Smartphone apps for depression and anxiety: a systematic review and meta-analysis of techniques to increase engagement

How Digital Solutions Might Provide a World of New Opportunities for Holistic and Empathic Support of Patients with Hidradenitis Suppurativa

Hidradenitis suppurativa (HS) is a complex chronic relapsing inflammatory condition anchored in the hair follicle wherein painful abscesses, nodules, and tunnels form under the skin with the potential for intermittent pus drainage and tissue scarring. Current estimates of incidence are 1-4% globally with the disease three times more prevalent in women and higher rates among Black populations. Patients with HS are also more likely to suffer from depression, anxiety, and loneliness underscoring the need for carefully approached strategies on disease awareness and interventions. Delays in formal diagnosis, which have been estimated at 7-10 years on average, impede timely provision of optimal care. Despite best intent, when patients present at a physician's office, stigmas relating to physical appearance can be exacerbated by negative interactions experienced by patients. In addition to long wait times and the dearth of available HS expert dermatology professionals, patients perceive heightened physician focus on two of the HS flare risk factors (smoking and body mass index [BMI]) as negatively impacting their care. Given the need for continual, personal, and sensitive patient support, herein we advocate for re-examination of approach to care and the leveraging of highly personalized digital support solutions. New medications which can directly or indirectly control elements of the disease and its comorbidities are also entering the marketplace. Collectively, we posit that these new developments provide opportunity for a holistic approach for patients with HS, leading to long-term engagement and improved outcomes.

Preliminary Effectiveness of a Therapist-Supported Digital Mental Health Intervention in Reducing Suicidal Ideation

Suicidal ideation (SI) is a significant public health concern with increasing prevalence. Therapist-supported digital mental health interventions (DMHI) are an emergent modality to address common mental health problems like depression and anxiety, although less is known about SI. This study examined SI trajectories among 778 patients who participated in a therapist-supported DMHI using multilevel models during and up to 6-months post-treatment. Estimates of associated suicide attempts and deaths by suicide were calculated using published data linking PHQ-9-assessed SI to records of suicide attempts and deaths by suicide. The proportion of participants reporting no SI significantly increased between baseline and end-of-treatment (78.02% to 91.00%). Effect sizes of SI changes between baseline and end-of-treatment, 3-month, and 6-month follow-ups were 0.33 (95%CI = 0.27-0.38), 0.32 (95%CI = 0.27-0.38), and 0.32 (95%CI = 0.27-0.38), respectively. Results also indicated an estimated 30.49% reduction (95%CI = 25.15%-35.13%) in suicide attempts and death by suicide across treatment. This study provides preliminary evidence of the effectiveness of a therapist-supported DMHI in reducing SI.

Parents' Perceptions of Their Parenting Journeys and a Mobile App Intervention (Parentbot-A Digital Healthcare Assistant): Qualitative Process Evaluation

BACKGROUND

Parents experience many challenges during the perinatal period. Mobile app-based interventions and chatbots show promise in delivering health care support for parents during the perinatal period.

OBJECTIVE

This descriptive qualitative process evaluation study aims to explore the perinatal experiences of parents in Singapore, as well as examine the user experiences of the mobile app-based intervention with an in-built chatbot titled Parentbot-a Digital Healthcare Assistant (PDA).

METHODS

A total of 20 heterosexual English-speaking parents were recruited via purposive sampling from a single tertiary hospital in Singapore. The parents (control group: 10/20, 50%; intervention group: 10/20, 50%) were also part of an ongoing randomized trial between November 2022 and August 2023 that aimed to evaluate the effectiveness of the PDA in improving parenting outcomes. Semistructured one-to-one interviews were conducted via Zoom from February to June 2023. All interviews were conducted in English, audio recorded, and transcribed verbatim. Data analysis was guided by the thematic analysis framework. The COREQ (Consolidated Criteria for Reporting Qualitative Research) checklist was used to guide the reporting of data.

RESULTS

Three themes with 10 subthemes describing parents' perceptions of their parenting journeys and their experiences with the PDA were identified. The main themes were (1) new babies, new troubles, and new wonders; (2) support system for the parents; and (3) reshaping perinatal support for future parents.

CONCLUSIONS

Overall, the PDA provided parents with informational, socioemotional, and psychological support and could be used to supplement the perinatal care provided for future parents. To optimize users' experience with the PDA, the intervention could be equipped with a more sophisticated chatbot, equipped with more gamification features, and programmed to deliver personalized care to parents. Researchers and health care providers could also strive to promote more peer-to-peer interactions among users. The provision of continuous, holistic, and family-centered care by health care professionals could also be emphasized. Moreover, policy changes regarding maternity and paternity leaves, availability of infant care centers, and flexible work arrangements could be further explored to promote healthy work-family balance for parents.

Working mechanisms of the use and acceptability of ecological momentary interventions: a realist evaluation of a guided self-help ecological momentary intervention targeting self-esteem

BACKGROUND

Technology improves accessibility of psychological interventions for youth. An ecological momentary intervention (EMI) is a digital intervention geared toward intervening in daily life to enhance the generalizability and ecological validity, and to be able to intervene in moments most needed. Identifying working mechanisms of the use of ecological momentary interventions might generate insights to improve interventions.

METHODS

The present study investigates the working mechanisms of the use and acceptability of an ecological momentary intervention, named SELFIE, targeting self-esteem in youth exposed to childhood trauma, and evaluates under what circumstances these mechanisms of use and acceptability do or do not come into play. A realist evaluation approach was used for developing initial program theories (data: expert interviews and a stakeholders focus group), and subsequently testing (data: 15 interviews with participants, a focus group with therapists, debriefing questionnaire), and refining them.

RESULTS

The SELFIE intervention is offered through a smartphone application enabling constant availability of the intervention and thereby increasing accessibility and feasibility. When the intervention was offered on their personal smartphone, this enhanced a sense of privacy and less hesitance in engaging with the app, leading to increased disclosure and active participation. Further, the smartphone application facilitates the practice of skills in daily life, supporting the repeated practice of exercises in different situations leading to the generalizability of the effect. Buffering against technical malfunction seemed important to decrease its possible negative effects.

CONCLUSIONS

This study enhanced our understanding of possible working mechanisms in EMIs, such as the constant availability supporting increased accessibility and feasibility, for which the use of the personal smartphone was experienced as a facilitating context. Hereby, the current study contributes to relatively limited research in this field. For the field to move forward, mechanisms of use, and acceptability of EMIs need to be understood. It is strongly recommended that alongside efficacy trials of an EMI on specific target mechanisms, a process evaluation is conducted investigating the working mechanisms of use.

TRIAL REGISTRATION

The current paper reports on a realist evaluation within the SELFIE trial (Netherlands Trial Register NL7129 (NTR7475)).

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.

Long-Term Emotional Impact of the COVID-19 Pandemic and Barriers and Facilitators to Digital Mental Health Tools in Long-Term Care Workers: Qualitative Study

BACKGROUND

The overall pandemic created enormous pressure on long-term care workers (LTCWs), making them particularly vulnerable to mental disorders. Despite this, most of the available evidence on professional well-being during COVID-19 has exclusively focused on frontline health care workers.

OBJECTIVE

This study aimed to identify the long-term psychological needs of LTCWs derived from the COVID-19 pandemic and to explore barriers and facilitators related to digital mental health tools. This is part of a project that seeks to develop a digital mental health intervention to reduce psychological distress in this population group.

METHODS

We performed a qualitative study with a rapid research approach. Participants were LTCWs of the autonomous community of Catalonia. We conducted 30 semistructured interviews between April and September 2022. We used a qualitative content analysis method with an inductive-deductive approach.

RESULTS

The period of the pandemic with the highest mental health burden was the COVID-19 outbreak, with almost all workers having experienced some form of emotional distress. Emotional distress persisted over time in more than half of the participants, with fatigue and nervousness being the main emotions expressed at the time of the interview. High workload, the feeling that pandemic times are not over, and poor working conditions that have remained since then have been the most frequently expressed determinants of such emotions. Potential barriers and facilitators to engagement with digital tools were also identified in terms of previous experience and beliefs of the target population, possibilities for the integration of a digital tool into daily life, preferences regarding the level of guidance, the possibility of social connectedness through the tool, and privacy and confidentiality. The identified factors may become especially relevant in the context of the pandemic remission phase.

CONCLUSIONS

More than 2 years after the pandemic outbreak, emotional distress is still relevant. The persistent burden of psychological distress points to a need for institutions to take action to improve working conditions and promote employees' well-being. Considering factors that act as barriers and facilitators for the use of digital mental health tools, it is important to develop tailored tools that could offer valuable support to this population during and after a pandemic.

Investigating mobile persuasive design for mental wellness: A cross-domain analysis

BACKGROUND

Global mental health issues have increased the demand for digital mental health support. Mobile apps with persuasive technology play a vital role in enhancing mental well-being.

OBJECTIVE

Analysing and Comparing persuasive intervention design across various app categories, this study aims to inspire innovative design approaches for improving the persuasiveness of mental wellness apps during their development.

METHODS

We retrieved a total of 100 mobile apps from five distinct categories (20 for each): Mental wellness, Social media, Entertainment, Fitness & Physical health and News & Information from Apple Store and Google Play. Two researchers examined and coded the apps to identify the persuasive features employed within each category using the Persuasive Systems Design (PSD) Framework, while a third researcher participated in discussions to resolve discrepancies. Kendall's Rank Correlation Coefficient was performed to determine the relationship between persuasive features and effectiveness.

RESULTS

Trustworthiness (n = 81), Liking (n = 78), Surface credibility (n = 71), Reminders (n = 63), and Reduction (n = 57) were the most widely implemented persuasive features. Dialogue support and system credibility support features were heavily used across different app types, while social support features were less commonly employed, particularly in mental health apps. A positive correlation was found between Surface credibility, Trustworthiness, Liking, Reminders, Self-monitoring, Expertise features and apps' effectiveness.

CONCLUSION

Through a cross-domain analysis using the PSD framework to investigate persuasive feature implementations, the findings from this study offer design suggestions to create innovative and effective mobile apps promoting mental well-being.

Evaluation of the internet-based intervention "Selfapy" in participants with unipolar depression and the impact on quality of life: a randomized, parallel group study

PURPOSE

Depressive disorders cause a major burden of disease worldwide and often lead to a loss of social functioning. Patients suffering from depressive disorders report a lower quality of life (QOL) than people without a history of mental health issues. Internet-based interventions (IBIs) based on cognitive behavioral therapy (CBT) are effective in reducing symptom severity but data on their impact on quality of life in clinically depressed patients so far is scarce.

METHODS

Selfapy is a CBT-based IBI for depressive disorders. 401 participants (332 female, mean age 37 (SD = 11) with a diagnosis of major depressive disorder (MDD) or dysthymia were enrolled in a randomized, parallel, three-arm trial comparing a therapist-guided Selfapy intervention with an unguided Selfapy intervention and a waiting list control. QOL was measured using the WHOQOL-BREF at baseline, post-treatment (12 weeks) and at 24-week follow-up. The effects of the interventions on QOL were calculated using linear mixed effects models.

RESULTS

At post-treatment (12 weeks) the guided and unguided intervention groups reported an increase in QOL on physical and psychological health domains compared to controls (significant group*time interaction). The gain in QOL was maintained over the follow-up period only for psychological health. QOL decreased in the social relationships and environment domains over the course of treatment and during the follow-up treatment for all participants. There were no differences between the guided and the unguided intervention.

CONCLUSION

Selfapy proved to positively affect psychological and physical QOL in a sample of participants suffering from depressive disorders and can therefore be considered an effective and highly scalable therapeutic tool. The pattern of results might partly be attributable to effects of the COVID-19 pandemic and public health measures that coincided with the trial.

TRIAL REGISTRATION

German Clinical Trials Register (DRKS): DRKS00017191. Registered June 14th, 2019, https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00017191 .

Symptom Reduction and Engagement in a Cognitive-Behavioral Mobile Phone App: A Study of User Profiling to Determine Prognostic Indicators

OBJECTIVE

We investigated the presence of latent transition profiles in a sample of users of a cognitive-behavioral mental health app for the general population. Users' baseline characteristics were used as predictors of the profiles. The role of engagement with the app in the transition profiles was examined.

METHOD

A total of 541 users completed the Patient Health Questionnaire-9 and the General Anxiety Disorder-7 when started using the app and 30 days after. Random-Intercept Latent Transition Analysis was implemented to identify users' profiles and transition patterns as classes. The age of the users and the Emotional Self-Awareness Scale-Revised (ESAS-R) were used as predictors of class membership at baseline. The Homework Rating Scale-Mobile Application (HRS-MA; as a measure of engagement) was used as a predictor of class membership at 30 days of app use.

RESULTS

A 3-class solution was obtained according to the severity of symptoms (from mild to moderately severe). Age and ESAS-R predicted class membership initially; the higher the age and ESAS-R, the higher the probability of starting using the app with lower distress levels. The HRS-MA predicted class membership at 30 days of app use; the higher the engagement for more symptomatic and younger users, the higher the probability of improvement. However, older users tended to engage less.

CONCLUSION

Our findings underpin the relevance of easily accessible digital interventions for young adults with mild to moderate mental health problems. Further studies and developments are required to enhance these apps for older cohorts.

Preliminary Efficacy of a Digital Intervention for Adolescent Depression: Randomized Controlled Trial

BACKGROUND

Adolescent depression is a significant public health concern; however, access to effective mental health care is limited. Digital therapeutics (DTx) can improve access to evidence-based interventions; however, their efficacy in adolescents is sparsely documented.

OBJECTIVE

This study aims to examine the efficacy of a mobile app DTx versus an active control as an adjunct treatment for adolescent depression symptoms.

METHODS

An internet-based open-label randomized control trial was conducted nationwide with a partial crossover design, and 168 adolescents aged 13 to 21 years with symptoms of depression were recruited between November 2020 and September 2021. Participants were randomized (1:1) to the cognitive behavioral therapy-based treatment app (Spark) or to a psychoeducational control app (control), which they would use for a duration of 5 weeks. The primary outcome was a between-group (Spark vs control) difference in the change in depression symptoms from baseline to postintervention, as measured by the Patient Health Questionnaire-8 (PHQ-8) using a linear mixed-effects analysis. The PHQ-8 ranges from 0 to 24, with scores of 5 to 9 indicating mild depression symptoms, scores of 10 to 14 indicating moderate symptoms, scores of 15 to 19 indicating moderately severe symptoms, and scores of 20 to 24 indicating severe symptoms. A minimal clinically important difference (5-point reduction between baseline and postintervention) in the Spark arm and group differences in remission and treatment response rates based on the PHQ-8 at postintervention were also investigated.

RESULTS

A total of 160 participants were randomized, 80 in the Spark arm (mean age 16.89, SD 2.5 y) and 80 in the control arm (mean age 16.79, SD 2.59 y). Data from 121 participants (Spark: n=63; control: n=58) with moderate to severe (PHQ-8≥10) symptoms at baseline were included in the primary analyses following a modified intention-to-treat principle. A linear mixed-effect analysis revealed a nonsignificant difference between the study arms in depression symptom change over the intervention period. The Spark arm met a minimal clinically important difference threshold (mean -5.08, 95% CI -6.72 to -3.42). The remission rate in the Spark arm was significantly higher than that in the control arm (11/63, 17% vs 2/58, 3%; χ21=6.2; P=.01; false discovery rate-adjusted P=.03). The treatment response rates were not significantly different between the study arms (P=.07; false discovery rate-adjusted P=.16). Post hoc analyses including participants with mild to severe (PHQ-8 score ≥5) symptoms at baseline revealed promising evidence that Spark is effective in those with mild to severe symptoms.

CONCLUSIONS

There is initial evidence that a self-guided, cognitive behavioral therapy-based DTx intervention may effectively treat mild to severe depression symptoms in adolescents. DTx may improve access to mental health care for adolescents or serve as an important adjunct to the standard of care.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04524598; https://clinicaltrials.gov/study/NCT04524598.

Digitally managing depression: A fully remote randomised attention-placebo controlled trial

Background

Depression is a common and disabling condition. Digital apps may augment or facilitate care, particularly in under-served populations. We tested the efficacy of juli, a digital self-management app for depression in a fully remote randomised controlled trial.

Methods

A pragmatic randomised controlled trial that included participants aged > 18 who self-identified as having depression and scored > 5 on the Patient Health Questionnaire-8. Participants were randomly assigned (1:1) to receive juli for 8 weeks or a limited attention-placebo control app. Our primary outcome was the difference in Patient Health Questionnaire-8 scores at 8 weeks. Secondary outcomes were remission, minimal clinically important difference, worsening of depression, and health-related quality of life. Analyses were per-protocol (primary), and modified and full intention-to-treat (secondary). The trial was registered at ISRCTN (ISRCTN12329547).

Results

Between May 2021 and January 2023, we randomised 908 participants. 662 completed the week 2 outcome assessment and were included in the modified intention-to-treat analysis, and 456 completed the week 8 outcome assessments (per-protocol). In the per-protocol analysis, the juli group had a greater reduction in Patient Health Questionnaire-8 score (10.78, standard deviation 6.26) than the control group (11.88, standard deviation 5.73) by week 8 (baseline adjusted β-coefficient -0.94, 95% CI: -1.87 to -0.22, p = 0.045). Achieving remission and a minimal clinically important difference was more likely in the juli group at 8 weeks (adjusted odds ratios 2.22, 95% CI: 1.45-3.39, p < 0.001 and 1.56, 95% CI: 1.08-2.27, p = 0.018, respectively). There were no between-group differences in health-related quality of life or worsening of depression. Modified and full intention-to-treat analyses found similar results, but the primary outcome was non-significant.

Conclusion

The use of juli for 8 weeks resulted in a small reduction in symptoms of depression compared with an attention-placebo control. The juli app is a digital self-management tool that could increase the accessibility of evidence-based depression treatments.

Burst versus continuous delivery design in digital mental health interventions: Evidence from a randomized clinical trial

Objective

Digital mental health interventions delivered via smartphone-based apps effectively treat various conditions; however, optimizing their efficacy while minimizing participant burden remains a key challenge. In this study, we investigated the potential benefits of a burst delivery design (i.e. interventions delivered only in pre-defined time intervals) in comparison to the continuous delivery of interventions.

Methods

We randomly assigned 93 participants to the continuous delivery (CD) or burst delivery (BD) group. The CD group engaged in ReApp, a mobile app that increases positive cognitive reappraisal with a consistent delivery schedule that provides five prompts per day throughout the 3-week-long study, while the BD group received five daily prompts only in the first and third weeks of the study.

Results

No significant differences were found between the groups in terms of adherence, mental health outcomes (specifically depressive and anxiety symptoms), level of perceived stress, and perceived helpfulness of intervention. The BD group showed a significantly decreased perceived difficulty of intervention over time.

Conclusions

The results suggest that the burst delivery may be as suitable for digital mental health interventions as the continuous delivery. The perceived difficulty of the intervention declined more steeply for the BD group, indicating that it improved the feasibility of the positive cognitive reappraisal intervention without hurting its efficacy. This outcome may inform the design of less burdensome interventions with improved outcomes in future research.

Internet-delivered psychological interventions for older adults with depression: A scoping review

BACKGROUND

Depression is prevalent among older adults, and internet-delivered psychological interventions (IDPIs) have emerged as a promising solution.

AIM

To explore the landscape of IDPIs for late-life depression, examining current characteristics, psychotherapies, intervention strategies, facilitators, and barriers.

METHOD

Guided by a PRISMA-guided scoping review, we systematically searched five electronic databases.

RESULTS

25 relevant studies were identified. IDPIs were used for treatment, prevention, and assessment. Internet-based cognitive behavioral therapy was the most common psychotherapy. Seven strategies to provide tailored services include psychotherapy courses, professional involvement, mood and progress tracking, virtual community, timed reminders, additional learning resources, and gamification elements. Barriers contained cognitive impairment, low digital literacy, device inaccessibility, limited depression awareness, adherence issues, and acclimation time, while facilitators included prior treatment experience, real-life character stories, strong client-worker bonds, and integration into daily care routines.

CONCLUSION

IDPIs present an accessible and convenient avenue for older adults. Future directions suggest exploring minimalist interventions, diverse strategies, and optimized implementation to amplify IDPIs impact among this vulnerable group.

Digitalising mental health care: Practical recommendations from the European Psychiatric Association

The digitalisation of mental health care is expected to improve the accessibility and quality of specialised treatment services and introduce innovative methods to study, assess, and monitor mental health disorders. In this narrative review and practical recommendation of the European Psychiatric Association (EPA), we aim to help healthcare providers and policymakers to navigate this rapidly evolving field. We provide an overview of the current scientific and implementation status across two major domains of digitalisation: i) digital mental health interventions and ii) digital phenotyping, discuss the potential of each domain to improve the accessibility and outcomes of mental health services, and highlight current challenges faced by researchers, clinicians, and service users. Furthermore, we make several recommendations meant to foster the widespread adoption of evidence-based digital solutions for mental health care in the member states of the EPA. To realise the vision of a digitalised, patient-centred, and data-driven mental health ecosystem, a number of implementation challenges must be considered and addressed, spanning from human, technical, ethical-legal, and economic barriers. The list of priority areas and action points our expert panel has identified could serve as a playbook for this process.

An intervention to promote concrete thinking style in young adults: Effects on depressive symptoms and its protective factors

BACKGROUND AND OBJECTIVES

Individuals with low concreteness-experiential thought (CET) tend to have exacerbated depressive symptoms. Interventions aimed at increasing CET have been shown to influence depressive symptoms. The present study examined the effects of increasing CET on depressive symptoms and its protective factors.

METHODS

A two-armed experimental intervention was conducted with 86 healthy university students in Japan. They were randomly allocated to the intervention and waitlist groups. Participants in the intervention group engaged in an unguided and web-based (UW) intervention to increase CET (UW-CET). This intervention included a one-off session, to explain the rationale behind increasing CET via a psychoeducation video, and a five-session training on CET over a week. We assessed depressive symptoms, thought styles, and protective factors, such as mindfulness and goal striving, both pre- and-post-assessment and at the one-month follow-up.

RESULTS

Participants in the intervention group had marginally increased CET in the follow-up assessments; however, participants in the waitlist group did not. Furthermore, participants in the intervention showed marginally increased mindfulness tendencies and strivings toward their personal goals, but their depressive symptoms were not affected.

LIMITATIONS

The present study did not include any active control conditions. Additionally, the sample consisted of only healthy university students.

CONCLUSIONS

The findings suggest that the UW-CET can marginally increase adaptive thinking, such as CET, and promote positive psychological aspects in healthy young adults; however, the effect is small. The findings may also help expand clinical implementations to prevent depression in young adults.

Empowerment Enabled by Information and Communications Technology and Intention to Sustain a Healthy Behavior: Survey of General Users

BACKGROUND

Most people with chronic conditions fail to adhere to self-management behavioral guidelines. In the last 2 decades, several mobile health apps and IT-based systems have been designed and developed to help patients change and sustain their healthy behaviors. However, these systems often lead to short-term behavior change or adherence while the goal is to engage the population toward long-term behavior change.

OBJECTIVE

This study aims to contribute to the development of long-term health behavior changes or to help people sustain their healthy behavior. For this purpose, we built and tested a theoretical model that includes enablers of empowerment and an intention to sustain a healthy behavior when patients are assisted by information and communications technology.

METHODS

Structural equation modeling was used to analyze 427 survey returns collected from a diverse population of participants and patients. Notably, the model testing was performed for physical activity as a generally desirable healthy goal.

RESULTS

Message aligned with personal goals, familiarity with technology tools, high self-efficacy, social connection, and community support played a significant role (P<.001) in empowering individuals to maintain a healthy behavior. The feeling of being empowered exhibited a strong influence, with a path coefficient of 0.681 on an intention to sustain healthy behavior.

CONCLUSIONS

The uniqueness of this model is its recognition of needs (ie, social connection, community support, and self-efficacy) to sustain a healthy behavior. Individuals are empowered when they are assisted by family and community, specifically when they possess the knowledge, skills, and self-awareness to ascertain and achieve their goals. This nascent theory explains what might lead to more sustainable behavior change and is meant to help designers build better apps that enable people to conduct self-care routines and sustain their behavior.

App-Based Interventions for Moderate to Severe Depression: A Systematic Review and Meta-Analysis

Importance

Mobile mental health applications (apps) for moderate to severe depression are proliferating, likely owing to their capacity to overcome the limitations of conventional psychotherapy, but research on the potential moderators of treatment efficacy is lacking.

Objective

To examine the treatment efficacy associated with mobile app interventions for moderate to severe depression and identify the potential moderators associated with better treatment outcomes.

Data Sources

PubMed, Embase, and PsycINFO were searched from their inception to January 22, 2023.

Study Selection

Only randomized clinical trials evaluating mobile app treatments in adults with moderate to severe depression that published their results in English were included in the analysis.

Data Extraction and Synthesis

Three independent researchers extracted and assessed relevant studies, their risk of bias, the characteristics of the population and study design, and the components of the intervention program following the Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guidelines. A fixed-effects model was used for data analysis, and exploratory post hoc meta-regression and subgroup analyses were also conducted. Data were analyzed from February 16 to March 25, 2023.

Main Outcomes and Measures

The main outcome was changes in depression symptom severity from before to after treatment, measured by standardized depression assessment instruments. Secondary outcomes included study-, intervention-, and patient-level factors associated with app efficacy.

Results

Of 2128 studies identified, 13 studies evaluating 16 intervention apps with 1470 participants with moderate to severe depression were included in the analysis. The overall pooled effect size of mobile app interventions vs both active and inactive control groups was 0.50 (95% CI, 0.40 to 0.61). Interventions with in-app notifications were associated with significantly lower treatment outcomes (standardized mean difference [SMD], 0.45; 95% CI, 0.29-0.60) than interventions without (SMD, 0.71; 95% CI, 0.54-0.87; P = .02). In addition, app interventions delivered for less than 8 weeks were associated with a significantly greater effect size (SMD, 0.77; 95% CI, 0.59-0.96) than interventions delivered for 8 weeks or longer (SMD, 0.43; 95% CI, 0.30-0.57; P = .004).

Conclusions and Relevance

In this systematic review and meta-analysis, the feasibility and efficacy of mobile app interventions were supported in treating moderate and severe depression, and practical implications were also provided for developing effective app-based interventions in clinical practice.

Challenges With the Use of Digital Sham: Systematic Review and Recommendations

BACKGROUND

Digital therapeutics (DTx) are software-based products that prevent, manage, or treat a medical condition and are delivered through a smartphone app, web application, or wearable device. Clinical trials assessing DTx pose challenges, foremost among which is designing appropriate digital shams (or digital placebos), which should ideally mimic DTx (in terms of design, components, and duration of treatment) while omitting the active principle or component.

OBJECTIVE

The objective of our review was to understand how digital shams are being used in clinical research on DTx in neuroscience, which is the most common therapy area for DTx.

METHODS

We conducted a systematic literature review of DTx in neuroscience (including neurodevelopmental, neurodegenerative, and psychiatric disorders) with a focus on controlled clinical trials involving digital shams. Studies were identified from trial registries (ClinicalTrials.gov, the European Union Clinical Trials Register, and Trial Trove) and through structured searches in MEDLINE and Embase (both via the Embase website) and were limited to articles in English published from 2010 onward. These were supplemented by keyword-based searches in PubMed, Google, and Google Scholar and bibliographic searches. Studies assessing DTx in neuroscience (including neurodevelopmental, neurodegenerative, and psychiatric disorders) were included. Details related to the publication, DTx, comparator, patient population, and outcomes were extracted and analyzed.

RESULTS

Our search criteria identified 461 neuroscience studies involving 213 unique DTx. Most DTx were extended reality based (86/213, 40.4%) or mobile device based (56/213, 26.3%); 313 were comparative, of which 68 (21.7%) used shams. The most common therapeutic areas assessed in these studies were stroke (42/213, 19.7%), depression (32/213, 15%), and anxiety (24/213, 11.3%). The most common treatments were cognitive behavioral therapy or behavioral therapy (67/213, 32.4%), physical rehabilitation (60/213, 28.2%), and cognitive training (41/213, 19.2%). We identified the following important issues related to the use of digital shams in neuroscience: shams were not validated before use in studies, they varied widely in design (from being nearly identical to the DTx to using different software programs altogether), and the level of patient engagement or satisfaction with the sham and the impact of the sham on study outcomes were infrequently reported.

CONCLUSIONS

Digital shams are critical for the clinical development of DTx in neuroscience. Given the importance of sham controls in evaluating DTx efficacy, we provide recommendations on the key information that should be reported in a well-designed DTx trial and propose an algorithm to allow the correct interpretation of DTx study results. Sham-controlled studies should be routinely used in DTx trials-in early-phase studies-to help identify DTx active components and-in late-phase studies-to confirm the efficacy of DTx. The use of shams early in development will ensure that the appropriate sham control is used in later confirmatory trials.

Mental Health Self-Tracking Preferences of Young Adults With Depression and Anxiety Not Engaged in Treatment: Qualitative Analysis

BACKGROUND

Despite the high prevalence of anxiety and depression among young adults, many do not seek formal treatment. Some may turn to digital mental health tools for support instead, including to self-track moods, behaviors, and other variables related to mental health. Researchers have sought to understand processes and motivations involved in self-tracking, but few have considered the specific needs and preferences of young adults who are not engaged in treatment and who seek to use self-tracking to support mental health.

OBJECTIVE

This study seeks to assess the types of experiences young adults not engaged in treatment have had with digital self-tracking for mood and other mental health data and to assess how young adults not seeking treatment want to engage in self-tracking to support their mental health.

METHODS

We conducted 2 online asynchronous discussion groups with 50 young adults aged 18 years to 25 years who were not engaged in treatment. Participants were recruited after indicating moderate to severe symptoms of depression or anxiety on screening surveys hosted on the website of Mental Health America. Participants who enrolled in the study responded anonymously to discussion prompts on a message board, as well as to each other's responses, and 3 coders performed a thematic analysis of their responses.

RESULTS

Participants had mixed experiences with self-tracking in the past, including disliking when tracking highlighted unwanted behaviors and discontinuing tracking for a variety of reasons. They had more positive past experiences tracking behaviors and tasks they wanted to increase, using open-ended journaling, and with gamified elements to increase motivation. Participants highlighted several design considerations they wanted self-tracking tools to address, including building self-understanding; organization, reminders, and structure; and simplifying the self-tracking experience. Participants wanted self-tracking to help them identify their feelings and how their feelings related to other variables like sleep, exercise, and events in their lives. Participants also highlighted self-tracking as useful for motivating and supporting basic activities and tasks of daily living during periods of feeling overwhelmed or low mood and providing a sense of accomplishment and stability. Although self-tracking can be burdensome, participants were interested and provided suggestions for simplifying the process.

CONCLUSIONS

These young adults not engaged in treatment reported interest in using self-tracking to build self-understanding as a goal in and of itself or as a first step in contemplating and preparing for behavior change or treatment-seeking. Alexithymia, amotivation, and feeling overwhelmed may serve both as barriers to self-tracking and opportunities for self-tracking to help.

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.

Potential implications of mobile applications in oral cancer

ABSTRACT

The modern era has observed vast technological advancements with a definite impact on the health sector. There has been an upsurge in mobile applications (mApps) used for varied purposes. Many mApps are available that target different arenas in dentistry including a range of oral health issues, the most important being oral cancer. These mApps with specific algorithms have been used for risk assessment, screening and diagnosis of oral potentially malignant and malignant disorders. Other benefits include remote consultation, timely referral, treatment of the disease, self monitoring and adherence to medications. Therefore, this review is designed to appraise the utility of mobile apps in oral cancer. The systematic research of the literature was done to find relevant articles regarding the development and applications of mApps in oral cancer by using specific research engines. PubMed, Cochrane and Clinical Key databases were searched electronically, irrespective of date of publication, with an assortment of several independent terms. A total of 423 articles were accessed, and screened. After applying the definite inclusion and exclusion criteria, 9 articles were finally selected which highlighted the impact of mApps in oral cancer. It was concluded that the potential of mobile applications could be harnessed judiciously to improve the screening, diagnosis and treatment of oral cancer.

Longitudinal Patterns of Engagement and Clinical Outcomes: Results From a Therapist-Supported Digital Mental Health Intervention

OBJECTIVE

Digital mental health interventions (DMHIs) are an effective treatment modality for common mental disorders like depression and anxiety; however, the role of intervention engagement as a longitudinal "dosing" factor is poorly understood in relation to clinical outcomes.

METHODS

We studied 4978 participants in a 12-week therapist-supported DMHI (June 2020-December 2021), applying a longitudinal agglomerative hierarchical cluster analysis to the number of days per week of intervention engagement. The proportion of people demonstrating remission in depression and anxiety symptoms during the intervention was calculated for each cluster. Multivariable logistic regression models were fit to examine associations between the engagement clusters and symptom remission, adjusting for demographic and clinical characteristics.

RESULTS

Based on clinical interpretability and stopping rules, four clusters were derived from the hierarchical cluster analysis (in descending order): a) sustained high engagers (45.0%), b) late disengagers (24.1%), c) early disengagers (22.5%), and d) immediate disengagers (8.4%). Bivariate and multivariate analyses supported a dose-response relationship between engagement and depression symptom remission, whereas the pattern was partially evident for anxiety symptom remission. In multivariable logistic regression models, older age groups, male participants, and Asians had increased odds of achieving depression and anxiety symptom remission, whereas higher odds of anxiety symptom remission were observed among gender-expansive individuals.

CONCLUSIONS

Segmentation based on the frequency of engagement performs well in discerning timing of intervention disengagement and a dose-response relationship with clinical outcomes. The findings among the demographic subpopulations indicate that therapist-supported DMHIs may be effective in addressing mental health problems among patients who disproportionately experience stigma and structural barriers to care. Machine learning models can enable precision care by delineating how heterogeneous patterns of engagement over time relate to clinical outcomes. This empirical identification may help clinicians personalize and optimize interventions to prevent premature disengagement.

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.

User-Centered Design of a Digitally Enabled Care Pathway in a Large Health System: Qualitative Interview Study

BACKGROUND

Major depressive disorder (MDD) is a leading cause of disability worldwide. Management of chronic conditions such as MDD can be improved by enhanced patient engagement, measurement-based care (MBC), and shared decision-making (SDM). A user-centered design approach can improve the understanding of the patient journey and care team workflows and thus aid the development of digital health care innovations optimized for the needs of patients living with MDD and their primary care teams.

OBJECTIVE

This study aims to use qualitative research methods for the user-centered design of a digitally enabled MDD care platform, PathwayPlatform, intended to enhance patient engagement, MBC, and SDM.

METHODS

Insights were gathered through 2 stages of qualitative interviews by a study team with expertise in qualitative research and user-centered design methods. Thematic analysis was used to generate an overarching understanding of a set of shared experiences, thoughts, or behaviors across a broad qualitative data set, including transcripts of interviews, to allow both inductive and deductive insights to emerge. Thematic analysis of interviews was supported by Dedoose (SocioCultural Research Consultants, LLC), a qualitative data analysis software tool that enables systematized coding. Findings and insights were presented based on code frequency, salience, and relevance to the research project.

RESULTS

In stage 1, interviews were conducted with 20 patients living with MDD and 15 health care providers from September 2018 to January 2019 to understand the experiences with and perceptions about the initial functionality of the Pathway app while also exploring the perceptions about potential additional features and functionality. Feedback about care team workflows and treatment approaches was collected in stage-2 interviews with 36 health care providers at 8 primary care sites. Inductive and deductive thematic analyses revealed several themes related to app functionality, patient-provider engagement, workflow integration, and patient education. Both patients and their care teams perceived the remote tracking of patient-reported outcomes via digital tools to be clinically useful and reliable and to promote MBC and SDM. However, there was emphasis on the need to enhance the flow of real-time data shared with the care team, improve trend visualizations, and integrate the data within the existing clinical workflow and educational programs for patients and their care teams. User feedback was incorporated into the iterative development of the Pathway app.

CONCLUSIONS

Ongoing communication with patients living with MDD and their care teams provided an opportunity for user-centric developmental iterations of the Pathway Platform. Key insights led to further development of the patient-facing and care team-facing visit preparation features, collaborative goal-setting and goal-tracking features, patient-reported outcome summaries, and trend visualizations. The result is an enhanced digital platform with the potential to improve treatment outcomes and provide patients living with MDD additional support throughout their treatment journey.

Quality, Usability, and Effectiveness of mHealth Apps and the Role of Artificial Intelligence: Current Scenario and Challenges

The use of artificial intelligence (AI) and big data in medicine has increased in recent years. Indeed, the use of AI in mobile health (mHealth) apps could considerably assist both individuals and health care professionals in the prevention and management of chronic diseases, in a person-centered manner. Nonetheless, there are several challenges that must be overcome to provide high-quality, usable, and effective mHealth apps. Here, we review the rationale and guidelines for the implementation of mHealth apps and the challenges regarding quality, usability, and user engagement and behavior change, with a special focus on the prevention and management of noncommunicable diseases. We suggest that a cocreation-based framework is the best method to address these challenges. Finally, we describe the current and future roles of AI in improving personalized medicine and provide recommendations for developing AI-based mHealth apps. We conclude that the implementation of AI and mHealth apps for routine clinical practice and remote health care will not be feasible until we overcome the main challenges regarding data privacy and security, quality assessment, and the reproducibility and uncertainty of AI results. Moreover, there is a lack of both standardized methods to measure the clinical outcomes of mHealth apps and techniques to encourage user engagement and behavior changes in the long term. We expect that in the near future, these obstacles will be overcome and that the ongoing European project, Watching the risk factors (WARIFA), will provide considerable advances in the implementation of AI-based mHealth apps for disease prevention and health promotion.

Anxiety, mood, and substance use disorders in adult men and women with and without Attention-Deficit/Hyperactivity Disorder: a substantive and methodological overview

Knowledge on psychiatric comorbidity in adult ADHD is essential for prevention, detection, and treatment of these conditions. This review (1) focuses on large studies (n> 10,000; surveys, claims data, population registries) to identify (a) overall, (b) sex- and (c) age-specific patterns of comorbidity of anxiety disorders (ADs), major depressive disorder (MDD), bipolar disorder (BD) and substance use disorders (SUDs) in adults with ADHD relative to adults without ADHD; and (2) describes methodological challenges relating to establishing comorbidity in ADHD in adults as well as priorities for future research. Meta-analyses (ADHD: n=550,748; no ADHD n=14,546,814) yielded pooled odds ratios of 5.0(CI:3.29-7.46) for AD, 4.5(CI:2.44-8.34) for MDD, 8.7(CI:5.47-13.89) for BD and 4.6(CI:2.72-7.80) for SUDs, indicating strong differences in adults with compared to adults without ADHD. Moderation by sex was not found: high comorbidity held for both men and women with sex-specific patterns as in the general population: higher prevalences of ADs, MDD and BD in women and a higher prevalence of SUDs in men. Insufficient data on different phases of the adult lifespan prevented conclusions on developmental changes in comorbidity. We discuss methodological challenges, knowledge gaps, and future research priorities.

How Interactive Visualizations Compare to Ethical Frameworks as Stand-Alone Ethics Learning Tools for Health Researchers and Professionals

BACKGROUND

Despite the bourgeoning of digital tools for bioethics research, education, and engagement, little research has empirically investigated the impact of interactive visualizations as a way to translate ethical frameworks and guidelines. To date, most frameworks take the format of text-only documents that outline and offer ethical guidance on specific contexts. This study's goal was to determine whether an interactive-visual format supports frameworks in transferring ethical knowledge by improving learning, deliberation, and user experience.

METHODS

An experimental comparative study was conducted with a pre-, mid-, and post-test design using the online survey platform Qualtrics. Participants were university based early-stage health researchers who were randomly assigned to either the control condition (text-only document) or the experimental condition (interactive-visual). The primary outcome variables were learning, (measured using a questionnaire), deliberation (using cases studies) and user experience (measured using the SED/UD Scale). Analysis was conducted using descriptive statistics and mixed-effects linear regression.

RESULTS

Of the 80 participants, 44 (55%) used the text-only document and 36 (45%) used the interactive-visual. Results of the knowledge-test scores showed a statistically significant difference between participants' post-test scores, indicating that the interactive-visual format better supported understanding, acquisition, and application of the framework's knowledge. Findings from the case studies showed both formats supported ethical deliberation. Results further indicated the interactive-visual provided an overall better episodic and remembered user experience compared with the text-only document.

CONCLUSIONS

Our findings show that ethical frameworks formatted with interactive and visual qualities provide a more pleasing user experience and are effective formats for ethics learning and deliberation. These findings have implications for practitioners developing and deploying ethical frameworks and guidelines (e.g., in educational or employee-onboarding settings), in that the knowledge generated can lead to more effective dissemination practices of normative guidelines and health data ethics concepts.

Overcoming challenges in adherence and engagement digital interventions: The development of the ALGEApp for chronic pain management

Despite the growing body of evidence for the effectiveness of clinic-based interventions in increasing daily functioning in individuals with chronic pain, many sufferers still remain untreated or inadequately treated. Digital psychological interventions have been proposed as a means to overcome many of the barriers to face-to-face treatment (e.g., access, mobility, transportation problems) with the aim to improve health care for persons with chronic conditions in the convenience of their own space and time (home care). The main challenge of digital interventions however, is low user engagement and adherence. Focusing on users' engagement during the design phase of a digital intervention development can increase adherence, effectiveness, and acceptability. The purpose of this paper is to illustrate how we leveraged a recently proposed four-dimensional framework with evidence-based best practices and recommendations to develop a new digital intervention for chronic pain management, called the ALGEApp. A detailed presentation of how ALGEApp was designed and developed to adopt the recommendations and how this can aid engagement within digital interventions is proposed.

A Web-Based Stratified Stepped Care Platform for Mental Well-being (TourHeart+): User-Centered Research and Design

BACKGROUND

Internet-based mental health interventions have been demonstrated to be effective in alleviating psychological distress and promoting mental well-being. However, real-world uptake and engagement of such interventions have been low. Rather than being stand-alone interventions, situating internet-based interventions under a stratified stepped care system can support users to continue with mental health practice and monitor their mental health status for timely services that are commensurate with their needs. A user-centered approach should be used in the development of such web-based platforms to understand the facilitators and barriers in user engagement to enhance platform uptake, usability, and adherence so it can support the users' continued adoption and practice of self-care for their mental health.

OBJECTIVE

The aim of this study was to describe the design process taken to develop a web-based stratified stepped care mental health platform, TourHeart+, using a user-centered approach that gathers target users' perceptions on mental self-care and feedback on the platform design and incorporates them into the design.

METHODS

The process involved a design workshop with the interdisciplinary development team, user interviews, and 2 usability testing sessions on the flow of registration and mental health assessment and the web-based self-help interventions of the platform. The data collected were summarized as descriptive statistics if appropriate and insights are extracted inductively. Qualitative data were extracted using a thematic coding approach.

RESULTS

In the design workshop, the team generated empathy maps and point-of-view statements related to the possible mental health needs of target users. Four user personas and related processes in the mental health self-care journey were developed based on user interviews. Design considerations were derived based on the insights drawn from the personas and mental health self-care journey. Survey results from 104 users during usability testing showed that the overall experience during registration and mental health assessment was friendly, and they felt cared for, although no statistically significant differences on preference ratings were found between using a web-based questionnaire tool and through an interactive chatbot, except that chatbot format was deemed more interesting. Facilitators of and barriers to registering the platform and completing the mental health assessment were identified through user feedback during simulation with mock-ups. In the usability testing for guided self-help interventions, users expressed pain points in course adherence, and corresponding amendments were made in the flow and design of the web-based courses.

CONCLUSIONS

The design process and findings presented in the study are important in developing a user-centric platform to optimize users' acceptance and usability of a web-based stratified stepped care platform with guided self-help interventions for mental well-being. Accounting for users' perceptions and needs toward mental health self-care and their experiences in the design process can enhance the usability of an evidence-based mental health platform on the web.

Group behavioral activation with and without a smartphone app in intensive outpatient treatment for substance use disorder: A three-arm randomized controlled trial

INTRODUCTION

Reward deficits negatively impact recovery from substance use disorder (SUD). LETS ACT, a behavioral activation treatment targeting substance-free reward, has demonstrated effectiveness in reducing post treatment substance use. There remains room for modifications to extend recovery gains, and LETS ACT remains largely untested in outpatient treatment. We tested the effect of LETS ACT when delivered alongside intensive outpatient SUD treatment, with and without a smartphone app designed to extend access to treatment content outside of clinician-administered sessions.

METHODS

In this three-arm randomized controlled trial (N = 206; 54 % White, 67 % male), all participants received intensive outpatient SUD treatment as usual (TAU) and either LETS ACT (n = 56), smartphone-enhanced LETS ACT (n = 65), or assessments only (n = 61). Substance use days and substance related problems were assessed through 12 months posttreatment.

RESULTS

Generalized estimating equations indicated a significant condition*time interaction for substance use days; Days of substance use significantly declined from pretreatment until 1-month for TAU, 3-months for LETS ACT-SE, and 6-months for LETS ACT. Decreases in substance-related problems were maintained across all conditions through 12 months.

CONCLUSIONS

Adding LETS ACT to intensive outpatient treatment resulted in significant decreases in substance use through 6 months posttreatment, yet these gains were not sustained through 12 months posttreatment. A smartphone app did not facilitate superior treatment outcomes. Future studies should consider factors impacting treatment efficacy in outpatient settings and the utility of providing more than six sessions of behavioral activation.

Effects of a Smartphone-Based, Multisession Interpretation-Bias Modification for Anxiety: Positive Intervention Effects and Low Attrition

While interpretation-bias modification (IBM) is an effective intervention for treating anxiety, it is not broadly used in clinical or daily practice. To this end, this study developed and tested a smartphone-based IBM application. We adopted the ambiguous situation paradigm as an intervention task in conjunction with robust training materials that broadly covered situations encountered in daily life. We recruited participants with high-trait anxiety and divided them into three groups: (1) positive training; (2) 50% positive-50% negative training; and (3) no-training control. The first two groups completed 28 days of smartphone-based training (IBM in positive cases), and all groups completed six rounds of assessments. The smartphone-based IBM training changed positive and negative endorsements and more specific measures of interpretation bias, thus reducing anxiety. The results also showed that changes in the number of negative interpretations played a mediating role in anxiety reduction. It is notable that the attrition rate was extremely low across the experiment. Our follow-up showed that positive gains persisted throughout the intervening period. Smartphone-based IBM can help individuals with anxiety shift negative biases, broaden their thoughts, enhance their information processing, and effectively target the clinical features of anxiety.

User engagement in mobile apps for people with schizophrenia: A scoping review

Over the past decade, there has been an increase in the number of mobile apps designed for mental health proposes and mHealth has been perceived as a promising approach to help people with schizophrenia to manage their condition. However, adoption rates are relatively low and long-term user engagement is a major issue. The aim of this study is to identify and better understand what strategies and factors may influence user engagement and facilitate prolonged use of apps for people with schizophrenia to better manage their illness. A scoping review was conducted in accordance with the Arksey and O'Malley scoping review framework and following PRISMA ScR guidelines. The sources consisted of searching four electronic databases. Rayyan software was used for this study selection process and a narrative approach was used to synthesize the extracted data. A total of 28 studies which met the inclusion criteria were identified. The engagement strategies included push notifications, message prompts, personalization, application customization, goal setting, game-like features, use of different multimedia formats, social connectedness, support (peers and professionals), reliability of content and quality of feedback received. Some demographic factors may influence adherence such as age, gender, education level and socioeconomic status. Other factors also may play a role impacting engagement: health status, data privacy and security, involvement in design process, incentives for participation, app usage fitting in the user routines, initial training, and constant technical support. Included studies present high heterogeneity in outcome measures and thresholds criteria to assess engagement. Understanding what influences engagement and how to measure it is essential to enhance the design of mobile apps and deliver scalable solutions to help people with schizophrenia better manage their illness in their real-world uptake.

Psychotherapies and digital interventions for OCD in adults: What do we know, what do we need still to explore?

BACKGROUND

Despite significant advances in the understanding and treatment of obsessive compulsive disorder (OCD), current treatment options are limited in terms of efficacy for symptom remission. Thus, assessing the potential role of iterative or alternate psychotherapies is important. Also, the potential role of digital technologies to enhance the accessibility of these therapies, should not be underestimated. We also need to embrace the idea of a more personalized treatment choice, being cognisant of clinical, genetic and neuroimaging predictors of treatment response.

PROCEDURES

Non-systematic review of current literature on emerging psychological and digital therapies for OCD, as well as of potential biomarkers of treatment response.

FINDINGS

A number of 'third wave' therapies (e.g., Acceptance and Commitment Therapy, Mindfulness-Based Cognitive Therapy) have an emerging and encouraging evidence base in OCD. Other approaches entail employment of elements of other psychotherapies such as Dialectical Behaviour Therapy; or trauma-focussed therapies such as Eye Movement Desensitisation and Reprocessing, and Imagery Rescripting and Narrative Therapy. Further strategies include Danger Ideation Reduction Therapy and Habit Reversal. For these latter approaches, large-scale randomised controlled trials are largely lacking, and the precise role of these therapies in treating people with OCD, remains to be clarified. A concentrated 4-day program (the Bergen program) has shown promising short- and long-term results. Exercise, music, and art therapy have not been adequately tested in people with OCD, but may have an adjunctive role. Digital technologies are being actively investigated for enhancing reach and efficacy of psychological therapies for OCD. Biomarkers, including genetic and neuroimaging, are starting to point to a future with more 'personalised medicine informed' treatment strategizing for OCD.

CONCLUSIONS

There are a number of potential psychological options for the treatment of people with OCD who do not respond adequately to exposure/response prevention or cognitive behaviour therapy. Adjunctive exercise, music, and art therapy might be useful, albeit the evidence base for these is very small. Consideration should be given to different ways of delivering such interventions, including group-based, concentrated, inpatient, or with outreach, where appropriate. Digital technologies are an emerging field with a number of potential applications for aiding the treatment of OCD. Biomarkers for treatment response determination have much potential capacity and deserve further empirical testing.

DECENT: A sociotechnical approach for developing mobile health apps in underserved settings

Objective

Despite the fact that user engagement is critical to the efficacy of mobile health (mHealth) interventions in the Global South, many of these interventions lack user engagement features. This is because sociotechnical aspects of such initiatives are frequently ignored during the design, development, and implementation stages. This research highlighted the importance of considering sociotechnical factors when developing mHealth apps. The intended users for the mHealth technologies in this study are care professionals.

Materials and Methods

Five semi-structured interviews and a pilot interview were conducted to identify user engagement facilitators and barriers. The interview data were analysed using NVivo. The Capability, Opportunity, Motivation - Behaviour (COM-B) model is then used to map the facilitators and barriers to mHealth app engagement, allowing researchers to better understand how users engage/disengage with mHealth apps.

Results and Discussion

Capability facilitators included features that assist users in learning more about the app (e.g. a user manual and statistical data) as well as features that assist users in developing a routine. The lack of app skills and cognitive overload limit capability. While social connectedness and offline functionality were identified as facilitators of user engagement, non-user-friendly design and cultural dimensions were identified as barriers. Early user engagement and rewards were identified as motivational facilitators that influence user engagement. Furthermore, perceived non-utility and a lack of encouragement were identified as motivational barriers to engagement.

Conclusion

Several factors were discovered across all COM-B model components that could be used to develop more engaging mHealth apps. Adopting a techno-centric approach that ignores sociotechnical factors can reduce user engagement. The design process engagement enhancement system (DECENT) framework was proposed based on the findings.

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.

Mental health professionals views and the impact of COVID-19 pandemic on implementing digital mental health in China: A nationwide survey study

BACKGROUND

Using digital health technologies (DHTs) to deliver and augment healthcare is an innovative way to solve common challenges that the mental healthcare setting faces. Despite China's rapid development of DHT, a comprehensive understanding of staff views of DHTs is lacking, which limited the evidence to support implementation strategies. In the current study, we aim to: (i) investigate staff attitudes towards digital technology for mental health problems in China; (ii) explore staff's views on the facilitators and barriers regarding uptake and adoption of digital technology in mental health services in China; and (iii) understand how the COVID-19 pandemic has changed staff views on digital mental health.

METHODS

An online survey was conducted to explore staff attitudes towards implementing DHTs in China. Descriptive statistics were conducted to summarise quantitative data. Free-text data were analysed using qualitative content analysis.

RESULTS

1270 mental health professionals completed the survey. Respondents reported low levels of knowledge of DHTs and moderate levels of accessibility of DHTs in their hospitals. Respondents expressed positive attitudes towards DHTs and demonstrated moderate levels of perceived feasibility and acceptability of implementing DHTs in clinical services. As expected, respondents reported that the COVID-19 pandemic caused significant impacts on their clinical services, and almost all respondents deemed DHTs useful for services provision during the pandemic and were willing to apply such technologies in clinical services after the pandemic.

CONCLUSIONS

Despite the Chinese mental health staff expressed positive attitudes towards implementing DHTs in clinical practice, most of the staff lacked sufficient knowledge to provide such services. These findings highlight the need to develop implementation strategies such as training programmes and dissemination of research evidence to support the translation of research.

Analyzing the Impact of Mobile App Engagement on Mental Health Outcomes: Secondary Analysis of the Unwinding Anxiety Program

BACKGROUND

App-based interventions provide a promising avenue for mitigating the burden on mental health services by complimenting therapist-led treatments for anxiety. However, it remains unclear how specific systems' use of app features may be associated with changes in mental health outcomes (eg, anxiety and worry).

OBJECTIVE

This study was a secondary analysis of engagement data from a stage 1 randomized controlled trial testing the impact of the Unwinding Anxiety mobile app among adults with generalized anxiety disorder. The aims of this study were 2-fold: to investigate whether higher microengagement with the primary intervention feature (ie, educational modules) is associated with positive changes in mental health outcomes at 2 months (ie, anxiety, worry, interoceptive awareness, and emotional reactivity) and to investigate whether the use of adjunctive app features is also associated with changes in mental health outcomes.

METHODS

We analyzed the intervention group during the stage 1 trial of the Unwinding Anxiety mobile app. The total use of specific mobile app features and the use specific to each feature were calculated. We used multivariate linear models with a priori significance of α=.05 to investigate the impact of cumulative app use on anxiety, worry, interoceptive awareness, and emotional regulation at 2 months, controlling for baseline scores, age, and education level in all models. Significant relationships between system use metrics and baseline participant characteristics were assessed for differences in use groupings using between-group testing (ie, 2-tailed t tests for continuous data and chi-square analyses for categorical data).

RESULTS

The sample was primarily female (25/27, 93%), and the average age was 42.9 (SD 15.6) years. Educational module completion, the central intervention component, averaged 20.2 (SD 11.4) modules out of 32 for the total sample. Multivariate models revealed that completing >75% of the program was associated with an average 22.6-point increase in interoceptive awareness (b=22.6; SE 8.32; P=.01; 95% CI 5.3-39.8) and an 11.6-point decrease in worry (b=-11.6; SE 4.12; P=.01; 95% CI -20.2 to -3.1). In addition, a single log unit change in the total number of meditations was associated with a 0.62-point reduction in the Generalized Anxiety Disorder-7 scale scores (b=0.62; SE 0.27; P=.005; 95% CI -1.2 to -0.6), whereas a single log unit use of the stress meter was associated with an average of a 0.5-point increase in emotional regulation scores (Five Facet Mindfulness Questionnaire; b=0.5; SE 0.21; P=.03; 95% CI 0.1-0.9).

CONCLUSIONS

This study offers a clearer understanding of the impact of engagement with app features on broader engagement with the health outcomes of interest. This study highlights the importance of comprehensive investigations of engagement during the development of evidence-based mobile apps.

The Impact of Mobile Technology-Delivered Interventions on Youth Well-being: Systematic Review and 3-Level Meta-analysis

BACKGROUND

Rates of mental health problems among youth are high and rising, whereas treatment seeking in this population remains low. Technology-delivered interventions (TDIs) appear to be promising avenues for broadening the reach of evidence-based interventions for youth well-being. However, to date, meta-analytic reviews on youth samples have primarily been limited to computer and internet interventions, whereas meta-analytic evidence on mobile TDIs (mTDIs), largely comprising mobile apps for smartphones and tablets, have primarily focused on adult samples.

OBJECTIVE

This study aimed to evaluate the effectiveness of mTDIs for a broad range of well-being outcomes in unselected, at-risk, and clinical samples of youth.

METHODS

The systematic review used 5 major search strategies to identify 80 studies evaluating 83 wellness- and mental health-focused mTDIs for 19,748 youth (mean age 2.93-26.25 years). We conducted a 3-level meta-analysis on the full sample and a subsample of the 38 highest-quality studies.

RESULTS

Analyses demonstrated significant benefits of mTDIs for youth both at posttest (g=0.27) and follow-up (range 1.21-43.14 weeks; g=0.26) for a variety of psychosocial outcomes, including general well-being and distress, symptoms of diverse psychological disorders, psychosocial strategies and skills, and health-related symptoms and behaviors. Effects were significantly moderated by the type of comparison group (strongest for no intervention, followed by inert placebo or information-only, and only marginal for clinical comparison) but only among the higher-quality studies. With respect to youth characteristics, neither gender nor pre-existing mental health risk level (not selected for risk, at-risk, or clinical) moderated effect sizes; however, effects increased with the age of youth in the higher-quality studies. In terms of intervention features, mTDIs in these research studies were effective regardless of whether they included various technological features (eg, tailoring, social elements, or gamification) or support features (eg, orientation, reminders, or coaching), although the use of mTDIs in a research context likely differs in important ways from their use when taken up through self-motivation, parent direction, peer suggestion, or clinician referral. Only mTDIs with a clear prescription for frequent use (ie, at least once per week) showed significant effects, although this effect was evident only in the higher-quality subsample. Moderation analyses did not detect statistically significant differences in effect sizes based on the prescribed duration of mTDI use (weeks or sessions), and reporting issues in primary studies limited the analysis of completed duration, thereby calling for improved methodology, assessment, and reporting to clarify true effects.

CONCLUSIONS

Overall, this study's findings demonstrate that youth can experience broad and durable benefits of mTDIs, delivered in a variety of ways, and suggest directions for future research and development of mTDIs for youth, particularly in more naturalistic and ecologically valid settings.

Preliminary Real-World Evidence Supporting the Efficacy of a Remote Neurofeedback System in Improving Mental Health: Retrospective Single-Group Pretest-Posttest Study

Background

Neurofeedback training (NFT) has been shown to be effective in treating several disorders (eg, attention-deficit/hyperactivity disorder [ADHD], anxiety, and depression); however, little is currently known regarding the effectiveness of remote NFT systems.

Objective

This retrospective study provides real-world data (N=593) to assess the efficacy of app-based remote NFT in improving brain health and cognitive performance.

Methods

Improvement was measured from pre- to postintervention of in-app assessments that included validated symptom questionnaires (the 12-item General Health Questionnaire, the ADHD Rating Scale IV, the Adult ADHD Self-Report Scale, the 7-item Generalized Anxiety Disorder scale, and the 9-item Patient Health Questionnaire), a cognitive test of attention and executive functioning (ie, continuous performance task), and resting electroencephalography (EEG) markers. Clinically significant improvement was evaluated using standard approaches.

Results

The greatest improvement was reported for the anxiety questionnaire, for which 69% (68/99) of participants moved from abnormal to healthy score ranges. Overall, adult and child participants who engaged in neurofeedback to improve attention and executive functions demonstrated improved ADHD scores and enhanced performance on a cognitive (ie, response inhibition) task. Adults with ADHD additionally demonstrated elevated delta/alpha and theta/alpha ratios at baseline and a reduction in the delta/alpha ratio indicator following neurofeedback.

Conclusions

Preliminary findings suggest the efficacy of app-based remote neurofeedback in improving mental health, given the reduced symptom severity from pre- to postassessment for general psychological health, ADHD, anxiety, and depression, as well as adjusted resting EEG neural markers for individuals with symptoms of ADHD. Collectively, this supports the utility of the in-app assessment in monitoring behavioral and neural indices of mental health.

mSexHealth: An Overview of Mobile Sexual Health Applications

The aim of this study was to examine the existing mobile applications focused on sexual health and analyze the included content and therapeutic techniques. Three databases with mobile applications were searched and 47 applications met the criteria. More applications have been developed for men, most of them included content for erectile dysfunction, and only one for vaginismus. Most apps included sexuality tips and Kegel exercises, and only one technique for working on thoughts and emotions. In conclusion, a number of mobile applications have been developed to enhance sexual functioning, but scientific verification of their effectiveness has been completely lacking.

An insight into diagnosis of depression using machine learning techniques: a systematic review

BACKGROUND

In this modern era, depression is one of the most prevalent mental disorders from which millions of individuals are affected today. The symptoms of depression are heterogeneous and often coincide with other disorders such as bipolar disorder, Parkinson's, schizophrenia, etc. It is a serious mental illness that may lead to other health problems if left untreated. Currently, identifying individuals with depression is totally based on the expertise of the clinician's experience. In order to assist clinicians in identifying the characteristics and classifying depressed people, different types of data modalities and machine learning techniques have been incorporated by researchers in this field. This study aims to find the answers to some important questions related to the trend of publications, data modality, machine learning models, dataset usage, pre-processing techniques and feature extraction and selection techniques that are prevalent and guide the direction of future research on depression diagnosis.

METHODS

This systematic review was conducted using a broad range of articles from two major databases: IEEE Xplore and PubMed. Studies ranging from the years 2011 to April 2021 were retrieved from the databases resulting in a total of 590 articles (53 articles from the IEEE Xplore database and 537 articles from the PubMed database). Out of those, the articles which satisfied the defined inclusion criteria were investigated for further analysis.

RESULTS

A total of 135 articles were identified and analysed for this review. High growth in the number of publications has been observed in recent years. Furthermore, significant diversity in the use of data modalities and machine learning classifiers has also been noted in this study. fMRI data with an SVM classifier was found to be the most popular choice among researchers. In most of the studies, data scarcity and small sample size, particularly for neuroimaging data are major concerns. The use of identical data pre-processing tools for similar data modalities can be seen. This study also provides statistical analysis of the current framework with respect to the modality, machine learning classifier, sample size and accuracy by applying one-way ANOVA and the Tukey - Kramer test.

CONCLUSION

The results indicate that an effective fusion of machine learning techniques with a potential data modality has a promising future for assisting clinicians in automatic depression diagnosis.

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.

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

Efficacy of Smartphone Apps in Patients With Depressive Disorders: A Systematic Review

BACKGROUND

Digital interventions have become an accessible format in clinical practice to provide better support for patients with mental disorders. However, the clinical efficacy in patients with depressive disorders is not well known. We aimed to determine the efficacy of smartphone applications (apps) in patients diagnosed with a depressive disorder.

METHOD

An electronic database search was performed of PubMed, PsycINFO, and Web of Science, to identify relevant articles up to June 12, 2021. Peer-reviewed articles were screened and selected based on predetermined inclusion and exclusion criteria.

RESULTS

Seven articles met the inclusion criteria and therefore were selected for the systematic review, which included a total of 651 patients. The results were heterogeneous, essentially due to the different methodologies used in the selected studies.

CONCLUSIONS

Digital smartphone-delivered interventions do not appear to reduce depressive symptomatology nor improve the quality of life in patients diagnosed with depressive disorders when compared to an active control group. Taking into account the inherent methodological difficulties and the variability among such studies, it is apparent that further research-with more methodologically refined clinical trials, including larger sample sizes-is needed.

Evaluating the effectiveness and quality of mobile applications for perinatal depression and anxiety: A systematic review and meta-analysis

BACKGROUND

Our objectives were to assess: (1) the effectiveness of existing mHealth apps for reducing symptoms of maternal depression and/or anxiety during the prenatal period and/or the first year postpartum, and (2) the app quality of commercially available apps targeting perinatal depression and/or anxiety.

METHODS

To address Objective 1, we searched five electronic databases (MEDLINE, CINAHL, PsycINFO, Web of Science, and Embase) from their inception until May 3rd, 2021. For the second objective, we searched Google Play and Apple App Stores in the United States, United Kingdom, Canada, and Australia until May 3rd, 2021.

RESULTS

Our search identified 3,897 articles, seven of which were meta-analyzed. mHealth apps did not improve perinatal depression (SMD, -0.39; 95% CI, -0.80 to 0.03) or anxiety (SMD, 0.01; 95% CI, -0.13 to 0.16) within the first 3 months post-intervention or at 6 months post-intervention. Our search of app stores identified 74 commercially available apps, 37 of which were evaluated via MARS tool. Current apps for perinatal anxiety and/or depression were rated to be of moderate quality on the MARS (mean, 3.6/5).

LIMITATIONS

There is a small number of overall studies in this field and the individual studies have methodological limitations. Furthermore, few apps identified in our app store search have been clinically tested.

CONCLUSION

Despite their widespread availability, mHealth apps do not appear to effectively reduce perinatal depression or anxiety, and few were subjectively rated to be of high quality. There is a need to develop higher quality mHealth apps and assess their potential to improve perinatal maternal mental health.

Technology-supported strategies for promoting user engagement with digital mental health interventions: A systematic review

Background

Although digital mental health interventions (DMHIs) offer a potential solution for increasing access to mental health treatment, their integration into real-world settings has been slow. A key reason for this is poor user engagement. A growing number of studies evaluating strategies for promoting engagement with DMHIs means that a review of the literature is now warranted. This systematic review is the first to synthesise evidence on technology-supported strategies for promoting engagement with DMHIs.

Methods

MEDLINE, EmbASE, PsycINFO and PubMed databases were searched from 1 January 1995 to 1 October 2021. Experimental or quasi-experimental studies examining the effect of technology-supported engagement strategies deployed alongside DMHIs were included, as were secondary analyses of such studies. Title and abstract screening, full-text coding and quality assessment were performed independently by two authors. Narrative synthesis was used to summarise findings from the included studies.

Results

24 studies (10,266 participants) were included. Engagement strategies ranged from reminders, coaching, personalised information and peer support. Most strategies were disseminated once a week, usually via email or telephone. There was some empirical support for the efficacy of technology-based strategies towards promoting engagement. However, findings were mixed regardless of strategy type or study aim.

Conclusions

Technology-supported strategies appear to increase engagement with DMHIs; however, their efficacy varies widely by strategy type. Future research should involve end-users in the development and evaluation of these strategies to develop a more cohesive set of strategies that are acceptable and effective for target audiences, and explore the mechanism(s) through which such strategies promote engagement.

Artificially intelligent chatbots in digital mental health interventions: a review

INTRODUCTION

Increasing demand for mental health services and the expanding capabilities of artificial intelligence (AI) in recent years has driven the development of digital mental health interventions (DMHIs). To date, AI-based chatbots have been integrated into DMHIs to support diagnostics and screening, symptom management and behavior change, and content delivery.

AREAS COVERED

We summarize the current landscape of DMHIs, with a focus on AI-based chatbots. Happify Health's AI chatbot, Anna, serves as a case study for discussion of potential challenges and how these might be addressed, and demonstrates the promise of chatbots as effective, usable, and adoptable within DMHIs. Finally, we discuss ways in which future research can advance the field, addressing topics including perceptions of AI, the impact of individual differences, and implications for privacy and ethics.

EXPERT OPINION

Our discussion concludes with a speculative viewpoint on the future of AI in DMHIs, including the use of chatbots, the evolution of AI, dynamic mental health systems, hyper-personalization, and human-like intervention delivery.

Effect of Engagement With Digital Interventions on Mental Health Outcomes: A Systematic Review and Meta-Analysis

Digital mental health interventions (DMHIs) present a promising way to address gaps in mental health service provision. However, the relationship between user engagement and outcomes in the context of these interventions has not been established. This study addressed the current state of evidence on the relationship between engagement with DMHIs and mental health outcomes. MEDLINE, PsycINFO, and EmBASE databases were searched from inception to August 1, 2021. Original or secondary analyses of randomized controlled trials (RCTs) were included if they examined the relationship between DMHI engagement and post-intervention outcome(s). Thirty-five studies were eligible for inclusion in the narrative review and 25 studies had sufficient data for meta-analysis. Random-effects meta-analyses indicated that greater engagement was significantly associated with post-intervention mental health improvements, regardless of whether this relationship was explored using correlational [r = 0.24, 95% CI (0.17, 0.32), Z = 6.29, p < 0.001] or between-groups designs [Hedges' g = 0.40, 95% CI (0.097, 0.705), p = 0.010]. This association was also consistent regardless of intervention type (unguided/guided), diagnostic status, or mental health condition targeted. This is the first review providing empirical evidence that engagement with DMHIs is associated with therapeutic gains. Implications and future directions are discussed.

Systematic Review Registration: PROSPERO, identifier: CRD 42020184706.