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Is A Physician Prescription Enough For Promoting Physical Activity?

2011· article· en· W2328445301 on OpenAlexaffabout
Karla I. Galavíz, Lucie Lévesque

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2011
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedical prescriptionMedicineReferralPsychological interventionFamily medicinePhysical therapyIntervention (counseling)Primary careRandomized controlled trialInternal medicineNursing

Abstract

fetched live from OpenAlex

More than half of Canadians are not active enough to achieve the health benefits that physical activity (PA) offers. Primary care interventions have been used for addressing inactivity and have been shown to be effective for enhancing PA in adults, especially when using PA prescriptions and referrals to community programs. Yet, more evidence is needed to determine which of these strategies or combination of strategies is most effective for improving adults' PA behaviors. PURPOSE: To compare the effectiveness of a PA prescription plus a referral scheme with a PA prescription alone for improving adults' PA behaviors. METHODS: Ten family physicians (3 females) and 35 female patients (M age = 36.18 years, SD = 4.90) were sampled by convenience from a family medicine clinic located in a mid-size Canadian city. Patients were randomly assigned to one of three conditions: Prescription Plus (PP), Prescription Only (PO) and Usual Care (UC). The PP group received a PA prescription plus a referral to a community program, the PO group received just the PA prescription, and the UC group usual health care. Physicians in the PP and PO groups were trained to offer brief PA counseling using the 4-As model and to deliver the PA prescription. Self-reported PA was measured using an adaptation of the Godin Leisure-Time Exercise Questionnaire (Godin & Shephard, 1985) at baseline and eight weeks after patients received the intervention assigned. RESULTS: PA significantly increased from baseline to post-intervention in the PP (M = 42.0, SD = 23.9 vs. M = 59.7, SD = 27.5, p <.05) and the PO (M = 42.2, SD = 21.4 vs. M = 53.2, SD = 32.4, p <.05) groups. These increases were evident for the PP and PO groups whereas the UC group did not show any changes. The observed effect size indicated that the PP group achieved larger increases in PA (d =.70) than did the PO group (d =.40). However, PP and PO groups did not differ significantly. CONCLUSION: Both, the PP and the PO interventions improved participants' self-reported PA behaviors. In terms of cost-effectiveness, it seems that the PO intervention could be preferred given that positive PA outcomes can be achieved with fewer resources.

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)0.001
metaresearch head score (Gemma)0.011
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 score0.314
Threshold uncertainty score0.624

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.064
GPT teacher head0.343
Teacher spread0.279 · 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

Citations0
Published2011
Admission routes2
Has abstractyes

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