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Patient-Provider Communication Regarding Referral to Cardiac Rehabilitation

2005· article· en· W1989001785 on OpenAlexafffund
Peter R. Mitoff, Marta Wesolowski, Beth L. Abramson, Sherry L. Grace

Bibliographic record

VenueRehabilitation Nursing · 2005
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsUniversity Health NetworkUniversity of Toronto
FundersCanadian Institutes of Health ResearchHealth CanadaUniversity Health Network
KeywordsReferralSeriousnessAttendanceRehabilitationFamily medicineGrounded theoryMedicinePerceptionQualitative researchNursingPsychologyPhysical therapy

Abstract

fetched live from OpenAlex

This study investigated the dynamics of patient-provider communication in the cardiac rehabilitation (CR) referral process, to identify which aspects lead to CR participation. Semi-structured individual interviews were conducted with 31 patients eligible for CR. Questions probed the content and perception of the discussion that patients had with healthcare providers (HCP) regarding CR attendance. The interviews were audiotaped, transcribed, and imported into N6 software for grounded analyses. Key emerging themes were identified: illness perceptions; HCP encouragement; timing of discussion; and ease of referral. CR attenders were apt to self-advocate to ensure their enrollment in CR, whereas nonattenders were more likely to minimize the seriousness of their disease, and less likely to persevere to overcome obstacles in enrolling in a CR program. Surprisingly, the strength of the HCP referral did not influence the decision to attend CR as strongly when compared to the HCP's ability to facilitate enrollment in a CR program.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.311
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.052
GPT teacher head0.432
Teacher spread0.380 · 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.

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

Citations23
Published2005
Admission routes2
Has abstractyes

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