Bibliographic record
Abstract
BACKGROUND: The term "cancer" is imbued with identity signals that trigger certain assumed sociocultural responses. Clinical practice with hematological cancer patients suggests the experience of these patients may be different than that of solid tumor cancer patients. OBJECTIVE: We sought to explore the research question: How are identity experiences described and elucidated by adult hematological cancer patients? METHODS: This qualitative study was guided by interpretive description as the methodological framework. RESULTS: Preexisting identity labels and assumptions assigned to the overarching "cancer" diagnosis were viewed by patients as entirely inadequate to fully describe and inform their experience. Instead, findings revealed the propensity of adult hematology oncology patients to co-create and enact new identities increasingly reflective of the nonlocalized nature of their cancer subtype. Three themes that arose from the data included the unique cancer-self, the invasion of cancer opposed to self, and the personification of the cancer within self. CONCLUSIONS: Hematology oncology patients experience and claim a postdiagnosis identity that is self-described as distinct and highly specialized, and are distinct to solid tumor patients in aspects of systemic and total consumption of the self. This uniqueness is extended to the specific hematological cancer subtype down to genetics, indicating a strong "new" sense of self. IMPLICATIONS FOR PRACTICE: The manner in which hematology oncology patients in this study embraced notions of transformed self and isolating uniqueness provides practitioners with a lens through which new and innovative interventions can be constructed to improve patient care and psychosocial outcomes.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.025 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".