Science, Art, Litt, Science based Art & Science Communication
Q: Dr. Krishna, can you please explain what genuine scientific evidence is?
Understanding where true scientific evidence comes from, and what it means, is imperative to helping us tackle the most important issues affecting our own lives and the world we live in.
In science, evidence has utmost importance. Unless you provide evidence for your theory, your argument remains inconclusive and unattended. Majority of the people don't accept it. Evidence is what differentiates science from nonsense and is a part of scientific method.
So, if I ask for evidence in a lab, can you bring someone from outside who can vouch for what you say and say that is evidence? NO! We cannot trust such evidences.
Scientific evidence is information gathered from systematic scientific research, which takes a lot of time and patience to conduct. Evidence in general means information, facts or data supporting (or contradicting) a claim, assumption or hypothesis .
But evidence has several levels and where your evidence stands dictates the authenticity of your theory.
Evidence can range from non existent, weak, equivocal, consistent with, good, strong or compelling. Compelling evidence corresponds to the confirmation of a thing that is ‘satisfied beyond all reasonable doubt’ .
Now Scientific evidence differs from evidence presented in courts. When referring to "evidence from the scientific literature” we mean the empirical studies published in high quality peer-reviewed-journals. And meta analysis or systemic review is the highest form of evidence scientists accept.
Image source: Science Media center - NZ
The lowest form of evidence is anecdotal evidence like the ones accepted in courts (you can buy evidence if you want here), business (oh, so many celebrities in ads support so many products!) and in religion (this God really cured my disease when I prayed to him). Also like when people tell their stories based on their perceptions and not on reality. For instance, some quack or a God man gives a person a ' herbal medicine'. It might just be a placebo effect, but the person might feel better after taking it. Or his faith (or fear) in his 'guru' might make the person think the 'medicine' worked. What is the evidence that the 'medicine' actually worked? Unless you test the ingredients of the medicine in a genuine lab, its effects on a living system by taking large samples and avoiding all the pitfalls, fallacies, biases ( double blind trials), and confirm the results over and over again (reproduction of the results), you cannot come to a conclusion. Mere perception based on speculation is not evidence! Because it might not be true in reality.
Again opinions of even experts don't count much. An expert opinion on a particular topic is considered to be at the same level as anecdotal evidence. Of course, if references to other, more rigorous scientific studies are provided as part of the opinion, it can help, but it’s still best to go to the source of the evidence in these cases.
If a research paper says a substance 'has the potential to effect microbes', it doesn't become 'cure to a disease'. It is a mere speculation and not evidence! Get that right.
And if researchers 'publish' their work in dubious journals that take money to publish rubbish or announce their results in news papers or personal websites or books, they cannot be taken as genuine evidences.
These are a few examples of such anecdotal or false evidences even highly qualified people give:
Just ignore them. No genuine scientist accepts them as true evidence.
In the world of scientific research, the highest quality evidence are meta reviews, which are methods to contrast and combine results from a wide swath of peer-reviewed studies which may be useful in identifying patterns, sources of disagreement and other relationships. Since meta reviews combine the results from a larger number of studies, they can be more statistically significant. However, these reviews should be made by the scientific community only for the conclusions to be accurate.
Decisions about the utility of an intervention or the validity of a hypothesis cannot be based on the results of a single study, because results typically vary from one study to the next. Rather, a mechanism is needed to synthesize data across studies. Narrative reviews had been used for this purpose, but the narrative review is largely subjective (different experts can come to different conclusions) and becomes impossibly difficult when there are more than a few studies involved. Meta-analysis, by contrast, applies objective formulas (much as one would apply statistics to data within a single study), and can be used with any number of studies.
A meta-analysis is a statistical analysis that combines the results of multiple scientific studies. Meta-analysis can be performed when there are multiple scientific studies addressing the same question, with each individual study reporting measurements that are expected to have some degree of error. The aim then is to use approaches from statistics to derive a pooled estimate closest to the unknown common truth based on how this error is perceived. Existing methods for meta-analysis yield a weighted average from the results of the individual studies, and what differs is the manner in which these weights are allocated and also the manner in which the uncertainty is computed around the point estimate thus generated. In addition to providing an estimate of the unknown common truth, meta-analysis has the capacity to contrast results from different studies and identify patterns among study results, sources of disagreement among those results, or other interesting relationships that may come to light in the context of multiple studies.
A key benefit of this approach is the aggregation of information leading to a higher statistical power and more robust point estimate than is possible from the measure derived from any individual study. However, in performing a meta-analysis, an investigator must make choices which can affect the results, including deciding how to search for studies, selecting studies based on a set of objective criteria, dealing with incomplete data, analyzing the data, and accounting for or choosing not to account for publication bias.
Because large amount of studies are reviewed in meta-analysis, error margins are less, reproducibility of the results is covered and biases and fallacies are surmounted to a large extent. That is why conclusions obtained from meta-analysis - when done in the right manner - is the highest form of evidence and we trust it more than anything else.
The aim of science is to build more accurate and powerful natural explanations and use the knowledge for the benefit of the world, not to mislead and exploit the world using dubious means. Getting your evidence right is is utmost important in achieving these noble goals.