MétaCan
Menu
Back to cohort
Record W3029850259 · doi:10.1177/1534735420921439

Greater Well-Being in More Physically Active Cancer Patients Who Are Enrolled in Supportive Care Services

2020· article· en· W3029850259 on OpenAlexaboutno aff
Maíra Tristão Parra, Naghmeh Esmeaeli, Jordan N. Kohn, Brook L. Henry, Stephen D. Klagholz, Shamini Jain, Christopher M. Pruitt, Daniel Vicario, Wayne B. Jonas, Paul J. Mills

Bibliographic record

VenueIntegrative Cancer Therapies · 2020
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Heart, Lung, and Blood Institute
KeywordsMedicinePsychosocialCancerQuality of life (healthcare)Internal medicineDistressMoodBreast cancerProstate cancerDepression (economics)Physical therapyPsychiatry

Abstract

fetched live from OpenAlex

Background: Cancers are one of the leading causes of mortality worldwide. Cancer patients are increasingly seeking integrative care clinics to promote their health and well-being during and after treatment. Aim: To examine relationships between physical activity (PA) and quality of life (QoL) in a sample of cancer patients enrolling in integrative care in a supportive care clinic. Also, to explore circulating inflammatory biomarkers and heart rate variability (HRV) in relationship to PA and QoL. Methods: A cross-sectional design of adult patients who sought care in the InspireHealth clinic, Vancouver, British Columbia, Canada. Patients with complete PA data (n = 118) answered psychosocial questionnaires, provided blood samples, and received HRV recordings before enrollment. Patients were stratified into “less” versus “more” active groups according to PA guidelines (150 minutes of moderate or 75 minutes of vigorous PA or an equivalent combination). Results: Breast (33.1%) and prostate (10.2%) cancers were the most prevalent primary diagnoses. Patients engaging in more PA reported better physical ( U = 1265.5, P = .013), functional ( U = 1306.5, P = .024), and general QoL ( U = 1341, P = .039), less fatigue ( U = 1268, P = .014), fewer physical cancer-related symptoms ( U = 2.338, P = .021), and less general distress ( U = 2.061, P = .021). Between PA groups, type of primary cancer diagnosis differed (χ 2 = 41.79, P = .014), while stages of cancer did not (χ 2 = 3.95, P = .412). Fewer patients reported depressed mood within the more active group (χ 2 = 6.131, P = .047). More active patients were also less likely to have ever used tobacco (χ 2 = 7.41, P = .025) and used fewer nutritional supplements (χ 2 = 39.74, P ≤ .001). An inflammatory biomarker index was negatively correlated with vigorous PA ( r s = −0.215, P = .022). Multivariable linear regression ( R 2 = 0.71) revealed that age (β = 0.22; P = .001), fatigue (β = −0.43; P ≤ .001), anxiety (β = −0.14; P = .048), and social support (β = 0.38; P = .001) were significant correlates of QoL.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.286
Teacher spread0.275 · 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.

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

Citations3
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueIntegrative Cancer TherapiesSame topicCancer survivorship and careFrench-language works237,207