Identification of depressive sympotomatology in people with type II Diabetes

Keywords: Depression, Diabetes Mellitus, Health Psychology, Data Science


The aim of this work it's the identification of depressive symptomatology in people with type II diabetes. Among the literature, associations have been found between both, even considering depression as a possible risk identifier for developing Diabetes Mellitus. Due to this need to identify factors that affect depressive symptomatology in the population with diabetes, we sought to develop a classification model to determine which factors affect the aggravation of this psychological problem, and subsequently confirm these results using logistic regression models and cross-validation. A non-experimental cross-sectional research design was used. Using a non-probabilistic sampling by convenience, we worked with 200 people and found various factors that influenced depressive symptomatology in people with diabetes, according to the degree of depression, with negative attitudes towards oneself being a decisive factor in establishing the type of diagnosis. In this sense, for "Normal" depressive symptomatology, the most important factor was Impairment of performance; for "Mild" symptomatology, somatic alterations were observed; for "Moderate" symptomatology, sleep disturbances; and for "Severe" depressive symptomatology, the most notable somatic alterations were observed. It is argued the need to establish filters between "Normal" depressive symptomatology and those that could be an obstacle to achieve good adherence to treatment, considering contextual and biological aspects, the last in terms of brain activation.


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Alzoubi, A., Abunaser, R., Khassawneh, A., Alfaqih, M., Khasawneh, A. y Abdo, N. (2018). The bidirectional relationship between diabetes and depression: a literature review. Korean Journal of Family Medicine, 39(3), 137-146.

American Psychological Association. (2017). Ethical principles of psychologist and codeo f conduct. Recuperado de:

Asuzu, C., Walker, R., Strom, J. y Egede, L., (2017). Pathways for the relationship between diabetes distress depression, fatalism and glycemic control in adults with type 2 diabetes. Journal of Diabetes and its Complications, 31(1), 169-174.

Beck, A. y Lester, D. (1973). Components of depression in attempted suicides. The Journal of Psychology: Interdisciplinary and Applied, 85, 257-260.

Castillo-Quan, J., Barrera-Buenfil, D., Pérez-Osorio, J. y Álvarez-Cervera, F. (2010). Depresión y diabetes: de la epidemiología a la neurobiología. Revista de Neurología, 51(6), 347-359.

De la Fuente, J. y Heinze, G. (2014). Salud mental y medicina psicológica. McGraw Hill.

Diderichsen, F. y Andersen, I. (2019). The syndemics of diabetes and depression in Brazil – An epidemiological analysis. SSM – Population Health, 7.

González, F., Escoto, M. y Chávez, J. (2017). Estadística aplicada en psicología y ciencias de la salud. Manual Moderno.

Graham, E., Deschenes, S., Khalil, M., Danna, S., Filion, K. y Schmitz, N. (2020). Measures of depression and risk of type 2 diabetes: A systematic review and meta-analysis. Journal of Affective disorders, 265, 224-232.

Graham, E., Deschenes, S., Rosella, L. y Schmitz, N. (2021). Measures of depression and incident type 2 diabetes in a community sample. Annals of Epidemiology, 55, 4-9.

Horner, S., Fireman, G. y Wang, E. (2010). The relation of student behavior, peer status, race, and gender to decisions about school discipline using CHAID decision trees and regression modeling. Journal of School Psychology, 48, 135-161.

Jurado, S., Villegas, M., Méndez, L., Rodríguez, F., Loperena, V. y Varela, R. (1998). La estandarización del inventario de depresión de Beck para los residentes de la ciudad de México. Salud Mental, 21(3), 26-31.

Kerlinger, F. y Lee, H. (2002). Investigación del comportamiento. Métodos de investigación en ciencias sociales. McGraw-Hill.

Khan, Z. (2019). Prevalence of Depression and Associated Factors among Diabetic Patients in an Outpatient Diabetes Clinic. Psychiatry Journal, 2019.

Li, C., Xu., D., Hu, M., Tan, Y., Zhang, P., Li, G. y Chen, L. (2017). A systematic review and meta-analysis of randomized controlled trials of cognitive behavior therapy for patients with diabetes and depression. Journal of Psychosomatic Research, 95, 44-54.

Mezuk, B., Albrecht, S., Eaton, W. y Hill, S. (2008). Depression and Type 2 Diabetes Over the Lifespan: a meta-analysis. Diabetes Care, 31(12), 2383-2390.

Mohri, M., Rostamizadeh, A. y Talwalkar, A. (2018). Foundations of machine learning. The MIT Press.

Owens-Gary, M., Zhang, X., Jawanda, S., McKeever, K., Allweiss, P. y Smith, B. (2018). The Importance of Addressing Depression and Diabetes Distress in Adults with Type 2 Diabetes. Journal of General Internal Medicine, 34, 320-323.

Pineda, N., Bermúdez, V., Cano, C., Mengual, E., Romero, J., Medina, M., Leal, E., Rojas, J. y Toledo, A. (2004). Niveles de Depresión y Sintomatología característica en pacientes adultos con Diabetes Mellitus tipo 2. Archivos Venezol…