ArticlePsychological medicine2016
Self-reference in psychosis and depression: a language marker of illness.
Article in Psychological medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
33 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A Systematic Review of the Use of Blogs and Vlogs as Self-Expressors for People with Serious and Common Mental Illness.The Psychiatric quarterly · 2026Pooled it
- Lowering costs for large-scale screening in psychosis: a systematic review and meta-analysis of performance and value of information for speech-based psychiatric evaluation.Revista brasileira de psiquiatria (Sao Paulo, Brazil : 1999)Pooled it
- Shared and Distinct Time-Space Experiences Along the Psychotic-Affective Continuum.Schizophrenia bulletin · 2026Article
- Diagnostic Utility of Formal Thought Disorder Between Affective and Non-Affective Psychosis: A Machine Learning Approach.The Psychiatric quarterly · 2026Article
- Detecting Features of Interpersonal Difficulties in First-Person Accounts of Schizophrenia; Automated Linguistic and Network Analyses.Schizophrenia bulletin open · 2026Article
- Real-world conversations across the schizophrenia spectrum: Implementing passive audio sensing to examine linguistic style matching.Journal of psychopathology and clinical science · 2025Article
- Collecting language, speech acoustics, and facial expression to predict psychosis and other clinical outcomes: strategies from the AMP® SCZ initiative.Schizophrenia (Heidelberg, Germany) · 2025Article
- Comparing traditional natural language processing and large language models for mental health status classification: a multi-model evaluation.Scientific reports · 2025Article
- Discrimination of Speech Content in Unipolar Depression and Bipolar Mania: A Computer-Based Analysis with "General Inquirer".Turk psikiyatri dergisi = Turkish journal of psychiatry · 2025Article
- Deeper insight into speech characteristics of patients at ultra-high risk using classification and explainability models.Frontiers in psychiatry · 2025Article
- Tell Me about yourself: Analyzing self-referential language use in borderline personality disorder.Journal of psychiatric research · 2024Article
- Article
- Using Large Language Models to Understand Suicidality in a Social Media-Based Taxonomy of Mental Health Disorders: Linguistic Analysis of Reddit Posts.JMIR mental health · 2024Article
- Using HIPAA (Health Insurance Portability and Accountability Act)-Compliant Transcription Services for Virtual Psychiatric Interviews: Pilot Comparison Study.JMIR mental health · 2023Article
- Lower cohesion and altered first-person pronoun usage in the spoken life narratives of individuals with schizophrenia.Schizophrenia research · 2023Article
- An evolutionary account of impairment of self in cognitive disorders.Cognitive processing · 2023Article
- Posting patterns in peer online support forums and their associations with emotions and mood in bipolar disorder: Exploratory analysis.PloS one · 2023Article
- What Are the Characteristics of User Texts and Behaviors in Chinese Depression Posts?International journal of environmental research and public health · 2022Article
- Machine learning of language use on Twitter reveals weak and non-specific predictions.NPJ digital medicine · 2022Article
- Facing the pandemic and lockdown: an insight on mental health from a longitudinal study using diaries.Schizophrenia (Heidelberg, Germany) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
backgroundLanguage use is of increasing interest in the study of mental illness. Analytical approaches range from phenomenological and qualitative to formal computational quantitative methods. Practically, the approach may have utility in predicting clinical outcomes. We harnessed a real-world sample (blog entries) from groups with psychosis, strong beliefs, odd beliefs, illness, mental illness and/or social isolation to validate and extend laboratory findings about lexical differences between psychosis and control subjects.
methodWe describe the results of two experiments using Linguistic Inquiry and Word Count software to assess word category frequencies. In experiment 1, we compared word use in psychosis and control subjects in the laboratory (23 per group), and related results to subject symptoms. In experiment 2, we examined lexical patterns in blog entries written by people with psychosis and eight comparison groups. In addition to between-group comparisons, we used factor analysis followed by clustering to discern the contributions of strong belief, odd belief and illness identity to lexical patterns.
resultsConsistent with others' work, we found that first-person pronouns, biological process words and negative emotion words were more frequent in psychosis language. We tested lexical differences between bloggers with psychosis and multiple relevant comparison groups. Clustering analysis revealed that word use frequencies did not group individuals with strong or odd beliefs, but instead grouped individuals with any illness (mental or physical).
conclusionsPairing of laboratory and real-world samples reveals that lexical markers previously identified as specific language changes in depression and psychosis are probably markers of illness in general.
Indexed as
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.