ArticleJournal of medical Internet research2021
Behavioral Activation and Depression Symptomatology: Longitudinal Assessment of Linguistic Indicators in Text-Based Therapy Sessions.
Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05194722 (Optimizing Implementation of Mental Health Intervention Within Orthopedic Care), which is not on this map. Cited by 22 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.
Optimizing Implementation of Mental Health Intervention Within Orthopedic Care
Who cites it
22 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Natural language processing for mental health interventions: a systematic review and research framework.Translational psychiatry · 2023Pooled it
- Natural language processing in clinical neuroscience and psychiatry: A review.Frontiers in psychiatry · 2022Pooled it
- Scoping review on natural language processing applications in counselling and psychotherapy.British journal of psychology (London, England : 1953) · 2026Article
- Automated Speech Analysis for Screening and Monitoring Bipolar Depression: Machine Learning Model Development and Interpretation Study.JMIR medical informatics · 2025Article
- Objective speech measures capture depressive symptoms and associated cognitive difficulties.Translational psychiatry · 2025Article
- A randomised cross over trial examining the linguistic markers of depression and anxiety in symptomatic adults.Npj mental health research · 2025Article
- Using natural language processing to identify patterns associated with depression, anxiety, and stress symptoms during the COVID-19 pandemic.Journal of affective disorders · 2025Article
- Beyond electronic health record data: leveraging natural language processing and machine learning to uncover cognitive insights from patient-nurse verbal communications.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- The implementation of digital biomarkers in the diagnosis, treatment and monitoring of mood disorders: a narrative review.Frontiers in digital health · 2025Review
- LLMCARE: early detection of cognitive impairment via transformer models enhanced by LLM-generated synthetic data.Frontiers in artificial intelligence · 2025Article
- Measuring activation during behavioral activation therapy: a proof-of-concept study using smartphone sensors and LLM-derived ratings in adolescents with anhedonia.NPP - digital psychiatry and neuroscience · 2025Article
- Digital phenotyping of depression during pregnancy using self-report data.Journal of affective disorders · 2024Observational
- Linguistic markers of anxiety and depression in Somatic Symptom and Related Disorders: Observational study of a digital intervention.Journal of affective disorders · 2024Observational
- Deep Learning and Geriatric Mental Health.The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry · 2024Review
- Linguistic markers for major depressive disorder: a cross-sectional study using an automated procedure.Frontiers in psychology · 2024Article
- Relationships between daily emotional experiences and smartphone addiction among college students: moderated mediating role of gender and mental health problems.Frontiers in psychology · 2024Article
- Using HIPAA (Health Insurance Portability and Accountability Act)-Compliant Transcription Services for Virtual Psychiatric Interviews: Pilot Comparison Study.JMIR mental health · 2023Article
- The Promise of Affective Language for Identifying and Intervening on Psychopathology.Affective science · 2023Article
- ADscreen: A speech processing-based screening system for automatic identification of patients with Alzheimer's disease and related dementia.Artificial intelligence in medicine · 2023Article
- Deep Representations of First-person Pronouns for Prediction of Depression Symptom Severity.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundBehavioral activation (BA) is rooted in the behavioral theory of depression, which states that increased exposure to meaningful, rewarding activities is a critical factor in the treatment of depression. Assessing constructs relevant to BA currently requires the administration of standardized instruments, such as the Behavioral Activation for Depression Scale (BADS), which places a burden on patients and providers, among other potential limitations. Previous work has shown that depressed and nondepressed individuals may use language differently and that automated tools can detect these differences. The increasing use of online, chat-based mental health counseling presents an unparalleled resource for automated longitudinal linguistic analysis of patients with depression, with the potential to illuminate the role of reward exposure in recovery.
objectiveThis work investigated how linguistic indicators of planning and participation in enjoyable activities identified in online, text-based counseling sessions relate to depression symptomatology over time.
methodsUsing distributional semantics methods applied to a large corpus of text-based online therapy sessions, we devised a set of novel BA-related categories for the Linguistic Inquiry and Word Count (LIWC) software package. We then analyzed the language used by 10,000 patients in online therapy chat logs for indicators of activation and other depression-related markers using LIWC.
resultsDespite their conceptual and operational differences, both previously established LIWC markers of depression and our novel linguistic indicators of activation were strongly associated with depression scores (Patient Health Questionnaire [PHQ]-9) and longitudinal patient trajectories. Emotional tone; pronoun rates; words related to sadness, health, and biology; and BA-related LIWC categories appear to be complementary, explaining more of the variance in the PHQ score together than they do independently.
conclusionsThis study enables further work in automated diagnosis and assessment of depression, the refinement of BA psychotherapeutic strategies, and the development of predictive models for decision support.
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