Development and validation of Arabic version of the Hospital Anxiety and Depression Scale
نویسندگان
چکیده
INTRODUCTION The Hospital Anxiety and Depression Scale (HADS) is widely used to predict and diagnose hospital anxiety and depression. It has been translated and validated in many languages, but the existing Arabic version was not validated in hospitalized patients. The aim was to translate, culturally adapt, and validate the HADS Questionnaire into Arabic language for in-patient use, especially for surgical wards. METHODS A systematic translation process was used to translate the original English HADS into Arabic. After the pilot study, we validated our version in surgical patients at two tertiary care centers. We tested the reliability of our version using internal consistency. We examined the validity by assessing construct validity, concurrent validity (by testing the associations between HADS, Generalized Anxiety Disorder 7-item scale [GAD-7], and Major Depression Inventory [MDI]), and face validity. The questionnaire was administered before and after surgery to examine responsiveness. RESULTS A total of 110 patients (22 men, 88 women) were included in the study. Cronbach's αs for the HADS anxiety subscale were 0.83 (95% confidence interval: 0.79- 0.88) and for the HADS depression subscale were 0.77 (0.7-0.83). Nearly 36% of the patients reported symptoms indicative of borderline or case anxiety before surgery, which decreased to 25% 1 week after surgery. HADS anxiety score was strongly correlated with GAD-7, and HADS depression score was strongly associated with MDI. Patients with higher American Society of Anesthesiologists Physical Status and those who remained hospitalized for more than 5 days were more likely to report depression symptoms. Most patients found the HADS questions to be clear and easy to understand, and thought the questionnaire items covered all their problem areas regarding their hospital anxiety and depression. CONCLUSIONS Our Arabic version of HADS is a reliable and valid tool to assess the mood states in hospitalized patients.
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