Cancer disclosure: Experiences of Iranian cancer patients
Bibliographic record
Abstract
This study explored Iranian patients' experiences of cancer disclosure, paying particular attention to the ways of disclosure. Twenty cancer patients were invited to participate in this qualitative inquiry by research staff in the clinical setting. In-depth, semistructured interview data were analyzed through content analysis. The rigor of the study was established by principles of credibility, transferability, dependability, and confirmability. Four themes emerged: the atmosphere of non-disclosure, eventual disclosure, distress in knowing, and the desire for information. Non-disclosure was the norm for participants, and all individuals involved made efforts to maintain an atmosphere of non-disclosure. While a select few were informed of their diagnosis by a physician or another patient, the majority eventually became aware of their diagnosis indirectly by different ways. All participants experienced distress after disclosure. The participants wanted basic information about their prognosis and treatments from their treating physicians, but did not receive this information, and encountered difficulty accessing information elsewhere. These challenges highlight the need for changes in current medical practice in Iran, as well as patient and healthcare provider education.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".