Study settings and period
This study was conducted in Public Referral Hospitals of West Amhara Regional State, Ethiopia from January to February 2021. The regional state contains; 28 million population in mid – 2018 and it has 14 Zones, three- city administrations, and 180 woredas (139 rural and 41 urban . It also has 80 hospitals (8 referrals, 2 general, and 73 primaries), 847 health centers, and 3,342 health posts . Despite the increased number of health facilities, shortages of skilled health personnel, medical equipment, drugs, and medical supplies, inefficient and inequitable use of health resources are the challenges of the region . There are eight referral hospitals in Amhara regional state. Among them five of them (Debremarkos referral hospital, Tibebe Gion referral hospital, Felege Hiwot referral Hospital, Debre Tabor Referral Hospital and University of Gondar referral Hospital) were located in the north west part of the region where this study was conducted. Considering the resources, the University of Gondar (financial funders of this study) suggested to focus on hospitals located in the northwest part of the region. As a result, we included all the five hospitals in the study.
Study design and population
An institution-based cross-sectional study was conducted among nurses who were working in Public Referral Hospitals in Amhara region. The source population were all nurses working in each hospital. All permanently employed nurses with work experience of equal or greater six months during and working the time of study, and who agreed to participate in the study were included.
Sample size, sampling technique and procedures
To calculate the sample size, we considered the working condition as 50% and with an alpha error of 5%, a power of 95% and 10% of non-response rate. Then, 423 sample sizes were required for the study. Currently, there are five referral hospitals in West Amhara regional state from which samples were selected. For each hospital, the total sample size was allocated proportionally based on the number of nurses they had. Then, systematic random sampling was used to select nurses from each hospital. Then, the samples were taken from each working unit as per the sampling frame.
The dependent variable of the study was working environment. Age, sex, marital status, education status, position at work, professional experience,, working unit, salary, patient nurse ratio, working shift, hours worked, autonomy, flexibility schedule, participation in decision making, relationships with physicians, recognition of work, professional advancement opportunity, professional identification, satisfaction with salary were the explanatory variables.
Nurses working environment
Composite score was computed and nursing work environment was classified as healthy if the participants scored mean and above, and not healthy if they scored below the mean .
Data collection tools, measurements and procedures
The data were collected using self-administered English version questionnaires which were adapted from validated and standardized existing tools. The tools have two sections. Part-I: Socio-demographic and professional-related characteristics of nurses, and Part-II: working environment of nurses measurement scales.
The working environment was measured by the Practice Environment Scale of the Nursing Work Index  and which was validated in Spanish with Cronbach’s alpha coefficients of 0.90 . The scale was a five-point Likert scale (5 = Strongly Agree, 4 = agree; 3 = neutral; 2 = disagree, and 1 = strongly disagree) which consisted of 32 items. Nurses indicated the degree, according to what had been presented in each item in their work. In this study the scale has an item reliability of Cronbach’s alpha coefficients of 0.92 and has five outcome subscales (nurse participation in hospital affairs -α = 0.87, nursing involvement for quality of care-α = 0.83, nurse manager ability-α = 0.8, leadership and support of nurses, staffing and resource adequacy-α = 0.76 and collegial nurse-physician relationships-α = 0.89).
The overall Practice Environment Composite score was calculated from the average of subscale scores. Then, the mean score was used to classify the working environment of nurses in to two groups (conducive and non-conducive). Respondents who scored mean (98.3 ± 18.4) and above the mean score were classified as conducive, while those who scored less than the mean score were classified as non-conducive nursing environments.
Data management and analysis
EPI- DATA 3.1  was used for data entry and SPSS version-23 software  for data analysis. Descriptive statistics were made using statistical measurements. Frequency, percentages, means, and standard deviations were calculated. The outcome variable was categorized as conducive and non-conducive environment. Normality tests were performed using the normal Q-Q graph and the Kolmogorov- Smirnov goodness adjustment test and Practice Environment Scale of the Nursing Work Index admit the normal model. Binary and multivariable logistic regression analyses were computed to identify associated factors. Finally, texts, tables and graphs were used to report findings.
Quality assurance mechanisms
Before collecting the data, the face and content validity of the data collection tool was assured, checked by inviting experts in the field. The data collectors and supervisors were trained about the study purpose, and protocol. The research data collection tool was piloted (pre-tested) to check the fitness of the tool for the study settings and necessary corrections were made. The investigators exchanged all the necessary information regarding the data collection procedures with the supervisors on the daily basis. Furthermore, the respondents had been given brief information sheets to read before the filling in the questionnaires, and supervision was also done at the spot by the supervisors. In addition, detailed feedback was provided to the data collectors. The collected data were coded per operational definitions of the study variables and cheek-rechecked by the principal investigators for its completeness .
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