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Record W2280684174 · doi:10.1007/s12160-015-9761-9

Exercise to Enhance Smoking Cessation: the Getting Physical on Cigarette Randomized Control Trial

2016· article· en· W2280684174 on OpenAlexafffund
Harry Prapavessis, Stefanie De Jesus, L. Fitzgeorge, Guy Faulkner, Ralph Maddison, Sandra Batten

Bibliographic record

VenueAnnals of Behavioral Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsUniversity of TorontoFanshawe CollegeWestern University
FundersCanadian Cancer Society Research Institute
KeywordsSmoking cessationMedicineNicotine replacement therapyAbstinencePhysical therapyRandomized controlled trialIntervention (counseling)Health psychologyInternal medicinePublic healthPsychiatryNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Exercise has been proposed as a useful smoking cessation aid. PURPOSE: The purpose of the present study is to determine the effect of an exercise-aided smoking cessation intervention program, with built-in maintenance components, on post-intervention 14-, 26- and 56-week cessation rates. METHOD: Female cigarette smokers (n = 413) participating in a supervised exercise and nicotine replacement therapy (NRT) smoking cessation program were randomized to one of four conditions: exercise + smoking cessation maintenance, exercise maintenance + contact control, smoking cessation maintenance + contact control or contact control. The primary outcome was continuous smoking abstinence. RESULTS: Abstinence differences were found between the exercise and equal contact non-exercise maintenance groups at weeks 14 (57 vs 43 %), 26 (27 vs 21 %) and 56 (26 vs 23.5 %), respectively. Only the week 14 difference approached significance, p = 0.08. CONCLUSIONS: An exercise-aided NRT smoking cessation program with built-in maintenance components enhances post-intervention cessation rates at week 14 but not at weeks 26 and 56.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.072
GPT teacher head0.408
Teacher spread0.337 · 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 designRandomized trial
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

Citations42
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueAnnals of Behavioral MedicineSame topicSmoking Behavior and CessationFrench-language works237,207