Study design and setting
Institutional based cross-sectional study design was conducted from February 25 –April 25/2018 G.C among graduating nursing students at universities found in Amhara region namely University of Gondar, Bahir Dar University, Wollo University, Debre Birhan University, Debre Markos University and Woldia University.
Source and study Population
The source populations were all graduating BSc nursing students attending in Amara Region Universities whereas the study populations were all randomly selected graduating BSc nursing students in Amara Region Universities in 2018.
Inclusion and Exclusion Criteria
Graduating BSc nursing students attending regular degree program were included, whereas students who were critically ill during data collection period were excluded.
Sample Size Determination
Sample size was calculated using a single population proportion formula with the assumptions of P-value=0.25 which was the proportion of clinical practice competency in Hawasa university (4), a 95% confidence level, 5% margin of error and 10% non-response rate. Accordingly, the calculated final sample size of the study was found to be 307.
Sampling and Sampling Procedure
All universities having graduating nursing students were included in the study, and total sample size was proportionally allocated to each university. The lists of graduating students were obtained from the respective university registrar. Then, the study participants from each university were selected by computer generated simple random sampling technique.
Data Collection Method
The data was collected by six BSc nurses’ by using a pretested structured self-administered questionnaire and observational checklist which was adapted from previous studies which was conducted in Hawassa Ethiopia and international domains of competency for nurses (4, 6, 34). Since, English language is the medium of instruction in all Ethiopian nursing schools, it was used for the questionnaire and observational checklist. Factors associated with clinical practice competency was assessed by 29 reliable items (Cronbach’s alpha = 0.78) (items on clinical instructor factor, clinical environment, assessment method and clinical staff student interaction factors). The non-participatory observation was done prior to distributing self-administered questionnaire and oral consent was given for those nurse students who was observed but not the detail of observation. Observation was undertaken on 10% of the study population by using observational checklist to assess the actual clinical practice competency among graduating nurses which was used as a supplement study for the quantitative results.
Data Quality Assurance
Training was given for data collectors and supervisors about techniques of data collection and briefed on each question included in the data collection tool. The pre-test was conducted on 5% of sample size to ensure the validity of the tool, then correction was made before the actual data collection. Principal investigator and supervisors were checked on the spot and reviewed all the questionnaires to ensure completeness and consistency of the information collected and immediate action was taken accordingly. Double data entry was done by two data clerks and consistency of the entered data was cross-checked by comparing the two separately entered data.
Data processing and Analysis
The data were entered using Epi Data version 4.2 and exported to SPSS version 24 for analysis. Descriptive statistics like frequency, percentage and standard deviation was computed. Binary logistics regression model was applied to identify factors associated with clinical practice competency. For analysis of clinical practice competency, all questions were coded as yes and no response and finally those graduating students who score 50% and above were labeled as clinically competent and those who scored below 50% were labeled as clinically incompetent. Observational data was analyzed using and the result was carefully triangulated to validate the quantitative result. All variables with P ≤ 0.25 in the bivariate analysis were included in the final model of multivariate analysis in order to control all possible confounders. Multi-collinearity was checked to see the linear correlation among the independent variables by using standard error. Variables with a standard error of > 2 were dropped from the multivariable analysis. Model fitness was checked with the Hosmer-Lemeshow test. Adjusted odds ratio with 95% CI was estimated to identify the factors associated with clinical practice competency using multivariable logistic regression analysis. Level of statistical significance was declared at p-value <0.05.