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Record W4416222025 · doi:10.1177/15394492251388033

Health Behavior Performance After a Personalized Occupational Therapy Intervention in Cancer Survivors

2025· article· en· W4416222025 on OpenAlexaboutno aff
Alix G. Sleight, Yoko E. Fukumura, Sandy C. Takata, Alexandra E. Feldman, Pamela Roberts, Kim Bissell, L J Amaral, Kathleen Doyle Lyons

Bibliographic record

VenueOTJR Occupational Therapy Journal of Research · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
FundersWorld Cancer Research FundAmerican Occupational Therapy FoundationAmerican Society of Preventive OncologyAmerican Association for Cancer Research
KeywordsIntervention (counseling)CancerOccupational therapyHealth behaviorOccupational safety and healthCancer treatmentPublic health

Abstract

fetched live from OpenAlex

BACKGROUND: Health behaviors significantly influence health outcomes after cancer. However, few studies have tested occupational therapy (OT) self-management training to catalyze health behavior change. OBJECTIVES: To establish proof of concept of a 12-week OT intervention designed to improve occupational performance and/or satisfaction in cancer survivors. METHODS: This single-arm, prospective study used the Canadian Occupational Performance Measure to measure change in occupational performance and satisfaction related to health behaviors in a convenience sample of 20 cancer survivors. RESULTS: = 20) post-intervention. A total of 18 participants (86%) demonstrated a clinically significant change in performance scores (≥2), and 19 participants (95%) demonstrated a clinically significant change in satisfaction scores (≥2). CONCLUSION: OT, when leveraged for a health self-management intervention, may result in improvements in both occupational performance and satisfaction related to health behavior in cancer survivors.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 integrity0.0000.001
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 head0.151
GPT teacher head0.503
Teacher spread0.352 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

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