Explore the vast range of titles available.

Despite digital mental health services growing at a rapid pace to address global mental health needs, there exist challenges of low engagement and attrition. Ensuring continuity of care in the digital context can positively impact mental health care delivery and adherence to treatment, helping to establish digital mental health interventions (DMHIs) as a viable option for mental health support. This study aimed to examine the impact of adjunct app features of the mental health app Wysa and their ability to promote engagement and adherence to the text-based coaching sessions. This retrospective mixed methods observational study was based on real-world app data from users (n=1213) who subscribed to text-based sessions with mental health coaches (MHCs) between February 1 and July 31, 2022. Their engagement with the adjunct app features, such as brief interventions with the conversational agent, self-management tools, and journaling, was analyzed quantitatively using descriptive statistics. Acceptability of the app features was also assessed using qualitative feedback data. Adherence to sessions with MHCs was compared between app feature users (n=1042, 85.9%) and nonfeature users (n=171, 14.1%) using inferential statistics. Subgroup analysis was not feasible in the absence of demographic and clinical user data, potentially limiting the generalizability of the findings. Findings demonstrated high use of the adjunct app features, which allowed communication with the MHCs in between sessions. The thematic analysis captures user experiences of helpfulness within the app and with the MHCs. The Mann-Whitney U test indicated that users who accessed one or more features completed significantly more sessions compared with users who did not use any feature (Mann-Whitney U=154,085.0; P<.001; rB=0.73) with a large effect size. The odds ratio analysis indicated that users were almost thrice as likely to complete sessions after using the adjunct app features (odds ratio 2.91, 95% CI 2.24-3.38; P<.001). Inclusion of adjunct app features enhances continuity in care delivery between sessions with MHCs and is associated with improved engagement with DMHIs. Further efforts are needed to assess the impact of this approach in DMHIs on clinical mental health outcomes.

Major depressive disorder is a common diagnosis among adolescents. Cognitive behavioral therapy is recommended as the first line of treatment. Digital health interventions, such as apps, could contribute to treatment. Advantages could be easy accessibility and availability, reduced time for face-to-face therapy, and the ability to intensify therapy by incorporating it into the patients' everyday lives. Challenges such as low adherence rates are common in digital health interventions. Therefore, they need to undergo rigorous testing for feasibility and effectiveness. An evaluated, cognitive behavioral therapy-based face-to-face therapy program for depression in adolescents was transformed into an app called e-MICHI. This study examined its feasibility and efficacy for use in blended therapy in outpatient settings. Adolescents aged 12 to 18 years with major depressive disorder receiving outpatient care were recruited from 2 university hospitals (n=36 included in analysis). The e-MICHI intervention combined daily app engagement over 6 weeks with 3 face-to-face sessions with a therapist. Feasibility was measured using various variables, including an adherence score (0=no or little patient engagement to 3=excellent engagement) and engagement rates (number of modules completed, number of messages sent by participants via the in-app messenger), satisfaction ratings from both participants and therapists, as well as participants' ratings of the usefulness of the antidepressant strategies covered in the app and the transfer of these strategies to everyday practice. Trends of efficacy were evaluated from multiple perspectives (participant self-rating, independent rater, or therapist), using the Beck Depression Inventory-II, the Children's Depression Rating Scale-Revised, and the Clinical Global Impressions-Severity Scale. Feasibility metrics were assessed by analyzing their central tendency and dispersion, efficacy data were analyzed using a repeated measures ANOVA. e-MICHI was positively evaluated by both participants and therapists (participants: mean 7.3, SD 1.2 and therapists: mean 7.3, SD 1.1, on a scale from 0=bad to 10=excellent). Participants demonstrated high adherence rates (nearly 80%, n=25, received a \"good\" or \"excellent\" adherence score) and showed overall good engagement (app modules completed [maximum 6]: mean 5.03, SD 1.27 and messages sent via messenger: mean 23, SD 22.1). Participants rated the psychoeducational content of the app as particularly useful and reported consistent practice of the e-MICHI strategies in everyday life. Use of the app was associated with a significant reduction of depressive symptoms (before app use vs 3-month follow-up, Beck Depression Inventory-II: mean -6.76, SD 11.49, P=.01; Children's Depression Rating Scale-Revised: mean -16.45, SD 16.76, P<.001; Clinical Global Impressions-Severity Scale: mean -1.1, SD 1.24, P<.001). While acknowledging its limitations, such as the small number of participants and the limited validity concerning efficacy, this study confirms the feasibility of e-MICHI for treating adolescent depression in outpatient settings.

Mental ill health is a leading cause of disability worldwide, but access to evidence-based support remains limited. Digital mental health interventions offer a timely and low-cost solution. However, improvements in clinical outcomes are reliant on user engagement, which can be low for digital interventions. User characteristics, including demographics and personality traits, could be used to personalize platforms to promote longer-term engagement and improved outcomes. This study aims to investigate how character strengths, a set of positive personality traits, influence engagement patterns with moderated online social therapy, a national digital mental health platform offering individualized, evidence-based digital mental health treatment for young people aged 12-25 years. Data from 6967 young people who enrolled with moderated online social therapy between August 2021 and July 2023 were analyzed. Longitudinal analyses were used to investigate whether scores on 3-character strength dimensions (\"social harmony,\" \"positive determination,\" and \"courage and creativity\") were associated with (1) an accelerated or decelerated rate of dropout from the platform and (2) patterns of engagement over the first 12 weeks following onboarding. Engagement metrics were time spent on the platform, number of sessions on the platform, use of the embedded social network, and messages with the clinical team. On average, young people used the platform for 72.64 (SD 106.64) days. The 3-character strengths were associated with distinct engagement patterns during this time. Individuals scoring higher on \"social harmony\" demonstrated an accelerated dropout rate (coefficient=-0.15, 95% CI -0.26 to -0.04; P=.008). Interestingly, higher scores on this character strength were associated with high rates of initial engagement but a more precipitous decline in platform use over the first 12 weeks, in terms of time spent on the platform (β=-.01; SE 0.00; t2748=-5.05; P<.001) and the number of sessions completed (β=-.00; SE 0.00; t2837=-2.26; P=.02). In contrast, higher scores on \"positive determination\" and \"courage and creativity\" predicted more modest initial platform use but steadier engagement over time, in terms of time spent on the platform (\"positive determination\": β=.01; SE 0.00; t2748=4.05; P<.001 and \"courage and creativity\": β=.01; SE 0.00; t2748=2.66; P=.008). Contrary to our predictions, character strengths did not predict use of the embedded social network or the number of messages sent to the clinical team. Our findings illustrate how character strengths predict distinct engagement trajectories on a digital mental health platform. Specifically, individuals higher on \"social harmony\" showed high initial engagement that quickly declined, while those higher on \"positive determination\" and \"courage and creativity\" demonstrated lower initial engagement but a steadier use of the platform over time. The findings of this study demonstrate an opportunity for digital mental health interventions to be tailored to individual characteristics in a way that would promote greater initial and ongoing engagement.

Major depressive disorder (MDD) affects millions of Americans each year and is often diagnosed and treated in primary care. Evidence shows that self-management techniques, shared decision-making (SDM), and goal setting are effective strategies for managing MDD, but the required collaboration between patients and primary care clinicians can be difficult. Primary Care Path is a program for supporting depression management in primary care that includes a patient-facing mobile app and an accompanying care team-facing web interface. Leveraging programs that provide clinician-facing software with companion patient-facing mobile technology may help patients and physicians align depression treatment and management goals, support effective SDM, alleviate barriers, and improve both clinical care and patient outcomes. To pilot-test the use of Primary Care Path for MDD management in primary care and evaluate the impact of its use on depression treatment, symptoms, goal setting and attainment, and SDM. Four primary care clinical practices in the United States were assigned to program use (2 practices; intervention) versus usual care (2 practices; control). Intervention practices used the Primary Care Path program in their clinics and engaged patient participants in app use for 18 weeks. Clinical care teams engaged with the patient-informed program portal primarily during patient encounters (in-person, virtual or calls). Patient participants were smartphone users aged 18 years and older who were being treated for MDD. Patient participants received online surveys (medication changes, Patient Health Questionnaire-9 [PHQ-9], goal setting and attainment questions, and Shared Decision-Making Questionnaire-9 [SDM-Q-9]) at baseline, 6, 12, and 18 weeks. A total of 76 patient participants (34 intervention; 42 control) were enrolled; the majority were female (27/34, 79%; 32/42, 76%), White (31/34, 91%; 40/42, 95%), non-Hispanic/Latino/a (29/34, 85%; 40/40, 100%), and employed (26/34, 77%; 34/42, 81%). Control patient participants' conversations with their medical providers increased over the study period, while intervention patient conversations with their medical providers decreased over time. At week 18, intervention participants felt more successful than control in achieving their personalized treatment goals. More intervention patient participants initiated antidepressant medication by weeks 12 (P=.03) and 18 (P=.04) and switched medications by weeks 6 (P=.009) and 12 (P=.04) versus control. All patient participants demonstrated significant improvement in PHQ-9 scores throughout the study period (P<.001), with no difference in change by group. Clinicians and patients indicated using the program to support SDM, but no significant differences were observed in SDM-Q-9 between intervention and control. Preliminarily, the use of this digital health program related to earlier medication optimization, earlier conversations between patients and medical providers, and patient attainment of goals that matter most to them, indicating that coordinated use of the program by both patients and clinical team members may enhance MDD management in primary care clinical settings.

Digital coaching programs, offering virtually delivered mental health care by coaches and companion apps, are an increasingly popular care model designed to increase accessibility and reduce strain on traditional mental health care systems. Initial studies suggest these programs can produce a range of positive mental health outcomes; however, methodological limitations and a focus on homogeneous, subclinical populations have constrained conclusions about their effectiveness, especially in diverse and clinically severe samples. This study aimed to evaluate the impact of an evidence-based digital mental health coaching program in a clinically and demographically diverse sample. The study compared engagement with app-based content and changes in depression, anxiety, and stress symptoms, over the course of 1 month, among users who received coaching versus those who used the app alone (controls). Program users (N=64) were categorized as coaching users (attending at least 1 session) or controls (app-only users). Depression, anxiety, and stress symptoms were assessed using the Depression Anxiety Stress Scale-21 at baseline and after 30 days. Engagement with app content was also measured. Between-group differences were analyzed using t tests and mixed multivariate analysis of covariance models, with follow-up sensitivity analysis of covariance analyses (controlling for age). Participants were diverse in terms of demographics and clinical severity, with half reporting severe to extremely severe depression and nearly half reporting severe to extremely severe anxiety or stress at baseline. A repeated-measures multivariate analysis of covariance revealed a significant group-by-time interaction (P=.02), indicating greater symptom reduction among coaching users, primarily driven by changes in anxiety and stress. Follow-up analyses of covariance exploring symptom-specific patterns, excluding participants with subclinical baseline symptoms, yielded significant group-by-time interactions across depression (P=.04), anxiety (P=.003), and stress (P=.03). Engagement with app-based content did not significantly differ between the groups (P=.20), suggesting coaching's effectiveness was not contingent on differential app usage. This study demonstrates that digital mental health coaching can significantly improve clinical outcomes, even in diverse and clinically severe populations. These findings challenge the notion that coaching is only effective for subclinical or high-functioning individuals and highlight its potential to extend the reach of mental health care to underserved communities.

College students commonly struggle with procrastination, which is linked to mental health complaints and poor academic performance. Interventions based on cognitive behavioral therapy can be effective in reducing procrastination. Traditional face-to-face therapy and online interventions have shown promising outcomes, with the latter overcoming help-seeking barriers such as lengthy referral processes and waiting lists. This study aims to examine the feasibility and acceptability of a new eHealth intervention targeting procrastination for college students (\"GetStarted\") with guidance by student e-coaches. This cognitive behavioral therapy-based intervention was designed specifically for and together with the target demographic of students studying in the Netherlands. Guidance was offered by trained clinical psychology students in the form of written motivational, supportive messages. We conducted a single-arm study. The primary outcomes were satisfaction (8-item Client Satisfaction Questionnaire [CSQ-8]), usability (10-item System Usability Scale [SUS-10]), and adherence (completion rate). The secondary outcomes were changes to procrastination (Irrational Procrastination Scale [IPS]), depression (9-item Patient Health Questionnaire [PHQ-9]), stress (10-item Perceived Stress Scale [PSS-10]), quality of life (Mental Health Quality of Life Questionnaire [MHQoL]), and e-coaching satisfaction (Working Alliance Inventory for Guided Internet Interventions [WAI-I]). Of 734 participants who started the intervention, 335 (45.6%) completed the posttest. Students reported being satisfied with the intervention (CSQ-8: mean 23.48, SD 3.23) and found it very usable (SUS-10: mean 34.39, SD 4.52). Regarding adherence, participants completed 68.95% of the intervention on average, while 36.65% (n=269) of participants completed the full intervention. Participants showed a significant decrease in procrastination (IPS: mean decrease 35.39-32.56, Cohen d=0.63), depression (PHQ-9: mean decrease 9.27-7.73, Cohen d=0.35), and stress (PSS-10: mean decrease 20.79-19.02, Cohen d=0.31) as well as an increase in quality of life (MHQoL: mean increase 12.81-13.65, Cohen d=0.37) from baseline to posttest to follow-up. Participants reported a moderate-to-strong alliance with their e-coach (WAI-I: mean 45.26, SD 7.72). The internet-based, student-guided intervention \"GetStarted\" targeting procrastination appears to be acceptable and feasible for college students in the Netherlands. However, high attrition rates and the lack of a control group mean that results must be interpreted with caution. To further examine intervention effectiveness, a randomized controlled trial needs to be conducted.

Digital mental health (dMH) interventions offer the ability to reach many more adolescents with anxiety than face-to-face therapy. While efficacious dMH interventions are available for adolescents, premature dropout and low engagement are common, especially if delivered on a self-help basis without any form of therapist guidance. This is concerning, given that higher engagement, in terms of the number of sessions completed, has been repeatedly associated with improved clinical outcomes. The reasons for poor adolescent engagement in dMH programs are unclear. A clear understanding of when and why disengagement occurs is important in order to seek to improve engagement rates. Contemporary models consider engagement as multifaceted, comprising both \"use\" (eg, amount of content completed, frequency of use, duration spent logged into the dMH program, and depth of use, such as word or character count) and \"user experience\" (eg, interest and satisfaction in the program and affect and attention whilst engaging in the program). This study investigated the role of demographic and early engagement (EE) factors, specifically program use, in predicting overall program engagement and continued engagement, respectively, in a self-directed, internet-based cognitive behavioral therapy program for adolescent anxiety, namely, BRAVE Self-Help. It examined multiple measures of program use, including task completion, homework completion, and depth of response (character count of responses typed into program tasks). It also examined the moderating role of baseline anxiety severity. Data collected between July 2014 and May 2020 from 2850 adolescents aged 12 to 18 years who participated in BRAVE Self-Help were analyzed via a series of moderated regressions. Results showed that EE (in terms of program use) was associated with continued engagement, demonstrated by early tasks (tasks completed in the first two sessions; R2=0.035; P<.001) and early depth (characters written in the first two sessions; R2=0.08; P<.001) predicting continued depth of program response (total character count of responses typed into all program tasks from sessions 3 to 10). Demographic factors and anxiety severity did not directly impact adolescents' engagement in BRAVE Self-Help. These findings highlight the need to investigate ways to (1) enhance EE and (2) better understand how to measure and capture all aspects of program engagement.

Health anxiety by proxy is characterized by ruminations about severe illness in one's child that can cause severe distress in affected parents. Health anxiety by proxy may lead to repeated unnecessary medical consultations and checking the child's body for symptoms, as well as heightened attention to their child's behavior, sign of illness, and bodily symptoms. It has been hypothesized that health anxiety by proxy may pose a risk for transmission of maladaptive symptom coping and health anxiety from the parent to their child. In spite of this, no targeted treatment has previously been evaluated. Therefore, we developed an internet-delivered psychological treatment containing 8 modules based on cognitive behavioral therapy and acceptance and commitment therapy. The objective of this study was to investigate the feasibility and effect of the internet-delivered treatment PROXY for parents with health anxiety by proxy. A total of 4 participants with health anxiety by proxy entered a replicated randomized single-case experimental design. They were randomly allocated to a baseline period of 7-26 days before entering the 8-week treatment and 14-33 days follow-up phase. The primary outcomes were daily measures of anxiety, impact of anxiety, and value-based actions measured using 5 questions answered on a scale of 1-10 through a text-message link. The primary outcomes were analyzed using visual analysis and supplemented with statistical randomization tests. Secondary outcomes were standardized questionnaire measures of anxiety-related symptoms, experience of the treatment, and negative effects of the treatment reported using descriptive statistics for each participant individually. Visual and statistical analyses indicated that PROXY was an effective treatment for 2 participants as the primary outcomes changed in the preferable direction for both of them. The effect of PROXY was questionable for the remaining 2 participants, although visual analysis showed that the impact of anxiety decreased for one of them. The 2 participants with questionable effect also thought that the treatment was too short. All 4 participants were happy with the treatment, but 2 participants experienced that health anxiety for their own health deteriorated during treatment. PROXY holds potential as a treatment for HA by proxy. However, more work is required to determine when and how PROXY should be introduced to parents with HA by proxy, particularly in relation to duration of treatment, possible comorbidities, and the need for findings to be replicated in larger groups.

Alcohol consumption is a leading cause of death and disability worldwide, associated with numerous acute and chronic medical conditions. Digital health interventions offer a promising solution to overcome barriers associated with traditional treatment methods, providing accessible, scalable, and cost-effective means to support individuals in reducing hazardous drinking. This pilot study aims to evaluate the feasibility, acceptability, and preliminary efficacy of the Sober smartphone app in individuals with hazardous alcohol use. This single-group, pre- and postpilot study included 20 participants with risky alcohol use, identified using the Alcohol Use Disorder Identification Test. Participants used the Sober app for 4 weeks, incorporating cognitive behavioral therapy-based interventions. Feasibility was assessed by study and session completion rates, acceptability by participant satisfaction and perceived usefulness, and preliminary efficacy by changes in alcohol consumption and psychiatric symptoms. Semistructured interviews with participants and clinicians provided qualitative perspectives on the app's usability, efficacy, and areas for improvement. Of the 20 enrolled participants, 17 completed the study. The app demonstrated high feasibility with an 85% (17/20) study completion rate, and 59% (10/17) completed all cognitive behavioral therapy sessions. Participants reported positive acceptability, with average satisfaction and usefulness ratings of 3.8 and 3.7 of 5, respectively. Preliminary efficacy outcomes showed significant improvements: abstinence days increased from 67% to 85% (z=-3.17; P=.002), heavy drinking episodes decreased from 3.3 to 1.9 (t16=-2.97; P=.003), and total alcohol consumption reduced from 456.8 to 195.9 mL (t16=3.16; P=.002). Alcohol Use Disorder Identification Test scores dropped from 17.5 to 10.7 (t16=4.51; P<.001). Additionally, depression (Patient Health Questionnaire-9) scores decreased from 5.8 to 4.4 (t16=2.91; P=.01), and anxiety (Generalized Anxiety Disorder-7) scores from 3.4 to 2.1 (z=-2.80; P=.005). No adverse events were reported. Qualitative analysis found participants valued daily logging but noted usability issues, while clinicians called for tailored goals, enhanced communication features, and age-specific content. The mobile app Sober shows promise as an effective tool for reducing hazardous alcohol consumption and improving related psychiatric symptoms. The study demonstrated high feasibility and positive acceptability, with significant preliminary efficacy in reducing alcohol use. Qualitative findings provided actionable evidence for refining the app's usability and clinical integration. Further research through a randomized controlled trial is warranted to confirm these findings and optimize the app's features and content.

The targeted application and design of digital health interventions (DHIs) require an understanding of usage determinants. Usage includes uptake (initial use) and frequency (extent of use), but it is unclear whether both components are driven by the same determinants. This study aimed to examine the determinants of uptake and frequency of use and assess whether they differ. The investigated DHI was a web portal provided in an intervention for improving disease-related self-management. This study is a secondary analysis of intervention group data from a parallel-group randomized controlled trial. Eligibility criteria were being an adult and being diagnosed with type 2 diabetes and/or coronary heart disease. Sociodemographic, psychological, and health-related variables were examined as determinants. Determinants were analyzed using simple and multiple regression models. Uptake was analyzed using logistic regression, and frequency was analyzed using negative binomial regression with robust SEs. Frequency was analyzed for those who used the DHI at least once. Except for sociodemographic variables, all other variables were standardized to a range from 0 to 1. For simple regression, inflation of the α error due to multiple testing was controlled via the approach of Benjamini and Hochberg, and for multiple regression, it was controlled via the significance of the complete multiple regression model. Of 462 intervention group members, 199 (43.1%) used the web portal at least once. After controlling for inflation of the α error, simple regression for uptake yielded significant effects for higher education (B=0.56, 95% CI 0.18-0.95; P=.004), openness (B=1.08, 95% CI 0.33-1.83; P=.005), intention regarding physical activity (B=2.28, 95% CI 1.30-3.26; P<.001), and intention regarding healthy nutrition (B=2.30, 95% CI 1.30-3.31; P<.001). The multiple regression model for uptake was highly significant (P<.001), with significant positive associations for intentions regarding physical activity (B=1.86, 95% CI 0.74-2.97; P=.001) and healthy nutrition (B=2.22, 95% CI 1.00-3.44; P<.001), as well as a significant negative association for patient activation (B=-3.20, 95% CI -4.95 to -1.46; P<.001). After controlling for inflation of the α error, simple regression for frequency yielded no statistically significant effect, and the multiple regression model for frequency was not significant (P=.07). This study is innovative in jointly examining determinants of the uptake and frequency of use of the same DHI within a single context and sample. By demonstrating that factors driving uptake do not necessarily increase the frequency of use, it advances existing research. The study contributes to a more differentiated understanding of DHI use and shows that distinct strategies are required to promote adoption versus sustained engagement. Applying this approach to other DHIs and settings may support more targeted and equitable digital health implementation in real-world contexts, thereby optimizing digital health deployment strategies overall.