Clinicians' Concerns About Mobile Ecological Momentary Assessment Tools Designed for Emerging Psychiatric Problems: Prospective Acceptability Assessment of the MEmind App

Emotion detection for supporting depression screening

Depression is the most prevalent mental disorder in the world. One of the most adopted tools for depression screening is the Beck Depression Inventory-II (BDI-II) questionnaire. Patients may minimize or exaggerate their answers. Thus, to further examine the patient's mood while filling in the questionnaire, we propose a mobile application that captures the BDI-II patient's responses together with their images and speech. Deep learning techniques such as Convolutional Neural Networks analyze the patient's audio and image data. The application displays the correlation between the patient's emotional scores and DBI-II scores to the clinician at the end of the questionnaire, indicating the relationship between the patient's emotional state and the depression screening score. We conducted a preliminary evaluation involving clinicians and patients to assess (i) the acceptability of proposed application for use in clinics and (ii) the patient user experience. The participants were eight clinicians who tried the tool with 21 of their patients. The results seem to confirm the acceptability of the app in clinical practice.

Analysis of mHealth research: mapping the relationship between mobile apps technology and healthcare during COVID-19 outbreak

BACKGROUND

Mobile health applications (mHealth apps) offer enormous promise for illness monitoring and treatment to improve the provided medical care and promote health and wellbeing.

OBJECTIVE

We applied bibliometric quantitative analysis and network visualization to highlight research trends and areas of particular interest. We expect by summarizing the trends in mHealth app research, our work will serve as a roadmap for future investigations.

METHODS

Relevant English publications were extracted from the Scopus database. VOSviewer (version 1.6.17) was used to build coauthorship networks of authors, countries, and the co-occurrence networks of author keywords.

RESULTS

We analyzed 550 published articles on mHealth apps from 2020 to February 1, 2021. The yearly publications increased from 130 to 390 in 2021. JMIR mHealth and uHealth (33/550, 6.0%), J. Med. Internet Res. (27/550, 4.9%), JMIR Res. Protoc. (22/550, 4.0%) were the widest journals for these publications. The United States has the largest number of publications (143/550, 26.0%), and England ranks second (96/550, 17.5%). The top three productive authors were: Giansanti D., Samuel G., Lucivero F., and Zhang L. Frequent authors' keywords have formed major 4 clusters representing the hot topics in the field: (1) artificial intelligence and telehealthcare; (2) digital contact tracing apps, privacy and security concerns; (3) mHealth apps and mental health; (4) mHealth apps in public health and health promotion.

CONCLUSIONS

mHealth apps undergo current developments, and they remain hot topics in COVID-19. These findings might be useful in determining future perspectives to improve infectious disease control and present innovative solutions for healthcare.

Acceptability of digital health interventions: embracing the complexity

Acceptability is a core concept in digital health. Available frameworks have not clearly articulated why and how researchers, practitioners and policy makers may wish to study the concept of acceptability. Here, we aim to discuss (i) the ways in which acceptability might differ from closely related concepts, including user engagement; (ii) the utility of the concept of acceptability in digital health research and practice; (iii) social and cultural norms that influence acceptability; and (iv) pragmatic means of measuring acceptability, within and beyond the research process. Our intention is not to offer solutions to these open questions but to initiate a debate within the digital health community. We conducted a narrative review of theoretical and empirical examples from the literature. First, we argue that acceptability may usefully be considered an emergent property of a complex, adaptive system of interacting components (e.g., affective attitude, beliefs), which in turn influences (and is influenced by) user engagement. Second, acceptability is important due to its ability to predict and explain key outcomes of interest, including user engagement and intervention effectiveness. Third, precisely what people find acceptable is deeply contextualized and interlinked with prevailing social and cultural norms. Understanding and designing for such norms (e.g., through drawing on principles of user centered design) is therefore key. Finally, there is a lack of standard acceptability measures and thresholds. Star ratings coupled with free-text responses may provide a pragmatic means of capturing acceptability. Acceptability is a multifaceted concept, which may usefully be studied with a complexity science lens.

Barriers to and Facilitators of User Engagement With Digital Mental Health Interventions: Systematic Review

Background

Digital mental health interventions (DMHIs), which deliver mental health support via technologies such as mobile apps, can increase access to mental health support, and many studies have demonstrated their effectiveness in improving symptoms. However, user engagement varies, with regard to a user’s uptake and sustained interactions with these interventions.

Objective

This systematic review aims to identify common barriers and facilitators that influence user engagement with DMHIs.

Methods

A systematic search was conducted in the SCOPUS, PubMed, PsycINFO, Web of Science, and Cochrane Library databases. Empirical studies that report qualitative and/or quantitative data were included.

Results

A total of 208 articles met the inclusion criteria. The included articles used a variety of methodologies, including interviews, surveys, focus groups, workshops, field studies, and analysis of user reviews. Factors extracted for coding were related to the end user, the program or content offered by the intervention, and the technology and implementation environment. Common barriers included severe mental health issues that hampered engagement, technical issues, and a lack of personalization. Common facilitators were social connectedness facilitated by the intervention, increased insight into health, and a feeling of being in control of one’s own health.

Conclusions

Although previous research suggests that DMHIs can be useful in supporting mental health, contextual factors are important determinants of whether users actually engage with these interventions. The factors identified in this review can provide guidance when evaluating DMHIs to help explain and understand user engagement and can inform the design and development of new digital interventions.

Telemonitoring in Chronic Pain Management Using Smartphone Apps: A Randomized Controlled Trial Comparing Usual Assessment against App-Based Monitoring with and without Clinical Alarms

BACKGROUND

The usefulness of mHealth in helping to target face-to-face interventions for chronic pain more effectively remains unclear. In the present study, we aim to test whether the Pain Monitor mobile phone application (app) is well accepted by clinicians, and can help improve existent medical treatments for patients with chronic musculoskeletal pain. Regarding this last goal, we compared three treatment conditions, namely usual treatment, usual treatment with an app without alarms and usual treatment with an app with alarms. All treatments lasted one month. The three treatments were compared for all outcomes, i.e., pain severity and interference, fatigue, depressed mood, anxiety and anger.

METHODS

In this randomized controlled trial, the usual monitoring method (i.e., onsite; n = 44) was compared with daily ecological momentary assessment using the Pain Monitor app-both with (n = 43) and without alarms (n = 45). Alarms were sent to the clinicians in the presence of pre-established undesired clinical events and could be used to make treatment adjustments throughout the one-month study.

RESULTS

With the exception of anger, clinically significant changes (CSC; 30% improvement) were greater in the app + alarm condition across outcomes (e.g., 43.6% of patients experienced a CSC in depressed mood in the app + alarm condition, which occurred in less than 29% of patients in the other groups). The clinicians were willing to use the app, especially the version with alarms.

CONCLUSIONS

The use of apps may have some benefits in individual health care, especially when using alarms to tailor treatments.

Smartphone-based ecological momentary assessment (EMA) in psychiatric patients and student controls: A real-world feasibility study

BACKGROUND

Smartphone-based ecological momentary assessment (EMA) is a promising methodology for mental health research. The objective of this study is to determine the feasibility of smartphone-based active and passive EMA in psychiatric outpatients and student controls.

METHODS

Two smartphone applications -MEmind and eB²- were developed for behavioral active and passive monitoring. The applications were tested in psychiatric patients with a history of suicidal thoughts and/or behaviors (STB), psychiatric patients without a history of STB, and student controls. Main outcome was feasibility, measured as response to recruitment, retention, and EMA compliance. Secondary outcomes were patterns of smartphone usage.

RESULTS

Response rate was 87.3% in patients with a history of STB, 85.1% in patients without a history of STB, and 75.0% in student controls. 457 participants installed the MEmind app (120 patients with a history of STB and 337 controls) and 1,708 installed the eB² app (139 patients with a history of STB, 1,224 patients with no history of STB and 346 controls). For the MEmind app, participants were followed-up for a median of 49.5, resulting in 22,622 person-days. For the eB² application, participants were followed-up for a median of 48.9 days, resulting in 83,521 person-days. EMA compliance rate was 65.00% in suicidal patients and 75.21% in student controls. At the end of the follow-up, over 60% of participants remained in the study.

LIMITATIONS

Cases and controls were not matched by age and sex. Cases were patients who were receiving adequate psychopharmacological treatment and attending their appointments, which may result in an overstatement of clinical compliance.

CONCLUSIONS

Smartphone-based active and passive monitoring are feasible methods in psychiatric patients in real-world settings. The development of applications with friendly interfaces and directly useful features can help increase engagement without using incentives. The MEmind and eB² applications are promising clinical tools that could contribute to the management of mental disorders. In the near future, these applications could serve as risk monitoring devices in the clinical practice.

Theme Trends and Knowledge Structure on Mobile Health Apps: Bibliometric Analysis

Background

Due to the widespread and unprecedented popularity of mobile phones, the use of digital medicine and mobile health apps has seen significant growth. Mobile health apps have tremendous potential for monitoring and treating diseases, improving patient care, and promoting health.

Objective

This paper aims to explore research trends, coauthorship networks, and the research hot spots of mobile health app research.

Methods

Publications related to mobile health apps were retrieved and extracted from the Web of Science database with no language restrictions. Bibliographic Item Co-Occurrence Matrix Builder was employed to extract bibliographic information (publication year and journal source) and perform a descriptive analysis. We then used the VOSviewer (Leiden University) tool to construct and visualize the co-occurrence networks of researchers, research institutions, countries/regions, citations, and keywords.

Results

We retrieved 2802 research papers on mobile health apps published from 2000 to 2019. The number of annual publications increased over the past 19 years. JMIR mHealth and uHealth (323/2802, 11.53%), Journal of Medical Internet Research (106/2802, 3.78%), and JMIR Research Protocols (82/2802, 2.93%) were the most common journals for these publications. The United States (1186/2802, 42.33%), England (235/2802, 8.39%), Australia (215/2802, 7.67%), and Canada (112/2802, 4.00%) were the most productive countries of origin. The University of California San Francisco, the University of Washington, and the University of Toronto were the most productive institutions. As for the authors’ contributions, Schnall R, Kuhn E, Lopez-Coronado M, and Kim J were the most active researchers. The co-occurrence cluster analysis of the top 100 keywords forms 5 clusters: (1) the technology and system development of mobile health apps; (2) mobile health apps for mental health; (3) mobile health apps in telemedicine, chronic disease, and medication adherence management; (4) mobile health apps in health behavior and health promotion; and (5) mobile health apps in disease prevention via the internet.

Conclusions

We summarize the recent advances in mobile health app research and shed light on their research frontier, trends, and hot topics through bibliometric analysis and network visualization. These findings may provide valuable guidance on future research directions and perspectives in this rapidly developing field.