ArticlePloS one2023
Precise language responses versus easy rating scales-Comparing respondents' views with clinicians' belief of the respondent's views.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The trial behind it
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Who cites it
9 citing papers in PubMed.
- Analysis of the Validity of ChatGPT in the Assessment of Perceived Stress and Psychological Distress Among University Students: A Cross-Sectional Study.The Psychiatric quarterly · 2026Article
- Advancing psychological assessment: quantifying self-compassion through free-text responses and language model BERT.Scientific reports · 2025Article
- The rise of artificial intelligence for cognitive behavioral therapy: A bibliometric overview.Applied psychology. Health and well-being · 2025Review
- Statistics is not measurement: The inbuilt semantics of psychometric scales and language-based models obscures crucial epistemic differences.Frontiers in psychology · 2025Article
- Language or rating scales based classifications of emotions: computational analysis of language and alexithymia.Npj mental health research · 2024Article
- ALBA: Adaptive Language-Based Assessments for Mental Health.Proceedings of the conference. Association for Computational Linguistics. North American Chapter. Meeting · 2024Article
- Question-based computational language approach outperforms rating scales in quantifying emotional states.Communications psychology · 2024Article
- Predicting attitudes toward ambiguity using natural language processing on free descriptions for open-ended question measurements.Scientific reports · 2024Article
- Assessment of depression and anxiety in young and old with a question-based computational language approach.Npj mental health research · 2023Article
Corrections and comments
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundClosed-ended rating scales are the most used response format for researchers and clinicians to quantify mental states, whereas in natural contexts people communicate with natural language. The reason for using such scales is that they are typically argued to be more precise in measuring mental constructs; however, the respondents' views as to what best communicates mental states are frequently ignored, which is important for making them comply with assessment.
methodsWe assessed respondents' (N = 304) degree of depression using rating scales, descriptive words, selected words, and free text responses and probed the respondents for their preferences concerning the response formats across twelve dimensions related to the precision of communicating their mental states and the ease of responding. This was compared with the clinicians' (N = 40) belief of the respondent's view.
resultsRespondents found free text to be more precise (e.g., precision d' = .88, elaboration d' = 2.0) than rating scales, whereas rating scales were rated as easier to respond to (e.g., easier d' = -.67, faster d' = -1.13). Respondents preferred the free text responses to a greater degree than rating scales compared to clinicians' belief of the respondents' views.
conclusionsThese findings support previous studies concluding that future assessment of mental health can be aided by computational methods based on text data. Participants prefer an open response format as it allows them to elaborate, be precise, etc., with respect to their mental health issues, although rating scales are viewed as faster and easier.
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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.