Nurse-guided Mobile Health Care Program to Reduce Emotional Distress Experienced by Parents of Infants Prenatally Diagnosed with Critical Congenital Heart Disease: A Pilot Study

Background

Following prenatal diagnosis of critical congenital heart disease (CCHD), parents encounter emotional distress while facing caregiving challenges. Supportive psycho-educational interventions using mobile health (mHealth) can make care more accessible.

Objectives

We tested a novel nurse-guided mHealth care program, Preparing Heart and Mind™ (PHM™), with the objectives of examining feasibility and estimating the effect of the intervention on parents' emotional distress.

Methods

This pilot study design randomized participants using a 2:1 intervention to control ratio. Analysis involved description of retention, and intervention attendance and engagement, and adjusted linear mixed models to estimate group differences in depressive (CES-D), anxiety (STAI-S), and traumatic stress (IES-r) symptoms.

Results

The sample included 55 parents (n=38 PHM™ group, n=17 control). Complete retention of 37 (67%) parents included 29 (76%) in the PHM™ group and 8 (47%) control. Most attrition was due to infant death (7 parents), transplant referral (2 parents), or postnatal diagnostic ineligibility (4 parents). For the PHM™ group, ≥96% of parents attended pre- and postnatal sessions and most (65%) messaged with the nurse. mHealth engagement was highest prenatally, with handling uncertainty the most viewed topic (average 94% pages viewed). In linear mixed models analyses, the PHM™ group had on average 4.84 points lower depression (95% CI: -10.68-1.04), 6.56 points lower anxiety (-14.04-0.92), and 6.28 points lower trauma (-14.44-1.88) scores by study end.

Conclusion

Findings suggest that a nurse-guided mHealth approach is feasible and may contribute to a clinically important reduction in parents' emotional distress.

The landscape of decentralized clinical trials (DCTs): focusing on the FDA and EMA guidance

Decentralized clinical trials (DCTs) consist of off-site trial-related procedures referred to as decentralized elements. We aimed to provide an overview of the landscape of DCTs by comparing regulatory guidance reports and analyzing decentralized elements from clinical trial registries. Two guidance reports on DCTs published by the U.S. Food and Drug Administration and the European Medicines Agencies were summarized and analyzed. Both guidance publications commonly emphasized an assessment of the appropriateness of decentralized elements along 2 axes: patient safety and data integrity. DCT cases were identified from ClinicalTrials.gov by searching with 6 keywords: decentralized, remote, mobile, digital, virtual, and hybrid. Cases where the keyword was used in a non-DCT context, such as digital flexor tendon, were excluded by means of natural language processing. A total of 4,874 trials were identified as DCT cases, with annual increases, especially after 2020. The most common keywords were 'mobile' and 'digital' (36.2% and 24.8%, respectively). Interventions in the DCT cases were analyzed by means of a network analysis. Behavioral and technological tokens were frequently combined, such as 'rehabilitation' and 'app.' Drugs were used in only 1.8% of the DCT cases. Of these, most drugs had been approved previously (96.8%) and were in oral formulation (67.2%). Most of the DCT cases identified in this study involved simple interventions and low-risk drugs. These characteristics were in accordance with the common recommendations in the DCT guidance publications.

Identification of Atrial Fibrillation With Single-Lead Mobile ECG During Normal Sinus Rhythm Using Deep Learning

BACKGROUND

The acquisition of single-lead electrocardiogram (ECG) from mobile devices offers a more practical approach to arrhythmia detection. Using artificial intelligence for atrial fibrillation (AF) identification enhances screening efficiency. However, the potential of single-lead ECG for AF identification during normal sinus rhythm (NSR) remains under-explored. This study introduces a method to identify AF using single-lead mobile ECG during NSR.

METHODS

We employed three deep learning models: recurrent neural network (RNN), long short-term memory (LSTM), and residual neural networks (ResNet50). From a dataset comprising 13,509 ECGs from 6,719 patients, 10,287 NSR ECGs from 5,170 patients were selected. Single-lead mobile ECGs underwent noise filtering and segmentation into 10-second intervals. A random under-sampling was applied to reduce bias from data imbalance. The final analysis involved 31,767 ECG segments, including 15,157 labeled as masked AF and 16,610 as Healthy.

RESULTS

ResNet50 outperformed the other models, achieving a recall of 79.3%, precision of 65.8%, F1-score of 71.9%, accuracy of 70.5%, and an area under the receiver operating characteristic curve (AUC) of 0.79 in identifying AF from NSR ECGs. Comparative performance scores for RNN and LSTM were 0.75 and 0.74, respectively. In an external validation set, ResNet50 attained an F1-score of 64.1%, recall of 68.9%, precision of 60.0%, accuracy of 63.4%, and AUC of 0.68.

CONCLUSION

The deep learning model using single-lead mobile ECG during NSR effectively identified AF at risk in future. However, further research is needed to enhance the performance of deep learning models for clinical application.

Development of a web-based care networking system to support visiting healthcare professionals in the community

BACKGROUND

The role of visiting health services has been proven to be effective in promoting the health of older populations. Hence, developing a web system for nurses may help improve the quality of visiting health services for community-dwelling frail older adults. This study was conducted to develop a web application that reflects the needs of visiting nurses.

METHODS

Visiting nurses of public health centers and community centers in South Korea participated in the design and evaluation process. Six nurses took part in the focus group interviews, and 21 visiting nurses and community center managers participated in the satisfaction evaluation. Focus group interviews were conducted to identify the needs of visiting nurses with respect to system function. Based on the findings, a web application that can support the effective delivery of home visiting services in the community was developed. An artificial intelligence (AI) algorithm was also developed to recommend health and welfare services according to each patient's health status. After development, a structured survey was conducted to evaluate user satisfaction with system features using Kano's model.

RESULTS

The new system can be used with mobile devices to increase the mobility of visiting nurses. The system includes 13 features that support the management of patient data and enhance the efficiency of visiting services (e.g., map, navigation, scheduler, protocol archives, professional advice, and online case conferencing). The user satisfaction survey revealed that nurses showed high satisfaction with the system. Among all features, the nurses were most satisfied with the care plan, which included AI-based recommendations for community referral.

CONCLUSIONS

The system developed from the study has attractive features for visiting nurses and supports their essential tasks. The system can help with effective case management for older adults requiring in-home care and reduce nurses' workload. It can also improve communication and networking between healthcare and long-term care institutions.

The effect of health literacy intervention on adherence to medication of uncontrolled hypertensive patients using the M-health

BACKGROUND

Given that patients' medication adherence is regarded as the major part of disease control and improving health literacy can be effective in promoting adherence to healthy behaviors, the present study aimed to investigate the effect of health literacy intervention based on the medication adherence among uncontrolled hypertensive patients using mobile health (M-health).

METHODS

An interventional study with a quasi-experimental design, was conducted on 118 uncontrolled hypertensive patients. Participants were randomly divided into the intervention (n = 59) and control (n = 59) groups using blocked randomization. In the intervention group, a mobile health (M-health) program was designed using programmed instruction to improve patients' health literacy over a period of 3 months. Data was collected by administering health literacy and medication adherence questionnaires to participants before and after the intervention. The analysis involved using the independent sample t-test to compare the variables before and after the study.

RESULTS

Before the intervention, the total score of health literacy was 33.34 and 33.14 in the intervention and control groups, respectively. After the intervention, it increased to 40.36 and 34.20 in the intervention and control groups, respectively, which was statistically significant in the intervention group (p = 0.01). Moreover, the medication adherence score of the intervention group significantly increased after the intervention. Both systolic and diastolic blood pressure decreased in the intervention group. However, it should be noted that the decrease in systolic blood pressure by 148.98 was statistically significant, while the decrease observed in diastolic blood pressure in the intervention group was not statistically significant (p = 0.08).

CONCLUSION

The application of programmed instruction through M-Health has shown a positive effect on the health literacy of uncontrolled hypertensive patients. In addition to detecting and treating patients, it is important to prioritize the improvement of health literacy in terms of medication adherence and the adoption of healthy behaviors.

[Utility of the Abeona Health® app for patient participation in the identification of chemotherapy-induced toxicity according to the CTCAE classification]

OBJECTIVE

Since 2003, the National Cancer Institute (NCI) of the United States of America has been one of the world leaders in classifying adverse effects (AEs). Currently, smartphones allow, among many other things, the monitoring of these AEs of chemotherapy from home to improve the safety and quality of life of patients. The aim was to perform a descriptive comparative analysis of the AEs content of the Abeona Health® app and the latest version of the CTCAE (Common Terminology Criteria for Adverse Events).

METHODS

The Abeona Health® app and the CTCAE v5 guide were used. Subsequently, the most recurrent AEs in the existing chemotherapy treatment were analysed according to the NCI and the Spanish Society of Medical Oncology (SEOM) and finally, whether patients could identify them.

RESULTS

The CTCAE v5 (collects 837 AEs), where two hundred and twenty-five are signs and symptoms. The NCI classifies fifty-five signs and symptoms as the most recurrent, and the SEOM sixteen, of which fifteen coincide with the NCI. The Abeona Health® application has seven AEs, all included in the CTCAE v5. Of these seven, six appear in the NCI lists of most recurrent AEs and four in the SEOM list, all identifiable by the patient.

CONCLUSIONS

The Abeona Health® app is considered adequate for the patient participation in their self-care, although some fields could be expanded.

The efficacy of theory driven treatment adherence promotion program among type 2 diabetic patients: application of intervention mapping and mHealth

Background

Mobile health interventions (mHealth) may improve health-related lifestyle behaviors and disease management. Successful management of diabetes is patient-centered responsibility. The aim of this research was to determine the efficacy of the theory driven program of promoting treatment adherence in type 2 diabetes (T2DM) patients based on mHealth.

Methods

This quasi-experimental research was conducted on 70 T2DM patients in Tehran, Iran. Participants were randomly divided into intervention (n = 35) or control (n = 35) groups. The data collection tool was a questionnaire based on some of constructs Social Cognitive Theory (SCT) which elicit from formative evaluation. The SCT theory-based intervention program was developed, implemented, and evaluated based on Intervention Mapping (IM) as a framework in 8 sessions using online WhatsApp application. The data was collected through by online interviews before and one month after the implementation of the program and analyzed in SPSS version 16.

Results

After the implementation of the program, a significant increase in self-efficacy (P = 0.009), outcome expectations (P < 0.001), and also diabetes treatment adherence behaviors (P = 0.024) were indicated in the intervention group. The estimated effect sizes for self-efficacy, outcome expectations, social support, and diabetes treatment adherence behaviors were 0.78, 0.06, 0.07, and 0.62, respectively.

Conclusion

Estimated effect size of the implemented intervention was evaluated as "large" effect for diabetes treatment adherence behaviors. Findings indicated the usefulness and efficacy of the mHealth educational program based on SCT constructs and the IM approach in treatment adherence behaviors promotion among T2DM patients in Iran.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-023-01291-5.

Impact of Kayumidas© app on subjective symptoms and treatment adherence in allergic Rhinoconjunctivitis: Prospective Single-Arm interventional pilot study

INTRODUCTION

In the spring of 2021, a physician-supervised application (app) "Kayumidas© - Itchy Eye Alert" was released for allergy sufferers, which implements a function to predict pollen dispersal status for each user based on weather forecasts and notify users of the results. This app provides push notifications of warning levels of itchiness and other symptoms, countermeasures, and the time to use medication. However, no evaluation has been conducted to determine whether the use of app improves compliance with treatment. This study aimed to verify whether the use of a smartphone app is effective in relieving the symptoms of allergic conjunctivitis and rhinitis and how it changes patients' eye drop behavior.

METHODS

This was an investigator-initiated, observational, prospective cohort study that was conducted between February 2022 and May 2022. In 62 patients diagnosed with allergic conjunctivitis, the scores of nine subjective eye and nose symptoms (1-4) and eye itchiness (1-7) before and after using the app were compared using a questionnaire. The adherence scores for eye drops (1-4) were also investigated using a questionnaire.

RESULTS

The scores for all five ocular subjective symptoms and all four nasal subjective symptoms improved significantly after app use (p < 0.01). Both itching scores (4.1 ± 1.1 vs. 1.6 ± 0.5, p < 0.01) and eye drop compliance scores (2.0 ± 0.7 vs. 3.9 ± 0.3, p < 0.01) improved significantly after app use.

CONCLUSION

The use of the Kayumidas© app improved adherence to eye drops and the subjective symptoms of allergic conjunctivitis and rhinitis. Thus, app use effectively improves symptoms by changing behavior and improving self-care awareness regarding treatment in patients with allergic diseases.

Estimating Cognitive Load in a Mobile Personal Health Record Application: A Cognitive Task Analysis Approach

OBJECTIVES

Mobile health applications that are designed without considering usability criteria can lead to cognitive overload, resulting in the rejection of these apps. To avoid this problem, the user interface of mobile health applications should be evaluated for cognitive load. This evaluation can contribute to the improvement of the user interface and help prevent cognitive overload for the user.

METHODS

In this study, we evaluated a mobile personal health records application using the cognitive task analysis method, specifically the goals, operators, methods, and selection rules (GOMS) approach, along with the related updated GOMS model and gesture-level model techniques. The GOMS method allowed us to determine the steps of the tasks and categorize them as physical or cognitive tasks. We then estimated the completion times of these tasks using the updated GOMS model and gesture-level model.

RESULTS

All 10 identified tasks were split into 398 steps consisting of mental and physical operators. The time to complete all the tasks was 5.70 minutes and 5.45 minutes according to the updated GOMS model and gesture-level model, respectively. Mental operators covered 73% of the total fulfillment time of the tasks according to the updated GOMS model and 76% according to the gesture-level model. The inter-rater reliability analysis yielded an average of 0.80, indicating good reliability for the evaluation method.

CONCLUSIONS

The majority of the task execution times comprised mental operators, suggesting that the cognitive load on users is high. To enhance the application's implementation, the number of mental operators should be reduced.

Menstrual Cycle Tracking Apps: An Applied Combined Medical and Data Privacy Scoring

Today, many menstruating individuals track their cycles with mobile apps. These cycle apps use a lot of highly sensitive personal data. The goal of this study is to evaluate current cycle apps based on data privacy and medical criteria. First, a market analysis of currently available apps was conducted. Second, a scoring system was developed based on Digital Health application (Digitale Gesundheitsanwendungen, DiGA in German) guidelines, Mobile App Rating Scale (MARS), and other resources. A total of 18 apps were evaluated. The final scores (range from 0 to 1) ranged from 0.12 (worst result) to 0.64 (best result). The average "data privacy score" was 0.4, and the average "medical score" was 0.11. Only six apps received any points in the medical part of the scoring. A clear weakness of many tested apps was the issue of data minimization. 89% of the apps had permissions that were not necessary for this type of health app.

Nonlinear, Multicomponent Physical Exercise With Heart Rate Variability-Guided Prescription in Women With Breast Cancer During Treatment: Feasibility and Preliminary Results (ATOPE Study)

OBJECTIVE

The purpose of this study was to examine the feasibility, safety, adherence, and preliminary efficacy of the ATOPE program during radiotherapy (RT) or chemotherapy (CT) for women with breast cancer.

METHODS

This single-blind, pretest-posttest feasibility study included 38 women with breast cancer at the beginning of their treatment. The ATOPE program consisted of 12 to 18 sessions of a multimodal physical exercise program, prescribed based on daily heart rate variability and clinimetric assessments using the ATOPE+ mHealth system. Overall health was assessed with quality of life, autonomous balance, and body composition, whereas health-related fitness was measured through functional capacity, physical activity levels, and upper and lower limb strength.

RESULTS

The rates of recruitment, retention, and adherence were 52.35, 73.68, and 84.37%, respectively, and the satisfaction rating was 9.2 out of a possible 10 points. The perceived health status change score was 3.83 points, scored on a -5 to 5 point scale. No adverse effects were found. Compliance results showed that the ATOPE+ mHealth system was used on 73.38% of the days, and the Fitbit bracelet (Google, Mountain View, CA, USA) was used on 84.91% of the days. Women stayed physically active 55% of days. Regarding preliminary results, for overall health, the percentage of body fat in the RT group decreased by 1.93%, whereas it increased by 5.03% in the CT group. Lower limb strength increased in the RT group, specifically knee extensor isometric strength (6.07%), isokinetic knee flexors 180 degree/second (1.53%), and isokinetic knee extensors 300 degree/second (4.53%), in contrast with the reductions found in the CT group (11.07, 18.67, and 14.89%, respectively).

CONCLUSION

The ATOPE program, through nonlinear prescription based on daily monitoring with the ATOPE+ mHealth system, is feasible and safe for application during breast cancer treatment. The results suggest that the overall health can be maintained or even improved regarding most variables.

IMPACT

This study focused on the feasibility, safety, and completion of a physical therapist-led program at early diagnosis for adults with breast cancer. The multimodal, supervised, tailored, nonlinear physical exercise program is feasible and safe, showed a good completion rate, and was able to prevent the quality-of-life deficits that are often triggered by systemic breast cancer treatment. This study highlights the importance of daily morning assessments using the ATOPE+ mHealth system in patients with breast cancer to prescribe nonlinear physical exercise.

Development and pilot study of "Smart Cancer Care": a platform for managing side effects of chemotherapy

BACKGROUND

As outpatient chemotherapy treatment increases, cancer patients receiving chemotherapy spend more time at home. In addition, since the types of chemotherapy are gradually expanding, it will be essential to prepare patient self-management strategies for various chemotherapy-related side effects. This study aimed to develop a platform (called Smart Cancer Care) to implement a chemotherapy side effect management program and to evaluate its feasibility.

METHODS

Smart Cancer Care comprises an application for patients and a dashboard for medical staff. Thirty-two symptoms to be managed using Smart Cancer Care were summarized through a literature review and Delphi. Management guidelines were developed based on the severity of each symptom (3 stages), and installed in Smart Cancer Care according to the Common Terminology Criteria for Adverse Events (CTCAE) v5.0 guidelines. To evaluate the feasibility of the developed application and medical dashboard, cancer patients and cancer treatment medical staff used Smart Cancer Care for 2 to 3 weeks and subsequently reported the experience of using them.

RESULTS

The patient application provided a list of symptoms according to the cancer type and anticancer drug enabling presence and severity of each symptom to be evaluated. Patients received management guidelines for symptoms based on the symptom evaluation results. On the medical staff dashboard, administrators and authorized medical personnel could access and assess information regarding side effects and symptom severity submitted by the patient. The feasibility and usefulness of Smart Cancer Care were confirmed through a pilot test targeting 30 patients and 24 chemotherapy-related medical staff. For patients, the evaluation score for the "The program will be helpful when seeing medical staff" item was the highest. For medical staff, the score for the "By checking the patient's symptoms using the program, it helps to take appropriate measures for the patient" item was the highest. Although minor corrections were raised, most patients and medical staff expected that Smart Cancer Care would help their treatment.

CONCLUSIONS

The configuration of the application and dashboard of Smart Cancer Care detailed in this study could be used for the development of a widely accepted platform to implement a chemotherapy side effect management program.

Stability monitoring of patients with myasthenia gravis using a mobile-based application

Background: Failure in early diagnosis of myasthenia gravis (MG) and the risks of taking certain medications and undergoing surgery and anesthesia can lead to severe respiratory disorders and death. However, there are therapeutic measures that significantly control the disease and improve individual's functionality. Methods: First, an expert panel was formed, and a needs assessment questionnaire was prepared for the information elements and the capabilities required for the application and provided to neurologists with a subspecialty fellowship in neuromuscular diseases. Then, based on the analyzed results, the application was designed and created in 2 versions (physician and patient), and in 2 languages (Persian and English). Eventually, a questionnaire for user interaction and satisfaction was provided to 5 relevant physicians to evaluate the application. Results: The results showed that neurologists considered all items of the needs assessment questionnaire to be 100% essential. The capabilities of the application included registering the medication name and dose, recording symptoms and complaints by the patient, completing standard questionnaires, online chat, medication reminder, sending alerts to the doctor when the patient is unwell, and providing a variety of reports. The usability evaluation showed that neurologists evaluated the application at a good level with the average score of 8.23 ± 0.47 (out of 9 points). Conclusion: In the long run, using this technology can reduce costs, improve patients' quality of life (QOL) and health care, change health behaviors, and ultimately, improve individual's health.

Development and Validation of Simple Risk Scores to Predict Hospitalization in Outpatients with COVID-19 Including the Omicron Variant

Outpatient physicians need guidance to support decisions regarding hospitalization of COVID-19 patients and how closely to follow outpatients. Thus, we sought to develop and validate simple risk scores to predict hospitalization for outpatients with COVID-19 that do not require laboratory testing or imaging. METHODS: We identified outpatients 12 years and older who had a positive polymerase chain reaction test for SARS-CoV-2. Logistic regression was used to derive a risk score in patients presenting before March, 2021, and it was validated in a cohort presenting from March to September 2021 and an Omicron cohort from December, 2021 to January, 2022. RESULTS: Overall, 4.0% of 5843 outpatients in the early derivation cohort (before 3/1/21), 4.2% of 3806 outpatients in the late validation cohort, and 1.2% in an Omicron cohort were hospitalized. The base risk score included age, dyspnea, and any comorbidity. Other scores added fever, respiratory rate and/or oxygen saturation. All had very good overall accuracy (AUC 0.85-0.87) and classified about half of patients into a low-risk group with < 1% hospitalization risk. Hospitalization rates in the Omicron cohort were 0.22%, 1.3% and 8.7% for the base score. Two externally derived risk scores identified more low risk patients, but with a higher overall risk of hospitalization than our novel risk scores. CONCLUSIONS: A simple risk score suitable for outpatient and telehealth settings can classify over half of COVID-19 outpatients into a very low risk group with a 0.22% hospitalization risk in the Omicron cohort. The Lehigh Outpatient COVID Hospitalization (LOCH) risk score is available online as a free app: https://ebell-projects.shinyapps.io/LehighRiskScore/.

Evaluation of Usability and User Experience of Oncodoc 's M-Health Application for Early Detection of Cancer

OBJECTIVE

Cancer is a non-communicable disease that accounts for 71% of deaths globally. The prevalence of people living with cancer in Indonesia increased from 1.4/1000 population (2013) to 1.8/1,000 population (2018). This study aims to evaluate usability, user experience, and user feedback on the use of the Oncodoc m-health application.

METHODS

 The research method uses mixed methods with a cross-sectional approach and online survey sampling techniques (677 respondents), in December 2021-January 2022 in Indonesia. The instruments used are the System Usability Scale and User Experience Questionnaire. The variables measured include the characteristics of respondents, usability, user experience, and responses to using applications qualitatively. Quantitative data were analysed descriptively and the User Experience Questionnaire's analysis tool. Qualitative data were analysed thematically.

RESULTS

Evaluation of the usability of Oncodoc's m-health application is in the "acceptable" category (70.88), and the adjective rating is in the "Good" category. Evaluations of the relative quality of user experience are in the "good" and "very good" types. The average user experience scale is (mean; SD): attractiveness (1.80; 0.99), perspicuity (1.82; 1.05), efficiency (1.78; 1.09), dependability (1.56; 1.01), stimulation (1.81; 1.06), and novelty (1.32; 1.10). The findings of this study are 1) the ability to accommodate user needs, 2) usage barriers, and 3) user expectations for the Oncodoc application.

CONCLUSION

Overall, the Oncodoc m-health application is acceptable to users. We recommend developing a cancer early detection application with an approach that refers to user needs for further research.

Development and Validation of Simple Risk Scores to Predict Hospitalization in Outpatients with COVID-19 Including the Omicron Variant

INTRODUCTION

Outpatient physicians need guidance to support decisions regarding hospitalization of COVID-19 patients and how closely to follow outpatients. Thus, we sought to develop and validate simple risk scores to predict hospitalization for outpatients with COVID-19 that do not require laboratory testing or imaging. METHODS: We identified outpatients 12 years and older who had a positive polymerase chain reaction test for SARS-CoV-2. Logistic regression was used to derive a risk score in patients presenting before March, 2021, and it was validated in a cohort presenting from March to September 2021 and an Omicron cohort from December, 2021 to January, 2022. RESULTS: Overall, 4.0% of 5843 outpatients in the early derivation cohort (before 3/1/21), 4.2% of 3806 outpatients in the late validation cohort, and 1.2% in an Omicron cohort were hospitalized. The base risk score included age, dyspnea, and any comorbidity. Other scores added fever, respiratory rate and/or oxygen saturation. All had very good overall accuracy (AUC 0.85-0.87) and classified about half of patients into a low-risk group with < 1% hospitalization risk. Hospitalization rates in the Omicron cohort were 0.22%, 1.3% and 8.7% for the base score. Two externally derived risk scores identified more low risk patients, but with a higher overall risk of hospitalization than our novel risk scores. CONCLUSIONS: A simple risk score suitable for outpatient and telehealth settings can classify over half of COVID-19 outpatients into a very low risk group with a 0.22% hospitalization risk in the Omicron cohort. The Lehigh Outpatient COVID Hospitalization (LOCH) risk score is available online as a free app: https://ebell-projects.shinyapps.io/LehighRiskScore/.

A Mobile Health Application to Enhance Self-Management Skills of Patients with Shoulder Impingement Syndrome During Rehabilitation

Especially in chronic diseases, such as shoulder impingement syndrome (SIS), good self-management is important for patients to take personal responsibility for their treatment and make informed decisions in rehabilitation processes. Mobile apps integrating game design elements have great potential to increase patients self-management skills. A total of 21 functionalities for a self-management app were derived from semi-structured interviews with six patients and three therapists. Thereby, welcome messages, a personalized home-screen, and training plans are rated as particular useful. Ten of these functionalities could be implemented in a first prototype of SISco: your shoulder impingement syndrome companion. SISco provides possibilities for creating and executing training programs, learning about SIS, checking daily challenges, and making diary entries. Thereby, SISco motivates patients via progress bars, collecting XP, unlocking content and Dr. SISco the virtual therapist. Future work includes the implementation of further functionalities and the evaluation of SISco for usability and user acceptance.

Evaluation of the Usability of a Mobile Application on Neglected Skin Diseases in Côte d'Ivoire: A Pilot Study

This study investigated the usability of a mobile phone-based system, "eSkinHealth", for healthcare providers in Côte d'Ivoire. The eSkinHealth can be used both online and offline to address the poor Internet connectivity of these rural settings. Data recorded in the mobile application were synchronized with an online database, and specialists in Abidjan, Côte d'Ivoire and in Japan advised local healthcare providers on difficult cases. In this pilot study, 21 healthcare providers used the eSkinHealth and completed questionnaires assessing the usability. The average score of a system usability scale for eSkinHealth was 84.2 (SD 11.7), which can be interpreted as excellent. The average registration for patient information (e.g., name, sex, age, area of residence) was 8.6 (SD 15.5). Further studies with more targeted areas and participants are needed to evaluate the usability of eSkinHealth in rural Côte d'Ivoire.

Digital Methodology for Mobile Clinical Decision Support Development in Long-Term Care

The global COVID-19 pandemic has driven innovations in methods to sustain initiatives for the design, development, evaluation, and implementation of clinical support technology in long-term care settings while removing risk of infection for residents, family members, health care workers, researchers and technical professionals. We adapted traditional design and evaluation methodology for a mobile clinical decision support app - designated Mobile Application Information System for Integrated Evidence ("MAISIE") - to a completely digital design methodology that removes in-person contacts between the research team, developer, and nursing home staff and residents. We have successfully maintained project continuity for MAISIE app development with only minor challenges while working remotely. This digital design methodology can be implemented in projects where software can be installed without in-person technical support and remote work is feasible. Team skills, experience, and relationships are key considerations for adapting to digital environments and maintaining project momentum.

Remote Usability Testing to Facilitate the Continuation of Research

Usability testing has historically been an in-person activity where test participants and evaluation researchers are co-located. Recruiting participants into usability studies can be a challenging endeavor especially when potential participants are concerned about time commitments and social distancing. The global COVID-19 pandemic has driven the development of remote usability testing methods. In this paper, we describe remote usability testing as it evolved during a pre-pandemic research study. We adapted our in-person usability evaluation methodology for a commercially available mHealth app to a remote usability testing methodology to accommodate potential participants during a more convenient participant-identified time. In doing so we met the needs, preferences, and availability of our participants and maintained research progress. Adapting to patient-centered needs through remote usability testing has the potential to facilitate continued research and engage potential participants due to its convenience, flexibility, and decrease constraints presented by geographic limits.

Challenges and Facilitators of Using Smartphones in Educational Activities: Medical and Nursing Students' Perspective

BACKGROUND

Todays, smartphone technologies and applications are used in the medical and nursing fields. Medical and nursing students are among the groups in which the use of these tools is observed.

OBJECTIVES

To investigate their views on the barriers and facilitators of the use of these technologies.

METHODS

Four hundred people (200 people from each group) were invited randomly. A questionnaire was used to collect data. To collect data, hospitals were referred and the questionnaires were provided to students and after completion, they were collected. Data analysis was performed using SPSS software and descriptive and inferential statistics.

RESULTS

The most important barriers from the students' view included internet problems in the university or hospital, lack of technical support for this technology in the hospital or university, the quality of existing applications, lack of appropriate Apps in the local language, non-introduction of appropriate Apps and not knowing the right Apps. The most important facilitators were the appropriate support services in the university or hospital, placing the appropriate Apps on the department or university website, designing native Apps with the participation of experts, and introducing the appropriate Apps by professors or universities.

CONCLUSION

The use of Apps is increasing among medical and nursing students. In this regard, attention to the existing barriers and their elimination and strengthening the facilitators, and providing the necessary technical and educational infrastructure to facilitate the useful applications should be considered by decision-makers.

mBalance: Detect Postural Imbalance with Mobile Devices

BACKGROUND

Postural imbalance can be adopted for the early detection of age-related diseases or monitoring the course of the disease treatment; especially in monitoring, frequent balance measurement is crucial. This is mainly done through regular in-person examinations by a physician currently. Feedback in between examinations is often missing.

OBJECTIVES

This paper proposes mBalance, a mobile application that uses the Romberg test to detect postural imbalance. mBalance provides a camera-based, low-cost approach to measure imbalance frequently at home using mobile devices.

METHODS

Imbalance detection accuracy and usability was evaluated in two separate studies with 31 and 30 participants, respectively.

RESULTS

mBalance correctly detected imbalance with a sensitivity of 80% and a specificity of 87%. The study found good usability with no significant problems.

CONCLUSION

Overall, this study solves the problem of postural imbalance detection by digitizing a validated balance test into an easy-to-use mobile application.

Evaluation of the effectiveness of a mobile application in the management of dental anxiety: a randomized controlled trial

OBJECTIVE

The aim of this study was to evaluate the effectiveness of a specially designed mobile application developed to provide patients with a sense of anxiety control during the various stages of endodontic treatment. The patients' anxiety was assessed by measuring their salivary cortisol levels.

METHODS

A total of 46 patients requiring endodontic treatment were recruited. The patients were randomly assigned to two groups. The experimental group used the special communication application, while the control group did not. Salivary samples were collected from all patients preoperatively, postanesthesia, and postoperatively. The samples were analyzed with an enzyme-linked immunosorbent assay to measure the cortisol levels.

RESULTS

A significant difference in cortisol levels was observed between the experimental and the control group (Mann-Whitney U test, P < .05). This difference was significant in the experimental group in each step (P < .01). No difference was found in the control group steps (P > .05).

CONCLUSIONS

Perceived control of anxiety using the specially designed software was effective in reducing salivary cortisol levels.

Melanoma: How and When to Consider Clinical Diagnostic Technologies

In response to rising rates of melanoma worldwide, novel non-invasive melanoma detection techniques are emerging to facilitate the early detection of melanoma and decrease unnecessary biopsies of benign pigmented lesions. Because they often report similar study findings, it may be difficult to determine how best to incorporate these technologies into clinical practice based on their supporting studies alone. As an expansion of the recent article by Fried et al.¹, which reviewed the clinical data supporting these non-invasive melanoma detection techniques, the first article in this continuing medical education series provides practical advice on how and when to use various non-invasive melanoma detection techniques into clinical practice.

Mobile Health Technology and Healthcare Providers: Systemic Barriers to Adoption

Objectives

Despite the growing use of mobile health (mHealth), certain barriers seem to be hindering the use of mHealth applications in healthcare. This article presents a systematic review of the literature on barriers associated with mHealth reported by healthcare professionals.

Methods

This systematic review was carried out to identify studies published from January 2015 to December 2019 by searching four electronic databases (PubMed/MEDLINE, Web of Science, Embase, and Google Scholar). Studies were included if they reported perceived barriers to the adoption of mHealth from healthcare providers’ perspectives. Content analysis and categorization of barriers were performed based on a focus group discussion that explored researchers’ knowledge and experiences.

Results

Among the 273 papers retrieved through the search strategy, 18 works were selected and 18 barriers were identified. The relevant barriers were categorized into three main groups: technical, individual, and healthcare system. Security and privacy concerns from the category of technical barriers, knowledge and limited literacy from the category of individual barriers, and economic and financial factors from the category of healthcare system barriers were chosen as three of the most important challenges related to the adoption of mHealth described in the included publications.

Conclusions

mHealth adoption is a complex and multi-dimensional process that is widely implemented to increase access to healthcare services. However, it is influenced by various factors and barriers. Understanding the barriers to adoption of mHealth applications among providers, and engaging them in the adoption process will be important for the successful deployment of these applications.

[Untact Visit Service Development Based on an Application Reflecting the Circumstances during COVID-19: Focusing on Utilization in the Pediatric Intensive Care Units]

PURPOSE

This study aimed to develop an untact visit service based on an application that can be utilized in the pediatric intensive care unit (PICU) during COVID-19.

METHODS

This study adopted the double diamond process of service design comprising the discovery, defining, and development stages.

RESULTS

We developed an untact visit service based on an application that considered the child's status, schedule, photo, and video messages, and so on. Moreover, we derived a service flow regarding the required roles and the type of flow shown between each stakeholder.

CONCLUSION

Considering the ongoing pandemic, the untact visit service is designed to increase rapport and participation of parents, share the child's information in real-time, and provide one-stop service without increasing healthcare providers' work. It will be a useful visit service that can be applied and evaluated in various hospital settings and the PICU.

A Mobile App to Improve Patient Management in Emergency Departments: Caregiver Needs Analysis, Design and Early Technology Acceptance Assessment

Emergency care is very complex in that it requires patient-centered care in a coordinated manner among multiple providers in a highly distractible, unpredictable and stressful environment. Sharing information efficiently between providers in this context is difficult. Connecting emergency providers with each other through a digital communication channel could improve the efficiency of information sharing and emergency care. This study describes the development process of PIMPmyHospital, a mobile app dedicated to emergency department physicians and nurses to collaboratively manage their patients. We relied on a user-centered design process involving caregivers from a pediatric emergency department. The process started with semi-structured interviews that informed the specifications of the app, followed by an iterative design and development approach. The resulting prototype was evaluated by end-users using the perceived usefulness dimension of the technology acceptance model questionnaire. Early user engagement during the design and development of a dedicated mobile app must be taken into account to improve its perceived usefulness and future adoption.

Research Development Using REDCap Software

OBJECTIVES

High-quality clinical research is dependent on adequate design, methodology, and data collection. The utilization of electronic data capture (EDC) systems is recommended to optimize research data through proper management. This paper's objective is to present the procedures of REDCap (Research Electronic Data Capture), which supports research development, and to promote the utilization of this software among the scientific community.

METHODS

REDCap's web application version 10.4.1 released on 2021 (Vanderbilt University) is an EDC system suitable for clinical research development. This paper describes how to join the REDCap consortium and presents how to develop survey instruments and use them to collect and analyze data.

RESULTS

Since REDCap is a web application that stimulates knowledge-sharing among the scientific community, its development is not finished and it is constantly receiving updates to improve the system. REDCap's tools provide access control, audit trails, and data security to the research team.

CONCLUSIONS

REDCap is a web application that can facilitate clinical research development, mainly in health fields, and reduce the costs of conducting research. Its tools allow researchers to make the best use of EDC components, such as data storage.

The Design and Evaluation of a Mobile based Application to Facilitate Self-care for Pregnant Women with Preeclampsia during COVID-19 Prevalence

Preeclampsia is one of the most common complications of pregnancy that is very difficult to control and manage during the outbreak of COVID-19. One way to control and manage this disease is to use self-care applications. Therefore, the aim of this study was to design and develop a mobile-based application to facilitate self-care for women, who suffer from pregnancy poisoning in the COVID-19 pandemic. This study was conducted in two stages: In the first stage, according to the opinion of 20 obstetricians and pregnant women, a needs assessment was performed. In the second stage, based on the identified needs, the application prototype was designed and then evaluated. For evaluation, 20 pregnant women were asked to use the application for 10 days. QUIS questionnaire version 5.5 was used for evaluation. Descriptive statistics and mann-whitney test in SPSS software version 23 were used for data analysis. Out of the 66 information needs that were identified via the questionnaire, 58 were considered in designing the application. Features of the designed application were placed in 5 categories: User's profile, lifestyle, disease prevention and control, application capabilities and user's satisfaction. The capabilities of the application consist of introducing specialized COVID-19 medical centers, search for the location of medical centers and doctors' offices, drug management, drug allergies, self-assessment, stress reduction and control, nutrition and diet management, sleep management, doctor's appointment reminders, communication with other patients and physicians, application settings. Pregnant women rated the usability of the application at a good level. The designed application can reduce the anxiety and stress due to preeclampsia feel and also improve their knowledge as well as attitude towards the COVID-19 pandemic and preeclampsia.

WA Notify: the planning and implementation of a Bluetooth exposure notification tool for COVID-19 pandemic response in Washington State

Bluetooth exposure notification tools for mobile phones have emerged as one way to support public health contact tracing and mitigate the spread of COVID-19. Many states have launched their own versions of these tools. Washington State's exposure notification tool, WA Notify, became available on November 30, 2020, following a one-month Seattle campus pilot at the University of Washington. By the end of April 2021, 25% of the state's population had activated WA Notify, one of the highest adoption rates in the country. Washington State's formation of an Exposure Notification Advisory Committee, early pilot testing, and use of the EN Express system framework were all important factors in its adoption. Continuous monitoring and willingness to make early adjustments such as switching to automated texting of verification codes have also been important for improving the tool's value. Evaluation work is ongoing to determine and quantify WA Notify's effectiveness, timeliness, and accessibility.

A Smartphone App for Bedside Recording of Nursing Handovers in Haemodialysis Units

The purpose of this study is to present the design, development and initial evaluation of a smartphone software (mobile app), for the needs of nursing bedside shift reporting and documentation. The app records and process nursing handovers concerning haemodialysis patient data, and it runs on Android smartphones, offering a structured and friendly user interface. Data are collected, processed, stored and accessed easily, quickly and securely by authorized users. The evaluation, based on discussions and semi-structured interviews with a group of nurses, showed positive feedback on the user interface, structure and functions of the prototype. It can be a useful and efficient tool for the reporting and communication needs between nurses. Conclusions about the limitations of the study and future developments are reported.

Mobile Health Applications for Rehabilitation of Musculoskeletal Diseases of the Shoulder: A Systematic Analysis

Rehabilitation of musculoskeletal diseases (MSD) of the shoulder is a multifaceted long-term process, which is often not transparent to affected patients. Mobile health applications (apps) have the potential to support this complex process by improving patients' self-management skills. However, there seems to be a lack of apps providing a holistic approach to motivate and guide patients during the whole rehabilitation process. Therefore, a systematic analysis of apps on Google Play Store was conducted by two independent reviewers. A total of 3227 apps were identified, of which 64 met the eligibility criteria for the qualitative analysis. The majority of analyzed apps were developed generally for patients with MSD of the shoulder, rarely for specific diseases (individual needs of patients). The majority of apps focus on the provision of information, exercise training, and alternative medicine. Apps for diagnostics, inpatient treatment, and self-management, especially for multiple rehabilitation phases, are rare or even not existent. Game design elements are seldom used. If there are any, then simple to implement ones, e.g. messages and progress bars. The (psychological) effects of individual game design elements on patients seem to be neglected, when selecting and implementing game-components.

Criteria for Assessing and Recommending Digital Diabetes Tools: A Delphi Study

Diabetes self-management, an integral part of diabetes care, can be improved with the help of digital self-management tools such as apps, sensors, websites, and social media. The study objective was to reach a consensus on the criteria required to assess and recommend digital diabetes self-management tools targeting those with diabetes in Norway. Healthcare professionals working with diabetes care from all health regions in Norway were recruited to participate in a three-round Delphi study. In all rounds, the panellists rated criteria identified in a systematic review and interviews on a scale from 0-10, with the option to provide comments. On a scale of 0:not important to 10:extremely important, the highest rated criteria for assessing and recommending digital diabetes self-management tools were "Usability" and "Information quality", respectively. For assessing apps, "Security and privacy" was one of the lowest rated criteria. Having access to a list of criteria for assessing and recommending digital self-management tools can help diabetes care stakeholders to make informed choices in recommending and choosing suitable apps, websites, and social media for self-management. Future work on quality assessment of digital health tools should place emphasis on security and privacy compliance, to enable diabetes care stakeholders focus on other relevant criteria to recommend or choose and use such tools.

Developing an App for Cardiovascular Prevention and Scientific Data Collection

BACKGROUND

Mobile apps may encourage a lifestyle that avoids unhealthy behaviors, such as smoking or poor nutrition, which promotes cardiovascular diseases (CVD). Yet, little data is available on the utilization, perception, and long-term effects of such apps to prevent CVD.

OBJECTIVES

To develop a mobile app concept to reduce the individual CVD risk and collect information addressing research questions on CVD prevention while preserving data privacy and security.

METHODS

To validate the concept, a prototype will be built, and usability studies will be performed.

RESULTS

We expect to determine whether it is possible to reach a broad user base and to collect scientific information while protecting user data sufficiently.

CONCLUSION

To address CVD prevention, we propose a mobile coaching app. We expect high acceptance rates in validation studies.

Mobile Motion Tracking for Disease Prevention and Rehabilitation Using Apple ARKit

BACKGROUND

Physical activity helps improve the overall quality of life. The correct execution of physical activity is crucial both in sports as well as disease prevention and rehabilitation. Little to no automated commodity solutions for automated analysis and feedback exist.

OBJECTIVES

Validation of the Apple ARKit framework as a solution for automatic body tracking in daily physical exercises using the smartphones' built-in camera.

METHODS

We deliver insights into ARKit's body tracking accuracy through a lab experiment against the VICON system as Gold Standard. We provide further insights through case studies using apps built on ARKit.

RESULTS

ARKit exposes significant limitations in tracking the full range of motion in joints but accurately tracks the movement itself. Case studies show that applying it to measure the quantity of execution of exercises is possible.

CONCLUSION

ARKit is a light-weight commodity solution for quantitative assessment of physical activity. Its limitations and possibilities in qualitative assessment need to be investigated further.

StayHome: A FHIR-Native Mobile COVID-19 Symptom Tracker and Public Health Reporting Tool

As the COVID-19 pandemic continues to unfold and states experience the impacts of reopened economies, it is critical to efficiently manage new outbreaks through widespread testing and monitoring of both new and possible cases. Existing labor-intensive public health workflows may benefit from information collection directly from individuals through patient-reported outcomes (PROs) systems. Our objective was to develop a reusable, mobile-friendly application for collecting PROs and experiences to support COVID-19 symptom self-monitoring and data sharing with appropriate public health agencies, using Fast Healthcare Interoperability Resources (FHIR) for interoperability. We conducted a needs assessment and designed and developed StayHome, a mobile PRO administration tool. FHIR serves as the primary data model and driver of business logic. Keycloak, AWS, Docker, and other technologies were used for deployment. Several FHIR modules were used to create a novel "FHIR-native" application design. By leveraging FHIR to shape not only the interface strategy but also the information architecture of the application, StayHome enables the consistent standards-based representation of data and reduces the barrier to integration with public health information systems. FHIR supported rapid application development by providing a domain-appropriate data model and tooling. FHIR modules and implementation guides were referenced in design and implementation. However, there are gaps in the FHIR specification which must be recognized and addressed appropriately. StayHome is live and accessible to the public at https://stayhome.app. The code and resources required to build and deploy the application are available from https://github.com/uwcirg/stayhome-project.

[Connected health objects and medical devices]

Connected health objects and medical devices.A clear distinction is required between connected devices which change patient's care and those intended to im¬prove his well-being. Connected devices with a medical objective must obtain a CE mark assessing the technical reliability of both the physical piece and the associated software, but also ensuring the control of the hosting of data. Those who demonstrate individual or collective improvement in the diagnosis or treatment of a disease may be financed by the community. This reimbursement is the main tool in France expecting to reduce the digital divide.

Effects of Self-Education on Patient Safety via Smartphone Application for Self-Efficacy and Safety Behaviors of Inpatients in Korea

Objectives

This study aimed to determine whether self-educational intervention on patient safety via a smartphone application could improve the level of self-efficacy and safety behaviors of patients. In addition the effect of change in self-efficacy on the improvement of safety behaviors after self-educational intervention was investigated.

Methods

A one-group pre- and post-test design and convenience sampling were implemented. Self-educational intervention via smartphone application was provided to 94 participants in a tertiary university hospital in South Korea. The smartphone application included learning contents on why the participation of patients is critical in preventing hospital-acquired infections and surgery-related adverse events during hospitalization. Paired t-tests and hierarchical regression analysis were conducted to assess the effect of self-educational intervention and self-efficacy on the improvement of safety behaviors of patients.

Results

After the intervention, the level of self-efficacy and safety behaviors significantly increased from 2.53 to 2.95 and from 2.00 to 2.62, respectively. In the hierarchical regression analysis, the change in self-efficacy accounted for 35.4% of the variance in the improvement of safety behaviors.

Conclusions

The results of this study demonstrated that self-education on patient safety via a smartphone application was an effective strategy to enhance patients’ self-efficacy and safety behaviors. This process could ultimately enhance patient safety by promoting patient involvement during hospitalization and preventing the occurrence of medical errors.

Sleep apps: current limitations and challenges

Sleep app ownership is increasing exponentially, due to their accessibility and ease-of-use. However, there are several concerns regarding the use of sleep apps. Few sleep apps demonstrate empirical evidence to support their claims, and if they do, this evidence can be based on significant methodological limitations. In addition, there are data privacy concerns with regards to sleep apps, which share sensitive user data with business and marketing partners, unbeknownst to their users. Moreover, sleep apps may increase engagement with healthcare professionals, which may place additional strain on under-pressure sleep services. This would be compounded by the fact that some sleep apps produce many false positives, and clinicians would need more time to analyze the data provided by these apps. In the future, sleep apps must undergo rigorous validation studies and grant more autonomy to their users over how their data is shared.

Creating more than a directory: improving handover of information by renovating the induction app for University Hospital Wishaw

Starting in a new hospital can be an overwhelming experience for any grade of doctor. There is a vast amount of information that needs to be learnt immediately to function in the new environment. There is an annual changeover of doctors between hospitals in August nationwide and most junior doctors rotate specialties every 4–6 months. Evidence shows that doctors feel this transition has a negative impact on patient care and indicates that inpatient mortality rises during the August changeover. In our hospital, we noted problems with access to guidelines, referral information and investigations by junior doctors, especially at changeover. In an initial questionnaire, 100% of doctors had experienced difficulties with referring to a specialty and 96% felt time was wasted doing so. Furthermore, 87.5% of doctors had difficulties with ordering laboratory investigations and 100% of survey participates expressed difficulty accessing guidelines.

To tackle this issue, we created guidelines on how to refer to different specialties, order investigations and general running of the hospital. We then used a free app platform called induction and uploaded the guidelines as well as formal hospital guidelines to the app. After use of the app, we assessed these problems via further questionnaires. Doctors reporting problems with finding how to refer to specialties reduced from 100% to 0% in the final survey. Problems finding how to request investigations fell from 100% to 14.3% after 1 month to 7.7% after 3 months. Finally, problems finding guidelines fell from 100% to 15.4%. Further, 100% of doctors felt the app saved time.

Use of the induction app to access guidelines saves time and reduces problems accessing information needed to carry out tasks. This an easily replicated project with low running costs which proved to help with the universal problems around induction to a new hospital environment.

Mobile Applications for Caregivers of Individuals with Chronic Conditions and/or Diseases: Quantitative Content Analysis

BACKGROUND

Mobile health applications can help empowering caregivers and promote their wellbeing and their quality of life.

OBJECTIVE

To analyze the technical and functional characteristics of mobile health applications designed for caregivers of individuals with chronic conditions and/or diseases.

MATERIALS AND METHODS

Systematic search of mobile health applications for smartphones (apps) based on the PRISMA standard for systematic reviews on the App Store and Google Play store during May and June 2018. A second search was carried out on the Pubmed and Google Scholar database to determine whether the applications had been tested or evaluated with results published in scientific journals and then a third search was performed on the Spanish health apps catalogs to evaluate the quality and security of the selected apps.

RESULTS

746 available health apps were identified and 43 were included in this paper. 67% (n = 29) of the apps were aimed exclusively at informal caregivers, 51% (n = 22) were designed to support caregivers and only 21% (n = 9) of them provided any sort of social or emotional support. The screening in Pubmed and Google Scholar determined that the apps analyzed lacked published papers and most of the apps (84%; n = 36) lacked approval from official agencies supporting their usage.

DISCUSSION

The apps available on the market that meet the actual needs of caregivers are limited. Most of the apps were aimed at improving the care of the individual with a chronic illness.

CONCLUSION

Despite the remarkable benefits of mHealth regarding the care of chronic diseases, a relatively poor contribution has been made to support caregivers. Customized apps, interventions assessing their effectiveness and adequate evidence are needed to understand the impact of this digital tool on caregivers' health.

Analysis of Platforms and Functions of Mobile-Based Personal Health Record Systems

OBJECTIVES

Little is known about the platforms and functionalities of mobile-based personal health record (PHR) applications. The objective of this study was to investigate these two features of PHR systems.

METHODS

The unit of analysis was general hospitals with more than 100 beds. This study was based on a PHR survey conducted from May 1 to June 30, 2020 and the National Health Insurance administrative data as of March 31, 2020. The study considered the platform, Android and iPhone operation system (iOS), and types of functionalities of PHR systems. Among the 316 target hospitals, 103 hospitals had adopted PHR systems. A logistic regression analysis was used.

RESULTS

This study found that 103 hospitals had adopted mobile-based PHR systems for their patients. Sixty-four hospitals (62.1%) were adopting both Android and iOS, but 36 (35.0%) and 3 (2.9%) hospitals were adopting Android only or iOS only, respectively. The PHR systems of hospitals adopting both platforms were more likely to have functions for viewing prescriptions, clinical diagnostic test results, and upcoming appointment status compared to those adopting a single platform (p < 0.001). The number of beds (odds ratio [OR] = 1.004; confidence interval [CI], 1.001-1.007; p = 0.0029) and the number of computed tomography systems (CTs) per 100 beds (OR = 6.350; CI, 1.006-40.084; p = 0.0493) were significantly associated with the adoption of both platforms.

CONCLUSIONS

More than 60% of hospitals had adopted both Android and iOS platforms for their patients in Korea. Hospitals adopting both platforms had additional functionalities and significant association with the number of beds and CTs.

Integrating a Secure and Generic Mobile App for Patient Reported Outcome Acquisition into an EHR Infrastructure Based on FHIR Resources

Both patients and physicians of the University Hospital of Erlangen would welcome means of digital data exchange between patients and the hospital. This work presents a system's architecture, FHIR based data model, security measures, and application flow based on patient's smartphones and a public cloud infrastructure to obtain patient reported outcome measures and merge that information with clinical routine data.

Bridging Safety Language Disparities in Orchards: A Pesticide Label Mobile App

Objectives: The goal of this project was to determine if a mobile application displaying pesticide label information in Spanish and English was a viable approach to addressing safety and health disparities for orchard workers. This study assessed pesticide label use patterns in orchards; application user experience; and the potential of modern information systems to deliver bilingual content.Methods: Pesticide handlers and orchard managers were asked to use a mobile application prototype for a period of one month in 2016. A convenience sample of ten participants completed a 36-question interview to share their experiences. The research team summarized interview responses with summary statistics and grouped content analysis.Results: Mean participant (n=10) age was 49. Eight were Latinx and spoke Spanish as their primary language. Six used the app frequently (15 times), one used it sometimes (6 - 10 times), and three used it rarely or occasionally (1 - 5 times). All participants viewed sections about product information and personal protective equipment. Most viewed information related to emergency and first aid, hazards, and storage and disposal. Overall user experience was positive, with an emphasis on the importance of access to label information in Spanish.Conclusion: The overwhelming majority of the Pacific Northwest agricultural workforce is Spanish-speaking, despite critical pesticide safety information being provided on lengthy product label documents in technical English. This project demonstrated that the mobile application seems to be a viable approach to reducing language disparities and improving Latinx orchard worker safety.

Effects of a Mobile-App-Based Self-Management Support Program For Elderly Hemodialysis Patients

Objectives

To identify the effects of a mobile-app-based self-management program for elderly hemodialysis patients on their sick-role behavior, basic psychological needs, and self-efficacy.

Methods

A nonequivalent control group with a non-synchronized design was utilized, and 60 participants (30 in each of the experimental and control groups) were recruited from Chungnam National University Hospital from March to August 2018. The program consisted of continuous training on how to use the mobile-app, self-checking via the app, message transfer through Electronic Medical Records, and feedback. The control group received the usual care. Data were analyzed using the χ²-test, the t-test, the repeated-measures ANOVA, and the McNemar test. A formalized messaging program was developed, and the app was developed with consideration of the specific physical and cognitive limitations of the elderly.

Results

Comparisons were conducted between the experimental (n = 28) and control (n = 28) groups. Statistically significant increases in sick-role behavior, basic psychological needs, and self-efficacy were found in the experimental group (p < 0.001). Physiological parameters were maintained within the normal ranges in the experimental group, and the number of non-adherent patients decreased, although the change was not statistically significant.

Conclusions

The mobile-app-based self-management program developed in this study increased the sick-role behavior, basic psychological needs, and self-efficacy of elderly hemodialysis patients, while physiological parameters were maintained within the normal range. Future studies are needed to develop management systems for high-risk hemodialysis patients and family-sharing apps to manage non-adherent patients.

[Development and Effects of Smartphone App-Based Walking Exercise Program for Taxi Drivers: Based on Bandura's Self Efficacy Theory]

PURPOSE

The purpose of this study was to examine the effects of smart-phone app-based walking exercise programs for taxi drivers on self-efficacy and outcome expectations for exercise, health-related quality of life, walking as an exercise, and physiological indexes.

METHODS

A nonequivalent control group with a pre-post-test design was used. The subjects were recruited in G metropolitan city. Subjects were assigned to the experimental (n=31) or control groups (n=30). The smart phone app-based walking exercise program consisted of educations via the app, twelve short message services, and one individual telephone counseling session, which was spread over 12 weeks.

RESULTS

Self-efficacy, outcome expectations, and health-related quality of life had significantly higher pre-post test differences in scores in the experimental group. Additionally, blood pressure, body mass index, and waist circumference had significantly decreased pre-post-test difference levels in the experimental group. Walking as an exercise (which consisted of days walked, number of steps walked, and amount of time walked) had significantly increased in the experimental group after 7~12 weeks in the period following the intervention program rather than 1~6 weeks after the program.

CONCLUSION

The smart phone app-based walking exercise program based on the self-efficacy theory demonstrates a significant effect on improving self-efficacy, outcome expectations physical activities, and health-related quality of life for taxi drivers. Therefore, it is recommended to actively use the program as a tool to promote self-efficacy, physical activities, and health behaviors in taxi drivers.

Doctor Consultation through Mobile Applications in India: An Overview, Challenges and the Way Forward

Objectives

To layout mHealth (mobile health) applications operating in India with the facility of either online doctor consultation or offline doctor appointment booking.

Methods

A cross-sectional, observational and web-based study was conducted. We searched the Google Play Store with the search strategy “health apps in India”. In the results, 250 applications (apps) appeared. Out of 250 apps, finally, 22 apps were found to be providing online doctor consultation and/or doctor appointment booking-related services.

Results

Among the selected mHealth apps operating in India and providing doctor consultation-related services online/offline, Practo, mfine, DocsApp, 1mg, Netmeds, Lybrate, MediBuddy, and Medlife were found to be the eight most popular ones with over a million downloads and on average four-plus user rating out of five. Practo, mfine, and Lybrate offer doctor consultation through chat, audio, and video calling. Netmeds and DocsApp offer doctor consultation through both chat and audio call. 1mg offers free chat consultation, while MediBuddy and Medlife offer audio call consultation only. Considering booking doctor appointments for offline consultation, Practo, mfine, 1mg, and Lybrate only offer this facility among the eight most popular selected mHealth apps.

Conclusions

mHealth apps providing doctor consultation are gaining popularity in India, and they have enormous potential in the country. The government should make enabling policies to facilitate and popularise mHealth apps.

Immediate Effects and Acceptability of an Application-Based Stretching Exercise Incorporating Deep Slow Breathing for Neck Pain Self-management

Objectives

This study evaluated the immediate effects and acceptability of a smartphone application named NeckProtector to promote neck pain self-management through stretching incorporating deep slow breathing, among smartphone users with neck pain.

Methods

One-hundred participants were recruited in the study. Participants were divided into two groups by block randomized allocation. The researchers gave the NeckProtector application to all participants for acceptability testing by navigation of the application for 20–30 minutes. Next, the treatment group (n = 50) conducted the exercise program via smartphone application for 15–20 minutes, while the control group (n = 50) rested for 20 minutes. Evaluations were performed at baseline and after intervention for pain intensity, muscle tension, pressure pain threshold (PPT), and cervical range of motion (CROM). Quantitative and qualitative feedback was then obtained by an acceptability survey and open-ended questionnaires.

Results

The immediate effects showed statistically significant improvements in pain intensity, muscle tension, PPT, and CROM in the treatment group in comparison to the control group. Participants reported a high level of acceptability through ratings on a Likert scale. The qualitative questionnaires received positive responses that the application was easy to use and the exercise program was useful to cope with neck pain.

Conclusions

NeckProtector can be an alternative treatment for neck pain self-management via smartphone application among smartphone users with neck pain. Further studies should examine the long-term effectiveness (Clinical trials registry: TCTR20160523001).

The role of smartphone applications in clinical practice: a review

OBJECTIVE

The number of medical mobile phone applications continues to grow. Although otorhinolaryngology-specific applications represent a small proportion, there are exciting innovations emerging for the specialty. This article will assess the number of applications available and review how they may be used in clinical practice.

METHOD

The application stores of the two most popular mobile phone platforms, Apple and android, were searched using multiple search terms.

RESULTS

A total of 107 ENT applications were identified and categorised according to intended use. Eight applications were reviewed in more detail and assessed on whether a doctor or allied health professional was involved in their design and if they were evidence-based.

CONCLUSION

There are a number of ENT-specific smartphone applications currently available. As the technology progresses, their scope has extended beyond being purely for reference. Nevertheless, it remains difficult to assess the validity and security of these applications.

Factors Associated with Daily Completion Rates in a Smartphone-Based Ecological Momentary Assessment Study

Objectives

Ecological momentary assessment (EMA) methods are known to have validity for capturing momentary changes in variables over time. However, data quality relies on the completion rates, which are influenced by both participants' characteristics and study designs. This study applied an EMA method using a mobile application to assess momentary moods and stress levels in patients with Moyamoya disease to examine variables associated with EMA completion rates.

Methods

Adults with Moyamoya disease were recruited from a tertiary hospital in Seoul. Patients with cognitive impairment were excluded. The EMA survey was loaded as a mobile application onto the participants' personal smartphones. Notifications were sent at semi-random intervals four times a day for seven consecutive days. Daily completion rates were calculated as the percentage of completed responses per day; overall completion rates were calculated as the proportion of completed responses per total of the 28 scheduled measures in the study and assessed through a descriptive analysis, t-test, ANOVA, and regression analysis, with mixed modeling to identify the point at which the daily completion rate significantly decreased.

Results

A total of 98 participants responded (mean age, 41.00 ± 10.30 years; 69.4% female; 75.5% married). The overall completion rate was 70.66%, with no gender or age differences found. The daily completion rate decreased significantly after day 5 (p = 0.029).

Conclusions

Obtaining a good completion rate is essential for quality data in EMA methods. Strategic approaches to a study design should be established to encourage participants throughout a study to improve completion rates.