Fatih Basak1, Mustafa Hasbahceci2, Sunay Guner3, Abdullah Sisik3, Aylin Acar3, Metin Yucel3, Ali Kilic3, Gurhan Bas3. 1. Department of General Surgery, Umraniye Education and Research Hospital, Istanbul, Turkey. Electronic address: fatihbasak@gmail.com. 2. Department of General Surgery, Bezmialem Vakif University, Faculty of Medicine, Istanbul, Turkey. 3. Department of General Surgery, Umraniye Education and Research Hospital, Istanbul, Turkey.
Abstract
INTRODUCTION: Surgery is a major stress factor for patients, and is associated with significant anxiety or depression. The Hospital Anxiety and Depression Scale is one of the most common instruments used for assessment of patients' psychological stress. Here, we aimed to identify predictors of anxiety and depression in surgical inpatients. METHODS: The study group consisted of consecutive two-hundred patients who completed the Hospital Anxiety and Depression Scale questionnaire. A patient scoring more than cut-off values (10 for anxiety and seven for depression) was considered as being at risk of anxiety or depression. Demographical data, socioeconomic status, education level and diagnoses were recorded. The Chi-square, Fisher's exact, Mann-Whitney, Kruskal-Wallis tests and binary logistic regression analysis were used to identify the predictive parameters for anxiety and depression. RESULTS: It was found that female patients, patients older than 35 years, patients with low socioeconomic status and low education level had a relatively higher risk of anxiety. In addition, patients with low education and a hospital stay greater than seven days were at risk of depression. Logistic regression analysis revealed that socioeconomic status and education level were strongly predictive for anxiety. However, presence of anxiety was shown to be strongly predictive for depression. CONCLUSION: Healthcare providers should be aware of their patients' psychology and, therefore, it is recommended to consider predictive factors for anxiety and depression.
INTRODUCTION: Surgery is a major stress factor for patients, and is associated with significant anxiety or depression. The Hospital Anxiety and Depression Scale is one of the most common instruments used for assessment of patients' psychological stress. Here, we aimed to identify predictors of anxiety and depression in surgical inpatients. METHODS: The study group consisted of consecutive two-hundred patients who completed the Hospital Anxiety and Depression Scale questionnaire. A patient scoring more than cut-off values (10 for anxiety and seven for depression) was considered as being at risk of anxiety or depression. Demographical data, socioeconomic status, education level and diagnoses were recorded. The Chi-square, Fisher's exact, Mann-Whitney, Kruskal-Wallis tests and binary logistic regression analysis were used to identify the predictive parameters for anxiety and depression. RESULTS: It was found that female patients, patients older than 35 years, patients with low socioeconomic status and low education level had a relatively higher risk of anxiety. In addition, patients with low education and a hospital stay greater than seven days were at risk of depression. Logistic regression analysis revealed that socioeconomic status and education level were strongly predictive for anxiety. However, presence of anxiety was shown to be strongly predictive for depression. CONCLUSION: Healthcare providers should be aware of their patients' psychology and, therefore, it is recommended to consider predictive factors for anxiety and depression.
Authors: Cristina Civilotti; Daniela Acquadro Maran; Francesca Santagata; Antonella Varetto; Maria Rosa Stanizzo Journal: Support Care Cancer Date: 2020-02-08 Impact factor: 3.603
Authors: Matthias Christian Schrempf; Julian Quirin Petzold; Hugo Vachon; Morten Aagaard Petersen; Johanna Gutschon; Sebastian Wolf; Florian Sommer; Marcus Murnauer; Matthias Anthuber Journal: BMJ Open Date: 2021-04-07 Impact factor: 2.692
Authors: Matthias C Schrempf; Julian Petzold; Morten Aa Petersen; Tim Tobias Arndt; Stefan Schiele; Hugo Vachon; Dmytro Vlasenko; Sebastian Wolf; Matthias Anthuber; Gernot Müller; Florian Sommer Journal: Sci Rep Date: 2022-07-14 Impact factor: 4.996