why do we collect data in research

Regardless of the field of study or preference for defining data ( or ), accurate data collection is essential to maintaining the integrity of research. Both the selection of appropriate data collection instruments (existing, modified, or newly developed) and clearly delineated instructions for their correct use reduce the likelihood of
occurring. A formal data collection process is necessary as it ensures that the data gathered are both defined and accurate and that subsequent decisions based on arguments embodied in the findings are valid. The process provides both a baseline from which to measure and in certain cases an indication of what to improve. Once all of the research interviews have been transcribed and checked, it is time to begin coding. Field notes compiled during an interview can be a useful complementary source of information to facilitate this process, as the gap in time between an interview, transcribing, and coding can result in memory bias regarding nonverbal or environmental context issues that may affect interpretation of data.


Coding refers to the identification of topics, issues, similarities, and differences that are revealed through the participants narratives and interpreted by the researcher. This process enables the researcher to begin to understand the world from each participant s perspective. Coding can be done by hand on a hard copy of the transcript, by making notes in the margin or by highlighting and naming sections of text. More commonly, researchers use qualitative research software (e. g. , NVivo, QSR International Pty Ltd; ) to help manage their transcriptions. It is advised that researchers undertake a formal course in the use of such software or seek supervision from a researcher experienced in these tools.


Returning to and reading from lines 8 11, a code for this section might be diagnosis of mental health condition, but this would just be a description of what the participant is talking about at that point. If we read a little more deeply, we can ask ourselves how the participant might have come to feel that the doctor assumed he or she was aware of the diagnosis or indeed that they had only just been told the diagnosis. There are a number of pauses in the narrative that might suggest the participant is finding it difficult to recall that experience. Later in the text, the participant says nobody asked me any questions about my life (line 19). This could be coded simply as health care professionals consultation skills, but that would not reflect how the participant must have felt never to be asked anything about his or her personal life, about the participant as a human being.


At the end of this excerpt, the participant just trails off, recalling that no-one showed any interest, which makes for very moving reading. For practitioners in pharmacy, it might also be pertinent to explore the participant s experience of akathisia and why this was left untreated for 20 years. One of the questions that arises about qualitative research relates to the reliability of the interpretation and representation of the participants narratives. There are no statistical tests that can be used to check reliability and validity as there are in quantitative research. However, work by Lincoln and Guba suggests that there are other ways to establish confidence in the truth of the findings (p. 218).


They call this confidence trustworthiness and suggest that there are 4 criteria of trustworthiness: credibility (confidence in the truth of the findings), transferability (showing that the findings have applicability in other contexts), dependability (showing that the findings are consistent and could be repeated), and confirmability (the extent to which the findings of a study are shaped by the respondents and not researcher bias, motivation, or interest). One way of establishing the credibility of the coding is to ask another researcher to code the same transcript and then to discuss any similarities and differences in the 2 resulting sets of codes. This simple act can result in revisions to the codes and can help to clarify and confirm the research findings.

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