Response to COVID-19 recommended preventive behavioral messages among Guraghe zone communities, South Ethiopia: using constructs of the Extended Parallel Process Model (EPPM).

INTRODUCTION: The World Health Organization declared COVID-19 is a pandemic disease. Countries should take standard measures and responses to battle the effects of the viruses. However, little is known in Ethiopia regarding the recommended preventive behavioral messages responses. Therefore, the study aimed to assess the response to COVID-19 recommended preventive behavioral messages. METHODS: Community-based cross-sectional study design was carried out from 1 to 20, July 2020. We recruited 634 respondents by using a systematic sampling method. Data were analyzed using Statistical Package Software for Social Sciences version 23. Association between variables were explored using a bivariable and multi variable logistic regression model. The strength of the association is presented using odds ratio and regression coefficient with 95% confidence interval. A p-value of less than 0.05 was declared statistically significant. RESULTS: Three hundred thirty-six (53.1%) of respondents had good response to recommended preventive behavioral messages. The general precise rate of the knowledge questionnaire was 92.21%. The study showed that merchant was 1.86 (p ≈ 0.01) times more likely respond to COVID-19 recommended preventive behavioral messages than government-employed. Respondents who scored one unit increase for self-efficacy and response-efficacy, the odds of responding to COVID-19 recommended preventive behavioral messages were increased by 1.22 (p < 0.001), and 1.05 times (p = 0.002) respectively. Respondents who scored one unit increase to cues to action, the odds of responding to COVID-19 recommended preventive behavioral messages were 43% (p < 0.001) less likely. CONCLUSION: Even though respondents were highly knowledgeable about COVID-19, there is a lower level of applying response to recommended preventive behavioral messages. Merchant, self-efficacy, response efficacy, and cues to action were significantly associated with response to recommended preventive behavioral messages. Like merchants, government employer should be applying preventive behavioral messages and also, participants' self and response efficacy should be strengthened to improve the response. In addition, we should be changed or modified the way how-to deliver relevant information, promoting awareness, and also using appropriate reminder systems to preventive behavioral messages.

Factors influencing drop-out of households from community based health insurance membership in rural districts of Gurage Zone, Southern Ethiopia: Community based case-control study.

Background: Financial risk-sharing through community-based health insurance is a critical component of universal health coverage. However, its development is a great challenge, not only due to low enrollment but also due to the high dropout rate of members from the program, which threatens its sustainability. So far, the few existing studies in this area have focused on household enrollment into community-based health insurance, rather than on the number of members dropping out. This study aims to identify factors influencing households to drop out of community-based health insurance membership in rural districts of the Gurage Zone, Southern Ethiopia. Methods: A community-based case-control study was carried out from May to July 2021. Supplemented by qualitative focus group discussions. Multi-stage sampling was employed. An interviewer-administered prearranged tool was used for collecting data. Epi-data version 3.1 and SPSS version 21 were used for data entry and analysis. The association between factor and outcome variable was determined using binary logistic regression analysis at p < 0.05 and 95% CI. Qualitative data were analyzed thematically and triangulated. Results: From 525 (175 cases and 350 controls) rural household heads 171 cases and 342 controls responded, yielding a response rate of 97.7%. Of those, 73.1 and 69.0% were males in cases and controls, respectively. The statistically significant influencing factors associated with dropout from community-based health insurance were: highest wealth status (adjusted odds ratio [AOR] = 2.36, 95% confidence interval [CI]:1.14-4.87), unfavorable attitude toward CBHI (AOR: 1.81, 95% CI: 1.87-3.37), no illness experienced in the last 3 months (AOR: 5.21, 95% CI: 2.90-9.33). no frequent health facility visits (AOR:5.03, 95% CI:1.17-23.43), no exposure to indigenous community insurance (AOR:0.10, 95% CI: 0.03-0.37), not graduated in the model household (AOR: 3.20, 95% CI:1.75-5.83), being a member in the program for more than 3 years (AOR:0.55, 95% CI: 0.29-0.94), not trusting governing bodies (AOR:10.52, 95% CI:4.70-23.53), the ordered drug was not available in the contractual facility (AOR:14.62, 95% CI:5.37-39.83), waiting time was >3 h (AOR:4.26, 95% CI:1.70-10.66), and poor perception of service quality (AOR:12.38, 95%CI:2.46-62.24). Conclusion: The findings of this study illustrated various factors which positively and negatively influenced households to drop out from CBHI: wealth status, attitude toward CBHI, perceived poor provider attitude toward CBHI members, illness experience in the household, the experience of frequent health facility visits, model household graduation status, trust on CBHI committee (governing bodies), availability of a prescribed drug in the contractual health facility, waiting time and perceived quality of health service from the contractual facility, exposure to any of the indigenous insurance (IDIR and/or IQUB) and length of membership in program. We strongly recommend all responsible stakeholders give strong attention to promoting the community, and for providers to project a favorable attitude toward community-based health insurance, to achieve model household graduation, and improve quality of service by addressing the basic quality-related areas like waiting time, and drug availability).