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Record W2098472978 · doi:10.1123/apaq.29.4.329

Enhancing Physical Activity Guidelines: A Needs Survey of Adults With Spinal Cord Injury and Health Care Professionals

2012· article· en· W2098472978 on OpenAlexaff
Brianne L. Foulon, Valerie LeMay, Victoria Ainsworth, Kathleen A. Martin Ginis

Bibliographic record

VenueAdapted Physical Activity Quarterly · 2012
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversité LavalMcMaster University
Fundersnot available
KeywordsHelpfulnessTetraplegiaSpinal cord injuryPhysical activityParaplegiaMedicinePhysical therapyPsychologySpinal cordPsychiatry

Abstract

fetched live from OpenAlex

The purpose of this study was to determine preferences of people with spinal cord injury (SCI) and health care professionals (HCP) regarding the content and format of a SCI physical activity guide to support recently released SCI physical activity guidelines. Seventy-eight people with SCI and 80 HCP completed a survey questionnaire. Participants with SCI identified desired content items and their preferences for format. HCP rated the helpfulness of content items to prescribe physical activity. All content items were rated favorably by participants with SCI and useful by HCP. The risks and benefits of activity and inactivity, and strategies for becoming more active, were rated high by both samples. Photographs and separate information for those with paraplegia versus tetraplegia were strongly endorsed. These data were used to guide the development of an SCI physical activity guide to enhance the uptake of physical activity guidelines for people with SCI. The guide was publically released November 11, 2011.

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)0.003
metaresearch head score (Gemma)0.010
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 score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.096
GPT teacher head0.450
Teacher spread0.354 · 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

Citations19
Published2012
Admission routes1
Has abstractyes

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