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Record W1986145602 · doi:10.3810/psm.2011.05.1894

Self-Reported Physical Activity Preferences in Individuals with Prediabetes

2011· article· en· W1986145602 on OpenAlexafffundabout
Lorian Taylor, John C. Spence, Kim D. Raine, Arya M. Sharma, Ronald C. Plotnikoff

Bibliographic record

VenueThe Physician and Sportsmedicine · 2011
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchUniversity of AlbertaUniversity of CambridgeHeart and Stroke Foundation of Canada
KeywordsPrediabetesMedicineBody mass indexMarital statusDemographyPhysical activityGerontologyPhysical therapyPreferenceDiabetes mellitusType 2 diabetesEnvironmental healthInternal medicinePopulationEndocrinology

Abstract

fetched live from OpenAlex

PURPOSE: The primary objective of this study was to determine the physical activity (PA) preferences in a sample of individuals with prediabetes. METHODS: Individuals with prediabetes (N = 232) residing in Northern Alberta, Canada completed a mailed questionnaire that assessed demographic and health variables, self-reported PA (Godin Leisure-Time Exercise Questionnaire), and PA preferences. RESULTS: Respondents indicated they would like to be counseled about PA (75%), were physically able to participate (96%), were interested in a PA program for individuals with prediabetes (86%), and were most interested in walking (71%). Activity status, number of comorbidities, level of employment, marital status, body mass index, and time since diagnosis with prediabetes all demonstrated significant influence on different PA preference variables. CONCLUSIONS: There is a demand for PA-related programs for individuals with prediabetes. Incorporating identified PA preferences of those with prediabetes might aid in the development of relevant intervention tools, programs, and strategies to support PA.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.038
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.289
Teacher spread0.240 · 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 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

Citations5
Published2011
Admission routes3
Has abstractyes

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