Patient, Caregiver, and Clinician Perspectives on the Time Burdens of Cancer Care
Bibliographic record
Abstract
Importance: Cancer and its care impose significant time commitments on patients and care partners. The oncology community has only recently conceptualized these commitments and the associated burden as the "time toxicity" of cancer care. As the concept gains traction, there is a critical need to fundamentally understand the perspectives of multiple stakeholders on the time burdens of cancer care. Objectives: To explore time-consuming aspects of cancer care that were perceived as burdensome, identify the individuals most affected by time burdens of cancer care, and evaluate the consequences of these time burdens. Design, Setting, and Participants: Participants in this qualitative analysis were recruited from a National Cancer Institute-designated cancer center in Minnesota, where semistructured qualitative interviews were conducted from February 1 to October 31, 2023. Purposive and criterion sampling methods were used to recruit patients (adults with advanced stage gastrointestinal cancer receiving systemic cancer-directed treatment), care partners (patient-identified informal [unpaid] partners), and clinicians (physicians, physician assistants, nurse practitioners, nurses, social workers, and schedulers). Data were analyzed from February 2023 to February 2024. Main Outcomes and Measures: Thematic analysis was conducted with a hybrid (inductive and deductive methods) approach. Themes, subthemes, and illustrative quotations are presented. Results: Interviews included 47 participants (16 patients [8 aged ≤60 years; 12 women (75.0%)], 15 care partners [12 aged ≤60 years; 9 women (60.0%)], and 16 clinicians [11 women (68.7%)]). A total of 31 subthemes were identified that were grouped into 5 themes. Theme 1 captured time burdens due to health care outside the home (eg, travel, parking, and waiting time), while theme 2 identified the often invisible tasks performed at home (eg, handling insurance and medical bills, receiving formal home-based care). Theme 3 explored how care partners are affected alongside patients (eg, burdens extending to the wider network of family, friends, and community) and theme 4 represented the consequences of time burdens (eg, demoralization, seemingly short visits turned into all-day affairs). Finally, theme 5 referenced positive time spent in clinical interactions and hope for change (eg, patients value meaningful care, the "time toxicity" label is a spark for change). Conclusions and Relevance: This qualitative analysis identifies key sources and effects of time toxicity, as well as the populations affected. The results of this study will guide the oncology community to map, measure, and address future time burdens.
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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 | 0.015 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".