Attitude toward aging and elderliness and death anxiety in geriatric individuals with chronic diseases in Turkey: Artificial neural network prediction

The aim of this study was to predict which demographic characteristics contribute to attitudes towards aging and old age and death anxiety in geriatric individuals with chronic disease. artificial neural network (ANN) modeling, a machine learning method, was used to provide this prediction. Full factorial test data (3456 value) were analyzed, considering variables such as age, gender, marital status, education, income, number of children, and relationships with children. Findings show that Turkish Death Anxiety Scale is moderate (TDAS=40-60 points), with women, married individuals, and those with higher income exhibiting higher anxiety. Anxiety decreases with higher education and more children, while worsening relationships with children increase anxiety. Attitudes toward Ageing and Elderliness Scale (ATAES=140-170 points) are highest at 90 years of age, with similar levels in both genders. Education level and poor relationships with children lead to more negative attitudes. Single individuals have stronger negative attitudes than married ones. ANN prediction performance of at least 72.24% was achieved. These insights highlight modifiable risk factors that can be addressed to reduce death anxiety and improve attitudes toward aging in older adult individuals with chronic diseases. ANN performed well in predicting the effect of demographic characteristics on attitudes toward aging and old age and death anxiety in older adult individuals with chronic diseases. By using ANN, predictions of factors that may pose risk in terms of demographic characteristics of individuals can be determined.