, objective, and convenient manner. Furthermore, by using a smartphone, the examiner can check these measurements anywhere and at any time, which facilitates data collection. UR - https://mhealth.jmir.org/2021/10/e32444 UR - http://dx.doi.org/10.2196/32444 UR - http://www.ncbi.nlm.nih.gov/pubmed/34538776 ID - info:doi/10.2196/32444 ER - TY - JOUR AU - Haglo, Håvard AU - Wang, Eivind AU - Berg, Kristian Ole AU - Hoff, Jan AU - Helgerud, Jan PY - 2021/10/21 TI - Smartphone-Assisted High-Intensity Interval Training in Inflammatory Rheumatic Disease Patients: Randomized Controlled Trial JO - JMIR Mhealth Uhealth SP - e28124 VL - 9 IS - 10 KW - VO2max KW - maximal oxygen uptake KW - mobile app KW - cardiovascular health KW - quality of life KW - endurance training N2 - Background: Patients with inflammatory rheumatic diseases (IRDs) experience disease-related barriers to physical training. Compared with the general population, IRD patients are reported to have reduced maximal oxygen uptake (VO2max) and physical activity levels. Supervised high-intensity interval training (HIIT) is documented to counteract the reduced VO2max and poor cardiovascular health associated with IRDs. However, supervised HIIT is resource demanding. Objective: This study sought to investigate if self-administered 4×4-min HIIT guided by a smartphone app (Myworkout GO) could yield similar HIIT-induced effects as standard 4×4-min HIIT performed under the guidance and supervision of health care professionals. The effects studied were on VO2max and health-related quality of life (HRQoL). Methods: Forty patients (33 female patients, mean age 48 years, SD 12 years; 7 male patients, mean age 52 years, SD 11 years) diagnosed with rheumatoid arthritis, spondyloarthritis, or systemic lupus erythematosus were randomized to a supervised group (SG) or an app group (AG). Both groups were instructed to perform 4×4-min intervals with a rate of perceived exertion of 16 to 17, corresponding to 85% to 95% of the maximal heart rate, twice a week for 10 weeks. Treadmill VO2max and HRQoL measured using RAND-36 were assessed before and after the exercise period. Results: VO2max increased (P<.001) in both groups after 10 weeks of HIIT, with improvements of 3.6 (SD 1.3) mL/kg/min in the SG and 3.7 (SD 1.5) mL/kg/min in the AG. This was accompanied by increases in oxygen pulse in both groups (P<.001), with no between-group differences apparent for either measure. Improvements in the HRQoL dimensions of bodily pain, vitality, and social functioning were observed for both groups (P<.001 to P=.04). Again, no between-group differences were detected. Conclusions: High-intensity 4×4-min interval training increased VO2max and HRQoL, contributing to patients? reduced cardiovascular disease risk, improved health and performance, and enhanced quality of life. Similar improvements were observed following HIIT when IRD patients were guided using perceived exertion by health care professionals or the training was self-administered and guided by the app Myworkout GO. Utilization of the app may help reduce the cost of HIIT as a treatment strategy in this patient population. Trial Registration: ClinicalTrials.gov NCT04649528; https://clinicaltrials.gov/ct2/show/NCT04649528 UR - https://mhealth.jmir.org/2021/10/e28124 UR - http://dx.doi.org/10.2196/28124 UR - http://www.ncbi.nlm.nih.gov/pubmed/34673536 ID - info:doi/10.2196/28124 ER - TY - JOUR AU - Payne Riches, Sarah AU - Piernas, Carmen AU - Aveyard, Paul AU - Sheppard, P. James AU - Rayner, Mike AU - Albury, Charlotte AU - Jebb, A. Susan PY - 2021/10/21 TI - A Mobile Health Salt Reduction Intervention for People With Hypertension: Results of a Feasibility Randomized Controlled Trial JO - JMIR Mhealth Uhealth SP - e26233 VL - 9 IS - 10 KW - salt reduction KW - behavior change KW - mobile health KW - mHealth KW - smartphone app KW - mobile phone N2 - Background: A high-salt diet is a risk factor for hypertension and cardiovascular disease; therefore, reducing dietary salt intake is a key part of prevention strategies. There are few effective salt reduction interventions suitable for delivery in the primary care setting, where the majority of the management and diagnosis of hypertension occurs. Objective: The aim of this study is to assess the feasibility of a complex behavioral intervention to lower salt intake in people with elevated blood pressure and test the trial procedures for a randomized controlled trial to investigate the intervention?s effectiveness. Methods: This feasibility study was an unblinded, randomized controlled trial of a mobile health intervention for salt reduction versus an advice leaflet (control). The intervention was developed using the Behavior Change Wheel and comprised individualized, brief advice from a health care professional with the use of the SaltSwap app. Participants with an elevated blood pressure recorded in the clinic were recruited through primary care practices in the United Kingdom. Primary outcomes assessed the feasibility of progression to a larger trial, including follow-up attendance, fidelity of intervention delivery, and app use. Secondary outcomes were objectively assessed using changes in salt intake (measured via 24-hour urine collection), salt content of purchased foods, and blood pressure. Qualitative outcomes were assessed using the think-aloud method, and the process outcomes were evaluated. Results: A total of 47 participants were randomized. All progression criteria were met: follow-up attendance (45/47, 96%), intervention fidelity (25/31, 81%), and app use (27/31, 87%). There was no evidence that the intervention significantly reduced the salt content of purchased foods, salt intake, or blood pressure; however, this feasibility study was not powered to detect changes in secondary outcomes. Process and qualitative outcomes demonstrated that the trial design was feasible and the intervention was acceptable to both individuals and practitioners and positively influenced salt intake behaviors. Conclusions: The intervention was acceptable and feasible to deliver within primary care; the trial procedures were practicable, and there was sufficient signal of potential efficacy to change salt intake. With some improvements to the intervention app, a larger trial to assess intervention effectiveness for reducing salt intake and blood pressure is warranted. Trial Registration: International Standard Randomized Controlled Trial Number (ISRCTN): 20910962; https://www.isrctn.com/ISRCTN20910962 UR - https://mhealth.jmir.org/2021/10/e26233 UR - http://dx.doi.org/10.2196/26233 UR - http://www.ncbi.nlm.nih.gov/pubmed/34673535 ID - info:doi/10.2196/26233 ER - TY - JOUR AU - Domogalla, Lena AU - Beck, Alena AU - Schulze-Hagen, Theresa AU - Herr, Raphael AU - Benecke, Johannes AU - Schmieder, Astrid PY - 2021/10/25 TI - Impact of an eHealth Smartphone App on the Mental Health of Patients With Psoriasis: Prospective Randomized Controlled Intervention Study JO - JMIR Mhealth Uhealth SP - e28149 VL - 9 IS - 10 KW - psoriasis KW - eHealth KW - mHealth KW - telemedicine KW - teledermatology KW - patient educational program KW - disease management KW - smartphone app KW - mental health KW - mobile phone N2 - Background: Psoriasis has a negative impact on patients? physical and mental health and can lead to anxiety and depression. Disease management strategies, including educational programs and eHealth devices, have been shown to improve health care for several chronic diseases. However, such disease management strategies are lacking in the routine care of patients with psoriasis. Objective: This study aims to study the impact of a novel intervention that combines an educational program with a disease management smartphone app on the mental health of patients with psoriasis. Methods: Patients with psoriasis in the intervention group received an educational program; attended visits on weeks 0, 12, 24, 36, and 60; and had access to the study app. Patients in the control group only attended the visits. The primary endpoint was a significant reduction of scores on the Hospital Anxiety and Depression Scale (HADS). Secondary end points were reductions in Dermatology Life Quality Index score, Psoriasis Area and Severity Index score, pruritus, and pain, as well as improvements in mood and daily activities. In addition, modulating effects of sex, age, disease duration, and app use frequency were evaluated. Results: A total of 107 patients were included in the study and randomized into the control group (53/107, 49.5%) or intervention group (54/107, 50.5%). Approximately 71.9% (77/107) of the patients completed the study. A significant reduction in HADS-Depression (HADS-D) in the intervention group was found at weeks 12 (P=.04) and 24 (P=.005) but not at weeks 36 (P=.12) and 60 (P=.32). Patient stratification according to app use frequency showed a significant improvement in HADS-D score at weeks 36 (P=.004) and 60 (P=.04) and in HADS-Anxiety (HADS-A) score at weeks 36 (P=.04) and 60 (P=.05) in the group using the app less than once every 5 weeks. However, in patients using the app more than once every 5 weeks, no significant reduction in HADS-D (P=.84) or HADS-A (P=.20) score was observed over the 60-week study period compared with that observed in patients in the control group. All findings were independent of sex, age, and disease duration. Conclusions: These findings support the use of a disease management smartphone app as a valid tool to achieve long-term improvement in the mental health of patients with psoriasis if it is not used too frequently. Further studies are needed to analyze the newly observed influence of app use frequency. Trial Registration: Deutsches Register Klinischer Studien DRKS00020755; https://tinyurl.com/nyzjyvvk UR - https://mhealth.jmir.org/2021/10/e28149 UR - http://dx.doi.org/10.2196/28149 UR - http://www.ncbi.nlm.nih.gov/pubmed/34431478 ID - info:doi/10.2196/28149 ER - TY - JOUR AU - Singh, Ajit Devinder Kaur AU - Goh, Wen Jing AU - Shaharudin, Iqbal Muhammad AU - Shahar, Suzana PY - 2021/10/12 TI - A Mobile App (FallSA) to Identify Fall Risk Among Malaysian Community-Dwelling Older Persons: Development and Validation Study JO - JMIR Mhealth Uhealth SP - e23663 VL - 9 IS - 10 KW - fall risk KW - self-screening KW - mobile app KW - older person N2 - Background: Recent falls prevention guidelines recommend early routine fall risk assessment among older persons. Objective: The purpose of this study was to develop a Falls Screening Mobile App (FallSA), determine its acceptance, concurrent validity, test-retest reliability, discriminative ability, and predictive validity as a self-screening tool to identify fall risk among Malaysian older persons. Methods: FallSA acceptance was tested among 15 participants (mean age 65.93 [SD 7.42] years); its validity and reliability among 91 participants (mean age 67.34 [SD 5.97] years); discriminative ability and predictive validity among 610 participants (mean age 71.78 [SD 4.70] years). Acceptance of FallSA was assessed using a questionnaire, and it was validated against a comprehensive fall risk assessment tool, the Physiological Profile Assessment (PPA). Participants used FallSA to test their fall risk repeatedly twice within an hour. Its discriminative ability and predictive validity were determined by comparing participant fall risk scores between fallers and nonfallers and prospectively through a 6-month follow-up, respectively. Results: The findings of our study showed that FallSA had a high acceptance level with 80% (12/15) of older persons agreeing on its suitability as a falls self-screening tool. Concurrent validity test demonstrated a significant moderate correlation (r=.518, P<.001) and agreement (k=.516, P<.001) with acceptable sensitivity (80.4%) and specificity (71.1%). FallSA also had good reliability (intraclass correlation .948; 95% CI .921-.966) and an internal consistency (?=.948, P<.001). FallSA score demonstrated a moderate to strong discriminative ability in classifying fallers and nonfallers. FallSA had a predictive validity of falls with positive likelihood ratio of 2.27, pooled sensitivity of 82% and specificity of 64%, and area under the curve of 0.802. Conclusions: These results suggest that FallSA is a valid and reliable fall risk self-screening tool. Further studies are required to empower and engage older persons or care givers in the use of FallSA to self-screen for falls and thereafter to seek early prevention intervention. UR - https://mhealth.jmir.org/2021/10/e23663 UR - http://dx.doi.org/10.2196/23663 UR - http://www.ncbi.nlm.nih.gov/pubmed/34636740 ID - info:doi/10.2196/23663 ER - TY - JOUR AU - Bendtsen, Marcus AU - Bendtsen, Preben AU - Müssener, Ulrika PY - 2021/10/21 TI - Six-Month Outcomes from the NEXit Junior Trial of a Text Messaging Smoking Cessation Intervention for High School Students: Randomized Controlled Trial With Bayesian Analysis JO - JMIR Mhealth Uhealth SP - e29913 VL - 9 IS - 10 KW - smoking KW - cessation KW - text messaging KW - high school KW - randomized controlled trial KW - intervention KW - student KW - young adult KW - teenager KW - outcome KW - Bayesian KW - Sweden KW - prevalence KW - lifestyle KW - behavior N2 - Background: The prevalence of daily or occasional smoking among high school students in Sweden was approximately 20% in 2019, which is problematic since lifestyle behaviors are established in adolescence and track into adulthood. The Nicotine Exit (NEXit) Junior trial was conducted in response to a lack of evidence for the effects of text message smoking cessation interventions among high school students in Sweden. Objective: The aim of this study was to estimate the 3- and 6-month effects of a text messaging intervention among high school students in Sweden on smoking cessation outcomes. Methods: A 2-arm, single-blind randomized controlled trial was employed to estimate the effects of the intervention on smoking cessation in comparison to treatment as usual. Participants were recruited from high schools in Sweden using advertising and promotion by school staff from January 10, 2018, to January 10, 2019. Weekly or daily smokers who were willing to make a quit attempt were eligible for inclusion. Prolonged abstinence and point prevalence of smoking cessation were measured at 3 and 6 months after randomization. Results: Complete case analysis was possible on 57.9% (310/535) of the participants at 6 months, with no observed statistically significant effect on 5-month prolonged abstinence (odds ratio [OR] 1.27, 95% CI 0.73-2.20; P=.39) or 4-week smoking cessation (OR 1.42; 95% CI 0.83-2.46; P=.20). Sensitivity analyses using imputation yielded similar findings. Unplanned Bayesian analyses showed that the effects of the intervention were in the anticipated direction. The findings were limited by the risk of bias induced by high attrition (42.1%). The trial recruited high school students in a pragmatic setting and included both weekly and daily smokers; thus, generalization to the target population is more direct compared with findings obtained under more strict study procedures. Conclusions: Higher than expected attrition rates to follow-up 6 months after randomization led to null hypothesis tests being underpowered; however, unplanned Bayesian analyses found that the effects of the intervention were in the anticipated direction. Future trials of smoking cessation interventions targeting high school students should aim to prepare strategies for increasing retention to mid- and long-term follow-up. Trial Registration: IRCTN Registry ISRCTN15396225; https://www.isrctn.com/ISRCTN15396225 International Registered Report Identifier (IRRID): RR2-10.1186/s13063-018-3028-2 UR - https://mhealth.jmir.org/2021/10/e29913 UR - http://dx.doi.org/10.2196/29913 UR - http://www.ncbi.nlm.nih.gov/pubmed/34673532 ID - info:doi/10.2196/29913 ER - TY - JOUR AU - Seberger, S. John AU - Patil, Sameer PY - 2021/10/5 TI - Post-COVID Public Health Surveillance and Privacy Expectations in the United States: Scenario-Based Interview Study JO - JMIR Mhealth Uhealth SP - e30871 VL - 9 IS - 10 KW - COVID-19 KW - pandemic-tracking apps KW - privacy concerns KW - infrastructure KW - health surveillance KW - scenario KW - interview KW - thematic analysis N2 - Background: Smartphone-based apps designed and deployed to mitigate the COVID-19 pandemic may become infrastructure for postpandemic public health surveillance in the United States. Through the lenses of privacy concerns and user expectations of digital pandemic mitigation techniques, we identified possible long-term sociotechnical implications of such an infrastructure. Objective: We explored how people in the United States perceive the possible routinization of pandemic tracking apps for public health surveillance in general. Our interdisciplinary analysis focused on the interplay between privacy concerns, data practices of surveillance capitalism, and trust in health care providers. We conducted this analysis to achieve a richer understanding of the sociotechnical issues raised by the deployment and use of technology for pandemic mitigation. Methods: We conducted scenario-based, semistructured interviews (n=19) with adults in the United States. The interviews focused on how people perceive the short- and long-term privacy concerns associated with a fictional smart thermometer app deployed to mitigate the ?outbreak of a contagious disease.? In order to elicit future-oriented discussions, the scenario indicated that the app would continue functioning ?after the disease outbreak has dissipated.? We analyzed interview transcripts using reflexive thematic analysis. Results: In the context of pandemic mitigation technology, including app-based tracking, people perceive a core trade-off between public health and personal privacy. People tend to rationalize this trade-off by invoking the concept of ?the greater good.? The interplay between the trade-off and rationalization forms the core of sociotechnical issues that pandemic mitigation technologies raise. Participants routinely expected that data collected through apps related to public health would be shared with unknown third parties for the financial gain of the app makers. This expectation suggests a perceived alignment between an app-based infrastructure for public health surveillance and the broader economics of surveillance capitalism. Our results highlight unintended and unexpected sociotechnical impacts of routinizing app-based tracking on postpandemic life, which are rationalized by invoking a nebulous concept of the greater good. Conclusions: While technologies such as app-based tracking could be useful for pandemic mitigation and preparedness, the routinization of such apps as a form of public health surveillance may have broader, unintentional sociotechnical implications for individuals and the societies in which they live. Although technology has the potential to increase the efficacy of pandemic mitigation, it exists within a broader network of sociotechnical concerns. Therefore, it is necessary to consider the long-term implications of pandemic mitigation technologies beyond the immediate needs of addressing the COVID-19 pandemic. Potential negative consequences include the erosion of patient trust in health care systems and providers, grounded in concerns about privacy violations and overly broad surveillance. UR - https://mhealth.jmir.org/2021/10/e30871 UR - http://dx.doi.org/10.2196/30871 UR - http://www.ncbi.nlm.nih.gov/pubmed/34519667 ID - info:doi/10.2196/30871 ER - TY - JOUR AU - Balaskas, Andreas AU - Schueller, M. Stephen AU - Cox, L. Anna AU - Doherty, Gavin PY - 2021/10/6 TI - The Functionality of Mobile Apps for Anxiety: Systematic Search and Analysis of Engagement and Tailoring Features JO - JMIR Mhealth Uhealth SP - e26712 VL - 9 IS - 10 KW - mental health KW - cognitive behavioral therapy KW - mobile apps KW - anxiety KW - stress KW - mHealth KW - mobile phone N2 - Background: A range of mobile apps for anxiety have been developed in response to the high prevalence of anxiety disorders. Although the number of publicly available apps for anxiety is increasing, attrition rates among mobile apps are high. These apps must be engaging and relevant to end users to be effective; thus, engagement features and the ability to tailor delivery to the needs of individual users are key. However, our understanding of the functionality of these apps concerning engagement and tailoring features is limited. Objective: The aim of this study is to review how cognitive behavioral elements are delivered by anxiety apps and their functionalities to support user engagement and tailoring based on user needs. Methods: A systematic search for anxiety apps described as being based on cognitive behavioral therapy (CBT) was conducted on Android and iPhone marketplaces. Apps were included if they mentioned the use of CBT for anxiety-related disorders. We identified 597 apps, of which 36 met the inclusion criteria and were reviewed through direct use. Results: Cognitive behavioral apps for anxiety incorporate a variety of functionalities, offer several engagement features, and integrate low-intensity CBT exercises. However, the provision of features to support engagement is highly uneven, and support is provided only for low-intensity CBT treatment. Cognitive behavioral elements combine various modalities to deliver intervention content and support the interactive delivery of these elements. Options for personalization are limited and restricted to goal selection upon beginning use or based on self-monitoring entries. Apps do not appear to provide individualized content to users based on their input. Conclusions: Engagement and tailoring features can be significantly expanded in existing apps, which make limited use of social features and clinical support and do not use sophisticated features such as personalization based on sensor data. To guide the evolution of these interventions, further research is needed to explore the effectiveness of different types of engagement features and approaches to tailoring therapeutic content. UR - https://mhealth.jmir.org/2021/10/e26712 UR - http://dx.doi.org/10.2196/26712 UR - http://www.ncbi.nlm.nih.gov/pubmed/34612833 ID - info:doi/10.2196/26712 ER - TY - JOUR AU - Wu, Ko-Lin AU - Alegria, Rebeca AU - Gonzalez, Jazzlyn AU - Hu, Harrison AU - Wang, Haocen AU - Page, Robin AU - Robbins-Furman, Patricia AU - Ma, Ping AU - Tseng, Tung-Sung AU - Chen, Lei-Shih PY - 2021/10/14 TI - Characteristics and Quality of Mobile Apps Containing Prenatal Genetic Testing Information: Systematic App Store Search and Assessment JO - JMIR Mhealth Uhealth SP - e30404 VL - 9 IS - 10 KW - mobile applications KW - prenatal genetic testing KW - pregnancy KW - review KW - evaluation N2 - Background: Prenatal genetic testing is an essential part of routine prenatal care. Yet, obstetricians often lack the time to provide comprehensive prenatal genetic testing education to their patients. Pregnant women lack prenatal genetic testing knowledge, which may hinder informed decision-making during their pregnancies. Due to the rapid growth of technology, mobile apps are a potentially valuable educational tool through which pregnant women can learn about prenatal genetic testing and improve the quality of their communication with obstetricians. The characteristics, quality, and number of available apps containing prenatal genetic testing information are, however, unknown. Objective: This study aims to conduct a firstreview to identify, evaluate, and summarize currently available mobile apps that contain prenatal genetic testing information using a systematic approach. Methods: We searched both the Apple App Store and Google Play for mobile apps containing prenatal genetic testing information. The quality of apps was assessed based on the criteria adopted from two commonly used and validated mobile app scoring systems, including the Mobile Application Rating Scale (MARS) and the APPLICATIONS evaluation criteria. Results: A total of 64 mobile apps were identified. Of these, only 2 apps were developed for a specific prenatal genetic test. All others were either pregnancy-related (61/64, 95%) or genetics-related (1/64, 2%) apps that provided prenatal genetic testing information. The majority of the apps (49/64, 77%) were developed by commercial companies. The mean quality assessment score of the included apps was 13.5 (SD 2.9), which was equal to the average of possible theoretical score. Overall, the main weaknesses of mobile apps in this review included the limited number of prenatal genetic tests mentioned; incomprehensiveness of testing information; unreliable and missing information sources; absence of developmental testing with users (not evidence based); high level of readability; and the lack of visual information, customization, and a text search field. Conclusions: Our findings suggest that the quality of mobile apps with prenatal genetic testing information must be improved and that pregnant women should be cautious when using these apps for prenatal genetic testing information. Obstetricians should carefully examine mobile apps before referring any of them to their patients for use as an educational tool. Both improving the quality of existing mobile apps, and developing new, evidence-based, high-quality mobile apps targeting all prenatal genetic tests should be the focus of mobile app developers going forward. UR - https://mhealth.jmir.org/2021/10/e30404 UR - http://dx.doi.org/10.2196/30404 UR - http://www.ncbi.nlm.nih.gov/pubmed/34647898 ID - info:doi/10.2196/30404 ER - TY - JOUR AU - Sekandi, Nabbuye Juliet AU - Kasiita, Vicent AU - Onuoha, Amara Nicole AU - Zalwango, Sarah AU - Nakkonde, Damalie AU - Kaawa-Mafigiri, David AU - Turinawe, Julius AU - Kakaire, Robert AU - Davis-Olwell, Paula AU - Atuyambe, Lynn AU - Buregyeya, Esther PY - 2021/10/27 TI - Stakeholders? Perceptions of Benefits of and Barriers to Using Video-Observed Treatment for Monitoring Patients With Tuberculosis in Uganda: Exploratory Qualitative Study JO - JMIR Mhealth Uhealth SP - e27131 VL - 9 IS - 10 KW - tuberculosis KW - adherence KW - mHealth KW - video directly observed therapy KW - Uganda KW - mobile phone N2 - Background: Nonadherence to treatment remains a barrier to tuberculosis (TB) control. Directly observed therapy (DOT) is the standard for monitoring adherence to TB treatment worldwide, but its implementation is challenging, especially in resource-limited settings. DOT is labor-intensive and inconvenient to both patients and health care workers. Video DOT (VDOT) is a novel patient-centered alternative that uses mobile technology to observe patients taking medication remotely. However, the perceptions and acceptability of potential end users have not been evaluated in Africa. Objective: This study explores stakeholders? acceptability of, as well as perceptions of potential benefits of and barriers to, using VDOT to inform a pilot study for monitoring patients with TB in urban Uganda. Methods: An exploratory, qualitative, cross-sectional study with an exit survey was conducted in Kampala, Uganda, from April to May 2018. We conducted 5 focus group discussions, each comprising 6 participants. Groups included patients with TB (n=2 groups; male and female), health care providers (n=1), caregivers (n=1), and community DOT volunteer workers (n=1). The questions that captured perceived benefits and barriers were guided by domains adopted from the Technology Acceptance Model. These included perceived usefulness, ease of use, and intent to use technology. Eligible participants were aged ?18 years and provided written informed consent. For patients with TB, we included only those who had completed at least 2 months of treatment to minimize the likelihood of infection. A purposive sample of patients, caregivers, health care providers, and community DOT workers was recruited at 4 TB clinics in Kampala. Trained interviewers conducted unstructured interviews that were audio-recorded, transcribed, and analyzed using inductive content analysis to generate emerging themes. Results: The average age of participants was 34.5 (SD 10.7) years. VDOT was acceptable to most participants on a scale of 1 to 10. Of the participants, 70% (21/30) perceived it as highly acceptable, with scores ?8, whereas 30% (9/30) scored between 5 and 7. Emergent themes on perceived benefits of VDOT were facilitation of easy adherence monitoring, timely follow-up on missed doses, patient-provider communication, and saving time and money because of minimal travel to meet in person. Perceived barriers included limited technology usability skills, inadequate cellular connectivity, internet access, availability of electricity, cost of the smartphone, and use of the internet. Some female patients raised concerns about the disruption of their domestic work routines to record videos. The impact of VDOT on privacy and confidentiality emerged as both a perceived benefit and barrier. Conclusions: VDOT was acceptable and perceived as beneficial by most study participants, despite potential technical and cost barriers. Mixed perceptions emerged about the impact of VDOT on privacy and confidentiality. Future efforts should focus on training users, ensuring adequate technical infrastructure, assuring privacy, and performing comparative cost analyses in the local context. UR - https://mhealth.jmir.org/2021/10/e27131 UR - http://dx.doi.org/10.2196/27131 UR - http://www.ncbi.nlm.nih.gov/pubmed/34704961 ID - info:doi/10.2196/27131 ER - TY - JOUR AU - Shi, Boqun AU - Liu, Xi AU - Dong, Qiuting AU - Yang, Yuxiu AU - Cai, Zhongxing AU - Wang, Haoyu AU - Yin, Dong AU - Wang, Hongjian AU - Dou, Kefei AU - Song, Weihua PY - 2021/10/27 TI - The Effect of a WeChat-Based Tertiary A-Level Hospital Intervention on Medication Adherence and Risk Factor Control in Patients With Stable Coronary Artery Disease: Multicenter Prospective Study JO - JMIR Mhealth Uhealth SP - e32548 VL - 9 IS - 10 KW - WeChat KW - telemedicine KW - coronary artery disease KW - medication adherence KW - mobile phone N2 - Background: In China, ischemic heart disease is the main cause of mortality. Having cardiac rehabilitation and a secondary prevention program in place is a class IA recommendation for individuals with coronary artery disease. WeChat-based interventions seem to be feasible and efficient for the follow-up and management of chronic diseases. Objective: This study aims to evaluate the effectiveness of a tertiary A-level hospital, WeChat-based telemedicine intervention in comparison with conventional community hospital follow-up on medication adherence and risk factor control in individuals with stable coronary artery disease. Methods: In this multicenter prospective study, 1424 patients with stable coronary artery disease in Beijing, China, were consecutively enrolled between September 2018 and September 2019 from the Fuwai Hospital and 4 community hospitals. At 1-, 3-, 6-, and 12-month follow-up, participants received healthy lifestyle recommendations and medication advice. Subsequently, the control group attended an offline outpatient clinic at 4 separate community hospitals. The intervention group had follow-up visits through WeChat-based telemedicine management. The main end point was medication adherence, which was defined as participant compliance in taking all 4 cardioprotective medications that would improve the patient?s outcome (therapies included antiplatelet therapy, ?-blockers, statins, and angiotensin-converting-enzyme inhibitors or angiotensin-receptor blockers). Multivariable generalized estimating equations were used to compare the primary and secondary outcomes between the 2 groups and to calculate the relative risk (RR) at 12 months. Propensity score matching and inverse probability of treatment weighting were performed as sensitivity analyses, and propensity scores were calculated using a multivariable logistic regression model. Results: At 1 year, 88% (565/642) of patients in the intervention group and 91.8% (518/564) of patients in the control group had successful follow-up data. We matched 257 pairs of patients between the intervention and control groups. There was no obvious advantage in medication adherence with the 4 cardioprotective drugs in the intervention group (172/565, 30.4%, vs 142/518, 27.4%; RR 0.99, 95% CI 0.97-1.02; P=.65). The intervention measures improved smoking cessation (44/565, 7.8%, vs 118/518, 22.8%; RR 0.48, 95% CI 0.44-0.53; P<.001) and alcohol restriction (33/565, 5.8%, vs 91/518, 17.6%; RR 0.47, 95% CI 0.42-0.54; P<.001). Conclusions: The tertiary A-level hospital, WeChat-based intervention did not improve adherence to the 4 cardioprotective medications compared with the traditional method. Tertiary A-level hospital, WeChat-based interventions have a positive effect on improving lifestyle, such as quitting drinking and smoking, in patients with stable coronary artery disease and can be tried as a supplement to community hospital follow-up. Trial Registration: ClinicalTrials.gov NCT04795505; https://clinicaltrials.gov/ct2/show/NCT04795505 UR - https://mhealth.jmir.org/2021/10/e32548 UR - http://dx.doi.org/10.2196/32548 UR - http://www.ncbi.nlm.nih.gov/pubmed/34569467 ID - info:doi/10.2196/32548 ER - TY - JOUR AU - Woo, MinJae AU - Mishra, Prabodh AU - Lin, Ju AU - Kar, Snigdhaswin AU - Deas, Nicholas AU - Linduff, Caleb AU - Niu, Sufeng AU - Yang, Yuzhe AU - McClendon, Jerome AU - Smith, Hudson D. AU - Shelton, L. Stephen AU - Gainey, E. Christopher AU - Gerard, C. William AU - Smith, C. Melissa AU - Griffin, F. Sarah AU - Gimbel, W. Ronald AU - Wang, Kuang-Ching PY - 2021/10/12 TI - Complete and Resilient Documentation for Operational Medical Environments Leveraging Mobile Hands-free Technology in a Systems Approach: Experimental Study JO - JMIR Mhealth Uhealth SP - e32301 VL - 9 IS - 10 KW - emergency medical services KW - prehospital documentation KW - speech recognition software KW - natural language processing KW - military medicine KW - documentation KW - development KW - challenge KW - paramedic KW - disruption KW - attention KW - medical information KW - audio KW - speech recognition KW - qualitative KW - simulation N2 - Background: Prehospitalization documentation is a challenging task and prone to loss of information, as paramedics operate under disruptive environments requiring their constant attention to the patients. Objective: The aim of this study is to develop a mobile platform for hands-free prehospitalization documentation to assist first responders in operational medical environments by aggregating all existing solutions for noise resiliency and domain adaptation. Methods: The platform was built to extract meaningful medical information from the real-time audio streaming at the point of injury and transmit complete documentation to a field hospital prior to patient arrival. To this end, the state-of-the-art automatic speech recognition (ASR) solutions with the following modular improvements were thoroughly explored: noise-resilient ASR, multi-style training, customized lexicon, and speech enhancement. The development of the platform was strictly guided by qualitative research and simulation-based evaluation to address the relevant challenges through progressive improvements at every process step of the end-to-end solution. The primary performance metrics included medical word error rate (WER) in machine-transcribed text output and an F1 score calculated by comparing the autogenerated documentation to manual documentation by physicians. Results: The total number of 15,139 individual words necessary for completing the documentation were identified from all conversations that occurred during the physician-supervised simulation drills. The baseline model presented a suboptimal performance with a WER of 69.85% and an F1 score of 0.611. The noise-resilient ASR, multi-style training, and customized lexicon improved the overall performance; the finalized platform achieved a medical WER of 33.3% and an F1 score of 0.81 when compared to manual documentation. The speech enhancement degraded performance with medical WER increased from 33.3% to 46.33% and the corresponding F1 score decreased from 0.81 to 0.78. All changes in performance were statistically significant (P<.001). Conclusions: This study presented a fully functional mobile platform for hands-free prehospitalization documentation in operational medical environments and lessons learned from its implementation. UR - https://mhealth.jmir.org/2021/10/e32301 UR - http://dx.doi.org/10.2196/32301 UR - http://www.ncbi.nlm.nih.gov/pubmed/34636729 ID - info:doi/10.2196/32301 ER - TY - JOUR AU - Woulfe, Fionn AU - Fadahunsi, Philip Kayode AU - Smith, Simon AU - Chirambo, Baxter Griphin AU - Larsson, Emma AU - Henn, Patrick AU - Mawkin, Mala AU - O? Donoghue, John PY - 2021/10/12 TI - Identification and Evaluation of Methodologies to Assess the Quality of Mobile Health Apps in High-, Low-, and Middle-Income Countries: Rapid Review JO - JMIR Mhealth Uhealth SP - e28384 VL - 9 IS - 10 KW - mHealth app KW - health app KW - mobile health KW - health website KW - quality KW - quality assessment KW - methodology KW - high-income country KW - low-income country KW - middle-income country KW - LMIC KW - mobile phone N2 - Background: In recent years, there has been rapid growth in the availability and use of mobile health (mHealth) apps around the world. A consensus regarding an accepted standard to assess the quality of such apps has yet to be reached. A factor that exacerbates the challenge of mHealth app quality assessment is variations in the interpretation of quality and its subdimensions. Consequently, it has become increasingly difficult for health care professionals worldwide to distinguish apps of high quality from those of lower quality. This exposes both patients and health care professionals to unnecessary risks. Despite progress, limited understanding of the contributions of researchers in low- and middle-income countries (LMICs) exists on this topic. Furthermore, the applicability of quality assessment methodologies in LMIC settings remains relatively unexplored. Objective: This rapid review aims to identify current methodologies in the literature to assess the quality of mHealth apps, understand what aspects of quality these methodologies address, determine what input has been made by authors from LMICs, and examine the applicability of such methodologies in LMICs. Methods: This review was registered with PROSPERO (International Prospective Register of Systematic Reviews). A search of PubMed, EMBASE, Web of Science, and Scopus was performed for papers related to mHealth app quality assessment methodologies, which were published in English between 2005 and 2020. By taking a rapid review approach, a thematic and descriptive analysis of the papers was performed. Results: Electronic database searches identified 841 papers. After the screening process, 52 papers remained for inclusion. Of the 52 papers, 5 (10%) proposed novel methodologies that could be used to evaluate mHealth apps of diverse medical areas of interest, 8 (15%) proposed methodologies that could be used to assess apps concerned with a specific medical focus, and 39 (75%) used methodologies developed by other published authors to evaluate the quality of various groups of mHealth apps. The authors in 6% (3/52) of papers were solely affiliated to institutes in LMICs. A further 15% (8/52) of papers had at least one coauthor affiliated to an institute in an LMIC. Conclusions: Quality assessment of mHealth apps is complex in nature and at times subjective. Despite growing research on this topic, to date, an all-encompassing appropriate means for evaluating the quality of mHealth apps does not exist. There has been engagement with authors affiliated to institutes across LMICs; however, limited consideration of current generic methodologies for application in LMIC settings has been identified. Trial Registration: PROSPERO CRD42020205149; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=205149 UR - https://mhealth.jmir.org/2021/10/e28384 UR - http://dx.doi.org/10.2196/28384 UR - http://www.ncbi.nlm.nih.gov/pubmed/34636737 ID - info:doi/10.2196/28384 ER - TY - JOUR AU - Rahimi-Eichi, Habiballah AU - Coombs III, Garth AU - Vidal Bustamante, M. Constanza AU - Onnela, Jukka-Pekka AU - Baker, T. Justin AU - Buckner, L. Randy PY - 2021/10/6 TI - Open-source Longitudinal Sleep Analysis From Accelerometer Data (DPSleep): Algorithm Development and Validation JO - JMIR Mhealth Uhealth SP - e29849 VL - 9 IS - 10 KW - actigraphy KW - accelerometer KW - sleep KW - deep-phenotyping KW - smartphone KW - mobile phone N2 - Background: Wearable devices are now widely available to collect continuous objective behavioral data from individuals and to measure sleep. Objective: This study aims to introduce a pipeline to infer sleep onset, duration, and quality from raw accelerometer data and then quantify the relationships between derived sleep metrics and other variables of interest. Methods: The pipeline released here for the deep phenotyping of sleep, as the DPSleep software package, uses a stepwise algorithm to detect missing data; within-individual, minute-based, spectral power percentiles of activity; and iterative, forward-and-backward?sliding windows to estimate the major Sleep Episode onset and offset. Software modules allow for manual quality control adjustment of the derived sleep features and correction for time zone changes. In this paper, we have illustrated the pipeline with data from participants studied for more than 200 days each. Results: Actigraphy-based measures of sleep duration were associated with self-reported sleep quality ratings. Simultaneous measures of smartphone use and GPS location data support the validity of the sleep timing inferences and reveal how phone measures of sleep timing can differ from actigraphy data. Conclusions: We discuss the use of DPSleep in relation to other available sleep estimation approaches and provide example use cases that include multi-dimensional, deep longitudinal phenotyping, extended measurement of dynamics associated with mental illness, and the possibility of combining wearable actigraphy and personal electronic device data (eg, smartphones and tablets) to measure individual differences across a wide range of behavioral variations in health and disease. A new open-source pipeline for deep phenotyping of sleep, DPSleep, analyzes raw accelerometer data from wearable devices and estimates sleep onset and offset while allowing for manual quality control adjustments. UR - https://mhealth.jmir.org/2021/10/e29849 UR - http://dx.doi.org/10.2196/29849 UR - http://www.ncbi.nlm.nih.gov/pubmed/34612831 ID - info:doi/10.2196/29849 ER - TY - JOUR AU - Santala, E. Onni AU - Halonen, Jari AU - Martikainen, Susanna AU - Jäntti, Helena AU - Rissanen, T. Tuomas AU - Tarvainen, P. Mika AU - Laitinen, P. Tomi AU - Laitinen, M. Tiina AU - Väliaho, Eemu-Samuli AU - Hartikainen, K. Juha E. AU - Martikainen, J. Tero AU - Lipponen, A. Jukka PY - 2021/10/22 TI - Automatic Mobile Health Arrhythmia Monitoring for the Detection of Atrial Fibrillation: Prospective Feasibility, Accuracy, and User Experience Study JO - JMIR Mhealth Uhealth SP - e29933 VL - 9 IS - 10 KW - atrial fibrillation KW - ECG KW - algorithm KW - stroke KW - mHealth KW - user experience KW - Awario analysis Service KW - Suunto Movesense KW - cardiology KW - digital health KW - mobile health KW - wearable device KW - heart belt KW - arrhythmia monitor KW - heart monitor N2 - Background: Atrial fibrillation (AF) is the most common tachyarrhythmia and associated with a risk of stroke. The detection and diagnosis of AF represent a major clinical challenge due to AF?s asymptomatic and intermittent nature. Novel consumer-grade mobile health (mHealth) products with automatic arrhythmia detection could be an option for long-term electrocardiogram (ECG)-based rhythm monitoring and AF detection. Objective: We evaluated the feasibility and accuracy of a wearable automated mHealth arrhythmia monitoring system, including a consumer-grade, single-lead heart rate belt ECG device (heart belt), a mobile phone application, and a cloud service with an artificial intelligence (AI) arrhythmia detection algorithm for AF detection. The specific aim of this proof-of-concept study was to test the feasibility of the entire sequence of operations from ECG recording to AI arrhythmia analysis and ultimately to final AF detection. Methods: Patients (n=159) with an AF (n=73) or sinus rhythm (n=86) were recruited from the emergency department. A single-lead heart belt ECG was recorded for 24 hours. Simultaneously registered 3-lead ECGs (Holter) served as the gold standard for the final rhythm diagnostics and as a reference device in a user experience survey with patients over 65 years of age (high-risk group). Results: The heart belt provided a high-quality ECG recording for visual interpretation resulting in 100% accuracy, sensitivity, and specificity of AF detection. The accuracy of AF detection with the automatic AI arrhythmia detection from the heart belt ECG recording was also high (97.5%), and the sensitivity and specificity were 100% and 95.4%, respectively. The correlation between the automatic estimated AF burden and the true AF burden from Holter recording was >0.99 with a mean burden error of 0.05 (SD 0.26) hours. The heart belt demonstrated good user experience and did not significantly interfere with the patient?s daily activities. The patients preferred the heart belt over Holter ECG for rhythm monitoring (85/110, 77% heart belt vs 77/109, 71% Holter, P=.049). Conclusions: A consumer-grade, single-lead ECG heart belt provided good-quality ECG for rhythm diagnosis. The mHealth arrhythmia monitoring system, consisting of heart-belt ECG, a mobile phone application, and an automated AF detection achieved AF detection with high accuracy, sensitivity, and specificity. In addition, the mHealth arrhythmia monitoring system showed good user experience. Trial Registration: ClinicalTrials.gov NCT03507335; https://clinicaltrials.gov/ct2/show/NCT03507335 UR - https://mhealth.jmir.org/2021/10/e29933 UR - http://dx.doi.org/10.2196/29933 UR - http://www.ncbi.nlm.nih.gov/pubmed/34677135 ID - info:doi/10.2196/29933 ER - TY - JOUR AU - Follmann, Andreas AU - Ruhl, Alexander AU - Gösch, Michael AU - Felzen, Marc AU - Rossaint, Rolf AU - Czaplik, Michael PY - 2021/10/18 TI - Augmented Reality for Guideline Presentation in Medicine: Randomized Crossover Simulation Trial for Technically Assisted Decision-making JO - JMIR Mhealth Uhealth SP - e17472 VL - 9 IS - 10 KW - augmented reality KW - smart glasses KW - wearables KW - guideline presentation KW - decision support KW - triage N2 - Background: Guidelines provide instructions for diagnostics and therapy in modern medicine. Various mobile devices are used to represent the potential complex decision trees. An example of time-critical decisions is triage in case of a mass casualty incident. Objective: In this randomized controlled crossover study, the potential of augmented reality for guideline presentation was evaluated and compared with the guideline presentation provided in a tablet PC as a conventional device. Methods: A specific Android app was designed for use with smart glasses and a tablet PC for the presentation of a triage algorithm as an example for a complex guideline. Forty volunteers simulated a triage based on 30 fictional patient descriptions, each with technical support from smart glasses and a tablet PC in a crossover trial design. The time to come to a decision and the accuracy were recorded and compared between both devices. Results: A total of 2400 assessments were performed by the 40 volunteers. A significantly faster time to triage was achieved in total with the tablet PC (median 12.8 seconds, IQR 9.4-17.7; 95% CI 14.1-14.9) compared to that to triage with smart glasses (median 17.5 seconds, IQR 13.2-22.8, 95% CI 18.4-19.2; P=.001). Considering the difference in the triage time between both devices, the additional time needed with the smart glasses could be reduced significantly in the course of assessments (21.5 seconds, IQR 16.5-27.3, 95% CI 21.6-23.2) in the first run, 17.4 seconds (IQR 13-22.4, 95% CI 17.6-18.9) in the second run, and 14.9 seconds (IQR 11.7-18.6, 95% CI 15.2-16.3) in the third run (P=.001). With regard to the accuracy of the guideline decisions, there was no significant difference between both the devices. Conclusions: The presentation of a guideline on a tablet PC as well as through augmented reality achieved good results. The implementation with smart glasses took more time owing to their more complex operating concept but could be accelerated in the course of the study after adaptation. Especially in a non?time-critical working area where hands-free interfaces are useful, a guideline presentation with augmented reality can be of great use during clinical management. UR - https://mhealth.jmir.org/2021/10/e17472 UR - http://dx.doi.org/10.2196/17472 UR - http://www.ncbi.nlm.nih.gov/pubmed/34661548 ID - info:doi/10.2196/17472 ER - TY - JOUR AU - Singh, Ajit Devinder Kaur AU - Goh, Wen Jing AU - Shaharudin, Iqbal Muhammad AU - Shahar, Suzana PY - 2021/10/28 TI - Correction: A Mobile App (FallSA) to Identify Fall Risk Among Malaysian Community-Dwelling Older Persons: Development and Validation Study JO - JMIR Mhealth Uhealth SP - e34368 VL - 9 IS - 10 UR - https://mhealth.jmir.org/2021/10/e34368 UR - http://dx.doi.org/10.2196/34368 UR - http://www.ncbi.nlm.nih.gov/pubmed/34710052 ID - info:doi/10.2196/34368 ER - TY - JOUR AU - Rykov, Yuri AU - Thach, Thuan-Quoc AU - Bojic, Iva AU - Christopoulos, George AU - Car, Josip PY - 2021/10/25 TI - Digital Biomarkers for Depression Screening With Wearable Devices: Cross-sectional Study With Machine Learning Modeling JO - JMIR Mhealth Uhealth SP - e24872 VL - 9 IS - 10 KW - depression KW - digital biomarkers KW - screening KW - wearable electronic device KW - fitness tracker KW - circadian rhythm KW - rest-activity rhythm KW - heart rate KW - machine learning N2 - Background: Depression is a prevalent mental disorder that is undiagnosed and untreated in half of all cases. Wearable activity trackers collect fine-grained sensor data characterizing the behavior and physiology of users (ie, digital biomarkers), which could be used for timely, unobtrusive, and scalable depression screening. Objective: The aim of this study was to examine the predictive ability of digital biomarkers, based on sensor data from consumer-grade wearables, to detect risk of depression in a working population. Methods: This was a cross-sectional study of 290 healthy working adults. Participants wore Fitbit Charge 2 devices for 14 consecutive days and completed a health survey, including screening for depressive symptoms using the 9-item Patient Health Questionnaire (PHQ-9), at baseline and 2 weeks later. We extracted a range of known and novel digital biomarkers characterizing physical activity, sleep patterns, and circadian rhythms from wearables using steps, heart rate, energy expenditure, and sleep data. Associations between severity of depressive symptoms and digital biomarkers were examined with Spearman correlation and multiple regression analyses adjusted for potential confounders, including sociodemographic characteristics, alcohol consumption, smoking, self-rated health, subjective sleep characteristics, and loneliness. Supervised machine learning with statistically selected digital biomarkers was used to predict risk of depression (ie, symptom severity and screening status). We used varying cutoff scores from an acceptable PHQ-9 score range to define the depression group and different subsamples for classification, while the set of statistically selected digital biomarkers remained the same. For the performance evaluation, we used k-fold cross-validation and obtained accuracy measures from the holdout folds. Results: A total of 267 participants were included in the analysis. The mean age of the participants was 33 (SD 8.6, range 21-64) years. Out of 267 participants, there was a mild female bias displayed (n=170, 63.7%). The majority of the participants were Chinese (n=211, 79.0%), single (n=163, 61.0%), and had a university degree (n=238, 89.1%). We found that a greater severity of depressive symptoms was robustly associated with greater variation of nighttime heart rate between 2 AM and 4 AM and between 4 AM and 6 AM; it was also associated with lower regularity of weekday circadian rhythms based on steps and estimated with nonparametric measures of interdaily stability and autocorrelation as well as fewer steps-based daily peaks. Despite several reliable associations, our evidence showed limited ability of digital biomarkers to detect depression in the whole sample of working adults. However, in balanced and contrasted subsamples comprised of depressed and healthy participants with no risk of depression (ie, no or minimal depressive symptoms), the model achieved an accuracy of 80%, a sensitivity of 82%, and a specificity of 78% in detecting subjects at high risk of depression. Conclusions: Digital biomarkers that have been discovered and are based on behavioral and physiological data from consumer wearables could detect increased risk of depression and have the potential to assist in depression screening, yet current evidence shows limited predictive ability. Machine learning models combining these digital biomarkers could discriminate between individuals with a high risk of depression and individuals with no risk. UR - https://mhealth.jmir.org/2021/10/e24872 UR - http://dx.doi.org/10.2196/24872 UR - http://www.ncbi.nlm.nih.gov/pubmed/34694233 ID - info:doi/10.2196/24872 ER -