Recent works indicated the potential relevance of Natural Language Processing techniques for the detection of clinical conditions. This paper tries to address the issue in the Eating Disorder domain, by exploiting “linguistic biomarkers” for Anorexia Nervosa (AN) detection in female teenagers. We hypothesize that (i) disturbances in self-perceived body image, black and white thinking and mood changes strongly associated with AN disorder can result in altered linguistic patterns; and (ii) these subtle modifications can be identified by means of NLP tools, acting as early proxy measures for the disorder. To this aim, we enrolled 51 participants (age range: 14-18): 17 girls with a clinical diagnosis of Anorexia Nervosa and 34 normal weighted peers, matched by gender, age and educational level. Both the groups were asked to produce three written texts (around 10-15 lines long), i.e. two autobiographical narratives and a short description of a complex figure. A rich set of linguistic features was extracted from the text samples and the statistical significance in pinpointing the pathological process was measured. Our preliminary results show that subtle language disruptions, mainly at the lexical and syntactic level, can actually represent an early but reliable marker of the disease. However, an analysis on a bigger cohort with follow-up information, still ongoing, is needed to consolidate this assumption.

Giulia Minori, G.G. (2020). Linguistic Markers of Anorexia Nervosa: Preliminary Data from a Prospective Observational Study. Paris : European Language Resources Association [10.1007/s40519-022-01425-3].

Linguistic Markers of Anorexia Nervosa: Preliminary Data from a Prospective Observational Study

Giulia Minori
Data Curation
;
Gloria Gagliardi
Writing – Original Draft Preparation
;
Vittoria Cuteri
Data Curation
;
Fabio Tamburini
Writing – Review & Editing
;
Antonia Parmeggiani
Supervision
2020

Abstract

Recent works indicated the potential relevance of Natural Language Processing techniques for the detection of clinical conditions. This paper tries to address the issue in the Eating Disorder domain, by exploiting “linguistic biomarkers” for Anorexia Nervosa (AN) detection in female teenagers. We hypothesize that (i) disturbances in self-perceived body image, black and white thinking and mood changes strongly associated with AN disorder can result in altered linguistic patterns; and (ii) these subtle modifications can be identified by means of NLP tools, acting as early proxy measures for the disorder. To this aim, we enrolled 51 participants (age range: 14-18): 17 girls with a clinical diagnosis of Anorexia Nervosa and 34 normal weighted peers, matched by gender, age and educational level. Both the groups were asked to produce three written texts (around 10-15 lines long), i.e. two autobiographical narratives and a short description of a complex figure. A rich set of linguistic features was extracted from the text samples and the statistical significance in pinpointing the pathological process was measured. Our preliminary results show that subtle language disruptions, mainly at the lexical and syntactic level, can actually represent an early but reliable marker of the disease. However, an analysis on a bigger cohort with follow-up information, still ongoing, is needed to consolidate this assumption.
2020
Proceedings of LREC 2020 Language Resources and Evaluation Conference 11-16 May 2020: 3rd RaPID Workshop, Resources and Processing of Linguistic, Para-linguistic and Extra-linguistic Data from People with Various Forms of Cognitive/Psychiatric/Developmental Impairments.
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Giulia Minori, G.G. (2020). Linguistic Markers of Anorexia Nervosa: Preliminary Data from a Prospective Observational Study. Paris : European Language Resources Association [10.1007/s40519-022-01425-3].
Giulia Minori, Gloria Gagliardi, Vittoria Cuteri, Fabio Tamburini, Elisabetta Malaspina, Paola Gualandi, Francesca Rossi, Filomena Moscano, Valentina ...espandi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/759149
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