Data “Mixing”

An important step in mixed methods research is to prepare a clear approach to analyzing the different types of data together. This process is known as “mixing” the data and is the “explicit relating of the two data sets” (Creswell and Clark, 2007, pg. 83). There are several procedures for mixing qualitative and quantitative data; two data types can be merged, one can be embedded within the other, or they can be connected. For purposes of this study, we merged the data during the interpretation/analysis stage. This

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mixing design is known as “triangulation.” Analysis of the data was performed concurrently and then merged during the final stages of analysis. Both data sets were given equal emphasis with the intent of drawing valid conclusions about the research problem (implementation of P4HB®) (Creswell and Clark, 2007). Triangulation is a well- known research strategy of combining “methodologies in the study of the same

phenomenon” (Denzin, 1978, pg. 291). Using this approach in mixed methods research provides the opportunity for cross validation “when two or more distinct methods are found to be congruent and yield comparable data” (Jick, 1979, pg. 1). We present the findings from this triangulation in Chapter 7 and then discussion the implications for theory and policy development in the final chapter (Chapter 8) of the dissertation.

3.13 Rigor

Ensuring rigor is equally important in qualitative research as it is in quantitative research. However, the approach to obtaining the validity of data and results differs for each type. In quantitative research, validity is obtained when a researcher can draw meaning inferences from the results to a specific population and consistently over time (Creswell and Clark, 2007). In qualitative research, rigor is derived from the researcher’s participation and involvement in the data collection process. The researcher’s presence is important as is the researcher’s interaction with the study participants (Merriam, 1995).

As noted above, one important approach we took to ensure the validity and reliability of our mixed methods was the process of triangulation. We employed not only methodological triangulation, which assess data from multiple data collection methods (interviews, focus groups, document reviews, provider surveys), but also data source triangulation in which several data sources (e.g., data from more than one person and

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more than one point in time) was used to strengthen the finding (Lincoln and Guba, 1985; Patton, 2002).

Additional steps were taken to ensure the validity and reliability of the qualitative results. First, to strengthen internal validity, we used narrative member checks, or verbal summarizations, with all informants to verify authenticity with the information of the interpretation and analysis of the data (Richards, 2009). These member checks were conducted during and after each of the focus groups and informant interviews. Participants were also given the opportunity to request copies of the focus group or interview summaries. Second, summary reports were maintained after each interview and focus group and compared to the transcripts to assure accuracy of the data as well as conceptualization of emerging themes.

To address external validity, again a concept most commonly assigned to quantitative data, we focused on the “transferability” of the finding, or the ability of the findings to be “transferred” by the reader/user to his or own situation (Lincoln and Guba, 1985). In the case of Planning for Healthy Babies®, we were interested in whether our findings could be found transferable to other states with similar experiences, albeit, Medicaid family planning programs. Given this concern, two techniques were used to strengthen the transferability, or external validity, of the qualitative results. First, we findings from this research provide rich description of the study participants, data, and results that enable readers to determine how well these findings “transfer” to their own situation. (Krefting, 1991). Second, the use of multiple methods and triangulation strategies also provides for a systematic approach to the research that can be applied to similar settings (Slevin, 2000)

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Finally, to address the reliability of the data, I produced an audit trail of my data collection methods and sources. Audit trails, first introduced by Lincoln and Guba (1985), are used to establish the “confirmability” of qualitative findings. Audit trails reflect the conceptual mapping of the logic of the researcher (Carcary, 2009; Cutcliffe and McKenna, 2004). Several sources of information were collected to inform the audit process, including 1) listing of all data collection methods (interviews, document review, focus groups, surveys); 2) summary notes of emerging themes; and 3) process notes, that included decisions made through the data collection and analysis stages.

3.14 Ethics

As noted earlier, the study was approved by institutional review boards at Georgia State University (GSU), Georgia Tech University (GTU), Emory University, as well as DPH. These reviews were deemed necessary due to the academic institutions that are affiliated with the researcher’s dissertation work (GSU, GTU), and employment location (Emory University) where a majority of the interview and survey data were collected by telephone or fax. Since the researcher spoke with women who receive health care services at public health clinics and interviews public health providers, approval from DPH was also required.

Other ethical considerations were undertaken during the course of this study. Consent was obtained by all study participants before data were collected. Participants were also provided the opportunity to ask questions about the study, about their

participation in the study, and to decline participation even after the data were collected. In addition, participants were offered the opportunity to be given copies of the completed,

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de-identified transcripts, field note summaries, and future study publications. To assure anonymity, all interview and focus group participants were given pseudonyms to help protect their names and associations. Also because some informants, particularly state officials could potentially be identified through association, the researcher made special effort to generalize the identity of these informants and limit acknowledgement to the Medicaid or public health agency level.