An exploratory cross-sectional study of the effects of ongoing relationships with accompanying patients on cancer care experience, self-efficacy, and psychological distress
Bibliographic record
Abstract
BACKGROUND: Centre hospitalier de l'Université de Montréal in Canada introduced accompanying patients (APs) into the breast cancer care trajectory. APs are patients who have been treated for breast cancer and have been integrated into the clinical team to expand the services offered to people affected by cancer. This study describes the profiles of the people who received the support and explores whether one-offs vs ongoing encounters with APs influence their experience of care, on self-efficacy in coping with cancer, and on their level of psychological distress. METHODS: An exploratory cross-sectional study was carried out among patients to compare patients who had one encounter with an AP (G1) with those who had had several encounters (G2). Five questionnaires were administered on socio-demographic characteristics, care pathway, evaluation of the support experience, self-efficacy in coping with cancer, and level of psychological distress. Logbooks, completed by the APs, determined the number of encounters. Linear regression models were used to evaluate the associations between the number of encounters, patient characteristics, care pathway, number of topics discussed, self-efficacy measures in coping with cancer, and level of psychological distress. RESULTS: Between April 2020 and December 2021, 60% of 535 patients who were offered support from an AP accepted. Of these, one hundred and twenty-four patients participated in the study. The study aimed to recruit a minimum of 70 patients with the expectation of obtaining at least 50 participants, assuming a response rate of 70%. There were no differences between G1 and G2 in terms of sociodemographic data and care pathways. Statistical differences were found between G1 and G2 for impacts on and the return to daily life (p = 0.000), the return to the work and impacts on professional life (p = 0.044), announcement of a diagnosis to family and friends (p = 0.033), and strategies for living with treatment under the best conditions (p = 0.000). Significant differences were found on the topics of cancer (p = 0.000), genetic testing (p = 0.023), therapeutic options (p = 0.000), fatigue following treatment (p = 0.005), pain and discomfort after treatment or surgery (p = 0.000), potential emotions and their management (p = 0.000) and the decision-making processes (p = 0.011). A significant relationship was found between the two groups for patients' ability to cope with cancer (p = 0.038), and their level of psychological distress at different stages of the care pathway (p = 0.024). CONCLUSIONS: This study shows differences between one-time and ongoing support for cancer patients. It highlights the potential for APs to help patients develop self-efficacy and cope with the challenges of cancer treatment.
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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) | 0.000 | 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".