@inproceedings{pelloni-etal-2026-evaluation,
title = "Evaluation of Multilingual Text Simplification for the Mental Health Domain: Exploring Small Language Models",
author = "Pelloni, Olga and
Just, Sandra and
Bongo, Lars",
editor = "Demner-Fushman, Dina and
Ananiadou, Sophia and
Roberts, Kirk and
Tsujii, Junichi",
booktitle = "{B}io{NLP} 2026",
month = jul,
year = "2026",
address = "San Diego, California",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.bionlp-1.36/",
pages = "464--474",
ISBN = "979-8-89176-434-7",
abstract = "Individuals with particular mental health disorders may find it difficult to learn about their own condition. Therefore, efforts have been made to create materials that explain complex medical information in simpler words, which are also beneficial for caregivers and others. However, text simplification is commonly done in English and only sporadically in other languages. In this study, we explore potential ways for language-agnostic medical text simplification for the mental health domain. Our approach is to simplify the ICD-11 articles on primary psychotic disorders in English, German and French, using small LMs and various metrics for evaluating different aspects of the texts: lexical complexity and readability. Our results show that acceptable texts were produced only in English, and that a joint analysis of Measure of Textual Lexical Diversity (MTLD) and Flesch Reading Ease (FRE) provides the most insight, capturing both the best outcomes and signaling different types of issue. The study is preliminary and requires further investigation."
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<abstract>Individuals with particular mental health disorders may find it difficult to learn about their own condition. Therefore, efforts have been made to create materials that explain complex medical information in simpler words, which are also beneficial for caregivers and others. However, text simplification is commonly done in English and only sporadically in other languages. In this study, we explore potential ways for language-agnostic medical text simplification for the mental health domain. Our approach is to simplify the ICD-11 articles on primary psychotic disorders in English, German and French, using small LMs and various metrics for evaluating different aspects of the texts: lexical complexity and readability. Our results show that acceptable texts were produced only in English, and that a joint analysis of Measure of Textual Lexical Diversity (MTLD) and Flesch Reading Ease (FRE) provides the most insight, capturing both the best outcomes and signaling different types of issue. The study is preliminary and requires further investigation.</abstract>
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%0 Conference Proceedings
%T Evaluation of Multilingual Text Simplification for the Mental Health Domain: Exploring Small Language Models
%A Pelloni, Olga
%A Just, Sandra
%A Bongo, Lars
%Y Demner-Fushman, Dina
%Y Ananiadou, Sophia
%Y Roberts, Kirk
%Y Tsujii, Junichi
%S BioNLP 2026
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California
%@ 979-8-89176-434-7
%F pelloni-etal-2026-evaluation
%X Individuals with particular mental health disorders may find it difficult to learn about their own condition. Therefore, efforts have been made to create materials that explain complex medical information in simpler words, which are also beneficial for caregivers and others. However, text simplification is commonly done in English and only sporadically in other languages. In this study, we explore potential ways for language-agnostic medical text simplification for the mental health domain. Our approach is to simplify the ICD-11 articles on primary psychotic disorders in English, German and French, using small LMs and various metrics for evaluating different aspects of the texts: lexical complexity and readability. Our results show that acceptable texts were produced only in English, and that a joint analysis of Measure of Textual Lexical Diversity (MTLD) and Flesch Reading Ease (FRE) provides the most insight, capturing both the best outcomes and signaling different types of issue. The study is preliminary and requires further investigation.
%U https://aclanthology.org/2026.bionlp-1.36/
%P 464-474
Markdown (Informal)
[Evaluation of Multilingual Text Simplification for the Mental Health Domain: Exploring Small Language Models](https://aclanthology.org/2026.bionlp-1.36/) (Pelloni et al., BioNLP 2026)
ACL