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Record W4403584965 · doi:10.3390/healthcare12202049

Identifying Elements for a Cardiac Rehabilitation Program for Caregivers: An International Delphi Consensus

2024· article· en· W4403584965 on OpenAlexfundno aff
Maria Loureiro, João Duarte, Eugénia Mendes, Isabel Oliveira, Gonçalo F. Coutinho, María Manuela Martins, André Novo

Bibliographic record

VenueHealthcare · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsnot available
FundersReseau canadien de recherche respiratoire
KeywordsDelphi methodPsychological interventionRehabilitationContext (archaeology)Focus groupHealth careMedicineDelphiNursingPsychologyMedical educationFamily medicinePhysical therapyComputer science

Abstract

fetched live from OpenAlex

Background/Objectives: Caregivers of patients with heart disease may often feel physically, emotionally, and psychologically overwhelmed by their role. The analysis of cardiac rehabilitation (CR) components and caregivers’ needs suggests that some interventions may benefit them. Therefore, this study aimed to identify a consensus on the CR components targeting caregivers of patients with heart disease. Methods: A three-round international e-Delphi study with experts on CR was conducted. In round 1, experts provided an electronic level of agreement on a set of initial recommendations originating from a previous scoping review. In round 2, experts were asked to re-rate the same items after feedback and summary data were provided from round 1. In round 3, the same experts were asked to re-rate items that did not reach a consensus from round 2. Results: A total of 57 experts were contacted via e-mail to participate in the Delphi panel, and 43 participated. The final version presents seven recommendations for caregivers of patients with heart disease in CR programs. Conclusions: These recommendations are an overview of the evidence and represent a tool for professionals to adapt to their context in the different stages of CR, integrating the caregiver as a care focus and as support for their sick family members. By identifying the components/interventions, there is potential to benchmark the development of a cardiac rehabilitation strategy to be used and tested by the healthcare team for optimizing the health and role of these caregivers.

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)0.002
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 score0.850
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.218
GPT teacher head0.572
Teacher spread0.355 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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