‘’It’s like I am always on a leash’’: A multi-stakeholder qualitative analysis of the time toxicity of cancer care.
Bibliographic record
Abstract
209 Background: As the oncology community increasingly acknowledges the time burdens of cancer care, there is a critical need for foundational work to understand the sources, populations impacted, and consequences of time toxicity. We sought to evaluate these through qualitative interviews. Methods: We conducted semi-structured interviews with adults with advanced stage gastrointestinal cancer, informal care partners, and clinicians at an NCI-designated cancer center in MN, USA from Feb-Oct 2023. We explored aspects of cancer care that took up time and were perceived as burdensome, identified those most impacted, and the consequences. We recorded and transcribed interviews, and conducted inductive thematic analysis. Results: We interviewed 47 participants [16 patients (8 <60 years; 12 women), 15 care partners (10 <60 years; 9 women), and 16 clinicians (including advanced practice providers, nurses, physicians, schedulers, and social workers; 11 women)]. We identified 22 subthemes that we grouped into 5 themes (Table). Conclusions: This multi-stakeholder qualitative analysis provides a deeper understanding of time toxicity. These data will help the oncology community to map, measure, and ultimately address time toxicity. Theme Subthemes Illustrative quotes Source: Healthcare outside the home Travel, parking, and, waiting time, planned appointments, unplanned care, hospitalizations and facility-based care '’My wife and I made over 100 drives in two years, over an hour and a half in each direction.’’ (Patient) Source: Often invisible tasks performed at home Logistic and administrative tasks, learning about the disease and treatment, medical management, time spent managing symptoms and on recovery, home-based care ‘’A large burden was like the insurance paperwork.’’ (Care partner)‘’And that has happened before where I've just spent the whole day at home waiting for home care.’’ (Patient) Populations impacted: Care partners alongside patients Care partners are equally affected, taking over social responsibilities/ tasks of daily living ‘’Anything that takes time for me, is almost an equal burden on her. If not more sometimes.’’ (Patient) Consequences Care becomes all-consuming, short visits turn into ‘’all-day’’ affairs, missing important life events/work, emotional distress, demoralization, financial burdens ‘’ It’s like I am always on a leash. I really don't have any control.’’ (Patient)‘’Even for a 30-minute infusion, you'll be there, like half a day or a whole day.’’ (Patient) Positive interactions and hope for change Not all time spent is perceived as burdensome, clinicians are hopeful of decreasing time burdens, clinicians recognize their own time burdens as a barrier to addressing patients’ ‘’Patients having to walk through this incredibly long, circuitous way to check in, do labs as ritual—we are disdainful of a patient's time. We should demand change.’’ (Clinician)
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".