Distribución y estado de nanoplaquetas y nanocintas en los composites

1. The information in the semi-structured interviews from the first qualitative strand of this study was analyzed from their full transcripts in Czech. A summary of the obtained information in English was prepared. The purpose of this simple analysis was to establish a more official knowledge base of this issue, because at that moment there were not any published analyses of this phenomenon in the CR. After concluding this initial strand of my study, I had confirmed information about the migration of Czech nurses from reliable sources, as opposed to previously unofficial opinions and fragmented knowledge. I used these confirmed findings to inform the two later strands by mixing data between sources and methods. Two informants with expert knowledge were intentionally selected to share the detailed information on the migration of Czech nurses with me.

2. The use of statistics is a common method to analyze quantitative data, and I intended to collect data from a large number of respondents. The goal of this strand was to describe the extent of the nursing migration phenomena in the Czech Republic. Therefore in the second

quantitative strand, the analysis of the quantitative data was performed using statistical

software SPSS 17.0 in summer 2014; for this step, I consulted a sociologist in the Czech Republic who performed the statistical tests, which I then analyzed. The sample consisted of 120 Czech nurses with migration experience, using non-representative, convenience and snowball sampling design. The respondents self-selected to participate in the survey, and a more reliable and representative sampling framework was not available.

The purpose of a descriptive statistics´ analysis is to describe the characteristics of only the study sample. Since the majority of the variables measured in this study was of categorical level, I used percentages and frequencies to describe the findings. The mean, range or standard deviation are typically used to report on continuous variables (Grant and Tomal, 2013).

Inferential statistics enables us to generalize the findings from a sample onto the whole population (Grant and Tomal, 2013). However, the performed inferential statistics tests were not used due to the limits of my sample, as recommended by the consulting statistician.

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Given the limiting sampling approach, the number and the characteristics of the non- respondents could not be assessed by evaluating the demographic characteristics of the respondents. Therefore, the sampling bias32 _{could not be estimated, and indeed some nurses} might have decided not to participate in the survey for specific reasons. Similarly, the sample size estimates could not be performed because the sample was not randomly selected. The data obtained in this strand were integrated with the findings of the last qualitative strand.

3. In the third qualitative strand of this study, I conducted three mini-focus groups with migrating Czech nurses in order to explore the findings from the previous strands in detail and answer the research questions in more depth. I followed a thorough and transparent procedure for the analysis of qualitative data to be able to justify the conclusions drawn from this strand (Grant and Tomal, 2013). I intentionally used the mechanical system for qualitative analysis (a variation to “the long table” technique), as opposed to using any qualitative data analysis software (e.g. NVivo, N6, Atlas, Ethnograph), with the goal of fully experiencing the process of qualitative analysis. Eliot & Associates (2005) suggest using Excel spreadsheets to analyze data from the focus group, and give a detailed description of this process as an alternative to the “long table” technique.

The method of thematic analysis was adopted, mainly because it is suitable for new qualitative researchers. Thematic analysis allows us to recognize themes and patterns across a dataset which relate to our research question (Brown and Clarke, 2013).

The analysis of the qualitative data obtained in the third strand began immediately after conducting the first focus groups (August 2015) and lasted until January 2016. The first step was always a transcription33 _{of the focus group recording, as I preferred to undertake transcript}

32 _{Sampling bias refers to a systematic overrepresentation or underrepresentation of a group of the population}

with certain characteristics, which has an impact on the representativeness of obtained results (Polit and Beck, 2004).

33 _{The focus groups were conducted in Czech, and they were transcribed in this language as well. The codes and}

themes were developed in English, and the demonstrative extracts of the participants statements were translated into English by the researcher. Inevitably, a certain spontaneity was lost in this translation. One page from two focus groups was translated as well in order to demonstrate the analytical process. See Appendix D1.

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based analysis as opposed to tape based analysis (Krueger and Casey, 2000a). The transcription process lasted approximately 10 hours for each recording, and it allowed me to get familiar with the data (for this reason I did not consider hiring a professional transcriber).

After preparing the transcript for analysis, I first read and then carefully and repeatedly re-read the transcripts to further familiarize myself with the data (Braun and Clarke, 2013). Then, while re-reading the first transcript, I marked all the relevant chunks34 _{of the participants´} contribution in the transcript with different colored pencils, with each color being a potential code. At this point, I also kept a list of the potential codes. According to Brown and Clark, coding is a process to identify an aspect of the data which relate to a research question. A code is “an expression of the content of the participant’s statement by which the researcher should grasp the meaning of the participant’s statement” (Braun and Clarke, 2013).

At this stage, the codes were definitely data driven, i.e. expressing what was said by the participants. I continued with this complete coding process (coding across the whole dataset) with the two remaining transcripts, returning back and forth to the list and to the other transcripts, always checking the previously suggested codes and considering their appropriateness (Braun and Clarke, 2013). This method, developed by Strauss and Corbin, is called constant comparison analysis, and is used to check the relevance of the developed codes.

The researcher can approach the actual process of qualitative analysis very individually, including the “long table” electronic approach, or any other suitable approach (Braun and Clarke, 2013). I collated all codes and their demonstrating statements in a color coded Excel table (each focus group had a different color font). For logistical reasons, I preferred this way of collating codes over the use of large roles of paper with relevant chunks glued onto them. During the coding process, I was able to move the chunks to different codes to optimize the answers to my research questions. The next step was to search for candidate themes. Brown and Clarke (2013) describes theme as a category which is broader than a code and has many facets, captures many ideas, but “all are organized around a central concept.” A good theme

34 _{I omitted coding chunks of the text which did not seem to contribute to answer the research questions (e.g.}

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should have enough data demonstrating it, should not be too busy and should not be created in a rush (Braun and Clarke, 2013).

I paid extra attention to naming the themes, which should be creative, informative, catchy, short, evocative, as well as making use of the active voice. (Braun and Clarke, 2013) Themes were later reviewed and named, redrafting the names several times. Also, the actual codes and themes were regrouped a few times. In the beginning of my analysis, two candidate themes emerged from the data:

1. The development of the Czech health care system 2. Nursing professionalism

The remaining codes all related to the motivation for migration, and were therefore grouped as such. After more analytical work with the transcripts, I reworked the themes and decided on four:

1. Discrimination

2. Returning home only to migrate again 3. Nursing professionalism

4. Reasons for migration

At that point, I consciously stepped away from the data for a week. When I returned to it, I was able to see the data with fresh eyes, and I decided to collapse theme No. 2 into themes No. 3 and No. 4. After more rewording, a less intense regrouping of codes, and after consulting the findings with my supervisors, I decided to keep the developed codes and themes, because they seemed to give thus far the best answers to my research questions, while fully utilizing all of the participants´ insights.

I analyzed how the themes related to each other and how each of them related to the research questions. When thinking about overarching themes, the topic of “development” seemed to unite a lot of my data. Later, I realized that different aspects of “respect” (e.g. nurses respecting patients, nurses respecting each other, nurses respecting guidelines, other health care

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professionals respecting nurses, society respecting nurses) as suggested by Bludau (2012), were present in many codes, and in all of the themes created from my qualitative data.

In January and February, 2016, I performed one last reading of the transcripts and compared them against the suggested codes and themes. Only after I had worked with the codes and themes for around six months was I able to approach the data more creatively and stop relying on their mere description. Also, I consulted the findings with my colleagues (qualitative researchers) at my university and they offered some unexpected feedback which contributed to an explanation of some factors. Consultation with my supervisors was sought as well, resulting in the final version of my qualitative findings. At this point, I re-read the transcripts and I consciously searched for any evidence of the following three concepts mentioned in the literature, which had only recently been suggested to me: transformation, respect and gender – i.e. concept-driven coding (Gibbs, 2008). I found evidence of “transformation”, and this reinforced my use of it as one of my codes; “respect” is overarching all of my themes.