Self-management of Chronic Conditions Using mHealth Interventions in Korea: A Systematic Review

Nurses' Use of mHealth Apps for Chronic Conditions: Cross-Sectional Survey

BACKGROUND

Mobile health (mHealth) is increasingly used to support public health practice, as it has positive benefits such as enhancing self-efficacy and facilitating chronic disease management. Yet, relatively few studies have explored the use of mHealth apps among nurses, despite their important role in caring for patients with and at risk of chronic conditions.

OBJECTIVE

The aim of the study is to explore nurses' use of mHealth apps to support adults with or at risk of chronic conditions and understand the factors that influence technology adoption.

METHODS

A web-based cross-sectional survey was conducted between September 2022 and January 2023. The survey was shared via social media and professional nursing organizations to Australian nurses caring for adults with or at risk of chronic conditions.

RESULTS

A total of 158 responses were included in the analysis. More than two-thirds (n=108, 68.4%) of respondents reported that they personally used at least 1 mHealth app. Over half (n=83, 52.5% to n=108, 68.4%) reported they use mHealth apps at least a few times a month for clinical purposes. Logistic regression demonstrated that performance expectancy (P=.04), facilitating condition (P=.05), and personal use of mHealth apps (P=.05) were significantly associated with mHealth app recommendation. In contrast, effort expectancy (P=.09) and social influence (P=.46) did not have a significant influence on whether respondents recommended mHealth apps to patients. The inability to identify the quality of mHealth apps and the lack of access to mobile devices or internet were the most common barriers to mHealth app recommendation.

CONCLUSIONS

While nurses use mHealth apps personally, there is potential to increase their clinical application. Given the challenges reported in appraising and assessing mHealth apps, app regulation and upskilling nurses will help to integrate mHealth apps into usual patient care.

Mobile Apps for Patients with Peritoneal Dialysis: Systematic App Search and Evaluation

BACKGROUND

Peritoneal dialysis (PD) is one type of renal replacement therapy. If patients have problems during the dialysis process, healthcare providers may not be able assist the patients immediately. mHealth can provide patients with information and help them to solve problems in real-time, potentially increasing their willingness to choose PD.

OBJECTIVE

The objectives of this study were to conduct a comprehensive review of free mobile applications for patients with PD on the Internet and to recommend suitable mobile applications to facilitate patient self-management and health.

METHODS

We conducted a systematic search for PD mobile applications on Google Play and the Apple iTunes Store from 3 to 16 June 2023.

RESULTS

A total of 828 identifiable mobile applications were initially identified, and ultimately, 21 met the inclusion criteria. The Mobile App Rating Scale (MARS) assessment of the applications revealed the highest score in the functionality domain, followed by the aesthetics, information, app-specific, subjective quality, and engagement domains, respectively. In the comprehensive self-management of PD, the highest percentage was related to disease-related information.

CONCLUSION

The findings of this study suggest that some applications, with the highest quality, can be recommended to patients for use in English or traditional Chinese.

Mobile Apps for Common Noncommunicable Disease Management: Systematic Search in App Stores and Evaluation Using the Mobile App Rating Scale

Background

The success of mobile apps in improving the lifestyle of patients with noncommunicable diseases through self-management interventions is contingent upon the emerging growth in this field. While users of mobile health (mHealth) apps continue to grow in number, little is known about the quality of available apps that provide self-management for common noncommunicable diseases such as diabetes, hypertension, and obesity.

Objective

We aimed to investigate the availability, characteristics, and quality of mHealth apps for common noncommunicable disease health management that included dietary aspects (based on the developer's description), as well as their features for promoting health outcomes and self-monitoring.

Methods

A systematic search of English-language apps on the Google Play Store (Google LLC) and Apple App Store (Apple Inc) was conducted between August 7, 2022, and September 13, 2022. The search terms used included weight management, obesity, diabetes, hypertension, cardiovascular diseases, stroke, and diet. The selected mHealth apps' titles and content were screened based on the description that was provided. Apps that were not designed with self-management features were excluded. We analyzed the mHealth apps by category and whether they involved health care professionals, were based on scientific testing, and had self-monitoring features. A validated and multidimensional tool, the Mobile App Rating Scale (MARS), was used to evaluate each mHealth app's quality based on a 5-point Likert scale from 1 (inadequate) to 5 (excellent).

Results

Overall, 42 apps were identified. Diabetes-specific mHealth apps accounted for 7% (n=3) of the market, hypertension apps for 12% (n=5), and general noncommunicable disease management apps for 21% (n=9). About 38% (n=16) of the apps were for managing chronic diseases, while 74% (n=31) were for weight management. Self-management features such as weight tracking, BMI calculators, diet tracking, and fluid intake tracking were seen in 86% (n=36) of the apps. Most mHealth apps (n=37, 88%) did not indicate whether there was involvement of health professionals in app development. Additionally, none of the apps reported scientific evidence demonstrating their efficacy in managing health. The overall mean MARS score was 3.2 of 5, with a range of 2.0 to 4.1. Functionality was the best-rated category (mean score 3.9, SD 0.5), followed by aesthetics (mean score 3.2, SD 0.9), information (mean score 3.1, SD 0.7), and engagement (mean score 2.9, SD 0.6).

Conclusions

The quality of mHealth apps for managing chronic diseases was heterogeneous, with roughly half of them falling short of acceptable standards for both quality and content. The majority of apps contained scant information about scientific evidence and the developer's history. To increase user confidence and accomplish desired health outcomes, mHealth apps should be optimized with the help of health care professionals. Future studies on mHealth content analysis should focus on other diseases as well.

The effects of a 24-week interactive text message-based mobile health intervention for enhancing self-care behaviours of patients with heart failure: A quasi-experimental study

AIMS

The aim of this study was to identify the effects of a 24-week interactive text message-based mobile health intervention (called) on enhancing the self-care behaviours of patients with heart failure.

BACKGROUND

Whether text message-based mobile health intervention can be used to improve long-term adherence to self-care behaviours among heart failure patients remains unclear.

DESIGN

A quasi-experimental study with a pretest-post-test design and repeated measures.

METHODS

Data from 100 patients (mean age, 58.78 years; 83.0% men) were analysed. The intervention group (n = 50) used the program over 24 weeks, which consisted of weekly goal setting and interactive text messaging, while the control group (n = 50) received usual care. Trained research assistants collected data using self-reported Likert questionnaires. Primary (self-care behaviours) and secondary (health literacy, eHealth literacy, and disease knowledge) outcome variables were measured at baseline and at 1, 3 and 6 months after intervention for follow-up.

RESULTS

The findings showed that the intervention group demonstrated significantly better self-care behaviours than the control group during the 6 months. Notably, the trajectory of self-care behaviours of the patients in the intervention group showed a steep rise between the first- and third-month follow-up, followed by high stability between the third- and sixth-month follow-up. In addition, the intervention group had significantly higher disease knowledge than the control group at the first- and sixth-month follow-up.

CONCLUSIONS

We found that the program, as an interactive text messaging service, may be an optimal strategy for improving long-term adherence to self-care behaviours through motivating and providing social support.

RELEVANCE TO THE NURSING PRACTICE

The WithUs program can help nurses and other healthcare professionals to track patients' health indicators such as symptom severity, diet and physical activity. In addition, nurses can take an important role in evaluating the efficacy of the app in relation to patients' health outcome.

PATIENT OR PUBLIC CONTRIBUTION

Patients have completed a self-reported questionnaire after providing informed consent.

The intention to use mHealth applications among Dutch older adults prior and during the COVID pandemic

Background

Mobile health (mHealth) applications are widely valued for their potential to increase self-management among older adults and reduce their healthcare demands. However, the intention to use mHealth of Dutch older adults before the COVID-19 pandemic was modest. Healthcare access was considerably reduced during the pandemic and mHealth services substituted for in person health services. As older adults utilize health services more frequently and have been particularly vulnerable to the pandemic, they can be viewed to have especially benefitted from the transition toward mHealth services. Furthermore, one might expect their intention to use these services and reap the potential benefits has increased, especially during the pandemic.

Objective

The aim of this study was to examine whether the intention of Dutch older adults to use medical applications increased during the COVID pandemic and how the explanatory power of the extended Technology Acceptance Model (TAM) developed for this purpose was affected by the onset of the pandemic.

Methods

We conducted a cross-sectional survey using two samples collected before (n = 315) and after (n = 501) the onset of the pandemic. Data was collected using questionnaires which were distributed digitally and on paper, by convenience sampling and snowballing. Participants were 65 years or older, lived independently or in a senior living facility, without cognitive impairment. A controlled analysis was performed to test for significant differences in the intention to use mHealth. The before and after differences in extended TAM variables and their relationship with intention to use (ITU) were analyzed using controlled (multivariate) logistic and linear regression models. These models were also used to explore whether the onset of the pandemic had an effect on ITU not captured by the extended TAM model.

Results

While the two samples differed in ITU (p = 0.017; uncontrolled) there was no statistically significant difference in ITU in the controlled logistic regression analysis (p = 0.107). The scores of the extended TAM variables explaining intention to use were all significantly higher, except for Subjective norm and Feelings of Anxiety. The relationships of these variables with intention to use before and after the onset of the pandemic were similar, except for Social relationships which lost its significance. We found no indications of effects of the pandemic on intention to use not captured by our instrument.

Conclusion

The intention to use mHealth applications of Dutch older adults has not changed since the onset of the pandemic. The extended TAM model has robustly explained intention to use, with only minor differences after the first months of the pandemic. Interventions targeting facilitation and support are likely to promote the uptake of mHealth. Follow-up studies are needed to investigate whether the pandemic has had long term effects on the ITU of the older adult.

Development of an Automatic Pill Image Data Generation System

OBJECTIVES

Since the easiest way to identify pills and obtain information about them is to distinguish them visually, many studies on image processing technology exist. However, no automatic system for generating pill image data has yet been developed. Therefore, we propose a system for automatically generating image data by taking pictures of pills from various angles. This system is referred to as the pill filming system in this paper.

METHODS

We designed the pill filming system to have three components: structure, controller, and a graphical user interface (GUI). This system was manufactured with black polylactic acid using a 3D printer for lightweight and easy manufacturing. The mainboard controls data storage, and the entire process is managed through the GUI. After one reciprocating movement of the seesaw, the web camera at the top shoots the target pill on the stage. This image is then saved in a specific directory on the mainboard.

RESULTS

The pill filming system completes its workflow after generating 300 pill images. The total time to collect data per pill takes 21 minutes and 25 seconds. The generated image size is 1280 × 960 pixels, the horizontal and vertical resolutions are both 96 DPI (dot per inch), and the file extension is .jpg.

CONCLUSIONS

This paper proposes a system that can automatically generate pill image data from various angles. The pill observation data from various angles include many cases. In addition, the data collected in the same controlled environment have a uniform background, making it easy to process the images. Large quantities of high-quality data from the pill filming system can contribute to various studies using pill images.

Using data visualization to detect patterns in whole-person health data

Data visualization techniques are useful for examining large multidimensional data sets. In this exploratory data analysis (EDA) study, we applied a visualization pattern detection and testing process to deidentified data to discover patterns in whole-person health for adults 65 and older. Whole-person health examines a person's environmental, psychosocial, and physical health, as well as their health-related behaviors; and assesses their strengths, challenges, and needs. Strengths are defined as assets and capabilities in the face of short-or long-term stressors. We collected data using a mobile application that delivers a comprehensive whole-person assessment using a simplified version of a standardized instrument, the Omaha System. The visualization pattern detection process is iterative, includes various techniques, and requires visualization literacy. The data visualization techniques applied in this analysis included bubble charts, parallel coordinates line graphs, box plots, and alluvial flow diagrams. We discovered six patterns within the visualizations. We formulated and tested six hypotheses based on these six patterns, and all six hypotheses were supported. Adults 65 and older had more strengths than challenges and more challenges than needs (p < 0.001). Strengths and challenges were negatively correlated (p < 0.001). Unexpectedly, a subset of adults 65 and older who had many, but not all, strengths had significantly more needs (p = 0.04). The use of standardized terminology with its inherent data interrelationships was key to discovering patterns in whole-person health. This methodology may be used in future EDA research using new data sets.

Functional requirements of a mobile-based application for stroke self-management: A Delphi study

This study aimed to determine the functional requirements of a self-management mobile application for stroke survivors. For extracting the initial functional requirements, a literature review as well as interviews with 17 patients and caregivers were done. The results were analyzed using the content analysis method. The initial extracted requirements were then provided to the specialists by the Delphi technique to determine the final functional requirements. Content validity ratio (CVR) and content validity index (CVI) were calculated according to the Lawshe model. Criteria for item approval included CVR > 0.49 and CVI > 0.79. Finally, the approved items were turned into a five-point Likert scale questionnaire and were then provided to 53 experts and items with a mean score higher than 3.75 were approved. Functional requirements including creating a user account, educational material, support services, providing reminders and alerts for drugs administration and physician appointments, and rehabilitation exercises (to improve balance, upper and lower extremities rehabilitation, and activities of daily living (ADLs)) were approved. Most of the approved functional requirements were related to rehabilitation exercises for improving upper limb motor function. The experts did not approve the requirements for using splints and slings or the recommendation to take some medications.

Gender differences regarding intention to use mHealth applications in the Dutch elderly population: a cross-sectional study

BACKGROUND

In light of the increasing demands in health care, a call has been made for the development of new strategies. One of these strategies is placing a higher emphasis on individuals, who are expected to better manage their own health and illness. mHealth applications could increase this self-management behaviour among older adults. However, it is crucial to know the intention to use mHealth of older adults before implementing these services. Even less is known regarding differences between genders on factors influencing this intention to use mHealth applications.

OBJECTIVE

The aim of this study was to study the gender differences regarding the relationship between technology acceptance factors and the intention to use mHealth applications in the Dutch elderly population.

METHODS

We conducted a quantitative cross-sectional study using questionnaires. The participants were 65 years or older, lived independently or in a senior living facility, without cognitive impairment. Logistic regression with interaction terms was done to determine gender differences in the relationship between the intention to use mHealth applications and technology acceptance factors.

RESULTS

While we found that half of the studied population had intention to use medical applications (50.3%) a notable difference was observed within gender groups which showed more men had intention to use medical applications rather than women (59.4% vs. 43.4% respectively). Adjusted logistic regression analysis per factor on the male and female part of the study population respectively showed that the factors Perceived usefulness (OR 21,69 and 2,39, resp.), Perceived ease of use (OR 7,21 and 2,74), Attitude toward use (OR 24,61 and 4,94), Sense of control (OR 4,12 and 2,67), Personal innovativeness (OR 2,54 and 1,58), Self-perceived effectiveness (OR 3,21 and 2,34), Service availability (OR 4,38 and 2,51) and Facilitating circumstances (OR 3,04 and 2,18) had a statistically significant influence on intention to use in both models. Logistic regression with interaction terms showed that two of the technology acceptance factors differed statistically significant in their relationship with intention to use when comparing females to males, namely Perceived usefulness (OR 0,11) and Attitude toward use (OR 0.24). Both factors were more strongly associated with intention to use for men compared to women.

CONCLUSION

Policymakers and interventions aiming to stimulate the uptake of mHealth applications should acknowledge gender differences. Interventions based on improving the Perceived usefulness and Attitude toward use among female users could be a means to stimulate the full potential of medical applications and improve the uptake.

Normalizing Telemonitoring in Nurse-Led Care Models for Complex Chronic Patient Populations: Case Study

BACKGROUND

The implementation of telemonitoring (TM) has been successful in terms of the overall feasibility and adoption in single disease care models. However, a lack of available research focused on nurse-led implementations of TM that targets patients with multiple and complex chronic conditions (CCC) hinders the scale and spread to these patient populations. In particular, little is known about the clinical perspective on the implementation of TM for patients with CCC in outpatient care.

OBJECTIVE

This study aims to better understand the perspective of the clinical team (both frontline clinicians and those in administrative positions) on the implementation and normalization of TM for complex patients in a nurse-led clinic model.

METHODS

A pragmatic, 6-month implementation study was conducted to embed multicondition TM, including heart failure, hypertension, and diabetes, into an integrated nurse-led model of care. Throughout the study, clinical team members were observed, and a chart review was conducted of the care provided during this time. At the end of the study, clinical team members participated in qualitative interviews and completed the adapted Normalization Measure Development questionnaires. The Normalization Process Theory guided the deductive data analysis.

RESULTS

Overall, 9 team members participated in the study as part of a larger feasibility study of the TM program, of which 26 patients were enrolled. Team members had a shared understanding of the purpose and value of TM as an intervention embedded within their practice to meet the diverse needs of their patients with CCC. TM aligned well with existing chronic care practices in several ways, yet it changed the process of care delivery (ie, interactional workability subconstruct). Effective TM normalization in nurse-led care requires rethinking of clinical workflows to incorporate TM, relationship development between the clinicians and their patients, communication with the interdisciplinary team, and frequent clinical care oversight. This was captured well through the subconstructs of skill set workability, relational integration, and contextual integration of the Normalization Process Theory.

CONCLUSIONS

Clinicians successfully adopted TM into their everyday practice such that some providers felt their role would be significantly and negatively affected without TM. This study demonstrated that smartphone-based TM systems complemented the routine and challenging clinical work caring for patients with CCC in an integrated nurse-led care model.

The Effect of a Mobile and Wearable Device Intervention on Increased Physical Activity to Prevent Metabolic Syndrome: Observational Study

Background

Research on whether wearable devices and app-based interventions can effectively prevent metabolic syndrome (MetS) by increasing physical activity (PA) among middle-aged people living in the rural areas of South Korea remains insufficient.

Objective

The aim of this study was to determine whether mobile and wearable device interventions can improve health indicators, including PA, in MetS risk groups in rural South Korea.

Methods

In this clinical trial, performed from December 2019 to June 2020, participants were asked to use a wearable device (GalaxyWatch Active1) alone (standard intervention) or the wearable device and mobile app (Yonsei Health Korea) (enhanced intervention). Clinical measures and International Physical Activity Questionnaire (IPAQ) scores were evaluated initially and after 6 months. The number of steps was monitored through the website. The primary outcome was the difference in PA and clinical measures between the enhanced intervention and standard intervention groups. The secondary outcome was the decrease in MetS factors related to the change in PA.

Results

A total of 267 participants were randomly selected, 221 of whom completed the 6-month study. Among the 221 participants, 113 were allocated to the enhanced intervention group and 108 were allocated to the standard intervention group. After 6 months, the body weight and BMI for the enhanced intervention group decreased by 0.6 (SD 1.87) and 0.21 (SD 0.76), respectively (P<.001). In both groups, systolic blood pressure, diastolic blood pressure, waist circumference, and glycated hemoglobin A_1c (HbA_1c) decreased (P<.001). The total PA was approximately 2.8 times lower in the standard intervention group (mean 44.47, SD 224.85) than in the enhanced intervention group (mean 124.36, SD 570.0). Moreover, the enhanced intervention group achieved the recommended level of moderate to vigorous physical activity (MVPA), whereas the standard intervention group did not (188 minutes/week vs 118 minutes/week). Additionally, the number of participants in the enhanced intervention group (n=113) that reached 10,000 daily steps or more after the intervention increased from 9 (8.0%) to 26 (23.1%) (P=.002), whereas this number did not increase significantly in the standard intervention group (n=108), from 8 (7.4%) to 16 (14.8%) (P=.72). The number of participants without any MetS factors increased by 12 (11%) and 8 (7%) in the enhanced and standard intervention group, respectively.

Conclusions

PA monitoring and an intervention using wearable devices were effective in preventing MetS in a rural population in Korea. Blood pressure, waist circumference, and HbA_1c were improved in both intervention groups, which were effective in reducing MetS factors. However, only the participants in the enhanced intervention group continuously increased their MVPA and step counts above the recommended level to prevent MetS. Body weight and BMI were further improved, and a higher number of participants with zero MetS factors was attained from the enhanced intervention.

Trial Registration

Clinical Research Information Service KCT0005783; https://cris.nih.go.kr/cris/search/detailSearch.do/16123

A new privacy framework for the management of chronic diseases via mHealth in a post-Covid-19 world

Aim

New challenges are being faced by global healthcare systems such as an increase in the elderly population, budget cuts as well as the ongoing Covid-19 pandemic. As pressures mount on healthcare systems to provide treatment to patients, mHealth is seen as one of the possible solutions to addressing these challenges. Given the sensitivity of health data, the rapid development of the mHealth sector raises privacy concerns. The aims of this research were to investigate privacy threats/concerns in the context of mHealth and the management of chronic diseases and to propose a novel privacy framework to address these concerns.

Subject and method

The study adopted a modified version of the engineering design process. After defining the problem, information was gathered through literature reviews, and analyses of existing regulatory (privacy) frameworks and past research on privacy threats/concerns. Requirements for a new framework were then specified leading to its development and comparison with existing frameworks.

Results

A novel future-proof privacy framework was developed and illustrated. Using existing regulatory frameworks for privacy and privacy threats/concerns from research studies, privacy principles and their resulting requirements were identified. Furthermore, mechanisms and associated technologies needed to implement the privacy principles/requirements into a functional prototype were also identified. A comparison of the proposed framework with existing frameworks, showed that it addressed privacy threats/concerns in a more comprehensive manner.

Conclusion

This research makes a valuable contribution to protecting privacy in mHealth. The novel framework developed is an improvement on existing frameworks. It is also future-proof since its foundations are built on regulatory frameworks and privacy threats/concerns existing at the time of its deployment/revision.

Food Allergy Symptom Self-Management With Technology (FASST) mHealth Intervention to Address Psychosocial Outcomes in Caregivers of Children With Newly Diagnosed Food Allergy: Protocol for a Pilot Randomized Controlled Trial

Background

Approximately 2.4 million children in the United States suffer from food-induced anaphylaxis, a condition that is annually responsible for over 200 deaths and 200,000 emergency room visits. As a result, caregivers of children newly diagnosed with severe and life-threatening food allergic reactions experience clinically significant symptoms of psychological distress, including fatigue, anxiety, depressed mood, social isolation, and substantially reduced quality of life. Despite this recognition, there is a lack of caregiver-centered self-management interventions to address these concerns.

Objective

In this protocol, we propose to develop and conduct feasibility testing of a technology-enhanced, self-management, mobile health, smartphone app intervention called Food Allergy Symptom Self-Management with Technology for Caregivers (FASST) designed to meet the psychosocial health needs of caregivers of children with a new diagnosis of food allergy.

Methods

This pilot study uses qualitative work (Phase I) to inform a 4-week longitudinal randomized controlled trial (Phase II). In Phase I, 10 caregivers of children (≤18 years old) with established food allergy (≥1 year from diagnosis) will participate in semistructured interviews to inform the development of the FASST app. In Phase II, 30 caregivers of children (≤18 years old) with a newly diagnosed food allergy (≤90 days from diagnosis) will be randomized 2:1 to receive the FASST intervention (n=20) or control condition (basic app with educational resources; n=10). Process measures include feasibility, caregiver acceptability, adherence, and satisfaction. Outcome measures include caregiver fatigue, anxiety, depression, sleep, self-efficacy, and quality of life measured at baseline, week 4, and 3 months post study completion.

Results

Phase I study activities have been completed, and Phase II participant enrollment into the randomized controlled trial is expected to commence in 2021.

Conclusions

With limited readily available resources at their disposal, the results from this study have the potential to provide caregivers of children with a newly diagnosed food allergy a tool to help them self-manage and mitigate negative psychosocial factors during a critical time period in the caregiving/condition trajectory.

Trial Registration

ClinicalTrials.gov Identifier NCT04512924: https://clinicaltrials.gov/ct2/show/NCT04512924

International Registered Report Identifier (IRRID)

DERR1-10.2196/25805

Interdisciplinary collaboration between nursing and engineering in health care: A scoping review

BACKGROUND

Due to the rapid advancements in precision medicine and artificial intelligence, interdisciplinary collaborations between nursing and engineering have emerged. Although engineering is vital in solving complex nursing problems and advancing healthcare, the collaboration between the two fields has not been fully elucidated.

OBJECTIVES

To identify the study areas of interdisciplinary collaboration between nursing and engineering in health care, particularly focusing on the role of nurses in the collaboration.

METHODS

In this study, a scoping review using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews was performed. A comprehensive search for published literature was conducted using the PubMed, Cumulative Index to Nursing and Allied Health Literature, Scopus, Embase, Web of Science, ScienceDirect, Institute of Electrical and Electronics Engineers Digital Library, and Association for Computing Machinery Digital Library from inception to November 22, 2020. Data screening and extraction were performed independently by two reviewers. Any discrepancies in results were resolved through discussions or in consultation with a third reviewer. Data were analyzed by descriptive statistics and content analysis. Results were visualized in an interdisciplinary collaboration model.

RESULTS

We identified 6,752 studies through the literature search, and 60 studies met the inclusion criteria. The study areas of interdisciplinary collaboration concentrated on patient safety (n = 18), symptom monitoring and health management (n = 18), information system and nursing human resource management (n = 16), health education (n = 5), and nurse-patient communication (n = 3). The roles of nurses in the interdisciplinary collaboration were divided into four themes: requirement analyst (n = 21), designer (n = 22), tester(n = 37) and evaluator (n = 49). Based on these results, an interdisciplinary collaboration model was constructed.

CONCLUSIONS

Interdisciplinary collaborations between nursing and engineering promote nursing innovation and practice. However, these collaborations are still emerging and in the early stages. In the future, nurses should be more involved in the early stages of solving healthcare problems, particularly in the requirement analysis and designing phases. Furthermore, there is an urgent need to develop interprofessional education, strengthen nursing connections with the healthcare engineering industry, and provide more platforms and resources to bring nursing and engineering disciplines together.

Lifelog Data-Based Prediction Model of Digital Health Care App Customer Churn: Retrospective Observational Study

Background

Customer churn is the rate at which customers stop doing business with an entity. In the field of digital health care, user churn prediction is important not only in terms of company revenue but also for improving the health of users. Churn prediction has been previously studied, but most studies applied time-invariant model structures and used structured data. However, additional unstructured data have become available; therefore, it has become essential to process daily time-series log data for churn predictions.

Objective

We aimed to apply a recurrent neural network structure to accept time-series patterns using lifelog data and text message data to predict the churn of digital health care users.

Methods

This study was based on the use data of a digital health care app that provides interactive messages with human coaches regarding food, exercise, and weight logs. Among the users in Korea who enrolled between January 1, 2017 and January 1, 2019, we defined churn users according to the following criteria: users who received a refund before the paid program ended and users who received a refund 7 days after the trial period. We used long short-term memory with a masking layer to receive sequence data with different lengths. We also performed topic modeling to vectorize text messages. To interpret the contributions of each variable to model predictions, we used integrated gradients, which is an attribution method.

Results

A total of 1868 eligible users were included in this study. The final performance of churn prediction was an F1 score of 0.89; that score decreased by 0.12 when the data of the final week were excluded (F1 score 0.77). Additionally, when text data were included, the mean predicted performance increased by approximately 0.085 at every time point. Steps per day had the largest contribution (0.1085). Among the topic variables, poor habits (eg, drinking alcohol, overeating, and late-night eating) showed the largest contribution (0.0875).

Conclusions

The model with a recurrent neural network architecture that used log data and message data demonstrated high performance for churn classification. Additionally, the analysis of the contribution of the variables is expected to help identify signs of user churn in advance and improve the adherence in digital health care.

The Impact of Mobile Health on Cancer Screening: A Systematic Review

Introduction:

Mobile health is an emerging technology around the world that can be effective in cancer screening. This study aimed to examine the effectiveness of mobile health applications on cancer screening.

Methods:

We conducted a systematic literature review of studies related to the use of mobile health applications in cancer screening. We also conducted a comprehensive search of articles on cancer screening related to the use of mobile health applications in journals published between January 1, 2008, and January 31, 2019, using 5 databases: IEEE, Scopus, Web of Science, Science Direct and PubMed.

Results:

A total of 23 articles met the inclusion criteria and were included in the present review. All studies have identified positive effects of applications on cancer screening and clinical health outcomes. Furthermore, more than half of mobile applications had multiple functions such as providing information, planning and education. Moreover, most of the studies, which examined the satisfaction of patients and quality improvement, showed healthcare application users have significantly higher satisfaction of living and it leads to improving quality.

Conclusion:

This study found that the use of mobile health applications has a positive impact on health-related behaviours and outcomes. Application users were more satisfied with applying mobile health applications to manage their health condition in comparison with users who received conventional care.

mHealth Interventions to Promote Anti-Retroviral Adherence in HIV: Narrative Review

Background

Antiretrovirals (ARVs) are key in the management of HIV. Although no cure exists, ARVs help patients live healthy lives and prevent transmission to others. Adherence to complex regimens is paramount to outcomes and in avoiding the emergence of drug-resistant viruses. The goal of therapy is to reach an undetectable viral load. However, adherence is a common problem, stemming from issues such as mental health, chaotic home situations, and busy work schedules. Mobile health (mHealth) represents a new approach in improving medication adherence, and multiple studies have been performed in this area.

Objective

This study aims to review the current implementation of mHealth in the management of HIV among different groups of patients.

Methods

We used PubMed, Academic Search Elite, and 1 journal database with various search terms to review the current implementation of mHealth in HIV care.

Results

Titles and abstracts were screened, and 61 papers were identified and fully reviewed. The literature was divided into lower- and higher-income nations, as defined by the United Nations. A total of 20 studies with quantitative results were identified, with 10 being text- and SMS-based interventions (the majority of these being in lower-income countries) and 8 being smartphone-based apps (primarily in higher-income countries). The majority of these studies determined whether there was an effect on adherence or biochemical parameters (viral load and CD4 count). Various qualitative studies have also been conducted, and many have focused on determining the specific design of interventions that were successful (frequency of messaging, types of messages, etc) as well as priorities for patients with regard to mHealth interventions.

Conclusions

There seems to be a role of mHealth in the management of HIV in lower-income nations; however, the optimal design of an intervention needs to be delineated. In higher-income countries, where the 2 significant risk factors were injection drugs and men who have sex with men, the benefit was less clear, and more research is needed.

The Use of Mobile Personal Health Records for Hemoglobin A1c Regulation in Patients With Diabetes: Retrospective Observational Study

BACKGROUND

The effectiveness of personal health records (PHRs) in diabetes management has already been verified in several clinical trials; however, evidence of their effectiveness in real-world scenarios is also necessary. To provide solid real-world evidence, an analysis that is more accurate than the analyses solely based on patient-generated health data should be conducted.

OBJECTIVE

This study aimed to conduct a more accurate analysis of the effectiveness of using PHRs within electronic medical records (EMRs). The results of this study will provide precise real-world evidence of PHRs as a feasible diabetes management tool.

METHODS

We collected log data of the sugar function in the My Chart in My Hand version 2.0 (MCMH 2.0) app from Asan Medical Center (AMC), Seoul, Republic of Korea, between December 2015 and April 2018. The EMR data of MCMH 2.0 users from AMC were collected and integrated with the PHR data. We classified users according to whether they were continuous app users. We analyzed and compared their characteristics, patterns of hemoglobin A_1c (HbA_1c) levels, and the proportion of successful HbA_1c control. The following confounders were adjusted for HbA_1c pattern analysis and HbA_1c regulation proportion comparison: age, sex, first HbA_1c measurement, diabetes complications severity index score, sugar function data generation weeks, HbA_1c measurement weeks before MCMH 2.0 start, and generated sugar function data count.

RESULTS

The total number of MCMH 2.0 users was 64,932, with 7453 users having appropriate PHRs and diabetes criteria. The number of continuous and noncontinuous users was 133 and 7320, respectively. Compared with noncontinuous users, continuous users were younger (P<.001) and had a higher male proportion (P<.001). Furthermore, continuous users had more frequent HbA_1c measurements (P=.007), shorter HbA_1c measurement days (P=.04), and a shorter period between the first HbA_1c measurement and MCMH 2.0 start (P<.001). Diabetes severity-related factors were not statistically significantly different between the two groups. Continuous users had a higher decrease in HbA_1c (P=.02) and a higher proportion of regulation of HbA_1c levels to the target level (P=.01). After adjusting the confounders, continuous users had more decline in HbA_1c levels than noncontinuous users (P=.047). Of the users who had a first HbA_1c measurement higher than 6.5% (111 continuous users and 5716 noncontinuous users), continuous users had better regulation of HbA_1c levels with regard to the target level, 6.5%, which was statistically significant (P=.04).

CONCLUSIONS

By integrating and analyzing patient- and clinically generated data, we demonstrated that the continuous use of PHRs improved diabetes management outcomes. In addition, the HbA_1c reduction pattern was prominent in the PHR continuous user group. Although the continued use of PHRs has proven to be effective in managing diabetes, further evaluation of its effectiveness for various diseases and a study on PHR adherence are also required.

Integrated Care Intervention Supported by a Mobile Health Tool for Patients Using Noninvasive Ventilation at Home: Randomized Controlled Trial

BACKGROUND

Home-based noninvasive ventilation has proven cost-effective. But, adherence to therapy still constitutes a common clinical problem. We hypothesized that a behavioral intervention supported by a mobile health (mHealth) app could enhance patient self-efficacy. It is widely accepted that mHealth-supported services can enhance productive interactions among the stakeholders involved in home-based respiratory therapies.

OBJECTIVE

This study aimed to measure changes in self-efficacy in patients with chronic respiratory failure due to diverse etiologies during a 3-month follow-up period after the intervention. Ancillary objectives were assessment of usability and acceptability of the mobile app as well as its potential contribution to collaborative work among stakeholders.

METHODS

A single-blind, single-center, randomized controlled trial was conducted between February 2019 and June 2019 with 67 adult patients with chronic respiratory failure undergoing home-based noninvasive ventilation. In the intervention group, a psychologist delivered a face-to-face motivational intervention. Follow-up was supported by a mobile app that allowed patients to report the number of hours of daily noninvasive ventilation use and problems with the therapy. Advice was automatically delivered by the mobile app in case of a reported problem. The control group received usual care. The primary outcome was the change in the Self Efficacy in Sleep Apnea questionnaire score. Secondary outcomes included app usability, app acceptability, continuity of care, person-centered care, and ventilatory parameters.

RESULTS

Self-efficacy was not significantly different in the intervention group after the intervention (before: mean 3.4, SD 0.6; after: mean 3.4, SD 0.5, P=.51). No changes were observed in adherence to therapy nor quality of life. Overall, the mHealth tool had a good usability score (mean 78 points) and high acceptance rate (mean score of 7.5/10 on a Likert scale). It was considered user-friendly (mean score of 8.2/10 on a Likert scale) and easy to use without assistance (mean score of 8.5/10 on a Likert scale). Patients also scored the perception of continuity of care and person-centered care as high.

CONCLUSIONS

The integrated care intervention supported by the mobile app did not improve patient self-management. However, the high acceptance of the mobile app might indicate potential for enhanced communication among stakeholders. The study identified key elements required for mHealth tools to provide effective support to collaborative work and personalized care.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03932175; https://clinicaltrials.gov/ct2/show/NCT03932175.

mHealth Family Adaptation Intervention for Families of Young Children with Down Syndrome: A Feasibility Study

PURPOSE

The aim of this study was to explore the feasibility of using the mHealth Family Adaptation Intervention (FamilyAdapt-DS), with families of young children with Down syndrome (DS), and to assess the effect of participating in this mHealth intervention on family adaptation.

DESIGN AND METHODS

A one-group pre-test post-test design was employed. Sixteen parents from eight families of young children with DS (under the age of three years) participated in this study between September 2015 and September 2016. A Wilcoxon signed rank test was used to identify the difference between the pre-test and post-test scores.

RESULTS

All parents perceived that the program was feasible to use and they were willing to recommend the intervention to other families. Improvements were noted between pre-test and post-test scores. For fathers, views of their child's daily life became more positive, their child's condition became more manageable, their problem-solving communication became more affirming and their family functioning scores improved. Mothers reported less difficulty managing their child's condition.

CONCLUSIONS

These findings suggest that FamilyAdapt-DS is a feasible m-Health intervention for families of young children with DS; however, scaling up of this program with larger and more diverse samples is needed to test its effectiveness.

PRACTICE IMPLICATIONS

Nurses and other healthcare providers may find it helpful to use therapeutic conversations and mHealth interventions such as the one described in this paper to tailor the care they provide to families of young children with DS.

The Use of Measurement Systems to Support Patient Self-Management of Long-Term Conditions: An Overview of Opportunities and Challenges

Long-term conditions are a major public health concern that present many challenges for patients living with them. There is increasing policy focus on promoting patient self-management and supporting patients to take ownership of managing their conditions. Because long term conditions often fluctuate over time, ongoing monitoring of disease activity is necessary for self-management; this can be achieved through using Patient Reported Outcome Measures (PROMs). PROMs can provide additional information about patients' symptoms, functioning, and emotional wellbeing, informing clinical care for patients. Measurement systems are an innovative method to gather and report PROMs throughout a patient's course of care, to support clinical practice and improve overall quality of care. Measurement systems are often delivered via a digital platform, which can convey patient-reported information to healthcare professionals and provide tailored self-management advice to patients, all based on information collected via PROMs. There are a number of potential benefits of this approach to self-management. Measurement systems can improve clinical practice, creating efficient clinical encounters and positively influencing patient-clinician interactions. The use of monitoring throughout a patient's care is also thought to empower patients, by improving their knowledge of their condition, increasing their engagement with their health, and influencing their overall management of their condition. Challenges associated with using measurement systems in this way include finding appropriate PROMs, provisioning of suitable technology, and limiting the burden for patients. To increase the implementation of measurement systems into practice it is important to consider how to engage and educate healthcare professionals and patients to empower their use. Overall, adopting measurement systems into clinical practice may improve clinicians' ability to support patient self-management of long-term conditions.

The impact of an mHealth app on knowledge, skills and anxiety about dressing changes: A randomized controlled trial

AIMS

To evaluate the effectiveness of a mobile health (mHealth) application, based on self-regulation theory, on patients' knowledge of wound care, skills in changing dressings and anxiety.

DESIGN

A prospective randomized controlled trial.

METHODS

Seventy patients (or family members) at a 1,500-bed university hospital in Taiwan were randomized into an experimental (N = 35) or control group (N = 35) from March to December 2016. The experimental group used a mHealth application for wound care; the control group received verbal instructions and a booklet. Instruments to collect data were a wound care knowledge scale, wound care skills scale, State-Trait Anxiety Inventory, and a digital heart variability device. Data were collected at baseline, after three additional demonstrations and before discharge. The generalized estimating equation was used for statistical analysis.

RESULTS

The experimental group showed significantly higher levels of wound care knowledge, improved wound care skills, lower levels of state anxiety, and lower heart rate variability than the control group after baseline data collection.

CONCLUSIONS

Results support hat a mHealth application may be effective in health education. Clinicians can use the results to promote patients' wound care knowledge, enhance their wound care skills, and reduce anxiety related to dressing changes.

IMPACT

Lack of wound care knowledge and skills can affect the willingness and ability to perform effective wound dressing changes, producing anxiety and having an impact on a patient's self-care after hospital discharge. mHealth applications (apps) have the potential to deliver health information in targeted and tailored ways that strengthen the self-management of diseases. mHealth app can increase wound care knowledge, improve care skills, and reduce anxiety related to wound care. mHealth app effectively supports self-monitoring of the wound healing process, self-judgement of the wound condition, and self-reaction of wound care accuracy. mHealth app provides step-by-step visual tutorials on wound care that allow patients and family caregivers to take pictures of the wounds and monitor the wound healing process. mHealth app for wound care knowledge is an effective and individualized method for learning.

CLINICAL TRIAL

This study was registered by U.S. National Library of Medicine, ClinicalTrials.gov (ID: NCT03683303).

Need Assessment for Smartphone-Based Cardiac Telerehabilitation

Objectives

To identify the current status of smartphone usage and to describe the needs for smartphone-based cardiac telerehabilitation of cardiac patients.

Methods

In 2016, a questionnaire survey was conducted in a supervised ambulatory cardiac rehabilitation (CR) program in a university affiliated hospital with the participation of heart failure or heart transplantation patients who were smartphone users. The questionnaire included questions regarding smartphone usage, demands for smartphone-based disease education, and home health monitoring systems. Results were described and analyzed according to principal diagnosis.

Results

Ninety-six patients (66% male; mean age, 53 ± 11 years), including 56 heart failure and 40 heart transplantation patients, completed the survey (completion rate, 95%). The median daily smartphone usage time was 120 minutes (interquartile range, 60-300), and the most frequently used smartphone function was text messaging (61.5%). Of the patients, 26% stated that they searched for health-related information using their smartphones more than 1 time per week. The major source of health-related information was Internet browsing (50.0%), and the least sought source was the hospital's website (3.1%). Patients with heart failure expressed significantly higher needs for disease education on treatment plan, home health monitoring of blood pressure, and body weight (χ² = 5.79, 6.27, 4.50, p < 0.05). Heart transplantation patients expressed a significant need for home health monitoring of body temperature (χ² = 5.25, p < 0.05).

Conclusions

Heart failure and heart transplantation patients show high usage of and interest in mobile health technology. A smartphone-based cardiac telerehabilitation program should be developed based on high demand areas and modified to suit to each principal diagnosis.