The Experience of Patients with Cancer during Diagnosis and Treatment Planning: A Descriptive Study of Canadian Survey Results
Bibliographic record
Abstract
BACKGROUND: Communication with health care providers during diagnosis and treatment planning is of special importance because it can influence a patient's emotional state, attitude, and decisions about their care. Qualitative evidence suggests that some patients experience poor communication with health care providers and have negative experiences when receiving their cancer diagnosis. Here, we use survey data from 8 provinces to present findings about the experiences of Canadian patients, specifically with respect to patient-provider communication, during the diagnosis and treatment planning phases of their cancer care. METHODS: Data from the Ambulatory Oncology Patient Satisfaction Survey, representing 17,809 survey respondents, were obtained for the study. RESULTS: Most respondents (92%) felt that their care provider told them of their cancer diagnosis in a sensitive manner. Most respondents (95%) also felt that they were provided with enough information about their planned cancer treatment. In contrast, more than half the respondents who had emotional concerns upon diagnosis (56%) were not referred to services that could help with their anxieties and fears. Also, 18% of respondents reported that they were not given the opportunity to discuss treatment options with a care provider, and 17% reported that their care providers did not consider their travel concerns while planning for treatment. CONCLUSIONS: Measuring the patient experience allows for an understanding of how well the cancer control system is addressing the physical, emotional, and practical needs of patients during diagnosis and treatment planning. Although results suggest high levels of patient satisfaction with some aspects of care, quality improvement efforts are still needed to provide person-centred care.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".