Profiling alumni of a Brazilian public dental school

A web-based password-protected questionnaire was sent to 633 registered dentists who graduated from the Federal University of Goias between 1988 and 2007. Job-related information was retrieved from 14 closed questions, on subjects such as gender, occupational routine, training, profits, income status, and self-perception of professional career, generating an automatic database for analysis. The two-step cluster method was used for dividing dentists into groups on the basis of minimal within-group and maximal between-group variation, using job-related variables to represent attributes upon which the clustering was based.There were 322 respondents (50.9%), predominantly female (64.9%) and the mean age was 34 years (SD = 6.0). The automatic selection of an optimal number of clusters included 289 cases (89.8%) in 3 natural clusters. Clusters 1, 2 and 3 included 52.2%, 30.8% and 17.0% of the sample respectively. Interpretation of within-group rank of variable importance for cluster segmentation resulted in the following characterization of clusters: Cluster 1 - specialist dentists with higher profits and positive views of the profession; Cluster 2 - general dental practitioners in small cities; Cluster 3 - underpaid and less motivated dentists with negative views of the profession. Male dentists were predominant in cluster 1 and females in cluster 3. One-way Anova showed that age and time since graduation were significantly lower in Cluster 2 (P < 0.001). Alternative solutions with 4 and 5 clusters revealed specific discrimination of Cluster 1 by gender and dental education professionals.Cluster analysis was a valuable method for identifying natural grouping with relatively homogeneous cases, providing potentially meaningful information for professional orientation in dentistry in a variety of professional situations and environments.Identifying professional profiles in follow-up studies of former students is an efficient way to organize the entire process of professiona