Development of the Digital Inclusion Questionnaire (DIQUEST) in Parkinson’s Disease

Abstract

Abstract Background No tool is currently able to measure digital inclusion in clinical populations suitable for telemedicine. We developed the “Digital Inclusion Questionnaire” (DIQUEST) to estimate access and skills in Parkinson’s Disease (PD) patients and verified its properties with a pilot study. Methods Thirty PD patients completed the initial version of the DIQUEST along with the Mobile Device Proficiency Questionnaire (MDPQ) and a practical computer task. A Principal Components Analysis (PCA) was conducted to define the DIQUEST factor structure and remove less informative items. We used Cronbach’s α to measure internal reliability and Spearman’s correlation test to determine the convergent and predictive validity with the MDPQ and the practical task, respectively. Results The final version of the DIQUEST consisted of 20 items clustering in five components: “advanced skills,” “navigation skills,” “basic skills/knowledge,” “physical access,” and “economical access.” All components showed high reliability (α > 0.75) as did the entire questionnaire (α = 0.94). Correlation analysis demonstrated high convergent (rho: 0.911; p<0.001) and predictive (rho: 0.807; p<0.001) validity. Conclusions We have here presented the development of the DIQUEST as a screening tool to assess the level of digital inclusion, particularly addressing the access and skills domains. Future studies are needed for its validation beyond PD.