Mental Health Apps in Psychiatric Treatment: A Patient Perspective on Real World Technology Usage

Mobile apps to reduce depressive symptoms and alcohol use in youth: A systematic review and meta-analysis: A systematic review

Background

Among youth, symptoms of depression, anxiety, and alcohol use are associated with considerable illness and disability. Youth face many personal and health system barriers in accessing mental health care. Mobile applications (apps) offer youth potentially accessible, scalable, and anonymous therapy and other support. Recent systematic reviews on apps to reduce mental health symptoms among youth have reported uncertain effectiveness, but analyses based on the type of app-delivered therapy are limited.

Objectives

We conducted this systematic review with youth co-researchers to ensure that this review addressed the questions that were most important to them. The objective of this review is to synthesize the best available evidence on the effectiveness of mobile apps for the reduction of depressive symptoms (depression, generalized anxiety, psychological distress) and alcohol use among youth.

Search Methods

We conducted electronic searches of the following bibliographic databases for studies published between January 1, 2008, and July 1, 2022: MEDLINE (via Ovid), Embase (via Ovid), PsycINFO (via Ovid), CINAHL (via EBSCOHost), and CENTRAL (via the Cochrane Library). The search used a combination of indexed terms, free text words, and MeSH headings. We manually screened the references of relevant systematic reviews and included randomized controlled trials (RCTs) for additional eligible studies, and contacted authors for full reports of identified trial registries or protocols.

Selection Criteria

We included RCTs conducted among youth aged 15-24 years from any setting. We did not exclude populations on the basis of gender, socioeconomic status, geographic location or other personal characteristics. We included studies which assessed the effectiveness of app-delivered mental health support or therapy interventions that targeted the management of depressive disorders and/or alcohol use disorders. We excluded apps that targeted general wellness, apps which focused on prevention of psychological disorders and apps that targeted bipolar disorder, psychosis, post-traumatic stress disorder, attention-deficit hyperactivity disorder, substance use disorders (aside from alcohol), and sleep disorders. Eligible comparisons included usual care, no intervention, wait-list control, alternative or controlled mobile applications. We included studies which reported outcomes on depressive symptoms, anxiety symptoms, alcohol use and psychological distress over any follow-up period.

Data Collection and Analysis

We standardized the PICO definitions (population, intervention, comparison, and outcome) of each included study and grouped studies by the type of therapy or support offered by the app. Whenever app design and clinical homogeneity allowed, we meta-analyzed outcomes using a random-effects model. Outcome data measured using categorical scales were synthesized using odds ratios. Outcome data measured using continuous scales were synthesized as the standardized mean difference. We assessed the methodological quality of each included study using the Cochrane Risk of Bias 2.0 tool and we assessed certainty of the evidence using the GRADE approach.

Main Results

From 5280 unique citations, we included 36 RCTs published in 37 reports and conducted in 15 different countries (7984 participants). Among the 36 included trials, we assessed two with an overall low risk of bias, 8 trials with some concern regarding risk of bias, and 26 trials with a high risk of bias. Interventions varied in the type of therapy or supports offered. The most common intervention designs employed mindfulness training, cognitive behavioral therapy (CBT), or a combination of the two (mindfulness + CBT). However, other interventions also included self-monitoring, medication reminders, cognitive bias modification or positive stimulation, dialectical behavioral therapy, gamified health promotion, or social skill building. Mindfulness apps led to short term improvements in depressive symptoms when compared to a withheld control (SMD = -0.36; 95% CI [-0.63, -0.10]; p = 0.007, n = 3 RCTs, GRADE: very low certainty) and when compared to an active control (SMD = -0.27; 95% CI [-0.53, -0.01]; p = 0.04, n = 2 RCTs, GRADE: very low). Apps delivering this type of support also significantly improved symptoms of anxiety when compared to a withheld control (SMD = -0.35; 95% CI [-0.60, -0.09]; p = 0.008, n = 3 RCTs, GRADE: very low) but not when compared to an active control (SMD = -0.24; 95% CI [-0.50, 0.02]; p = 0.07, n = 2 RCTs, GRADE: very low). Mindfulness apps showed improvements in psychological stress that approached statistical significance among participants receiving the mindfulness mobile apps compared to those in the withheld control (SMD = -0.27; 95% CI [-0.56, 0.03]; p = .07, n = 4 RCTs, GRADE: very low). CBT apps also led to short-term improvements in depressive symptoms when compared to a withheld control (SMD = -0.40; 95% CI [-0.80, 0.01]; p = 0.05, n = 2 RCTs, GRADE: very low) and when compared to an active control (SMD = -0.59; 95% CI [-0.98, -0.19]; p = 0.003, n = 2 RCTs, GRADE: very low). CBT-based apps also improved symptoms of anxiety compared to a withheld control (SMD = -0.51; 95% CI [-0.94, -0.09]; p = 0.02, n = 3 RCTs, GRADE: very low) but not when compared to an active control (SMD = -0.26; 95% CI [-1.11, 0.59]; p = 0.55, n = 3 RCTs, GRADE: very low). Apps which combined mindfulness and CBT did not significantly improve symptoms of depression (SMD = -0.20; 95% CI [-0.42, 0.02]; p = 0.07, n = 2 RCTs, GRADE: very low) or anxiety (SMD = -0.21; 95% CI [-0.49, 0.07]; p = 0.14, n = 2 RCTs, GRADE: very low). However, these apps did improve psychological distress (SMD = -0.43; 95% CI [-0.74, -0.12]; p = 0.006, n = 2 RCTs, GRADE: very low). The results of trials on apps to reduce alcohol use were inconsistent. We did not identify any harms associated with the use of apps to manage mental health concerns. All effectiveness results had a very low certainty of evidence rating using the GRADE approach, meaning that apps which deliver therapy or other mental health support may reduce symptoms of depression, anxiety and psychological distress but the evidence is very uncertain.

Authors' Conclusions

We reviewed evidence from 36 trials conducted among youth. According to our meta-analyses, the evidence is very uncertain about the effect of apps on depression, anxiety, psychological distress, and alcohol use. Very few effects were interpreted to be of clinical importance. Most of the RCTs were small studies focusing on efficacy for youth at risk for depressive symptoms. Larger trials are needed to evaluate effectiveness and allow for further analysis of subgroup differences. Longer trials are also needed to better estimate the clinical importance of these apps over the long term.

Algorithmic surveillance in the era of the mental health appsphere

Digital mental health applications, also known as mHealth apps, are designed to help users manage their mental health using technology such as mobile devices and smartphones. However, there has been little critical engagement surrounding their impact on marginalized communities, and Black people in Canada. This article aims to explore how state and private actors conceptualize the digitalization of mental health access, leading to the creation and implementation of these apps. It is important to consider the links and interconnections between the platform and the app, and to be cautious and curious before adopting yet another app that claims to manage and mitigate moods and address mental health needs. We should be considering the implications of what comes with this access and apparent ease of use.

Predictors of Use and Drop Out From a Web-Based Cognitive Behavioral Therapy Program and Health Community for Depression and Anxiety in Primary Care Patients: Secondary Analysis of a Randomized Controlled Trial

BACKGROUND

A previously reported study examined the treatment of primary care patients with at least moderate severity depressive or anxiety symptoms via an evidence-based computerized cognitive behavioral therapy (CCBT) program (Beating the Blues) and an online health community (OHC) that included a moderated internet support group. The 2 treatment arms proved to be equally successful at 6-month follow-up.

OBJECTIVE

Although highly promising, e-mental health treatment programs have encountered high rates of noninitiation, poor adherence, and discontinuation. Identifying ways to counter these tendencies is critical for their success. To further explore these issues, this study identified the primary care patient characteristics that increased the chances patients would not initiate the use of an intervention, (ie, not try it even once), initiate use, and go on to discontinue or continue to use an intervention.

METHODS

The study had 3 arms: one received access to CCBT (n=301); another received CCBT plus OHC (n=302), which included a moderated internet support group; and the third received usual care (n=101). Participants in the 2 active intervention arms of the study were grouped together for analyses of CCBT use (n=603) because both arms had access to CCBT, and there were no differences in outcomes between the 2 arms. Analyses of OHC use were based on 302 participants who were randomized to that arm.

RESULTS

Several baseline patient characteristics were associated with failure to initiate the use of CCBT, including having worse physical health (measured by the Short Form Health Survey Physical Components Score, P=.01), more interference from pain (by the Patient-Reported Outcomes Measurement Information System Pain Interference score, P=.048), less formal education (P=.02), and being African American or another US minority group (P=.006). Characteristics associated with failure to initiate use of the OHC were better mental health (by the Short Form Health Survey Mental Components Score, P=.04), lower use of the internet (P=.005), and less formal education (P=.001). Those who initiated the use of the CCBT program but went on to complete less of the program had less formal education (P=.01) and lower severity of anxiety symptoms (P=.03).

CONCLUSIONS

This study found that several patient characteristics predicted whether a patient was likely to not initiate use or discontinue the use of CCBT or OHC. These findings have clear implications for actionable areas that can be targeted during initial and ongoing engagement activities designed to increase patient buy-in, as well as increase subsequent use and the resulting success of eHealth programs.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01482806; https://clinicaltrials.gov/study/NCT01482806.

Clinician and Patient Perspectives on the Use of Passive Mobile Monitoring and Self-Tracking for Patients With Serious Mental Illness: User-Centered Approach

BACKGROUND

Early intervention in mental health crises can prevent negative outcomes. A promising new direction is remote mental health monitoring using smartphone technology to passively collect data from individuals to rapidly detect the worsening of serious mental illness (SMI). This technology may benefit patients with SMI, but little is known about health IT acceptability among this population or their mental health clinicians.

OBJECTIVE

We used the Health Information Technology Acceptability Model to analyze the acceptability and usability of passive mobile monitoring and self-tracking among patients with serious mental illness and their mental health clinicians.

METHODS

Data collection took place between December 2020 and June 2021 in 1 Veterans Administration health care system. Interviews with mental health clinicians (n=16) assessed the acceptability of mobile sensing, its usefulness as a tool to improve clinical assessment and care, and recommendations for program refinements. Focus groups with patients with SMI (n=3 groups) and individual usability tests (n=8) elucidated patient attitudes about engaging in health IT and perceptions of its usefulness as a tool for self-tracking and improving mental health assessments.

RESULTS

Clinicians discussed the utility of web-based data dashboards to monitor patients with SMI health behaviors and receiving alerts about their worsening health. Potential benefits included improving clinical care, capturing behaviors patients do not self-report, watching trends, and receiving alerts. Clinicians' concerns included increased workloads tied to dashboard data review, lack of experience using health IT in clinical care, and how SMI patients' associated paranoia and financial instability would impact patient uptake. Despite concerns, all mental health clinicians stated that they would recommend it. Almost all patients with SMI were receptive to using smartphone dashboards for self-monitoring and having behavioral change alerts sent to their mental health clinicians. They found the mobile app easy to navigate and dashboards easy to find and understand. Patient concerns centered on privacy and "government tracking," and their phone's battery life and data plans. Despite concerns, most reported that they would use it.

CONCLUSIONS

Many people with SMI would like to have mobile informatics tools that can support their illness and recovery. Similar to other populations (eg, older adults, people experiencing homelessness) this population presents challenges to adoption and implementation. Health care organizations will need to provide resources to address these and support successful illness management. Clinicians are supportive of technological approaches, with adapting informatics data into their workflow as the primary challenge. Despite clear challenges, technological developments are increasingly designed to be acceptable to patients. The research development-clinical deployment gap must be addressed by health care systems, similar to computerized cognitive training. It will ensure clinicians operate at the top of their skill set and are not overwhelmed by administrative tasks, data summarization, or reviewing data that do not indicate a need for intervention.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/39010.

User types, psycho-social effects and societal trends related to the use of consumer health technologies

Objective

The term consumer health technologies we use in this paper refers to fitness and health apps, wearables and other self-tracking devices that collect health-related data. Our paper aims to bridge the gap between the growing literature base of sociological research and ethical reflection on the (non-intended) effects of consumer health technology use on the psycho-social level, such as stress, responsibilization or a loss of intuitive sense for signs of health or illness. Special consideration should be given to vulnerable individuals, as the positive and negative effects of consumer health technology use may be unequally distributed. This perspective may help to guide policymaking and the responsible development of consumer health technologies.

Methods

Using a narrative review approach, we refer to empirical and theoretical studies dealing with user types and effects related to the use of consumer health technologies. We provide an overview of consumer health technology user typologies and evidence of the unintended psycho-social effects of consumer health technology use. On this basis, we propose a user typology that may serve as a future tool for ethical reflection on negative side effects.

Results

Evidence of the potential negative side effects of consumer health technology use, as presented in the literature, is inconclusive due to the high diversity of consumer health technology users and the way they use consumer health technologies. Our proposed user typology aims to more comprehensively document the diversity of users by incorporating the way in which users identify with and use their self-tracked data, attitudes towards the new technology and social interactions via consumer health technologies, and the purpose and self-determinedness of consumer health technology use.

Conclusions

More systematic and quantitative empirical research on the effects of consumer health technology use in diverse settings and with diverse user types is necessary to inform public health policy. In addition to evidence-based certification of medical consumer health technologies, more practical and flexible ways to protect users from side effects may have to be developed and adopted, especially regarding the increasing number of non-medical consumer health technologies.

Understanding users’ perspectives on mobile apps for anxiety management

Anxiety disorders are the most common type of mental health problem. The potential of apps to improve mental health has led to an increase in the number of anxiety apps available. Even though anxiety apps hold the potential to enhance mental health care for individuals, there is relatively little knowledge concerning users’ perspectives. This mixed-methods study aims to understand the nature of user burden and engagement with mental health apps (MHapps) targeting anxiety management, in order to identify ways to improve the design of these apps. Users’ perspectives on these apps were gathered by analyzing 600 reviews from 5 apps on the app stores (Study 1), and conducting 15 interviews with app users (Study 2). The results shed light on several barriers to adoption and sustained use. Users appreciate apps that offer content variation, customizability, and good interface design, and often requested an enhanced, personalized experience to improve engagement. We propose addressing the specific app quality issues identified through human-centered design, more personalized content delivery, and by improving features for social and therapeutic support.

Did Usage of Mental Health Apps Change during COVID-19? A Comparative Study Based on an Objective Recording of Usage Data and Demographics

This paper aims to objectively compare the use of mental health apps between the pre-COVID-19 and during COVID-19 periods and to study differences amongst the users of these apps based on age and gender. The study utilizes a dataset collected through a smartphone app that objectively records the users' sessions. The dataset was analyzed to identify users of mental health apps (38 users of mental health apps pre-COVID-19 and 81 users during COVID-19) and to calculate the following usage metrics; the daily average use time, the average session time, the average number of launches, and the number of usage days. The mental health apps were classified into two categories: guidance-based and tracking-based apps. The results include the increased number of users of mental health apps during the COVID-19 period as compared to pre-COVID-19. Adults (aged 24 and above), compared to emerging adults (aged 15-24 years), were found to have a higher usage of overall mental health apps and guidance-based mental health apps. Furthermore, during the COVID-19 pandemic, males were found to be more likely to launch overall mental health apps and guidance-based mental health apps compared to females. The findings from this paper suggest that despite the increased usage of mental health apps amongst males and adults, user engagement with mental health apps remained minimal. This suggests the need for these apps to work towards improved user engagement and retention.

Promoting resilience in healthcare students through psychological interventions

Given the impact of well-known chronic stressors on health and social care students, the concept of resilience has gained importance in the field of health professional education. Many interventions have been tested that are aimed at fostering students’ resilience, but the underlying evidence has not been rigorously assessed. This was the aim of the review in this issue's Cochrane Corner. In this Round the Corner section, we discuss those findings and put them into further context.

PROTOCOL: Mobile apps to reduce depressive symptoms and alcohol use in youth: A systematic review and meta-analysis

Background

Depressive symptoms and alcohol use in youth doubled in the first year of the COVID-19 pandemic. The COVID-19 pandemic has created sustained disruption in society, schools, and universities, including increasing poverty and discrimination. Public health restrictions have caused isolation and reduced social and emotional support. Together, these factors make depressive symptoms and alcohol use in youth a global public health emergency. Mobile applications (apps) have emerged as potentially scalable intervention to reduce depressive symptoms and alcohol use in youth that could meet increased demands for mental health resources. Mobile apps may potentially reduce psychological distress with accessible technology-based mental health resources.

Objectives

This systematic review and meta-analysis aims to assess the effect of mobile apps on depressive symptoms and alcohol use in youth.

Search Methods

We will develop a systematic search strategy in collaboration with an experienced librarian. We will search a series of databases (MEDLINE, Embase, PsycINFO, CINAHL, CENTRAL) from January 2008 to July 2021.

Selection Criteria

Following the PRISMA reporting guidelines for systematic reviews, two independent reviewers will identify eligible studies: randomized controlled trials on mobile apps for the management of depressive disorders (depression and anxiety) and alcohol use in youth aged 15-24 years of age.

Data Collection and Analysis

Eligible studies will be assessed for risk of bias, and outcomes pooled, when appropriate, for meta-analysis. Heterogeneity, if present, will be examined for gender. ethnicity, and socioeconomic status contributions. A narrative synthesis will highlight similarities and differences between the included studies. We will report GRADE summary of finding tables.

User Experience, Engagement, and Popularity in Mental Health Apps: Secondary Analysis of App Analytics and Expert App Reviews

Background

User experience and engagement are critical elements of mental health apps’ abilities to support users. However, work examining the relationships among user experience, engagement, and popularity has been limited. Understanding how user experience relates to engagement with and popularity of mental health apps can demonstrate the relationship between subjective and objective measures of app use. In turn, this may inform efforts to develop more effective and appealing mental health apps and ensure that they reach wide audiences.

Objective

We aimed to examine the relationship among subjective measures of user experience, objective measures of popularity, and engagement in mental health apps.

Methods

We conducted a preregistered secondary data analysis in a sample of 56 mental health apps. To measure user experience, we used expert ratings on the Mobile App Rating Scale (MARS) and consumer ratings from the Apple App Store and Google Play. To measure engagement, we acquired estimates of monthly active users (MAU) and user retention. To measure app popularity, we used download count, total app revenue, and MAU again.

Results

MARS total score was moderately positively correlated with app-level revenue (Kendall rank [T]=0.30, P=.002), MAU (T=0.39, P<.001), and downloads (T=0.41, P<.001). However, the MARS total score and each of its subscales (Engagement, Functionality, Aesthetics, and Information) showed extremely small correlations with user retention 1, 7, and 30 days after downloading. Furthermore, the total MARS score only correlated with app store rating at T=0.12, which, at P=.20, did not meet our threshold for significance.

Conclusions

More popular mental health apps receive better ratings of user experience than less popular ones. However, user experience does not predict sustained engagement with mental health apps. Thus, mental health app developers and evaluators need to better understand user experience and engagement, as well as to define sustained engagement, what leads to it, and how to create products that achieve it. This understanding might be supported by better collaboration between industry and academic teams to advance a science of engagement.

Individualized Intervention to Support Mental Health Recovery Through Implementation of Digital Tools into Clinical Care: Feasibility Study

Myriad digital tools exist to support mental health but there are multiple barriers to using these tools in routine care. This study aimed to assess the feasibility of an intervention incorporating a support role to help the clinical team identify and use technology to promote recovery. The technology specialist intervention is 3 months in duration and comprises four stages: goal setting, researching and evaluating tools, demonstrating and selecting tools, and ongoing support. We implemented the intervention in a community mental health center and a dual diagnosis treatment program, working with eight clients and their case managers. Clients and case managers willingly engaged with the technology specialist and found the intervention beneficial. Integration and collaboration with the care team facilitated implementation of the technology specialist in these real-world settings. Clients reported that the intervention made it easy to try a digital tool. Six of the eight participants stated that they made substantial progress toward their goals. The technology specialist is a promising new role for mental health care delivery to augment traditional services and enhance individualized recovery.

Adapting and Implementing Apps for Mental Healthcare

PURPOSE OF REVIEW

To describe examples of adapting apps for use in mental healthcare and to formulate recommendations for successful adaptation in mental healthcare settings.

RECENT FINDINGS

International examples are given to explore implementation procedures to address this multitude of challenges. There are only few published examples of adapting apps for use in mental healthcare. From these examples and from results of studies in implementation science in general clinical settings, it can be concluded that the process of adapting apps for mental healthcare needs to address clinician training and information needs, user needs which include cultural adaptation and go beyond mere translation, and organizational needs for blending app use into everyday clinical mental healthcare workflows.

Apps and gaps in bipolar disorder: A systematic review on electronic monitoring for episode prediction

BACKGROUND

Long-term clinical monitoring in bipolar disorder (BD) is an important therapeutic tool. The availability of smartphones and wearables has sparked the development of automated applications to remotely monitor patients. This systematic review focus on the current state of electronic (e-) monitoring for episode prediction in BD.

METHODS

We systematically reviewed the literature on e-monitoring for episode prediction in adult BD patients. The systematic review was done according to the guidelines for reporting of systematic reviews and meta-analyses (PRISMA) and was registered in PROSPERO on April 29, 2020 (CRD42020155795). We conducted a search of Web of Science, MEDLINE, EMBASE, and PsycINFO (all 2000-2020) databases. We identified and extracted data from 17 published reports on 15 relevant studies.

RESULTS

Studies were heterogeneous and most had substantial methodological and technical limitations. Models varied widely in their performance. Published metrics were too heterogeneous to lend themselves to a meta-analysis. Four studies reported sensitivity (range: 0.21 - 0.95); and two reported specificity for prediction of mood episodes (range: 0.36 - 0.99). Two studies reported accuracy (range: 0.64 - 0.88) and four reported area under the curve (AUC; range: 0.52-0.95). Overall, models were better in predicting manic or hypomanic episodes, but their performance depended on feature type.

LIMITATIONS

Our conclusions are tempered by the lack of appropriate information impeding our ability to synthesize the available evidence.

CONCLUSIONS

Given the clinical variability in BD, predicting mood episodes remains a challenging task. Emerging e-monitoring technology for episode prediction in BD requires more development before it can be adopted clinically.

Accessibility and Digital Mental Health: Considerations for More Accessible and Equitable Mental Health Apps

Digital mental health is often touted as a solution to issues of access to mental health care. However, there has been little research done to understand the accessibility of digital mental health, especially for those with disabilities. In this piece, we define accessibility as it relates to mental health apps, describe the current state of accessibility in the digital world broadly and in mental health apps more specifically, outline why accessibility matters in mental health apps, and identify future steps to better incorporate accessibility into research and development of mental health apps.

Evaluating the Clinical Feasibility of an Artificial Intelligence-Powered, Web-Based Clinical Decision Support System for the Treatment of Depression in Adults: Longitudinal Feasibility Study

BACKGROUND

Approximately two-thirds of patients with major depressive disorder do not achieve remission during their first treatment. There has been increasing interest in the use of digital, artificial intelligence-powered clinical decision support systems (CDSSs) to assist physicians in their treatment selection and management, improving the personalization and use of best practices such as measurement-based care. Previous literature shows that for digital mental health tools to be successful, the tool must be easy for patients and physicians to use and feasible within existing clinical workflows.

OBJECTIVE

This study aims to examine the feasibility of an artificial intelligence-powered CDSS, which combines the operationalized 2016 Canadian Network for Mood and Anxiety Treatments guidelines with a neural network-based individualized treatment remission prediction.

METHODS

Owing to the COVID-19 pandemic, the study was adapted to be completed entirely remotely. A total of 7 physicians recruited outpatients diagnosed with major depressive disorder according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria. Patients completed a minimum of one visit without the CDSS (baseline) and 2 subsequent visits where the CDSS was used by the physician (visits 1 and 2). The primary outcome of interest was change in appointment length after the introduction of the CDSS as a proxy for feasibility. Feasibility and acceptability data were collected through self-report questionnaires and semistructured interviews.

RESULTS

Data were collected between January and November 2020. A total of 17 patients were enrolled in the study; of the 17 patients, 14 (82%) completed the study. There was no significant difference in appointment length between visits (introduction of the tool did not increase appointment length; F2,24=0.805; mean squared error 58.08; P=.46). In total, 92% (12/13) of patients and 71% (5/7) of physicians felt that the tool was easy to use; 62% (8/13) of patients and 71% (5/7) of physicians rated that they trusted the CDSS. Of the 13 patients, 6 (46%) felt that the patient-clinician relationship significantly or somewhat improved, whereas 7 (54%) felt that it did not change.

CONCLUSIONS

Our findings confirm that the integration of the tool does not significantly increase appointment length and suggest that the CDSS is easy to use and may have positive effects on the patient-physician relationship for some patients. The CDSS is feasible and ready for effectiveness studies.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04061642; http://clinicaltrials.gov/ct2/show/NCT04061642.

Ease of Use of the Electroconvulsive Therapy App by Its Users: Cross-Sectional Questionnaire Study

Background

Electroconvulsive therapy (ECT) is one of the oldest, most effective, and potentially life-saving noninvasive brain stimulation treatments for psychiatric illnesses such as severe depression, mania, and catatonia. The decision-making process to use ECT involves well-informed discussion between the clinician and the client. A platform, like an app, which provides this information in an easy-to-understand format may be of benefit to various stakeholders in making an informed decision. Apps developed by clinicians/hospitals taking into consideration user perspectives will filter and provide trustworthy information to the users. In this regard, the ECT app, an app which is freely available for download at the Apple Store, was developed by the Leicestershire Partnership National Health Service (NHS) Trust and Leicestershire Health Informatics Service (LHIS).

Objective

The objective of this study is to evaluate and demonstrate the accessibility of the ECT app to the chosen audiences it was created for, via a paper and electronic questionnaire.

Methods

A survey was conducted between January 2017 and March 2019. A survey questionnaire designed for the study was sent to mental health professionals, medical students, patients, carers, and members of the public via post, email, and SurveyMonkey or informed via posts shared in Psychiatry online groups and face-to-face contact. All participants who were willing to participate in the study were included.

Results

Results were collected via paper forms, email responses, and SurveyMonkey and all were inputted into SurveyMonkey to facilitate analysis. A total of 20 responses were received during the study period (January 2017 to March 2019). The participants of the survey, which included a mixed group of professionals (12/20, 60%), patients (3/20, 15%), and carers (1/20, 5%), opined that the app was easy to download (14/20, 70%) and use (9/20, 45%); contained adequate information (19/20, 95%); they felt more informed after having used the app (9/20, 45%); and they would recommend it to others (19/20, 95%). The participants of the survey also provided suggestions on the app (10/20, 50%).

Conclusions

The ECT app can be beneficial in sharing appropriate information to professionals and the public alike and help in gathering unbiased and nonjudgmental information on the current use of ECT as a treatment option.

Coached Mobile App Platform for the Treatment of Depression and Anxiety Among Primary Care Patients: A Randomized Clinical Trial

Importance

Depression and anxiety are common and disabling. Primary care is the de facto site for treating these mental health problems but is typically underresourced to meet the burden of these demands.

Objective

To evaluate the efficacy of a mobile intervention platform, IntelliCare, for addressing depression and anxiety among primary care patients.

Design, Setting, and Participants

Two-arm randomized clinical trial at internal medicine clinics at the University of Arkansas for Medical Sciences. Adult primary care patients (N = 146) who screened positive for depression on the Patient Health Questionnaire-8 (PHQ; score  ≥ 10) or anxiety on the Generalized Anxiety Disorder-7 (GAD-7; score ≥ 8) were recruited between July 17, 2018, and December 14, 2018.

Interventions

The coach-supported platform composed of a suite of apps, was delivered over 8 weeks. Wait list control participants received treatment as usual for 8 weeks, then the mobile platform.

Main Outcomes and Measures

Primary outcomes were changes in depression (PHQ-9) and anxiety (GAD-7) during the intervention period. Secondary outcomes were differences in the proportion of patients who achieved recovery (PHQ-9/GAD-7 <5 or 50% improvement from baseline), sustainment of intervention effects during 2-month follow-up, and app use during the intervention period.

Results

One hundred forty-six patients were included (119 of 146 were women [81.5%]; mean [SD] age, 42.3 [13.8] years). Of the 146 patients, 122 (83.6%) were diagnosed as having depression and 131 (89.7%) were diagnosed as having anxiety. A greater proportion of intervention vs wait list control participants achieved recovery from depression (n = 38 of 64 [59%] vs n = 18 of 58 [31%]; odds ratio, 3.25; 95% CI, 1.54-6.86) and anxiety (n = 37 of 65 [57%] vs n = 25 of 66 [38%]; odds ratio, 2.17; 95% CI, 1.08-4.36). Sustained effects were observed for depression (slope, 0.01; 95% CI, -0.09 to 0.10; P = .92) and anxiety scores (slope, 0.02; 95% CI, -0.08 to 0.12; P = .67) during follow-up. App use was high, with a median of 93 and 98 sessions among participants with depression and anxiety, respectively.

Conclusions and Relevance

In this trial, a mobile intervention app was effective for depression and anxiety among primary care patients. Findings also support designing digital mental health interventions as platforms containing simple, brief apps that can be bundled by users to meet their needs.

Trial Registration

ClinicalTrials.gov Identifier: NCT03500536.

Smartphone Apps for the Treatment of Mental Disorders: Systematic Review

BACKGROUND

Smartphone apps are an increasingly popular means for delivering psychological interventions to patients suffering from a mental disorder. In line with this popularity, there is a need to analyze and summarize the state of the art, both from a psychological and technical perspective.

OBJECTIVE

This study aimed to systematically review the literature on the use of smartphones for psychological interventions. Our systematic review has the following objectives: (1) analyze the coverage of mental disorders in research articles per year; (2) study the types of assessment in research articles per mental disorder per year; (3) map the use of advanced technical features, such as sensors, and novel software features, such as personalization and social media, per mental disorder; (4) provide an overview of smartphone apps per mental disorder; and (5) provide an overview of the key characteristics of empirical assessments with rigorous designs (ie, randomized controlled trials [RCTs]).

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for systematic reviews were followed. We performed searches in Scopus, Web of Science, American Psychological Association PsycNET, and Medical Literature Analysis and Retrieval System Online, covering a period of 6 years (2013-2018). We included papers that described the use of smartphone apps to deliver psychological interventions for known mental disorders. We formed multidisciplinary teams, comprising experts in psychology and computer science, to select and classify articles based on psychological and technical features.

RESULTS

We found 158 articles that met the inclusion criteria. We observed an increasing interest in smartphone-based interventions over time. Most research targeted disorders with high prevalence, that is, depressive (31/158,19.6%) and anxiety disorders (18/158, 11.4%). Of the total, 72.7% (115/158) of the papers focused on six mental disorders: depression, anxiety, trauma and stressor-related, substance-related and addiction, schizophrenia spectrum, and other psychotic disorders, or a combination of disorders. More than half of known mental disorders were not or very scarcely (<3%) represented. An increasing number of studies were dedicated to assessing clinical effects, but RCTs were still a minority (25/158, 15.8%). From a technical viewpoint, interventions were leveraging the improved modalities (screen and sound) and interactivity of smartphones but only sparingly leveraged their truly novel capabilities, such as sensors, alternative delivery paradigms, and analytical methods.

CONCLUSIONS

There is a need for designing interventions for the full breadth of mental disorders, rather than primarily focusing on most prevalent disorders. We further contend that an increasingly systematic focus, that is, involving RCTs, is needed to improve the robustness and trustworthiness of assessments. Regarding technical aspects, we argue that further exploration and innovative use of the novel capabilities of smartphones are needed to fully realize their potential for the treatment of mental health disorders.

Digital Opportunities for Outcomes in Recovery Services (DOORS): A Pragmatic Hands-On Group Approach Toward Increasing Digital Health and Smartphone Competencies, Autonomy, Relatedness, and Alliance for Those With Serious Mental Illness

Digital health technologies such as smartphones present the potential for increased access to care and on-demand services. However, many patients with serious mental illnesses (eg, schizophrenia) have not been offered the digital health training necessary to fully utilize these innovative approaches. To bridge this digital divide in knowledge and skills, we created a hands-on and interactive training program grounded in self-determination theory, technology use cases, and the therapeutic alliance. This article introduces the need and theoretical foundation for and the experience of running the resulting Digital Opportunities for Outcomes in Recovery Services (DOORS) group in the setting of 2 programs: a first-episode psychosis program and a clubhouse for individuals with serious mental illness. The experience of running these 2 DOORS groups resulted in 2 publicly available, free training manuals to empower others to run such groups and adapt them for local needs. Future work on DOORS will expand the curriculum to best support digital health needs and increase equity of access to and knowledge and skills related to technology use in serious mental illness.

Exploring the use of mobile information and communication technologies by people with mood disorders

Information and communication technologies (ICTs) have become increasingly integrated into how care is delivered and received. However, no research has yet explored how people with mood disorders use mobile information and communication technologies (mICTs) in their everyday lives and, more specifically, how they might use mICTs to look after themselves. An exploratory qualitative study, within secondary and specialist mental health Services, was undertaken. Data generation involved in-depth, semi-structured interviews with 26 people with mood disorders. Participants' data sets were analysed using constructivist grounded theory (CGT). The resultant theory explains how mICTs were used in daily life, and also, more specifically, how they were used to manage recovery from mood disorders. The findings reveal that people with mood disorders used their mICTs to centralize themselves within their on- and offline worlds and their importance of attachment were central in their continued use. These findings have the potential to inform and encourage the further incorporation of mICTs into the health and social care settings; spanning the therapeutic to systemic levels so that the full potential of these ubiquitous technologies can be harnessed to improve care and care delivery. Yet, without adequate resource and support, health and social care professionals' efforts will be hampered, contributing to technology redundancy and high attrition rates in the use of this type of technology.

Beyond the Impact Factor: Reflecting on Twenty Years of Leading Efforts in Research, Innovation in Publishing, and Investment in People

This viewpoint celebrates the accomplishments of the Journal of Medical Internet Research on its twentieth anniversary and reviews accomplishments around research publications, journal innovation, and supporting people.

User-centered design for technology-enabled services for eating disorders

OBJECTIVE

Technology-enabled services frequently have limited reach and suboptimal engagement when implemented in real-world settings. One reason for these implementation failures is that technology-enabled services are not designed for the users and contexts in which they will be implemented. User-centered design is an approach to designing technologies and services that is grounded in information from the stakeholders who will be using or impacted by them, and the contexts for implementation. The purpose of this article is to present user-centered design methods that can be applied to technology-enabled services for eating disorders.

METHOD

We provide an overview of the user-centered design process, which is iterative and involves stakeholders throughout. One model is presented that depicts six phases of a user-centered design process: investigate, ideate, prototype, evaluate, refine and develop, and validate.

RESULTS

We then review how user-centered design approaches can be applied to designing technology-enabled services for patients with eating disorders, and we integrate a hypothetical case example that demonstrates the application of these techniques to designing a technology-enabled service for binge eating. Most of the user-centered design techniques can be implemented relatively quickly, allowing us to rapidly learn what stakeholders want and to identify problems before devoting time and resources to developing and delivering technologies and services.

DISCUSSION

Through this work, we show how designing services that fit into the patterns and routines that stakeholders already are doing can ensure that services are relevant to stakeholders and meet their needs, potentially improving engagement and clinical impact.

RESUMEN

Los servicios habilitados tecnológicamente frecuentemente tienen un alcance limitado y un involucramiento subóptimo cuando son implementados en escenarios del mundo real. Una razón para estas fallas de implementación es que los servicios habilitados tecnológicamente no están diseñados para los usuarios y contextos en los que serán implementados. El diseño centrado en el usuario es un abordaje para diseñar tecnologías y servicios que está basado en información de las partes interesadas que estarán haciendo uso o impactados por ellos, y los contextos para implementación. El propósito de este estudio es presentar métodos de diseños centrados en el usuario que pueden ser aplicados a servicios habilitados tecnológicamente para trastornos de la conducta alimentaria. Ofrecemos una visión general del proceso de diseño centrado en el usuario, que es iterative e involucra a las partes interesadas a lo largo de todo el proceso. Hemos presentado un modelo que describe seis fases de un proceso de diseño centrado en el usuario: investigar, idear, crear prototipos, evaluar, refinar y desarrollar, y validar. Luego revisamos cómo estos abordajes de diseño centrado en el usuario pueden ser aplicados para diseñar servicios habilitados tecnológicamente para pacientes con trastornos de la conducta alimentaria, e integramos un ejemplo de caso hipotético que demuestra la aplicación de estas técnicas para diseñar un servicio habilitado tecnológicamente para comer en atracones. Muchas de las técnicas de diseño centrado en el usuario pueden ser implementadas relativamente rápido, lo que nos permite aprender rápidamente lo que las partes interesadas quieren e identificar los problemas antes de dedicarles tiempo y recursos al desarrollo y entrega de tecnologías y servicios. A través de este trabajo, mostramos cómo el diseño de servicios que se ajustan a los patrones y rutinas que las partes interesadas ya están haciendo puede garantizar que los servicios sean relevantes para los interesados y que satisfagan sus necesidades, lo que podría mejorar la participación y el impacto clínico.