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Development of the Digital Inclusion Questionnaire (DIQUEST) in Parkinson's Disease.
Canoro, Vincenzo; Picillo, Marina; Cuoco, Sofia; Pellecchia, Maria Teresa; Barone, Paolo; Erro, Roberto.
Afiliación
  • Canoro V; Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", Neuroscience Section, 84081, Baronissi, SA, Italy.
  • Picillo M; Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", Neuroscience Section, 84081, Baronissi, SA, Italy.
  • Cuoco S; Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", Neuroscience Section, 84081, Baronissi, SA, Italy.
  • Pellecchia MT; Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", Neuroscience Section, 84081, Baronissi, SA, Italy.
  • Barone P; Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", Neuroscience Section, 84081, Baronissi, SA, Italy.
  • Erro R; Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", Neuroscience Section, 84081, Baronissi, SA, Italy. rerro@unisa.it.
Neurol Sci ; 45(3): 1063-1069, 2024 Mar.
Article en En | MEDLINE | ID: mdl-37843691
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.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedad de Parkinson Límite: Humans Idioma: En Revista: Neurol Sci Asunto de la revista: NEUROLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Italia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Enfermedad de Parkinson Límite: Humans Idioma: En Revista: Neurol Sci Asunto de la revista: NEUROLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Italia