Effects of occupational therapy on quality of life, occupational performance, and occupational satisfaction in older adults with cancer: a multicentre, pragmatic, randomized, controlled trial protocol (OCEAN-OT)
Bibliographic record
Abstract
BACKGROUND: Cancer can impact the way older adults and their care partners engage in their occupations. As an expert in the field of occupations, the occupational therapist is able to assess and support both a person with cancer and (if applicable) their care partners, with regard to occupational disruptions. The primary objective of this study is to assess the effect of occupational therapy (OT) on quality of life (QoL) in older adults with cancer. The study's secondary objectives are to (i) describe changes over time in occupational performance and satisfaction scores in older adults with cancer receiving (or not) OT and (if applicable) for their care partners, (ii) assess the effect of OT sessions on QoL and adverse events in older adults with cancer and in their care partners, and (iii) describe the OT sessions' content and procedures. METHODS: OCEAN-OT is a multicentre, pragmatic, three-arm, parallel-group, open-label, assessor-blinded, superiority randomized controlled trial. The inclusion criteria are age 70 or over, a diagnosis of colorectal, breast, prostate or lung cancer, treatment with curative intent, and residence at-home. The first control group will receive usual care. A second control group will receive usual care and a priority-setting interview called the Canadian Occupation Performance Measure (COPM) at baseline and at 3 and 6 months. The intervention group will receive usual care, the COPM, and a three-month program of home OT sessions. QoL will be assessed by administering the 30-item European Organisation for Research and Treatment of Cancer Quality of Life Group Core Questionnaire at baseline and at 3 and 6 months (for patients) and the Zarit Burden Interview (for care partners). DISCUSSION: There are few published, evidence-based studies of rehabilitation in older adults with cancer, and the available data are related to exercise and physical health, rather than occupations. The future trial results might have implications for health policies and might be crucial for maintaining quality of life for older adults with cancer and for their care partners. TRIAL REGISTRATION: The study protocol has been approved by an investigational review board (reference: 2023-A00925-40) and registered at ClinicalTrials.gov (NCT05878782).
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".