ReviewNPJ digital medicine2022
Natural language processing applied to mental illness detection: a narrative review.
Review in NPJ digital medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 109 papers, 7 of them syntheses that pooled it.
What it found
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
109 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- "It's Not Only Attention We Need": Systematic Review of Large Language Models in Mental Health Care.JMIR mental health · 2025Pooled it
- Speech and Language Markers as Longitudinal Predictors of Youth Mental Health: A Systematic Review.Early intervention in psychiatry · 2025Pooled it
- Linguistic markers for identifying post-traumatic stress disorder and associated symptoms: a systematic literature review.Journal of the American Medical Informatics Association : JAMIA · 2025Pooled it
- Application of artificial intelligence and psychosocial functioning in psychosis: a systematic review and meta-analysis.Frontiers in psychiatry · 2025Pooled it
- Implementation of generative AI for the assessment and treatment of autism spectrum disorders: a scoping review.Frontiers in psychiatry · 2025Pooled it
- Self-Administered Interventions Based on Natural Language Processing Models for Reducing Depressive and Anxiety Symptoms: Systematic Review and Meta-Analysis.JMIR mental health · 2024Pooled it
- Machine Learning for Multimodal Mental Health Detection: A Systematic Review of Passive Sensing Approaches.Sensors (Basel, Switzerland) · 2024Pooled it
- Effect of AI-Based Natural Language Feedback on Engagement and Clinical Outcomes in Fully Self-Guided Internet-Based Cognitive Behavioral Therapy for Depression: 3-Arm Randomized Controlled Trial.Journal of medical Internet research · 2026Trial
- Enhancing explainability and performance of the depression detection model on social media utilizing feature engineering and LLMs.Health information science and systems · 2026Article
- Absolutist word usage in spoken language as a marker of depression: an ecological momentary assessment study.BMC psychiatry · 2026Article
- Enhancing Case Formulation Competence in Novice Counselors: A ChatGPT-Assisted Approach Using the 4P Model.Behavioral sciences (Basel, Switzerland) · 2026Article
- Speech and Language Markers of Bipolar Disorder: Challenges and Opportunities.Bipolar disorders · 2026Review
- Speech markers of psychological change following a psychedelic 5-MeO-DMT retreat.Journal of psychopharmacology (Oxford, England) · 2026Article
- Temporal Patterns of Engagement and Sentiment in a Suicide Prevention Mobile App: Three-Year Observational Study.JMIR mental health · 2026Observational
- Article
- Natural Language Processing Applied to Psychiatric Clinical Notes: Scoping Review.JMIR medical informatics · 2026Article
- AI and machine learning for early identification of eating disorders: a narrative review and Indian contextual insights.Eating and weight disorders : EWD · 2026Review
- The missing informant: should we ask adolescents what they tell their AI?European child & adolescent psychiatry · 2026Article
- A large-scale annotated Urdu corpus and deep learning benchmark for mental health classification.Scientific reports · 2026Article
- Computational Analysis of Expressive Behavior in Clinical Assessment.Annual review of clinical psychology · 2026Review
49 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mental illness is highly prevalent nowadays, constituting a major cause of distress in people's life with impact on society's health and well-being. Mental illness is a complex multi-factorial disease associated with individual risk factors and a variety of socioeconomic, clinical associations. In order to capture these complex associations expressed in a wide variety of textual data, including social media posts, interviews, and clinical notes, natural language processing (NLP) methods demonstrate promising improvements to empower proactive mental healthcare and assist early diagnosis. We provide a narrative review of mental illness detection using NLP in the past decade, to understand methods, trends, challenges and future directions. A total of 399 studies from 10,467 records were included. The review reveals that there is an upward trend in mental illness detection NLP research. Deep learning methods receive more attention and perform better than traditional machine learning methods. We also provide some recommendations for future studies, including the development of novel detection methods, deep learning paradigms and interpretable models.
Identifiers
What OpenQuestion holds
Registered trials
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.