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Record W2183731764 · doi:10.5750/ejpch.v3i4.1022

The Diverse Journeys of Rural Older Adults with Atrial Fibrillation

2015· article· en· W2183731764 on OpenAlexaff
Kathy L. Rush, Nelly D. Oelke, Matt Shay, Robert Reid

Bibliographic record

VenueEuropean Journal for Person Centered Healthcare · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsTypologyThematic analysisMedicineDisease managementHealth careAtrial fibrillationMedical emergencyQualitative researchHealth management systemAlternative medicineCardiology

Abstract

fetched live from OpenAlex

Rationale, aims and objectives: Atrial fibrillation (AF) is a serious chronic heart condition characterized by an irregular, rapid heartbeat and unpredictable course. Patients with AF often struggle with managing the impact of the disease on daily activities. Afflicted rural dwelling patients face added challenges including inequities in health services and a lack of cardiac specialty services. AF patient journeys through the healthcare system have not been well documented, but offer a valuable tool for improving patient management and outcomes. The purpose of this study was to document individual AF patient journeys of rural living older adults. Method: This study used a 6-month longitudinal design to examine the rural healthcare experiences of 10 AF patients. AF patient journeys were mapped using information gathered through interviews, written logs, photographs and an electronic health record review. Thematic analysis was used in clustering common features of the healthcare journeys of older adult patients with AF and a typology developed to describe them. Results: Each patient’s journey with AF was unique. Symptom and disease severity, health service utilization and needs emerged as differentiating features in the identification of 3 journey types: (1) Stable, (2) Chronically Unstable and (3) Acute Crisis. Conclusions: These journey types provide a valuable person-centered tool to assess patient needs at any point in the AF trajectory and to address salient risks that accompany each type to improve management of the increasing number of persons suffering from AF.

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)0.015
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.307
Threshold uncertainty score0.617

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.416
GPT teacher head0.406
Teacher spread0.009 · 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 designNot applicable
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

Citations2
Published2015
Admission routes1
Has abstractyes

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