Engineering care in pandemic technogovernance: The politics of care in China and South Korea's COVID-19 tracking apps

This article critically examines South Korea and China's COVID-19 tracking apps by bridging surveillance studies with feminist technoscience's understanding of the "politics of care". Conducting critical readings of the apps and textual analysis of discursive materials, we demonstrate how the ideological, relational, and material practices of the apps strategically deployed "care" to normalize a particular form of pandemic technogovernance in these two countries. In the ideological dimension, media and state discourse utilized a combination of vilifying and nationalist rhetoric that framed one's acquiescence to surveillance as a demonstration of national belonging. Meanwhile, the apps also performed ambivalent roles in facilitating essential care services and mobilizing self-tracking activities, which contributed to the manufacturing of pseudonormality in these societies. In the end, we argue that the Chinese and South Korean governments managed to frame their aggressive surveillance infrastructure during COVID-19 as a form of paternalistic care by finessing the blurred boundaries between care and control. [ FROM AUTHOR] Copyright of New Media & Society is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Implementation of a self-help mobile mental health app in COVID-19 frontline health care workers: A quality improvement project

Aim Frontline health care workers (FHCWs) have endured a range of adverse mental health outcomes during the COVID-19 pandemic. Despite the widespread availability and ease-of-use of self-help mobile mental health apps, little is known about the feasibility of implementing such tools among COVID-19 FHCWs in real-world nursing settings. Methods This quality improvement project evaluated the feasibility of implementing the COVID Coach app among COVID-19 FHCWs in a skilled nursing facility. Results Participants endorsed high average ratings of the acceptability, appropriateness, feasibility, knowledge, perceived usefulness of the app. Discussion Implications for the broader dissemination of mobile self-help apps are discussed.

Acceptability of an mHealth App for Monitoring Perinatal and Postpartum Mental Health: Qualitative Study With Women and Providers.

BACKGROUND: Up to 15% of pregnant and postpartum women commonly experience undiagnosed and untreated mental health conditions, such as depression and anxiety, which may result in serious health complications. Mobile health (mHealth) apps related to mental health have been previously used for early diagnosis and intervention but not among pregnant and postpartum women. OBJECTIVE: This study aims to assess the acceptability of using mHealth to monitor and assess perinatal and postpartum depression and anxiety. METHODS: Focus group discussions with pregnant and postpartum women (n=20) and individual interviews with health care providers (n=8) were conducted to inform the acceptability of mHealth and determine its utility for assessing perinatal and postpartum mood symptoms. Participants were recruited via purposive sampling from obstetric clinics and the surrounding community. A semistructured interview guide was developed by an epidemiologist with qualitative research training in consultation with an obstetrician. The first author conducted all focus group discussions and provider interviews either in person or via Zoom (Zoom Video Communications, Inc) depending on the COVID-19 protocol that was in place during the study period. All interviews were audio recorded with consent; transcribed; and uploaded for coding to ATLAS.ti 8 (ATLAS.ti Scientific Software Development Gmb H), a qualitative data analysis and retrieval software. Data were analyzed using the deductive content analysis method using a set of a priori codes developed based on the interview guide. Methodological rigor and quality were ensured by adopting a systematic approach during the implementation, data collection, data analysis, and reporting of the data. RESULTS: Almost all women and providers had downloaded and used at least 1 health app. The respondents suggested offering short questions in layperson language that could be understood by women of all educational levels and offering no more than 2 to 3 assessments per day at preferred timings decided by the women themselves. They also suggested that the women themselves receive the alerts first, with other options being family members, spouses, or friends if the women themselves did not respond within 24 to 72 hours. Customization and snooze features were strongly endorsed by women and providers to improve acceptability and utility. Women mentioned competing demands on their time during the postpartum period, fatigue, privacy, and the security of mental health data as concerns. Health care professionals highlighted the long-term sustainability of app-based mood assessment and monitoring as an important challenge. CONCLUSIONS: The findings from this study show that mHealth would be acceptable to pregnant and postpartum women for monitoring mood symptoms. This could inform the development of clinically meaningful and inexpensive tools for facilitating the continuous monitoring of, the early diagnosis of, and an early intervention for mood disorders in this vulnerable population.

Contact-Tracing Apps as Boundary Objects of Pandemic Governance: The State-by-State Approach to Contain the Spread of COVID-19 in the United States

Digital contact tracing has been claimed as imperative to controlling the spread of COVID19. However, the state-by-state approach in the United States led to divergences in contact tracing. This study analyzed contact-tracing apps as "boundary objects" through which each state worked toward the governance of the pandemic without having a formal consensus. Through media coverage and walkthrough analyses of three digital contacttracing apps in Alabama, California, and New York, we closely investigated both convergences and divergences of the apps. In the process, we located the implications of Google/Apple's Bluetooth-based exposure notification system for digital contact tracing within and beyond state boundaries. Our findings suggest that the development of apps shared the notion of an ideal contact-tracing method-exposure notification-while each state was also situated in their local experiences of the pandemic as reflected in distinct app features. We further discuss the implications of techno-solutionist standardization of such digital contact-tracing apps.

Parallel CNN-ELM: A multiclass classification of chest X-ray images to identify seventeen lung diseases including COVID-19.

Numerous epidemic lung diseases such as COVID-19, tuberculosis (TB), and pneumonia have spread over the world, killing millions of people. Medical specialists have experienced challenges in correctly identifying these diseases due to their subtle differences in Chest X-ray images (CXR). To assist the medical experts, this study proposed a computer-aided lung illness identification method based on the CXR images. For the first time, 17 different forms of lung disorders were considered and the study was divided into six trials with each containing two, two, three, four, fourteen, and seventeen different forms of lung disorders. The proposed framework combined robust feature extraction capabilities of a lightweight parallel convolutional neural network (CNN) with the classification abilities of the extreme learning machine algorithm named CNN-ELM. An optimistic accuracy of 90.92% and an area under the curve (AUC) of 96.93% was achieved when 17 classes were classified side by side. It also accurately identified COVID-19 and TB with 99.37% and 99.98% accuracy, respectively, in 0.996 microseconds for a single image. Additionally, the current results also demonstrated that the framework could outperform the existing state-of-the-art (SOTA) models. On top of that, a secondary conclusion drawn from this study was that the prospective framework retained its effectiveness over a range of real-world environments, including balanced-unbalanced or large-small datasets, large multiclass or simple binary class, and high- or low-resolution images. A prototype Android App was also developed to establish the potential of the framework in real-life implementation.

A developer-oriented recommender model for the app store: A predictive network analytics approach

While thousands of new mobile applications (i.e., apps) are being added to the major app markets daily, only a small portion of them attain their financial goals and survive in these competitive marketplaces. A key to the quick growth and success of relatively less popular apps is that they should make their way to the limited list of apps recommended to users of already popular apps;however, the focus of the current literature on consumers has created a void of design principles for app developers. In this study, employing a predictive network analytics approach combined with deep learning-based natural language processing and explainable artificial intelligence techniques, we shift the focus from consumers and propose a developer-oriented recommender model. We employ a set of app-specific and network-driven variables to present a novel approach for predicting potential recommendation relationships among apps, which enables app developers and marketers to characterize and target appropriate consumers. We validate the proposed model using a large (>23,000), longitudinal dataset of medical apps collected from the iOS App Store at two time points. From a total of 10,234 network links (rec-ommendations) formed between the two data collection points, the proposed approach was able to correctly predict 8,780 links (i.e., 85.8 %). We perform Shapley Additive exPlanation (SHAP) analysis to identify the most important determinants of link formations and provide insights for the app developers about the factors and design principles they can incorporate into their development process to maximize the chances of success for their apps.

Recommendation system for emotional self-control of older adults post-COVID-19 in Panama

The effects of the pandemic can translate into a variety of physical and emotional reactions that are affecting the population, particularly the elderly Panamanian population, who have not been able to overcome the mainly emerging challenges of an infectious disease with health implications. physical and has also profoundly affected their well-being and mental health. To allow the Panamanian elderly population to improve emotional self-control and mental relaxation, we propose a software architecture for the development of a recommendation system integrating: artificial intelligence (AI), internet of things (IoT) and mobile applications. This research will contribute to the elderly population in Panama having a mobile application which is beneficial as a non-pharmaceutical alternative to cope with psychological conditions caused by the Covid-19 disease. Regarding the most relevant limitations we have are the acquisition of the data set for training. As future works, we hope to have a more robust architecture to implement it in other activities related to the heath self-control of Panamanian patients. © 2022, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.

The Attitude of Mobile Apps and It Impact in Health and Life Services Through Pandemic (Covid-19) In Iraq National Survey

Through and after the quarantine period of the COVID-19 epidemic, Mobile Applications developed for different purposes and goals, such as contacts and patient tracing, digital services, monitoring and testing, epidemiological research, and quarantine compliance. The main aim of this study is to highlight the effect of mobile pandemic applications in Iraqi society and the trustworthiness of developers and distributors of apps. To this end, we explored differences in the attitudes of smartphone users toward pandemic apps and shared the data to conduct research. The method adopted to achieve the Survey in this study is an Email and telephone-based Survey of (318) participants adults over 18 years old in Iraq. We used a total of (315) for Statistical Analysis. This 9-item Survey examined the current use of epidemic applications, motivations for using them, trust in app distributors, data handling, willingness to share coded data with researchers using a pandemic app, attitudes toward app use among people, demographics, and personal characteristics. The results of this study showed that most participants stated they were using smartphones (307/315, 97.5), but only (77/307, 24.4) were using pandemic apps on their smartphones. Intriguingly, in this Survey, when participants asked for the preferable organizations for storing data and application division, trust in federal or state government, regional health office, public-appointed such as statutory health insurance, or government-funded organizations (research institutes) was much higher than in private organizations (private research institutions, clinics, health insurances, information technology companies). © University of Garmian. All Rights Reserved.

The role of mobile applications in the conservative management of stress urinary incontinence in women

Urinary incontinence, affecting over 300 million women worldwide, regardless of race and age, is considered one of the most important health issues in the 21st century. owing to the scale of the problem, the priority should be to provide therapy to as many patients as possible. Although effective conservative treatment measures for urinary incontinence are available, they may not cater for all individuals who seek help. Sometimes, a sense of embarrassment or a fear of stigmatization causes patients' reluctance to report urinary incontinence symptoms to their health care provider and to join therapy. That forces therapists to search for a new approach. in this field, the use of mHealth technologies seems very promising. They have become even more valuable during the CoVid-19 pandemic, when the interest in telemedicine, as a means of providing care while not being exposed to the risk of virus infection, further increased. The purpose of this work was a narrative review showing possibilities of employing conservative measures to manage stress urinary incontinence in women, with a particular emphasis on the use of mHealth technologies, as recent studies have shown that mobile applications seem to be an effective tool in terms of improving stress urinary incontinence symptoms, satisfaction, and adherence to therapy.Copyright © Wroclaw University of Health and Sport Sciences.

Comparing the Use of a Mobile App and a Web-Based Notification Platform for Surveillance of Adverse Events Following Influenza Immunization: Randomized Controlled Trial.

BACKGROUND: Vaccine safety surveillance is a core component of vaccine pharmacovigilance. In Canada, active, participant-centered vaccine surveillance is available for influenza vaccines and has been used for COVID-19 vaccines. OBJECTIVE: The objective of this study is to evaluate the effectiveness and feasibility of using a mobile app for reporting participant-centered seasonal influenza adverse events following immunization (AEFIs) compared to a web-based notification system. METHODS: Participants were randomized to influenza vaccine safety reporting via a mobile app or a web-based notification platform. All participants were invited to complete a user experience survey. RESULTS: Among the 2408 randomized participants, 1319 (54%) completed their safety survey 1 week after vaccination, with a higher completion rate among the web-based notification platform users (767/1196, 64%) than among mobile app users (552/1212, 45%; P<.001). Ease-of-use ratings were high for the web-based notification platform users (99% strongly agree or agree) and 88.8% of them strongly agreed or agreed that the system made reporting AEFIs easier. Web-based notification platform users supported the statement that a web-based notification-only approach would make it easier for public health professionals to detect vaccine safety signals (91.4%, agreed or strongly agreed). CONCLUSIONS: Participants in this study were significantly more likely to respond to a web-based safety survey rather than within a mobile app. These results suggest that mobile apps present an additional barrier for use compared to the web-based notification-only approach. TRIAL REGISTRATION: ClinicalTrials.gov NCT05794113; https://clinicaltrials.gov/show/NCT05794113.

Observations of positive mental health indicators in undergraduates using specialized mobile apps during the COVID-19 pandemic

This dissertation presents findings from three longitudinal studies examining indicators of positive undergraduate mental health primarily during COVID-19 pandemic conditions at a large, residential, urban university in Canada (Western University) using apps with personal sensing data collection capabilities (e.g. GPS, step counts) over March 2019-August 2021. The apps featured mental health-related questionnaires - responses were representative of psychosocial outcomes for participants. Personal sensing data were representative of participant behavior/lifestyle. Questionnaires and personal sensing data were collected at the same time;personal sensing data was also collected hourly in the background for the final two studies. Associations between psychosocial outcomes and behavior/lifestyle found via mixed linear modelling revealed indicators of positive mental health. The first study, Smart Healthy Campus 1.0, began March 2019, concluding with limited data when COVID-19 was declared a pandemic;possible associations were identified. Initial plans were to improve SHC 1.0 with an upgraded SHC 2.0 study, but the Student Pandemic Experience (SPE) study was launched first, with questionnaires more fixated on pandemic conditions. Following this, SHC 2.0 was also launched shortly after, still relevant, although using shorter generic questionnaires. SPE completed with 315 participants who were primarily female (76%) iOS users (85.3%). Data collected for 40 weeks (11/2020 - 09/2021) included 4851 questionnaire responses and 25985 sensor samples with up to 68 individual values per sample. Mixed linear models were fit relating 15 mobile device (phone or tablet) sensors (e.g. step count) to 12 mental health-related questionnaire scores. SHC 2.0 ran with 94 participants were who primarily male (76.6%) iOS users (86%). Data collected for 30 weeks (01/2021 - 08/2021) included 1722 questionnaire responses and 6518 sensor samples with up to 68 individual values per sample. Mixed linear models were fit relating 12 mobile device (phone or tablet) sensors (e.g. step count) to the SHC 2.0 questionnaires. From these studies, it was found that device sensors had statistically significant associations with the selected mental health-related questionnaires for undergraduates during a major pandemic. These findings suggest directions for mental health-related programs (e.g. apps or physical activity) and interventions during a pandemic for a comparable group and setting. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

MODELLING M-COMMERCE ADOPTION AMONG GENERATION Z IN THE PANDEMIC CONTEXT

The development of online technologies and mobile apps have transformed the ways in which consumers buy and/or sell. Recently, the coronavirus pandemic has increased the usage of e-commerce and m-commerce around the world. Therefore, this study aims to investigate what drives mobile shopping apps adoption by generation Z during the pandemic. Drawing on the Technology Acceptance Model (TAM), this quantitative research shows that fear of COVID-19 exerted a positive effect on perceived usefulness of mobile apps. Furthermore, the perceived safety of mobile apps has a positive effect on perceived usefulness and perceived ease of use. Perceived usefulness has a direct influence on the intention to use mobile apps, and both a fear of COVID-19 and perceived safety have strong indirect effects on the intention to use an app. It can be argued that the research results are relevant from both theoretical and practical perspectives taking into consideration the development of m-commerce in the context of the COVID-19 pandemic. © 2023, Bucharest University of Economic Studies. All rights reserved.

Use of a Mobile Biofeedback App to Provide Health Coaching for Stress Self-management: Pilot Quasi-Experiment.

BACKGROUND: Mental health is an increasing concern among vulnerable populations, including college students and veterans. OBJECTIVE: The purpose of this study was to determine if mobile health technology combined with health coaching can better enable a user to self-manage their mental health. METHODS: This study evaluated the mobile app "Biofeedback" that provided health coaching on stress self-management for college student veterans' mental health concerns. Twenty-four college student veterans were recruited from a large public university in Texas during the spring 2020 semester, impacted by COVID-19. Ten participants were assigned to the intervention group where they used the mobile Biofeedback app on their smartphones and smartwatches, and 14 were assigned to the control group without the app; assignment was based on mobile phone compatibility. Both groups participated in one initial lab session where they learned a deep-breathing exercise technique. The intervention group was then asked to use the mobile Biofeedback app during their daily lives and a smartwatch, and the control group was asked to perform the breathing exercises on their own. Both groups filled out Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder (GAD-7) self-assessments at 2-week intervals. At the end of the semester, both groups were given an exit interview to provide user experience and perceived benefits of health coaching via the mobile biofeedback app. RESULTS: The deep-breathing exercise in the initial lab session reduced stress in both groups. Over the course of the study, the app recorded 565 coached breathing exercises with a significant decrease (approximately 3 beats per minute) in participants' heart rate during the 6-minute time period immediately after conducting the breathing exercises (Spearman rank correlation coefficient -0.61, P<.001; S=9,816,176). There was no significant difference between the two groups for PHQ-9 and GAD-7 scores over the course of the semester. Exit interview responses indicated that participants perceived that the mobile Biofeedback app improved their health and helped them address stress challenges. All participants reported that the intervention helped them manage their stress better and expressed that health coaching via a mobile device would improve their overall health. CONCLUSIONS: Participants reported a positive perception of the app for their mental health self-management during a stressful semester. Future work should examine long-term effects of the app with a larger sample size balanced between male and female participants, randomized participant allocation, real-time detection of mental health symptoms, and additional features of the app.

Quality Dimensions of Augmented Reality-based Mobile Apps for Smart-Tourism and its Impact on Customer Satisfaction & Reuse Intention

The COVID-19 pandemic has severely affected the tourism industry, with national lockdowns aimed at curbing the spread of the virus mandating travel restrictions and prohibiting events and gatherings. The shift to online video conferencing tools, which offer limited interactivity, has spurred the need to integrate augmented reality (AR) in various contexts, such as meetings, exhibitions, museums, and travel. This quantitative study examines visitors' perspectives on AR-based apps in tourism. It investigates the influence of three kinds of quality determinants, such as information quality, system quality, and service quality, on visitors' perspectives on AR apps. Their impact on visitor satisfaction ultimately triggers visitors to reuse AR-based mobile apps. The research makes a theoretical contribution to the literature on AR and the quality dimensions of mobile apps. We expect demand for AR-based apps to rapidly increase, as people continue to follow preventive measures even after COVID-19.

A Scoping Review and a Taxonomy to Assess the Impact of Mobile Apps on Cancer Care Management.

Mobile Health (mHealth) has a great potential to enhance the self-management of cancer patients and survivors. Our study aimed to perform a scoping review to evaluate the impact and trends of mobile application-based interventions on adherence and their effects on health outcomes among the cancer population. In addition, we aimed to develop a taxonomy of mobile-app-based interventions to assist app developers and healthcare researchers in creating future mHealth cancer care solutions. Relevant articles were screened from the online databases PubMed, EMBASE, and Scopus, spanning the time period from 1 January 2016 to 31 December 2022. Of the 4135 articles initially identified, 55 were finally selected for the review. In the selected studies, breast cancer was the focus of 20 studies (36%), while mixed cancers were the subject of 23 studies (42%). The studies revealed that the usage rate of mHealth was over 80% in 41 of the 55 studies, with factors such as guided supervision, personalized suggestions, theoretical intervention foundations, and wearable technology enhancing adherence and efficacy. However, cancer progression, technical challenges, and unfamiliarity with devices were common factors that led to dropouts. We also proposed a taxonomy based on diverse theoretical foundations of mHealth interventions, delivery methods, psycho-educational programs, and social platforms. We suggest that future research should investigate, improve, and verify this taxonomy classification to enhance the design and efficacy of mHealth interventions.

The effectiveness of digital health technologies for patients with diabetes mellitus: A systematic review.

Introduction: Diabetes mellitus (DM) is a leading cause of morbidity and mortality worldwide. At the same time, digital health technologies (DHTs), which include mobile health apps (mHealth) have been rapidly gaining popularity in the self-management of chronic diseases, particularly following the COVID-19 pandemic. However, while a great variety of DM-specific mHealth apps exist on the market, the evidence supporting their clinical effectiveness is still limited. Methods: A systematic review was performed. A systematic search was conducted in a major electronic database to identify randomized controlled trials (RCTs) of mHealth interventions in DM published between June 2010 and June 2020. The studies were categorized by the type of DM and impact of DM-specific mHealth apps on the management of glycated haemoglobin (HbA1c) was analysed. Results: In total, 25 studies comprising 3,360 patients were included. The methodological quality of included trials was mixed. Overall, participants diagnosed with T1DM, T2DM and Prediabetes all demonstrated greater improvements in HbA1c as a result of using a DHT compared with those who experienced usual care. The analysis revealed an overall improvement in HbA1c compared with usual care, with a mean difference of -0.56% for T1DM, -0.90% for T2DM and -0.26% for Prediabetes. Conclusion: DM-specific mHealth apps may reduce HbA1c levels in patients with T1DM, T2DM and Prediabetes. The review highlights a need for further research on the wider clinical effectiveness of diabetes-specific mHealth specifically within T1DM and Prediabetes. These should include measures which go beyond HbA1c, capturing outcomes including short-term glycemic variability or hypoglycemic events.

Attitudes of Physicians and Individuals Toward Digital Mental Health Tools: Protocol for a Web-Based Survey Research Project.

BACKGROUND: Digital transformation is impacting health care delivery. Great market dynamism is bringing opportunities and concerns alike into public discussion. Digital health apps are a vibrant segment where regulation is emerging, with Germany paving the way with its DiGA (Digitale Gesundheitsanwendungen, in German, meaning digital health apps) program. Simultaneously, mental ill-health constitutes a global health concern, and prevalence is expected to worsen due to the COVID-19 pandemic and its containment measures. Portugal and its National Health System may be a useful testbed for digital health interventions. OBJECTIVE: The paper outlines the protocol for a research project on the attitudes of physicians and potential users toward digital mental health apps to improve access to care, patient outcomes, and reduce the burden of disease of mental ill-health. METHODS: Web surveys will be conducted to acquire data from the main stakeholders (physicians and the academic community). Data analysis will replicate the statistical analysis performed in the studies from Dahlhausen and Borghouts to derive conclusions regarding the relative acceptance and likelihood of successful implementation of digital mental health apps in Portugal. RESULTS: The findings of the proposed studies will elicit important information on how physicians and individuals perceive digital mental health app interventions to improve access to care, patient outcomes, and reduce the burden of disease of mental ill-health. Data collection ran between September 26 and November 6, 2022, for the first study and September 20 and October 20, 2022, for the second study. We obtained 160 responses to the first study's survey and 539 answers to the second study's survey. Data analysis is concluded, and both studies' results are expected to be published in 2023. CONCLUSIONS: The results of the studies projected in this research protocol will have implications for researchers and academia, industry, and policy makers concerning the adoption and implementation of digital health mental apps and associated interventions. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/41040.

Training Staff Across the Veterans Affairs Health Care System to Use Mobile Mental Health Apps: A National Quality Improvement Project.

BACKGROUND: The National Center for PTSD, within the Department of Veterans Affairs (VA), has developed a suite of free, publicly available, evidence-informed apps that can reach an increasing number of veterans and bridge gaps in care by providing resources to those who are not engaged in mental health treatment. To expand the reach of these apps, staff across VA service lines learned about these apps, their features and limitations, and how to introduce them to veterans. OBJECTIVE: This study aimed to develop, disseminate, and evaluate a training for multidisciplinary staff as part of a national quality improvement project to increase the reach of mobile mental health apps as a resource for veterans. METHODS: Sites from all of VA's 18 geographic regions enrolled in this project. At each site, a minimum of 25 VA staff members who had direct contact with veterans, including staff from the mental health service line and all other service lines, were recruited to participate. Training included a 3-hour multidisciplinary core module, and a 1-hour clinical integration module designed specifically for mental health clinicians. Owing to the COVID-19 pandemic, the trainings were adapted to a live, web-based format. Pre- and posttraining surveys assessed program reach (ie, participants enrolled per site), satisfaction, and effectiveness of the training as measured by changes in knowledge, basic skills, and behavioral intentions to use apps with veterans. RESULTS: A total of 1110 participants representing 34 disciplines at 19 VA sites completed the training. Overall, 67% (743/1109) of participants were mental health staff members. Sites averaged 58.4 participants (SD 36.49, median [IQR] 51). Most (961/1024, 93.85%) participants were satisfied with the training and reported that they (941/1018, 92.44%) would recommend it to others. App knowledge scores significantly increased from pretraining (mean 80.8% correct, SD 15.77%) to posttraining (mean 91.1% correct, SD 9.57%; P<.001). At posttraining, participants also reported greater confidence in their ability to show veterans how to download (z=-13.86; P<.001) and use VA mental health apps (z=-15.13; P<.001). There was near universal endorsement by staff for their intentions to recommend apps to veterans as well as their ability to think of at least one specific veteran to whom they could recommend an app. Staff also reported a strong motivation to encourage other VA staff to share apps with veterans. CONCLUSIONS: The training far exceeded the initial goals for staff recruitment and training for all three metrics. Overall, 33% (366/1109) of participants came from service lines outside of mental health, indicating the feasibility of introducing these mental health resources during medical appointments and in other contexts.

Persuasive Design Solutions for a Sustainable Workforce: Review of Persuasive Apps for Real-Time Capability Support for Rural Health Care Professionals.

BACKGROUND: There is a need to further investigate how persuasive design principles can change rural health professionals' behaviors to look after their own health workforce capability. Several theories are used when developing apps to persuade people to change behavior, including the Persuasive System Design Model, consisting of primary task, dialogue, system credibility, and social support categories, and Cialdini's principles of persuasion. These have not been analyzed yet in the field of health workforce capability. OBJECTIVE: This study aims to determine the persuasive design techniques used in capability building-related apps and to provide recommendations for designing a health workforce app to increase their persuasiveness. METHODS: A Python script was used to extract a total of 3060 apps from Google Play. Keywords centered around health workforce capability elements. App inclusion criteria were as follows: been updated since 2019, rated by users on average 4 and above, and more than 100,000 downloads. Next, 2 experts reviewed whether 32 persuasive strategies were used in the selected apps, and these were further analyzed by capability categories: competencies and skills, health and personal qualities, values and attitudes, and work organization. RESULTS: In all, 53 mobile apps were systematically reviewed to identify the persuasive design techniques. The most common were surface credibility (n=48, 90.6%) and liking (n=48), followed by trustworthiness (n=43, 81.1%), reminders (n=38, 71.7%), and suggestion (n=30, 56.6%). The techniques in the social support domain were the least used across the different apps analyzed for health workforce capability, whereas those in the primary task support domain were used most frequently. The recommendations reflect learnings from our analysis. These findings provided insight into mobile app design principles relevant to apps used in improving health workforce capability. CONCLUSIONS: Our review showed that there are many persuasive design techniques that can assist in building health workforce capability. Additionally, several apps are available in the market that can assist in improving health workforce capability. There is, however, a specific lack of digital, real-time support to improve health workforce capability. Social support strategies through using social support persuasive design techniques will need to be integrated more prominently into a health workforce capability app. An app to measure and monitor health workforce capability scores can be used in conjunction with direct real-world person and real-time support to discuss and identify solutions to improve health workforce capability for rural and remote health professionals who are at high risk of burnout or leaving the rural health workforce.