Description

Rationale

Evidence on the effectiveness of screening and brief-intervention of unhealthy alcohol consumption in conflict-affected population in countries like Ethiopia are insufficient. This can affect the development and implementation of effective alcohol policies and interventions unless more studies strive to fill such gaps.

By screening post-war alcohol consumption and examining the efficacy of brief-interventions, this research will address the gap on the effectiveness of Screening and Brief-Intervention on reduction of hazardous/harmful alcohol consumption among public hospital outpatients. Findings can lead policymakers and health professionals to develop initiatives that promote abstinence or low risk drinking behavior to improve alcohol related health outcomes among hospital outpatients. Findings of this study can assist the development of evidence-based policy and management programs to reduce risky alcohol consumptions among public hospital outpatients.

Therefore, post-war alcohol consumption in Tigray public hospital outpatients needs to be rigorously studied to formulate an appropriate and effective intervention mechanism to prevent and reduce risky alcohol consumption among outpatients.

General Objectives:

To screen post-war alcohol consumptions and test the effectiveness of Brief-Intervention in reducing risky alcohol consumption among Public Hospital outpatients in Tigray from 2024 to 2026.

Specific Objectives:

To assess rate of post-war alcohol consumption among public hospital outpatients in Tigray from 2024 to 2026.

To determine associated factors of post-war alcohol consumptions among public hospital outpatients in Tigray from 2024 to 2026.

To test the effectiveness of screening and Brief-Intervention of alcohol consumption among public hospital outpatients in Tigray.

Methodology

The researchers want to study the effectiveness of screening and brief-intervention of post-war alcohol consumption among public hospital outpatients in Tigray. The study will have a continuous outcome (AUDIT score) and equal sample size in both intervention and control groups. Therefore, the researchers prefer to use the simplest established formula to calculate the sample size in each group as follows.

Assuming the mean difference in AUDIT score between intervention and control groups that this study will bring is 4.4, Standard Deviation is 10, alpha (α) is 0.05 at 95% confidence interval, beta (β) is 0.20 then the sample size in each group is calculated to be n=81 with a total required sample of 162. However, since evidence are reporting that there were 28% and 33% of loss of follow-up at 6 and 12 months respectively, the required sample size in each group will be inflated to 131 with a total required sample size of 262. All female and male outpatients aged 18 years and above with no serious medical or mental illnesses with an AUDIT score of 8-19 will be included in the intervention. While outpatients less than 18 years, those with serious illnesses and have an AUDIT score of less than 7 or ≥ 20 will be excluded from the intervention.

Intervention group will receive a single session of simple advice, brief-counseling and broacher with 6-and 12-months follow-up screening. Whereas outpatients in control group will only receive the 6- and 12-months follow-up screening to see their level of alcohol consumption.

Data management and analysis Data will be collected via face-to-face interview by trained data collectors. Collected data will be handled in a secured place and in a confidential way. The data will be coded, entered and analyzed to SPSS Vs 26. Means, standard deviations and percentage will be used for the descriptive statistics. Independent sample t-test or Mann-Whitney U test will be used to compare the mean of normally distributed or none-normally distributed AUDIT scores between intervention and control groups respectively. Repeated measure ANOVA will be used to test the effectiveness of Screening and Brief-Intervention of post-war alcohol consumption. However, non-parametric alternatives like Friedman test will be also used if assumptions for parametric statistics are failed.