Design of LONGEVITI (LIVinG with chrONIc cancEr Therapies): A Narrative Arts-Based Study of Living with Advanced Cancers Treated with Targeted Therapy
Bibliographic record
Abstract
Today, cancer treatments and the resultant illness experience is rapidly changing. In the early 2000’s breakthroughs in cancer biology and technology allowed the detection of molecular tumor characteristics promoting cancer growth, metastasis and cell immortality. These discoveries prompted the development of oral drugs specifically designed to block these targets. These oral targeted medications are ‘cytostatic’ as the disease remains in ‘stasis’ and does not grow or advance. As a result, advanced cancers that were formerly rapid death sentences are now treated with agents so effective that people are living for years with stable advanced cancers. Survivorship is commonly interpreted to define a state of being for individuals cured of early stage or localized cancers, commonly treated with surgery, chemotherapy and/or radiation. For those living with incurable chronic cancer, the cancer ‘battle’ is different from that of curable individuals. Targeted therapies continue until diagnostic imaging or bloodwork demonstrates the cancer is becoming resistant. Accordingly, incurable chronic cancer and evolving physical effects of the disease remain powerfully omnipresent for the remainder of the individual’s life. The aim of this research is to explore the day-to-day experiences of people living with advanced chronic cancers while being treated with self-administered oral targeted therapies. We will collect data through both qualitative interviews and arts-based methods. Semi structured in-depth interviews will explore people’s experiences of living with advanced cancers and receiving targeted therapies. The LIVinG with chrONIc cancEr treatments (LONGEVITI) study will enhance our understanding of the experiences of individuals self-managing advanced cancer with targeted medications. It will also assess the acceptability of innovative research methodologies. Ultimately, the goal is to advanced knowledge about this new and complex chronic disease among patients, healthcare providers and the general public.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".