Towards a better understanding of the dynamics of patient provider interaction: the use of sequence analysis.

Ever since, in the early eighties, Inui and Carter published their classic series of articles on doctor-patient interaction analysis [1] and [2], there is a recurrent debate on the most adequate strategies for analyzing the often complex interactions between patients and their health care providers. At that time, patient-provider communication was usually examined by presenting frequencies of coded communication behaviors and using correlation-based statistical techniques to analyze relations between those frequencies, thus ignoring the interactions between the two main players: the doctor (or nurse) and the patient. This led Inui and Carter to their provoking statement that most researchers reduced the medical encounter to a flat bundle of statistics, as if Hamlet would be described as " a play with 21 principal characters, a ghost, a group of players, and various numbers of lords, ladies, officers, soldiers, sailors, messengers, and attendants – one of whom is already dead, one of whom dies by drowning, one poisoned by drink, two by poisoned sword and one by poisoned sword and drink " [3]. A more vivid way to describe the lack of dynamics in patient-provider communication studies could hardly be given. Qualitative studies were generally seen as the most adequate way of revealing the micro dynamics of patient-provider interaction. It is only fairly recently that researchers also started to use quantitative techniques to zoom in on the interaction between doctor and patient, for example by analyzing turn-taking [4], or applying sequence analysis on the coded data [5]. Sequence analysis, which is not a single statistical technique, but a body of questions about how social processes emerge and a collection of techniques to study those [6]-has recently become quite popular among health communication studies, as was shown by Zimmermann et al in their recent review [5]. Sequence analysis studies, other than frequency association studies, allow an understanding of the temporal relationship between events, focusing on interactions in terms of what precedes and follows specified target behaviour [5]. Strictly spoken, these methods do not permit causal inferences, just like it is the case in frequency-based association studies. However, there is no doubt that analysing the order of events may give a better idea of how the interaction between doctor and patient proceeds over time under influence of the other participants' contribution. Therefore, sequence analysis is, in itself, a valuable contribution to the methodology of patient-provider communication studies. In this issue, an important paper is …