Research Article

The Role of Emotional Intelligence in Diabetes Management: Evaluating Predictive Power for Self-Care Behaviors Using Artificial Intelligence Models

Volume: 5 Number: 1 June 20, 2026
EN

The Role of Emotional Intelligence in Diabetes Management: Evaluating Predictive Power for Self-Care Behaviors Using Artificial Intelligence Models

Abstract

Objective: This study examined the effect of emotional intelligence on self-care behaviors in individuals with type 2 diabetes and their prediction using artificial intelligence based models. Material and Methods: This cross-sectional, quantitative study included 200 individuals diagnosed with type 2 diabetes mellitus (DM). “Personal Information Form’’, “Diabetes Self-Care Activities Questionnaire”, and “Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF)” were used. Random Forest, Support Vector Machine, Artificial Neural Networks, and Linear Regression algorithms were applied in the analyses. Results: The mean age of the participants was 54.88 ± 6.41 years, 76.0% were women, and 94.0% were married. The overall emotional intelligence level was moderate (71.48 ±1.51). Among sub-dimensions, emotionality had the highest mean score (4.55 ± 0.47), while sociability had the lowest (3.14±0.19). Emotionality was positively associated with diet and blood glucose monitoring but negatively associated with exercise. In contrast, sociability showed a negative relationship with diet and a positive relationship with exercise. Among the applied models, Random Forest demonstrated the best performance, explaining approximately 14% of the variance in the total self-care score (R2 = .146) while Support Vector Machine (R2 = -.077), Linear Regression (R2 = -.023), and Artificial Neural Network (R2 = -3.538) models yielded negative R2 values, indicating that emotional intelligence sub-dimensions alone were insufficient to generate meaningful predictions. Feature importance analysis identified “Well-being” and “Self-control” as the primary contributors, while “Emotionality” ranked lowest despite its strong bivariate correlations reflecting methodological differences between the two analyses. Conclusion: These exploratory findings indicate that emotional intelligence sub-dimensions alone have limited predictive value (R2 = .146), suggesting that self-care is a multidimensional construct extending beyond emotional capacity.

Keywords

Artificial intelligence, Emotional intelligence, Diabetes management, Self-care, Type 2 diabetes

Supporting Institution

There is no financially supporting body for this article.

Ethical Statement

The required ethical approval for this study was obtained from the Non-Interventional Clinical Research Ethics Committee of Gaziantep Islamic Science and Technology University with the protocol number 2025-2ÖNP-0276, dated 19/09/2025. Before initiating the study, the purpose of the research was explained to voluntary participants. Necessary institutional permissions were also obtained from the official organization where the research was conducted. Throughout the study, the ethical principles of the Helsinki Declaration on Human Rights were followed.

References

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APA
Kardaş Kin, Ö., & Güngör Tolasa, A. (2026). The Role of Emotional Intelligence in Diabetes Management: Evaluating Predictive Power for Self-Care Behaviors Using Artificial Intelligence Models. Farabi Medical Journal, 5(1). https://doi.org/10.59518/farabimedj.1930416
AMA
1.Kardaş Kin Ö, Güngör Tolasa A. The Role of Emotional Intelligence in Diabetes Management: Evaluating Predictive Power for Self-Care Behaviors Using Artificial Intelligence Models. Farabi Medical Journal. 2026;5(1). doi:10.59518/farabimedj.1930416
Chicago
Kardaş Kin, Özlem, and Arzu Güngör Tolasa. 2026. “The Role of Emotional Intelligence in Diabetes Management: Evaluating Predictive Power for Self-Care Behaviors Using Artificial Intelligence Models”. Farabi Medical Journal 5 (1). https://doi.org/10.59518/farabimedj.1930416.
EndNote
Kardaş Kin Ö, Güngör Tolasa A (June 1, 2026) The Role of Emotional Intelligence in Diabetes Management: Evaluating Predictive Power for Self-Care Behaviors Using Artificial Intelligence Models. Farabi Medical Journal 5 1
IEEE
[1]Ö. Kardaş Kin and A. Güngör Tolasa, “The Role of Emotional Intelligence in Diabetes Management: Evaluating Predictive Power for Self-Care Behaviors Using Artificial Intelligence Models”, Farabi Medical Journal, vol. 5, no. 1, June 2026, doi: 10.59518/farabimedj.1930416.
ISNAD
Kardaş Kin, Özlem - Güngör Tolasa, Arzu. “The Role of Emotional Intelligence in Diabetes Management: Evaluating Predictive Power for Self-Care Behaviors Using Artificial Intelligence Models”. Farabi Medical Journal 5/1 (June 1, 2026). https://doi.org/10.59518/farabimedj.1930416.
JAMA
1.Kardaş Kin Ö, Güngör Tolasa A. The Role of Emotional Intelligence in Diabetes Management: Evaluating Predictive Power for Self-Care Behaviors Using Artificial Intelligence Models. Farabi Medical Journal. 2026;5. doi:10.59518/farabimedj.1930416.
MLA
Kardaş Kin, Özlem, and Arzu Güngör Tolasa. “The Role of Emotional Intelligence in Diabetes Management: Evaluating Predictive Power for Self-Care Behaviors Using Artificial Intelligence Models”. Farabi Medical Journal, vol. 5, no. 1, June 2026, doi:10.59518/farabimedj.1930416.
Vancouver
1.Özlem Kardaş Kin, Arzu Güngör Tolasa. The Role of Emotional Intelligence in Diabetes Management: Evaluating Predictive Power for Self-Care Behaviors Using Artificial Intelligence Models. Farabi Medical Journal. 2026 Jun. 1;5(1). doi:10.59518/farabimedj.1930416