Experiences, Opinions, and Use of Complementary and Alternative Medicine Among Alberta Midwives
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Complementary and alternative medicines (CAMs) are widely used by individuals in many parts of the world to treat different ailments and maintain good health. Midwives are maternity care providers who may recommend or provide CAMs to assist clients with their pregnancies and childbirth and the early neonatal health of infants. There are currently no provincial data on the recommendation and use of CAMs by Alberta midwives. Objectives: To describe the use, experiences, and opinions of Alberta midwives about CAMs, as well as their self-reported educational needs relating to CAM. Method: A descriptive cross-sectional survey was distributed to all midwives registered with the Alberta Association of Midwives. Result: The response rate to the survey was 23.7% and the completion rate was 82.7%. About 90% of the participating midwives recommended CAM, and 45.8% provided CAM very often to their clients. Client preferences and scientific evidence of efficacy were the most commonly stated reasons for recommending CAM. More than two-thirds (70.8%) of respondents believed that they lacked adequate CAM education. Conclusion: CAM was frequently recommended by the midwives who participated in this study. However, the majority of the participants indicated that they lack adequate knowledge and education in regard to CAM. Consequently, providing more CAM education opportunities for midwives may be justified. This article has been peer reviewed.
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it