ABSTRACT
Aim To assess a psychosocial impact of the Coronavirus disease 2019 (COVID-19) on health care workers and to quantify the size of depression symptoms, anxiety and stress levels. Methods This cross-sectional study used an anonymous online survey questionnaire as a research instrument and it included 114 health workers of all profiles from the Sarajevo Canton employed in private and public institutions. The research was voluntary, non-commercial and all participants provided an oral informed consent. Depression, Anxiety and Stress Scale (DASS-21) questionnaire was used for assessing emotional status of depression, anxiety and stress. Results The mean age of participants was 40.5±8.44 years with male:female ratio of 0.28. Prevalence of depression was 46.5%, anxiety61.4%, and 36.9% stress. Age and gender had no effect on emotional status, but it was revealed that women achieved higher depression, anxiety and stress scores than men (without statistical significance). The most notable effect on the emotional state was found for direct or indirect contact with COVID-19 patients. Medical workers in direct contact with COVID-19 patients achieved greater depression (p=0.005), anxiety (p=0.001), stress (p=0.030) and total DASS-21 (p=0.003) scores. Conclusion High prevalence of health workers affected by various psychological ailments during the COVID-19 pandemic was found. This evidence underscores the need to address adverse effects of the pandemic on mental health of health care workers.
ABSTRACT
AIM: The aim of this study is to represent the prevalence of non-communicable diseases risks among patients of family medicine practices in the Federation of Bosnia and Herzegovina. Risks prevalence was obtained from an organized massive screening being performed by 100 family medicine teams in four cities of the Federation of B&H during 2013. MATERIAL AND METHODS: Our concept of "preventive treatment of a patient" included detecting and monitoring the following chronic non-communicable diseases risk factors: (a) hypertension; (b) obesity; (c) smoking; (d) physical inactivity; and (e) dyslipidemia; (f) diabetes mellitus. Our sample of examined patients was 46.638. RESULTS: Highest risk prevalence within entire F B&H is observed for dyslipidemia (90.3%) and physical inactivity (64.7%). Lowest prevalence was found for blood sugar and hypertension at 19.2% and 21.6%, respectively. Smoking prevalence of the examined patients was 28.4%. Prevalence of the obesity as health risk (ITM > 30) was 25.5 %. It is of interest that statistically significant differences of individual risk prevalence among cities are evident. Risk distribution among cities ranked from highest to lowest prevalence, shows clearly that Sarajevo is leading in four risks compared to the other cities, while Zenica is ranked lowest for four risk factors. The examined population of the four cities can be ranked from lowest to highest prevalence of the examined risk factors as follows: Sarajevo, Mostar, Tuzla, and Zenica.
ABSTRACT
AIM: To determine the influence of sociodemographic factors on patients´ satisfaction with health care system. METHODS: In a cross-sectional study, 1,995 patients from 12 municipalities of Zenica-Doboj Canton were interviewed after a visit to the practice. Individual interviews were conducted and the questionnaire was made on the basis of EUROPEP (European Task Force on Patient Evaluations of General Practice Care) standardized questionnaire. RESULTS: Out of the total number patients, 47.1% were females, 47.9% were from urban population and median of age was 42.0 years (IQR = 30.0 to 53.0 years). The rural population was more likely to buy drugs for medical treatment (p < 0.001) and parenteral injections in primary care practice (p < 0.001). Patients with lower level of education were more likely: to be ordered for physical examination (p = 0.001), to buy drugs for medical treatment (p = 0.001), to buy parenteral injections in primary care practice (p < 0.001); to pay unofficially to someone from medical staff (p < 0.001); to feel that they could be better treated (p = 0.032) and they had longer waiting for health service in primary care practice (p < 0.001). Older population had better assessment of secondary (p = 0.040) and tertiary health care practices (p = 0.034); needed more time is needed to reach health facilities (p = 0.016), longer waiting for health service in primary care practice (p < 0.001); more likely to have health problems in the past 12 months but they did not request medical treatment (p = 0.008); more likely to be ordered for physical examination (p < 0.001); more likely to buy drugs for medical treatment (p = 0.004); more likely to buy parenteral injections in primary care practice (p < 0.001). CONCLUSION: The following variables: gender, age, overall perception of health status and financial status appear to be predictors of patients´ satisfaction.
ABSTRACT
AIM: To determine the rural-urban differences in primary care practice, hospital inpatient care and total services. METHODS: This cross-sectional study used data from Zenica-Doboj Canton in Federation of Bosnia and Herzegovina (FBiH). The overall sample size for the study was 1,995. Individual interviews were conducted in one randomly selected day of the week, except Monday and Friday, on the basis of EUROPEP (European Task Force on Patient Evaluations of General Practice Care) standardized questionnaire. RESULTS: Out of total number (n=1 995), 47.9% was urban population and median of age was 42 years for both populations. The most of urban residents (81.4%) had finished high school or higher education compared with rural residents (58.5%) (p < 0.001). There are significant differences in employment status between rural and urban population (p < 0.001). Rural residents are more likely to travel more than 15 minutes to see their health facilities compared with urban residents (61.7% vs. 24.4%, respectively). Median of distance (kilometers) from residence location to the nearest hospital was statistically significantly higher in rural Me = 8.0 (5.0 do 14.5) km compared to urban population Me = 1.5 (1.0 to 3.0) km (p < 0.001). The rural population was more likely to buy drugs for medical treatment (p < 0.001) and parenteral injections in primary care practice (p < 0.001). CONCLUSION: There are significant differences in the overall health care assessment of rural populations as compared to urban populations.
