Problems of Clinical Nurse Performance Appraisal System: A Qualitative Study

PURPOSE: The purpose of this study is to explore problems of clinical nurse performance appraisal system. METHODS: This study employed a descriptive qualitative approach. The participants were purposively selected from clinical nurses working across all of the hospital units in a large metropolitan teaching hospital in Tehran, Iran in 2012. Data were collected using five focus group interviews, which were audio taped. The number of participants in each group ranged from 7 to 10. The semi-structured interviews were guided by a set of nondirective questions, and continued until the data reached saturation. Data were analyzed using framework analysis. RESULTS: Four major themes regarding the problems of clinical nurse performance appraisal system emerged from the analysis of textual data. These themes were contextual problems, problems related to performance appraisal structure, problems related to performance appraisal process and those related to performance appraisal results. CONCLUSION: The findings of this study reveal that the nurse performance appraisal system confronts with various problems. Some of these problems are related to organizational context while the others concerned structure, process and results of the performance appraisal system. In order to achieve high quality of patient care as the final goal of performance appraisal, changing and revision of this system is necessary.

Comparison of univariate and multivariate gene set analysis in acute lymphoblastic leukemia.

BACKGROUND: Gene set analysis (GSA) incorporates biological with statistical knowledge to identify gene sets which are differentially expressed that between two or more phenotypes. MATERIALS AND METHODS: In this paper gene sets differentially expressed between acute lymphoblastic leukaemia (ALL) with BCR-ABL and those with no observed cytogenetic abnormalities were determined by GSA methods. The BCR-ABL is an abnormal gene found in some people with ALL. RESULTS: The results of two GSAs showed that the Category test identified 30 gene sets differentially expressed between two phenotypes, while the Hotelling's T2 could discover just 19 gene sets. On the other hand, assessment of common genes among significant gene sets showed that there were high agreement between the results of GSA and the findings of biologists. In addition, the performance of these methods was compared by simulated and ALL data. CONCLUSIONS: The results on simulated data indicated decrease in the type I error rate and increase the power in multivariate (Hotelling's T2) test as increasing the correlation between gene pairs in contrast to the univariate (Category) test.