Development and psychometric testing of a breast cancer patient-profiling questionnaire

Abstract

Introduction

The advent of “personalized medicine” has been driven by technological advances in genomics. Concentration at the subcellular level of a patient’s cancer cells has meant inevitably that the “person” has been overlooked. For this reason, we think there is an urgent need to develop a truly personalized approach focusing on each patient as an individual, assessing his/her unique mental dimensions and tailoring interventions to his/her individual needs and preferences. The aim of this study was to develop and test the psychometric properties of the ALGA-Breast Cancer (ALGA-BC), a new multidimensional questionnaire that assesses the breast cancer patient’s physical and mental characteristics in order to provide physicians, prior to the consultation, with a patient’s profile that is supposed to facilitate subsequent communication, interaction, and information delivery between the doctor and the patient.

Methods

The specific validation processes used were: content and face validity, construct validity using factor analysis, reliability and internal consistency using test–retest reliability, and Cronbach’s alpha correlation coefficient. The exploratory analysis included 100 primary breast cancer patients and 730 healthy subjects.

Results

The exploratory factor analysis revealed eight key factors: global self-rated health, perceived physical health, anxiety, self-efficacy, cognitive closure, memory, body image, and sexual life. Test–retest reliability and internal consistency were good. Comparing patients with a sample of healthy subjects, we also observed a general ability of the ALGA-BC questionnaire to discriminate between the two.

Conclusion

The ALGA-BC questionnaire with 29 items is a valid instrument with which to obtain a patient’s profile that is supposed to help physicians achieve meaningful personalized care which supplements biological and genetic analyses.

Keywords:

• personalized medicine
• patient–physician communication
• questionnaire validation
• patient preferences

Acknowledgments

This work was supported by the European Union ICT Program (Project “p-medicine – from data sharing and integration via VPH models to personalized medicine” FP7-ICT-2009.5.3).

Disclosure

The authors report no conflicts of interest in this work.