Guaranteeing Trustworthiness in Qualitative Research
Trustworthiness in qualitative research means consistency, objectivity and lack of ambiguity in testing statistical data or sets of measurements. In other words, it implies how accurate the measuring device is in measuring what it alleges to measure. It relates to the ability of research instruments to produce findings that are in agreement with theoretical or conceptual values (Marshall, & Rossman, 1999). Trustworthiness in qualitative research is guaranteed through construction of appropriate data collection methods and analysis. It is not achieved through manipulation of quantitative variables. Trustworthiness is concerned about the reliability of data that is, it seeks to know whether conclusions made are reliable. In qualitative research, it is enhanced through increasing verifiability of the perspective or by applying triangulation. Furthermore, the researcher can construct a checklist for testing possible errors. Once detected, the researcher makes sure that they are rectified in data collection, conclusion and methodology (Silverman, 2001).
A researcher makes sure that trustworthiness is achieved through adopting the principle of coherence. This is related to following scientific rule, which states that methods must meet the goals or objectives of the study. The research questions must be answered by the results of any study. If a research does not accomplish this mission, other canvassers could not accept the findings. The study should not only answer a single research question meaning that all questions are to be addressed by the findings. Furthermore, trustworthiness of any research can be realized through adopting openness that is, to what extent did the researcher use otherwise suitable methods (Rubin, & Rubin, 2005). Each study is special, which calls for specific methods. It is upon the researcher to carry out preliminary investigation to identify the most suitable qualitative research method. Application of case studies may not yield needed results in all cases. Finally, findings are more reliable when conducted by a group of researchers.
Analyzing Interview Data for Themes
Data analysis in qualitative study calls for a canvasser to classify prototypes and themes in the unruffled data. This is a multifaceted duty, particularly with qualitative studies, which are non-numeric and frequently in a textual or storyline structure. Interpreting qualitative data is a mesmerizing, but protracted process because of large amount of data. A well-groomed research approach can help an investigator to bring order to his/her study without being caught up in the process. The first step would be reading and evaluating collected data, which is an important stage of data analysis in qualitative studies. Qualitative data usually entails interview notes or transcriptions. As a researcher goes through interview data, it is advisable that he/she writes some notes. The researcher marks key passages or can make notes in the boundaries. Since data generated through interviews is capacious, the researcher looks for ways of managing it. This could involve the use of file folders to sort out critical data succinctly. The researcher moves on to code data, which implies classifying themes within interview notes. In other words, themes are regular ideas and prototypes that the researcher observes repetitively as he/she goes through collected information. Themes are not identified instantly meaning that a canvasser would have to go through collected data continuously to identify them.
After identifying main themes, the researcher proceeds to interpret data by assigning particular meaning to such themes and prototypes. Furthermore, the researcher is to write a list of major prototypes and ideas as he/she goes on with evaluation process. At this stage, it is important for a researcher to come up with alternative explanations by scrutinizing variations of answers documented in collected data. Finally, the researcher should draft a report that documents his/her conclusions. This is because writing a study report is part of data analysis in qualitative research. Writing a report allows the researcher to make sense of the collected information by fusing and summarizing them.
Using Nvivo Software
For a researcher to comprehend how various themes mesh together to form a whole, it is important to evaluate individual themes. The use of software could prove to be problematic, although it is resourceful as far as counting of respondents is concerned. A theme is associated with other ideas by considering notes written in the process of evaluation. The model explore in the Nvivo software is very essential since it is utilized in outlining diagrammatically how the prototypes relate to each other. Once information have been evaluated manually, it is possible to start the coding process again with only thematic codes being utilized. This stage of data analysis is significant in qualitative studies because it guarantees inclusion of theoretical ideas. Themes that could have emerged in the first round of coding are analytically indicated in the data. This addresses the problem of validity (Creswell, 1998). Specific words in the interview note are coded automatically as opposed to doing it manually, which is time consuming and inaccurate. In the interview note provided, honesty is one of the themes that appear in almost all answers given by the respondents, meaning that it could easily be captured by the software. All respondents holding the principle that honesty is a desired quality in a role model can be grouped together. This shows that Nvivo coding takes place after interpreting themes manually, although it depends on the size of data. Electronic and manual coding of themes are applied jointly in order to realize powerful results.
The search engine in Nvivo permits the canvasser to cross-examine his/her data at any level. This develops the rigor for evaluation process by authenticating some of the investigator’s impression of data. On the other hand, the software is less helpful in terms of tackling issues related to legality and consistency in the thematic thoughts that emerge during data investigation process. Obviously, information can be verified from the content of certain nodes and this could influence the way themes are related. Nevertheless, when checking for themes NVivo is less helpful just because of the type of searching it is able to do. It is essential that canvassers identify the importance of both handbook and electronic instruments in qualitative studies (Strauss, & Corbin, 1990). The two techniques can augment each other to produce acceptable results.
Data obtained through interview guides can be scrutinized using Nvivo software. It is not a difficult process hence saves time and resources. Interview guides produce too much information that needs categorization and elucidation. The researcher organizes data to set up what is pertinent to the study. One method in which such accuracy could be achieved is by employing the search facility in NVivo, which is perceived by the manufacturing designers as one of its key resources that enables assessment of information (Lee, & Esterhuizen, 2000). This is realistic when data is searched in terms of distinctiveness. In this study for example, the canvasser seeks to know why individuals like certain people. Obviously, analyzing such results through electronic means would produce more reliable results than conducting it manually. The software ensures that human slip-up is avoided.
Preparing a Write-up of interview Data
After collecting and analyzing data from an interview note, a researcher should report the findings. The report should present a clear and objective description of data gathered, as well as findings and inferences drawn from data. There are some specific principles that must be taken into consideration. First, before a researcher designs a report, he/she must formulate an outline that stresses on the importance of the report. The intention or goal of the report must also be made clear to the audience at this stage. For accurate writing of a report, a researcher needs to make a framework that would help him identify what to focus on. The researcher can then put his/her findings in a logical order. What follows is the writing of main body, which discusses the things listed in the outline. Furthermore, the researcher should write appendixes. It is advisable that the researcher starts with the simplest part in order to acquaint the audience with what actually is contained in the report. Jargons should follow later because not all people are familiar with scientific or professional terms. Writing should be coherent and fluent because it would help the researcher to develop a powerful final report (Blank, 2004). It is suitable for the researcher to re-visit the main body after taking some time because it would facilitate some objectivity. The researcher must try as much as possible to convince the audience that the findings are applicable by using facts from data instead of using additional information that can upset the reader.
A good report must have an extensive introduction that tells readers what the main body contains. This implies that any report should be introduced in a simple way, in order make things clear for the reader. The introduction should not be detailed but it should only talk about the main points of the report. A researcher can go ahead to write recommendations and conclusions after introducing the topic. Such conclusions should logically be based on results and data. Furthermore, recommendations must be based on conclusions. This implies that there must be consistent progression of ideas from results to suggestions and conclusions. A summary of the report is written last. It should visibly state the findings and views of the study. Major ideas of the report, suggestions and conclusions are restated in the summary section (Patton, 1990). Finally, it is necessary for a researcher to get a third or even a fourth person to give his/her opinion before drafting a final report. Generally, it is advisable to allow others review the findings of the study before presenting them to the audience. There are errors that could have been omitted by the researcher during revision, which can be identified by others. A report is very important because it determines the reliability, as well as validity of the study. The report should be written in a tentative manner meaning that it should be open to criticism. A researcher should recommend further studies by arguing that his/her findings can be utilized as preliminary data in conducting powerful studies in future.
References
- Marshall, C., & Rossman, B. (1999). Designing qualitative research (3rd ed.). Newbury Park: Sage.
- Rubin, H., & Rubin, S. (2005). Qualitative interviewing: The art of hearing data (2nd ed.). Thousand Oaks, CA: Sage.
- Silverman, D. (2001). Interpreting qualitative data: methods for analyzing talk, text and interaction (2nd ed.). London: Sage.
- Blank, G. (2004). Teaching qualitative data analysis to graduate students. Social Science Computer Review, 22(2), 187-196.
- Creswell, J. (1998). Qualitative Inquiry and Research Design: Choosing Among Five Traditions. California: Sage.
- Lee, R. M., & Esterhuizen, L. (2000). Computer software and qualitative analysis: Trends, issues, and responses. International Journal of Social Research Methodology, 3, 231-243.
- Patton, M. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Newbury Park, CA: Sage Publications.
- Strauss, A., & Corbin, J. (1990). Basics of qualitative research: Grounded theory procedures and techniques. Newbury Park, CA: Sage Publications.