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Record W4295874833 · doi:10.1177/07334648221125781

Considering a Need for Dementia-Specific, Family-Centered Patient Navigation in Canada

2022· article· en· W4295874833 on OpenAlexafffundabout
Kristina M. Kokorelias, Roula Markoulakis, Sander L. Hitzig

Bibliographic record

VenueJournal of Applied Gerontology · 2022
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsToronto Rehabilitation InstituteUniversity of TorontoHealth Sciences CentreSunnybrook Health Science Centre
FundersAlzheimer Society
KeywordsDementiaNursingPsychologyQualitative researchMedicineDiseaseSociology

Abstract

fetched live from OpenAlex

Patient navigation has been proposed as a novel family-centered, integrated care model to address the care needs of persons living with dementia and their family caregivers by helping them navigate the complex range of dementia services offered in hospital and community settings. A key informant qualitative descriptive study explored the perspectives of 48 healthcare professionals to explore the need for dementia-specific patient navigation. Data were analyzed thematically. We identified one overarching theme: "Variability in the Need for Illness-Specific Patient Navigation" and five themes that highlight considerations when providing navigation to individuals with dementia: (1) Taking Part in Ongoing Training, (2) Addressing Stigma, (3) Focusing on Quality of Life, (4) Defining Home, and (5) A Continuous Process of Support. These themes provide preliminary insights into the conceptual differences about the need for illness-specific patient navigation and the areas within patient navigation where healthcare professionals are encouraged to find consensus.

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.274
Threshold uncertainty score0.551

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0210.007
Scholarly communication0.0050.003
Open science0.0010.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.123
GPT teacher head0.347
Teacher spread0.223 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations6
Published2022
Admission routes3
Has abstractyes

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