Impact of Treatments on the Family of Breast, Prostate, Colon and Lung Cancer Patients
Bibliographic record
Abstract
Objective: Many patients describe travel to cancer treatment as inconvenient and a practical hardship and it may be perceived or experienced as a barrier to treatment. We investigated which impact cancer treatments has on the family of the patients, especially for the most frequent cancer type prostate, breast, colon and lung cancer.The aim was to identify groups of patients with an increased burden for the family.Method: All patients coming in February 2012 for chemotherapy to one of the four centres of the hospital or to the unique private practice were asked to answer a survey. The questionnaire covered items as gender, date of birth, living place, kind of cancer, kind of treatment and questions covering different aspects of the travel: how the patient travelled to the centre, how long the travel lasted, which kind of support was necessary to travel and who provided this support, whether the accompanying person had to absent herself from her workplace, whether the patient lives alone or not and how many journeys to health care providers the patients had in the last month were included in the analysisResults: 298 patients answered to all required questions (73%). 186 came accompanied, a vast majority by a member of the family and one out of four of the accompanying person had to leave the workplace. Help at home is almost exclusively provided by family members. Patients have several journeys to health care providers per month.Conclusions: The type of cancer has an impact on the support needed and must added to the previously published factors as age, gender and distance. The journey to the cancer treatment is not the unique journey to health care providers the patients have and increase the burden for the patient and the family.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".