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Record W4212829088 · doi:10.7202/1086401ar

What are the Needs of People Living in Remote Areas About the Essential Components of a Cardiac Rehabilitation Program?

2022· article· en· W4212829088 on OpenAlexafffundvenue
Jessica Bernier, Mélissa Lavoie, Marie-Ève Poitras

Bibliographic record

VenueScience of Nursing and Health Practices · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsUniversité du Québec à ChicoutimiUniversité de Sherbrooke
FundersRéseau de recherche portant sur les interventions en sciences infirmières du QuébecUniversité du Québec à Chicoutimi
KeywordsRehabilitationMedicineHealth careMyocardial infarctionIntervention (counseling)Focus groupPhysical therapyMedical emergencyNeeds assessmentNursingCardiology

Abstract

fetched live from OpenAlex

Introduction: Cardiac rehabilitation (CR) is an effective intervention to support patients in achieving their health objectives and in decreasing their risk of suffering from another myocardial infarction (MI). However, in several remote areas, no cardiac rehabilitation program (CRP) exists to support patients having experienced an MI. Before the creation of an intervention CRP adapted to patients living in these areas, it is essential to describe patients and healthcare professionals' needs regarding cardiac rehabilitation care. Objective: This study describes the needs of remote patients and healthcare professionals for the essential components in a CR program following myocardial infarction and percutaneous transluminal coronary angioplasty. Methods: A qualitative formative research study was conducted involving 10 men, 6 women, and 4 family physicians. Data were collected through in-depth individual interviews and one focus group. Results: Results show that patients who have suffered an MI have multiple unmet needs. This gap may be due to the variability in follow-ups by healthcare professionals. In the absence of a cardiac rehabilitation program, these patients must adapt quickly to their new health condition. Discussion and conclusion: It is critical that the needs of patients living in remote areas are better addressed in cardiac rehabilitation. To do this, it is essential to create a CRP that is tailored to the needs of both patients and professionals, thus providing patient-centered 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 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)0.008
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.806

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.059
GPT teacher head0.448
Teacher spread0.389 · 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

Citations4
Published2022
Admission routes3
Has abstractyes

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