Study Design and Period: School based cross-sectional study was conducted in two randomly selected governmental preparatory schools among 541 regular preparatory school students in Arba Minch town from December 01-30/2019.
Study Area: The study was conducted in Arba Minch town which is found in Gamo zone, the Southern Nations Nationalities and Peoples Region (SNNPR). It is located in Southern 505km far from Addis Ababa (capital city of Ethiopia) and 275km southwest of Hawassa (capital town of the regional state). It is structured or divided in to 4 sub city and 11 kebeles in order to facilitate socio-economic development of the town residents. Arba Minch is home to14governmental health facilities, 34 private clinics, 13 drug store and 2 community pharmacy providing health care services for the community and also23 primary schools [8 Governmental, and 15 private (4 of them are 1-4 grade)], 9 high schools (5 Governmental and 4 privates) and 6 preparatory schools (3 Governmental and 3 private schools). Total number of the students enrolled in 2019 G.C. 11th and 12th grade are 2878 (2274 students in governmental and 604private schools).
Source Population: All students enrolled to preparatory school in Arba Minch town in 2019.
Study Population: All students in randomly selected preparatory schools in Arba Minch town were the study population.
Inclusion and Exclusion Criteria
All regular students between ages of 15-19years old enrolled in to preparatory school in 2019 and Regular preparatory school students drop out from school, severely sick and unable avail themselves on the data collection period were exclude.
Sample Size Determination: A single population proportion formula was used to calculate the required sample size by assessment of RH service utilization and associated factors among high students (p) = 67.3% in Goba town, confidence level of 95%, and 5% of margin of error the sample and the underlying population as follows:
Where: n= sample size required; p = Estimated proportion of RH among preparatory adolescents = 0.673 (from Goba; d = maximum tolerable error which is = 0.05; Z = value of standard normal distribution at 95% confidence level which is1.96.
Finally by adding 10% nonresponse rate and because of multistage sampling method was used sample size 338 was multiplied by design effect 1.5 and the final sample sizes was 541.
Sampling Technique
After calculating sample size, two stage sampling technique was used by considering two preparatory schools in Arba Minch town and also students was stratified in to eleventh and twelve’s grade stream and then to male and female. The samples were selected by using simple random sampling (SRS) technique and from each grade and sex. The sample size was distributed to each grade proportional to their size. Generally, the required numbers of students was selected computer generated numbers from each grades and sex (figure 1).
Data Collection
Data was collected by using semi-structured self-administered method by using pre-tested questionnaires. Data collection period was from Dec. 10-11/2019. Data collectors were school instructors and facilitator was selected for the school a day before the data collection. The purpose of the study was explained to study participants in order to identify the clarity of questionnaires and their sensitiveness.
Data Quality Control
To assure the quality of the data, orientation was given for data collectors and supervised, on spot checking and reviewing the completeness of questionnaires done by investigator. The questionnaires was prepared originally in English and translated to Amharic then back to English. The questionnaire was pre-tested among 5% of similar setting students In Birbir preparatory students before the actual data collection processes to ensure its clarity, ordering, consistency and acceptance. After collecting the data, each questionnaire was checked for completeness and being filled correctly.
Data Management and Analysis
Data was entered in to EpiData version 4.6 and export to SPSS Version 25 software package for analysis. Bivariate logistic regression was used to identify the association between the dependent and independent variable. The variables whose significance level less than P<0.25 were considered as candidate for the multivariable logistic regression analysis. Before multivariable analysis, independent variables were checked for multicollinearty effect using correlation matrix. Hosmer-Lemshow test was used to test goodness-of-fit to assess whether the necessary assumptions for application of multivariable logistic regression. Finally to determine the independent factors associated with F/P and VCT utilization, multivariable logistic regression was done. Variables with P-value <0.05 in the final model was considered statistically significant. Variables were explained by frequency text, tables and figures.