2015International Journal of SurgeryOpen access

Prediction of anxiety and depression in general surgery inpatients: A prospective cohort study of 200 consecutive patients

Fatih Başak, Mustafa Hasbahçecı, Sunay Guner, Abdullah Şişik, Aylin Acar, Metin Yücel, Ali Cagri Kilic, Gürhan Baş

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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.

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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.

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Available 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.

Key concepts: Anxiety, Depression (economics), Medicine, Logistic regression, Socioeconomic status, Hospital Anxiety and Depression Scale, Prospective cohort study, Psychiatry

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