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JMIR mHealth and uHealth

Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.

JMIR's Thomson Reuter Impact Factor of 4.636 for 2016
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Journal Description

JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a sister journal of JMIR, the leading eHealth journal. JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, and Science Citation Index Expanded (SCIE), and in June 2017 received an impressive inaugural Impact Factor of 4.636, which ranks the journal #2 (behind JMIR) out of over 20 journals in the medical informatics category indexed by the Science Citation Index Expanded (SCIE) by Thomson Reuters/Clarivate

The journal focusses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics.

JMIR mHealth and uHealth publishes since 2013 and was the first mhealth journal in Pubmed. It publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research

JMIR mHealth and uHealth features a rapid and thorough peer-review process, professional copyediting, professional production of PDF, XHTML, and XML proofs.

JMIR mHealth and uHealth adheres to the same quality standards as JMIR and all articles published here are also cross-listed in the Table of Contents of JMIR, the worlds' leading medical journal in health sciences / health services research and health informatics.

 

Recent Articles:

  • The Impact of mHealth Interventions: Systematic Review of Systematic Reviews

    Abstract:

    Background: Mobile phone usage has been rapidly increasing worldwide. mHealth could efficiently deliver high-quality health care, but the evidence supporting its current effectiveness is still mixed. Objective: We performed a systematic review of systematic reviews to assess the impact or effectiveness of mobile health (mHealth) interventions in different health conditions and in the processes of health care service delivery. Methods: We used a common search strategy of five major scientific databases, restricting the search by publication date, language, and parameters in methodology and content. Methodological quality was evaluated using the Measurement Tool to Assess Systematic Reviews (AMSTAR) checklist. Results: The searches resulted in a total of 10,689 articles. Of these, 23 systematic reviews (371 studies; more than 79,665 patients) were included. Seventeen reviews included studies performed in low- and middle-income countries. The studies used diverse mHealth interventions, most frequently text messaging (short message service, SMS) applied to different purposes (reminder, alert, education, motivation, prevention). Ten reviews were rated as low quality (AMSTAR score 0-4), seven were rated as moderate quality (AMSTAR score 5-8), and six were categorized as high quality (AMSTAR score 9-11). A beneficial impact of mHealth was observed in chronic disease management, showing improvement in symptoms and peak flow variability in asthma patients, reducing hospitalizations and improving forced expiratory volume in 1 second; improving chronic pulmonary diseases symptoms; improving heart failure symptoms, reducing deaths and hospitalization; improving glycemic control in diabetes patients; improving blood pressure in hypertensive patients; and reducing weight in overweight and obese patients. Studies also showed a positive impact of SMS reminders in improving attendance rates, with a similar impact to phone call reminders at reduced cost, and improved adherence to tuberculosis and human immunodeficiency virus therapy in some scenarios, with evidence of decrease of viral load. Conclusions: Although mHealth is growing in popularity, the evidence for efficacy is still limited. In general, the methodological quality of the studies included in the systematic reviews is low. For some fields, its impact is not evident, the results are mixed, or no long-term studies exist. Exceptions include the moderate quality evidence of improvement in asthma patients, attendance rates, and increased smoking abstinence rates. Most studies were performed in high-income countries, implying that mHealth is still at an early stage of development in low-income countries.

  • This is the hospital-owned app from VGHTPE. One can follow up the queue of the clinic by the mobile app anytime and anywhere. Source: Image created by the Authors; Copyright: The Authors; URL: http://mhealth.jmir.org/2018/1/e22/; License: Creative Commons Attribution (CC-BY).

    Hospital-Owned Apps in Taiwan: Nationwide Survey

    Abstract:

    Background: Over the last decade, the use of mobile phone apps in the health care industry has grown rapidly. Owing to the high penetration rate of Internet use in Taiwan, hospitals are eager to provide their own apps to improve the accessibility of medical care for patients. Objective: The aims of this study were to provide an overview of the currently available hospital-owned apps in Taiwan and to conduct a cross-hospital comparison of app features. Methods: In May 2017, the availability of apps from all 414 hospitals in Taiwan was surveyed from the hospital home pages and the Google Play app store. The features of the downloaded apps were then examined in detail and, for each app, the release date of the last update, download frequency, and rating score were obtained from Google Play. Results: Among all the 414 hospitals in Taiwan, 150 (36.2%) owned Android apps that had been made available for public use, including 95% (18/19) of the academic medical centers, 77% (63/82) of the regional hospitals, and 22.0% (69/313) of the local community hospitals. Among the 13 different functionalities made available by the various hospital-owned apps, the most common were the doctor search (100%, 150/150), real-time queue monitoring (100%, 150/150), and online appointment scheduling (94.7%, 142/150) functionalities. The majority of apps (57.3%, 86/150) had a rating greater than 4 out of 5, 49.3% (74/150) had been updated at some point in 2017, and 36.0% (54/150) had been downloaded 10,000 to 50,000 times. Conclusions: More than one-third of the hospitals owned apps intended to increase patient access to health care. The most common app features might reflect the health care situation in Taiwan, where the overcrowded outpatient departments of hospitals operate in an open-access mode without any strict referral system. Further research should focus on the effectiveness and safety of these apps.

  • Source: iStock by Getty Images; Copyright: Petrunjela; URL: http://www.istockphoto.com/gb/photo/what-to-do-today-gm585288128-100343859; License: Licensed by the authors.

    Comparing Diet and Exercise Monitoring Using Smartphone App and Paper Diary: A Two-Phase Intervention Study

    Abstract:

    Background: There is increasing recognition that personalized approaches may be more effective in helping people establish healthier eating patterns and exercise more, and that this approach may be particularly effective in adolescents. Objective: The objective of this study was to investigate the use of a smartphone app (FoodWiz2) in supporting healthy lifestyle choices in adolescence. Methods: Participants (N=34: 11 male, 23 female) aged 16-19 years in full- or part-time education were recruited from sixth form colleges, schools, and other further education establishments in Norfolk and Suffolk, United Kingdom, between February and May 2015. Participants recorded food intake and exercise using a paper diary for 4-5 weeks and then used the app for the same duration. Initial nutrition education and general support were provided during the paper diary use, but the app included personalized messages sent in response to app activity. At the end of each study phase, participants completed an online questionnaire to describe their experience of using the paper diary and app. Results: Record completion declined throughout the study, possibly affected by examination pressure. Food intake data showed increased fruit consumption and significantly reduced consumption of chocolate snacks (P=.01) and fizzy drinks (P=.002) among participants using the app. Questionnaire responses indicated that the app was generally preferred to the paper diary, in particular, the app was seen as less boring to use (P=.03) and more acceptable in social settings (P<.001). Conclusions: This app-based approach has shown the potential for a more effective approach to improving adolescent diet and exercise levels.

  • Copyright: Code Innovation / SHG Platform; URL: https://www.shgplatform.com/about-us/our-story/; License: Creative Commons Attribution (CC-BY).

    Tanzania Health Information Technology (T-HIT) System: Pilot Test of a Tablet-Based System to Improve Prevention of Mother-to-Child Transmission of HIV

    Abstract:

    Background: The prevention of mother-to-child transmission (PMTCT) of HIV requires innovative solutions. Although routine monitoring is effective in some areas, standardized and easy-to-scale solutions to identify and monitor pregnant women, test them for HIV, and treat them and their children is still lacking. Mobile health (mHealth) offers opportunities for surveillance and reporting in rural areas of low- and middle-income countries. Objective: The aim of this study was to document the preliminary impacts of the Tanzania Health Information Technology (T-HIT) system mHealth intervention aimed at health workers for PMTCT care delivery and capacity building in a rural area of Tanzania. Methods: We developed T-HIT as a tablet-based system for an electronic data collection system designed to capture and report PMTCT data during antenatal, delivery, and postnatal visits in Misungwi, Tanzania. T-HIT was tested by health workers in a pilot randomized trial comparing seven sites using T-HIT assigned at random to seven control sites; all sites maintained standard paper record-keeping during the pilot intervention period. We compared numbers of antenatal visits, number of HIV tests administered, and women testing positive across all sites. Results: Health workers recorded data from antenatal visits for 1530 women; of these, 695 (45.42%) were tested for HIV and 3.59% (55/1530) tested positive. Health workers were unable to conduct an HIV test for 103 women (6.73%, 103/1530) because of lack of reagent, which is not captured on paper logs. There was no difference in the activity level for testing when comparing sites T-HIT to non-T-HIT sites. We observed a significant postintervention increase in the numbers of women testing positive for HIV compared with the preintervention period (P=.04), but this was likely not attributable to the T-HIT system. Conclusions: T-HIT had a high degree of acceptability and feasibility and is perceived as useful by health workers, who documented more antenatal visits during the pilot intervention compared with a traditional system of paper logs, suggesting potential for improvements in antenatal care for women at risk for HIV.

  • Source: Pxhere; Copyright: Pxhere; URL: https://pxhere.com/en/photo/642488; License: Public Domain (CC0).

    Usage of an Exercise App in the Care for People With Osteoarthritis: User-Driven Exploratory Study

    Abstract:

    Background: Exercise has proven to reduce pain and increase quality of life among people living with osteoarthritis (OA). However, one major challenge is adherence to exercise once supervision ends. Objective: This study aimed to identify mental and physical barriers and motivational and social aspects of training at home, and to test or further develop an exercise app. Methods: The study was inspired from participatory design, engaging users in the research process. Data were collected through focus groups and workshops, and analyzed by systematic text condensation. Results: Three main themes were found: competition as motivation, training together, and barriers. The results revealed that the participants wanted to do their training and had knowledge on exercise and pain but found it hard to motivate themselves. They missed the observation, comments, and encouragement by the supervising physiotherapist as well as their peers. Ways to optimize the training app were identified during the workshops as participants shared their experience. Conclusions: This study concludes that the long-term continuation of exercising for patients with OA could be improved with the use of a technology tailored to users’ needs, including motivational and other behavioral factors.

  • Source: Pixabay.com; Copyright: Alterfines; URL: https://pixabay.com/p-1909979/?no_redirect; License: Public Domain (CC0).

    Face-to-Face Versus Mobile Versus Blended Weight Loss Program: Randomized Clinical Trial

    Abstract:

    Background: Conventional face-to-face weight loss and weight control programs are very labor intensive for both the patient and the provider. It is unclear to what extent conventional programs can be (partially) completed by mobile health (mHealth) apps. Objective: The aim of this study was to compare the effectiveness of different weight loss programs using a combination of conventional and mobile programs among adults who are overweight (body mass index [BMI]>29 kg/m²). Methods: A single-blinded randomized controlled trial among obese adults was performed from September 2015 to March 2016. The study took place in Leuven, Belgium. Of the 102 eligible (BMI >29 kg/m²) adults, 81 (79%) completed the study. The three intervention groups consisted of a conventional face-to-face weight loss program, a weight loss app program (app group), and a partial face-to-face and partial app program (combi group). All intervention groups received the same advice from a dietician and a physical activity coach during a 12-week period. The control group did not receive any information during the same period. Primary outcomes were weight reduction (5% decrease of baseline weight in kg), BMI, metabolic risk factors, dietary pattern, and physical activity. Results: Significant more participants in all three intervention groups lost at least 5% or more of their weight at baseline compared with the control group. No significant difference was found between the combi group and the conventional group. A trend was found that more participants in the combi group lost 5% or more compared with the app group (19%), P=.06. A significant time x group effect was found for BMI and metabolic risk factors, with the control group having the worst results and the combi group being significantly better with regard to BMI compared with the app group. No significant group x time effects were found for the intake of different food and drinks and moderate to vigorous physical activity (MVPA). Conclusions: The results of this study show that a conventional weight loss program could partially be completed with an mHealth program without affecting the effectiveness. Trial Registration: Clinicaltrials.gov NCT02595671; https://clinicaltrials.gov/ct2/show/NCT02595671 (Archived by WebCite at http://www.webcitation.org/6w1H0x1Q6)

  • The Hearing Test app (montage). Source: The Authors / Mockdrop.io; Copyright: JMIR Publications; URL: https://mhealth.jmir.org/2018/1/e10/; License: Creative Commons Attribution (CC-BY).

    Hearing Tests Based on Biologically Calibrated Mobile Devices: Comparison With Pure-Tone Audiometry

    Abstract:

    Background: Hearing screening tests based on pure-tone audiometry may be conducted on mobile devices, provided that the devices are specially calibrated for the purpose. Calibration consists of determining the reference sound level and can be performed in relation to the hearing threshold of normal-hearing persons. In the case of devices provided by the manufacturer, together with bundled headphones, the reference sound level can be calculated once for all devices of the same model. Objective: This study aimed to compare the hearing threshold measured by a mobile device that was calibrated using a model-specific, biologically determined reference sound level with the hearing threshold obtained in pure-tone audiometry. Methods: Trial participants were recruited offline using face-to-face prompting from among Otolaryngology Clinic patients, who own Android-based mobile devices with bundled headphones. The hearing threshold was obtained on a mobile device by means of an open access app, Hearing Test, with incorporated model-specific reference sound levels. These reference sound levels were previously determined in uncontrolled conditions in relation to the hearing threshold of normal-hearing persons. An audiologist-assisted self-measurement was conducted by the participants in a sound booth, and it involved determining the lowest audible sound generated by the device within the frequency range of 250 Hz to 8 kHz. The results were compared with pure-tone audiometry. Results: A total of 70 subjects, 34 men and 36 women, aged 18-71 years (mean 36, standard deviation [SD] 11) participated in the trial. The hearing threshold obtained on mobile devices was significantly different from the one determined by pure-tone audiometry with a mean difference of 2.6 dB (95% CI 2.0-3.1) and SD of 8.3 dB (95% CI 7.9-8.7). The number of differences not greater than 10 dB reached 89% (95% CI 88-91), whereas the mean absolute difference was obtained at 6.5 dB (95% CI 6.2-6.9). Sensitivity and specificity for a mobile-based screening method were calculated at 98% (95% CI 93-100.0) and 79% (95% CI 71-87), respectively. Conclusions: The method of hearing self-test carried out on mobile devices with bundled headphones demonstrates high compatibility with pure-tone audiometry, which confirms its potential application in hearing monitoring, screening tests, or epidemiological examinations on a large scale.

  • Source: Shutterstock; Copyright: Ditty_about_summer; URL: https://www.shutterstock.com/image-photo/smart-phone-computer-158503835?irgwc=1&utm_medium=Affiliate&utm_campaign=TinEye&utm_source=77643&utm_term=; License: Licensed by the authors.

    Toward mHealth Brief Contact Interventions in Suicide Prevention: Case Series From the Suicide Intervention Assisted by Messages (SIAM) Randomized Controlled...

    Abstract:

    Background: Research indicates that maintaining contact either via letter or postcard with at-risk adults following discharge from care services after a suicide attempt (SA) can reduce reattempt risk. Pilot studies have demonstrated that interventions using mobile health (mHealth) technologies are feasible in a suicide prevention setting. Objective: The aim of this study was to report three cases of patients recruited in the Suicide Intervention Assisted by Messages (SIAM) study to describe how a mobile intervention may influence follow-up. Methods: SIAM is a 2-year, multicenter randomized controlled trial conducted by the Brest University Hospital, France. Participants in the intervention group receive SIAM text messages 48 hours after discharge, then at day 8 and day 15, and months 1, 2, 3, 4, 5, and 6. The study includes participants aged 18 years or older, who have attended a participating hospital for an SA, and have been discharged from the emergency department (ED) or a psychiatric unit (PU) for a stay of less than 7 days. Eligible participants are randomized between the SIAM intervention messages and a control group. In this study, we present three cases from the ongoing SIAM study that demonstrate the capability of a mobile-based brief contact intervention for triggering patient-initiated contact with a crisis support team at various time points throughout the mobile-based follow-up period. Results: Out of the 244 patients recruited in the SIAM randomized controlled trial, three cases were selected to illustrate the impact of mHealth on suicide risk management. Participants initiated contact with the emergency crisis support service after receiving text messages up to 6 months following discharge from the hospital. Contact was initiated immediately following receipt of a text message or up to 6 days following a message. Conclusions: This text message–based brief contact intervention has demonstrated the potential to reconnect suicidal individuals with crisis support services while they are experiencing suicidal ideation as well as in a period after receiving messages. As follow-up phone calls over an extended period of time may not be feasible, this intervention has the potential to offer simple technological support for individuals following discharge from the ED. Trial Registration: ClinicalTrials.gov NCT02106949; https://clinicaltrials.gov/ct2/show/NCT02106949 (Archived by WebCite at http://www.webcitation.org/6wMtAFL49)

  • Source: Pexels; Copyright: Kaboompics // Karolina; URL: https://www.pexels.com/photo/close-up-portrait-of-a-young-woman-typing-a-text-message-on-mobile-phone-6400/; License: Public Domain (CC0).

    Effectiveness and Appropriateness of mHealth Interventions for Maternal and Child Health: Systematic Review

    Abstract:

    Background: The application of mobile health (mHealth) technology in reproductive, maternal, newborn, and child health (RMNCH) is increasing worldwide. However, best practice and the most effective mHealth interventions have not been reviewed systematically. Objective: A systematic review and meta-analysis of studies of mHealth interventions for RMNCH around the world were conducted to investigate their characteristics as well as the features and effectiveness of mHealth interventions. Methods: Studies of mHealth interventions for RMNCH between January 2011 and December 2016 were retrieved from 6 databases (PubMed, EMBASE, Global Health, China National Knowledge Infrastructure, VIP Database for Chinese Technical Periodicals, and Wanfang Data Knowledge Service Medium). Comparable studies were included in a random-effects meta-analysis for both exclusive breastfeeding (EBF) and antenatal checks (ANC). Descriptive analyses were conducted for mHealth studies with a range of study designs. Results: Analyses of 245 studies were included, including 51 randomized controlled trials (RCTs). Results showed that there are increasing numbers of studies on mHealth interventions for RMNCH. Although 2 meta-analysis, one with 2 RCTs on EBF (odds ratio [OR] 2.03, 95% CI 1.34-3.08, I2=25%) and the other with 3 RCTs on ANC (OR 1.43, 95% CI 1.13-1.79, I2=78%), showed that mHealth interventions are more effective than usual care, almost half (43%) of RCTs showed negative or unclear results on mHealth interventions. Functions described in mHealth interventions were diverse, and the health stages covered were broad. However, single function or single stage appeared to be dominant among mHealth interventions compared with multiple functions or stages. Conclusions: More rigorous evaluations are needed to draw consistent conclusions and to analyze mHealth products with multiple functions, especially those popular in the app markets.

  • Source: The Authors / Mockdrop.io; Copyright: Evgenii Pustozerov & Maximilian Beck; URL: http://mhealth.jmir.org/2018/1/e6/; License: Creative Commons Attribution (CC-BY).

    Development and Evaluation of a Mobile Personalized Blood Glucose Prediction System for Patients With Gestational Diabetes Mellitus

    Abstract:

    Background: Personalized blood glucose (BG) prediction for diabetes patients is an important goal that is pursued by many researchers worldwide. Despite many proposals, only a few projects are dedicated to the development of complete recommender system infrastructures that incorporate BG prediction algorithms for diabetes patients. The development and implementation of such a system aided by mobile technology is of particular interest to patients with gestational diabetes mellitus (GDM), especially considering the significant importance of quickly achieving adequate BG control for these patients in a short period (ie, during pregnancy) and a typically higher acceptance rate for mobile health (mHealth) solutions for short- to midterm usage. Objective: This study was conducted with the objective of developing infrastructure comprising data processing algorithms, BG prediction models, and an appropriate mobile app for patients’ electronic record management to guide BG prediction-based personalized recommendations for patients with GDM. Methods: A mobile app for electronic diary management was developed along with data exchange and continuous BG signal processing software. Both components were coupled to obtain the necessary data for use in the personalized BG prediction system. Necessary data on meals, BG measurements, and other events were collected via the implemented mobile app and continuous glucose monitoring (CGM) system processing software. These data were used to tune and evaluate the BG prediction model, which included an algorithm for dynamic coefficients tuning. In the clinical study, 62 participants (GDM: n=49; control: n=13) took part in a 1-week monitoring trial during which they used the mobile app to track their meals and self-measurements of BG and CGM system for continuous BG monitoring. The data on 909 food intakes and corresponding postprandial BG curves as well as the set of patients’ characteristics (eg, glycated hemoglobin, body mass index [BMI], age, and lifestyle parameters) were selected as inputs for the BG prediction models. Results: The prediction results by the models for BG levels 1 hour after food intake were root mean square error=0.87 mmol/L, mean absolute error=0.69 mmol/L, and mean absolute percentage error=12.8%, which correspond to an adequate prediction accuracy for BG control decisions. Conclusions: The mobile app for the collection and processing of relevant data, appropriate software for CGM system signals processing, and BG prediction models were developed for a recommender system. The developed system may help improve BG control in patients with GDM; this will be the subject of evaluation in a subsequent study.

  • NeuroScreen. Source: Image created by the Authors; Copyright: The Authors; URL: http://mhealth.jmir.org/2018/1/e5/; License: Creative Commons Attribution (CC-BY).

    A Mobile App to Screen for Neurocognitive Impairment: Preliminary Validation of NeuroScreen Among HIV-Infected South African Adults

    Abstract:

    Background: Neurocognitive impairment (NCI) is one of the most common complications of HIV infection, and has serious medical and functional consequences. South Africa has 7 million people living with HIV (PLHIV) with up to three-quarters of antiretroviral therapy (ART)-naïve individuals having NCI. South Africa’s health system struggles to meet the care needs of its millions of PLHIV; screening for NCI is typically neglected due to limited clinical staff trained to administer, score, and interpret neuropsychological tests, as well as long test batteries and limited screening tools for South African populations. Without accurate, clinically useful, and relatively brief NCI screening tests that can be administered by all levels of clinical staff, critical opportunities to provide psychoeducation, behavioral planning, additional ART adherence support, and adjuvant therapies for NCI (when they become available) are missed. To address these challenges and gap in care, we developed an mHealth app screening tool, NeuroScreen, to detect NCI that can be administered by all levels of clinical staff, including lay health workers. Objective: The purpose of this study was to examine sensitivity and specificity of an adapted version of NeuroScreen to detect NCI (as determined by a gold standard neuropsychological test battery administered by a trained research psychometrist) among HIV-infected South Africans when administered by a lay health worker. Methods: A total of 102 HIV-infected black South African adults who had initiated ART at least 12 months prior were administered NeuroScreen and a gold standard neuropsychological test battery in the participants’ choice of language (ie, English or isiXhosa). Three composite z scores were calculated for NeuroScreen: (1) sum of all individual test scores, (2) sum of all individual test scores and error scores from four tests, and (3) sum of four tests (abbreviated version). Global deficit scores were calculated for the gold standard battery where a score of 0.5 or greater indicated the presence of NCI. Results: The mean age of participants was 33.31 (SD 7.46) years, most (59.8%, 61/102) had at least 12 years of education, and 81.4% (83/102) of the sample was female. Gold standard test battery results indicated that 26.5% (27/102) of the sample had NCI. Sensitivity and specificity of age-, education-, and sex-adjusted NeuroScreen scores were 81.48% and 74.67% for composite score 1, 81.48% and 81.33% for composite score 2, and 92.59% and 70.67% for composite score 3, respectively. Conclusions: NeuroScreen, a highly automated, easy-to-use, tablet-based screening test to detect NCI among English- and isiXhosa-speaking South African HIV patients demonstrated robust sensitivity and specificity to detect NCI when administered by lay health workers. NeuroScreen could help make screening for NCI more feasible. However, additional research is needed with larger samples and normative test performance data are needed.

  • Source: Pexels.com; Copyright: Porapak Apichodilok; URL: https://www.pexels.com/photo/android-blur-cellphone-cellular-346736/; License: Public Domain (CC0).

    Health Information Technology Usability Evaluation Scale (Health-ITUES) for Usability Assessment of Mobile Health Technology: Validation Study

    Abstract:

    Background: Mobile technology has become a ubiquitous technology and can be particularly useful in the delivery of health interventions. This technology can allow us to deliver interventions to scale, cover broad geographic areas, and deliver technologies in highly tailored ways based on the preferences or characteristics of users. The broad use of mobile technologies supports the need for usability assessments of these tools. Although there have been a number of usability assessment instruments developed, none have been validated for use with mobile technologies. Objective: The goal of this work was to validate the Health Information Technology Usability Evaluation Scale (Health-ITUES), a customizable usability assessment instrument in a sample of community-dwelling adults who were testing the use of a new mobile health (mHealth) technology. Methods: A sample of 92 community-dwelling adults living with HIV used a new mobile app for symptom self-management and completed the Health-ITUES to assess the usability of the app. They also completed the Post-Study System Usability Questionnaire (PSSUQ), a widely used and well-validated usability assessment tool. Correlations between these scales and each of the subscales were assessed. Results: The subscales of the Health-ITUES showed high internal consistency reliability (Cronbach alpha=.85-.92). Each of the Health-ITUES subscales and the overall scale was moderately to strongly correlated with the PSSUQ scales (r=.46-.70), demonstrating the criterion validity of the Health-ITUES. Conclusions: The Health-ITUES has demonstrated reliability and validity for use in assessing the usability of mHealth technologies in community-dwelling adults living with a chronic illness.

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  • Assessing Physical Activity in Rehabilitation after Cardiac Surgery using Wearable Technology

    Date Submitted: Jan 17, 2018

    Open Peer Review Period: Jan 17, 2018 - Mar 14, 2018

    Background: Wearable technology is finding its way in clinical practices. Physical Activity (PA) describes patient’s functional status after cardiac surgery and in remote monitoring by use of PA tr...

    Background: Wearable technology is finding its way in clinical practices. Physical Activity (PA) describes patient’s functional status after cardiac surgery and in remote monitoring by use of PA trackers. Objective: The aim of this work is to assess the usability of a wearable fitness tracker, to monitor patients who underwent coronary artery bypass surgery, by either the conventional Off-Pump procedure (OPCAB) or robotically assisted CABG (RA-MIDCAB). We hypothesized a faster recovery of functional status after RA-MIDCAB in the first weeks after discharge. Methods: Patients undergoing RA-MIDCAB or OPCAB were included. Each patient received a Fitbit Charge Heart Rate PA tracker (Fitbit Inc., San Francisco, CA, USA) following discharge. Rehabilitation progress was assessed by measuring the number of steps and physical activity level (PAL) daily. PAL was calculated as energy expenditure divided by basic metabolic rate. Results: 10 RA-MIDCAB patients with a median age of 68 (IQR: [60;76]) and 12 OPCAB patients with a median age of 69 (IQR: [65;76]) were included. Baseline characteristics were comparable except for BMI (RA-MIDCAB: 26 Kg/m² [24;27] versus OPCAB: 29 Kg/m² [27;31]; P<0.001, respectively). Intubation time (P<0.05) was significantly lower in the RA-MIDCAB group. A clear trend, although not statistically significant, was observed towards a higher number of steps in RA-MIDCAB patients in the first week following discharge. Conclusions: Wearable PA trackers can describe functional status in a cardiac rehabilitation setting after surgery. RA-MIDCAB patients have an advantage in recovery in the first weeks of revalidation reflected by the number of steps and PAL, measured by the Fitbit Charge HR, compared to OPCAB patients. However, unsupervised assessment of daily PA varied greatly and this could involve consequences for the use of these trackers as research tools. Clinical Trial: S59757

  • Using video technology to increase treatment completion for patients with latent tuberculosis infection on 3-months isoniazid and rifapentine

    Date Submitted: Jan 16, 2018

    Open Peer Review Period: Jan 16, 2018 - Mar 13, 2018

    Background: Since January 2013 the New York City (NYC) Health Department TB Program has offered persons diagnosed with latent tuberculosis infection (LTBI) the 3-month, once-weekly isoniazid and rifap...

    Background: Since January 2013 the New York City (NYC) Health Department TB Program has offered persons diagnosed with latent tuberculosis infection (LTBI) the 3-month, once-weekly isoniazid and rifapentine (3HP) treatment regimen. Patients on this treatment are monitored in-person under directly observed therapy (DOT). To address patient and provider barriers to in-person DOT, we piloted the used a videoconferencing software application to remotely conduct DOT (VDOT) for patients on 3HP. Objective: We evaluated the implementation of VDOT for patients on 3HP and whether treatment completion for patients on 3HP increased when monitored using VDOT compared to using the standard in-person DOT. Methods: Between February and October 2015, patients diagnosed with LTBI at any of the four NYC Health Department TB clinics who met eligibility criteria for treatment with 3HP under VDOT (V3HP) were followed-up until treatment completion or 16 weeks after treatment initiation, whichever came first. Treatment completion of V3HP patients were compared to historical data on treatment completion of patients on 3HP under clinic-based in-person DOT. Outcomes of video sessions with V3HP patients were collected and analyzed. Results: During the pilot period, 50 (70%) of 71 eligible patients were place on V3HP. Treatment completion among V3HP patients was 88% (44/50) compared to 65% (196/302) among 3HP patients on clinic DOT (P < .001). A total of 360 video sessions were conducted for V3HP patients with a median of 8 sessions per patient (range: 1-11), and a median time of 4 minutes (range: 1-59 minutes) per session. Adherence issues (e.g. >15 minutes late) during video sessions occurred 104 times. No major side effects were reported by V3HP patients. Conclusions: The NYC TB program observed higher treatment completion among patients on 3HP with VDOT than historically seen with clinic DOT. Expanding the use of VDOT may improve treatment completion and corresponding outcomes for LTBI.

  • The Conceptual Modeling of Interoperability Framework of Heart Sound Monitor

    Date Submitted: Jan 14, 2018

    Open Peer Review Period: Jan 15, 2018 - Mar 12, 2018

    Background: Heart sound monitor (HSM), a device suitable for home-use, can be used to record heart sounds and to store, transmit or analyze those recordings. It enables cardiac reserve telemonitoring...

    Background: Heart sound monitor (HSM), a device suitable for home-use, can be used to record heart sounds and to store, transmit or analyze those recordings. It enables cardiac reserve telemonitoring which has been largely evolved and widely used in recent years. Nevertheless, the designers of HSM paid little attention to the consistency of its information model and data interaction, and because of that, the collected heart sounds data could not be shared and aggregated effectively. Thus, the device’s development and its application in telehealth service are hindered. Objective: In order to solve the above problem and to build interoperability for HSM devices, this paper proposes a HSM interoperability framework that is composed of the hierarchical information model and the transport-independent interaction model, which is constructed by using standardized modeling methods. Methods: The authors collected and studied the common device-output information of HSM involved in the cardiac reserve telemonitoring, leveraged the standardized interoperability framework defined in ISO/IEEE 11073 Personal Health Device (11073-PHD) standards to model the static data structure and dynamic interaction behaviors of HSM. Results: Via the meta analysis, the authors identified that the common device-output information of HSM mainly includes the phonocardiogram (PCG), the feature parameters of PCG, the ratio of diastolic to systolic duration (D/S), for example, and the threshold data, device status, sensor location, etc. Based on such information, an 11073-PHD-compliant domain information model has been successfully created. This enables the interoperability between HSM and aggregation device, allowing inter-device plug&play using service model and communication model. A prototype of this design has been implemented and validated via the Continua Enabling Software Library. Conclusions: The ISO/IEEE 11073-PHD standard framework has the potential to accommodate the HSM device. The standard-compliant domain information models can be established to cover the common HSM device-output information. Findings in this paper may be taken as a reference for standard developing organizations to establish a standardized interoperability framework for HSM.

  • Popular Nutrition-Related Mobile Apps: A Relative Reliability Assessment

    Date Submitted: Jan 14, 2018

    Open Peer Review Period: Jan 14, 2018 - Mar 11, 2018

    Background: Nutrition-related apps are commonly used to provide information about the users’ dietary intake, but limited research has been performed on the evaluation of their reliability. Objective...

    Background: Nutrition-related apps are commonly used to provide information about the users’ dietary intake, but limited research has been performed on the evaluation of their reliability. Objective: To evaluate the relative reliability of popular nutrition-related apps for the assessment of energy and available macro- and micronutrients against a standard method. Methods: Dietary analysis of 24-hour weighed food records (n = 20) were compared between five nutrition-related apps: S Health, MyFitnessPal, FatSecret, Noom Coach and Lose It!, and DietPlan6 (reference method). Estimates of energy, macronutrients (carbohydrate, protein, fat, saturated fat and fibre) and micronutrients (sodium, calcium, iron, vitamin A and vitamin C) were compared using t-tests and Wilcoxon signed-rank tests, correlation coefficients and Bland-Altman plots. 24-hour weighed food records from 20 participants (female/male, 15/5; mean age, 36.3 years; mean body mass index, 22.9 kg/m2) recruited from previous controlled studies conducted at the Hugh Sinclair Unit of Human Nutrition, University of Reading, UK. Results: No significant difference in estimation of energy and saturated fat intake between DietPlan6 and the diet apps was observed. Estimates of protein and sodium intake were significantly lower using Lose It! and FatSecret than DietPlan6. Lose It! also gave significantly lower estimates for other reported outputs: carbohydrate, fat, fibre and sodium, compared with DietPlan6. For S Health and MyFitnessPal, calcium, iron and vitamin C were all significantly under-estimated compared with DietPlan6, although there was no significant difference for vitamin A. No other significant differences were observed between DietPlan6 and the apps. Correlation coefficients ranged from -0.12 for iron (S Health vs. DietPlan6) to 0.91 for protein (FatSecret vs DietPlan6). Noom Coach was limited to energy output but it had a high correlation with DietPlan6 (r=0.91) and S Health had the greatest variation of correlation, with energy at 0.79. Bland-Altman analysis revealed potential proportional bias for vitamin A. Conclusions: The findings suggest that the apps provide comparable estimates of energy and saturated fat intake compared with DietPlan6. With the exception of Lose It!, the apps also provided comparable estimates of carbohydrate, total fat and fibre. Two apps displayed a tendency to underestimate protein and sodium (FatSecret and Lose It!). Apart from vitamin A, the estimates of micronutrient intake (calcium, iron and vitamin C) by the two apps (S Health and MyFitnessPal) were inconsistent and less reliable. Lose It! was the less comparable app in relation to DietPlan6. As the use and availability of apps grows, this study helps clinicians and researchers to make better-informed decisions about using these apps in research and practice.

  • Usability Study on Mobile Data Collection Support for Large-Scale Healthcare Scenarios

    Date Submitted: Jan 12, 2018

    Open Peer Review Period: Jan 13, 2018 - Mar 10, 2018

    Background: Many research domains still heavily rely on paper-based data collection procedures despite numerous drawbacks. However, the QuestionSys framework is intended to empower researchers as well...

    Background: Many research domains still heavily rely on paper-based data collection procedures despite numerous drawbacks. However, the QuestionSys framework is intended to empower researchers as well as clinicians with no programming skills to develop their own smart mobile applications in order to collect data in their specific scenarios. Objective: In order to validate the feasibility of this model-driven end-user programming approach, a study with N=80 participants was conducted. Methods: Across 2 sessions (7 days between Session 1 and Session 2), participants had to model 10 data collection instruments (5 at each session) with the developed configurator component. Thereby, performance measures like time and operations needed and the resulting errors were evaluated. Participants were separated in two groups (i.e., novices vs. experts) based on prior knowledge in process modeling, which is one fundamental pillar of the QuestionSys approach. Results: T-tests revealed that novices showed significant learning effects in errors, operations, and time during the use of the configurator (all p < .05) and experts showed learning effects in operations and time (both p < .05) but not in errors as the experts' errors were already very low at the first modeling of a data collection instrument. Moreover, regarding time and operations needed, novices got significantly better after 3rd modeling task than experts were after the 1st one (t-Tests; both p < .05). With regard to errors, novices did not get significantly better at any of the 10 data collection instruments than experts were at the 1st modeling task, but novices' error rates in all 5 data collection instruments at Session 2 were not significantly different anymore from the ones of experts at the 1st modeling task. During the 7 days without using the configurator (from Session 1 to Session 2), the experts' learning effect of Session 1 remained stable, but the novices' learning effect of Session 1 lessened significantly regarding time and operations (t-Tests; both p < .05). Conclusions: In conclusion, novices are able to use the configurator properly and show fast (but still instable) learning effects so that they become as good as experts already after little experience with the configurator. Researchers and clinicians can use the QuestionSys configurator to develop data collection applications for smart mobile devices on their own.

  • A Systematic Review of Mindfulness-Based Apps for Adults with a COPD or Lung Cancer History

    Date Submitted: Jan 12, 2018

    Open Peer Review Period: Jan 12, 2018 - Mar 9, 2018

    Background: Up to 70% of lung cancer survivors are also affected by chronic obstructive pulmonary disease (COPD), a common, debilitating, comorbid disease characterized by symptoms such as breathlessn...

    Background: Up to 70% of lung cancer survivors are also affected by chronic obstructive pulmonary disease (COPD), a common, debilitating, comorbid disease characterized by symptoms such as breathlessness and fatigue. These distressing symptoms detract from a survivor’s quality of life Objective: To identify and evaluate evidence-based, commercially available apps for promoting mindfulness-based strategies among adults with a COPD or lung cancer history. Methods: An interdisciplinary research team used 19 keyword combinations in the search engines of Google and iOS app stores in May 2017. Evaluations were conducted on apps’ (1) content, (2) usability heuristics, (3) grade-level readability, and (4) cultural sensitivity. Results: The search resulted in 768 apps (508 in iOS and 260 in Google stores). Nine apps met the inclusion criteria and received further evaluation. Only one app had below an eighth-grade reading level; the ninth did not have enough text to calculate a readability score. None of the 9 apps met the cultural sensitivity evaluation criteria. Conclusions: This systematic review identified critical design flaws that may affect the ease of using the apps in this study. Few mobile apps promote mindfulness-based strategies among adults with a COPD or lung cancer history, but those that exist, overall, do not meet the latest scientific evidence. Recommendations include more stringent regulation of health-related apps; use of evidence-based frameworks and participatory design processes; following evidence-based usability practices; use of culturally sensitive language and images; and ensuring that content is written in plain language. Clinical Trial: N/A

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