Options for BlendingQualitative and Quantitative

Research Methods

Ian McDowell(Based on a seminar presentation in 1997)

Overview• Epidemiologic research methods are gradually

evolving in recognition of inadequacies in current methods

• Two paradigms: positivist & quantitative vs. subjectivist or postmodern

• There are strengths in each …• So how can we blend the two, in:

– study design– data collection– analysis– communicating results?

Styles of Thought(how do we know that we know what we think we know?)

Perennial dualisms throughout history of thought:• Yin and Yang• Greek Apollonian vs. Dionysiac• Male and female• Right brain and left• Deductive vs. inductive• Quantitative vs. qualitative• Reductionist vs. systems thinking

Changing philosophies of knowledge

• 17th & 18th centuries: order, logic and science, world seen

through senses. Mechanical world. Realism and logical

positivism. Laplace & description of determinism, 1804.

• 19th century - social revolution: can we analyze behaviour

logically? Idealism: the human mind as source of knowledge;

people, as well as logic, crucial in explaining reality.

Nonetheless, still used mechanical metaphors

• 20th century - phenomenology; qualitative research

Two paradigms• Biological variability poses a major challenge:

should we focus on the general or the specific? We can often predict the general (“How many?”) but not the individual (“Which?”)

• ‘Nomothetic’ science seeks general truths, using deductive methods. Public health; epidemiology.

• Yet the ultimate purpose of science is to explain specific instances: ‘idiographic’ studies. Clinical medicine; psychology; inductive methods.

Quantitative approach• Describes and imposes external structure on data

(e.g., fixed questions in questionnaire) • Gives parsimonious summary of results: reductionist (for

example, statistical analysis assigns shared variance to one variable, so reducing complexity)

• Seeks to isolate systems from their environment and to generalize findings

• Efficient, but incomplete view of interconnectedness of reality

• Asks the “How?” question• Externally valid: generalizing rather than particularizing

Qualitative approach• Interprets, explains; generates concepts• Responds to Bacon’s challenge of induction: to begin

from careful observation• Seeks to be open, flexible• Asks the “Why?” question• Particularizes; internally valid • The investigator is the instrument; art versus science• Sampling becomes a crucial issue (in data collection

and in analysis)• “Somewhat magical approach to analysis”

Blending Qualitative and Quantitative

• Metaphor of binocular vision• A combination seeks to array strengths of one

against limitations of the other• Nature of the balance may depend on stage of the

study: for example qualitative may predominate in a process evaluation, quantitative in an outcome evaluation study.

Five blends of qualitative & quantitative

Hierarchical model: one method takes the leadi. Qualitative leads, orii. Quantitative leads

Partnership model: equal but contrasting contributions

iii. Sequentialiv. Cyclicalv. Simultaneous application (triangulation)

Applying these types of blend

In different stages of research:1. Conceptualizing the study

2. Collecting data

3. Analyzing data

4. Interpreting the data

Stage 1: Conceptualizing the Study

• Hierarchical model, quantitative leading, in “hard” science (a rise in cancer cases)

• Hierarchical model, qualitative leading, in “soft” topics (public concern over rise in cancers)

• Partnership model applicable in mixed studies or in broad programme of research that involves sequence of individual studies

• Sequential partnership in formulating study: qualitative leads into quantitative (public concern leads to an evaluation of an intervention to address this)

Stage 2: Collecting the Data• Goal of blending approaches is to compensate for

limitations in each approach• Hierarchical model illustrated by data

supplementation (e.g., qualitative interviews with a few respondents offer interpretation of responses to a standardized questionnaire)

• Partnership sequential model illustrated in qualitative work to develop questionnaires

Stage 3: Data Analysis• Generally hierarchical; determined by design of study.

Orientation of funding agencies often makes it hard to achieve a true balance (“disciplinary racism”)

• Hierarchical, with quantitative leading, illustrated by analyses of outliers

• Hierarchical, qualitative leading: case studies are followed by secondary analysis of quantitative data (e.g. surveys) to estimate representativeness of insights gained from the case study

• Iterative analyses in partnership model, liable to be criticized from both camps.

4: Interpreting & Disseminating Results

• Hierarchical, quantitative leading: – Use case histories or quotations to illustrate

quantitative results– Use qualitative results to comment on

exceptions to the rule• Hierarchical, qualitative leading: use

quantitative results to validate what people suspected all along

Future Directions• Funding agencies now recognize importance of

qualitative research. It’s a start, but….– The paradigms are sufficiently different that it’s very hard to

blend them: attempts rapidly lead to criticism that you are perverting the tenets of each approach

– Disciplinary purity seems remarkably important to academics – a fundamental part of personal identity – so conflicts will be common

• A successful blend will be truly “transdisciplinary”– Now we need to figure out what that means!