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Record W2077740693 · doi:10.1007/s12160-014-9588-9

Exercise Counseling to Enhance Smoking Cessation Outcomes: The Fit2Quit Randomized Controlled Trial

2014· article· en· W2077740693 on OpenAlexaff
Ralph Maddison, Vaughan S. Roberts, Hayden McRobbie, Chris Bullen, Harry Prapavessis, Marewa Glover, Yannan Jiang, Paul Brown, William Leung, Sue Taylor, Midi Tsai

Bibliographic record

VenueAnnals of Behavioral Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsWestern University
FundersHealth Research Council of New ZealandEconomic and Social Research CouncilMedical Research Council
KeywordsSmoking cessationRandomized controlled trialMedicinePhysical therapyHealth psychologyPhysical activityPsychologyPublic healthInternal medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Regular exercise has been proposed as a potential smoking cessation aid. PURPOSE: This study aimed to determine the effects of an exercise counseling program on cigarette smoking abstinence at 24 weeks. METHODS: A parallel, two-arm, randomized controlled trial was conducted. Adult cigarette smokers (n = 906) who were insufficiently active and interested in quitting were randomized to receive the Fit2Quit intervention (10 exercise telephone counseling sessions over 6 months) plus usual care (behavioral counseling and nicotine replacement therapy) or usual care alone. RESULTS: There were no significant group differences in 7-day point-prevalence and continuous abstinence at 6 months. The more intervention calls successfully delivered, the lower the probability of smoking (OR, 0.88; 95 % CI 0.81-0.97, p = 0.01) in the intervention group. A significant difference was observed for leisure time physical activity (difference = 219.11 MET-minutes/week; 95 % CI 52.65-385.58; p = 0.01). CONCLUSIONS: Telephone-delivered exercise counseling may not be sufficient to improve smoking abstinence rates over and above existing smoking cessation services. (Australasian Clinical Trials Registry Number: ACTRN12609000637246.).

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.041
Threshold uncertainty score0.636

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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)0.0000.000

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 head0.069
GPT teacher head0.414
Teacher spread0.345 · 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.

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

Citations26
Published2014
Admission routes1
Has abstractyes

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