Mental Health Apps in China: Analysis and Quality Assessment

Mobile mental health application use, and app feature preferences among individuals with mental disorders in Ethiopia: A cross-sectional survey

BACKGROUND

Mobile health applications have been shown to assist in the treatment of mental illnesses, yet their potential remains underutilized. As supportive care, mental health applications use may be useful tools in improving mental health literacy and treatment outcomes, but patients' use of and interest in using these apps have not been studied in low-income countries like Ethiopia. This study explores the determinants of patients' mental health app use interests and app feature preferences.

METHODS

A cross-sectional study was conducted with 419 outpatient individuals with mental health disorders at Amanuel Mental Specialized Hospital, Ethiopia, between October and November 2023, using a convenience sampling method. Patients' self-reported mental health app use, interests, attitudes, and app feature preferences were collected. A multivariate logistic regression model was used to identify the associated factors.

RESULTS

Overall prevalence of not interested, somewhat interested, interested, and extremely interested in mental health app use was 5.3 %, 16.9 %, 27.7 %, and 50.1 % respectively. The proportion of current mental health apps use was low (21.2 %). Current mental health app use is associated with living in an urban area (AOR = 6.69, CI: 3.19-14) and having a higher education level (4.12 (2.02-8.04). Furthermore, app features such as psychoeducation, symptom tracking, and self-management techniques ranked as the most preferred app features.

CONCLUSIONS

Most study participants were interested in using mental health apps, but only about one in four were using mental health apps. This suggests promise for their utility in the Ethiopian context. App developers and policymakers should consider rural residents', lower educational levels, and patient app preferences when developing these applications.

What Chinese Women Seek in Mental Health Apps: Insights from Analyzing Xiaohongshu User Posts during the COVID-19 Pandemic

Gender disparity poses a prominent obstacle to achieving effective mental health outcomes in digital healthcare. Despite women being more inclined to use mental health apps and seeking designs tailored to their specific needs, there is limited research on the factors influencing female users' engagement with these apps. The COVID-19 pandemic has further exacerbated its disproportionate impact on women's mental health. This study investigates female users' posts (n = 5538) about mental health apps during the pandemic, using data collected via a Python web crawler from Xiaohongshu, a popular female-centric social media platform in China. A mixed-methods approach used qualitative thematic analysis and quantitative descriptive statistics. Among these posts, therapeutic functionality emerged as the highest priority, followed by credibility and user experience, with specific design elements highlighted as particularly significant. These findings provide valuable insights for mental health researchers and developers, including you, aiming to create gender-tailored mobile solutions to address the mental health challenges faced by women, especially during future pandemics.

Quality assessment of mHealth apps: a scoping review

Introduction

The number of mHealth apps has increased rapidly during recent years. Literature suggests a number of problems and barriers to the adoption of mHealth apps, including issues such as validity, usability, as well as data privacy and security. Continuous quality assessment and assurance systems might help to overcome these barriers. Aim of this scoping review was to collate literature on quality assessment tools and quality assurance systems for mHealth apps, compile the components of the tools, and derive overarching quality dimensions, which are potentially relevant for the continuous quality assessment of mHealth apps.

Methods

Literature searches were performed in Medline, EMBASE and PsycInfo. Articles in English or German language were included if they contained information on development, application, or validation of generic concepts of quality assessment or quality assurance of mHealth apps. Screening and extraction were carried out by two researchers independently. Identified quality criteria and aspects were extracted and clustered into quality dimensions.

Results

A total of 70 publications met inclusion criteria. Included publications contain information on five quality assurance systems and further 24 quality assessment tools for mHealth apps. Of these 29 systems/tools, 8 were developed for the assessment of mHealth apps for specific diseases, 16 for assessing mHealth apps for all fields of health and another five are not restricted to health apps. Identified quality criteria and aspects were extracted and grouped into a total of 14 quality dimensions, namely "information and transparency", "validity and (added) value", "(medical) safety", "interoperability and compatibility", "actuality", "engagement", "data privacy and data security", "usability and design", "technology", "organizational aspects", "social aspects", "legal aspects", "equity and equality", and "cost(-effectiveness)".

Discussion

This scoping review provides a broad overview of existing quality assessment and assurance systems. Many of the tools included cover only a few dimensions and aspects and therefore do not allow for a comprehensive quality assessment or quality assurance. Our findings can contribute to the development of continuous quality assessment and assurance systems for mHealth apps.

Systematic Review Registration

https://www.researchprotocols.org/2022/7/e36974/, International Registered Report Identifier, IRRID (DERR1-10.2196/36974).

Critical review of self-diagnosis of mental health conditions using artificial intelligence

The advent of artificial intelligence (AI) has revolutionised various aspects of our lives, including mental health nursing. AI-driven tools and applications have provided a convenient and accessible means for individuals to assess their mental well-being within the confines of their homes. Nonetheless, the widespread trend of self-diagnosing mental health conditions through AI poses considerable risks. This review article examines the perils associated with relying on AI for self-diagnosis in mental health, highlighting the constraints and possible adverse outcomes that can arise from such practices. It delves into the ethical, psychological, and social implications, underscoring the vital role of mental health professionals, including psychologists, psychiatrists, and nursing specialists, in providing professional assistance and guidance. This article aims to highlight the importance of seeking professional assistance and guidance in addressing mental health concerns, especially in the era of AI-driven self-diagnosis.

Healthcare professionals' and patients' assessments of listed mobile health apps in China: a qualitative study

Background

In recent years, mobile health (mHealth) has gradually developed in China, and intelligent medicine has become an important research topic. However, there are still significant problems in mHealth applications (apps). Although healthcare professionals and patients are the main users, few studies have focused on their perceptions of the quality of mHealth apps.

Objective

This study aimed to (1) understand the respective perceptions of healthcare professionals and patients regarding mHealth apps, (2) assess what barriers exist that influence the user experience, and (3) explore how to improve the quality of mHealth apps and the development of the mHealth market in China. The study aims to promote the standardization of mHealth apps and provide effective information for the improvement and development of mHealth apps in the future.

Methods

Semistructured interviews with 9 patients and 14 healthcare professionals were conducted from January 2022 to April 2022 in the Affiliated Hospital of Xuzhou Medical University. The participants used mHealth apps for more than 3 months, including the "Good Mood" and "Peace and Safe Doctors" apps and apps developed by the hospital that were popular in China. Interview transcripts were analysed using thematic analysis.

Results

The following five themes were extracted: different concerns, hidden medical dangers, distance and insecurity, barriers for older people, and having positive perceptions of mHealth apps. Healthcare professionals prioritized simplicity in regard to mHealth apps, whereas patients rated effectiveness as the most crucial factor. The study also revealed several problems with mHealth apps, including insufficient information about physician qualifications, inaccurate medical content, nonstandard treatment processes, and unclear accountability, which led to a sense of distance and insecurity among participants. Older individuals faced additional obstacles when using mHealth apps. Despite these issues, the participants remained optimistic about the future of mHealth app development.

Conclusion

The utilization, advantages, and obstacles of mHealth applications for healthcare professionals and patients were explored through semistructured interviews. Despite the promising prospects for mHealth apps in China, numerous issues still need to be addressed. Enhancing the safety monitoring system and developing user-friendly mHealth apps for older adult patients are essential steps to bridge the gap between healthcare providers and patients.

An exploratory study on the 10-year dynamic changes of mental health policy development and media stigma reporting in China (2011-2020)

BACKGROUND

China has introduced a large number of national mental health policies over the past decade. However, few studies have touched on what changes the policies brought to the media.

AIMS

This study aimed to investigate the relationship between stigma reports, classifications of mental disorders (SMI: severe mental illness vs. CMD: common mental disorders) and sources of information (mental health professionals vs. non-mental health professionals) from 2011 to 2020 in China Daily, an established official media of China.

METHOD

This study consists of policy review and media review. The policy review reviewed the media management content in Chinese national plans, policies, and laws on mental health from 2011 to 2020. China Daily news articles reporting mental illness-related topics were included in this study as the media material. After a two-step review, the eligible news articles were coded with a structured codebook. The proportion and frequency of stigma depiction of mental disorders, classifications of mental disorders and source of information were counted by year. Chi-test was undertaken to determine the relationship between stigma reports and different classifications of mental disorders and sources of information. An exploratory analysis was conducted to explore the changes in depiction around time points of policy publications.

RESULTS

The number of anti-stigmatizing articles increased significantly from 2011 to 2020. There is a statistical difference in the proportion of stigmatizing codes between articles featuring SMI and CMD (χ2 = 44.56, p < .001) and different sources of information (χ2 = 78.49, p < .001). And the statistical difference remained over the decade.

CONCLUSION

The results of the research indicate that the media may have alleviated the problem of stigma. But the subtle stigmatization still exists, which needs joint efforts of the government and media.

Dr. Smartphone, can you support my trauma? An informatics analysis study of App Store apps for trauma- and stressor-related disorders

Background

Psychological trauma is prevalent in developed countries, with prevalence rates and treatment needs exceeding health system capacity. As telemedicine and out-of-patient care are promoted, there has been an expansion of digital apps to compliment therapeutic stages in psychological trauma. To date there are no reviews that have compared these apps and their clinical utility. This study aims to identify the availability of trauma- and stressor-related mhealth apps, assess their functionality, and review their therapeutic abilities.

Methodology

The authors conducted a systematic search using an iPhone 13 Pro in the Australian IOS App Store to extract trauma- and stressor-related apps that resulted from the search criteria. A cross-adaptation of the Mobile App Rating Scale (MARS) and the Comprehensive App Evaluation Model (CAEM) were used as a framework to produce the mTrauma App Evaluation Conceptual Model and Informatics Framework. App content descriptors were analysed based on their general characteristics, usability, therapeutic focus, clinical utility, data integration. Following an applicability in concordance with psychological trauma-informed delivery.

Results

A total of 234 apps resulting from the search strategy were screened, with 81 apps that met the inclusion criteria. The majority of apps were marketed to 4+ to 17+ years of age, categorised as 'health and fitness', with the highest target markets observed for adolescents, children, parents, clinicians, and clients. A total of 43 apps (53.1%) contained a trauma-informed specified section, and 37 (45.7%) incorporated a section useful to support trauma-related symptoms. A significant number of apps there was an absence of therapeutic utility (in 32 apps (39.5%)). Most apps were supporting post-traumatic stress disorder-informed, cognitive behavioural therapy and eye movement desensitisation and reprocessing. Provision of psychoeducation, courses, guided sessions, trainings, self-reflection/journaling, symptom management and progress tracking were highly present.

Conclusions

Trauma-informed mobile apps are available in the App Store, expanding in its target market reach and usability, with an increase of creative psychotherapies being introduced alongside conventional modalities. However, based on the app descriptors, the scarcity of evidenced-based testimonials and therapeutic applicability remains questionable for clinical validity. Although mhealth tools are marketed as trauma-related, current available apps employ a multifunctional approach to general psychological symptomatology, through to associated comorbid conditions and emphasizes on passive activity. For higher uptake on user engagement, clinical application and validity, trauma-apps require curated specification to fulfil its role as complimentary psychological treatment.

"I'm stressed!": The work effect of process innovation on mental health

Objectives

The prevalence of unmet mental healthcare needs is a common challenge faced by many developing countries. This situation may worsen if more attention is not paid to the dramatic changes in the industrial workplace because of the diffusion of new automation and robotisation in the process of production.We aim to examine whether mental health problems are associated with frontline workers' direct experience of process innovation in the firms where they operate and verify whether/which of these mechanisms are involved in this relationship.

Methods

Our data were obtained from the Foshan Workplace Employee Survey (FWES). Mental health was proxied by the subjective assessment of workers' need to receive psychological counselling or treatment. To address endogeneity concerns, this study employed an extended ordered probit model and the two-stage least squares (2SLS) method.

Results

Frontline workers employed in innovative manufacturing firms are significantly more likely than those in firms taking no such action to experience psychological difficulties and to seek psychological counselling or treatment. Firms with a higher likelihood of upgrading their production process are more capable of taking a range of measures to significantly but not sufficiently mitigate the psychological problems of their workers induced by process innovation. In workplaces with a new advanced automation environment, workers believe that they face higher job insecurity (JI) and work stress, which in turn is partially and effectively linked to the deterioration in their mental health and further increases treatment-seeking behaviours.

Conclusion

This study suggests that carrying out process innovation is associated with increased psychological distress and, hence, more needs for mental healthcare services. To narrow the treatment gap originally subject to existing obstacles, it is necessary to face the new challenges posed by automation-induced change in the workplace, which policies should be particularly attentive to.

Changes in Mobile Health Apps Usage Before and After the COVID-19 Outbreak in China: Semilongitudinal Survey

BACKGROUND

Mobile health (mHealth) apps are rapidly emerging technologies in China due to strictly controlled medical needs during the COVID-19 pandemic while continuing essential services for chronic diseases. However, there have been no large-scale, systematic efforts to evaluate relevant apps.

OBJECTIVE

We aim to provide a landscape of mHealth apps in China by describing and comparing digital health concerns before and after the COVID-19 outbreak, including mHealth app data flow and user experience, and analyze the impact of COVID-19 on mHealth apps.

METHODS

We conducted a semilongitudinal survey of 1593 mHealth apps to study the app data flow and clarify usage changes and influencing factors. We selected mHealth apps in app markets, web pages from the Baidu search engine, the 2018 top 100 hospitals with internet hospitals, and online shopping sites with apps that connect to smart devices. For user experience, we recruited residents from a community in southeastern China from October 2019 to November 2019 (before the outbreak) and from June 2020 to August 2020 (after the outbreak) comparing the attention of the population to apps. We also examined associations between app characteristics, functions, and outcomes at specific quantiles of distribution in download changes using quantile regression models.

RESULTS

Rehabilitation medical support was the top-ranked functionality, with a median 1.44 million downloads per app prepandemic and a median 2.74 million downloads per app postpandemic. Among the top 10 functions postpandemic, 4 were related to maternal and child health: pregnancy preparation (ranked second; fold change 4.13), women's health (ranked fifth; fold change 5.16), pregnancy (ranked sixth; fold change 5.78), and parenting (ranked tenth; fold change 4.03). Quantile regression models showed that rehabilitation (P₇₅, P₉₀), pregnancy preparation (P₉₀), bodybuilding (P₅₀, P₉₀), and vaccination (P₇₅) were positively associated with an increase in downloads after the outbreak. In the user experience survey, the attention given to health information (prepandemic: 249/375, 66.4%; postpandemic: 146/178, 82.0%; P=.006) steadily increased after the outbreak.

CONCLUSIONS

mHealth apps are an effective health care approach gaining in popularity among the Chinese population following the COVID-19 outbreak. This research provides direction for subsequent mHealth app development and promotion in the postepidemic era, supporting medical model reformation in China as a reference, which may provide new avenues for designing and evaluating indirect public health interventions such as health education and health promotion.

Preferences for a Mental Health Support Technology Among Chinese Employees: Mixed Methods Approach

BACKGROUND

Workplace mental health is under-studied in China, making it difficult to design effective interventions. To encourage the engagement with interventions, it is crucial to understand employees' motivation toward seeking help through technologies.

OBJECTIVE

This study aimed to understanding how Chinese employees view digital mental health support technology and how mental health support technology could be designed to boost the motivation of Chinese employees to use it.

METHODS

A mixed methods approach was used. In total, 458 Chinese employees (248/458, 54% female) in 5 industries (manufacturing, software, medical, government, and education) responded to a survey, and 14 employees and 5 managers were interviewed.

RESULTS

Government data and employee responses showed that mental health support in China is limited. In the workplace, Chinese employees experience a lower sense of autonomy satisfaction compared with competence and relatedness. Although managers and employees try to empathize with those who have mental health issues, discrimination and the stigma of mental illness are rife in Chinese workplaces. Digital technologies are perceived as a potential medium for mental health interventions; however, privacy is a major concern.

CONCLUSIONS

The results of this study demonstrated the potential of self-help digital mental health support for Chinese employees. Interdisciplinary cooperation between design engineers and mental health researchers can contribute toward understanding the issues that engage or disengage users with digital mental health interventions.

Public Trust in Artificial Intelligence Applications in Mental Health Care: Topic Modeling Analysis

Background

Mental disorders (MDs) impose heavy burdens on health care (HC) systems and affect a growing number of people worldwide. The use of mobile health (mHealth) apps empowered by artificial intelligence (AI) is increasingly being resorted to as a possible solution.

Objective

This study adopted a topic modeling (TM) approach to investigate the public trust in AI apps in mental health care (MHC) by identifying the dominant topics and themes in user reviews of the 8 most relevant mental health (MH) apps with the largest numbers of reviewers.

Methods

We searched Google Play for the top MH apps with the largest numbers of reviewers, from which we selected the most relevant apps. Subsequently, we extracted data from user reviews posted from January 1, 2020, to April 2, 2022. After cleaning the extracted data using the Python text processing tool spaCy, we ascertained the optimal number of topics, drawing on the coherence scores and used latent Dirichlet allocation (LDA) TM to generate the most salient topics and related terms. We then classified the ascertained topics into different theme categories by plotting them onto a 2D plane via multidimensional scaling using the pyLDAvis visualization tool. Finally, we analyzed these topics and themes qualitatively to better understand the status of public trust in AI apps in MHC.

Results

From the top 20 MH apps with the largest numbers of reviewers retrieved, we chose the 8 (40%) most relevant apps: (1) Wysa: Anxiety Therapy Chatbot; (2) Youper Therapy; (3) MindDoc: Your Companion; (4) TalkLife for Anxiety, Depression & Stress; (5) 7 Cups: Online Therapy for Mental Health & Anxiety; (6) BetterHelp-Therapy; (7) Sanvello; and (8) InnerHour. These apps provided 14.2% (n=559), 11.0% (n=431), 13.7% (n=538), 8.8% (n=356), 14.1% (n=554), 11.9% (n=468), 9.2% (n=362), and 16.9% (n=663) of the collected 3931 reviews, respectively. The 4 dominant topics were topic 4 (cheering people up; n=1069, 27%), topic 3 (calming people down; n=1029, 26%), topic 2 (helping figure out the inner world; n=963, 25%), and topic 1 (being an alternative or complement to a therapist; n=870, 22%). Based on topic coherence and intertopic distance, topics 3 and 4 were combined into theme 3 (dispelling negative emotions), while topics 2 and 1 remained 2 separate themes: theme 2 (helping figure out the inner world) and theme 1 (being an alternative or complement to a therapist), respectively. These themes and topics, though involving some dissenting voices, reflected an overall high status of trust in AI apps.

Conclusions

This is the first study to investigate the public trust in AI apps in MHC from the perspective of user reviews using the TM technique. The automatic text analysis and complementary manual interpretation of the collected data allowed us to discover the dominant topics hidden in a data set and categorize these topics into different themes to reveal an overall high degree of public trust. The dissenting voices from users, though only a few, can serve as indicators for health providers and app developers to jointly improve these apps, which will ultimately facilitate the treatment of prevalent MDs and alleviate the overburdened HC systems worldwide.

Education on Depression in Mental Health Apps: Systematic Assessment of Characteristics and Adherence to Evidence-Based Guidelines

BACKGROUND

Suboptimal understanding of depression and mental health disorders by the general population is an important contributor to the wide treatment gap in depression. Mental health literacy encompasses knowledge and beliefs about mental disorders and supports their recognition, management, and prevention. Besides knowledge improvement, psychoeducational interventions reduce symptoms of depression, enhance help-seeking behavior, and decrease stigma. Mental health apps often offer educational content, but the trustworthiness of the included information is unclear.

OBJECTIVE

The aim of this study is to systematically evaluate adherence to clinical guidelines on depression of the information offered by mental health apps available in major commercial app stores.

METHODS

A systematic assessment of the educational content regarding depression in the apps available in the Apple App Store and Google Play was conducted in July 2020. A systematic search for apps published or updated since January 2019 was performed using 42matters. Apps meeting the inclusion criteria were downloaded and assessed using two smartphones: an iPhone 7 (iOS version 14.0.1) and a Sony XPERIA XZs (Android version 8.0.0). The 156-question assessment checklist comprised general characteristics of apps, appraisal of 38 educational topics and their adherence to evidence-based clinical guidelines, as well as technical aspects and quality assurance. The results were tabulated and reported as a narrative review, using descriptive statistics.

RESULTS

The app search retrieved 2218 apps, of which 58 were included in the analysis (Android apps: n=29, 50%; iOS apps: n=29, 50%). Of the 58 included apps, 37 (64%) apps offered educational content within a more comprehensive depression or mental health management app. Moreover, 21% (12/58) of apps provided non-evidence-based information. Furthermore, 88% (51/58) of apps included up to 20 of the educational topics, the common ones being listing the symptoms of depression (52/58, 90%) and available treatments (48/58, 83%), particularly psychotherapy. Depression-associated stigma was mentioned by 38% (22/58) of the apps, whereas suicide risk was mentioned by 71% (41/58), generally as an item in a list of symptoms. Of the 58 included apps, 44 (76%) highlighted the importance of help seeking, 29 (50%) emphasized the importance of involving the user's support network. In addition, 52% (30/58) of apps referenced their content, and 17% (10/58) included advertisements.

CONCLUSIONS

Information in mental health and depression apps is often brief and incomplete, with 1 in 5 apps providing non-evidence-based information. Given the unmet needs and stigma associated with the disease, it is imperative that apps seize the opportunity to offer quality, evidence-based education or point the users to relevant resources. A multistakeholder consensus on a more stringent development and publication process for mental health apps is essential.

A brief review of applied psychology in China

Psychology in China has a long past, but a rather short history. Modern psychology was introduced to China in the early 20th century soon, psychology as a scientific discipline was established when the teaching, research, and academic exchanges began. Specifically, applied psychology was established until the last decade of the 20th century; however, the past 30 years have witnessed the fast growth of applied psychology in China. In this article, we briefly introduce the history of psychology in China, its establishment as a discipline and a profession, and present some applications of psychology in the domains of public mental health as well as in educational and organizational settings.

Multipurpose Mobile Apps for Mental Health in Chinese App Stores: Content Analysis and Quality Evaluation

Background

Mental disorders impose varying degrees of burden on patients and their surroundings. However, people are reluctant to take the initiative to seek mental health services because of the uneven distribution of resources and stigmatization. Thus, mobile apps are considered an effective way to eliminate these obstacles and improve mental health awareness.

Objective

This study aims to evaluate the quality, function, privacy measures, and evidence-based and professional background of multipurpose mental health apps in Chinese commercial app stores.

Methods

A systematic search was conducted on iOS and Android platforms in China to identify multipurpose mental health apps. Two independent reviewers evaluated the identified mobile apps using the Mobile App Rating Scale (MARS). Each app was downloaded, and the general characteristics, privacy and security measures, development background, and functional characteristics of each app were evaluated.

Results

A total of 40 apps were analyzed, of which 35 (87.5%) were developed by companies and 33 (82.5%) provided links to access the privacy policy; 21 (52.5%) apps did not mention the involvement of relevant professionals or the guidance of a scientific basis in the app development process. The main built-in functions of these apps include psychological education (38/40, 95%), self-assessment (34/40, 85%), and counseling (33/40, 82.5%). The overall quality average MARS score of the 40 apps was 3.54 (SD 0.39), and the total score was between 2.96 and 4.30. The total MARS score was significantly positively correlated with the scores of each subscale (r=0.62-0.88, P<.001). However, the user score of the app market was not significantly correlated with the total MARS score (r=0.17, P=.33).

Conclusions

The quality of multipurpose mental health apps in China’s main app market is generally good. However, health professionals are less involved in the development of these apps, and the privacy protection policy of the apps also needs to be described in more detail. This study provides a reference for the development of multipurpose mental health apps.

Selecting and Evaluating Mobile Health Apps for the Healthy Life Trajectories Initiative: Development of the eHealth Resource Checklist

Background

The ubiquity of smartphones and mobile devices in the general population presents an unprecedented opportunity for preventative health. Not surprisingly, the use of electronic health (eHealth) resources accessed through mobile devices in clinical trials is becoming more prevalent; the selection, screening, and collation of quality eHealth resources is necessary to clinical trials using these technologies. However, the constant creation and turnover of new eHealth resources can make this task difficult. Although syntheses of eHealth resources are becoming more common, their methodological and reporting quality require improvement so as to be more accessible to nonexperts. Further, there continues to be significant variation in quality criteria employed for assessment, with no clear method for developing the included criteria. There is currently no single existing framework that addresses all six dimensions of mobile health app quality identified in Agarwal et al’s recent scoping review (ie, basic descriptions of the design and usage of the resource; technical features and accessibility; health information quality; usability; evidence of impact; and user engagement and behavior change). In instances where highly systematic tactics are not possible (due to time constraints, cost, or lack of expertise), there may be value in adopting practical and pragmatic approaches to helping researchers and clinicians identify and disseminate e-resources.

Objective

The study aimed to create a set of guidelines (ie, a checklist) to aid the members of the Healthy Life Trajectories Initiative (HeLTI) Canada trial—a preconception randomized controlled clinical trial to prevent child obesity—to assist their efforts in searching, identifying, screening, and including selected eHealth resources for participant use in the study intervention.

Methods

A framework for searching, screening, and selecting eHealth resources was adapted from the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) checklist for systematic and scoping reviews to optimize the rigor, clarity, and transparency of the process. Details regarding searching, selecting, extracting, and assessing quality of eHealth resources are described.

Results

This study resulted in the systematic development of a checklist consisting of 12 guiding principles, organized in a chronological versus priority sequence to aid researchers in searching, screening, and assessing the quality of various eHealth resources.

Conclusions

The eHealth Resource Checklist will assist researchers in navigating the eHealth resource space by providing a mechanism to detail their process of developing inclusion criteria, identifying search location, selecting and reviewing evidence, extracting information, evaluating the quality of the evidence, and synthesizing the extracted evidence. The overarching goal of this checklist is to provide researchers or generalists new to the eHealth field with a tool that balances pragmatism with rigor and that helps standardize the process of searching and critiquing digital material—a particularly important aspect given the recent explosion of and reliance on eHealth resources. Moreover, this checklist may be useful to other researchers and practitioners developing similar health interventions.

Tools for Evaluating the Content, Efficacy, and Usability of Mobile Health Apps According to the Consensus-Based Standards for the Selection of Health Measurement Instruments: Systematic Review

Background

There are several mobile health (mHealth) apps in mobile app stores. These apps enter the business-to-customer market with limited controls. Both, apps that users use autonomously and those designed to be recommended by practitioners require an end-user validation to minimize the risk of using apps that are ineffective or harmful. Prior studies have reviewed the most relevant aspects in a tool designed for assessing mHealth app quality, and different options have been developed for this purpose. However, the psychometric properties of the mHealth quality measurement tools, that is, the validity and reliability of the tools for their purpose, also need to be studied. The Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) initiative has developed tools for selecting the most suitable measurement instrument for health outcomes, and one of the main fields of study was their psychometric properties.

Objective

This study aims to address and psychometrically analyze, following the COSMIN guideline, the quality of the tools that are used to measure the quality of mHealth apps.

Methods

From February 1, 2019, to December 31, 2019, 2 reviewers searched PubMed and Embase databases, identifying mHealth app quality measurement tools and all the validation studies associated with each of them. For inclusion, the studies had to be meant to validate a tool designed to assess mHealth apps. Studies that used these tools for the assessment of mHealth apps but did not include any psychometric validation were excluded. The measurement tools were analyzed according to the 10 psychometric properties described in the COSMIN guideline. The dimensions and items analyzed in each tool were also analyzed.

Results

The initial search showed 3372 articles. Only 10 finally met the inclusion criteria and were chosen for analysis in this review, analyzing 8 measurement tools. Of these tools, 4 validated ≥5 psychometric properties defined in the COSMIN guideline. Although some of the tools only measure the usability dimension, other tools provide information such as engagement, esthetics, or functionality. Furthermore, 2 measurement tools, Mobile App Rating Scale and mHealth Apps Usability Questionnaire, have a user version, as well as a professional version.

Conclusions

The Health Information Technology Usability Evaluation Scale and the Measurement Scales for Perceived Usefulness and Perceived Ease of Use were the most validated tools, but they were very focused on usability. The Mobile App Rating Scale showed a moderate number of validated psychometric properties, measures a significant number of quality dimensions, and has been validated in a large number of mHealth apps, and its use is widespread. It is suggested that the continuation of the validation of this tool in other psychometric properties could provide an appropriate option for evaluating the quality of mHealth apps.

Quality evaluation of stress, anxiety and depression apps for COVID-19

Background

COVID-19 has caused increased stress, anxiety and depression with increased barriers to treatment. Mobile apps offer a potential solution, but there is no information on the quality of such apps recommended for COVID-19. This study aims to evaluate the quality of stress, anxiety and depression apps recommended for COVID-19.

Methods

A search was conducted to identify relevant apps on the iOS and Android platforms. 44 apps were evaluated using the Mobile App Rating Scale (MARS), and the American Psychiatric Association's app evaluation model for data privacy and security.

Results

Overall quality scores of iOS and Android apps were 3.69 ± 0.43 and 3.66 ± 0.47. Thirty percent had good/excellent overall scores. In general, the iOS and Android versions of the apps scored best for functionality (4.21 ± 0.48, 4.12 ± 0.53), followed by aesthetics (3.84 ± 0.50, 3.78 ± 0.56), information (3.39 ± 0.54, 3.40 ± 0.60), and engagement (3.31 ± 0.81, 3.34 ± 0.84). Over half (59%) shared personal information with third parties and 14% were compliant with data protection standards.

Limitations

Only free apps available in Singapore were evaluated. Our results are time sensitive due to addition, removal, and update of apps in the app stores, thus our results should be extrapolated with caution to apps from other countries and paid apps.

Conclusion

Apps that addressed all three conditions had the highest overall quality scores. The top ranked apps (Sanvello, Woebot, Happify, Youper, Bloom) were of good quality, but majority were of acceptable quality and had room for improvement. App developers are encouraged to use our findings to improve and develop better quality apps.

Considerations of diversity, equity, and inclusion in mental health apps: A scoping review of evaluation frameworks

Mental health applications or apps are a promising approach to reduce the pervasive unmet mental health need observed among marginalized groups. However, these groups face unique challenges to engage in and benefit from these interventions, and apps that consider issues of diversity, equity, and inclusion (DEI) may be better positioned to reach them. App evaluation frameworks emerge as crucial tools for researchers, clinicians, and users to select evidence-based apps. Nevertheless, it is unclear the extent to which existing assessment tools capture DEI factors. The present scoping review identified 68 studies that employed one or more assessment tools to evaluate a mental health app, leading to 44 unique app evaluation frameworks. Results showed that most frameworks were developed after 2015, and only 58% of them considered at least one DEI criterion. Frameworks that performed exceptionally well were those that combined multiple standardized and validated measures. This lack of consideration for DEI variables may limit the ability of app-based interventions to serve marginalized communities, or even worse, create new disparities. Therefore, we provide recommendations to improve current app evaluation frameworks' cultural robustness and clinical utility, maximizing their effectiveness when working with individuals from marginalized communities.

Self-medication with Chinese Medicine Online

The internet provides the means for people to play an expanded role in managing their own health. I describe an online group of 325 students seeking to address various health issues through a collaborative "online clinic." I have coined the term DIO (Do-It-Ourselves) to emphasize the underlying collaboration in this self-care trend. As a living tradition, Chinese medicine is transforming as lay people participate in this process, and their collaborative study in a digital classroom suggests a new style of knowing.

Mobile Mental Health Apps in China: Systematic App Store Search

Background

Smartphones have become ubiquitous in China, offering a promising way to deliver mental health interventions; however, little is known about the current use and characteristics of smartphone apps for mental health.

Objective

The purpose of this study was to gain insight into mobile mental health apps available in China as of December 2018.

Methods

A systematic search was conducted to identify and evaluate the most downloaded apps from iOS and Android platforms. Apps were categorized according to their main purpose and downloaded to evaluate their content. Each app’s affiliation, cost, target users, information security, and evidence-based nature were evaluated.

Results

Of the 172 unique apps that were identified, there were 37 apps (21.5%) for psychological counseling, 50 apps (29.1%) for assessment, 12 apps (7.0%) to relieve stress, 24 apps (14.0%) for psychoeducation, and 49 (28.4%) multipurpose apps (ie, a combination of counseling and assessment). Most apps were developed for adults in the general population (166/172, 96.5%), rather than for psychiatric patients. App-based counseling was mostly provided by psychologists, and of the assessed apps, only 40% (70/172) used evidence-based scales to assess mental health problems such as anxiety or depressed mood. Guided meditation was used as the main technique in stress-relieving apps.

Conclusions

Many apps contained useful and evidence-based elements, such as good quality information, validated measurements, and useful meditation methods; however, for mobile apps to contribute significantly to mental health care in China, considerable challenges remain, including the need for more patient-focused apps that can actually take on the role of a health care provider. In addition, efficacy studies are needed.