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Record W4386175272 · doi:10.1249/tjx.0000000000000015

From a Vital Sign to Vitality: Selling Exercise So Patients Want to Buy It

2016· article· en· W4386175272 on OpenAlexaff
Michelle Segar, Eva Guérin, Edward M. Phillips, Michelle Fortier

Bibliographic record

VenueTranslational Journal of the American College of Sports Medicine · 2016
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsMontfort Hospital
Fundersnot available
KeywordsVitalitySign (mathematics)Medical prescriptionExercise prescriptionPsychologyValue (mathematics)Physical activityHealth careFeelingMedicineApplied psychologyNursingPhysical therapySocial psychologyComputer science

Abstract

fetched live from OpenAlex

ABSTRACT Exercise is Medicine ® (EIM) and physical activity as a vital sign are based on health-focused research and reflect ideal frames and messages for clinicians. However, they are nonoptimal for patients because they do not address what drives patients’ decision-making and motivation. With the growing national emphasis on patient-centered and value-based care, it is the perfect time for EIM to evolve and advance a second-level consumer-oriented exercise prescription and communication strategy. Through research on decision-making, motivation, consumer behavior, and meaningful goal pursuit, this article features six evidence-based issues to help clinicians make physical activity more relevant and compelling for patients to sustain in ways that concurrently support patient-centered care. Physical activity prescriptions and counseling can evolve to reflect affective and behavioral science and sell exercise so patients want to buy it.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.834
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.000

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 head0.030
GPT teacher head0.349
Teacher spread0.320 · 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

Citations10
Published2016
Admission routes1
Has abstractyes

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