MétaCan
Menu
Back to cohort
Record W4283118456 · doi:10.3390/jpm12061001

Co-Designing an Integrated Care Network with People Living with Parkinson’s Disease: A Heterogeneous Social Network of People, Resources and Technologies

2022· article· en· W4283118456 on OpenAlexaffabout
Amélie Gauthier-Beaupré, Emely Poitras, Sylvie Grosjean, Tiago Mestre

Bibliographic record

VenueJournal of Personalized Medicine · 2022
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersAgence Nationale de la Recherche
KeywordsParkinson's diseaseDiseaseGerontologyMedicineSocial careSocial network (sociolinguistics)Physical medicine and rehabilitationComputer scienceWorld Wide WebNursingPathologySocial media

Abstract

fetched live from OpenAlex

As part of the iCARE-PD project, a multinational and multidisciplinary research endeavour to address complex care in Parkinson's disease, a Canadian case study focused on gaining a better understanding of people living with Parkinson's disease (PwP) experiences with health and medical services, particularly their vision for a sustainable, tailored and integrated care delivery network. The multifaceted nature of the condition means that PwP must continuously adapt and adjust to every aspect of their lives, and progressively rely on support from care partners (CP) and various health care professionals (HCP). To envision the integrated care delivery network from the perspective of PwP, the study consisted of designing scenarios for an integrated care delivery network with patients, their CP and their HCP, as well as identifying key requirements for designing an integrated care delivery network. The results demonstrate that numerous networks interact, representing specific inscriptions, actors and mediators who meet at specific crossing points. This resulted in the creation of a roadmap and toolkit that takes into consideration the unique challenges faced by PwP, and the necessity for an integrated care delivery network that can be personalized and malleable so as to adapt to evolving and changing needs over time.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.422
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.281
Teacher spread0.263 · 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 teacher head, 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

Citations7
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Personalized MedicineSame topicAutism Spectrum Disorder ResearchFrench-language works237,207