Health research: need for a methodological revolution?

The polarization of research ideologies into two camps, qualitative versus quantitative, has been commented on by a number of authors. One of the more recent contributions to this debate comes from the journal Addiction in which McKeganey (1995) discusses the divide between the two underlying philosophies and concludes that this divide no longer serves a useful function. He then discusses a number of procedures for the analysis of qualitative data, before suggesting that qualitative research might benefit from a more systematic and rigorous approach in the interests of increasing the explanatory power of that method. The suggestion that the qualitative and quantitative camps might usefully come closer together has now become an established wisdom, and many researchers as a matter of routine suggest both quantitative and qualitative components in their grant applications. I certainly do this myself, as grant funding agencies seem to like this combination and in the present academic climate it pays to give people what they want However, as indicated in a number of following letters to McKeganey's article, there may be a problem here. Basically, the philosophies underlying the two approaches are not, and in my view never can be, complementary. Whilst at a practical level we can ride rough shod over this issue in our research, by including some user-friendly group discussions along with our latest forced-choice questionnaire bashing exercise, the basic philosophical incompatibility of the two approaches remains unresolved. Since historically both schools of thought have at various times claimed superiority for their own method of pursuing 'truth' (see, e.g. The Psychologist, 5(10), 1992), differences in the data or information yielded create (insoluble?) problems as to which is 'truer'; these usually being resolved by latter-day workers in terms of some more or less unsatisfactory linguistic sleight of hand. This typically takes the form of a story in which differences between data sets are explained on the basis that qualitative data shed light on how the individual person sees the issue, and thus do more justice to that person's individual constructions ; whilst, on the other hand, questionnaire data comprise 'scientific measurements' that are comparable across individuals, and tnus provide the basis for statistical comparisons in terms of standardized measures derived from procedures of proven reliability and validity. If different pictures emerge, therefore, it does not matter since such differences can be explained away by the assertion that the two methods shed light on different …