Evaluating patient satisfaction through latent class factor analysis.
This paper introduces Health and Place readers interested in studying the latent concept of satisfaction to the methodology of latent variable analysis. In particular, some suitable methods for analyzing individual opinions expressed on ordinal scales are illustrated. The basic theory behind these methods is explained and a step by step description of how they should be used in practice is given. The discussion of the subject starts with the simplest methods, in which opinions are grouped into two categories: typically positive and negative. Furthermore, more complex methods are presented to deal with opinions expressed on ordinal scales (e.g., very satisfied, somewhat satisfied, and not satisfied). All methods are described by showing various results obtained through the analysis of a dataset containing patients' opinions about their satisfaction with hospital care, collected through a survey conducted after their discharge from an Italian hospital. The database was created using a questionnaire covering different aspects of satisfaction and a five-point Likert scale. This represents an example of multi-level data: patients are clustered according to the hospital ward in which they were hospitalized. Thus, some specific latent variable methods able to deal with this particular structure of the data are also described.
Department of Statistics, University of Bologna, via delle Belle Arti, 41-40126 Bologna, Italy. giulia.cavrini@unibo.it
Giulia
G
Cavrini
Giuliano
G
Galimberti
Gabriele
G
Soffritti
D000328:Adult; D005163:Factor Analysis, Statistical; D005260:Female; D006760:Hospitalization; D006801:Humans; D007558:Italy; D008297:Male; D008875:Middle Aged; D005791:Patient Care; D017060:Patient Satisfaction / Q000706:statistics & numerical data*; D011795:Surveys and Questionnaires