Mapi Publications

Item Reduction, Scoring, and First Validation of the ACCEPTance by the Patients of their Treatment (ACCEPT©) Questionnaire

Arnould B, Gilet H, Patrick DL, Acquadro C.

Objectives

The objectives of this study were to finalize, develop the scoring, and explore the psychometric properties of the ACCEPTance by the Patients of their Treatment (ACCEPT©) questionnaire, as well as to provide the first elements for its interpretation and guidance for its future use.

Methods

ACCEPT© was finalized according to reference methods including testing in a pilot study, i.e., a multi-center, observational, longitudinal study conducted in France, in collaboration with a network of pharmacists. Principal component analysis using Varimax rotation was performed. The loadings of items on components in the principal component analysis were used to inform item selection. Validity of the measurement model of ACCEPT© was confirmed using Multi-trait/Multi-item Analysis based on item-scale Spearman correlations. Internal consistency reliability of the questionnaire was assessed by determining the Cronbach's α coefficient. Linear and logistic regressions were used to identify predictors of general acceptance, and to study predictors of persistence.

Results

A total of 189 patients were included. The final version of ACCEPT© is composed of 25 items, distributed in seven dimensions providing a comprehensive appraisal of acceptance of long-term medication, with six scores measuring acceptance of treatment specific attributes and one score measuring general treatment acceptance. The measurement properties of ACCEPT© were overall fairly satisfactory. Regressions showed that Acceptance/Effectiveness is a predictor of general acceptance. However, no predictor of persistence could be identified.

Conclusion

The self-administered ACCEPT© questionnaire is a valid and reliable instrument for the assessment of patients' acceptance of long-term medication. Disease-specific and large prospective studies are needed to assess the ability of ACCEPT© to predict persistence with treatment.

Read full article