depression among diabetes

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Amharic translation of questionnaires was performed before data collection process since the Amharic language is the working language in the study area. A pre-test was also done among twenty-one diabetes mellitus patients (5%) of sample size at Abaymado Hospital, a hospital located about 5km away from the study area. Three BSc nurses were involved in the data collection. The data collectors and supervisors were given short term training about study aims, procedures, ethical issues, and data quality control methods. Continuous supervision was done by supervisors and principal investigator throughout the data collection process. Depression was assessed using the Patient Health Questionnaire-9 screening instrument the Amharic version of which had been validated in Ethiopia. The PHQ-9 asses depressive symptoms in past 2 weeks and consisted of 9 questions each of which can be scored from 0 (not at all), 1(several days), 2 (more than half of the days), or 3 (nearly every day) with an overall score ranging from 0 to 27. This score was dichotomized at a cut-off score of 10 with sensitivity 86% and specificity 67% for diagnosing MDD(60) and had been used in plenty of studies previously in Ethiopia(25, 27, 38). Level of adherence to diabetic medication was assessed as poor, medium and high adherence using Morisky-8 medication adherence scale. Poor-adherence was defined as a score of less than 6, medium adherence with a score of 6-7 and high adherence with a score of 8 (61-64). Social support was assessed using Oslo-3 item social support scale. Poor social support, moderate social support, and good social support were defined at cut-off point 3-8, 9-11 and 12-14 points (65).Data Processing and AnalysisEpi-info version 7 was used as a data entry tool and Statistical Packages for Social Sciences, version 20(SPSS-20) had been utilized to analyze the data after it was exported from Epi-info. Frequency, mean, median, standard deviation and crosstabs were the descriptive statistical measures employed in summarizing the outcome and independent variables. A logistic regression model was fitted to identify risk factors for depression. A p-value