Qualitative Methods in Epidemiology

Qualitative methods (QM) are used to explore a wide range of experiences in epidemiology and public health. These methods examine the depths of experience to identify why or how complex events happen, and they are particularly useful for exploring new and complicated topics. Characteristics of QM studies generally include field contact and are intended to provide a holistic perspective. If an estimate of the magnitude of a problem is needed, QM will not be useful. Generalizability from the purposive sample (which samples the topic of interest) to the general population is not a goal of QM research.

The goals of QM are usually exploratory and descriptive, with the aim of understanding and describing a phenomenon and focusing on perceptions of the ‘lived experience’ from the perspective of the research respondent. For example, after determining whether or how well a prevention program works using quantitative methods, a researcher may turn to QM to examine how the program works and what aspects of the program the research participants and the staff believe are and are not working. A QM approach is particularly necessary in participatory research, where giving voice to vulnerable populations is often a particular concern.

QM approaches are derived from various philosophies that inform each of the steps in the research process: framing the research purpose, collecting data, analyzing, and interpreting. Data are generally collected using interviews, focus groups, existing documents, and observation. The most common methods of QM are grounded theory, phenomenology, ethnography, and case study, with the latter two using quantitative data in addition to qualitative data.

Grounded theory examines a process, usually a psychosocial process of change such as adapting to a new diagnosis of a health problem. A first sample of data is collected using ‘purposive sampling,’ which refers to sampling to cover the topic of interest. Next, an initial analysis is done, and it then informs the further collection of data, which is followed by analysis of the new data. This process is called ‘constant comparison.’ When new data yield no additional information, ‘data saturation’ has been reached, and data collection stops. Analysis involves coding the meaning for each segment of the document, aggregating the codes into themes and then, usually, formulating a core category. The context, conditions, covariances, and consequences are explored in formulating how the core category relates all the themes together. Symbolic interaction theory informs this approach.

Phenomenology focuses on the essential core meaning of a phenomenon, with primary importance given to the social meanings people ascribe to the phenomenon. Recognizing that interpretation is an intermediate step between recognition and behavior, the researcher uses reflective description and meditation to identify the essence. Models or theories are not the goal of this approach. This approach arose from the philosophical traditions of Edmund Husserl and Martin Heidegger.

[Page 868]Ethnography aims to describe a group or a culture, focusing on the routines and usual lives of the people as observed in behaviors and information from records. As with the other QM, ethnography emphasizes a holistic perspective, the multiple realities of the different respondents, and the embeddedness of data in the specific context. Structure and function, symbol and ritual, and microand macrolevels of data are concepts that guide this approach. Analysis often involves identification of patterns of thoughts and actions, making flowcharts of major concepts, and the use of simple nonparametric statistics and scales.

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