Writing between the lines: A secondary analysis of unsolicited narratives from cancer survivors regarding their fear of cancer recurrence
Bibliographic record
Abstract
Background: Fear of cancer recurrence (FCR) is a common concern for posttreatment cancer survivors. In this secondary analysis we explore cancer survivors' unsolicited narratives on a survey about FCR. Methods: We used an interpretive descriptive approach and statistical analyses to explore these narratives and determine the characteristics of survivors who did and did not provide narratives. Findings: We developed three themes based on our analysis: describe posttreatment experiences; elaborate or contextualize FCR responses and use their voice toward change in cancer care. Those who provided narratives had lower overall FCR. Most narratives were used to provide context to responses or to indicate that some survey items were irrelevant. Conclusion: Our results highlight potential reasons for unsolicited narratives on a survey and illuminate the potential value of expressive interventions for cancer survivors. Results indicate the usefulness of mixed methods approaches where survey respondents are offered space to provide open text.
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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 | 0.013 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".