Prevalence and Predictors of Complementary and Alternative Medicine (CAM) Use Among Health Workers in Nigeria
Bibliographic record
Abstract
BACKGROUND: The use of complimentary and alternative medicines has risen globally. We therefore, explored the prevalence and predictors of use of complementary and alternative medicines among healthcare workers. METHODS: This was a cross-sectional study that was conducted between 1st June and 31st August 2018 on the use of complementary and alternative medicines among health workers in Federal Medical Center Makurdi and Benue State University Teaching Hospital, Makurdi in Benue State. Questionnaire was used to collect data from respondents and data analysed using logistic binary regression models. RESULT: Response rate for the study was 80.2% out of which females were 196 (58.2%) with 215 (65.7%) in the age bracket of 31 – 60 years. Married respondents were 244 (72.4%) while Medical Doctors followed by Nurses were 87 (25.8%) and 84 (24.9%) respectively. Majority of the respondents, 113 (33.8%) have a monthly salary of above N100,000 (277.8 USD @ exchange rate of N360) while health workers of Tiv ethnic extraction had the highest number of 202 (60.7%) followed by those of Idoma extraction, 95 (28.5%). Those with years of work experience between (0 -15) were 268 (87.9%). The most used CAM was spiritual therapy, 230 (68.2%) while whole-body therapy was the least with 84 (24.9%). Use of biological therapy and manipulative therapy were 182 (54%) and 207 (61.4%) respectively. The odds of a female health worker using spiritual therapy was more than twice that of their male counterpart, (AOR: 2.218, 95% CI: 1.391 – 3.538). The odds of a Community Health Extension Worker and a medical doctor using a biological therapy among the study population were four times and almost thrice respectively compared to a pharmacist (AOR: 4.117, 95% CI: 1.690 – 10.030) and (AOR: 2.541, 95% CI: 1.095 – 5.896). The odds of an Idoma health worker using a manipulative and body-based therapy was thrice that of a Tiv health worker (AOR: 3.00, 95% CI: 1.318 – 6.829). While the odds of a Tiv health worker using whole-body therapy was seven times that of Idoma (AOR: 7.420, 95% CI: 2.186 – 25.188. CONCLUSION: There was high prevalence of CAM use by health workers and this has potentials to influence integration of CAM with conventional medicines.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| 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".