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

Digital Mental Health's Unstable Dichotomy-Wellness and Health

This Viewpoint discusses the unacknowledged risks and harms and unrealized clinical benefits of digital mental wellness and health technologies and offers suggestions for ways to catalyze the next phase of these technologies by focusing on safety, evidence, and engagement.

Enhancing outpatient anxiety treatment with mobile technology: A quality improvement study

INTRODUCTION

Mobile mental health applications are a novel treatment method with unique qualities and capabilities for enhancing existing psychiatric treatments. Outpatient settings such as Mile Square Health Clinic have identified a need to leverage this new technology into their routine care.

BACKGROUND

In the U.S., over 40 million people suffer from an anxiety disorder, however, only 1 in 4 responds to pharmacological treatment. Preliminary research indicates mental health apps are acceptable, feasible, and can improve patient outcomes for those with anxiety.

METHODS

Participants from two different outpatient psychiatric clinics locations with generalized anxiety disorder were identified and recruited by participating nurse practitioners. Participants were instructed on how to download and use IntelliCare by the Project Lead. The Project Lead administered a semi-structured interview to collect qualitative data at three weeks and six weeks follow-up.

RESULTS AND CONCLUSIONS

Survey responses at three and six weeks showed relevant themes of increased journaling, increased feelings of connectedness, positive associations with gamification, and IntelliCare being most useful for a moderate to severe level of anxiety.

RECOMMENDATIONS

The results of this QI project demonstrate the clinical utility of incorporating the IntelliCare app into regular outpatient practice. IntelliCare should be used with those with moderate to severe anxiety and journaling features should follow research developments to incorporate best-practice guidelines.

The use of coaching in smartphone app-based cognitive behavioral therapy for body dysmorphic disorder

Background

Body dysmorphic disorder (BDD) is severe and undertreated. Digital mental health could be key to expanding access to evidence-based treatments, such as cognitive behavioral therapy for BDD (CBT-BDD). Coach guidance is posited to be essential for effective uptake of digital interventions. However, little is known about how different patients may use coaching, what patterns correspond to meaningful outcomes, and how to match coaching to patient needs.

Methods

Participants were 77 adults who received a 12-week guided smartphone CBT-BDD. Bachelor's-level coaches were available via asynchronous messaging. We analyzed the 400 messages sent by users to coaches during treatment. Message content was coded using the efficiency model of support (i.e., usability, engagement, fit, knowledge, and implementation). We aimed to clarify when and for what purposes patients with BDD used coaching, and if we can meaningfully classify patients by these patterns. We then assessed potential baseline predictors of coach usage, and whether distinct patterns relate to clinical outcomes.

Results

Users on average sent 5.88 messages (SD = 4.51, range 1-20) and received 9.84 (SD = 5.74, range 2-30). Regarding frequency of sending messages, latent profile analysis revealed three profiles, characterized by: (1) peak mid-treatment (16.88 %), (2) bimodal/more communication early and late in treatment (10.39 %), and (3) consistent low/no communication (72.73 %). Regarding content, four profiles emerged, characterized by mostly (1) engagement (51.95 %), (2) fit (15.58 %), (3) knowledge (15.58 %), and (4) miscellaneous/no messages (16.88 %). There was a significant relationship between frequency profile and age, such that the early/late peak group was older than the low communication group, and frequency profile and adherence, driven by the mid-treatment peak group completing more modules than the low contact group. Regarding content, the engagement and knowledge groups began treatment with more severe baseline symptoms than the fit group. Content profile was associated with dropout, suggesting higher dropout rates in the miscellaneous/no contact group and reduced rates in the engagement group. There was no relationship between profile membership and other outcomes.

Discussion

The majority of participants initiated little contact with their coach and the most common function of communications was to increase engagement. Results suggest that older individuals may prefer or require more support than younger counterparts early in treatment. Additionally, whereas individuals using coaching primarily for engagement may be at lower risk of dropping out, those who do not engage at all may be at elevated risk. Findings can support more personalized, data-driven coaching protocols and more efficient allocation of coaching resources.

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.

Feasibility and Acceptability of a Mobile App-Based TEAM-CBT (Testing Empathy Assessment Methods-Cognitive Behavioral Therapy) Intervention (Feeling Good) for Depression: Secondary Data Analysis

BACKGROUND

The Feeling Good App is an automated stand-alone digital mobile mental health tool currently undergoing beta testing with the goal of providing evidence-informed self-help lessons and exercises to help individuals reduce depressive symptoms without guidance from a mental health provider. Users work through intensive basic training (IBT) and ongoing training models that provide education regarding cognitive behavioral therapy principles from a smartphone.

OBJECTIVE

The key objective of this study was to perform a nonsponsored third-party academic assessment of an industry-generated data set; this data set focused on the safety, feasibility, and accessibility of a commercial automated digital mobile mental health app that was developed to reduce feelings associated with depression.

METHODS

The Feeling Good App development team created a waitlist cohort crossover design and measured symptoms of depression and anxiety using the Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and an app-specific measure of negative feelings called the 7 Dimension Emotion Slider (7-DES). The waitlist cohort crossover design divided the participants into 2 groups, where 48.6% (141/290) of the participants were given immediate access to the apps, while 51.4% (149/290) were placed on a 2-week waitlist before being given access to the app. Data collected by the Feeling Good App development team were deidentified and provided to the authors of this paper for analysis through a nonsponsored university data use agreement. All quantitative data were analyzed using SPSS Statistics (version 28.0; IBM Corp). Descriptive statistics were calculated for demographic variables. Feasibility and acceptability were descriptively assessed. All participants included in the quantitative data were given access to the Feeling Good App; this study did not include a control group.

RESULTS

In terms of safety, there was no statistically significant change in suicidality from preintervention to postintervention time points (t288=0.0; P>.99), and there was a statistically significant decrease in hopelessness from preintervention to postintervention time points (F289=30.16; P<.01). In terms of acceptability, 72.2% (166/230) of the users who started the initial 2-day IBT went on to complete it, while 34.8% (80/230) of the users who started IBT completed the entirety of the apps' 4-week protocol (150/230, 65.22% dropout rate over 4 weeks).

CONCLUSIONS

This study is the first reported proof-of-concept evaluation of the Feeling Good App in terms of safety, feasibility, and statistical trends within the data set. It demonstrates a feasible and novel approach to industry and academic collaboration in the process of developing a digital mental health technology translated from an existing evidence-informed treatment. The results support the prototype app as safe for a select nonclinical population. The app had acceptable levels of engagement and dropouts throughout the intervention. Those who stay engaged showed reductions in symptom severity of depression warranting further investigation of the app's efficacy.

Effectiveness of a Web-Based Cognitive Behavioral Self-Help Intervention for Binge Eating Disorder: A Randomized Clinical Trial

Importance

Binge eating disorder (BED) is one of the most frequent eating pathologies and imposes substantial emotional and physical distress, yet insufficient health care resources limit access to specialized treatment. Web-based self-help interventions emerge as a promising solution, offering more accessible care.

Objective

To examine the effectiveness of a web-based cognitive behavioral self-help intervention for individuals with BED.

Design, Setting, and Participants

This 2-arm, parallel-group randomized clinical trial conducted from January 15, 2021, to August 3, 2022, in Germany and other German-speaking countries enrolled patients aged 18 to 65 years who met the diagnostic criteria for BED (according to the Diagnostic and Statistical Manual of Mental Disorders [Fifth Edition]). Data analysis occurred between January 27 and September 4, 2023, following our statistical analysis plan.

Interventions

Participants were randomized to a web-based self-help intervention or a waiting-list control condition.

Main Outcomes and Measures

The primary outcome was a change in objective binge eating episodes from baseline to after treatment. Secondary outcomes included global eating pathology, clinical impairment, work capacity, well-being, comorbid psychopathology, self-esteem, and emotion regulation.

Results

A total of 1602 patients were screened, of whom 154 (mean [SD] age, 35.93 [10.59] years; 148 female [96.10%]) fulfilled the criteria for BED and were randomized (77 each to the intervention and control groups). The web-based intervention led to significant improvements in binge eating episodes (Cohen d, -0.79 [95% CI, -1.17 to -0.42]; P < .001), global eating psychopathology (Cohen d, -0.71 [95% CI, -1.07 to -0.35]; P < .001), weekly binge eating (Cohen d, -0.49 [95% CI, -0.74 to -0.24]; P < .001), clinical impairment (Cohen d, -0.75 [95% CI, -1.13 to -0.37]; P < .001), well-being (Cohen d, 0.38 [95% CI, 0.01 to 0.75]; P = .047), depression (Cohen d, -0.49 [95% CI, -0.86 to -0.12]; P = .01), anxiety (Cohen d, -0.37 [95% CI, -0.67 to -0.07]; P = .02), self-esteem (Cohen d, 0.36 [95% CI, 0.13 to 0.59]; P = .003), and emotion regulation (difficulties: Cohen d, -0.36 [95% CI, -0.65 to -0.07]; P = .01 and repertoire: Cohen d, 0.52 [95% CI, 0.19 to 0.84]; P = .003).

Conclusion and Relevance

In this randomized clinical trial of a web-based self-help intervention for patients with BED, the findings confirmed its effectiveness in reducing binge eating episodes and improving various mental health outcomes, highlighting a scalable solution to bridge the treatment gap for this condition.

Trial Registration

ClinicalTrials.gov Identifier: NCT04876183.

Internet-delivered transdiagnostic psychological treatments for individuals with depression, anxiety or both: a systematic review with meta-analysis of randomised controlled trials

OBJECTIVE

Depression and anxiety are major public health problems. This study evaluated the effects of internet-delivered transdiagnostic psychological treatments for individuals with depression, anxiety, or both.

DESIGN

Systematic review with meta-analysis.

DATA SOURCES

Medline (Ovid), Cochrane Library (Wiley), the Web of Science Core Collection (Clarivate), and PsycInfo (EBSCO) were searched on 24 May 2021, with an update on 6 February 2023.

ELIGIBILITY CRITERIA

Randomised controlled trials of internet-delivered transdiagnostic psychological treatments, open to both participants with primary depression and participants with primary anxiety. This review concerned all treatment frameworks, both guided and unguided formats and all age groups.

DATA EXTRACTION AND SYNTHESIS

In random-effects meta-analysis, we estimated pooled effects on depression symptoms and anxiety in terms of Hedges' g with 95% CIs. Absolute and relative heterogeneity was quantified as the τ2 and I 2.

RESULTS

We included 57 trials with 21 795 participants. Nine trials (16%) recruited exclusively from routine care, and three (5%) delivered treatment via video. For adults, large within-group reductions were seen in depression (g=0.90; 95% CI 0.81 to 0.99) and anxiety (g=0.87; 95% CI 0.78 to 0.96). Compared with rudimentary passive controls, the added effects were moderate (depression: g=0.52; 95% CI 0.42 to 0.63; anxiety: g=0.45; 95% CI 0.34 to 0.56) and larger in trials that required all participants to meet full diagnostic criteria for depression or an anxiety disorder. Compared with attention/engagement controls, the added effects were small (depression: g=0.30; 95% CI 0.07 to 0.53; anxiety: g=0.21; 95% CI 0.01 to 0.42). Heterogeneity was substantial, and the certainty of the evidence was very low. Two trials concerned adolescents and reported mixed results. One trial concerned older adults and reported promising results.

CONCLUSION

Internet-delivered transdiagnostic treatments for depression and anxiety show small-to-moderate added effects, varying by control condition. Research is needed regarding routine care, the video format, children and adolescents and older adults.

PROSPERO REGISTRATION NUMBER

CRD42021243172.

Factors Predicting Intentions of Adoption and Continued Use of Artificial Intelligence Chatbots for Mental Health: Examining the Role of UTAUT Model, Stigma, Privacy Concerns, and Artificial Intelligence Hesitancy

Background: Artificial intelligence-based chatbots (AI chatbots) can potentially improve mental health care, yet factors predicting their adoption and continued use are unclear. Methods: We conducted an online survey with a sample of U.S. adults with symptoms of depression and anxiety (N = 393) in 2021 before the release of ChatGPT. We explored factors predicting the adoption and continued use of AI chatbots, including factors of the unified theory of acceptance and use of technology model, stigma, privacy concerns, and AI hesitancy. Results: Results from the regression indicated that for nonusers, performance expectancy, price value, descriptive norm, and psychological distress are positively related to the intention of adopting AI chatbots, while AI hesitancy and effort expectancy are negatively associated with adopting AI chatbots. For those with experience in using AI chatbots for mental health, performance expectancy, price value, descriptive norm, and injunctive norm are positively related to the intention of continuing to use AI chatbots. Conclusions: Understanding the adoption and continued use of AI chatbots among adults with symptoms of depression and anxiety is essential given that there is a widening gap in the supply and demand of care. AI chatbots provide new opportunities for quality care by supporting accessible, affordable, efficient, and personalized care. This study provides insights for developing and deploying AI chatbots such as ChatGPT in the context of mental health care. Findings could be used to design innovative interventions that encourage the adoption and continued use of AI chatbots among people with symptoms of depression and anxiety and who have difficulty accessing care.

The Effect of Digital Mental Health Literacy Interventions on Mental Health: Systematic Review and Meta-Analysis

BACKGROUND

Accelerated by technological advancements and the recent global pandemic, there is burgeoning interest in digital mental health literacy (DMHL) interventions that can positively affect mental health. However, existing work remains inconclusive regarding the effectiveness of DMHL interventions.

OBJECTIVE

This systematic review and meta-analysis investigated the components and modes of DMHL interventions, their moderating factors, and their long-term impacts on mental health literacy and mental health.

METHODS

We used a random-effects model to conduct meta-analyses and meta-regressions on moderating effects of DMHL interventions on mental health.

RESULTS

Using 144 interventions with 206 effect sizes, we found a moderate effect of DMHL interventions in enhancing distal mental health outcomes (standardized mean difference=0.42, 95% CI -0.10 to 0.73; P<.001) and a large effect in increasing proximal mental health literacy outcomes (standardized mean difference=0.65, 95% CI 0.59-0.74; P<.001). Uptake of DMHL interventions was comparable with that of control conditions, and uptake of DMHL interventions did not moderate the effects on both proximal mental health literacy outcomes and distal mental health outcomes. DMHL interventions were as effective as face-to-face interventions and did not differ by platform type or dosage. DMHL plus interventions (DMHL psychoeducation coupled with other active treatment) produced large effects in bolstering mental health, were more effective than DMHL only interventions (self-help DMHL psychoeducation), and were comparable with non-DMHL interventions (treatment as usual). DMHL interventions demonstrated positive effects on mental health that were sustained over follow-up assessments and were most effective in enhancing the mental health of emerging and older adults.

CONCLUSIONS

For theory building, our review and meta-analysis found that DMHL interventions are as effective as face-to-face interventions. DMHL interventions confer optimal effects on mental health when DMHL psychoeducation is combined with informal, nonprofessional active treatment components such as skills training and peer support, which demonstrate comparable effectiveness with that of treatment as usual (client-professional interactions and therapies). These effects, which did not differ by platform type or dosage, were sustained over time. Additionally, most DMHL interventions are found in Western cultural contexts, especially in high-income countries (Global North) such as Australia, the United States, and the United Kingdom, and limited research is conducted in low-income countries in Asia and in South American and African countries. Most of the DMHL studies did not report information on the racial or ethnic makeup of the samples. Future work on DMHL interventions that target racial or ethnic minority groups, particularly the design, adoption, and evaluation of the effects of culturally adaptive DMHL interventions on uptake and mental health functioning, is needed. Such evidence can drive the adoption and implementation of DMHL interventions at scale, which represents a key foundation for practice-changing impact in the provision of mental health resources for individuals and the community.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42023363995; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023363995.

A hybrid effectiveness-implementation trial of application-based tiered care (Mom's Good Mood) in treating perinatal anxiety within a primary health care system in China

INTRODUCTION

Perinatal anxiety (PNA) is a major public health concern.

METHODS

A hybrid effectiveness-implementation trial was conducted in two antenatal clinics in Hefei, China, to assess the effectiveness and cost-effectiveness of application-based tiered care (Mom's Good Mood, MGM) in treating PNA and to understand how well it fits into routine practices. Pregnant women who scored at least 5 points on the 7-Item Generalised Anxiety Disorder Scale (GAD-7) scale were successively assigned to the control group or the intervention group, which were given the usual care and MGM on usual care, respectively. At 6 months post partum, anxiety, depression and life satisfaction were assessed. Intention-to-treat analysis and the Reach, Effectiveness, Adoption, Implementation and Maintenance framework were adopted.

RESULTS

A total of 214 women were assigned to the control group and 341 to the intervention group. The mean changes in GAD-7 scores (Least-squares means, LSM, -1.42, 95% CI -2.18 to -0.66) and the risk of anxiety (adjusted odds ratio, aOR 0.30, 95% CI 0.18 to 0.51) were decreased, and the anxiety remission rate (aOR 2.72, 95% CI 1.69 to 4.40) were improved in the intervention group. Similar findings were observed regarding the change in Edinburgh Postnatal Depression Scale scores (LS -1.92, 95% CI -2.85 to -0.99), depression remission rate (aOR 2.24, 95% CI 1.39 to 3.63) and the risk of depression (aOR 0.57, 95% CI 0.33 to 0.98). MGM only costs ¥1.88 (US$0.27) per pregnant woman to boost the postpartum anxiety remission rate by 1% and was revealed to have a high reach rate of 78.3%, an adoption rate of 51.3%-80.8%.

CONCLUSION

MGM is a cost-effective and accessible tool in coping with PNA.

TRIAL REGISTRATION NUMBER

ChiCTR2100053419.

User experiences of college students using mental health applications to improve self-care: Implications for improving engagement

The purpose of this study is to evaluate themes on 'user experiences' among college students (N = 265) enrolled in an upper-division Psychopathology course who were assigned a project in which they were instructed to identify a self-care goal, choose from a list of six mental health-focused mobile applications (apps) provided by the instructor, and use the app over the course of three weeks to support progress towards their goal. Prior literature on user experiences typically evaluates user reviews, or asks participants to reflect on past app use or anticipate future use. Students reported their experiences using the app during key decision points: app selection, while using the app, and at the conclusion of the assignment. Using thematic analysis, results identified seven central themes and eight subthemes pertaining to the content of the app (e.g., app features) and the context of using the app (e.g., classroom assignment). Content-wise students liked: 1) features with a strong evidence base, namely, thought diaries and guided meditations; 2) progress tracking, because it increased awareness of mood/stressors, motivated students to see improvement, and helped them stay on track. Students appreciated having 3) crisis support resources; 4) app interfaces that allowed for customization (poor app interfaces were sometimes cited as the reason for disengagement); and 5) apps that included varied, comprehensive resources such that it felt like a one-stop shop. In addition to the content of features and design interface, the context in which mental health apps are introduced and used is important. The remaining themes related to the context in which the app was used, including 6) preparation for app usage, such as reviewing scholarly/credible sources, and 7) social support from fellow students completing the same assignment. Future research should evaluate the 'who, what, when, why, where, and how' of app utilization during key decision points, such as initial app selection or subscription renewal, to better understand the impact of user experience on engagement.

From formative design to service-ready therapeutic: A pragmatic approach to designing digital mental health interventions across domains

As digital mental health interventions (DMHIs) proliferate, there is a growing need to understand the complexities of moving these tools from concept and design to service-ready products. We highlight five case studies from a center that specializes in the design and evaluation of digital mental health interventions to illustrate pragmatic approaches to the development of digital mental health interventions, and to make transparent some of the key decision points researchers encounter along the design-to-product pipeline. Case studies cover different key points in the design process and focus on partnership building, understanding the problem or opportunity, prototyping the product or service, and testing the product or service. We illustrate lessons learned and offer a series of questions researchers can use to navigate key decision points in the digital mental health intervention (DMHI) development process.

Standardising the role of a digital navigator in behavioural health: a systematic review

As the number and availability of digital mental health tools increases, patients and clinicians see benefit only when these tools are engaging and well integrated into care. Digital navigators-ie, members of health-care teams who are dedicated to supporting patient use of digital resources-offer one solution and continue to be piloted in behavioural health; however, little is known about the core features of this position. The aims of this systematic review were to assess how digital navigators are implemented in behavioural health, and to provide a standardised definition of this position. In January, 2023, we conducted a systematic literature search resulting in 48 articles included in this systematic review. Results showed high heterogeneity between four attributes of digital navigators: training specifications, educational background, frequency of communication, and method of communication with patients. Reported effect sizes for depression and anxiety were medium to large, but could not be synthesised due to study heterogeneity and small study sample size. This systematic review was registered with PROSPERO (CRD42023391696). Results suggest that digital navigator support can probably increase access to, engagement with, and clinical integration of digital health technology, with standards for training and defined responsibilities now emerging.

Association Between User Interaction and Treatment Response of a Voice-Based Coach for Treating Depression and Anxiety: Secondary Analysis of a Pilot Randomized Controlled Trial

BACKGROUND

The quality of user interaction with therapeutic tools has been positively associated with treatment response; however, no studies have investigated these relationships for voice-based digital tools.

OBJECTIVE

This study evaluated the relationships between objective and subjective user interaction measures as well as treatment response on Lumen, a novel voice-based coach, delivering problem-solving treatment to patients with mild to moderate depression or anxiety or both.

METHODS

In a pilot trial, 42 adults with clinically significant depression (Patient Health Questionnaire-9 [PHQ-9]) or anxiety (7-item Generalized Anxiety Disorder Scale [GAD-7]) symptoms or both received Lumen, a voice-based coach delivering 8 problem-solving treatment sessions. Objective (number of conversational breakdowns, ie, instances where a participant's voice input could not be interpreted by Lumen) and subjective user interaction measures (task-related workload, user experience, and treatment alliance) were obtained for each session. Changes in PHQ-9 and GAD-7 scores at each ensuing session after session 1 measured the treatment response.

RESULTS

Participants were 38.9 (SD 12.9) years old, 28 (67%) were women, 8 (19%) were Black, 12 (29%) were Latino, 5 (12%) were Asian, and 28 (67%) had a high school or college education. Mean (SD) across sessions showed breakdowns (mean 6.5, SD 4.4 to mean 2.3, SD 1.8) decreasing over sessions, favorable task-related workload (mean 14.5, SD 5.6 to mean 17.6, SD 5.6) decreasing over sessions, neutral-to-positive user experience (mean 0.5, SD 1.4 to mean 1.1, SD 1.3), and high treatment alliance (mean 5.0, SD 1.4 to mean 5.3, SD 0.9). PHQ-9 (Ptrend=.001) and GAD-7 scores (Ptrend=.01) improved significantly over sessions. Treatment alliance correlated with improvements in PHQ-9 (Pearson r=-0.02 to -0.46) and GAD-7 (r=0.03 to -0.57) scores across sessions, whereas breakdowns and task-related workload did not. Mixed models showed that participants with higher individual mean treatment alliance had greater improvements in PHQ-9 (β=-1.13, 95% CI -2.16 to -0.10) and GAD-7 (β=-1.17, 95% CI -2.13 to -0.20) scores.

CONCLUSIONS

The participants had fewer conversational breakdowns and largely favorable user interactions with Lumen across sessions. Conversational breakdowns were not associated with subjective user interaction measures or treatment responses, highlighting how participants adapted and effectively used Lumen. Individuals experiencing higher treatment alliance had greater improvements in depression and anxiety. Understanding treatment alliance can provide insights on improving treatment response for this new delivery modality, which provides accessibility, flexibility, comfort with disclosure, and cost-related advantages compared to conventional psychotherapy.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04524104; https://clinicaltrials.gov/study/NCT04524104.

Peer-supported mobile mental health for veterans in primary care: A pilot study

One in four veteran primary care patients suffers from a mental health condition; however, most do not receive any treatment for these problems. Mobile health (mHealth) can overcome barriers to care access, but poor patient engagement limits the effectiveness and implementation of these tools. Peers may facilitate patient engagement with mHealth. We designed a protocol for peers to support implementation of mobile mental health tools in primary care and tested the feasibility, acceptability, and clinical utility of this approach. Thirty-nine patients across two Veterans Affairs sites who screened positive for depression during a primary care visit and were not currently in mental health treatment were enrolled. Participants were scheduled for four phone sessions with a peer over 8 weeks and introduced to five mobile apps for a range of transdiagnostic mental health issues (stress, low mood, sleep problems, anger, and trauma). Pre/post phone interviews using quantitative and qualitative approaches assessed participants' self-reported app use, satisfaction with the intervention, symptom change (stress, anxiety, depression, insomnia), and progress with personal health goals. On average, patients reported using 3.04 apps (SD = 1.46). Per the Client Satisfaction Questionnaire, global satisfaction with the intervention was high (M = 25.71 out of 32, SD = 3.95). Pre to post participants reported significant improvements in their level of stress, based on a quantitative measure (p = .008), and 87% reported progress on at least one personal health goal. Findings support the feasibility, acceptability, and clinical utility of peer-supported mobile mental health for veterans in primary care. A randomized controlled trial of an adaptive version of this intervention is recommended. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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 Engagement Clusters of an 8-Week Digital Mental Health Intervention Guided by a Relational Agent (Woebot): Exploratory Study

BACKGROUND

With the proliferation of digital mental health interventions (DMHIs) guided by relational agents, little is known about the behavioral, cognitive, and affective engagement components associated with symptom improvement over time. Obtaining a better understanding could lend clues about recommended use for particular subgroups of the population, the potency of different intervention components, and the mechanisms underlying the intervention's success.

OBJECTIVE

This exploratory study applied clustering techniques to a range of engagement indicators, which were mapped to the intervention's active components and the connect, attend, participate, and enact (CAPE) model, to examine the prevalence and characterization of each identified cluster among users of a relational agent-guided DMHI.

METHODS

We invited adults aged 18 years or older who were interested in using digital support to help with mood management or stress reduction through social media to participate in an 8-week DMHI guided by a natural language processing-supported relational agent, Woebot. Users completed assessments of affective and cognitive engagement, working alliance as measured by goal and task working alliance subscale scores, and enactment (ie, application of therapeutic recommendations in real-world settings). The app passively collected data on behavioral engagement (ie, utilization). We applied agglomerative hierarchical clustering analysis to the engagement indicators to identify the number of clusters that provided the best fit to the data collected, characterized the clusters, and then examined associations with baseline demographic and clinical characteristics as well as mental health outcomes at week 8.

RESULTS

Exploratory analyses (n=202) supported 3 clusters: (1) "typical utilizers" (n=81, 40%), who had intermediate levels of behavioral engagement; (2) "early utilizers" (n=58, 29%), who had the nominally highest levels of behavioral engagement in week 1; and (3) "efficient engagers" (n=63, 31%), who had significantly higher levels of affective and cognitive engagement but the lowest level of behavioral engagement. With respect to mental health baseline and outcome measures, efficient engagers had significantly higher levels of baseline resilience (P<.001) and greater declines in depressive symptoms (P=.01) and stress (P=.01) from baseline to week 8 compared to typical utilizers. Significant differences across clusters were found by age, gender identity, race and ethnicity, sexual orientation, education, and insurance coverage. The main analytic findings remained robust in sensitivity analyses.

CONCLUSIONS

There were 3 distinct engagement clusters found, each with distinct baseline demographic and clinical traits and mental health outcomes. Additional research is needed to inform fine-grained recommendations regarding optimal engagement and to determine the best sequence of particular intervention components with known potency. The findings represent an important first step in disentangling the complex interplay between different affective, cognitive, and behavioral engagement indicators and outcomes associated with use of a DMHI incorporating a natural language processing-supported relational agent.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05672745; https://classic.clinicaltrials.gov/ct2/show/NCT05672745.

Cultural Responsivity in Technology-Enabled Services: Integrating Culture Into Technology and Service Components

Technology-enabled services (TESs) are clinical interventions that combine technological and human components to provide health services. TESs for mental health are efficacious in the treatment of anxiety and depression and are currently being offered as frontline treatments around the world. It is hoped that these interventions will be able to reach diverse populations across a range of identities and ultimately decrease disparities in mental health treatment. However, this hope is largely unrealized. TESs include both technology and human service components, and we argue that cultural responsivity must be considered in each of these components to help address existing treatment disparities. To date, there is limited guidance on how to consider cultural responsivity within these interventions, including specific targets for the development, tailoring, or design of the technologies and services within TESs. In response, we propose a framework that provides specific recommendations for targets based on existing models, both at the technological component level (informed by the Behavioral Intervention Technology Model) and the human support level (informed by the Efficiency Model of Support). We hope that integrating culturally responsive considerations into these existing models will facilitate increased attention to cultural responsivity within TESs to ensure they are ethical and responsive for everyone.

The Effect of a Digital Mental Health Program on Anxiety and Depression Symptoms: Retrospective Analysis of Clinical Severity

BACKGROUND

Evidence-based digital health programs have shown efficacy in being primary tools to improve emotional and mental health, as well as offering supplementary support to individuals undergoing psychotherapy for anxiety, depression, and other mental health disorders. However, information is lacking about the dose response to digital mental health interventions.

OBJECTIVE

The objective of the study was to examine the effect of time in program and program usage on symptom change among individuals enrolled in a real-world comprehensive digital mental health program (myStrength) who are experiencing severe anxiety or depression.

METHODS

Eligible participants (N=18,626) were adults aged 18 years and older who were enrolled in myStrength for at least four weeks as part of their employee wellness benefit program, who completed baseline, the 2-week, 2-month, and 6-month surveys querying symptoms of anxiety (Generalized Anxiety Disorder-7 [GAD-7]) and depression (Patient Health Questionnaire-9 [PHQ-9]). Linear growth curve models were used to analyze the effect of average weekly program usage on subsequent GAD-7 and PHQ-9 scores for participants with scores indicating severe anxiety (GAD-7≥15) or depression (PHQ-9≥15). All models were adjusted for baseline score and demographics.

RESULTS

Participants in the study (N=1519) were 77.4% female (1176/1519), had a mean age of 45 years (SD 14 years), and had an average enrollment time of 3 months. At baseline, participants reported an average of 9.39 (SD 6.04) on the GAD-7 and 11.0 (SD 6.6) on the PHQ-9. Those who reported 6-month results had an average of 8.18 (SD 6.15) on the GAD-7 and 9.18 (SD 6.79) on the PHQ-9. Participants with severe scores (n=506) experienced a significant improvement of 2.97 (SE 0.35) and 3.97 (SE 0.46) at each time point for anxiety and depression, respectively (t=-8.53 and t=-8.69, respectively; Ps<.001). Those with severe baseline scores also saw a reduction of 0.27 (SE 0.08) and 0.25 (SE 0.09) points in anxiety and depression, respectively, for each additional program activity per week (t=-3.47 and t=-2.66, respectively; Ps<.05).

CONCLUSIONS

For participants with severe baseline scores, the study found a clinically significant reduction of approximately 9 points for anxiety and 12 points for depression after 6 months of enrollment, suggesting that interventions targeting mental health must maintain active, ongoing engagement when symptoms are present and be available as a continuous resource to maximize clinical impact, specifically in those experiencing severe anxiety or depression. Moreover, a dosing effect was shown, indicating improvement in outcomes among participants who engaged with the program every other day for both anxiety and depression. This suggests that digital mental health programs that provide both interesting and evidence-based activities could be more successful in further improving mental health outcomes.

Selecting and describing control conditions in mobile health randomized controlled trials: a proposed typology

Hundreds of randomized controlled trials (RCTs) have tested the efficacy of mobile health (mHealth) tools for a wide range of mental and behavioral health outcomes. These RCTs have used a variety of control condition types which dramatically influence the scientific inferences that can be drawn from a given study. Unfortunately, nomenclature across mHealth RCTs is inconsistent and meta-analyses commonly combine control conditions that differ in potentially important ways. We propose a typology of control condition types in mHealth RCTs. We define 11 control condition types, discuss key dimensions on which they differ, provide a decision tree for selecting and identifying types, and describe the scientific inferences each comparison allows. We propose a five-tier comparison strength gradation along with four simplified categorization schemes. Lastly, we discuss unresolved definitional, ethical, and meta-analytic issues related to the categorization of control conditions in mHealth RCTs.

Efficacy, Safety, and Evaluation Criteria of mHealth Interventions for Depression: Systematic Review

BACKGROUND

Depression is a significant public health issue that can lead to considerable disability and reduced quality of life. With the rise of technology, mobile health (mHealth) interventions, particularly smartphone apps, are emerging as a promising approach for addressing depression. However, the lack of standardized evaluation tools and evidence-based principles for these interventions remains a concern.

OBJECTIVE

In this systematic review and meta-analysis, we aimed to evaluate the efficacy and safety of mHealth interventions for depression and identify the criteria and evaluation tools used for their assessment.

METHODS

A systematic review and meta-analysis of the literature was carried out following the recommendations of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. Studies that recruited adult patients exhibiting elevated depressive symptoms or those diagnosed with depressive disorders and aimed to assess the effectiveness or safety of mHealth interventions were eligible for consideration. The primary outcome of interest was the reduction of depressive symptoms, and only randomized controlled trials (RCTs) were included in the analysis. The risk of bias in the original RCTs was assessed using version 2 of the Cochrane risk-of-bias tool for randomized trials.

RESULTS

A total of 29 RCTs were included in the analysis after a comprehensive search of electronic databases and manual searches. The efficacy of mHealth interventions in reducing depressive symptoms was assessed using a random effects meta-analysis. In total, 20 RCTs had an unclear risk of bias and 9 were assessed as having a high risk of bias. The most common element in mHealth interventions was psychoeducation, followed by goal setting and gamification strategies. The meta-analysis revealed a significant effect for mHealth interventions in reducing depressive symptoms compared with nonactive control (Hedges g=-0.62, 95% CI -0.87 to -0.37, I2=87%). Hybrid interventions that combined mHealth with face-to-face sessions were found to be the most effective. Three studies compared mHealth interventions with active controls and reported overall positive results. Safety analyses showed that most studies did not report any study-related adverse events.

CONCLUSIONS

This review suggests that mHealth interventions can be effective in reducing depressive symptoms, with hybrid interventions achieving the best results. However, the high level of heterogeneity in the characteristics and components of mHealth interventions indicates the need for personalized approaches that consider individual differences, preferences, and needs. It is also important to prioritize evidence-based principles and standardized evaluation tools for mHealth interventions to ensure their efficacy and safety in the treatment of depression. Overall, the findings of this study support the use of mHealth interventions as a viable method for delivering mental health care.

TRIAL REGISTRATION

PROSPERO CRD42022304684; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=304684.

Efficacy of a Text-Based Mental Health Coaching App in Improving the Symptoms of Stress, Anxiety, and Depression: Randomized Controlled Trial

BACKGROUND

Stress, anxiety, and depression are major mental health concerns worldwide. A wide variety of digital mental health interventions have demonstrated efficacy in improving one's mental health status, and digital interventions that involve some form of human involvement have been shown to demonstrate greater efficacy than self-guided digital interventions. Studies demonstrating the efficacy of digital mental health interventions within the Asian region are scarce.

OBJECTIVE

This study aimed to investigate the potential efficacy of the digital mental health intervention, ThoughtFullChat, which consists of one-on-one, asynchronous, text-based coaching with certified mental health professionals and self-guided tools, in improving self-reported symptoms of depression, anxiety, and stress. The study also aims to examine the potential differences in efficacy among occupational subgroups and between sexes.

METHODS

A randomized controlled study was conducted among housemen (trainee physicians), students, faculty members, and corporate staff at International Medical University, Malaysia. A total of 392 participants were enrolled and randomized to the intervention (n=197, 50.3%) and control (n=195, 49.7%) groups. Depression, anxiety, and stress symptoms were measured using the Depression, Anxiety, and Stress Scale-21 items at baseline and after the 3-month intervention period. The Satisfaction with Life Scale and Brief Resilience Scale were also included, along with a questionnaire about demographics.

RESULTS

Significant decrease was observed in depression (P=.02) and anxiety (P=.002) scores in the intervention group. A subgroup (corporate staff) also demonstrated significant decrease in stress (P=.005) alongside depression (P=.006) and anxiety (P=.002). Females showed significant improvements in depression (P=.02) and anxiety (P<.001) when compared with males.

CONCLUSIONS

This study provides evidence that the ThoughtFullChat app is effective in improving the symptoms of depression, anxiety, and stress in individuals, particularly among corporate staff from the educational field. It also supports the notion that mobile mental health apps that connect users to mental health professionals in a discreet and cost-efficient manner can make important contributions to the improvement of mental health outcomes. The differential improvements among occupational subgroups and between sexes in this study indicate the need for future digital mental health app designs to consider an element of personalization focused on systemic components relating to occupation.

TRIAL REGISTRATION

Clinicaltrials.gov NCT04944277; https://classic.clinicaltrials.gov/ct2/show/NCT04944277.

Assessing Patient Adherence to and Engagement With Digital Interventions for Depression in Clinical Trials: Systematic Literature Review

BACKGROUND

New approaches to the treatment of depression are necessary for patients who do not respond to current treatments or lack access to them because of barriers such as cost, stigma, and provider shortage. Digital interventions for depression are promising; however, low patient engagement could limit their effectiveness.

OBJECTIVE

This systematic literature review (SLR) assessed how participant adherence to and engagement with digital interventions for depression have been measured in the published literature, what levels of adherence and engagement have been reported, and whether higher adherence and increased engagement are linked to increased efficacy.

METHODS

We focused on a participant population of adults (aged ≥18 years) with depression or major depressive disorder as the primary diagnosis and included clinical trials, feasibility studies, and pilot studies of digital interventions for treating depression, such as digital therapeutics. We screened 756 unique records from Ovid MEDLINE, Embase, and Cochrane published between January 1, 2000, and April 15, 2022; extracted data from and appraised the 94 studies meeting the inclusion criteria; and performed a primarily descriptive analysis. Otsuka Pharmaceutical Development & Commercialization, Inc (Princeton, New Jersey, United States) funded this study.

RESULTS

This SLR encompassed results from 20,111 participants in studies using 47 unique web-based interventions (an additional 10 web-based interventions were not described by name), 15 mobile app interventions, 5 app-based interventions that are also accessible via the web, and 1 CD-ROM. Adherence was most often measured as the percentage of participants who completed all available modules. Less than half (44.2%) of the participants completed all the modules; however, the average dose received was 60.7% of the available modules. Although engagement with digital interventions was measured differently in different studies, it was most commonly measured as the number of modules completed, the mean of which was 6.4 (means ranged from 1.0 to 19.7) modules. The mean amount of time participants engaged with the interventions was 3.9 (means ranged from 0.7 to 8.4) hours. Most studies of web-based (34/45, 76%) and app-based (8/9, 89%) interventions found that the intervention group had substantially greater improvement for at least 1 outcome than the control group (eg, care as usual, waitlist, or active control). Of the 14 studies that investigated the relationship between engagement and efficacy, 9 (64%) found that increased engagement with digital interventions was significantly associated with improved participant outcomes. The limitations of this SLR include publication bias, which may overstate engagement and efficacy, and low participant diversity, which reduces the generalizability.

CONCLUSIONS

Patient adherence to and engagement with digital interventions for depression have been reported in the literature using various metrics. Arriving at more standardized ways of reporting adherence and engagement would enable more effective comparisons across different digital interventions, studies, and populations.

Study protocol paper for the multi-site feasibility evaluation of mobile and technology-assisted aftercare services for crisis stabilization units

BACKGROUND

Law enforcement frequently responds to substance abuse and mental health crises. Crisis stabilization units (CSUs) operate as a public-receiving facility to provide short-term stabilization services for individuals experiencing these crises and offer law enforcement an important alternative to arrest. However, there is limited understanding about how and when law enforcement decides to use CSUs. There is also the challenge of retaining individuals in treatment after CSU stabilization to prevent future crises and persistent engagement with police. This study will respond to these gaps by exploring CSU procedures and examining the feasibility and acceptability of a technology-assisted mobile aftercare intervention designed for individuals brought to a CSU by law enforcement.

METHODS

This study will consist of three aims. Aim 1 will include qualitative interviews with law enforcement and CSU-affiliated mental health staff (n=80) regarding CSU utilization and collaboration logistics between the groups. Findings from Aim 1 will be synthesized for the development of an implementation guide of our intervention, mobile, and technology-assisted aftercare, designed for individuals brought to a CSU by law enforcement, during Aim 2. During Aim 2, intervention services will be pilot-tested for 6 months through a small sample (n=24), randomized control trial (RCT). Control participants will receive standard services available for individuals discharging from a CSU. Treatment participants will receive the mobile aftercare intervention. Qualitative and quantitative data will be collected at 2 weeks, 3 months, and 6 months post-recruitment for all study participants. Aims 1 and 2 will inform the design of a multi-site RCT to compare CSUs with and without mobile and technology-assisted aftercare (Aim 3).

DISCUSSION

The study will offer decision making and procedural insight into law enforcement use of CSUs as an alternative to jail and provide opportunities to inform that process. This research will provide outcome trends for those who go through standard CSU services compared to those who receive mobile and technology-assisted aftercare services. The current study will inform a larger RCT efficacy study of CSUs with and without technology-assisted aftercare services.

TRIAL REGISTRATION

This study was registered on ClinicalTrials.gov (reference #NCT04899934) on May 25, 2021.

Designing High-Fidelity Mobile Health for Depression in Indonesian Adolescents Using Design Science Research: Mixed Method Approaches

BACKGROUND

COVID-19 mitigation protocols, enacted to control the pandemic, have also been shown to have a negative impact on mental health, including the mental health of adolescents. The threat of being infected by SARS-CoV-2 and substantial changes in lifestyle, including limited social interaction due to stay-at-home orders, led to loneliness as well as depressive symptoms. However, offline psychological assistance is restricted, as psychologists are bounded by mitigation protocols. Further, not all adolescents' guardians are open to their children attending or have the means to pay for psychological service; thus, adolescents remain untreated. Having a mobile health (mHealth) app for mental health that uses monitoring, provides social networks, and delivers psychoeducation may provide a solution, especially in countries that have limited health facilities and mental health workers.

OBJECTIVE

This study aimed to design an mHealth app to help prevent and monitor depression in adolescents. The design of this mHealth app was carried out as a high-fidelity prototype.

METHODS

We used a design science research (DSR) methodology with 3 iterations and 8 golden rule guidelines. The first iteration used interviews, and the second and third iterations used mixed method approaches. The DSR stages include the following: (1) identify the problem; (2) define the solution; (3) define the solution objective; (4) develop, demonstrate, and evaluate the solution; and (5) communicate the solution. This study involved students and medical experts.

RESULTS

The first iteration resulted in a wireframe and prototype for the next iteration. The second iteration resulted in a System Usability Scale score of 67.27, indicating a good fit. In the third iteration, the system usefulness, information quality, interface quality, and overall values were 2.416, 2.341, 2.597, and 2.261, respectively, indicating a good design. Key features of this mHealth app include a mood tracker, community, activity target, and meditation, and supporting features that complement the design include education articles and early detection features.

CONCLUSIONS

Our findings provide guidance for health facilities and to design and implement future mHealth apps to help treat adolescent depression.

Exploring the Safety of a General Digital Mental Health Intervention to Effect Symptom Reduction among Individuals with and without Suicidal Ideation: A Secondary Analysis

Trials of digital mental health interventions (DMHIs) often exclude individuals with suicide-related thoughts and behaviors precluding an understanding of whether DMHIs for affective disorders are safe for, and perform similarly within, this high-risk group. We explore the safety and performance of a DMHI for depression in participants with and without suicidal ideation (SI) at baseline. Three hundred and one participants were included in this secondary data analysis from a trial of an 8-week DMHI comprising 14 smartphone apps. We found that SI decreased across the study among participants with baseline SI and that baseline SI status did not attenuate depression treatment effects. Through a case study of the IntelliCare platform, we find that DMHIs for general affective disorders can be safe.

A System for Rapidly Yet Rigorously Evaluating the Quality of Randomized Controlled Trials

ABSTRACT

This tutorial describes a system for rapidly yet rigorously assessing the quality of randomized controlled trials (RCTs). The system has 7 criteria, represented by the acronym "BIS FOES." The BIS FOES system directs readers to assess RCTs based on the following 7 criteria: the RCT's use (or not) of effective (1) Blinding; the RCT's use (or not) of (2) Intent-to-Treat Analysis; the RCT's (3) Size and other information reflecting the effectiveness of randomization; the amount of sample lost during (4) Follow-up; the (5) Outcomes examined by the RCT (specifically, the outcome measures used by the RCT), the (6) Effects reported (ie, the statistical and clinical significance of the RCT's primary, secondary, and safety findings), and any (7) Special Considerations (ie, additional strengths, limitations, or notable features of the RCT). The first 6 criteria are of basic importance to the assessment of every RCT, whereas the Special Considerations criteria allows the system to be expanded to include virtually any other important aspect of the RCT. This tutorial explains the importance of these criteria and how to assess them. This tutorial also describes how many BIS FOES criteria can be initially assessed from the RCT Abstract while also directing readers to specific locations in the RCT article where additional important information can be found. We hope that the BIS FOES system will help healthcare trainees, but also potentially clinicians, researchers, and the general public, rapidly and thoroughly assess RCTs.

Anxiety Screening: Evidence Report and Systematic Review for the US Preventive Services Task Force

Importance

Anxiety is commonly seen in primary care and associated with substantial burden.

Objective

To review the benefits and harms of screening and treatment for anxiety and the accuracy of instruments to detect anxiety among primary care patients.

Data Sources

MEDLINE, PsychINFO, Cochrane library through September 7, 2022; references of existing reviews; ongoing surveillance for relevant literature through November 25, 2022.

Study Selection

English-language original studies and systematic reviews of screening or treatment compared with control conditions and test accuracy studies of a priori-selected screening instruments were included. Two investigators independently reviewed abstracts and full-text articles for inclusion. Two investigators independently rated study quality.

Data Extraction and Synthesis

One investigator abstracted data; a second checked accuracy. Meta-analysis results were included from existing systematic reviews where available; meta-analyses were conducted on original research when evidence was sufficient.

Main Outcomes and Measures

Anxiety and depression outcomes; global quality of life and functioning; sensitivity and specificity of screening tools.

Results

Of the 59 publications included, 40 were original studies (N = 275 489) and 19 were systematic reviews (including ≈483 studies [N≈81 507]). Two screening studies found no benefit for screening for anxiety. Among test accuracy studies, only the Generalized Anxiety Disorder (GAD) GAD-2 and GAD-7 screening instruments were evaluated by more than 1 study. Both screening instruments had adequate accuracy for detecting generalized anxiety disorder (eg, across 3 studies the GAD-7 at a cutoff of 10 had a pooled sensitivity of 0.79 [95% CI, 0.69 to 0.94] and specificity of 0.89 [95% CI, 0.83 to 0.94]). Evidence was limited for other instruments and other anxiety disorders. A large body of evidence supported the benefit of treatment for anxiety. For example, psychological interventions were associated with a small pooled standardized mean difference of -0.41 in anxiety symptom severity in primary care patients with anxiety (95% CI, -0.58 to -0.23]; 10 RCTs [n = 2075]; I2 = 40.2%); larger effects were found in general adult populations.

Conclusions and Relevance

Evidence was insufficient to draw conclusions about the benefits or harms of anxiety screening programs. However, clear evidence exists that treatment for anxiety is beneficial, and more limited evidence indicates that some anxiety screening instruments have acceptable accuracy to detect generalized anxiety disorder.

A CBT-based mobile intervention as an adjunct treatment for adolescents with symptoms of depression: a virtual randomized controlled feasibility trial

Background

High rates of adolescent depression demand for more effective, accessible treatment options. A virtual randomized controlled trial was used to assess the feasibility and acceptability of a 5-week, self-guided, cognitive behavioral therapy (CBT)-based mobile application, Spark, compared to a psychoeducational mobile application (Active Control) as an adjunct treatment for adolescents with depression during the COVID-19 pandemic.

Methods

A community sample aged 13-21, with self-reported symptoms of depression, was recruited nationwide. Participants were randomly assigned to use either Spark or Active Control (N_Spark = 35; N_{Active Control} = 25). Questionnaires, including the PHQ-8 measuring depression symptoms, completed before, during, and immediately following completion of the intervention, evaluated depressive symptoms, usability, engagement, and participant safety. App engagement data were also analyzed.

Results

60 eligible adolescents (female = 47) were enrolled in 2 months. 35.6% of those expressing interest were consented and all enrolled. Study retention was high (85%). Spark users rated the app as usable (System Usability Scale_mean = 80.67) and engaging (User Engagement Scale-Short Form_mean = 3.62). Median daily use was 29%, and 23% completed all levels. There was a significant negative relationship between behavioral activations completed and change in PHQ-8. Efficacy analyses revealed a significant main effect of time, F = 40.60, p < .001, associated with decreased PHQ-8 scores over time. There was no significant Group × Time interaction (F = 0.13, p = .72) though the numeric decrease in PHQ-8 was greater for Spark (4.69 vs. 3.56). No serious adverse events or adverse device effects were reported for Spark users. Two serious adverse events reported in the Active Control group were addressed per our safety protocol.

Conclusion

Recruitment, enrollment, and retention rates demonstrated study feasibility by being comparable or better than other mental health apps. Spark was highly acceptable relative to published norms. The study's novel safety protocol efficiently detected and managed adverse events. The lack of significant difference in depression symptom reduction between Spark and Active Control may be explained by study design and study design factors. Procedures established during this feasibility study will be leveraged for subsequent powered clinical trials evaluating app efficacy and safety.

Clinical Trial Registration

https://clinicaltrials.gov/ct2/show/NCT04524598.

A qualitative exploration of college students' experiences using mobile apps to improve self-care during the COVID-19 pandemic

Objective: This project examines students' experiences using a mental health mobile application (app) as part of a class assignment developed to support student well-being. Participants: Data was collected from 265 undergraduate students enrolled in a psychology course during the COVID-19 pandemic. Methods: Students developed a self-care goal and used an app to support progress toward it. Thematic analysis was applied to students' written reflections about their experiences using the app and practicing self-care. Results: Students reported using an app for self-care was 1) more helpful than expected for improving focus, productivity, motivation, sleep, and mental health symptoms; 2) challenging due to loss of interest, slow improvement, difficulty integrating into routine, or negative feelings triggered; and 3) influenced by the pandemic and transition to remote learning. Conclusions: A classroom assignment designed to promote self-care using a mental health app shows promise. Future research is needed to better understand engagement and impact.

The Perceived Utility of Smartphone and Wearable Sensor Data in Digital Self-tracking Technologies for Mental Health

Mental health symptoms are commonly discovered in primary care. Yet, these settings are not set up to provide psychological treatment. Digital interventions can play a crucial role in stepped care management of patients' symptoms where patients are offered a low intensity intervention, and treatment evolves to incorporate providers if needed. Though digital interventions often use smartphone and wearable sensor data, little is known about patients' desires to use these data to manage mental health symptoms. In 10 interviews with patients with symptoms of depression and anxiety, we explored their: symptom self-management, current and desired use of sensor data, and comfort sharing such data with providers. Findings support the use digital interventions to manage mental health, yet they also highlight a misalignment in patient needs and current efforts to use sensors. We outline considerations for future research, including extending design thinking to wraparound services that may be necessary to truly reduce healthcare burden.

Enhancing Internet-based psychotherapy for adults with emotional disorders using ecological momentary assessments and interventions: Study protocol of a feasibility trial with "My EMI, Emotional Well-being" app

INTRODUCTION

Emotional disorders are the most frequent mental health problems globally. To ensure the dissemination of psychological treatments for these conditions, novel forms of delivery (e.g., Internet or mobile apps) and more scalable forms of psychotherapy (e.g., transdiagnostic interventions) have become increasingly popular. Research, however, shows that a significant number of patients, around 40 % according to some studies, do not respond to the interventions as expected (i.e., not-on-track patients). Ecological momentary assessments (EMAs) and ecological momentary interventions (EMIs) could simplify tailoring treatments to the patients' progress and rapidly respond to undesired outcomes during psychotherapy. Therefore, these would facilitate measurement-based care with little therapist involvement. This study aims to explore the feasibility of an app-based system called My EMI, Emotional Well-being for people with emotional disorders. According to daily EMAs, the app will provide personalized EMIs while participants receive a self-applied online transdiagnostic treatment. The app will be used as an add-tool to the online intervention to address emotion dysregulation, foster adherence, and reinforce contents. The current study describes the study protocol for this trial.

METHOD AND ANALYSIS

A single-group, open trial design will be used. Participants will be 30 adults suffering from emotional disorders. Primary outcomes will be app usability, acceptability, and response rates. Secondary outcomes will be either evaluated in Qualtrics at pre-treatment, post-treatment, and 3-month follow-up (depression and anxiety severity, and transdiagnostic dimensions of emotional disorders) or daily throughout the study with the app (EMAs of mood and five transdiagnostic mechanisms of therapeutic change). EMIs will consist of brief, evidence-based transdiagnostic CBT digital content (images, infographics, or videos) delivered just-in-time. Only if problems persist, short phone calls or episodic videocalls will be conducted. The Ethics Committee of the Jaume I University approved the study and all its procedures (CD/111/2021) in December 2021.

DISCUSSION

Identifying personalized and scalable interventions is paramount to improve mental health care, especially its accessibility, and to reduce the psychological distress of people with mental health problems. Feasibility data of the app (EMA and EMI system) supported by a self-applied online transdiagnostic intervention will be important to explore whether this modern approach is a real option to move forward personalized psychological interventions for persons with emotional disorders.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT05109780. Registered 05 November 2021, https://clinicaltrials.gov/ct2/show/NCT05109780.

Effects of Mobile Mindfulness Meditation on the Mental Health of University Students: Systematic Review and Meta-analysis

BACKGROUND

Mobile mindfulness meditation (MMM) is a mindfulness meditation intervention implemented using mobile devices such as smartphones and apps. MMM has been used to help manage the mental health of university students.

OBJECTIVE

This study aims to evaluate the effectiveness of MMM on the mental health of university students in the areas of stress, anxiety, depression, mindfulness, well-being, and resilience.

METHODS

We conducted a systematic review and meta-analysis of the effectiveness of MMM on the mental health of university students. This study followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. An electronic literature search was performed on PubMed, Web of Science, EBSCO, Cochrane Library, and Embase databases, from inception to July 16, 2021. This study was conducted to identify studies that reported the effects of MMM on the primary outcomes including stress, anxiety, and depression, and on the secondary outcomes including mindfulness, well-being, and resilience. Two reviewers retrieved articles, evaluated quality, and extracted data independently. The methodological quality of the selected studies was determined using the Cochrane criteria for risk-of-bias assessment. Standardized mean differences (SMDs) for continuous outcomes and risk ratios for dichotomous outcomes were calculated. Sensitivity analyses and subgroup analyses were performed for results with high heterogeneity. The RevMan version 5.3 was used to perform meta-analysis.

RESULTS

A total of 10 studies, including 958 university students, were selected for this meta-analysis. Results of the primary outcome showed that the MMM groups were more effective than the control groups in decreasing stress (SMD -0.41, 95% CI -0.59 to -0.23; P<.001) and alleviating anxiety (SMD -0.29, 95% CI -0.50 to -0.09; P=.004). However, there was no difference between the MMM groups and the control groups in depression (SMD -0.14, 95% CI -0.30 to 0.03; P=.11). The use of either waitlist control or traditional face-to-face intervention in the control group was identified as the source of heterogeneity. Specifically, the waitlist control subgroup (SMD -0.33, 95% CI -0.53 to -0.13; P=.002) was superior when compared with the face-to-face subgroup (SMD 0.29, 95% CI -0.01 to 0.59; P=.06). Results of the secondary outcome showed that the MMM groups were more effective than the control groups in enhancing well-being (SMD 0.30, 95% CI 0.11-0.50; P=.003) and improving mindfulness (SMD 2.66, 95% CI 0.77-4.55; P=.006). Whether commercial sponsorship was obtained was considered as the source of heterogeneity. The "without company support" group (SMD 17.60, 95% CI 11.32-23.87; P<.001) was superior to the "with company support" group (SMD 1.17, 95% CI -0.82 to 3.15; P=.25) in raising the level of mindfulness. However, there was no difference between the MMM and control groups in resilience (SMD -0.06, 95% CI -0.26 to 0.15; P=.59). The evidence level of the results from the 10 studies was determined to be moderate to low.

CONCLUSIONS

MMM was an effective method to reduce stress and anxiety, and to increase the well-being and mindfulness of university students. However, further studies are needed to confirm our findings.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42022303585; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=303585.

Antidepressants overuse in primary care: Prescription trends between 2010 and 2019 in Catalonia

INTRODUCTION

There has been an increase in the prescription of antidepressants (AD) in primary care (PC). However, it is unclear whether this was explained by a rise in diagnoses with an indication for AD. We investigated the changes in frequency and the variables associated with AD prescription in Catalonia, Spain.

METHODS

We retrieved AD prescription, sociodemographic, and health-related data using individual electronic health records from a population-representative sample (N=947.698) attending PC between 2010 and 2019. Prescription of AD was calculated using DHD (Defined Daily Doses per 1000 inhabitants/day). We compared cumulative changes in DHD with cumulative changes in diagnoses with an indication for AD during the study period. We used Poisson regression to examine sociodemographic and health-related variables associated with AD prescription.

RESULTS

Both AD prescription and mental health diagnoses with an indication for AD gradually increased. At the end of the study period, DHD of AD prescriptions and mental health diagnoses with an indication for AD reached cumulative increases of 404% and 49% respectively. Female sex (incidence rate ratio (IRR)=2.83), older age (IRR=25.43), and lower socio-economic status (IRR=1.35) were significantly associated with increased risk of being prescribed an AD.

CONCLUSIONS

Our results from a large and representative cohort of patients confirm a steady increase of AD prescriptions that is not explained by a parallel increase in mental health diagnoses with an indication for AD. A trend on AD off-label and over-prescriptions in the PC system in Catalonia can be inferred from this dissociation.

Effectiveness of Mental Health Apps for Distress During COVID-19 in US Unemployed and Essential Workers: Remote Pragmatic Randomized Clinical Trial

BACKGROUND

During the COVID-19 pandemic, the general public was concerned about the mental health impacts of unemployment due to COVID-19 and the stress essential workers experienced during this time. Several reports indicated that people in distress were turning to digital technology, but there was little evidence about the impact of these tools on mitigating distress.

OBJECTIVE

This study seeks to determine the acceptability, feasibility, usability, and effectiveness of mobile mental health apps for decreasing mental health symptoms in essential workers and unemployed individuals with suicide risk.

METHODS

We recruited participants who indicated that they were unemployed because of COVID-19 or were COVID-19-designated essential workers. Participants were randomized to 1 of 4 free commercial mobile apps for managing distress that were (1) highly rated by PsyberGuide and (2) met the criteria for intervention features these participants indicated were desirable in a previous survey. Participants used the apps for 4 weeks and completed baseline and 4-week self-assessments of depression, anxiety emotional regulation, and suicide risk.

RESULTS

We found no differences between the apps in any outcome but did find significant changes in depression and anxiety over time (Patient Health Questionnaire [PHQ]-9: estimate=-1.5, SE 0.2, 95% CI -1.1 to -1.8, P<.001; Generalized Anxiety Disorder Scale [GAD]-7: estimate=-1.3, SE 0.2, 95% CI -1.0 to -1.6, P<.001). We found no significant changes in suicidal behavior (Suicide Behaviors Questionnaire-Revised [SBQ-R]) or emotional regulation (Difficulties in Emotion Regulation Scale - Short Form [DERS-SF]) for the 4 weeks. We did find a significant dose-response pattern for changes in depression and anxiety. Using the app at least once a week resulted in greater improvements in treatment conditions over time on depression (estimate=-0.6, SE 0.2, 95% CI 1.0-0.2, P=.003) and anxiety (estimate=0.1, SE 0.2, 95% CI 0.4-0.6, P=.78). There was no association between app frequency and changes in suicidal behavior (SBQ-R) or emotional regulation (DERS-SF). We further found a significant difference between the conditions with regard to app usability, with the control app being the most usable (mean_{Beautiful Mood} 72.9, SD 16.7; mean_{COVID Coach} 71.2, SD 15.4; mean_Calm 66.8, SD 17.3; mean_{7 Cups} 65.2, SD 17.7). We found no significant differences for app acceptability or appropriateness.

CONCLUSIONS

Few studies have evaluated prospectively the utility and usability of commercial apps for mood. This study found that free, self-guided commercial mobile mental health apps are seen as usable, but no one app is superior to the other. Although we found that regular use is indicated for effects on depression and anxiety to occur in those who are more symptomatic, regression to the mean cannot be ruled out.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04536935; https://tinyurl.com/mr36zx3s.

Mobile App to Enhance Patient Activation and Patient-Provider Communication in Major Depressive Disorder Management: Collaborative, Randomized Controlled Pilot Study

BACKGROUND

Enhanced patient-provider engagement can improve patient health outcomes in chronic conditions, including major depressive disorder (MDD).

OBJECTIVE

We evaluated the impact of a digitally enabled care mobile app, Pathway, designed to improve MDD patient-provider engagement. Patients used a mobile interface to assess treatment progress and share this information with primary care providers (PCPs).

METHODS

In this 52-week, real-world effectiveness and feasibility study conducted in primary care clinics, 40 patients with MDD who were recently prescribed antidepressant monotherapy were randomized to use a mobile app with usual care (20/40, 50%) or usual care alone (20/40, 50%). Patients in the app arm engaged with the app daily for 18 weeks; a report was generated at 6-week intervals and shared with the PCPs to facilitate shared treatment decision-making discussions. The patients discontinued the app at week 18 and were followed through year 1. Coprimary outcome measures, assessed via research visits, included change from baseline in the 13-item Patient Activation Measure (PAM-13) and 7-item Patient-Provider Engagement Scale scores at week 18. Additional outcome measures included depression severity (9-item Patient Health Questionnaire [PHQ-9]) and cognitive symptoms (5-item Perceived Deficits Questionnaire-Depression).

RESULTS

All 37 patients (app arm: n=18, 49%; usual care arm: n=19, 51%) who completed the 18-week follow-up period (n=31, 84% female, mean age 36, SD 11.3 years) had moderate to moderately severe depression. Improvements in PAM-13 and PHQ-9 scores were observed in both arms. Increases in PAM-13 scores from baseline to 18 weeks were numerically greater in the app arm than in the usual care arm (mean 10.5, SD 13.2 vs mean 8.8, SD 9.4; P=.65). At 52 weeks, differences in PAM-13 scores from baseline demonstrated significantly greater improvements in the app arm than in the usual care arm (mean 20.2, SD 17.7 vs mean 1.6, SD 14.2; P=.04). Compared with baseline, PHQ-9 scores decreased in both the app arm and the usual care arm at 18 weeks (mean 7.8, SD 7.2 vs mean 7.0, SD 6.5; P=.73) and 52 weeks (mean 9.5, SD 4.0 vs mean 4.7, SD 6.0; P=.07). Improvements in 7-item Patient-Provider Engagement Scale and WHO-5 scores were observed in both arms at 18 weeks and were sustained through 52 weeks in the app arm. Improvements in WHO-5 scores at 52 weeks were significantly greater in the app arm than in the usual care arm (41.5 vs 20.0; P=.02).

CONCLUSIONS

Patients with MDD will engage with a mobile app designed to track treatment and disease progression. PCPs will use the data generated as part of their assessment to inform clinical care. The study results suggest that an app-enabled clinical care pathway may enhance patient activation and benefit MDD management.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03242213; https://clinicaltrials.gov/ct2/show/NCT03242213.

Impact of the coronavirus disease 2019 pandemic on delivery of and models for supportive and palliative care for oncology patients

PURPOSE OF REVIEW

Supportive and palliative care services have been an important component of the overall COVID-19 pandemic response. However, significant changes in the provision and models of care were needed in order to optimize the care delivered to vulnerable cancer patients. This review discusses the evolution of palliative and supportive care service in response to the pandemic, and highlights remaining challenges.

RECENT FINDINGS

Direct competition for resources, as well as widespread implementation of safety measures resulted in major shifts in the mode of assessment and communication with cancer patients by supportive care teams. Telemedicine/virtual consultation and follow-up visits became an integral strategy, with high uptake and satisfaction amongst patients, families and providers. However, inequities in access to the required technologies were sometimes exposed. Hospice/palliative care unit (PCU) bed occupancy declined markedly because of restrictive visitation policies. Collection of patient-reported outcome (PRO) data was suspended in many cancer centers, with resulting under-recognition of anxiety and depression in ambulatory patients. As in many other areas, disparities in delivery of supportive and palliative care were magnified by the pandemic.

SUMMARY

Virtual care platforms have been widely adopted and will continue to be used to include a wider circle of family/friends and care providers in the provision of palliative and supportive care. To facilitate equitable delivery of supportive care within a pandemic, further research and resources are needed to train and support generalists and palliative care providers. Strategies to successfully collect PROs from all patients in a virtual manner must be developed and implemented.

Operationalizing Engagement With an Interpretation Bias Smartphone App Intervention: Case Series

BACKGROUND

Engagement with mental health smartphone apps is an understudied but critical construct to understand in the pursuit of improved efficacy.

OBJECTIVE

This study aimed to examine engagement as a multidimensional construct for a novel app called HabitWorks. HabitWorks delivers a personalized interpretation bias intervention and includes various strategies to enhance engagement such as human support, personalization, and self-monitoring.

METHODS

We examined app use in a pilot study (n=31) and identified 5 patterns of behavioral engagement: consistently low, drop-off, adherent, high diary, and superuser.

RESULTS

We present a series of cases (5/31, 16%) from this trial to illustrate the patterns of behavioral engagement and cognitive and affective engagement for each case. With rich participant-level data, we emphasize the diverse engagement patterns and the necessity of studying engagement as a heterogeneous and multifaceted construct.

CONCLUSIONS

Our thorough idiographic exploration of engagement with HabitWorks provides an example of how to operationalize engagement for other mental health apps.

Treatment of Mental Health in Patients With Chronic Liver Disease

Content available: Author Interview and Audio Recording.

Lessons Learned: Providing Supportive Accountability in an Online Anxiety Intervention

Technology-delivered interventions have the potential to help address the treatment gap in mental health care but are plagued by high attrition. Adding coaching, or minimal contact with a nonspecialist provider, may encourage engagement and decrease dropout, while remaining scalable. Coaching has been studied in interventions for various mental health conditions but has not yet been tested with anxious samples. This study describes the development of and reactions to a low-intensity coaching protocol administered to N = 282 anxious adults identified as high risk to drop out of a web-based cognitive bias modification for interpretation intervention. Undergraduate research assistants were trained as coaches and communicated with participants via phone calls and synchronous text messaging. About half of the sample never responded to coaches' attempts to schedule an initial phone call or did not answer the call, though about 30% completed the full intervention with their coach. Some anxious adults may choose technology-delivered interventions specifically for their lack of human contact and may fear talking to strangers on the phone; future recommendations include taking a more intensive user-centered design approach to creating and implementing a coaching protocol, allowing coaching support to be optional, and providing users with more information about how and why the intervention works.

Human Support in App-Based Cognitive Behavioral Therapies for Emotional Disorders: Scoping Review

BACKGROUND

Smartphone app-based therapies offer clear promise for reducing the gap in available mental health care for people at risk for or people with mental illness. To this end, as smartphone ownership has become widespread, app-based therapies have become increasingly common. However, the research on app-based therapies is lagging behind. In particular, although experts suggest that human support may be critical for increasing engagement and effectiveness, we have little systematic knowledge about the role that human support plays in app-based therapy. It is critical to address these open questions to optimally design and scale these interventions.

OBJECTIVE

The purpose of this study is to provide a scoping review of the use of human support or coaching in app-based cognitive behavioral therapy for emotional disorders, identify critical knowledge gaps, and offer recommendations for future research. Cognitive behavioral therapy is the most well-researched treatment for a wide range of concerns and is understood to be particularly well suited to digital implementations, given its structured, skill-based approach.

METHODS

We conducted systematic searches of 3 databases (PubMed, PsycINFO, and Embase). Broadly, eligible articles described a cognitive behavioral intervention delivered via smartphone app whose primary target was an emotional disorder or problem and included some level of human involvement or support (coaching). All records were reviewed by 2 authors. Information regarding the qualifications and training of coaches, stated purpose and content of the coaching, method and frequency of communication with users, and relationship between coaching and outcomes was recorded.

RESULTS

Of the 2940 titles returned by the searches, 64 (2.18%) were eligible for inclusion. This review found significant heterogeneity across all of the dimensions of coaching considered as well as considerable missing information in the published articles. Moreover, few studies had qualitatively or quantitatively evaluated how the level of coaching impacts treatment engagement or outcomes. Although users tend to self-report that coaching improves their engagement and outcomes, there is limited and mixed supporting quantitative evidence at present.

CONCLUSIONS

Digital mental health is a young but rapidly expanding field with great potential to improve the reach of evidence-based care. Researchers across the reviewed articles offered numerous approaches to encouraging and guiding users. However, with the relative infancy of these treatment approaches, this review found that the field has yet to develop standards or consensus for implementing coaching protocols, let alone those for measuring and reporting on the impact. We conclude that coaching remains a significant hole in the growing digital mental health literature and lay out recommendations for future data collection, reporting, experimentation, and analysis.

Current directions in digital interventions for mood and anxiety disorders

PURPOSE OF REVIEW

The purpose of this review is to provide an overview of the current scope of digital interventions for anxiety and mood disorders, with a focus on smartphone apps, for clinicians and mental healthcare providers.

RECENT FINDINGS

Of the 11 randomized controlled trials analyzed, 7 showed evidence that guided digital interventions (those supported by humans) were effective in improving anxiety and mood symptoms, and 3 showed evidence that unguided (those not supported by humans) interventions were effective. Psychoeducation was the most popular feature of both guided and unguided interventions. Attrition was highest (50%) in the unguided app-based intervention and lowest in the guided interventions. Many studies lacked active control groups and comparison was often made to a nondigital or waitlist control condition.

SUMMARY

Guided digital interventions continue to show promising results and can be used to enhance clinical care with minimal resources although more direct comparisons to existing treatments are necessary to understand their actual efficacy. Unguided self-help apps and chatbots remain promising, but more work is necessary to understand the real-world engagement and efficacy of these interventions.

Impact of Smartphone App-Based Psychological Interventions for Reducing Depressive Symptoms in People With Depression: Systematic Literature Review and Meta-analysis of Randomized Controlled Trials

Background

Depression is a serious, disabling mental disorder that severely affects quality of life. Patients with depression often do not receive adequate treatment. App-based psychotherapy is considered to have great potential to treat depression owing to its reach and easy accessibility.

Objective

We aim to analyze the impact of app-based psychological interventions for reducing depressive symptoms in people with depression.

Methods

We conducted a systematic literature review and meta-analysis. We searched Medline, Embase, PsycINFO, Web of Science, and Cochrane Central Register of Controlled Trials from inception to December 23, 2020. We selected randomized controlled trials to examine the impact of app-based psychological interventions for reducing depressive symptoms in people with depression. Study selection, data extraction, and critical appraisal (using the Cochrane Risk of Bias tool for randomized studies and the ROBINS-I tool for nonrandomized studies) were conducted independently by 2 reviewers. Where possible, we pooled data using random effects meta-analyses to obtain estimates of the effect size of the intervention. We conducted post hoc meta-regression analyses to explore the factors associated with intervention success.

Results

After screening 3468 unique references retrieved from bibliographic searches and assessing the eligibility of 79 full texts, we identified 12 trials (2859 participants) evaluating 14 different interventions. Of 14 trials, 7 (58%) were conducted in the United States; 3 (25%) trials, in Asia (Japan, South Korea, and China); 1 (8%) trial, in Australia; and 1 (8%) trial, in Germany. Of the 12 trials, 5 (42%) trials presented a low risk of bias. The mean duration of the interventions was 6.6 (SD 2.8) weeks. Two-thirds of the interventions were based on cognitive behavioral therapy alone or included it in combination with cognitive control therapy, positive psychology, brief behavioral activation, or mindfulness- and acceptance-based therapy. With no evidence of publication bias, a pooled analysis of 83% (10/12) of the trials and 86% (12/14) of the interventions showed that app-based interventions, compared with a control group receiving usual care or minimal intervention, produced a moderate reduction in depressive symptoms (standardized mean difference [SMD] −0.51, 95% CI −0.69 to −0.33; 2018/2859, 70.58% of the participants; I²=70%). Our meta-regression analyses indicated that there was a greater reduction in symptoms of depression (P=.04) in trials that included participants with moderate to severe depression (SMD −0.67, 95% CI −0.79 to −0.55), compared with trials with participants exhibiting mild to moderate depression (SMD −0.15, 95% CI −0.43 to −0.12).

Conclusions

App-based interventions targeted at people with depression produce moderate reductions in the symptoms of depression. More methodologically robust trials are needed to confirm our findings, determine which intervention features are associated with greater improvements, and identify those populations most likely to benefit from this type of intervention.

Trial Registration

PROSPERO CRD42019145689; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=145689

Innovative Use of a Mobile Web Application to Remotely Monitor Nonhospitalized Patients with COVID-19

Introduction: Most patients with COVID-19 do not require hospitalization but may need close monitoring, which can strain primary care practices. Our objective was to describe the implementation of a mobile web application to monitor COVID-19 signs and symptoms among nonhospitalized primary care patients and to assess the feasibility and acceptability of the application. Study Design: Retrospective analysis of (1) mobile web application data from March through December 2020 and (2) cross-sectional surveys administered in June 2020. Materials and Methods: We enrolled nonhospitalized patients and staff from nine New England primary care practices across 29 sites. Outcomes included feasibility and acceptability of the application as measured by the proportion of texts that resulted in a response, proportion of patients who agreed using the application was easy, and proportion of practice staff who agreed the application reduced outreach burden and that they would recommend use. Results: Five thousand five hundred thirty-two patients used the mobile web application, with 26,466 total responses. Overall, 78% of the daily texts resulted in a response from patients. Most patients agreed that responding to texts was easy (95%) and that they would be willing to participate in other texting programs (78%). Most staff agreed that the program reduced burden of outreach (94%) and that they would recommend use to other practices (100%). Conclusions: Use of a COVID-19 symptom tracking application was feasible and acceptable to patients and primary care practice staff. Outpatient practices should consider use of mobile web applications to monitor nonhospitalized patients with other acute illnesses.

Use of a Mobile Peer Support App Among Young People With Nonsuicidal Self-injury: Small-scale Randomized Controlled Trial

BACKGROUND

Nonsuicidal self-injury (NSSI) is a widespread behavior among adolescents and young adults. Although many individuals who self-injure do not seek treatment, there is evidence for web-based help-seeking through web-based communities and mobile peer support networks. However, few studies have rigorously tested the efficacy of such platforms on outcomes relevant for NSSI recovery.

OBJECTIVE

The aim of this small-scale preregistered randomized controlled trial is to provide preliminary insight into the shorter- and longer-term efficacy of the use of a peer support app, TalkLife, in reducing NSSI frequency and urges and increasing readiness to change. In addition, we explore contact with informal support, interest in therapy, and attitudes toward professional help-seeking.

METHODS

Individuals aged 16-25 years with current (within 3 months) and chronic (>6 episodes in the past year) NSSI history were eligible to participate in this study. After baseline assessments, the intervention group was instructed to use the app actively (eg, post or comment at least three times per week) and the control group received weekly psychoeducational materials through email, for 8 weeks. Follow-up was assessed at 1 month and 2 months. Linear mixed modeling was used to evaluate condition and time point effects for the primary outcomes of NSSI frequency and urges, readiness to change, contact with informal support, interest in therapy, and attitudes toward professional help-seeking.

RESULTS

A total of 131 participants were included in the analysis. We evidenced a significant effect of condition on NSSI frequency such that the participants using the peer support app self-injured less over the course of the study (mean 1.30, SE 0.18) than those in the control condition (mean 1.62, SE 0.18; P=.02; η2=0.02). We also evidenced a significant condition effect of readiness to change such that the treatment participants reported greater confidence in their ability to change their NSSI behavior (mean 6.28, SE 0.41) than the control participants (mean 5.67, SE 0.41; P=.04; η2=0.02). No significant differences were observed for contact with informal support, interest in therapy, or attitudes toward professional help-seeking.

CONCLUSIONS

Use of the peer support app was related to reduced NSSI frequency and greater confidence in one's ability to change NSSI behavior over the course of the study period, but no effects on NSSI urges, contact with informal support, interest in therapy, or attitudes toward professional help-seeking were observed. The findings provide preliminary support for considering the use of mobile peer support apps as a supplement to NSSI intervention and point to the need for larger-scale trials.

TRIAL REGISTRATION

Open Science Foundation; https://osf.io/3uay9.

Changes in healthcare costs following engagement with a virtual mental health system: a matched cohort study of healthcare claims data

The COVID-19 pandemic has exacerbated the pressing need for mental health services. Digital mental health interventions could increase access to care and be an effective approach to reducing anxiety and depression at scale; however, research on their impact on healthcare expenditure is in the nascent stage and requires further investigation. The current study used claims data to examine the associations between use of an on-demand digital mental health platform and healthcare utilization costs compared to a matched control cohort. The study found that there were no significant differences between cohorts in total healthcare costs and pharmacy costs. There was a 16.8% reduction in outpatient costs (p=.08). On-demand digital mental health interventions can serve as a scalable approach to addressing the current mental health demands and potentially lower outpatient costs.

Approaches for implementing digital interventions for alcohol use disorders in primary care: A qualitative, user-centered design study

Background

Digital interventions, such as smartphone apps, can be effective in treating alcohol use disorders (AUD). However, efforts to integrate digital interventions into primary care have been challenging. To inform successful implementation, we sought to understand how patients and clinicians preferred to use apps in routine primary care.

Methods

This study combined user-centered design and qualitative research methods, interviewing 18 primary care patients with AUD and nine primary care clinicians on topics such as prior experiences with digital tools, and design preferences regarding approaches for offering apps for AUD in primary care. Interviews were recorded and transcribed for template analysis whereby a priori codes were based on interview topics and refined through iterative coding. New codes and cross-cutting themes emerged from the data.

Results

Patient participants with AUD indicated they would be more likely to engage in treatment if primary care team members were involved in their use of apps. They also preferred to see clinicians “invested” and recommended that clinicians ask about app use and progress during follow-up appointments or check-ins. Clinician participants valued the opportunity to offer apps to their patients but noted that workflows would need to be tailored to individual patient needs. Time pressures, implementation complexity, and lack of appropriate staffing were cited as barriers. Clinicians proposed concrete solutions (e.g., education, tools, and staffing models) that could improve their ability to use apps within the constraints of primary care and suggested that some patients could potentially use apps without clinician support.

Conclusions

A user-centered approach to engaging patients in digital alcohol interventions in primary care may require personalized support for both initiation and follow-up. Meeting patients’ needs likely require increased staffing and efficient workflows in primary care. Health systems should consider offering multiple pathways for enrolling patients in apps to accommodate individual preferences and contextual barriers.

Plain Language Summary

Healthcare systems have begun using app-based treatments to help patients manage their health conditions, including alcohol use disorders. Some apps have been tested in research studies and appear to be effective. However, it is difficult for healthcare teams to offer apps to patients. Clinicians must engage in new activities that they have not done before, such as “teaching” patients to use apps and checking in on their use of the apps. Identifying how to use apps in routine healthcare is critical to their successful implementation. This study interviewed 27 people, including healthcare providers and patients in primary care, to uncover the most optimal ways to offer apps to patients with alcohol use disorders. The interviews combined the use of qualitative research methods and user-centered design. Results suggest that to use to address alcohol use disorders, primary care teams should be prepared to offer personalized support to patients. Both patient and clinician interviewees said that the steps required to use apps must be intuitive and simple. Patients could gain more benefits if clinicians introduced the apps and guided patients to use them, as opposed to making apps available for patients to download and use on their own. However, the exact approach to offering apps would depend on a given patient’s preferences and the extent that staffing was available in the clinic to support patients. Health systems should be prepared to offer and support patients in their use of apps, which should accommodate patient preferences and the constraints of the clinic.

Digitized thought records: a practitioner-focused review of cognitive restructuring apps

Mental health (MH) apps can be used as adjunctive tools in traditional face-to-face therapy to help implement components of evidence-based treatments. However, practitioners interested in using MH apps face a variety of challenges, including knowing which apps would be appropriate to use. Although some resources are available to help practitioners identify apps, granular analyses of how faithfully specific clinical skills are represented in apps are lacking. This study aimed to conduct a review and analysis of MH apps containing a core component of cognitive behaviour therapy (CBT) – cognitive restructuring (CR). A keyword search for apps providing CR functionality on the Apple App and Android Google Play stores yielded 246 apps after removal of duplicates, which was further reduced to 15 apps following verification of a CR component and application of other inclusionary/exclusionary criteria. Apps were coded based on their inclusion of core elements of CR, and general app features including app content, interoperability/data sharing, professional involvement, ethics, and data safeguards. They were also rated on user experience as assessed by the Mobile App Rating Scale (MARS). Whereas a majority of the CR apps include most core CR elements, they vary considerably with respect to more granular sub-elements of CR (e.g. rating the intensity of emotions), other general app features, and user experience (average MARS = 3.53, range from 2.30 to 4.58). Specific apps that fared best with respect to CR fidelity and user experience dimensions are highlighted, and implications of findings for clinicians, researchers and app developers are discussed.

Key learning aims

(1)

Centering Lived Experience in Developing Digital Interventions for Suicide and Self-injurious Behaviors: User-Centered Design Approach

BACKGROUND

The prevalence of self-injurious thoughts and behaviors (SITB) signals a growing public health crisis. Despite a recognized need for improved and scalable interventions, the field of SITB intervention faces several challenges: existing interventions are often time and resource intensive, most individuals with SITB do not seek formal mental health care, and efficacious treatments are characterized by small effects. Combined, these challenges indicate a need for improved SITB interventions for individuals in formal treatment and those who are not treatment engaged but are at high risk of worsening mental health and future suicide attempts.

OBJECTIVE

We present a methodological approach and set of techniques that may address these challenges by centering the lived experience of individuals with SITB in the process of developing needed services: user-centered design (UCD).

METHODS

We highlight the value of UCD in the context of digital interventions for SITB by describing the UCD approach and explicating how it can be leveraged to include lived experience throughout the development and evaluation process. We provide a detailed case example highlighting 3 phases of the early development process that can be used to design an intervention that is engaging and meets end-user needs. In addition, we point to novel applications of UCD to complement new directions in SITB research.

RESULTS

In this paper, we offer a 2-pronged approach to meet these challenges. First, in terms of addressing access to effective interventions, digital interventions hold promise to extend the reach of evidence-based treatments outside of brick-and-mortar health care settings. Second, to address challenges related to treatment targets and engagement, we propose involving individuals with lived experience in the design and research process.

CONCLUSIONS

UCD offers a well-developed and systematic process to center the unique needs, preferences, and perceived barriers of individuals with lived SITB experience in the development and evaluation of digital interventions.

Uptake and effectiveness of a self-guided mobile app platform for college student mental health

BACKGROUND

College students endorse high rates of mental health problems. While many colleges offer on-campus services, many students who could benefit from mental health services do not receive care. Indeed, nearly half of students who screen positive for depression, for example, do not receive treatment. Digital mental health programs, such as those delivered via mobile apps, may help expand access to mental health care and resources. This mixed-methods study aims to examine the uptake and effectiveness of an implementation of IntelliCare for College Students, a self-guided app-based mental health platform, on two university campuses.

METHODS

Data on counseling center utilization was collected prior to the implementation of the app (pre-implementation phase) and while the app was available on campus (implementation phase). Data on app usage was collected throughout the implementation phase. A subset of participants (n = 20), along with counseling center staff members (n = 10), completed feedback interviews.

RESULTS

Overall, uptake of the app platform was low. A total of 117 participants downloaded the app and registered their study ID during the implementation phase. Approximately 24% (28/117) of participants used the app only once. The number of days between the first and last day of app use ranged from 0 to 299, with a mean of 35.01 days and a median of 14 days. A relatively small portion of the sample (26.5%; 31/117) downloaded one or more of the IntelliCare interactive apps. In examining counseling center utilization, there were no significant changes in intake appointments, individual therapy sessions, or crisis appointments observed from the pre-implementation phase to the implementation phase of the study. Feedback interviews highlighted the significant level of disruption caused by the COVID-19 pandemic and shift to remote learning, including challenges disseminating information to students and a preference to spend less time with digital devices outside of class time.

CONCLUSIONS

Findings from this study indicate that there is an ongoing need to identify ways to reach college students and support student mental health and wellness for the remainder of the COVID-19 pandemic and beyond.