MétaCan
Menu
Back to cohort
Record W2587177696 · doi:10.1111/ctr.12929

Physical activity in solid organ transplant recipients: Participation, predictors, barriers, and facilitators

2017· article· en· W2587177696 on OpenAlexaffabout
Tanya Gustaw, Emma Schoo, Colleen Barbalinardo, Nicole Rodrigues, Yalda Zameni, Vinícius Nogueira Motta, Sunita Mathur, Tania Janaudis‐Ferreira

Bibliographic record

VenueClinical Transplantation · 2017
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsMcGill UniversityMcGill University Health CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineSolid organOrgan transplantationTransplantationIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Our objectives were to describe the physical activity (PA) levels, predictors, barriers, and facilitators to PA in solid organ transplant (SOT) recipients. METHODS: A web-based questionnaire was sent to members of the Canadian Transplant Association including the Physical Activity Scale for the Elderly (PASE), and questions regarding barriers and facilitators of PA. RESULTS: One hundred and thirteen SOT recipients completed the survey. The median PASE score was 164.5 (24.6-482.7). Re-transplantation was the only statistically significant predictor of levels of PA. The most common facilitators of PA included a feeling of health from activity (94%), motivation (88%), social support (76%), knowledge and confidence about exercise (74%) and physician recommendation (59%). Influential barriers were cost of fitness centers (42%), side effects post-transplant or from medications (41%), insufficient exercise guidelines (37%), and feelings of less strength post-transplant (37%). CONCLUSION: There is a large variation in PA levels among SOT recipients. Multiple factors may explain the variance in PA levels in SOT recipients. Identification of facilitators and barriers to PA can inform the development of health and educational promotion strategies to improve participation among SOT recipients with low activity levels.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.007
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.055
GPT teacher head0.415
Teacher spread0.359 · 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".

Quick stats

Citations51
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueClinical TransplantationSame topicRenal Transplantation Outcomes and TreatmentsFrench-language works237,207