Determining Occupational Performance Issues in Women with Breast Cancer Referred to Treatment Centers of Hamadan, Iran
Bibliographic record
Abstract
Objective: Women with breast cancer experience functional limitations at the time of diagnosis and after the initial treatment of cancer. Such limitations interfere with participation in self-care, work affairs, and leisure activities. The present study aimed to determine occupational performance priorities in women with breast cancer who had referred to treatment centers in Hamadan, Iran. Methods: In this cross-sectional, descriptive-analytical study, 102 women with breast cancer who had referred to treatment centers in Hamadan were selected through convenience sampling. The participants’ information was gathered using their medical records and a demographic information questionnaire. Then, they were interviewed using the Canadian Occupational Performance Measure (COPM) to determine their occupational performance issues. The gathered data were coded and analyzed using the SPSS statistical software, version 16. Results: The results indicated that out of the 22 defined codes for the patients’ selected activities, 45.8%, 30.8%, and 23.4% belonged to self-care, productivity, and leisure domains, respectively. Conclusion: Women with breast cancer experience various occupational performance issues due to disease complications and received treatments. In the present study, self-care comprised the occupational performance priority. Determining the clients’ intervention priorities, which is among the bases of occupational therapy interventions, can help women with breast cancer reach the desired quality of life.
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 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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".