Barriers to Communication About Complementary and Alternative Medicine With Patients: A Qualitative Study
Bibliographic record
Abstract
BACKGROUND: The purpose of this study is to explore the reasons for nurses’ reluctance to communicate with patients regarding the use of complementary and alternative medicines (CAM) and to determine ways of improving this communication. METHODS: A qualitative study using focus group interviews was conducted with 54 nurses participated in eight focus groups. Interview data were transcribed verbatim using framework analysis. Ethical approval was obtained from the Research Ethics Board. RESULTS: The themes were related to the reasons for nurses’ reluctance to communicate with patients were: (1) “the scope of nursing practice regarding CAM is unclear”, (2) “lack of CAM competencies in communication”, and (3) “unsupportive workplace culture in the communication of CAM”. The strategies for improving the communication were: (1) “awareness of the needs for CAM education”, (2) “engagement of interdisciplinary teamwork for CAM practice”, and (3) “establishment of an organizational standard for CAM practice”. CONCLUSIONS: This study provided new insights into the barriers to communication regarding CAM use with patients from the nurses’ perspectives, and helped identify the ways of improving this communication to advance the practice of nursing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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; 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".