Reliability and Validity
Thestudy recruited a large population sample of 4,864 nurses from 60hospitals randomly selected which was supplemented to the hospitaldischarged data of 113,426 patients this reduces errors associatedto population biases (Cho et al., 2016). The researcher engaged in adialogue with the nurses during the data collection this allowed thecollection of enough data to answer the study questions entirely. Forinstance, the study findings state that the most encounterednurse-reported adversative events included wrong medication, injuryfrom fall after admission and pressure ulcers. In fact, a stratifiedrandom sampling method was used to in order ensure that aproportionate number of nurses were represented from the selectedhospitals (Cho et al., 2016). This is important because using thisstrategy adds credibility to the findings of the study. Moreover, thesurvey data were collected using the Korean version of the PracticeEnvironment Scale of the Nursing Work Index (PES-NWI) (Cho et al.,2016). Also, the study findings were consistent with the datacollected from the existing researches, and this shows highcoefficient reliability in the research, though, the author did notindicate the co-efficient values.
Theresearchers took great care to ensure that the findings of the studywere not biased in any way. It is important to note that thevariables studied for adverse events were the frequency of wrongmedication administration, patients’ experience of pressure ulcer,and frequency of fall with an injury following admission and they aredirectly correlated to the work environment and the number of nurseshandling the patients. A 7-point Likert scale was used by nurses tomeasure each adverse event. In keeping with acceptable scientificstandard, this data collection tool has trusted validity andreliability for conducting research (Houser, 2016). The data analysiswas conducted using descriptive statistics and multilevel ordinallogistic regression, given that the researchers had to analyze nursesurvey data, hospital facility data, and patient hospital dischargedata. More specifically, the STATA version 13.1 software, ascientifically reliable tool for analyzing research data, was usedfor overall data analysis (Cho et al., 2016).
Cho,E., Chin, D. L., Kim, S., & Hong, O. (2016). The relationships ofnurse staffing level andworkenvironment with patient adverse events. Journal of NursingScholarship, 48(1), 74-82. doi:10.1111/jnu.12183
Houser,J. (2016). Nursing research: Reading, using, and creating evidence(4th ed.). Sudbury, MA: Jones
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