RUFF Methodology for the Evaluation of Natural Therapies
Received: 27-Aug-2020 / Accepted Date: 10-Sep-2020 / Published Date: 17-Sep-2020 DOI: 10.4172/2573-4555.1000297
Description
This brief paper outlines a new approach to the evaluation of natural therapies. The RUFF approach is a time-efficient, content-free methodology which is ideally suited to confirmatory research where the evaluator knows the answer in advance and is seeking the most efficient, means of demonstrating the veracity of his claims. In this brief report we outline the approach and compare its performance with similar techniques including GRR, ROAR and SciGen.
Ruff Methodology
RUFF is the acronym given to the Revu’ d’ Urbanity for Fixation approach [1-3]. Step 1 is the development of a working hypothesis for which there is a reasonable constituency of support. Such ‘reasonableness’ can be hard to define but the benchmark is drawn low to present no barrier to the use of the approach. It usually constitutes little more than a vested interest in showing one side of a story in two dimensional vortexual space [2]. Step 2 involves a rapid and selective review of the literature. This takes place in two stages. The first stage involves what is known as dogmatic interpolation. The aim here is to find the initial piece of evidence (patient zero) which can act as a starting point case study and that is broadly supportive of the hypothesis. The second stage is known as dogmatic extrapolation. This involves repeated gyrations repeatedly searching for and retrieving supportive stories. One continues in this manner repeatedly adding confirmatory evidence until the weight points towards overall success. Advances in search technology have improved the effectiveness of this approach considerably. One can now usually find evidence in support of anything. Spurious science supports the likes of steaming one’s vagina, bio-frequency enhanced band-aids, and jade eggs [4-6].
Results
In trial tests we found that convergence can usually be achieved in a mean of three gyrations (s.d. +/-1.2). Most searches converge very quickly. Even in the most intractable cases, it is rarely the case that convergence is not achieved. However, it is better to keep going beyond 3 quantum units of evidence as each additional factoid generates a multiplier effect up until around 8 quanta’s, beyond which the utility begins to diminish [4]. To illustrate, to complete this brief note we relied on only five gyrations excluding self-citation.
The gyrational approach has humorously been likened to a dog chasing its tail. There is an element of truth in this characterization, but in this case the tail chasing is less a sign of obsessive-compulsive disorder and more a sign of myopia [5].
Discussion
RUFF has proved more user friendly than either the popular GRR approach or its more intensive cousin ROAR methodologies. Both are quite aggressive techniques. In contrast RUFF can be used in an inquisitive sense (is there anybody there?) or in an invitational manner (can we play). It is an ideally suited method for use Natural Therapies given the extensive reluctance on the part of complimentary therapists to evaluate the effectiveness of their recommendations and their path dependency [1].
References
- Djelic M, Quack S (2007) Overcoming path dependency: Path generation in open systems. Theor Soc 36: 161-186.
- Dritschel D (1995) A general theory for two-dimensional vortex interactions. J Fluid Mech 293: 269-303.
- Ormazabal KM (1995) The law of diminishing marginal utility in Alfred Marshall’s Principles of Economics. Problems in Standard Microeconomic Theory. Eur J Hist Econ Thought 2: 91-126.
- Tiira K, Hakosalo O, Kareinen L (2012) Environmental effects on compulsive tail chasing in dogs. PLOSOne 7: e41684.
- Worthington C. How much can you trust the Goop Lab according to science? The Vulture 2020.
Citation: Brador AL (2020) RUFF Methodology for the Evaluation of Natural Therapies. J Tradit Med Clin Natur 10: 297. DOI: 10.4172/2573-4555.1000297
Copyright: © 2020 Brador AL. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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