Summary

Background and objective: The anaesthesiologist's preoperative interview with the patient is important in preparing the patient for surgery. Its potential protective influence on adverse side-effects from anaesthesia and convalescence is rarely investigated within the context of other perioperative factors. Structural equation modelling allows detection and quantification of all causal relationships and mediator effects in multivariate models. Therefore, this method is presented as a tool and applied to discover the influence of the preoperative interview within socio-demographic variables and duration of surgery on complaints and recovery after anaesthesia.

Methods: The influence of individual satisfaction with the anaesthesiologist's preoperative interview on postoperative events such as nausea/vomiting, difficulties in recovering from anaesthesia, experience of postoperative pain, physical discomfort and satisfaction with convalescence expressed by the patient was analysed by means of structural equation modelling. The variables gender, age and duration of surgery were also included as predictors in the analyses. The model in the total sample of 710 patients was then analysed for structural differences between groups treated either with propofol (n = 204) or with isoflurane + nitrous oxide (n = 267) for maintenance of anaesthesia.

Results: The model revealed that the anaesthesiologist's preoperative interview in combination with associated mediating side-effects explains 45% of the variance of ‘feeling physical discomfort’ and 18% of the variance of ‘satisfaction with convalescence’. The same model could be fitted in the propofol and the isoflurane + nitrous oxide group. Moreover, the structure and the strength of causal relations between variables were identical in the two groups.

Conclusions: The anaesthesiologist's efforts to improve the interview with the patient by more reassuring and proper information will result in less side-effects from anaesthesia and better recovery from surgery. It could be demonstrated that structural equation modelling is a powerful tool for detection of causal relationships and mediator effects in perioperative medicine.