What do we know about facilitating patient communication in the cancer care setting?
Bibliographic record
Abstract
Throughout the cancer diagnosis and treatment period, patients interact with multiple healthcare providers. In order to facilitate these communications, researchers have developed interventions primarily for providers, and, more recently, for patients. The aim of this paper is to conduct a critical examination of a sample of the empirical literature regarding current knowledge about the types of interventions that have been designed to facilitate cancer patients' communication with their healthcare providers. Overall, the empirical literature suggests that some types of patient-based interventions (e.g. prompt sheets, audiotapes, coaching sessions) may be beneficial in specific areas (e.g. increasing the number of questions asked, increased patient satisfaction). However, there are few consistent findings and the outcome measures that have been examined have varied substantially across studies. More controlled studies using carefully chosen outcome variables are needed. Increasing patients' communication skills so that their goals are met has the potential to positively affect the communication process.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".