ArticleBMC psychiatry2024
Demographic and clinical characteristics associated with anxiety and depressive symptom outcomes in users of a digital mental health intervention incorporating a relational agent.
Article in BMC psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05672745 (An Open-label Pilot Study to Learn How the Phenotypical Characteristics of Woebot Users Are Related to Clinical Outcomes), which is not on this map. Cited by 10 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
An Open-label Pilot Study to Learn How the Phenotypical Characteristics of Woebot Users Are Related to Clinical Outcomes
Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 15 citations in OpenAlex.
- Efficacy of internet-based interventions to reduce suicidal ideation: a systematic review and meta-analysis.BMC psychiatry · 2025Pooled it
- The Role of Artificial Intelligence in Clinical Psychology: How AI and NLP Systems Are Reshaping Psychological Interventions. A Systematic Review.Clinical psychology & psychotherapyPooled it
- User Engagement Clusters of an 8-Week Digital Mental Health Intervention Guided by a Relational Agent (Woebot): Exploratory Study.Journal of medical Internet research · 2023Trial
- Artificial Intelligence-Driven Tools in Mental Health Service Delivery: A Scoping Review.Healthcare (Basel, Switzerland) · 2026Review
- Reimagining psychiatric care with agentic AI: promise, challenges, and a roadmap forward.NPJ digital medicine · 2026Review
- Charting the evolution of artificial intelligence mental health chatbots from rule-based systems to large language models: a systematic review.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2025Article
- Advancing Mental Health Care: A Comprehensive Review of Digital Tools and Technologies for Enhancing Diagnosis, Treatment, and Wellness.Health care science · 2025Review
- What are practitioners' views of how digital health interventions may play a role in online child sexual abuse service delivery?Frontiers in digital health · 2024Article
- Systematic review and meta-analysis of AI-based conversational agents for promoting mental health and well-being.NPJ digital medicine · 2023Review
- Engagement, Satisfaction, and Mental Health Outcomes Across Different Residential Subgroup Users of a Digital Mental Health Relational Agent: Exploratory Single-Arm Study.JMIR formative research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDigital mental health interventions (DMHIs) may reduce treatment access issues for those experiencing depressive and/or anxiety symptoms. DMHIs that incorporate relational agents may offer unique ways to engage and respond to users and to potentially help reduce provider burden. This study tested Woebot for Mood & Anxiety (W-MA-02), a DMHI that employs Woebot, a relational agent that incorporates elements of several evidence-based psychotherapies, among those with baseline clinical levels of depressive or anxiety symptoms. Changes in self-reported depressive and anxiety symptoms over 8 weeks were measured, along with the association between each of these outcomes and demographic and clinical characteristics.
methodsThis exploratory, single-arm, 8-week study of 256 adults yielded non-mutually exclusive subsamples with either clinical levels of depressive or anxiety symptoms at baseline. Week 8 Patient Health Questionnaire-8 (PHQ-8) changes were measured in the depressive subsample (PHQ-8 ≥ 10). Week 8 Generalized Anxiety Disorder-7 (GAD-7) changes were measured in the anxiety subsample (GAD-7 ≥ 10). Demographic and clinical characteristics were examined in association with symptom changes via bivariate and multiple regression models adjusted for W-MA-02 utilization. Characteristics included age, sex at birth, race/ethnicity, marital status, education, sexual orientation, employment status, health insurance, baseline levels of depressive and anxiety symptoms, and concurrent psychotherapeutic or psychotropic medication treatments during the study.
resultsBoth the depressive and anxiety subsamples were predominantly female, educated, non-Hispanic white, and averaged 38 and 37 years of age, respectively. The depressive subsample had significant reductions in depressive symptoms at Week 8 (mean change =-7.28, SD = 5.91, Cohen's d = -1.23, p < 0.01); the anxiety subsample had significant reductions in anxiety symptoms at Week 8 (mean change = -7.45, SD = 5.99, Cohen's d = -1.24, p < 0.01). No significant associations were found between sex at birth, age, employment status, educational background and Week 8 symptom changes. Significant associations between depressive and anxiety symptom outcomes and sexual orientation, marital status, concurrent mental health treatment, and baseline symptom severity were found.
conclusionsThe present study suggests early promise for W-MA-02 as an intervention for depression and/or anxiety symptoms. Although exploratory in nature, this study revealed potential user characteristics associated with outcomes that can be investigated in future studies.
trial registrationThis study was retrospectively registered on ClinicalTrials.gov (#NCT05672745) on January 5th, 2023.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.