Qualitative Data Analysis Clause Samples
Qualitative Data Analysis. The qualitative data from the key informant interviews did not merit systematic analysis due to lack of depth. This was not due to poor data collection but the nature of the domains. Nine of the 16 key informant interviews were utilized for the history and description of the program. They included six senior and junior staff persons, a leader within the local Ministry of Health, and two community leaders, one who had also been a community health volunteer. Only the domains of history, CSRA today, lessons learned and best practices were analyzed for this paper.
Qualitative Data Analysis. As is typical in qualitative research, data collection and data analysis happen simultaneously (▇▇▇▇▇▇▇, 2011). Analysis of the key informant interviews used a modified grounded theory approach. Grounded theory is considered a circular process in which researchers systematically revisit data and observations to create a framework for the processes or experiences (▇▇▇▇▇▇▇, 2011). In this case, we used emergent themes from the transcripts to describe the attitudes and perspectives presented about barriers to accessing abortion and develop concepts to explore further in the surveys. We read five of the transcripts and conducted preliminary coding before developing a codebook and standard definitions for each code. We then re-read and, when necessary, re-coded each transcript to ensure standardization. We did all coding and analysis in Spanish and the quotes used to present results are translated into English (see appendix C for list of translated and Spanish quotes). We first coded the transcripts using deductive codes based on the research question and interview guide. Some examples of deductive codes are: financial barriers referring to any cost or price of services that delay or prevent women in accessing an abortion, religion, referring to descriptions of beliefs or fears about spiritual rules regarding abortion. Several distinct and unexpected themes emerged from the interviews and we developed these into inductive codes. Examples of these include: medical training, referring to descriptions of curricula or coursework in medical schools that facilitated, prevented or otherwise affected provision of quality abortion services, and conscientious objection “no debido” or “that should not be done,” referring to doctors that conscientiously objected to provision of abortion in a manner inconsistent with the legal boundaries for conscientious objection.
Qualitative Data Analysis. A Methods of Sourcebook. Singapore: Sage Publications Inc
Qualitative Data Analysis. An Introduction. 2nd edition. London: Sage. ▇▇▇▇▇▇▇▇▇, ▇▇▇▇▇▇▇▇▇▇, ed. 2018.
Qualitative Data Analysis. An Expanded Sourcebook. ▇▇▇▇▇▇▇▇ ▇▇▇▇, ▇▇▇▇▇▇, ▇▇▇ ▇▇▇▇▇: Sage Publications. ▇▇▇▇▇▇▇▇▇, ▇. (1984). The phenomenon of social representations. In ▇. ▇. ▇▇▇▇, ▇▇▇▇▇▇▇▇▇, S. (Ed.), Social Representations.
Qualitative Data Analysis. The analysis is done using MaxQda 11. Key patterns and themes emerging from the transcripts were identified by memoing the data. In addition to this, inductive codes pertaining to the research question, identified during the literature review and the data collection were applied to the data to fully answer the research question. The 4 codes used are: • Knowledge: Any reference to the participant’s knowledge/information regarding the etiology and effects of undernutrition in their children. This also included the participants knowledge of signs/symptoms associated with malnutrition. Sources of such an information, for example, Anganwadi worker, Family, Self etc. was also include in this coding category. Participant’s knowledge of IYCF practices i.e. how / when / what needs to be done in their community were also included in this coding category such as “Do you know when to start introducing complementary foods to your child?” In accordance to the variety of responses in this coding category, it was sub-coded into: • Attitudes Any reference to how the participants feel about children’s nutrition and feeding. This could include a stance, belief, or mode of behaving. Also includes a settled manner of thinking, feeling or behaving which reflects their state of mind or disposition and has the potential to predict behavior. The category stands synonymous with the participant’s perspective, outlook, inclination, approach, temper or reactions. For example, “Do you feel you get enough information from the Anganwadi worker?” The discussion was facilitated using the photographs collected from the participants. This coding category is sub-coded into Opinions, Perceived Barriers and Perceived importance of nutrition recommendations depending on the participants’ views and description of the pictures.
Qualitative Data Analysis. To begin the data analysis process, the evaluator listened to interview recordings of seven interviews that occurred either in-person or by phone and identifying important themes and information mentioned by each respondent. Each interview was designed to last no more than 30 minutes. The interviews were coded according to the textual analysis technique based in grounded theory, outlined by ▇▇▇▇▇▇▇ ▇▇▇▇▇▇▇, ▇▇▇▇ ▇▇▇▇▇▇, and ▇▇▇▇ ▇▇▇▇▇▇ in Qualitative Research Methods (▇▇▇▇▇▇▇, ▇▇▇▇▇▇, & ▇▇▇▇▇▇, 2011). The themes and information noted were organized under common or overarching themes and also organized according to which evaluation question they responded. A codebook was created and included these themes and their operational definitions. These codes included themes like “relationships” and “experience”. Other primary themes noted during interviews were from the “advice” code, the “needs and barriers”, “outcomes”, “timing”, and “future directions” (Appendix E). Upon organizing this information, results and recommendations were created for the program. Ethics Participant consent was obtained to interview and record them during the interview. After qualitative data analysis, the interview recordings were permanently deleted. Approval by the Emory Institutional Review Board (IRB) was not required because this evaluation was considered program quality improvement (Appendix F).
