Evidence map›Paper›PMID 37843691›Full record

ArticleNeurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology2024

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

Vincenzo Canoro, Marina Picillo, Sofia Cuoco, Maria Teresa Pellecchia, Paolo Barone, Roberto Erro

Abstract read
In one paragraph

Article in Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Digital Inclusion in Parkinson's Disease: A Case-Control Study.Movement disorders clinical practice · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Vincenzo CanoroDepartment of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", Neuroscience Section, 84081, Baronissi, SA, Italy.ORCID https://orcid.org/0000-0003-3159-0157
Marina PicilloDepartment of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", Neuroscience Section, 84081, Baronissi, SA, Italy.
Sofia CuocoDepartment of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", Neuroscience Section, 84081, Baronissi, SA, Italy.ORCID https://orcid.org/0000-0002-5755-4544
Maria Teresa PellecchiaDepartment of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", Neuroscience Section, 84081, Baronissi, SA, Italy.ORCID https://orcid.org/0000-0002-6217-313X
Paolo BaroneDepartment of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", Neuroscience Section, 84081, Baronissi, SA, Italy.ORCID https://orcid.org/0000-0001-8965-2504
Roberto ErroDepartment of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", Neuroscience Section, 84081, Baronissi, SA, Italy. rerro@unisa.it.ORCID http://orcid.org/0000-0002-7800-7419

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNo 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.

methodsThirty 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.

resultsThe 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.

conclusionsWe 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.

Indexed as

Parkinson DiseaseComputers, HandheldHumansPilot ProjectsPsychometricsReproducibility of ResultsSurveys and QuestionnairesDigital technologiesICTRemote visitsTelehealthTelemedicine

Identifiers

PMID37843691
PMCPMC10857963

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.