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Record W3006196982 · doi:10.1186/s12966-020-00924-9

Patterns and predictors of exercise behavior during 24 months of follow-up after a supervised exercise program during breast cancer chemotherapy

2020· article· en· W3006196982 on OpenAlexafffund
Ki‐Yong An, Dong‐Woo Kang, Andria R. Morielli, Christine M. Friedenreich, Robert D. Reid, Donald C. McKenzie, Karen A. Gelmon, John R. Mackey, Kerry S. Courneya

Bibliographic record

VenueInternational Journal of Behavioral Nutrition and Physical Activity · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsBC Cancer AgencyUniversity of OttawaUniversity of British ColumbiaAlberta Health ServicesUniversity of CalgaryUniversity of Alberta
FundersCanada Research ChairsAlberta InnovatesCanadian Breast Cancer Research AllianceAlberta Innovates - Health SolutionsCanadian Institutes of Health ResearchAlberta Cancer Foundation
KeywordsMedicineAerobic exerciseBreast cancerPhysical therapyPhysical fitnessRandomized controlled trialInternal medicineLogistic regressionBreast cancer chemotherapyCancer

Abstract

fetched live from OpenAlex

BACKGROUND: Understanding the longer-term exercise behavior of patients with breast cancer after chemotherapy is important to promote sustained exercise. The purpose of the current study was to report the longer-term patterns and predictors of exercise behavior in patients with breast cancer who exercised during chemotherapy. METHODS: In the Combined Aerobic and Resistance Exercise (CARE) Trial, 301 patients with breast cancer were randomized to three different exercise prescriptions during chemotherapy. Exercise behaviors after chemotherapy were self-reported at 6-, 12-, and 24-month follow-up. Exercise patterns were identified by categorizing patients according to which exercise guideline they were meeting (neither, aerobic only, resistance only, or combined) at each of the three follow-up timepoints (64 possible patterns). Predictors of longer-term exercise behavior included physical fitness, patient-reported outcomes, and motivational variables from the theory of planned behavior assessed at postintervention (postchemotherapy). Univariate and multivariate stepwise multinomial logistic regression and linear regression were used for statistical analyses. RESULTS: A total of 264 (88%) participants completed all three follow-up exercise behavior assessments and exhibited 50 different exercise patterns. Postintervention aerobic fitness was the most consistent predictor of longer-term exercise behavior at all three timepoints. For example, higher aerobic fitness (per 1 ml/kg/min) predicted better adherence to the "aerobic only" (OR = 1.09; p = 0.005) and "combined" (OR = 1.12; p < 0.001) guidelines compared to "neither" guideline at 6-month follow-up. Additionally, higher postintervention muscular strength (per 1 kg) was associated with better adherence to the "resistance only" (OR = 1.07; p = 0.025) and "combined" (OR = 1.08; p < 0.001) guidelines compared to "neither" guideline at 24-month follow-up. Finally, lower perceived difficulty (per 1 scale point) was associated with better adherence to the "combined" (OR = 0.62; p = 0.010) and "aerobic only" (OR = 0.58; p = 0.002) guideline compared to the "neither" guideline at the 24-month follow-up. CONCLUSIONS: Our study is the first to show that the longer-term exercise patterns of patients with breast cancer who exercised during chemotherapy are diverse and predicted by physical fitness and motivational variables after chemotherapy. Our novel implications are that improving physical fitness during chemotherapy and applying motivational counseling after chemotherapy may improve longer-term exercise behavior in patients with breast cancer. TRIAL REGISTRATION: (NCT00249015).

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)0.003
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.305
Teacher spread0.286 · 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

Citations32
Published2020
Admission routes2
Has abstractyes

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