Use Of mHealth Technologies Research Articles

Screening for atrial fibrillation in hypertensive patients using a mobile application (about 160 cases)

Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting between 1 and 4% of the general population and responsible for 10 to 20% of strokes. New technologies are now available for screening for AF, but their implementation in real clinical settings has not yet been fully investigated. The aim of our study is to evaluate the electrocardiogram (ECG) recordings on smartphones intended for screening for AF using the KardiaMobile device (Alivecor), a portable device 5 cm long and 80 g in weight, with a dedicated mobile application. Prospective screening for AF in patients aged 55 or over, known to be hypertensive for at least 5 years, was performed at the cardiology consultation services between June 2019 and July 2020. exclusion from the study. The CHA2DS2-VASc score was collected from each patient. A single lead ECG was acquired by placing the fingers of each hand on the electrodes. The diagnosis of the Kardia app was assessed by the consultation cardiologist, and a baseline ECG was performed for each suspected arrhythmia. A total of 160 ECGs were performed. The diagnosis of the Kardia app was provided in 93% of cases. A heart rhythm described as normal was detected in 120 consultants, in an atrial fibrillation was suspected in 8.1% of the patients described by the device as possible AF, and confirmed by a baseline ECG in 7.5% of the patients screened ( Fig. 1 ). Anti-coagulation was started in 6.2% of patients based on the CHADS-VASC score. The Kardia app is able to quickly filter and detect AF with high sensitivity and specificity. The possible diagnosis of possible AF warrants further cardiological evaluation screening through the use of mHealth technology could be an effective tool in patients at cardiovascular risk for better prevention.

Use of mHealth technology for modification of behavioural risk factors of noncommunicable diseases in primary health care settings

Noncommunicable diseases (NCDs) kill 41 million people each year, of which more than three-quarters occur in low- and middle-income countries. Four groups of diseases, namely cardiovascular diseases, cancers, respiratory diseases, and diabetes, account for over 80% of all premature NCD deaths, and four common modifiable behaviors, namely tobacco use, physical inactivity, unhealthy diet, and the harmful use of alcohol, increase the risk of NCDs. The use of mHealth interventions for Behavior Change Communication has been shown to be effective in modifying the behavioral risk factors, through various studies. The present study proposes to conduct a systematic review and meta-analysis to assess the effectiveness and feasibility of the use of mHealth in improving diet and increasing physical activity, which are two of the major behavioral risk factors of NCDs. Research reported on this, from countries in the South-East Asian Region, during the past 20 years, will be included in this review.

Use of mHealth Technology for Patient-Reported Outcomes in Community-Dwelling Adults with Acquired Brain Injuries: A Scoping Review.

The purpose of our scoping review was to describe the current use of mHealth technology for long-term assessment of patient-reported outcomes in community-dwelling individuals with acquired brain injury (ABI). Following PRISMA guidelines, we conducted a scoping review of literature meeting these criteria: (1) civilians or military veterans, all ages; (2) self-reported or caregiver-reported outcomes assessed via mobile device in the community (not exclusively clinic/hospital); (3) published in English; (4) published in 2015–2019. We searched Ovid MEDLINE(R) < 1946 to 16 August 2019, MEDLINE InProcess, EPub, Embase, and PsycINFO databases for articles. Thirteen manuscripts representing 12 distinct studies were organized by type of ABI [traumatic brain injury (TBI) and stroke] to extract outcomes, mHealth technology used, design, and inclusion of ecological momentary assessment (EMA). Outcomes included post-concussive, depressive, and affective symptoms, fatigue, daily activities, stroke risk factors, and cognitive exertion. Overall, collecting patient-reported outcomes via mHealth was feasible and acceptable in the chronic ABI population. Studies consistently showed advantage for using EMA despite variability in EMA timing/schedules. To ensure best clinical measurement, research on post-ABI outcomes should consider EMA designs (versus single time-point assessments) that provide the best timing schedules for their respective aims and outcomes and that leverage mHealth for data collection.

ARIA 2019: An Integrated Care Pathway for Allergic Rhinitis in Portugal

The Allergic Rhinitis and Its Impact on Asthma (ARIA) initiative started more than 20 years ago and has developed and disseminated evidence-based guidelines and projects in the field of allergic rhinitis. This initiative is currently focused on providing patient-centred guidelines that contribute to an integrated care pathway between the various levels of care and take advantage of digital solutions, and the introduction of integrated care pathways in clinical practice has been recommended. In this article we describe the adaptation for Portugal of the ARIA Integrated Care Pathways document. After a brief review of the epidemiology and impact of allergic rhinitis in Portugal and the activities carried out in Portugal within the ARIA initiative, we describe the broad knowledge base used for the development of recommendations for the pharmacological treatment of allergic rhinitis, and these recommendations are based on the GRADE methodology, real world evidence acquired by mobile technology (mHealth) and resulting from allergenic exposure chamber studies. What follows is a summary of integrated care pathways for allergen immunotherapy produced in 2019. Allergen immunotherapy is considered an example of precision medicine where the use of mHealth technologies will improve stratification for patient selection and response monitoring. These recommendations were considered as best practices of integrated patient-centred care supported by digital systems from Directorate General for Health and Food Safety of the European Union (DG Santé) and represent the ARIA Phase 4 Change Management strategy.

Associations Between Mobile Health Technology use and Self-rated Quality of Life: A Cross-sectional Study on Older Adults with Cognitive Impairment

Background: Quality of life (QoL) is affected even at early stages in older adults with cognitive impairment. The use of mobile health (mHealth) technology can offer support in daily life and improve the physical and mental health of older adults. However, a clarification of how mHealth technology can be used to support the QoL of older adults with cognitive impairment is needed. Objective: To investigate factors affecting mHealth technology use in relation to self-rated QoL among older adults with cognitive impairment. Methods: A cross-sectional research design was used to analyse mHealth technology use and QoL in 1,082 older participants. Baseline data were used from a multi-centered randomized controlled trial including QoL, measured by the Quality of Life in Alzheimer’s Disease (QoL-AD) Scale, as the outcome variable. Data were analyzed using logistic regression models. Results: Having moderately or high technical skills in using mHealth technology and using the internet via mHealth technology on a daily or weekly basis was associated with good to excellent QoL in older adults with cognitive impairment. Conclusions: The variation in technical skills and internet use among the participants can be interpreted as an obstacle for mHealth technology to support QoL.

MHealth applications to support caregiver needs and engagement during stroke recovery: A content review.

Caregiving in stroke results in severe physical, psychological, and social impacts on the caregiver. Over the past few years, researchers have explored the use of mHealth technologies to support healthcare-related activities due to their ability to provide real-time care at any given place or time. The purpose of this content review is to investigate mHealth apps in supporting stroke caregiving engagement based on three aspects: motivation, value, and satisfaction. We searched app stores and repositories for apps related to stroke caregiving published up to September 2020. Extracted apps were reviewed and filtered using inclusion criteria, and then downloaded onto compatible devices to determine eligibility. Results were compared with evidence-based frameworks to identify the ability of these apps in engaging and supporting the caregiver. Forty-seven apps were included in this review that enabled caregivers to support their needs, such as adjustment to new roles and relationships, involvement in care and caring for oneself using several different functionalities. These functionalities include information resources, risk assessment, remote monitoring, data sharing, reminders and so on. However, no single app was identified that focuses on all aspects of stroke caregiving. We also identified several challenges faced by users through their reviews and the factors associated with value and satisfaction. Our findings can add to the knowledge of existing mHealth technologies and their functionalities to support stroke caregiving needs, and the importance of considering user engagement in the design. They can be used by developers and researchers looking to design better mHealth apps for stroke caregiving.

PDB64 Use of Mobile Health Intervention for the Self-Management in Patients with Diabetes Mellitus: A Systematic Literature Review and Meta-Analysis of Randomized Controlled Trials

Mobile health (mHealth) intervention based on smartphone applications (apps) emerged as an important diagnostic measure to help improve diabetes care and self-management. Until today, no studies highlighted the effect of prescribable mHealth apps on diabetes mellitus (DM). Therefore, this study was designed to perform a systematic review and meta-analysis of randomized controlled trials (RCTs) to assess the effect of mHealth apps on DM patients. A systematic literature search in Embase, Medline, and Cochrane CENTRAL through Ovid was conducted to identify RCTs comparing mHealth apps with control (standard care). Mean difference (MD) with 95% confidence interval (CI) were calculated using the random/fixed effect model to evaluate the effect of mHealth apps on HbA1c, blood glucose (BG), and body mass index (BMI) in DM patients. Of 1086 retrieved articles, seven RCTs with 546 patients from four geographies (US, Europe, Australia and China) were included. Four studies reported outcomes of type 1 DM patients, two studies included type 2 DM patients and one study included both. Mean duration of DM was 5-18 years. The most commonly reported mhealth apps from included RCTs are DBEES, Glucose Buddy, Diabeo System, mDiab, Few Touch Application, Welldoc, or Welltang. Pooled results from the meta-analysis of included RCTs reported a significant improvement in HbA1c (MD: -0.42, 95%CI: -0.69, -0.16; P=0.002; I2=42%) and BG level (MD: -1.1, 95%CI: -1.75, -0.45; P=0.0009; I2=0%) with mHealth apps group as compared to control group. However, no significant improvement was observed in the BMI (MD: -0.9, 95%CI: -2.84, 1.03; P=0.36; I2=54%) with mHealth apps group when compared to control group. Meta-analysis of included RCTs suggested that mHealth apps used by the DM patients may improve HbA1c level and could be considered as an adjuvant to the standard self-management for the DM patients. Further studies are warranted to standardize the use of mHealth technology.

Comparison of Mobile Health Technology Use for Self-Tracking Between Older Adults and the General Adult Population in Canada: Cross-Sectional Survey.

BackgroundThe burden of population aging and chronic conditions has been reported worldwide. Older adults, especially those with high needs, experience social isolation and have high rates of emergency visits and limited satisfaction with the care they receive. Mobile health (mHealth) technologies present opportunities to address these challenges. To date, limited information is available on Canadian older adults’ attitudes toward and use of mHealth technologies for self-tracking purposes—an area that is increasingly important and relevant during the COVID-19 era.ObjectiveThis study presents contributions to an underresearched area on older adults and mHealth technology use. The aim of this study was to compare older adults’ use of mHealth technologies to that of the general adult population in Canada and to investigate the factors that affect their use.MethodsA cross-sectional survey on mHealth and digital self-tracking was conducted. A web-based questionnaire was administered to a national sample of 4109 Canadian residents who spoke either English or French. The survey instrument consisted of 3 sections assessing the following items: (1) demographic characteristics, health status, and comorbidities; (2) familiarity with and use of mHealth technologies (ie, mobile apps, consumer smart devices/wearables such as vital signs monitors, bathroom scales, fitness trackers, intelligent clothing); and (3) factors influencing the continued use of mHealth technologies.ResultsSignificant differences were observed between the older adults and the general adult population in the use of smart technologies and internet (P<.001). Approximately 47.4% (323/682) of the older adults in the community reported using smartphones and 49.8% (340/682) indicated using digital tablets. Only 19.6% (91/463) of the older adults using smartphones/digital tablets reported downloading mobile apps, and 12.3% (47/383) of the older adults who heard of smart devices/wearables indicated using them. The majority of the mobile apps downloaded by older adults was health-related; interestingly, their use was sustained over a longer period of time (P=.007) by the older adults compared to that by the general population. Approximately 62.7% (428/682) of the older adults reported tracking their health measures, but the majority did so manually. Older adults with one or more chronic conditions were mostly nontrackers (odds ratio 0.439 and 0.431 for traditional trackers and digital trackers, respectively). No significant differences were observed between the older adults and the general adult population with regard to satisfaction with mHealth technologies and their intention to continue using them.ConclusionsLeveraging mHealth technologies in partnership with health care providers and sharing of health/well-being data with health care professionals and family members remain very limited. A culture shift in the provision of care to older adults is deemed necessary to keep up with the development of mHealth technologies and the changing demographics and expectations of patients and their caregivers.

MHealth as a primary mode of intervention for women at risk of, or diagnosed with, gestational diabetes: a scoping review protocol.

To synthesize current knowledge on the use of mHealth as a primary mode of intervention for the prevention and management of gestational diabetes mellitus and its long-term implications among women at risk of, or diagnosed with, gestational diabetes mellitus. Prevention and management of gestational diabetes mellitus and its associated adverse outcomes are of paramount importance to both maternal and infant health. However, women with experience of gestational diabetes mellitus report several barriers to effective disease management and lifestyle change. Supporting women through use of mHealth technology may help overcome these barriers. Recent evidence suggests mobile apps may be useful for the prevention and management of gestational diabetes mellitus, however, less is known about the broader application of mHealth from preconception to interconception. Studies considered for inclusion are those focused on the use of mHealth as the primary mode of intervention for the prevention and management of gestational diabetes mellitus and its long-term implications among women at risk of, or diagnosed with, gestational diabetes mellitus. Studies will be limited to those published in English, with no date restrictions. The following databases will be searched: MEDLINE (Ovid), CINAHL (EBSCO), EMBASE (Ovid), Cochrane Database (Wiley), Scopus, and TRIP. Unpublished studies and gray literature will be searched using Open Grey, ISRCTN Registry, ClinicalTrials.gov, EU Clinical Trials register, and ANZCTR. Two reviewers will independently screen abstracts. Reviewers will assess full texts of selected citations against the inclusion criteria. Any disagreements will be discussed with a third reviewer. Data will be extracted and presented in diagrammatic or tabular form with an accompanying narrative in line with review objectives.

Patient Use of Cardiovascular Devices and Apps: Are We Getting Our Money's Worth?

The evolution of technology makes it likely that a large number of people will invest in and use health-related mobile applications and wearable devices. Yet the question remains: Do these technology-based interventions modify health behavior and improve health…and are we getting our money's worth? The vast majority of studies concerning health-related apps and wearable devices have small sample sizes and short time spans of 6 months or less, so it is not clear if these durations were determined by lack of consistent use over time. Furthermore, many of the most popular applications have not been subjected to randomized trials. Overall, the small demonstrated improvements in outcomes are often associated with professional involvement from clinicians, coaches, or diabetes educators provided in conjunction with use of mobile health (mHealth) platforms. This paper explores the use of mHealth technologies that address cardiovascular disease/prevention (eg, diabetes, diet, physical activity, and associated weight loss) and discusses the lack of adequate evidence to support even minimal patient investment in mobile applications or wearable devices at this time.

Mobile Health Technology for Hypertension Management: A Systematic Review

Hypertension is a chronic condition, and a major risk factor for other chronic conditions requires management. Considering the growth and extensive use of mobile health (mHealth) technologies and their capabilities, it is essential to examine the effects of these technologies on hypertension control and self-management. The present systematic review examined the effect of using mHealth technologies in controlling blood pressure and investigated the functionalities of mHealth technology on self-management aspects of patients with hypertension. A systematic search was conducted on PubMed, Web of Science, Embase, and Scopus databases. Clinical trials in English investigating the use of mHealth technologies for blood pressure control published from 2005 to 2018 were included in this study. The functionalities of these technologies were also investigated. These functionalities were divided into five categories of monitoring, alarms, feedbacks, education, and communication. The most frequently used technology for hypertension control was smartphones in the 15 articles examined. Moreover, the most frequent functionalities used for self-management of hypertension were communications and reminders, education, monitoring, and feedback, respectively. In the majority of the studies, these functionalities were employed in combination with mHealth technologies, a feature that affects hypertension control and self-management. The use of mHealth technologies, such as smartphones, positively affects hypertension self-management and reduces blood pressure. Functionalities such as communication and reminders, education, monitoring, and feedback are effective in hypertension self-management programs. The simultaneous use of these functionalities combined will be more effective in hypertension self-management programs.

Working Toward an mHealth Platform for Adolescents with Type 1 Diabetes: Focus Groups With Teens, Parents, and Providers.

The purpose of the study was to explore facilitators and barriers to self-management behaviors in adolescents with type 1 diabetes (T1D) to inform the development of an mHealth platform. Eight adolescents with T1D, 9 parents, and 13 health care providers participated in separate focus groups that explored teen self-management behaviors. Adolescents and their parents have distinct preferences for handling diabetes management and use of mHealth technologies. Health care providers support the use of new technologies yet acknowledge concern meeting the potential increased volume of communication requests from teens and families. Stakeholders agreed that an ideal mHealth platform would facilitate open communication between teens and their care network and easily integrate with other diabetes technologies. Future directions include incorporating additional feedback from stakeholders to build and modify the mHealth platform. The use of mHealth platforms could be integrated into clinical practice to optimize self-management and support communication between educators, providers, and families in between clinic visits.

Parental mobile health adherence to symptom home monitoring for infants with congenital heart disease during the single ventricle interstage period: A concept analysis.

Single ventricle heart disease is fraught with risk for infant mortality and morbidity. During the interstage period, or the time between palliative cardiac surgeries, mobile health (mHealth) technology improves the ability of registered nurse coordinators to monitor infant symptoms through parental monitoring and reporting. The concept of parental mHealth adherence to symptom home monitoring of infants with single ventricle congenital heart disease has not been defined, despite increasing use of mHealth technology. Rodger's concept analysis method was used to derive a unified definition of parental mHealth adherence to symptom home monitoring of infants with congenital heart disease during the single ventricle interstage period. A literature review included a search of databases for studies that addressed interstage home mHealth monitoring. Thematic analysis was applied to selected articles to derive a unified definition based on attributes, antecedents, consequences, related terms, and an illustrative case example. Sixteen publications were selected. Attributes, antecedents, and consequences of the concept were derived from the literature leading to a definition of parental mHealth adherence for infants with congenital heart disease during the single ventricle interstage period. The definition is the degree of adherence to which parents' transfer mHealth data for their infant meet healthcare providers' recommendations for symptom home monitoring. Consequences were improved infant symptom home monitoring through parental mHealth adherence measured by initiation, implementation, and discontinuation. The unified definition of the concept will provide a firmer ground for research in mHealth and interstage pediatric care and a guide for clinicians in developing new mHealth interventions for symptom home monitoring. This concept analysis hypothesizes that infants with a single ventricle during the interstage period, whose parents are mHealth symptom home monitoring adherent, will have timelier symptom identification with resultant superior outcomes compared with infants with a single ventricle during the interstage period whose parents are not mHealth adherent.

Wound Care Knowledge, Attitudes, and Practices and Mobile Health Technology Use in the Home Environment: Cross-Sectional Survey of Social Network Users.

BackgroundInjury causing wounds is a frequent event. Inadequate or inappropriate treatment of injuries can threaten individual health. However, little is known about wound care knowledge, attitudes, and practices and mobile health (mHealth) use in the home environment in Taiwan.ObjectiveThis study aimed to evaluate wound care knowledge, attitudes, and practices and mHealth technology use among social network users.MethodsA cross-sectional survey on social media platforms was conducted on adults aged 20 years and older. Data were collected from social network users in the home environment.ResultsA total of 361 participants were enrolled. The mHealth technology use of participants was positively correlated with wound care knowledge (r=.132, P=.01), attitudes (r=.239, P<.001), and practices (r=.132, P=.01). Participants did not have adequate knowledge (correct rate 69.1%) and were unfamiliar with the guidelines of proper wound care (correct rate 74.5%). Most participants had positive attitudes toward wound care and mHealth technology use. A total of 95.6% (345/361) of participants perceived that the use of mHealth technology can improve wound care outcomes, and 93.9% (339/361) perceived that wound care products should be optimized to be used with a mobile device. However, 93.6% (338/361) of participants had no experience using mHealth technology for wound care.ConclusionsOur study shows the potential of mHealth technology to enhance wound care knowledge among social network users. Thus, government agencies and medical institutions in Taiwan should provide easy-to-use information products that enhance wound care knowledge, promote adequate behavior toward wound care, and prevent unpredictable or undesirable outcomes.

Access to internet, smartphone usage, and acceptability of mobile health technology among cancer patients.

The use of mobile health (mHealth) technologies to augment patient care enables providers to communicate remotely with patients enhancing the quality of care and patient engagement. Few studies evaluated predictive factors of its acceptance and subsequent implementation, especially in medically underserved populations. A cross-sectional study of 151 cancer patients was conducted at an academic medical center in the USA. A trained interviewer performed structured interviews regarding the barriers and facilitators of patients' current and desired use of mHealth technology for healthcare services. Of the 151 participants, 35.8% were male and ages ranged from 21 to 104years. 73.5% of participants currently have daily access to internet, and 68.2% currently own a smartphone capable of displaying mobile applications. Among all participants, acceptability of a daily mHealth application was significantly higher in patients with a college-level degree (OR 2.78, CI95% 1.25-5.88) and lower in patients > 80years of age (OR 0.05, CI95% 0.01-0.23). Differences in acceptability when adjusted for current smartphone use and daily access to internet were nonsignificant. Among smartphone users, the desire to increase cancer knowledge was associated with a higher likelihood of utilizing a mHealth application (OR 261.53, CI95% 10.13-6748.71). The study suggests that factors such as age, educational achievement, and access to internet are significant predictors of acceptability of a mHealth application among cancer patients. Healthcare organizations should consider these factors when launching patient engagement platforms.

Feasibility and Acceptability of an mHealth-Based Approach as an HIV Prevention Strategy Among People Who Use Drugs on Pre-Exposure Prophylaxis.

IntroductionThere has been increasing interest in the use of mHealth technology in health care. To our knowledge, however, there is a lack of empirical evidence on the utilization of text messaging services (short message service; SMS) for HIV prevention among opioid-dependent people who use drugs (PWUD). As part of our formative work, we conducted an in-depth feasibility and acceptability study on the use of SMS reminders for HIV prevention in this risk group.MethodsForty HIV-negative, opioid-dependent PWUD who are currently taking pre-exposure prophylaxis (PrEP) were enrolled in the study. Participants received daily PrEP text reminders and weekly HIV risk reduction-related messages, which were developed using a user-centered approach. Participants were assessed at baseline and immediately post-intervention. Following the post-intervention assessment, participants completed an in-depth qualitative interview.ResultsFeasibility of text messaging service was high, as assessed by participants’ willingness to receive text messages (100%), retention (95%), and successful delivery of text messages (97%). Results further showed that participants were satisfied and perceived the use of daily PrEP reminder text messages as valuable and acceptable [mean: 75.0 (range 0–100)]. Whereas, acceptability for the weekly text messages on HIV risk reduction was 60.3 (±15.6), with 58.3% recommending them for future use. Thematic data exploration revealed important information for understanding and refining SMS content as well as logistical preferences.ConclusionOur findings provide preliminary evidence of the feasibility and acceptability of a text messaging-based approach as a potential tool for primary HIV prevention to improve PrEP adherence and HIV risk reduction among this underserved population. HIV risk reduction text messages need further modifications to become more appealing, with participant feedback taken into consideration.

Knowledge, attitude, and use of mHealth technology among students in Ghana: A university-based survey

BackgroundInterest in mHealth interventions, defined as the use of mobile phones to access healthcare is increasingly becoming popular globally. Given its technology-based applications, university students may be key clients of the mHealth adoption but studies are rare in sub-Saharan Africa. This study provides a snapshot and baseline evidence on knowledge, attitude and use of mHealth among university students in Ghana.MethodsUsing a self-administered questionnaire, we collected data between April and June 2017 from 963 randomly sampled undergraduate students at the Kwame Nkrumah University of Science and Technology (KNUST). Pearson’s Chi-square (χ2) test assessed the differences between variables whilst logistic regression models estimated the independent predictors of use of mHealth with p < 0.05 as significant.ResultsKnowledge on mHealth was moderately high. Specifically, more than half of the sample reported awareness of mHealth although the prevalence of use of mHealth stood at 51%. Logistic regressions revealed that mHealth use was positively associated with respondents’ year (second year: OR = 1.704, 95% CI: 1.185–2.452, and third year: OR = 1.528, 95% CI: 1.060–2.202), and monthly income (OR:3.112, 95%CI: 1.180-8.211). However, ethnicity [(OR = 0.761, 95% CI (0.580–0.997)] was negatively associated with the use of mHealth technology.ConclusionFindings suggest that knowledge of mHealth among university students is low. Policy and public health interventions for urgent awareness creation and promotion of use of mHealth as well as its possible integration into the mainstream healthcare system in Ghana are timely.

A Model for Assessing Necessary Conditions for Rural Health Care's Mobile Health Readiness: Qualitative Assessment of Clinician-Perceived Barriers.

BackgroundMobile health (mHealth) technology dissemination has penetrated rural and urban areas alike. Yet, health care organization oversight and clinician adoption have not kept pace with patient use. mHealth could have a unique impact on health and quality of life for rural populations. If organizations are prepared to manage mHealth, clinicians may improve the quality of care for their patients, both rural and urban. However, many organizations are not yet prepared to prescribe or prohibit third-party mHealth technologies.ObjectiveThis study explored organizational readiness for rural mHealth adoption, the use of patient-reported data by clinical care teams, and potential impact on improving rural health care delivery.MethodsSemistructured, open-ended interviews were used to investigate clinicians’ current practices, motivators, and perceived barriers to their use of mHealth technologies in rural settings.ResultsA total of 13 clinicians were interviewed, and 53.8% (7/13) reported encouraging use of mHealth apps or wearable devices with rural patients. Perceived barriers to adoption were categorized into three primary themes: (1) personal (clinician), (2) patient, and (3) organizational. Organizational was most prominent, with subcodes of time, uniformity, and policy or direction. Thematic analysis revealed code-category linkages that identify the complex nature of a rural health care organization’s current climate from a clinician’s perspective. A thematic map was developed to visualize the flow from category to code. Identified linkages guided the development of a refined rural mHealth readiness model.ConclusionsClinicians (including physicians) have limited time for continuing education, research, or exploration of emerging technologies. Clinicians are motivated to learn more, but they need guidance through organization-led directives. Rural health care institutions should consider investing in mHealth analysis, tool development, and formal recommendations of sanctioned tools for clinicians to use with patients.

Mobile health technology (WeChat) for the hierarchical management of community hypertension: protocol for a cluster randomized controlled trial.

PurposeThe prevalence of hypertension continues to increase worldwide, raising an urgent need for novel and efficient methods for controlling hypertension. As the Internet and smartphones become more popular, their multiple functions and large user base make mobile health (mHealth) technology a potential tool for hypertension management. We aim to evaluate the use of mHealth technology to improve blood pressure and self-management behavior in people with hypertension and prehypertension.InterventionThe mHealth intervention measures include health education, behavior promotion, group chatting and long-term blood pressure monitoring hierarchically delivered via WeChat application among 242 participants. The frequency, intensity and content of the hierarchical intervention are determined based on the cardiovascular risk stratification of the intervention subjects.Study designThis cluster randomized controlled trial was carried out in two subdistricts in Guangzhou, China, among 492 smartphone users with hypertension or prehypertension, from August 2018 to September 2019. The intervention group received hierarchical intervention through WeChat for six months, while the control group received usual care in the community healthcare center during this period. Indicators are measured at three time points for each group, and a telephone follow-up is planned for two years after the intervention. The primary outcome is systolic blood pressure; secondary outcomes include BMI, CPAT score, improvements in behavior and diet, score of self-efficacy and self-management. Feasibility is evaluated by intervention participation. The cost-effectiveness is evaluated by ICER.ConclusionThis study aims to evaluate the effect of the WeChat-based hierarchical management mode on improving blood pressure and self-management behavior in population with hypertension and prehypertension, based on health-related knowledge, self-efficacy and medication adherence. If successful, the management mode will serve as a feasible, economical and efficient hypertension management mode suitable for the community.Clinical trial identifier: ChiCTR1900023002

Technology for Behavioral Change in Rural Older Adults with Obesity

Background: Mobile health (mHealth) technologies comprise a multidisciplinary treatment strategy providing potential solutions for overcoming challenges of successfully delivering health promotion interventions in rural areas. We evaluated the potential of using technology in a high-risk population.Methods: We conducted a convergent, parallel mixed-methods study using semi-structured interviews, focus groups, and self-reported questionnaires, using purposive sampling of 29 older adults, 4 community leaders and 7 clinicians in a rural setting. We developed codes informed by thematic analysis and assessed the quantitative data using descriptive statistics.Results: All groups expressed that mHealth could improve health behaviors. Older adults were optimistic that mHealth could track health. Participants believed they could improve patient insight into health, motivating change and assuring accountability. Barriers to using technology were described, including infrastructure.Conclusions: Older rural adults with obesity expressed excitement about the use of mHealth technologies to improve their health, yet barriers to implementation exist.