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Record W2802666212

Exploring sedentary behaviour in young adult cancer survivors

2017· dissertation· en· W2802666212 on OpenAlexfundno aff
Ryan H. Collins

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2017
Typedissertation
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsnot available
FundersBeatrice Hunter Cancer Research InstituteCancer Research Institute
KeywordsQuality of life (healthcare)Psychological interventionPhysical activityGerontologyMedicinePhysical therapyPsychology
DOInot available

Abstract

fetched live from OpenAlex

To explore sedentary behaviour (SB), physical activity (PA), and quality of life (QoL) in young adult cancer survivors (YACS). Methods: YACS aged 18-44 completed an online survey, which assessed SB, PA, and QoL using validated measures (i.e., The SIT-Q, Leisure Score Index (LSI), Short Form-36 Health Survey (SF-36), and Functional Assessment of Cancer Therapy: General (FACT-G)). Results: Participants had an average of 777.1 (SD= 274.0) minutes/day of total sedentary time and 113.4 minutes/week of moderate-to-vigorous PA (SD= 132.4), which was positively correlated with the physical component score (PCS) (r= .32, p<.01) of the SF-36. Multiple regression analyses showed that moderate and vigorous PA significantly predicted the PCS (R²= .10, p<.01), as did napping and TV viewing time (R²= .13, p<.01). Conclusion: YACS were sedentary, inactive, and their activity levels positively correlated with indicators of QoL. Future research should focus on developing effective interventions to improve these behaviours in YACS.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.080
GPT teacher head0.333
Teacher spread0.254 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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