Mobile Technologies for Supporting Mental Health in Youths: Scoping Review of Effectiveness, Limitations, and Inclusivity

The effect of a universal mobile application on adolescents' mental health and well-being

Opp is a universal mental health-promoting mobile application (app) developed for adolescents, with the aim of promoting mental health and well-being and preventing mental health problems. In this randomized controlled trial, the effectiveness of Opp was tested among Norwegian adolescents aged 13 to 25 years. Mental health, well-being, self-efficacy, self-esteem, help-seeking behavior, and sleep quality were assessed at two measurement points (T1 and T2), that were approximately 11 weeks apart. Only the participants that answered at both measurement points were included in the main analyses (N = 399; 75 % girls; Mage = 16.90 years, SD = 1.40). The results demonstrated a statistically significant effect of the app on mental health, as measured by the SDQ Total Difficulties scale (F(1,790) = 4.35, p = .037), while no statistically significant effects were observed on the other outcomes. These results provide important insights, and a broader understanding of how mental health apps can influence the mental health and well-being of a general sample of adolescents.

mHealth Applications for Childhood Anxiety Disorders: Current Landscape, Challenges, and Future Directions

Purpose of Review

We review the literature on mHealth applications for childhood anxiety disorders, highlighting current use, limitations, and future directions.

Recent Findings

Although mHealth apps targeting childhood anxiety disorders have recently increased, most have not been evaluated for clinical effectiveness, data security, or quality standards. Many apps do not contain scientifically based content and do not adequately incorporate the principles of exposure-based cognitive behavioral therapy. In addition, many apps have significant deficiencies in age-appropriateness, data security, privacy, cultural sensitivity, and accessibility. Limitations remain in terms of the standards for evaluating apps in pediatric populations.

Summary

While interest in mHealth applications for childhood anxiety disorders is increasing, more research is needed to develop effective, safe, and age-appropriate digital interventions. Priorities include scientific grounding, privacy, equitable access, gamification, and parental involvement. Studies in this direction will increase the quality of applications and strengthen equality in access to mental health services.

mHealth Applications for Childhood Anxiety Disorders: Current Landscape, Challenges, and Future Directions

PURPOSE OF REVIEW

We review the literature on mHealth applications for childhood anxiety disorders, highlighting current use, limitations, and future directions.

RECENT FINDINGS

Although mHealth apps targeting childhood anxiety disorders have recently increased, most have not been evaluated for clinical effectiveness, data security, or quality standards. Many apps do not contain scientifically based content and do not adequately incorporate the principles of exposure-based cognitive behavioral therapy. In addition, many apps have significant deficiencies in age-appropriateness, data security, privacy, cultural sensitivity, and accessibility. Limitations remain in terms of the standards for evaluating apps in pediatric populations. While interest in mHealth applications for childhood anxiety disorders is increasing, more research is needed to develop effective, safe, and age-appropriate digital interventions. Priorities include scientific grounding, privacy, equitable access, gamification, and parental involvement. Studies in this direction will increase the quality of applications and strengthen equality in access to mental health services.

Health-Promoting Effects and Everyday Experiences With a Mental Health App Using Ecological Momentary Assessments and AI-Based Ecological Momentary Interventions Among Young People: Qualitative Interview and Focus Group Study

BACKGROUND

Considering the high prevalence of mental health conditions among young people and the technological advancements of artificial intelligence (AI)-based approaches in health services, mobile health (mHealth) apps for mental health are a promising way for low-threshold and large-scale mental health promotion, prevention, and intervention strategies, especially for young people. However, insufficient evidence on health-promoting effects and deficient user-centric designs emphasize the necessity for participatory methods in the interventions' development processes.

OBJECTIVE

This study aimed to explore young people's everyday experiences using an AI-based mHealth app for mental health promotion based on ecological momentary assessments and ecological momentary interventions. Our analysis of qualitative data focused on exploring young people's use patterns in daily life and mental health-promoting effects.

METHODS

We conducted problem-centered interviews and focus groups with a subsample of 27 young people aged 14 to 25 years, who were among the participants of 2 microrandomized trials testing and evaluating an AI-based mHealth app (AI4U training). Our study used a participatory approach, with "co- and peer researchers" from the dialogue population actively engaged in research processes and data analysis. Structural content analysis guided the qualitative analysis.

RESULTS

Participants reported enhanced emotional self-awareness and regulation in daily life through the ecological momentary assessments and ecological momentary interventions. Young people appreciated the AI4U training for managing emotions and stress. They had no trust issues regarding disclosing their mental health via the AI4U training in daily life. Some faced challenges integrating it into their daily routines and highlighted the value of autonomy in use decision-making processes.

CONCLUSIONS

Our findings reveal that young people benefited from enhanced emotional awareness and management through the use of the AI4U training, appreciating its anonymity for facilitating emotional disclosure. The results suggest that enhanced self-directed use may improve daily life integration, although participants noted that they sometimes avoided using the AI4U training during distress despite recognizing its potential benefits. These findings indicate the importance of balancing directed use and autonomy in digital interventions to harmonize compliance with effectiveness in daily life. We highlight the importance of participatory research for tailored digital mental health solutions.

Harm reduction interventions for AYA who use opioids: A scoping review

BACKGROUND

Adolescents and young adults (AYA) are highly vulnerable to substance use and substance use-related harms. Existing harm reduction programs do not optimally serve AYA, and there is minimal data regarding harm reduction interventions specific to AYA.

METHODS

We conducted a preliminary search in MEDLINE (Ovid) to identify names used to describe harm reduction interventions to include in the final search. We performed a scoping review of electronic bibliographic databases MEDLINE (Ovid), Embase (Elsevier), PsycINFO (EBSCO), and Web of Science (Clarivate). We included studies that discussed any harm reduction interventions specific to adolescents and young adults. We performed thematic analysis of included studies and used a narrative synthesis approach to consolidate and present findings.

RESULTS

We included 58 studies in our review. AYA demonstrated different patterns of substance use and engagement with harm reduction compared to adults. AYA are open to harm reduction practices and engage in forms of harm reduction informally. A variety of harm reduction interventions were effective among AYA, including naloxone training, fentanyl test strips, and safe injection facilities. AYA respond well to programs that are convenient, private, and emphasize longitudinal relationship building with community and providers. They may uniquely benefit from virtual programming, telehealth, and delivery services.

CONCLUSIONS

We must better serve AYA with youth-centered programs that prioritize privacy, safety, and convenience; offer a wide variety of services relevant to AYA substance use patterns; offer mobile and virtual options; and focus on building and leveraging community and networks.

Validity of a smartphone application for self-monitoring psychiatric symptoms in patients with schizophrenia

Objective

Despite increasing research on digital technologies for psychiatric disorders, studies specifically examining self-monitoring of symptoms with smartphone applications by patients with schizophrenia remain limited. This study aims to evaluate the validity and reliability of self-monitoring psychiatric symptoms using a smartphone application among patients with schizophrenia at Mindlink, a community-based early intervention center.

Methods

Fifty-three young patients with schizophrenia spectrum disorders participated. They rated their psychiatric symptoms across five domains-delusions, hallucinations, anxiety, depression, and perceived stress-using an 11-point Likert scale at baseline, 1 week, 8 weeks, and 16 weeks. Test-retest reliability was assessed using intraclass correlation coefficients (ICCs) between baseline and 1-week ratings. Concurrent validity was determined by correlating app-based ratings with established self-report and clinician-administered scales, including the Eppendorf Schizophrenia Inventory, Hamilton Program for Schizophrenia Voices Questionnaire, Beck Depression Inventory, Generalized Anxiety Disorder-7, and Perceived Stress Scale. The accuracy of the app's depression rating was assessed using receiver operating characteristic (ROC) analysis.

Results

ICCs for test-retest reliability were high across all symptom domains, ranging from 0.741 to 0.876 (p < 0.001). Significant correlations were observed between app-based ratings and formal assessments at all time points. ROC analysis for single-item self-ratings using the app yielded an area under the curve of 0.829 (p = 0.002), indicating good accuracy.

Conclusion

This study demonstrates that self-monitoring of key symptoms and stress using a smartphone application is valid and reliable for patients with schizophrenia. These findings support the app's potential to enhance symptom management and enable early detection of relapse in this population.

Evaluating predictive artificial intelligence approaches used in mobile health platforms to forecast mental health symptoms among youth: a systematic review

The youth mental health crisis is exacerbated by limited access to care and resources. Mobile health (mHealth) platforms using predictive artificial intelligence (AI) can improve access and reduce barriers, enabling real-time responses and precision prevention. This systematic review evaluates predictive AI approaches in mHealth platforms for forecasting mental health symptoms among youth (13-25 years). We searched studies from Embase, PubMed, Web of Science, PsycInfo, and CENTRAL, to identify relevant studies. From 11 studies identified, three studies predicted multiple symptoms, with depression being the most common (63%). Most platforms used smartphones and 25% integrated wearables. Key predictors included smartphone usage (N=5), sleep metrics (N=6), and physical activity (N=5). Nuanced predictors like usage locations and sleep stages improved prediction. Logistic regression was most used (N=6), followed by Support Vector Machines (N=3) and ensemble methods (N=4). F-scores for anxiety and depression ranged from 0.73 to 0.84, and AUCs from 0.50 to 0.74. Stress models had AUCs of 0.68 to 0.83. Bayesian model selection and Shapley values enhanced robustness and interpretability. Barriers included small sample sizes, privacy concerns, missing data, and underrepresentation bias. Rigorous evaluation of predictive performance, generalizability, and user engagement is critical before mHealth platforms are integrated into psychiatric care.

A Digital Mental Health Solution to Improve Social, Emotional, and Learning Skills for Youth: Protocol for an Efficacy and Usability Study

BACKGROUND

The COVID-19 pandemic has exposed a devastating youth mental health crisis in the United States, characterized by an all-time high prevalence of youth mental illness. This crisis is exacerbated by limited access to mental health services and the reduction of mental health support in schools. Mobile health platforms offer a promising avenue for delivering tailored and on-demand mental health care.

OBJECTIVE

To address the lack of youth mental health services, we created the Science Technology Engineering Math and Social and Emotional Learning (STEMSEL) study. Our aim was to investigate the efficacy of a digital mental health intervention, Neolth, in enhancing social and emotional well-being, reducing academic stress, and increasing mental health literacy and life skills among adolescents.

METHODS

The STEMSEL study will involve the implementation and evaluation of Neolth across 4 distinct phases. In phase 1, a comprehensive needs assessment will be conducted across 3 diverse schools, each using a range of teaching methods, including in-person, digital, and hybrid modalities. Following this, in phase 2, school administrators and teachers undergo intensive training sessions on Neolth's functionalities and intervention processes as well as understand barriers and facilitators of implementing a digital mental health program at their respective schools. Phase 3 involves recruiting middle and high school students aged 11-18 years from the participating schools, with parental consent and student assent obtained, to access Neolth. Students will then be prompted to complete an intake questionnaire, enabling the customization of available modules to address their specific needs. Finally, phase 4 will include a year-long pre- and posttest pilot study to rigorously evaluate the usability and effectiveness of Neolth in addressing the mental health concerns of students across the selected schools.

RESULTS

Phase 1 was successfully completed in August 2022, revealing significant deficits in mental health resources within the participating schools. The needs assessment identified critical gaps in available mental health support services. We are currently recruiting a diverse group of middle and high school students to participate in the study. The study's completion is scheduled for 2024, with data expected to provide insights into the real-world use of Neolth among the adolescent population. It is designed to deliver findings regarding the intervention's efficacy in addressing the mental health needs of students.

CONCLUSIONS

The STEMSEL study plays a crucial role in assessing the feasibility and adoption of digital mental health interventions within the school-aged youth population in the United States. The findings generated from this study have the potential to dismantle obstacles to accessing mental health assistance and broaden the availability of care through evidence-based strategies.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/59372.

The efficacy of mobile applications for reducing depression in adolescents and young adults: A meta-analysis of randomized control trials

BACKGROUND

Mobile applications for mental health have the potential to aid people with mental health disorders, especially depression, by providing them with tools and coping mechanisms. Adolescents and young adults, being at risk of depressive symptoms and leading mobile users, are among the main targets of using mobile applications to alleviate symptoms.

OBJECTIVE

This study aimed to evaluate the impact of mobile application-based psychological interventions in reducing depression symptoms in adolescents and young adults compared to those not exposed to the intervention.

METHODS

We conducted a meta-analysis focusing on mobile applications for reducing depressive symptoms. We searched two databases: MEDLINE and EMBASE and included randomized controlled trials conducted in English among participants aged 18-35 years old who were assessed for depressive symptoms using a validated screening measure and used mobile applications-based psychological interventions. Two of six independent reviewers conducted study selection, data extraction, and bias assessment. A pooled mean standardized difference (Cohen's d) and 95% CI were calculated using random-effects meta-analysis. Risk of bias was assessed using I2 statistics and forest plot. Egger's test was used for assessing publication bias.

RESULTS

After screening 740 references, we identified 12 trials with 1869 participants, with a mean age of participants ranging from 14.70 to 25.1 years. The interventions ranged from cognitive behavioral therapy (CBT)-based mobile apps to interactive story-telling apps and apps delivering a mix of CBT, interpersonal psychotherapy for adolescents, and dialectical behavior therapy elements. Control groups included information-only, waitlist, no intervention, and treatment as usual. Seven studies used Patient Health Questionnaire-9 (PHQ-9) to assess the severity of depressive symptoms, while the other five used different scales. There was no evidence of publication bias (p = 0.325). The mobile applications reduced depression score by 0.08 units of standardized difference more than the control, with a 95% CI of -0.19 to 0.03 (p = 0.294, I2 = 15.4%) using standardized mean difference (SMD) as the effect estimate. In a sensitivity analysis including only studies that used PHQ-9, we found a similar trend, SMD -0.72 (95%CI -1.48 to 0.03). However, both findings were not significant.

CONCLUSIONS

Current evidence is insufficient to support mobile applications to relieve depression symptoms in adolescents and young adults. Further trials with larger sample size are needed to confirm our findings of a positive trend. With emerging technologies and the high exposure of apps in this population, mobile applications for depression hold promise for the future of treatment and awareness of mental health disorders in this population.

Digital Therapeutics for Improving Effectiveness of Pharmaceutical Drugs and Biological Products: Preclinical and Clinical Studies Supporting Development of Drug + Digital Combination Therapies for Chronic Diseases

Limitations of pharmaceutical drugs and biologics for chronic diseases (e.g., medication non-adherence, adverse effects, toxicity, or inadequate efficacy) can be mitigated by mobile medical apps, known as digital therapeutics (DTx). Authorization of adjunct DTx by the US Food and Drug Administration and draft guidelines on "prescription drug use-related software" illustrate opportunities to create drug + digital combination therapies, ultimately leading towards drug-device combination products (DTx has a status of medical devices). Digital interventions (mobile, web-based, virtual reality, and video game applications) demonstrate clinically meaningful benefits for people living with Alzheimer's disease, dementia, rheumatoid arthritis, cancer, chronic pain, epilepsy, depression, and anxiety. In the respective animal disease models, preclinical studies on environmental enrichment and other non-pharmacological modalities (physical activity, social interactions, learning, and music) as surrogates for DTx "active ingredients" also show improved outcomes. In this narrative review, we discuss how drug + digital combination therapies can impact translational research, drug discovery and development, generic drug repurposing, and gene therapies. Market-driven incentives to create drug-device combination products are illustrated by Humira® (adalimumab) facing a "patent-cliff" competition with cheaper and more effective biosimilars seamlessly integrated with DTx. In conclusion, pharma and biotech companies, patients, and healthcare professionals will benefit from accelerating integration of digital interventions with pharmacotherapies.