Changes in daily activities of cancer patients after diagnosis: how do canadian and Iranian patients perceive the change?
Bibliographic record
Abstract
BACKGROUND: Being diagnosed with cancer has major impacts on a patient's life. This study was conducted to explore how specific daily activities of patients change as a result of cancer diagnosis or its treatment and how these patients feel about such changes. METHODS: This was a cross-sectional descriptive study. Cancer patients referred to our clinics and by completing a questionnaire, they reported their daily activities and how they changed after diagnosis. A total of 201 patients in Canada and 167 patients in Iran completed the questionnaire. The research setting was the outpatient cancer clinics of the Jewish General Hospital in Montreal, Canada (February to April 2008) and Imam Reza Hospital and Ghaem Hospital in Mashhad, Iran (March to August 2008). RESULTS: More than 40 percent of the patients reported changes after the diagnosis in at least 8 out of 22 daily activities listed in the questionnaire. While a negative perception towards the changes was more common, some patients also perceived some changes as positive. More than half of the participants (56.9%) who were employed at the time of diagnosis experienced changes in the amount or type of their paid work after being diagnosed with cancer. CONCLUSION: The impact of a cancer diagnosis and treatment on a patient's daily activities is drastic. There is a need to provide support and interventions to help patients maintain daily activities they need and/or like. Further studies are needed to better understand the nature of such interventions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".