MétaCan
Menu
Back to cohort
Record W3028906176 · doi:10.1017/cjn.2020.99

Perception of Healthcare Access and Utility of Telehealth Among Parkinson’s Disease Patients

2020· article· en· W3028906176 on OpenAlexaffvenue
Dakota Peacock, Peter Baumeister, Alex Monaghan, Jodi Siever, Joshua Yoneda, Daryl Wile

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2020
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsKelowna General HospitalUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsTelehealthFocus groupSpecialtyHealth careDiseasePerceptionMedicineParkinson's diseaseFamily medicineTelemedicinePsychologyGerontologyNursingBusiness

Abstract

fetched live from OpenAlex

Regional patient and physician density patterns pose problems to accessing care for people with Parkinson's disease, though telehealth may improve access. We surveyed and conducted a focus group for people with Parkinson's disease in Interior British Columbia regarding barriers to neurological care. Eighteen individuals completed the survey and seven parties joined the focus group. Perceived barriers include cost and difficulty of travel, wait times, and lack of specialized services outside large cities. 80% of participants (95% CI 64-96) would likely use telehealth for follow-up neurologist appointments. This sample of people with Parkinson's disease reports willingness to use telehealth to reduce travel and improve access to specialty care.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.071
GPT teacher head0.346
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations26
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicTelemedicine and Telehealth ImplementationFrench-language works237,207