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A Qualitative Study of Determinants Influencing Participation in a Cardiac Prevention Exercise-Based Program

2011· article· en· W2321635171 on OpenAlexaff
Mélissa Lesage-Moussavou-Nzamba, Julie Houle, François Trudeau

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2011
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Wellbeing Research
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsFeelingQualitative researchPerceptionCompliance (psychology)PsychologyMedicineMedical educationSocial psychology

Abstract

fetched live from OpenAlex

PURPOSE: The purpose of this study is to understand the determinants influencing the participation rate and the compliance in a primary and secondary cardiac prevention exercise-based program using a qualitative methodology. METHODS: With a descriptive qualitative approach, 10 participants were interviewed about their experiences at their entry to the program and following the end of the program. A qualitative analysis was performed by the identification of different themes and sub themes emerging from their experience and compared the first and second discussions. Those data helped understand determinants related to difficulties encountered by several participants in primary and secondary cardiac prevention and exercise programs. RESULTS: The determinants or factors emerging from the analysis of the interviews were: (1) knowledge and awareness of disease/risk factor, (2) perception of self-efficacy, (3) motivation, and (4) feeling of belonging to the program. Results showed that the four participants who were the most compliant to the program had a better awareness of the cardiac risk factors and their conditions, were more willing to make changes in their lifestyles to reach their objectives, had a better perception of self-efficacy, and had a better feeling of belonging to the program. Both compliant and non compliant participants had many episodes of discouragement during the program, and faced many barriers that came to interfere with their progress. CONCLUSIONS: This study highlights the need to consider the many factors and barriers that could be present in individuals undergoing a primary and secondary cardiac prevention programs to increase compliance and avoid early drop-outs.

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)0.016
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.136
GPT teacher head0.536
Teacher spread0.400 · 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".

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Citations0
Published2011
Admission routes1
Has abstractyes

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