Purpose -The purpose of this paper is to use a theoretical model to create a scale to predict medical tourism (MT) intentions.Design/methodology/approach -The theory of planned behavior (TPB) model was applied to MT by creating a 49-item questionnaire and collecting data from a convenience sample of 453 undergraduate students enrolled in a university located in the USA. Factor analysis was used to evaluate the results, and yielded a MEDTOUR scale containing 29 items.Findings -A regression of the three variables on an intentions scale of participation in MT had an R-value of 0.587. The model was able to explain around 35 percent of the variance in intentions. Given the general nature of the model and the first attempt at predicting MT, the results are positive.Research limitations/implications -This research is limited due to the use of a convenience sample of undergraduate students. Further research utilizing additional samples is needed to verify the MEDTOUR scale. In addition, future research can focus on demographic or other areas of interest in relation to the intention to participate in MT.Originality/value -The creation of the MEDTOUR scale represents a new application of the TPB to the area of MT. This theory-based scale is offered as a new tool for future research.
This study introduces the theory of planned behavior to health care marketers by extending and replicating a prior study that predicted student's intention to engage in medical tourism. Based on a sample of 164 usable survey responses, our findings suggested that the MEDTOUR scale (developed and introduced a prior study) is robust and works reasonably well with a national sample. Based on these findings, MEDTOUR appears to be worthy of further consideration by health marketing scholars.
EDUCATIONAL AND PSYCHOLOGICAL MEASUREMENT 1974, 34, 537-545. The effect of the number of scale intervals of a continuous variable on the results of principal components factor analysis was investigated. Analyses were performed for seven different numbers of scale intervals. The general effect was a decrease in the size of the eigenvalues, communalities, and factor loadings as the number of scale divisions was reduced. The magnitude of the effect was, however, not large and the pattern of the rotated factor loadings was not appreciably affected.IN recent years, there has been widespread interest in, and application of, factor analysis in a number of fields. One consideration that confronts the researcher is that the model underlying factor analysis seldom matches precisely the characteristics of the data being analyzed. One problem that has concerned investigators is the effect of the number of intervals along the measurement scale of a, continuous variable on the results of the analysis. In its extreme form it is desired to know what effect reducing a continuous measurement scale to a dichotomy has on the analysis where the Pearson product moment correlation is used to represent the relationships between dichotomous variables (Carroll, 1961;Henrysson and Thunberg, 1965).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.