A Roadmap for CAM Research towards the Horizon of 2020
Bibliographic record
Abstract
CAMbrella was the first pan-European research project that systematically evaluated the state of usage, motivation, provision, and regulation of CAM usage in European countries. It also documented the need and the way forward for research in Europe. Some of the finest minds in European CAM research were either part of the consortium or were invited as experts to some of the specialist meetings. Thus, CAMbrella formulates a consensus never seen in European research on this topic before. Results of the work packages – most of them systematic reviews – have been published, also in open access format in FORSCHENDE KOMPLEMENTARMEDIZIN [1]. Now, the final piece, roadmap 2020, has been published and is available online [2]. This roadmap sums up the findings briefly and points towards the future direction of research. You do not have to be a wizard to understand the most important message: European research was once at the forefront of research in this topic, and it is in danger of becoming last, being overtaken by countries such as USA, Canada, Australia, India, China, Africa even. All these countries and continents have either formulated a research agenda (Canada), or have dedicated institutes that have funding available (USA, Australia, India), or have at least understood that traditional approaches to medicine are a resource (India, China, Africa). In USA, a steady funding stream of approximately USD 120 million per year enables the maintenance of a proper research agenda. What about Europe? Apart from isolated pockets full of projects: nothing. UK, often a forerunner, spends 0.0085% of its research budget on CAM research, where 10% of the population use CAM approaches each year and approximately 50% are lifetime users. The figures are even lower for Germany which is among the countries of the highest prevalence of usage [3]. European researchers were among those that were invited to the first foundational conferences of the Office of Alternative Medicine at the National Institutes of Health (NIH) in the 1990s, because of innovative research design and because CAM research has had a long tradition in Europe. What happened afterwards? The USA saw that this was a growth market, supported research by founding a National Center for CAM research (NCCAM), and became world leader in research in this area [4]. And Europe? A few projects to have a placating answer for the public in the drawer, but nothing serious. We feel we are at the brink of an important junction in history. If we want to continue improving the health of European citizens, we cannot ignore that CAM is a potentially important player, being used by up to 60% of the population [5]. It is important to realize that we know very little about its comparative effectiveness vis-a-vis conventional approaches. We do not know whether and when it would be beneficial for patients to integrate CAM treatments into their conventional treatment regime. We do not know how many patients would want that. We do not know which treatments would be safe. And we do not know how it happens that seemingly strange treatments can produce such strong effects that in a time of abundance of medical provision people are prepared to pay out of their pocket for such treatments. This in itself is a topic of highest interest. But CAM would have other things in stock that answer well to consensus goals and strategies of the European Union: Antibiotic resistance is a major threat to the future health of our population. Developing more antibiotics will not help (and will probably not happen for economic reasons). How about a different strategy? Various CAM approaches might offer alternatives here, but we do not know enough about them, because they are not being researched. The major challenges to the threat of health will be chronic and degenerative diseases. Those will be very difficult and costly to treat with approaches that are designed for acutetype interventions, and will rarely be healed by them for good.
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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 | 0.051 | 0.057 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.013 | 0.027 |
| Open science | 0.006 | 0.014 |
| Research integrity | 0.022 | 0.015 |
| Insufficient payload (model declined to judge) | 0.080 | 0.028 |
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".