Personalised app-based relapse prevention of depressive and anxiety disorders in remitted adolescents and young adults:a protocol of the StayFine RCT

INTRODUCTION: Youth in remission of depression or anxiety have high risks of relapse. Relapse prevention interventions may prevent chronicity. Aim of the study is therefore to (1) examine efficacy of the personalised StayFine app for remitted youth and (2) identify high-risk groups for relapse and resilience. METHOD AND ANALYSIS: In this Dutch single-blind parallel-group randomised controlled trial, efficacy of app-based monitoring combined with guided app-based personalised StayFine intervention modules is assessed compared with monitoring only. In both conditions, care as usual is allowed. StayFine modules plus monitoring is hypothesised to be superior to monitoring only in preventing relapse over 36 months. Participants (N=254) are 13–21 years and in remission of depression or anxiety for >2 months. Randomisation (1:1) is stratified by previous treatment (no treatment vs treatment) and previous episodes (1, 2 or >3 episodes). Assessments include diagnostic interviews, online questionnaires and monitoring (ecological momentary assessment with optional wearable) after 0, 4, 12, 24 and 36 months. The StayFine modules are guided by certified experts by experience and based on preventive cognitive therapy and ingredients of cognitive behavioural therapy. Personalisation is based on shared decision-making informed by baseline assessments and individual symptom networks. Time to relapse (primary outcome) is assessed by the Kiddie Schedule for Affective Disorders and Schizophrenia-lifetime version diagnostic interview. Intention-to-treat survival analyses will be used to examine the data. Secondary outcomes are symptoms of depression and anxiety, number and duration of relapses, global functioning, and quality of life. Mediators and moderators will be explored. Exploratory endpoints are monitoring and wearable outcomes. ETHICS, FUNDING AND DISSEMINATION: The study was approved by METC Utrecht and is funded by the Netherlands Organisation for Health Research and Development (636310007). Results will be submitted to peer-reviewed scientific journals and presented at (inter)national conferences. TRIAL REGISTRATION NUMBER: NCT05551468; NL8237

Congruency of multimodal data-driven personalization with shared decision-making for StayFine:individualized app-based relapse prevention for anxiety and depression in young people

Tailoring interventions to the individual has been hypothesized to improve treatment efficacy. Personalization of target-specific underlying mechanisms might improve treatment effects as well as adherence. Data-driven personalization of treatment, however, is still in its infancy, especially concerning the integration of multiple sources of data-driven advice with shared decision-making. This study describes an innovative type of data-driven personalization in the context of StayFine, a guided app-based relapse prevention intervention for 13- to 21-year-olds in remission of anxiety or depressive disorders ( n = 74). Participants receive six modules, of which three are chosen from five optional modules. Optional modules are Enhancing Positive Affect, Behavioral Activation, Exposure, Sleep, and Wellness. All participants receive Psycho-Education, Cognitive Restructuring, and a Relapse Prevention Plan. The personalization approach is based on four sources: (1) prior diagnoses (diagnostic interview), (2) transdiagnostic psychological factors (online self-report questionnaires), (3) individual symptom networks (ecological momentary assessment, based on a two-week diary with six time points per day), and subsequently, (4) patient preference based on shared decision-making with a trained expert by experience. This study details and evaluates this innovative type of personalization approach, comparing the congruency of advised modules between the data-driven sources (1-3) with one another and with the chosen modules during the shared decision-making process (4). The results show that sources of data-driven personalization provide complementary advice rather than a confirmatory one. The indications of the modules Exposure and Behavioral Activation were mostly based on the diagnostic interview, Sleep on the questionnaires, and Enhancing Positive Affect on the network model. Shared decision-making showed a preference for modules improving positive concepts rather than combating negative ones, as an addition to the data-driven advice. Future studies need to test whether treatment outcomes and dropout rates are improved through personalization. </p

Effectiveness and moderators of individual cognitive behavioral therapy versus treatment as usual in clinically depressed adolescents:A randomized controlled trial

We examined if manualized cognitive behavioral therapy (CBT) was more effective than Treatment As Usual (TAU) for clinically depressed adolescents within routine care. This multisite Randomized controlled trail included 88 clinically depressed adolescents (aged 12-21 years) randomly assigned to CBT or TAU. Multiple assessments (pre-, post treatment and six-month follow-up) were done using semi-structured interviews, questionnaires and ratings and multiple informants. The primary outcome was depressive or dysthymic disorder based on the KSADS. Completers, CBT (n = 19) and TAU (n = 26), showed a significant reduction of affective diagnoses at post treatment (76% versus 76%) and after six months (90% versus 79%). Intention-to-treat analyses on depressive symptoms showed that 41.6% within CBT and 31.8% within the TAU condition was below clinical cut-off at post treatment and after six-months, respectively 61.4% and 47.7%. No significant differences in self-reported depressive symptoms between CBT and TAU were found. No prediction or moderation effects were found for age, gender, child/parent educational level, suicidal criteria, comorbidity, and severity of depression. We conclude that CBT did not outperform TAU in clinical practice in the Netherlands. Both treatments were found to be suitable to treat clinically referred depressed adolescents. CBT needs further improvement to decrease symptom levels below the clinical cut-off at post treatment

Congruency of multimodal data-driven personalization with shared decision-making for StayFine: individualized app-based relapse prevention for anxiety and depression in young people

Tailoring interventions to the individual has been hypothesized to improve treatment efficacy. Personalization of target-specific underlying mechanisms might improve treatment effects as well as adherence. Data-driven personalization of treatment, however, is still in its infancy, especially concerning the integration of multiple sources of data-driven advice with shared decision-making. This study describes an innovative type of data-driven personalization in the context of StayFine, a guided app-based relapse prevention intervention for 13- to 21-year-olds in remission of anxiety or depressive disorders ( n = 74). Participants receive six modules, of which three are chosen from five optional modules. Optional modules are Enhancing Positive Affect, Behavioral Activation, Exposure, Sleep, and Wellness. All participants receive Psycho-Education, Cognitive Restructuring, and a Relapse Prevention Plan. The personalization approach is based on four sources: (1) prior diagnoses (diagnostic interview), (2) transdiagnostic psychological factors (online self-report questionnaires), (3) individual symptom networks (ecological momentary assessment, based on a two-week diary with six time points per day), and subsequently, (4) patient preference based on shared decision-making with a trained expert by experience. This study details and evaluates this innovative type of personalization approach, comparing the congruency of advised modules between the data-driven sources (1-3) with one another and with the chosen modules during the shared decision-making process (4). The results show that sources of data-driven personalization provide complementary advice rather than a confirmatory one. The indications of the modules Exposure and Behavioral Activation were mostly based on the diagnostic interview, Sleep on the questionnaires, and Enhancing Positive Affect on the network model. Shared decision-making showed a preference for modules improving positive concepts rather than combating negative ones, as an addition to the data-driven advice. Future studies need to test whether treatment outcomes and dropout rates are improved through personalization

Is Digital Treatment the Holy Grail? Literature Review on Computerized and Blended Treatment for Depressive Disorders in Youth

Computerized and blended treatments seem to be an attractive treatment for adolescents as an alternative to face-to-face treatment, but mental health professionals seem hesitant to use these treatment modalities. This review provides an overview of factors contributing to and withholding from using computerized or blended treatment in routine care. Three databases were searched with terms related to (1) adolescents, (2) depression, (3) computerized or blended, and (4) treatment. Of the 33 articles identified, 10 focused on unguided computerized treatments, six on guided, two on blended, two compared unguided, blended- and face-to-face treatment to no treatment, and eight studies on games. Further, two articles that were focused on an online monitoring tool and three on intervention characteristics or preferred modes of help-seeking. Evidence for effectiveness, adherence, drop-out, and forming therapeutic relations were suspected to be barriers, but are no reason to reject computerized or blended treatment. Improvement in mental health literacy and the possibility to tailor the intervention are facilitators. However, adolescents&rsquo; intention to seek help, acceptability of computerized treatment, symptom severity, time spent by therapist, and other facilities are identified as barriers and they need to be taken into account when using computerized or blended interventions. Nevertheless, computerized and blended are promising treatments for depressed youth

Is Digital Treatment the Holy Grail? Literature Review on Computerized and Blended Treatment for Depressive Disorders in Youth

Computerized and blended treatments seem to be an attractive treatment for adolescents as an alternative to face-to-face treatment, but mental health professionals seem hesitant to use these treatment modalities. This review provides an overview of factors contributing to and withholding from using computerized or blended treatment in routine care. Three databases were searched with terms related to (1) adolescents, (2) depression, (3) computerized or blended, and (4) treatment. Of the 33 articles identified, 10 focused on unguided computerized treatments, six on guided, two on blended, two compared unguided, blended- and face-to-face treatment to no treatment, and eight studies on games. Further, two articles that were focused on an online monitoring tool and three on intervention characteristics or preferred modes of help-seeking. Evidence for effectiveness, adherence, drop-out, and forming therapeutic relations were suspected to be barriers, but are no reason to reject computerized or blended treatment. Improvement in mental health literacy and the possibility to tailor the intervention are facilitators. However, adolescents’ intention to seek help, acceptability of computerized treatment, symptom severity, time spent by therapist, and other facilities are identified as barriers and they need to be taken into account when using computerized or blended interventions. Nevertheless, computerized and blended are promising treatments for depressed youth

Long Term Outcomes of Blended CBT Compared to Face-to-Face CBT and Treatment as Usual for Adolescents with Depressive Disorders: Analyses at 12 Months Post-Treatment

Depression is a major problem in youth mental health and identified as the leading cause of disability worldwide. There is ample research on the acute effects of treatment, with estimated small-to-moderate effect sizes. However, there is a lack of research on long-term outcomes. A total of 129 adolescents with clinical depression (82.2% female), aged 13–22 (M = 16.60, SD = 2.03), received blended CBT, face-to-face CBT or treatment as usual. Data were collected at 12 months after the intervention and compared between treatment conditions. Clinical diagnosis, depressive symptoms, suicide risk, internalizing symptoms and externalizing symptoms decreased significantly over time, from baseline to the 12-month follow-up, and also from post-treatment to the 12-month follow-up in all three conditions. Changes were not significantly different between conditions. At the long-term, improvements following the treatment continued. Due to the large amount of missing data and use of history control condition, our findings need to be interpreted with caution. However, we consider these findings as a clinical imperative. More evidence might contribute to convincing adolescents to start with therapy, knowing it has lasting effects. Further, especially for adolescents for whom it is not possible to receive face-to-face treatment, blended treatment might be a valuable alternative. Our findings might contribute to the implementation of blended CBT. View Full-Tex

Personalised app-based relapse prevention of depressive and anxiety disorders in remitted adolescents and young adults: A protocol of the StayFine RCT

Introduction Youth in remission of depression or anxiety have high risks of relapse. Relapse prevention interventions may prevent chronicity. Aim of the study is therefore to (1) examine efficacy of the personalised StayFine app for remitted youth and (2) identify high-risk groups for relapse and resilience. Method and analysis In this Dutch single-blind parallel-group randomised controlled trial, efficacy of app-based monitoring combined with guided app-based personalised StayFine intervention modules is assessed compared with monitoring only. In both conditions, care as usual is allowed. StayFine modules plus monitoring is hypothesised to be superior to monitoring only in preventing relapse over 36 months. Participants (N=254) are 13-21 years and in remission of depression or anxiety for >2 months. Randomisation (1:1) is stratified by previous treatment (no treatment vs treatment) and previous episodes (1, 2 or >3 episodes). Assessments include diagnostic interviews, online questionnaires and monitoring (ecological momentary assessment with optional wearable) after 0, 4, 12, 24 and 36 months. The StayFine modules are guided by certified experts by experience and based on preventive cognitive therapy and ingredients of cognitive behavioural therapy. Personalisation is based on shared decision-making informed by baseline assessments and individual symptom networks. Time to relapse (primary outcome) is assessed by the Kiddie Schedule for Affective Disorders and Schizophrenia-lifetime version diagnostic interview. Intention-to-treat survival analyses will be used to examine the data. Secondary outcomes are symptoms of depression and anxiety, number and duration of relapses, global functioning, and quality of life. Mediators and moderators will be explored. Exploratory endpoints are monitoring and wearable outcomes. Ethics, funding and dissemination The study was approved by METC Utrecht and is funded by the Netherlands Organisation for Health Research and Development (636310007). Results will be submitted to peer-reviewed scientific journals and presented at (inter)national conferences. Trial registration number NCT05551468; NL8237