A model of identity grounded in the acute season of survivorship
Bibliographic record
Abstract
OBJECTIVE: Survivorship literature generally focuses on the cancer experience after diagnosis and treatment. However, acute survivorship, beginning with diagnosis and ending at the completion of treatment, has a lasting impact on the well-being of patients. The purpose of this study was to generate a theoretical understanding of how identity is affected during acute survivorship. METHODS: Using grounded theory and interviews with patients, their families, and their friends, the impact of the acute survivorship phase on the identity of patients was explored in Manitoba, Canada. Forty-two interviews were carried out, involving 18 patients with early malignancies and 15 friends and family members. RESULTS: The theory which evolved suggests that identity can be viewed as a construct of 3 concepts: values, social domains, and routine. Following diagnosis identity is disrupted as patients face challenges integrating the health care recipient social domain into their established routine. Patients indicated that the impact of the cancer diagnosis on their identities could have been minimized through earlier provision of the necessary information to re-establish routine. CONCLUSIONS: The theory that emerged from this study articulates the impact of the early cancer experience on the identity of patients. It also provides a framework for predicting which interventions may improve the cancer experience. Exploring how to best provide information that helps patients re-establish and maintain their routines after diagnosis is an important future direction.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 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".