Abstract:
The aim of our study was to examine the relationship between menopausal symptoms and attitudes towards menopause and cyberchondria levels in climacteric women. The sample of our descriptive and cross-sectional study consisted of 489 climacteric women living in a city in western Turkey. The data were collected by the researchers between May and October 2022 by using the online questionnaire method. Data were analyzed using SPSS 22.0, G*Power 3.1, R programming language 4.1.3 programs. The results of the analysis of the hierarchical regression model show that the model is significant and usable F(2,486) =19.806, p = 0.001). Statistical that the decrease in the level of Menopause Symptoms of the participants (t = - 5.974, & beta; =-0.533, p < 0.001) caused a statistical increase in the level of Attitude towards Menopause. The change in the level of cyberchondria (t =-0.590, & beta; =-0.026, p = 0.556) does not statistically affect the level of Attitude towards Menopause. Random Forest regression was found to be the best performing algorithm in the prediction model for the attitude towards menopause variable. The contributions of the variables to the model were calculated with Shapley values (Shapley Additive Explanations (SHAP)). It was determined that the most important variable that should be in the model to predict the attitudes towards menopause variable is the menopausal symptoms variable. As menopausal symptoms increase in climacteric women, attitudes towards menopause decrease. Longitudinal studies on menopause are recommended.
