An analysis on self-management and treatment-related functionality and characteristics of highly rated anxiety apps

Road to serenity: Individual variations in the efficacy of unobtrusive respiratory guidance for driving stress regulation

Stress impacts driving-related cognitive functions like attention and decision-making, and may arise in automated vehicles due to non-driving tasks. Unobtrusive relaxation techniques are needed to regulate stress without distracting from driving. Tactile wearables have shown efficacy in stress regulation through respiratory guidance, but individual variations may affect their efficacy. This study assessed slow-breathing tactile guidance under different stress levels on 85 participants. Physiological, behavioral and subjective data were collected. The influence of individual variations (e.g., driving habits and behavior, personality) using logistic regression analysis was explored. Participants could follow the guidance and adjust breathing while driving, but subjective efficacy depended on individual variations linked to different efficiency in using the technique, in relation with its attentional cost. An influence of factors linked to the evaluation of context criticality was also found. The results suggest that considering individual and contextual variations is crucial in designing and using such techniques in demanding driving contexts. In this line some design recommendations and insights for further studies are provided.

Attraction and achievement as 2 attributes of gamification in healthcare: an evolutionary concept analysis

This study conducted a conceptual analysis of gamification in healthcare utilizing Rogers’ evolutionary concept analysis methodology to identify its attributes and provide a method for its applications in the healthcare field. Gamification has recently been used as a health intervention and education method, but the concept is used inconsistently and confusingly. A literature review was conducted to derive definitions, surrogate terms, antecedents, influencing factors, attributes (characteristics with dimensions and features), related concepts, consequences, implications, and hypotheses from various academic fields. A total of 56 journal articles in English and Korean, published between August 2 and August 7, 2023, were extracted from databases such as PubMed Central, the Institute of Electrical and Electronics Engineers, the Association for Computing Machinery Digital Library, the Research Information Sharing Service, and the Korean Studies Information Service System, using the keywords “gamification” and “healthcare.” These articles were then analyzed. Gamification in healthcare is defined as the application of game elements in health-related contexts to improve health outcomes. The attributes of this concept were categorized into 2 main areas: attraction and achievement. These categories encompass various strategies for synchronization, enjoyable engagement, visual rewards, and goal-reinforcing frames. Through a multidisciplinary analysis of the concept’s attributes and influencing factors, this paper provides practical strategies for implementing gamification in health interventions. When developing a gamification strategy, healthcare providers can reference this analysis to ensure the game elements are used both appropriately and effectively.

The Relationship between Gamified Physical Exercise and Mental Health in Adolescence: An Example of Open Innovation in Gamified Learning

Interest in gamified physical activity has been driven by its potential to benefit student mental health. Integrating gamified practices for mental health improvement represents a significant innovation within multidisciplinary approaches to enhancing mental well-being. This review follows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and was conducted using the Scopus and Web of Science (WOS) databases, primary sources for education-related studies. Thirteen papers were analyzed, yielding important insights into the relationship between gamified physical activity and mental health. The findings indicate that gamified physical activity positively influences adolescents' mental health and well-being. Additionally, there is a need for improved application and game design to enhance learning within school contexts. Tailoring exergames to fit specific disciplines and school-related characteristics can promote healthier mobile application usage and offer significant benefits for the mental health of young individuals. The difference between this study and previous ones is that it focuses on mobile applications for encouraging active living to improve quality of life and mental health.

A Smartphone Application for Caregivers of Children With Severe Burns: A Survey to Identify Minimum Data Set and Requirements

Recent advances in digital health and increasing access to mobile health (mHealth) tools have led to more effective self-care. This study aimed to identify the minimum data set (MDS) and the requirements of a smartphone application (app) to support caregivers of children with severe burns. The study was performed in three phases in a burn center in the north of Iran in 2022. In the first phase, a literature review was performed. In the second phase, interviews were conducted with 18 caregivers. The third phase was performed in two stages: first, an initial questionnaire was prepared in which the content validity ratio and content validity index were calculated. The final questionnaire included 71 data elements about the MDS and requirements and open-ended elements. Then, the data elements were surveyed by 25 burn experts using the Delphi technique. The minimum acceptable mean score for each item was 3.75. Out of the 71 elements in the first Delphi round, 51 were accepted. In the second Delphi round, 14 data elements were assessed. The most important elements for the MDS were a family relationship, TBSA, the primary cause of the burn, anatomical location, itch, pain, and infection. User registration, educational materials, caregiver-clinician communication, chat box, and appointment booking were the most highlighted functional requirements. Safe login was the most important element for the nonfunctional requirements. It is recommended that health managers and software designers use these functionalities in designing smartphone apps for caregivers of children with burns.

Evaluation of mobile applications focused on the care of patients with anxiety disorders: A systematic review in app stores in Brazil

OBJECTIVE

To identify and evaluate the quality of mobile apps available in Brazil focused on the care of patients with anxiety disorders.

METHODS

A comprehensive search was conducted until October 2021 on Play Store (Android) and Apple Store (iOS) in Brazil, using the terms "anxiety," "phobia," "panic attack," and "social phobia." Two independent authors identified the apps and performed data extraction and quality assessment using the Mobile App Rating Scale (MARS). Pearson's correlation was used to analyze the relationship between user star rating and the quality defined by the MARS instrument.

RESULTS

A total of 3,278 potential apps were identified, of which 71 fully met the eligibility criteria. Most apps were made available on the Play Store (91.74%), in English (69.01%), and updated in the last two years (90.14%). Approximately half of the apps (50.70%) did not inform the developer's country and most of them did not report the user star rating (70.42%). The target population was indicated as free by most apps (85.92%), with generalized anxiety disorder being the most addressed disorder (74.65%), followed by panic disorder (33.80%). The three main purposes of the apps were education (83.10%), self-assessment (38.03%), and meditation/breathing (32.39%). Only 31 apps (43.66%) had acceptable quality (above 3.0) and the average total MARS quality score of 2.93 (2.20 to 3.90), with the functionality section receiving the highest score (3.90) and the lowest scoring sections being engagement (2.16). The apps that were rated stars by users (29.58%) showed a negative Pearson correlation (ρ = -0.100), evidencing a difference in the user's evaluation and that performed using the MARS instrument.

CONCLUSION

Gaps in the quality of apps focused on the care of patients with anxiety disorders were evidenced since most were classified as having low quality through the MARS instrument. Thus, users are recommended to use these apps with caution.

Thinking Aloud or Screaming Inside: Exploratory Study of Sentiment Around Work

Background

Millions of workers experience work-related ill health every year. The loss of working days often accounts for poor well-being because of discomfort and stress caused by the workplace. The ongoing pandemic and postpandemic shift in socioeconomic and work culture can continue to contribute to adverse work-related sentiments. Critically investigating state-of-the-art technologies, this study identifies the research gaps in recognizing workers’ need for well-being support, and we aspire to understand how such evidence can be collected to transform the workforce and workplace.

Objective

Building on recent advances in sentiment analysis, this study aims to closely examine the potential of social media as a tool to assess workers’ emotions toward the workplace.

Methods

This study collected a large Twitter data set comprising both pandemic and prepandemic tweets facilitated through a human-in-the-loop approach in combination with unsupervised learning and meta-heuristic optimization algorithms. The raw data preprocessed through natural language processing techniques were assessed using a generative statistical model and a lexicon-assisted rule-based model, mapping lexical features to emotion intensities. This study also assigned human annotations and performed work-related sentiment analysis.

Results

A mixed methods approach, including topic modeling using latent Dirichlet allocation, identified the top topics from the corpus to understand how Twitter users engage with discussions on work-related sentiments. The sorted aspects were portrayed through overlapped clusters and low intertopic distances. However, further analysis comprising the Valence Aware Dictionary for Sentiment Reasoner suggested a smaller number of negative polarities among diverse subjects. By contrast, the human-annotated data set created for this study contained more negative sentiments. In this study, sentimental juxtaposition revealed through the labeled data set was supported by the n-gram analysis as well.

Conclusions

The developed data set demonstrates that work-related sentiments are projected onto social media, which offers an opportunity to better support workers. The infrastructure of the workplace, the nature of the work, the culture within the industry and the particular organization, employers, colleagues, person-specific habits, and upbringing all play a part in the health and well-being of any working adult who contributes to the productivity of the organization. Therefore, understanding the origin and influence of the complex underlying factors both qualitatively and quantitatively can inform the next generation of workplaces to drive positive change by relying on empirically grounded evidence. Therefore, this study outlines a comprehensive approach to capture deeper insights into work-related health.

A Biofeedback-Based Mobile App With Serious Games for Young Adults With Anxiety in the United Arab Emirates: Development and Usability Study

Background

Following the outbreak of COVID-19, several studies have reported that young adults encountered a rise in anxiety symptoms, which could negatively affect their quality of life. Promising evidence suggests that mobile apps with biofeedback, serious games, breathing exercises, and positive messaging, among other features, are useful for anxiety self-management and treatment.

Objective

This study aimed to develop and evaluate the usability of a biofeedback-based app with serious games for young adults with anxiety in the United Arab Emirates (UAE).

Methods

This study consists of two phases: Phase I describes the design and development of the app, while Phase II presents the results of a usability evaluation by experts. To elicit the app’s requirements during Phase I, we conducted (1) a survey to investigate preferences of young adults in the UAE for mobile games for stress relief; (2) an analysis of serious games for anxiety; and (3) interviews with mental health professionals and young adults in the UAE. In Phase II, five experts tested the usability of the developed app using a set of Nielsen’s usability heuristics.

Results

A fully functional biofeedback-based app with serious games was co-designed with mental health professionals. The app included 4 games (ie, a biofeedback game, card game, arcade game, and memory game), 2 relaxation techniques (ie, a breathing exercise and yoga videos), and 2 additional features (ie, positive messaging and a mood tracking calendar). The results of Phase II showed that the developed app is efficient, simple, and easy to use. Overall, the app design scored an average of 4 out of 5.

Conclusions

The elicitation techniques used in Phase I resulted in the development of an easy-to-use app for the self-management of anxiety. Further research is required to determine the app’s usability and effectiveness in the target population.

Design and Preliminary Realization of a Screening and Early Warning Health Management System for Populations at High Risk for Depression

Depression has a high incidence in the world. Based on the concept of preventive treatment of disease of traditional Chinese medicine, timely screening and early warning of depression in populations at high risk for this condition can avoid, to a certain extent, the dysfunctions caused by depression. This work studied a method to collect information on depression, generate a database of depression features, design algorithms for screening populations at high risk for depression and creating an early warning model, develop an early warning short-message service (SMS) platform, and implement a scheme of depression screening and an early warning health management system. The implementation scheme included mobile application (app), cloud form, screening and early warning model, cloud platform, and computer software. Multiple modules jointly realized the screening, early warning, and management of the health functions of individuals at high risk for depression. At the same time, function modules such as mobile app and cloud form for collecting depression health information, early warning SMS platform, and health management software were designed, and the functions of the modules were preliminarily developed. Finally, the black-box test and white-box test were used to assess the system’s functions and ensure the reliability of the system. Through the integration of mobile app and computer software, this study preliminarily realized the screening and early warning health management of a population at high risk for depression.

Influencing Factors on College Students' Willingness to Spread Internet Public Opinion: Analysis Based on COVID-19 Data in China

Following COVID-19 outbreak, Internet public opinion has tended to proliferate. From a theoretical perspective, however, the spread law of Internet public opinion in major epidemic prevention and control may provide optimization strategies on how best to channel Internet public opinion. Specifically, this article aims at exploring key factors affecting our theoretical understanding on the spread of Internet public opinion on a major epidemic situation amongst college students. A questionnaire survey on college students was conducted via online research data collection platform located in Changsha, China, amassing three hundred and nineteen valid questionnaires. Smart PLS was applied to verify a theoretical model vis-à-vis the reliability and validity of the measuring instrument. Results show that adult attachment and social motivation have significant positive influences on the consciousness of social participation. Evidently, adult attachment, emotional orientation and risk perception also have significant positive influences on emotional motivation. Emotional motivation plays a mediating role in the relationship between affective disposition and dissemination willingness. Additionally, social motivation, consciousness of social participation and emotional motivation significantly influence one's dissemination willingness in a positive way. The consciousness of social participation plays a mediating role in the relationship between social motivation and dissemination willingness. Social motivation plays a moderating role in the relationship between risk perception and dissemination willingness. Altogether, theoretical rationalization to enhance understanding and guide the initiation and spread of Internet public opinion of major public health emergencies accurately has now been provided by this work.

Mobile Applications in Mood Disorders and Mental Health: Systematic Search in Apple App Store and Google Play Store and Review of the Literature

OBJECTIVES

The main objective of this work was to explore and characterize the current landscape of mobile applications available to treat mood disorders such as depression, bipolar disorder, and dysthymia.

METHODS

We developed a tool that makes both the Apple App Store and the Google Play Store searchable using keywords and that facilitates the extraction of basic app information of the search results. All app results were filtered using various inclusion and exclusion criteria. We characterized all resultant applications according to their technical details. Furthermore, we searched for scientific publications on each app's website and PubMed, to understand whether any of the apps were supported by any type of scientific evidence on their acceptability, validation, use, effectiveness, etc. Results: Thirty apps were identified that fit the inclusion and exclusion criteria. The literature search yielded 27 publications related to the apps. However, these did not exclusively concern mood disorders. 6 were randomized studies and the rest included a protocol, pilot-, feasibility, case-, or qualitative studies, among others. The majority of studies were conducted on relatively small scales and 9 of the 27 studies did not explicitly study the effects of mobile application use on mental wellbeing.

CONCLUSION

While there exists a wealth of mobile applications aimed at the treatment of mental health disorders, including mood disorders, this study showed that only a handful of these are backed by robust scientific evidence. This result uncovers a need for further clinically oriented and systematic validation and testing of such apps.

A Conceptual Framework to Design Connected Mental Health Solutions in the United Arab Emirates: Questionnaire Study

Background

Connected mental health (CMH) is a field presenting information and communications technology–based mental care interventions that could help overcome many mental care delivery barriers. Culture and background influence people’s attitudes, preferences, and acceptance of such solutions. Therefore, the suitability of CMH solutions to the targeted population is an important factor in their successful adoption.

Objective

The aim of this study is to develop a framework for the design and creation of CMH solutions suitable for the UAE context. The framework is based on investigating enablers and barriers of CMH adoption in the United Arab Emirates, from the mental health professional's (MHP) perspective and from related literature.

Methods

A survey of literature on relevant studies addressing the use of technology for mental care in Arab countries, and a web-based questionnaire-based survey with 17 MHPs practicing in the United Arab Emirates investigating their attitudes and views toward CMH was conducted. Results from the questionnaire and from related studies were analyzed to develop the design framework.

Results

On the basis of findings from the literature survey and analyzing MHP answers to the web-based survey, a framework for the design of CMH solutions for the UAE population was developed. The framework presents four types of recommendation categories: favorable criteria, which included blended care, anonymity, and ease of use; cultural factors including availability in multiple languages, mainly Arabic and English, in addition to religious and cultural considerations; technical considerations, including good-quality communication, availability in formats compatible with mobile phones, and providing technical support; and users’ health and data safety considerations, including users’ suitability testing, confidentiality, and ensuring MHP integrity.

Conclusions

CMH has the potential to help overcome many mental care barriers in the United Arab Emirates in particular and in the Arab world in general. CMH adoption in the United Arab Emirates has a potential for success. However, many factors should be taken into account, mainly cultural, religious, and linguistic aspects.

User experience and acceptance of patients and healthy adults testing a personalized self-management app for depression: A non-randomized mixed-methods feasibility study

Objective

Previous studies have shown positive treatment outcomes of e-mental health applications targeting depression. However, few applications provide personalized features. The aim of the present study is to ask for the user experience and acceptance of patients with depression and healthy adults, who tested the self-management app Self-administered Psycho Therapy SystemS over a period of 5 days. The results serve as a source for evidence-based recommendations for developers and clinicians.

Methods

A total of 110 participants (41 patients and 69 healthy controls) tested the app Self-administered Psycho Therapy SystemS over a period of 5 days and completed evaluation sheets developed for the purpose of this study. Quantitative measures were asked with 5-point Likert-scaled items (range: −2 to + 2) for the perceived quality of the programme and its components, its practicality (both referred to as user experience) and its acceptance. Student’s t-tests and Pearson correlations were calculated for group comparisons and associations, respectively. Open text fields were analysed by applying a qualitative structuring content analysis.

Results

The perceived quality of the total programme was rated with M = 0.96 (SD = 0.82), the practicality was M = 0.84 (SD = 0.08) and the acceptance was M = 0.25 (SD = 1.04). Patients rated perceived quality of the total programme and acceptance higher than healthy adults, while there was no difference in practicality. Acceptance was associated with increased depression scores (r = 0.33, p = .01), higher scores of perceived quality of the total programme (r = 0.48, p< .001) and of practicality (r = 0.45, p < .001). Feedback of both groups regarding usability, therapeutic content and personalization revealed a strong wish for guidance and insights into mood progress, opportunities for choice of interventions and features of customization for individualized treatment.

Conclusions

Patients with depression accepted the app Self-administered Psycho Therapy SystemS more than healthy adults and gave higher ratings in quality. User experience of all users shows a need for features of guidance, choice and personalization that clinicians and developers of future apps should pay attention to.

Unguided computer-assisted self-help interventions without human contact in patients with obsessive-compulsive disorder: a systematic review and meta-analysis (Preprint)

Background

Computer-assisted treatment may reduce therapist contact and costs and promote client participation. This meta-analysis examined the efficacy and acceptability of an unguided computer-assisted therapy in patients with obsessive-compulsive disorder (OCD) compared with a waiting list or attention placebo.

Objective

This study aimed to evaluate the effectiveness and adherence of computer-assisted self-help treatment without human contact in patients with OCD using a systematic review and meta-analysis approach.

Methods

Randomized controlled trials with participants primarily diagnosed with OCD by health professionals with clinically significant OCD symptoms as measured with validated scales were included. The interventions included self-help treatment through the internet, computers, and smartphones. We excluded interventions that used human contact. We conducted a search on PubMed, Cochrane Central Register of Controlled Trials, EMBASE, World Health Organization International Clinical Trials Registry Platform, and ClinicalTrials.gov, as well as the reference lists of the included studies. The risk of bias was evaluated using version 2 of the Cochrane risk-of-bias tool for randomized trials. We calculated the standardized mean differences for continuous outcomes and risk ratios for dichotomous outcomes. The primary outcomes were short-term improvement of OCD symptoms measured by validated scales and dropout for any reason.

Results

We included 11 randomized controlled trials with a total of 983 participants. The results indicated that unguided computer-assisted self-help therapy was significantly more effective than a waiting list or psychological placebo (standard mean difference −0.47, 95% CI −0.73 to −0.22). Unguided computer-assisted self-help therapy had more dropouts for any reason than waiting list or psychological placebo (risk ratio 1.98, 95% CI 1.21 to 3.23). However, the quality of evidence was very low because of the risk of bias and inconsistent results among the included studies. The subgroup analysis showed that exposure response and prevention and an intervention duration of more than 4 weeks strengthen the efficacy without worsening acceptability. Only a few studies have examined the interaction between participants and systems, and no study has used gamification. Most researchers only used text-based interventions, and no study has used a mobile device. The overall risk of bias of the included studies was high and the heterogeneity of results was moderate to considerable.

Conclusions

Unguided computer-assisted self-help therapy for OCD is effective compared with waiting lists or psychological placebo. An exposure response and prevention component and intervention duration of more than 4 weeks may strengthen the efficacy without worsening the acceptability of the therapy.

Trial Registration

PROSPERO (International Prospective Register of Systematic Reviews) CRD42021264644; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=264644

The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality

As the COVID-19 pandemic has largely increased the utilization of telehealth, mobile mental health technologies - such as smartphone apps, vir-tual reality, chatbots, and social media - have also gained attention. These digital health technologies offer the potential of accessible and scalable interventions that can augment traditional care. In this paper, we provide a comprehensive update on the overall field of digital psychiatry, covering three areas. First, we outline the relevance of recent technological advances to mental health research and care, by detailing how smartphones, social media, artificial intelligence and virtual reality present new opportunities for "digital phenotyping" and remote intervention. Second, we review the current evidence for the use of these new technological approaches across different mental health contexts, covering their emerging efficacy in self-management of psychological well-being and early intervention, along with more nascent research supporting their use in clinical management of long-term psychiatric conditions - including major depression; anxiety, bipolar and psychotic disorders; and eating and substance use disorders - as well as in child and adolescent mental health care. Third, we discuss the most pressing challenges and opportunities towards real-world implementation, using the Integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) framework to explain how the innovations themselves, the recipients of these innovations, and the context surrounding innovations all must be considered to facilitate their adoption and use in mental health care systems. We conclude that the new technological capabilities of smartphones, artificial intelligence, social media and virtual reality are already changing mental health care in unforeseen and exciting ways, each accompanied by an early but promising evidence base. We point out that further efforts towards strengthening implementation are needed, and detail the key issues at the patient, provider and policy levels which must now be addressed for digital health technologies to truly improve mental health research and treatment in the future.

Biofeedback-Based Connected Mental Health Interventions for Anxiety: Systematic Literature Review

Background

Connected mental health, which refers to the use of technology for mental health care and technology-based therapeutic solutions, has become an established field of research. Biofeedback is one of the approaches used in connected mental health solutions, which is mainly based on the analysis of physiological indicators for the assessment and management of the psychological state. Biofeedback is recommended by many therapists and has been used for conditions including depression, insomnia, and anxiety. Anxiety is associated with several physiological symptoms, including muscle tension and breathing issues, which makes the inclusion of biofeedback useful for anxiety detection and management.

Objective

The aim of this study was to identify interventions using biofeedback as a part of their process for anxiety management and investigate their perceived effectiveness.

Methods

A systematic literature review of publications presenting empirically evaluated biofeedback-based interventions for anxiety was conducted. The systematic literature review was based on publications retrieved from IEEE Digital Library, PubMed, ScienceDirect, and Scopus. A preliminary selection of papers was identified, examined, and filtered to include only relevant publications. Studies in the final selection were classified and analyzed to extract the modalities of use of biofeedback in the identified interventions, the types of physiological data that were collected and analyzed and the sensors used to collect them. Processes and outcomes of the empirical evaluations were also extracted.

Results

After final selection, 13 publications presenting different interventions were investigated. The interventions addressed either primarily anxiety disorders or anxiety associated with health issues such as migraine, Parkinson disease, and rheumatology. Solutions combined biofeedback with other techniques including virtual reality, music therapy, games, and relaxation practices and used different sensors including cardiovascular belts, wrist sensors, or stretch sensors to collect physiological data such as heart rate, respiration indicators, and movement information. The interventions targeted different cohorts including children, students, and patients. Overall, outcomes from the empirical evaluations yielded positive results and emphasized the effectiveness of connected mental health solutions using biofeedback for anxiety; however, certain unfavorable outcomes, such as interventions not having an effect on anxiety and patients’ preferring traditional therapy, were reported in studies addressing patients with specific physical health issues.

Conclusions

The use of biofeedback in connected mental health interventions for the treatment and management of anxiety allows better screening and understanding of both psychological and physiological patient information, as well as of the association between the two. The inclusion of biofeedback could improve the outcome of interventions and boost their effectiveness; however, when used with patients suffering from certain physical health issues, suitability investigations are needed.

Attitudes Toward Using COVID-19 mHealth Tools Among Adults With Chronic Health Conditions: Secondary Data Analysis of the COVID-19 Impact Survey

Background

Adults with chronic conditions are disproportionately burdened by COVID-19 morbidity and mortality. Although COVID-19 mobile health (mHealth) apps have emerged, research on attitudes toward using COVID-19 mHealth tools among those with chronic conditions is scarce.

Objective

This study aimed to examine attitudes toward COVID-19, identify determinants of COVID-19 mHealth tool use across demographic and health-related characteristics, and evaluate associations between chronic health conditions and attitudes toward using COVID-19 mHealth tools (eg, mHealth or web-based methods for tracking COVID-19 exposures, symptoms, and recommendations).

Methods

We used nationally representative data from the COVID-19 Impact Survey collected from April to June 2020 (n=10,760). Primary exposure was a history of chronic conditions, which were defined as self-reported diagnoses of cardiometabolic, respiratory, immune-related, and mental health conditions and overweight/obesity. Primary outcomes were attitudes toward COVID-19 mHealth tools, including the likelihood of using (1) a mobile phone app to track COVID-19 symptoms and receive recommendations; (2) a website to track COVID-19 symptoms, track location, and receive recommendations; and (3) an app using location data to track potential COVID-19 exposure. Outcome response options for COVID-19 mHealth tool use were extremely/very likely, moderately likely, or not too likely/not likely at all. Multinomial logistic regression was used to compare the likelihood of COVID-19 mHealth tool use between people with different chronic health conditions, with not too likely/not likely at all responses used as the reference category for each outcome. We evaluated the determinants of each COVID-19 mHealth intervention using Poisson regression.

Results

Of the 10,760 respondents, 21.8% of respondents were extremely/very likely to use a mobile phone app or a website to track their COVID-19 symptoms and receive recommendations. Additionally, 24.1% of respondents were extremely/very likely to use a mobile phone app to track their location and receive push notifications about whether they have been exposed to COVID-19. After adjusting for age, race/ethnicity, sex, socioeconomic status, and residence, adults with mental health conditions were the most likely to report being extremely/very or moderately likely to use each mHealth intervention compared to those without such conditions. Adults with respiratory-related chronic diseases were extremely/very (conditional odds ratio 1.16, 95% CI 1.00-1.35) and moderately likely (conditional odds ratio 1.23, 95% CI 1.04-1.45) to use a mobile phone app to track their location and receive push notifications about whether they have been exposed to COVID-19.

Conclusions

Our study demonstrates that attitudes toward using COVID-19 mHealth tools vary widely across modalities (eg, web-based method vs app) and chronic health conditions. These findings may inform the adoption of long-term engagement with COVID-19 apps, which is crucial for determining their potential in reducing disparities in COVID-19 morbidity and mortality among individuals with chronic health conditions.