- Dicle Tıp Dergisi
- Vol: 49 Issue: 3
- Evaluation of Occupational Variables Affecting Dentists Using Hierarchical Cluster Analysis
Evaluation of Occupational Variables Affecting Dentists Using Hierarchical Cluster Analysis
Authors : Başar Öztürk, Yusuf Çelik
Pages : 400-407
Doi:10.5798/dicletip.1169690
View : 22 | Download : 7
Publication Date : 2022-09-02
Article Type : Research
Abstract :Objective: This study aimed to examine the occupational variables affecting dentists. The relationship between variables was discovered by the dendrogram, using hierarchical cluster analysis. Methods: The study was a cross-sectional survey that includes 124 dentists in İstanbul (mean age ± S; 34.21 ± 7.35 years; occupation year 11.05 ± 6.78 years; 73 married, 51 single; 61 men, 63 women). Some assessments (sleep, depression, anxiety, pain, functionality, physical activity, and quality of life) were applied to the participants. Hierarchical Cluster Analysis of Multivariate Statistical Methods was used to determine the clustering tendency of the variables and see how these clusters can converge. Results: Two main clusters were obtained by using Hierarchical Cluster Analysis. Main Cluster I contains two sub-clusters: Sub-Cluster I: Age, Occupation year, Stress, Neck disability index; Sub-Cluster II: Depression, Anxiety, Pittsburg, BMI, Oswestry disability index. Main Cluster II: Quality of life, Physical activity, Chronic disease, Smoking, Family situation, and Gender variables were obtained. Discussion and Conclusion: As a result of our research, it is seen that the relations between the variables in the clusters we obtained are related to the literature. In this sense, the visual results and clusters obtained with the dendrogram enabled the variables to be presented regularly and systematically. Hierarchical cluster analysis draws attention as a modern method in terms of evaluating the physical and psychosocial variables that occur in dentistry, an important profession for society.Keywords : Dentists, Occupational variables, , Cluster Analysis, Dendrogram