Effects of a Self-Guided Transdiagnostic Smartphone App on Patient Empowerment and Mental Health: Randomized Controlled Trial

Background: Mental disorders impact both individuals and health systems. Symptoms and syndromes often remain undetected and untreated, resulting in chronification. Besides limited health care resources, within-person barriers such as the lack of trust in professionals, the fear of stigmatization, or the desire to cope with problems without professional help contribute to the treatment gap. Self-guided mental health apps may support treatment seeking by reducing within-person barriers and facilitating mental health literacy. Digital mental health interventions may also improve mental health related self-management skills and contribute to symptom reduction and the improvement of quality of life. Objective: This study aims to investigate the effects of a self-guided transdiagnostic app for mental health on help seeking, reduced stigma, mental health literacy, self-management skills, mental health symptoms, and quality of life using a randomized controlled design. Methods: Overall, 1045 participants (recruited via open, blinded, and web-based recruitment) with mild to moderate depression or anxiety-, sleep-, eating-, or somatization-related psychopathology were randomized to receive either access to a self-guided transdiagnostic mental health app (MindDoc) in addition to care as usual or care as usual only. The core features of the app were regular self-monitoring, automated feedback, and psychological courses and exercises. The coprimary outcomes were mental health literacy, mental health–related patient empowerment and self-management skills (MHPSS), attitudes toward help seeking, and actual mental health service use. The secondary outcomes were psychopathological symptom burden and quality of life. Data were collected at baseline and 8 weeks and 6 months after randomization. Treatment effects were investigated using analyses of covariance, including baseline variables as predictors and applying multiple imputation. Results: We found small but robust between-group effects for MHPSS (Cohen d=0.29), symptoms burden (Cohen d=0.28), and quality of life (Cohen d=0.19) 8 weeks after randomization. The effects on MHPSS were maintained at follow-up. Follow-up assessments also showed robust effects on mental health literacy and preliminary evidence for the improvement of help seeking. Predictors of attrition were lower age and higher personality dysfunction. Among the non-attritors, predictors for deterioration were less outpatient treatment and higher initial symptom severity. Conclusions: A self-guided transdiagnostic mental health app can contribute to lasting improvements in patient empowerment. Symptoms of common mental disorders and quality of life improved faster in the intervention group than in the control group. Therefore, such interventions may support individuals with symptoms of 1 or more internalizing disorders, develop health-centered coping skills, prevent chronification, and accelerate symptom improvement. Although the effects for individual users are small and predictors of attrition and deterioration need to be investigated further, the potential public health impact of a self-guided intervention can be large, given its high scalability. Trial Registration: German Clinical Trials Register DRKS00022531; https://drks.de/search/de/trial/DRKS00022531 JMIR Ment Health 2023;10:e4506

Screening accuracy of a 14-day smartphone ambulatory assessment of depression symptoms and mood dynamics in a general population sample: Comparison with the PHQ-9 depression screening

Introduction Major depression affects over 300 million people worldwide, but cases are often detected late or remain undetected. This increases the risk of symptom deterioration and chronification. Consequently, there is a high demand for low threshold but clinically sound approaches to depression detection. Recent studies show a great willingness among users of mobile health apps to assess daily depression symptoms. In this pilot study, we present a provisional validation of the depression screening app Moodpath. The app offers a 14-day ambulatory assessment (AA) of depression symptoms based on the ICD-10 criteria as well as ecologically momentary mood ratings that allow the study of short-term mood dynamics. Materials and methods N = 113 Moodpath users were selected through consecutive sampling and filled out the Patient Health Questionnaire (PHQ-9) after completing 14 days of AA with 3 question blocks (morning, midday, and evening) per day. The psychometric properties (sensitivity, specificity, accuracy) of the ambulatory Moodpath screening were assessed based on the retrospective PHQ-9 screening result. In addition, several indicators of mood dynamics (e.g. average, inertia, instability), were calculated and investigated for their individual and incremental predictive value using regression models. Results We found a strong linear relationship between the PHQ-9 score and the AA Moodpath depression score (r = .76, p < .001). The app-based screening demonstrated a high sensitivity (.879) and acceptable specificity (.745). Different indicators of mood dynamics covered substantial amounts of PHQ-9 variance, depending on the number of days with mood data that were included in the analyses. Discussion AA and PHQ-9 shared a large proportion of variance but may not measure exactly the same construct. This may be due to the differences in the underlying diagnostic systems or due to differences in momentary and retrospective assessments. Further validation through structured clinical interviews is indicated. The results suggest that ambulatory assessed mood indicators are a promising addition to multimodal depression screening tools. Improving app-based AA screenings requires adapted screening algorithms and corresponding methods for the analysis of dynamic processes over time

Mental health across two years of the COVID-19 pandemic: a 5-wave longitudinal study in Germany

The COVID-19 pandemic has been negatively associated with mental health. However, little is known about the temporal dynamics of mental health in the longer term of the pandemic. We aimed to investigate symptom levels and changes of depression, anxiety, posttraumatic stress, and loneliness spanning two years of the pandemic; and to examine associated risk factors. This five-wave, longitudinal online study from May 2020 to April 2022 included 636 adults (Mage = 39.5 years, SD = 16.11; 84.1% female) from the German general population who completed the international COVID-19 Mental Health Survey. Symptoms of anxiety (Generalized Anxiety Disorder-7; GAD-7), depression (Patient Health Questionnaire-9; PHQ-9), posttraumatic stress (PTSD Checklist for DSM-5; PCL-5), and loneliness (“Do you feel lonely?”) were assessed using mixed-effects models. Associations with anxiety and depressive symptoms were examined with having children, student status, financial worries, contamination fear, and loneliness. PHQ-9, GAD-7, PCL-5, and loneliness scores overall decreased throughout the two-year period of the pandemic but exhibited an increase during two national lockdowns. Controlled for significant associations with female gender and younger age, increased PHQ-9 and GAD-7 scores were associated with contamination fear, financial worries, and loneliness. No associations were found with having children and student status. Symptoms of depression, anxiety, posttraumatic stress, and loneliness decreased over time but varied along with the dynamics of the pandemic. Longitudinal monitoring of mental health in vulnerable subgroups is required, especially those of younger age, females, and the financially insecure

Mental health across two years of the COVID-19 pandemic: a 5-wave longitudinal study in Germany

The COVID-19 pandemic has been negatively associated with mental health. However, little is known about the temporal dynamics of mental health in the longer term of the pandemic. We aimed to investigate symptom levels and changes of depression, anxiety, posttraumatic stress, and loneliness spanning two years of the pandemic; and to examine associated risk factors. This five-wave, longitudinal online study from May 2020 to April 2022 included 636 adults (Mage = 39.5 years, SD = 16.11; 84.1% female) from the German general population who completed the international COVID-19 Mental Health Survey. Symptoms of anxiety (Generalized Anxiety Disorder-7; GAD-7), depression (Patient Health Questionnaire-9; PHQ-9), posttraumatic stress (PTSD Checklist for DSM-5; PCL-5), and loneliness (“Do you feel lonely?”) were assessed using mixed-effects models. Associations with anxiety and depressive symptoms were examined with having children, student status, financial worries, contamination fear, and loneliness. PHQ-9, GAD-7, PCL-5, and loneliness scores overall decreased throughout the two-year period of the pandemic but exhibited an increase during two national lockdowns. Controlled for significant associations with female gender and younger age, increased PHQ-9 and GAD-7 scores were associated with contamination fear, financial worries, and loneliness. No associations were found with having children and student status. Symptoms of depression, anxiety, posttraumatic stress, and loneliness decreased over time but varied along with the dynamics of the pandemic. Longitudinal monitoring of mental health in vulnerable subgroups is required, especially those of younger age, females, and the financially insecure

Associations between oxytocin and vasopressin concentrations, traumatic event exposure and posttraumatic stress disorder symptoms: group comparisons, correlations, and courses during an internet-based cognitive-behavioural treatment

Background: Posttraumatic stress disorder (PTSD) is characterized by impairments in extinction learning and social behaviour, which are targeted by trauma-focused cognitive behavioural treatment (TF-CBT). The biological underpinnings of TF-CBT can be better understood by adding biomarkers to the clinical evaluation of interventions. Due to their involvement in social functioning and fear processing, oxytocin and arginine vasopressin might be informative biomarkers for TF-CBT, but to date, this has never been tested. Objective: To differentiate the impact of traumatic event exposure and PTSD symptoms on blood oxytocin and vasopressin concentrations. Further, to describe courses of PTSD symptoms, oxytocin and vasopressin during an internet-based TF-CBT and explore interactions between these parameters. Method: We compared oxytocin and vasopressin between three groups of active and former male service members of the German Armed Forces (n = 100): PTSD patients (n = 39), deployed healthy controls who experienced a deployment-related traumatic event (n = 33) and non-deployed healthy controls who never experienced a traumatic event (n = 28). PTSD patients underwent a 5-week internet-based TF-CBT. We correlated PTSD symptoms with oxytocin and vasopressin before treatment onset. Further, we analysed courses of PTSD symptoms, oxytocin and vasopressin from pre- to post-treatment and 3 months follow-up, as well as interactions between the three parameters. Results: Oxytocin and vasopressin did not differ between the groups and were unrelated to PTSD symptoms. PTSD symptoms were highly stable over time, whereas the endocrine parameters were not, and they also did not change in mean. Oxytocin and vasopressin were not associated with PTSD symptoms longitudinally. Conclusions: Mainly due to their insufficient intraindividual stability, single measurements of endogenous oxytocin and vasopressin concentrations are not informative biomarkers for TF-CBT. We discuss how the stability of these biomarkers might be increased and how they could be better related to the specific impairments targeted by TF-CBT

Resilience of people with chronic medical conditions during the COVID-19 pandemic: a 1-year longitudinal prospective survey

Backgrounds Individuals with chronic medical conditions are considered highly exposed to COVID-19 pandemic stress, but emerging evidence is demonstrating that resilience is common even among them. We aimed at identifying sustained resilient outcomes and their predictors in chronically ill people during the first year of the pandemic. Methods This international 4-wave 1-year longitudinal online survey included items on socio-demographic characteristics, economic and living situation, lifestyle and habits, pandemic-related issues, and history of mental disorders. Adherence to and approval of imposed restrictions, trust in governments and in scientific community during the pandemic were also investigated. The following tools were administered: the Patient Health Questionnaire, the Generalized Anxiety Disorder scale, the PTSD Checklist DSM-5, the Oslo Social Support Scale, the Padua Inventory, and the Portrait Values Questionnaire. Results One thousand fifty-two individuals reporting a chronic condition out of 8011 total participants from 13 countries were included in the study, and 965 had data available for the final model. The estimated probability of being “sustained-resilient” was 34%. Older male individuals, participants employed before and during the pandemic or with perceived social support were more likely to belong to the sustained-resilience group. Loneliness, a previous mental disorder, high hedonism, fear of COVID-19 contamination, concern for the health of loved ones, and non-approving pandemic restrictions were predictors of not-resilient outcomes in our sample. Conclusions We found similarities and differences from established predictors of resilience and identified some new ones specific to pandemics. Further investigation is warranted and could inform the design of resilience-building interventions in people with chronic diseases

Guided digital health intervention for depression in Lebanon: randomised trial

Background Most people with mental disorders in communities exposed to adversity in low-income and middle-income countries (LMICs) do not receive effective care. Digital mental health interventions are scalable when digital access is adequate, and can be safely delivered during the COVID-19 pandemic. Objective To examine the effects of a new WHO-guided digital mental health intervention, Step-by-Step, supported by a non-specialist helper in Lebanon, in the context of concurring economic, humanitarian and political crises, a large industrial disaster and the COVID-19 pandemic. Methods We conducted a single-blind, two-arm pragmatic randomised trial, comparing guided Step-by-Step with enhanced care as usual (ECAU) among people suffering from depression and impaired functioning. Primary outcomes were depression (Patient Health Questionnaire 9 (PHQ-9)) and impaired functioning (WHO Disability Assessment Schedule-12 (WHODAS)) at post-treatment. Findings 680 people with depression (PHQ-9>10) and impaired functioning (WHODAS>16) were randomised to Step-by-Step or ECAU. Intention-to-treat analyses showed effects on depression (standardised mean differences, SMD: 0.71; 95% CI: 0.45 to 0.97), impaired functioning (SMD: 0.43; 95% CI: 0.21 to 0.65), post-traumatic stress (SMD: 0.53; 95% CI: 0.27 to 0.79), anxiety (SMD: 0.74; 95% CI: 0.49 to 0.99), subjective well-being (SMD: 0.37; 95% CI: 0.12 to 0.62) and self-identified personal problems (SMD: 0.56; 95% CI 0.29 to 0.83). Significant effects on all outcomes were retained at 3-month follow-up. Conclusions Guided digital mental health interventions can be effective in the treatment of depression in communities exposed to adversities in LMICs, although some uncertainty remains because of high attrition

A Feasibility Study of the WHO Digital Mental Health Intervention Step-by-Step to Address Depression Among Chinese Young Adults

Background: Chinese young adults experience barriers to mental health treatment, including the lack of treatment providers and stigma around treatment seeking. Evidence-based digital mental health interventions are promising and scalable alternatives to face-to-face treatment for this population, but lack rigorous evidence to support scale-up in China. Aim: The study was a feasibility study for a large-scale RCT of Step-by-Step, a behavioral activation-based, mental health intervention to address depression and anxiety symptoms in Chinese young adults. It sought to assess feasibility of recruitment and of delivery of Step-by-Step in a University setting, to assess acceptability of the intervention, and to examine potential effectiveness. Method: An uncontrolled, feasibility trial was conducted to assess the feasibility and acceptability of Chinese Step-by-Step for Chinese University students with elevated depressive symptoms (PHQ-9 scores at or above 10) in Macao, China. Data was collected at two different time points (i.e., baseline and 8-weeks after baseline), administered via questionnaires embedded in an interventional mobile application. Participation rate and dropout rate were measured. Depressive and anxiety symptom severity, well-being, and self-defined stress were assessed. Satisfaction with the program was assessed using qualitative interviews. Results: A total of 173 students were screened, 22.0% (n = 38) were eligible, and 63.2% of them (n = 24) started the intervention. The dropout rate by post-test was 45.8%. Results from completers showed that Step-by-Step was potentially effective in reducing depressive and anxiety symptom severity, and self-defined stress. Students were generally satisfied with the program, but also offered suggestions for continued improvement. Qualitative feedback was reported within the RE-AIM framework, covering recruitment, effectiveness, adoption, implementation, and maintenance. Amendments to the program were made according to the feedback (e.g., adding notification for new session, modify the time zone). Conclusion: A minimally guided Step-by-Step protocol and the study procedure were successfully pilot tested for use for Chinese University students. The intervention was acceptable and no adverse events were reported. The results support the potential effectiveness and feasibility of a large-scale evaluation of the program