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Punjabi <scp>S</scp>ikh Patients’ Perceived Barriers to Engaging in Physical Exercise Following Myocardial Infarction

2012· article· en· W2060061261 on OpenAlexaffabout
Paul Galdas, John L. Oliffe, H. Bindy K. Kang, Mary T. Kelly

Bibliographic record

VenuePublic Health Nursing · 2012
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsThematic analysisMedicineHealth promotionRehabilitationQualitative researchPromotion (chess)Public healthFamily medicinePhysical therapyNursingPolitics

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this research was to describe Punjabi Sikh patients' perceived barriers to engaging in physical exercise following myocardial infarction (MI). DESIGN AND SAMPLE: A qualitative, interpretive descriptive methodology was used. The sample included 15 Punjabi Sikh patients who were attending a cardiac rehabilitation education program in an urban center of British Columbia, Canada, following MI. MEASUREMENTS: Data were collected via semi-structured interviews and were audio recorded, translated from Punjabi to English, and transcribed verbatim. Data were analyzed using an interpretive thematic approach that involved a process of coding and constant comparison. RESULTS: Four key factors emerged that related to participants' perceived barriers to sustained engagement in physical activity: (1) difficulty in determining safe exertion levels independently; (2) fatigue and weakness; (3) preference for 'informal' exercise; and (4) migration-related challenges. CONCLUSIONS: The findings have implications for the design and delivery of health promotion strategies aimed at Punjabi Sikh patients' post-MI that is contingent on the use of 'formal' exercise settings to promote regular physical activity. The willingness among Punjabi Sikh patients to practise brisk walking offers a positive direction that public health nurses and other healthcare professionals may want to capitalize on in the delivery of exercise-related health promotion.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.372
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.340
Teacher spread0.313 · 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

Citations33
Published2012
Admission routes2
Has abstractyes

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