Patient–professional communication research in cancer: an integrative review of research methods in the context of a conceptual framework
Bibliographic record
Abstract
This paper uses the conceptual framework of Feldman-Stewart et al. to organize and review the types of research methodologies used to investigate various aspects of patient-health care professional communication in the context of cancer. Research methods employed are classified as either non-experimental or experimental. Non-experimental designs include naturalistic observational studies (e.g. participant observation, audio- or videotaping of interactions) and retrospective introspective descriptions (e.g. self-report questionnaires, qualitative interview methods). Experimental designs often involve interventions aimed at improving communication, such as physician or patient training, and the use of technology to enhance communication (e.g. audiotapes, computers). Using the conceptualization of the communication framework description, we argue that the outcome measures used in these studies address either primary goals, enabling goals, or secondary communication outcomes. Outcomes that are related to primary goals of the communication exchange include assessing the level of understanding of information conveyed, aspects of decision making, planning around treatments, or general provision of care. Outcomes related to enabling goals focus on elements that affect the ability to achieve primary goals. Outcomes secondary to the communication do not relate directly to what the communication is attempting to achieve. We conclude by identifying priority areas for further research, such as identifying the goals of both participants, understanding how particular aspects of the communication process affect their ability to achieve their goals, and examining the external environment in which communication takes place.
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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 | 0.098 | 0.107 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.033 | 0.031 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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".