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Record W7133008652

Success stories of South Asian patients attending cardiac rehabilitation: A qualitative study

2007· dissertation· W7133008652 on OpenAlexaff
Ananya Tina Banerjee

Bibliographic record

VenueTSpace · 2007
Typedissertation
Language
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsCanadian HeritageLibrary and Archives Canada
Fundersnot available
KeywordsSouth asiaQualitative researchDiseaseRehabilitationFace (sociological concept)Asian IndianCulturally appropriateQualitative property
DOInot available

Abstract

fetched live from OpenAlex

South Asians who have established cardiovascular disease could benefit from attending cardiac rehabilitation (CR) but have been identified among those least likely to attend to CR (Banerjee, Gupta, Singh, 2007). The purpose of this study was to examine the cultural relevant factors influencing South Asians' participation in CR programs. This qualitative study was based on the Precede-Proceed Framework. Data was collected through face to face semi-structured interviews with 16 South Asian participants enrolled in a CR program. Transcribed data was analyzed for common themes. Facilitators or the positive experiences of the participants mainly emerged. Various influential factors that were considered important among South Asians to readily attend CR included being informed of CR as a "medically supervised program", family and physician support and having prior knowledge of CR from other South Asian community members. This paper essentially illustrates the possibilities of CR programs for culturally diverse cardiac patients.

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)0.009
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0100.008
Scholarly communication0.0040.005
Open science0.0020.006
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.032
GPT teacher head0.480
Teacher spread0.449 · 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 designQualitative
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

Citations0
Published2007
Admission routes1
Has abstractyes

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