Protocol for a scoping review study on the prevalence and public health consequences of non-medical use (NMU) of tramadol in Africa
Bibliographic record
Abstract
BACKGROUND: Tramadol is one of the most prescribed painkillers in the world. It is a synthetic opioid that is an excellent alternative to morphine and its derivatives in African countries. It is an essential drug due to its low cost and constant availability. However, the health consequences of tramadol use due to illicit trafficking, like those caused by fentanyl and methadone in North America, are poorly documented. This scoping review aims to understand the nature and extent of the use and health consequences of the Non-Medical Use (NMU) of tramadol in Africa to guide future research. METHODS: Due to the perceived lack of African literature on the subject, our search strategy is based on the simultaneous use of the keywords "tramadol" and Medical Subject Heading (MeSH), such as "Drug abuse," "illicit drugs," or "Prescription Drug Misuse," combined with the term "Africa" and Boolean operators (and, or not) to form our search equations. Two researchers will independently select studies from literature searched in several databases such as Medline, Embase, the Scopus database, Web of Science, the African Journals online database, and for grey literature Google Scholar without any time restriction. All research, in various formats, conducted in Africa, will be included in our study on the prevalence of use in different African population groups or on evidence of addiction, intoxication, seizures and mortality related to NMU of tramadol. RESULTS: Through this study, we aim to map consumers and identify risk factors, health consequences, and prevalence of the NMU of tramadol in African countries. DISCUSSION: We are conducting the first scoping review study to investigate the prevalence and consequences of NMU of tramadol in Africa. Upon completion, our findings will be published in a peer-reviewed journal and presented at relevant conferences and workshops. However, since health is not limited to the lack of disease, our study is likely incomplete without incorporating the studies of the social impact of NMU of tramadol. SYSTEMATIC REVIEW REGISTRATION: Open Science Framework: https://osf.io/ykt25/.
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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 | 0.117 | 0.103 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.012 | 0.014 |
| Bibliometrics | 0.018 | 0.014 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.011 | 0.009 |
| Insufficient payload (model declined to judge) | 0.145 | 0.026 |
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".