As with the data collection for this study, data analysis of the quantitative and qualitative data occurred simultaneously. Data analysis of quantitative data began after an acceptable number of responses were obtained as determined by power analysis.
Qualitative data analysis commenced upon the completion of all interviews.
Quantitative data analysis. Data obtained from the BKAT-7 and demographic
tools was be entered in the statistical software package SPSS Version 15.0. Staff nurses were be divided into new graduate and experienced cohorts based on the number of months that they had worked as indicated on the demographic tool. Experienced nurses
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were grouped in a single cohort however the newly graduated nurse cohort was further subdivided into three groups based on the NGN transition intervals established by Schoessler and Waldo (2006). Demographics and BKAT scores were reported using descriptive statistics and a frequency distribution was developed to determine the appropriateness of parametric testing. The assumptions for parametric testing include interval or ratio levels of measure, random sampling, normally distributed populations, and independence of measures (Sprinthall, 2007). Since the assumptions for parametric testing were met, data analysis was completed including t-tests and analysis of variance (ANOVA). The 2-tailed t-test was used to determine the hypothesis of difference of mean BKAT scores between the NGN and experienced nurse groups. ANOVA was used to determine if there is significance between BKAT means in more than 2 groups. ANOVA was used to analyze the NGNs‟ scores within the three stages as well as between the three entry degree levels. The mean BKAT scores met the parametric testing requirements of both t-tests and ANOVA by coming from independent groups (NGNs and experienced nurses for t-test and NGN stages and degree level for ANOVA) and being interval data. If the assumptions of parametric tests had been unmet, then equivalent non-parametric tests would have been performed.
Qualitative data analysis. Qualitative data analysis occurred using an approach
outlined by Creswell (2003). These steps included data transcription and reading, data coding, rendering descriptions, and interpreting the data. Upon the completion of each interview, the data was transcribed verbatim into a word processing program. An analysis team consisting of the principal investigator (PI), two members of the dissertation
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analyzed the data. After individually reviewing and commenting on the transcribed tapes, the team members met via conference call to discuss the major categories and thematic analyses identified by the PI. Secondary interviews in person or over the phone were conducted to validate or increase the depth and breadth of themes as identified during analysis.
Often discussed in qualitative research, the concept of bracketing was not adopted when using hermeneutic phenomenology. After engaging in a self-reflective process, the researcher was not required to set aside pre-conceived beliefs, but instead entrenched those assumptions in the interpretive process. This essential step was achieved through journaling. The researcher included apriori experiences on an ongoing basis which assists in interpreting the data. This step permitted the researcher to incorporate implicit and explicit knowledge of the concept to enhance understanding (Laverty, 2003).
Trustworthiness, credibility and dependability of the data were established through purposive sampling. The researcher selected willing participants from the convenience sample based on sample characteristics including length of time since graduation and type of unit (specialty specific i.e. cardiac or general care) in which the NGN works. Only NGNs who were willing to reflect on the phenomena of interest were selected. Participant selection continued in each new grad group until saturation was reached. A comparison of data captured during the taped interview and transcription was conducted as well as a comparison of the responses given by the NGNs. Additionally the researcher who was the sole data collector journaled throughout the research process. Since NGNs face similar challenges wherever they choose to begin practice it was hoped
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that the authentic data that was gained is transferable to NGNs working in critical care units outside of this geographic region.
Triangulation. Used to boost credibility and enrich data, triangulation requires
using more than one type of data to validate conclusions (Polit & Beck, 2004). The use of unstructured data obtained during NGN interviews was blended with the quantitative measure of NGN knowledge. Upon the completion of qualitative analysis, the PI looked for relationships between the decision making and clinical judgment experiences of NGNs and their BKAT scores. A comparison were made between the NGN clinical judgment experiences, their group scores on the BKAT, and the length of time that the NGNs have been practicing. The coupling of qualitative and quantitative data assisted the researcher to understand and provide an accurate depiction of the phenomena of NGN basic knowledge and decision making in the critical care arena.
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Chapter 6
Results
Introduction
Simultaneous quantitative and qualitative data analysis began after four months of BKAT data collection. At that point no additional BKAT packets were being returned in response to flyers or the researcher visiting the units. Qualitative data analysis included journaling and taking field notes. Analysis of the NGN interviews began after all the interviews were completed and transcribed.