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Morphological Language Features of Anorexia Patients Based on Natural Language Processing

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Information Technology in Biomedicine (ITIB 2022)

Abstract

The aim of the article is to compare the morphological features of language between people suffering from anorexia and healthy people. The research was conducted in cooperation with the Medical University of Silesia on the basis of a pilot group of people: 41 from anorexia patients and 55 from healthy young females. The study focuses on the statistics for the following parts of speech: personal pronoun ‘I’, possessive adjective ‘my’ verbs, adjectives. Several significant differences were detected, including abnormal usage of the personal pronoun ‘I’ and mostly verb ‘to be’, and action verbs by anorectic people. In the future, it is planned to conduct the research on a larger group of patients and include the descriptions of the drawings in the re-search.

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References

  1. Springall, G., Cheung, M., Sawyer, S.M., Yeo, M.: Impact of the coronavirus pandemic on anorexia nervosa and atypical anorexia nervosa presentations to an Australian tertiary paediatric hospital. J. Paediatr. Child Health (2021). https://doi.org/10.1111/JPC.15755

    Article  Google Scholar 

  2. Gigantesco, A., Masocco, M., Picardi, A., Lega, I., Conti, S., Vichi, M.: Hospitalization for anorexia nervosa in Italy. Riv. Psichiatr. 45, 154–162 (2010)

    Google Scholar 

  3. Miniati, M., et al.: Eating disorders spectrum during the COVID pandemic: a systematic review. Front. Psychol. 12, 4161 (2021). https://doi.org/10.3389/FPSYG.2021.663376

    Article  Google Scholar 

  4. Vuillier, L., May, L., Greville-Harris, M., Surman, R., Moseley, R.L.: The impact of the COVID-19 pandemic on individuals with eating disorders: the role of emotion regulation and exploration of online treatment experiences. J. Eat. Disord. 9, 1–18 (2021). https://doi.org/10.1186/S40337-020-00362-9

    Article  Google Scholar 

  5. Rodgers, R.F., et al.: The impact of the COVID-19 pandemic on eating disorder risk and symptoms. Int. J. Eat. Disord. 53, 1166–1170 (2020). https://doi.org/10.1002/eat.23318

  6. Surgenor, L.J., Maguire, S.: Assessment of anorexia nervosa: an overview of universal issues and contextual challenges. J. Eat. Disord. 1, 1–12 (2013). https://doi.org/10.1186/2050-2974-1-29

    Article  Google Scholar 

  7. Damiano, S.R., Atkins, L., Reece, J.: The psychological profile of adolescents with anorexia and implications for treatment. J. Eat. Disord. 2, 1–1 (2014). https://doi.org/10.1186/2050-2974-2-S1-P9

    Article  Google Scholar 

  8. Anorexia Nervosa: Symptoms, Causes, and Treatments. https://www.healthline.com/health/anorexia-nervosa. Accessed 23 Jan 2022

  9. Smink, F.R.E., Van Hoeken, D., Hoek, H.W.: Epidemiology of eating disorders: incidence, prevalence and mortality rates. Curr. Psychiatry Rep. 14, 406–414 (2012). https://doi.org/10.1007/S11920-012-0282-Y

    Article  Google Scholar 

  10. Wu, J., Liu, J., Li, S., Ma, H., Wang, Y.: Trends in the prevalence and disability-adjusted life years of eating disorders from 1990 to 2017: results from the Global Burden of Disease Study 2017. Epidemiol. Psychiatr. Sci. 29 (2020). https://doi.org/10.1017/S2045796020001055

  11. Kotwas, A., Karakiewicz-Krawczyk, K., Zabielska, P., Jurczak, A., Bażydło, M., Karakiewicz, B.: The incidence of eating disorders among upper secondary school female students. Psychiatr. Pol. 54, 253–263 (2020). https://doi.org/10.12740/PP/ONLINEFIRST/99164

  12. Quick, V.M., Byrd-Bredbenner, C., Neumark-Sztainer, D.: Chronic illness and disordered eating: a discussion of the literature. Adv. Nutr. 4, 277 (2013). https://doi.org/10.3945/AN.112.003608

    Article  Google Scholar 

  13. Stice, E., Nathan Marti, C., Rohde, P.: Prevalence, incidence, impairment, and course of the proposed DSM-5 eating disorder diagnoses in an 8-year prospective community study of young women. J. Abnorm. Psychol. 122, 445 (2013). https://doi.org/10.1037/A0030679

    Article  Google Scholar 

  14. Abebe, D.S., Lien, L., Von Soest, T.: The development of bulimic symptoms from adolescence to young adulthood in females and males: a population-based longitudinal cohort study. Int. J. Eat. Disord. 45, 737–745 (2012). https://doi.org/10.1002/EAT.20950

    Article  Google Scholar 

  15. Guillaume, S., et al.: Characteristics of suicide attempts in anorexia and bulimia nervosa: a case-control study. PLoS ONE 6, 23578 (2011). https://doi.org/10.1371/JOURNAL.PONE.0023578

  16. Abbate-Daga, G., Amianto, F., Delsedime, N., De-Bacco, C., Fassino, S.: Resistance to treatment in eating disorders: a critical challenge. BMC Psychiatry 13, 1–18 (2013). https://doi.org/10.1186/1471-244X-13-294

    Article  Google Scholar 

  17. Robertson, A., Thornton, C.: Challenging rigidity in Anorexia (treatment, training and supervision): questioning manual adherence in the face of complexity. J. Eat. Disord. 9, 1–8 (2021). https://doi.org/10.1186/S40337-021-00460-2

    Article  Google Scholar 

  18. Bellows, B.K., et al.: Automated identification of patients with a diagnosis of binge eating disorder from narrative electronic health records. J. Am. Med. Inform. Assoc. 21, e163 (2014). https://doi.org/10.1136/AMIAJNL-2013-001859

  19. Funk, B., et al.: A framework for applying natural language processing in digital health interventions. J. Med. Internet Res. 22 (2020). https://doi.org/10.2196/13855

  20. Spinczyk, D., Bas, M., Dzieciąko, M., Maćkowski, M., Rojewska, K., Maćkowska, S.: Computer-aided therapeutic diagnosis for anorexia. Biomed. Eng. Online 19 (2020). https://doi.org/10.1186/S12938-020-00798-9

  21. Barańska, K., Różańska, A., Maćkowska, S., Rojewska, K., Spinczyk, D.: Determining the intensity of basic emotions among people suffering from anorexia nervosa based on free statements about their body. Electronics 11, 138 (2022). https://doi.org/10.3390/electronics11010138

  22. Iliev, R., Dehghani, M., Sagi, E.: Automated text analysis in psychology: methods, applications, and future developments. Lang. Cogn. 7, 265–290 (2015). https://doi.org/10.1017/LANGCOG.2014.30

    Article  Google Scholar 

  23. Calvo, R.A., Milne, D.N., Hussain, M.S., Christensen, H.: Natural language processing in mental health applications using non-clinical texts. Nat. Lang. Eng. 23, 649–685 (2017). https://doi.org/10.1017/S1351324916000383

    Article  Google Scholar 

  24. Rezaii, N., Walker, E., Wolff, P.: A machine learning approach to predicting psychosis using semantic density and latent content analysis. npj Schizophr. 5, 1–12 (2019). https://doi.org/10.1038/s41537-019-0077-9

  25. Van Puyvelde, M., Neyt, X., McGlone, F., Pattyn, N.: Voice stress analysis: a new framework for voice and effort in human performance. Front. Psychol. 9, 1994 (2018). https://doi.org/10.3389/FPSYG.2018.01994

    Article  Google Scholar 

  26. Rocco, D., Pastore, M., Gennaro, A., Salvatore, S., Cozzolino, M., Scorza, M.: Beyond verbal behavior: an empirical analysis of speech rates in psychotherapy sessions. Front. Psychol. 9, 978 (2018). https://doi.org/10.3389/FPSYG.2018.00978

    Article  Google Scholar 

  27. Cuteri, V., et al.: Linguistic Feature of Anorexia Nervosa: A Prospective Case-Control Pilot Study (2021). https://doi.org/10.21203/RS.3.RS-186615/V1

  28. Minori, G., et al.: Linguistic markers of anorexia nervosa: preliminary data from a prospective observational study. In: 3rd RaPID Workshop: Resources and Processing of Linguistic, Para-linguistic and Extra-linguistic Data from People with Various Forms of Cognitive/Psychiatric/Developmental Impairments, pp. 34–37 (2020)

    Google Scholar 

  29. Spinczyk, D., Nabrdalik, K., Rojewska, K.: Computer aided sentiment analysis of anorexia nervosa patients’ vocabulary. Biomed. Eng. Online 17, 1–11 (2018). https://doi.org/10.1186/S12938-018-0451-2

    Article  Google Scholar 

  30. Pyysalo, S.: Text parsing. In: Dubitzky, W., Wolkenhauer, O., Cho, KH., Yokota, H. (eds.) Encyclopedia of Systems Biology, pp. 2162–2163. Springer, New York (2013). https://doi.org/10.1007/978-1-4419-9863-7_182

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Correspondence to Stella Maćkowska .

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Maćkowska, S., Barańska, K., Różańska, A., Rojewska, K., Spinczyk, D. (2022). Morphological Language Features of Anorexia Patients Based on Natural Language Processing. In: Pietka, E., Badura, P., Kawa, J., Wieclawek, W. (eds) Information Technology in Biomedicine. ITIB 2022. Advances in Intelligent Systems and Computing, vol 1429. Springer, Cham. https://doi.org/10.1007/978-3-031-09135-3_9

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