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Record W2955221415 · doi:10.1002/oby.22535

Relationship of Consistency in Timing of Exercise Performance and Exercise Levels Among Successful Weight Loss Maintainers

2019· article· en· W2955221415 on OpenAlexaff
Leah M. Schumacher, J. Graham Thomas, Hollie A. Raynor, Ryan E. Rhodes, Kevin O’Leary, Rena R. Wing, Dale S. Bond

Bibliographic record

VenueObesity · 2019
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMorningMedicineAutomaticityConsistency (knowledge bases)EveningDemographyPhysical therapyPhysical activityInternal medicineCognitionMathematics

Abstract

fetched live from OpenAlex

OBJECTIVE: This study aimed to evaluate whether consistency in time of day that moderate- to vigorous-intensity physical activity (MVPA) is performed relates to MVPA levels among successful weight loss maintainers in the National Weight Control Registry. METHODS: Participants (n = 375) reporting MVPA on ≥ 2 d/wk completed measures of temporal consistency in physical activity (PA) (> 50% of MVPA sessions per week occurring during the same time window: early/late morning, afternoon, or evening), PA levels, PA automaticity, and consistency in cues underlying PA habit formation (e.g., location). RESULTS: Most (68.0%) participants reported temporally consistent MVPA. These individuals reported higher MVPA frequency (4.8 ± 1.6 vs. 4.4 ± 1.5 d/wk; P = 0.007) and duration (median [IQR]: 350.0 [200.0-510.0] vs. 285.0 [140.0-460.0] min/wk; P = 0.03), and they were more likely to achieve the national MVPA guideline (≥ 150 min/wk) than temporally inconsistent exercisers (86.3% vs. 74.2%, P = 0.004). Among temporally consistent exercisers, 47.8% were early-morning exercisers; MVPA levels did not differ by time of day of routine MVPA performance (P > 0.05). Greater automaticity and consistency in several cues were related to greater MVPA among all participants. CONCLUSIONS: Most participants reported consistent timing of MVPA. Temporal consistency was associated with greater MVPA, regardless of the specific time of day of routine MVPA performance. Consistency in exercise timing and other cues might help explain characteristic high PA levels among successful maintainers.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.293

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.029
GPT teacher head0.277
Teacher spread0.248 · 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 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

Citations30
Published2019
Admission routes1
Has abstractyes

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