Background: Although internet-based cognitive behavior therapy (iCBT) interventions can reduce depression symptoms, large differences in their effectiveness exist.
Objective: The aim of this study was to evaluate the effectiveness of an iCBT intervention called Thrive, which was designed to enhance engagement when delivered as a fully automated, stand-alone intervention to a rural community population of adults with depression symptoms.
Methods: Using no diagnostic or treatment exclusions, 343 adults with depression symptoms were recruited from communities using an open-access website and randomized 1:1 to the Thrive intervention group or the control group. Using self-reports, participants were evaluated at baseline and 4 and 8 weeks for the primary outcome of depression symptom severity and secondary outcome measures of anxiety symptoms, work and social adjustment, psychological resilience, and suicidal ideation.
Results: Over the 8-week follow-up period, the intervention group (n=181) had significantly lower depression symptom severity than the control group (n=162; P<.001), with a moderate treatment effect size (d=0.63). Moderate to near-moderate effect sizes favoring the intervention group were observed for anxiety symptoms (P<.001; d=0.47), work/social functioning (P<.001; d=0.39), and resilience (P<.001; d=0.55). Although not significant, the intervention group was 45% less likely than the control group to experience increased suicidal ideation (odds ratio 0.55).
Conclusions: These findings suggest that the Thrive intervention was effective in reducing depression and anxiety symptom severity and improving functioning and resilience among a mostly rural community population of US adults. The effect sizes associated with Thrive were generally larger than those of other iCBT interventions delivered as a fully automated, stand-alone intervention.
Trial Registration: ClinicalTrials.gov NCT03244878; https://clinicaltrials.gov/ct2/show/NCT03244878.
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http://dx.doi.org/10.2196/14754 | DOI Listing |
J Behav Health Serv Res
January 2025
Transitions to Adulthood Center for Research, Department of Psychiatry, UMass Chan Medical Schoo, 222 Maple Avenue, Shrewsbury, MA, 01545, USA.
This study sought to understand how young adults (age 18-25) with histories of mental health disorders are coping with disrupted transitions to adulthood during the COVID-19 pandemic. A cross-sectional web survey was conducted in March-June 2021 of 967 US young adults with pre-pandemic psychiatric disability to assess their current psychiatric status, interrupted transitions, and associations with social determinants including income, community participation, and social context. Mental health was assessed with the Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder Scale (GAD-7), and PTSD Checklist-Civilian Version.
View Article and Find Full Text PDFAnn Fam Med
January 2025
Departments of Psychiatry and Emergency Medicine, University of Arkansas for Medical Sciences, Little Rock, Arkansas.
Purpose: Mental health screening is recommended by the US Preventive Services Task Force for all patients in areas where treatment options are available. Still, it is estimated that only 4% of primary care patients are screened for depression. The goal of this study was to evaluate the efficacy of machine learning technology (Kintsugi Voice, v1, Kintsugi Mindful Wellness, Inc) to detect and analyze voice biomarkers consistent with moderate to severe depression, potentially allowing for greater compliance with this critical primary care public health need.
View Article and Find Full Text PDFCMAJ
January 2025
Schools of Health and Wellbeing (Nakada, Pell, Ho), and Cardiovascular and Metabolic Health (Welsh, Celis-Morales), University of Glasgow, Glasgow, UK; Human Performance Laboratory, Education, Physical Activity and Health Research Unit (Celis-Morales), Universidad Católica del Maule, Talca, Chile; Centro de Investigación en Medicina de Altura (CEIMA) (Celis-Morales), Universidad Arturo Prat, Iquique, Chile.
Background: Anxiety and depression are associated with cardiovascular disease (CVD). We aimed to investigate whether adding measures of anxiety and depression to the American Heart Association Predicting Risk of Cardiovascular Disease Events (PREVENT) predictors improves the prediction of CVD risk.
Methods: We developed and internally validated risk prediction models using 60% and 40% of the cohort data from the UK Biobank, respectively.
Environ Health Prev Med
January 2025
Department of Public Health, School of Medicine, International University of Health and Welfare.
Background: High levels of attention-deficit/hyperactivity disorder (ADHD) traits are associated with various outcomes, including depressive symptoms, functional impairment, and low self-esteem. Additionally, individuals with high levels of ADHD traits are reported to be more adversely affected by fear of coronavirus disease 2019 (COVID-19). The current study aimed to examine whether the association between ADHD traits and outcomes was partially mediated by fear of COVID-19 using mediation analysis.
View Article and Find Full Text PDFBiol Psychiatry Cogn Neurosci Neuroimaging
January 2025
Department of Psychiatry, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
Background: Effective connectivity (EC) analysis provides valuable insights into the directionality of neural interactions, crucial for understanding the mechanisms underlying cognitive and emotional regulation in depressive and anxiety disorders. This study examined EC within key neural networks during working memory (WM) and emotional regulation (ER) tasks in young adults, both healthy and seeking help from mental health professionals for emotional distress.
Methods: Dynamic Causal Modeling (DCM) was employed to analyze EC in two independent samples (n=97 and n=94).
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