ReviewPsychiatry research2024
Beyond rating scales: With targeted evaluation, large language models are poised for psychological assessment.
Review in Psychiatry research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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
30 citing papers in PubMed.
- Assessing the Need for Mental Health Support From Free-Text Responses: Development and Validation of Language-Based Assessments in Adults With Internalizing Symptoms.JMIR mental health · 2026Article
- Natural Language Response Formats for Assessing Depression and Worry With Large Language Models: A Sequential Evaluation With Model Pre-Registration.Assessment · 2026Article
- Clinicians' practices and attitudes toward depression assessment: a cross-sectional survey study.BMC psychology · 2026Article
- Conversational AI should fill the white space in mental health care, not replace humans.NPJ digital medicine · 2026Review
- Using large language models to evaluate the interplay between posttraumatic stress disorder symptom severity and intolerance to uncertainty: A large-scale ecological momentary assessment study.Journal of psychopathology and clinical science · 2026Article
- Scalable, context-sensitive psychiatric assessment with large language models and brief diaries.Psychological medicine · 2026Article
- Generative psychometrics via AI-GENIE: Automatic item generation and validation with network-integrated evaluation.Behavior research methods · 2026Article
- Functional Outcome Prediction in Young Adults With Mental Health Symptoms Using Machine Learning and Large Language Models: Longitudinal Observational Study.JMIR mental health · 2026Observational
- Validating an adaptive digital assessment of youth mental health needs: a cross-sectional study.NPJ digital medicine · 2026Article
- Language-based assessments can predict psychological and subjective well-being.Communications psychology · 2026Article
- Evaluating the Efficacy of AI-Based Interactive Assessments Using Large Language Models for Depression Screening: Development and Usability Study.JMIR formative research · 2026Article
- Psychometric applications of generative artificial intelligence: Lifecycle, risks, and research agenda.PLOS mental health · 2026Review
- Large language model performance versus human expert ratings in automated suicide risk assessment.Scientific reports · 2025Article
- Multimodal LLM vs. Human-Measured Features for AI Predictions of Autism in Home Videos.Algorithms · 2025Article
- Decoding the mind of self-compassion through a topic modeling analysis of 9000+ free-text narratives.Scientific reports · 2025Article
- Current applications and future directions in natural language processing for news media and mental health.Scientific reports · 2025Article
- Advancing psychological assessment: quantifying self-compassion through free-text responses and language model BERT.Scientific reports · 2025Article
- Collecting behavioural data across countries during pandemics: Development of the COVID-19 Risk Assessment Tool.Behavior research methods · 2025Article
- Automatic implicit motive codings are at least as accurate as humans' and 99% faster.Journal of personality and social psychology · 2025Article
- Towards a latent space cartography of subjective experience in mental health.Psychiatry and clinical neurosciences · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
In this narrative review, we survey recent empirical evaluations of AI-based language assessments and present a case for the technology of large language models to be poised for changing standardized psychological assessment. Artificial intelligence has been undergoing a purported "paradigm shift" initiated by new machine learning models, large language models (e.g., BERT, LAMMA, and that behind ChatGPT). These models have led to unprecedented accuracy over most computerized language processing tasks, from web searches to automatic machine translation and question answering, while their dialogue-based forms, like ChatGPT have captured the interest of over a million users. The success of the large language model is mostly attributed to its capability to numerically represent words in their context, long a weakness of previous attempts to automate psychological assessment from language. While potential applications for automated therapy are beginning to be studied on the heels of chatGPT's success, here we present evidence that suggests, with thorough validation of targeted deployment scenarios, that AI's newest technology can move mental health assessment away from rating scales and to instead use how people naturally communicate, in language.
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.