Non-science, pseudoscience, quasi-science and bad science; is there a difference?

Hi all,

I had been thinking about this recently, so thought I’d run this up the proverbial flagpole!

Much contemporary research in nursing and the social sciences today adopts the methods of empirical science, but there are many alternative philosophical discourses that have also been gaining ground, and presented as valid alternative ways of exploring the world. However, a challenge arises if we try to characterize them as scientific inquiry as their foundational concepts, frameworks and beliefs are very different to established empirical science. To understand these distinctions more clearly, let us explore the nature of non-science, pseudo-science and quasi-science in relationship to scientific inquiry. There is frequently disagreement and conflation of these terms (even by scientists themselves) and the have many similarities. The separation of non-science and pseudoscience from scientific practices has philosophical, ethical and political implications for professional healthcare. So here is my take on the subject:


Simply put non-science refers to inquiry, academic work or disciplines that do not involve the process of empirical verification, or the scientific process to generate their products or knowledge base. These are disciplines that do not adopt a systematic methodology based on evidence. Many of the greatest human achievements represent non-science. They are activities that don’t purport to be scientific and are easily identified as non-scientific in their nature, including the arts, religion, and even philosophy. They usually involve creative processes, the acceptance of subjective knowledge, belief, revelation or faith in establishing their epistemological basis. The rejection of the principles of scientific inquiry is also frequently acknowledged in much postmodern thinking, which can also be categorized as non-science.

We should note that although non-scientific approaches to knowledge are widespread and highly valued in peoples throughout the world they are not highly valued in Evidence Based Practice (EBP), and in most public healthcare policies. This has led to much criticism of the ideas behind EBP. In effect non-science represents an alternative to scientific thinking, and these approaches have gained ground in some societies, illustrated by the growth of complimentary and alternative medicine (CAM) in many western countries since the 1990’s (Barker, 2007).


Pseudo-science is sometimes difficult to identify, but can be thought of as disciplines, inquiry or work that purports to be scientific, but upon examination are found to be non-science. Pseudoscience and non-science are frequently conflated, but I suggest they are quite different. The word “pseudo” comes from the Greek language for “false,” and in this case applies to non-scientific disciplines that purport to be scientific. Pseudoscientific practices are presented as scientific, but lack supporting evidence, and employ non-scientific methods and cannot be reliably tested or verified. They also frequently adopt highly implausible theoretical stances, but in many cases so do scientific theories, so this may not help in their differentiation. Pseudoscience is more often characterized by vague, exaggerated or unfalsifiable claims, with an over-reliance on confirmation rather than rigorous attempts at refutation.

Key features are usually vague or impenetrable theoretical stances that can only be truly understood by the inner cabal, a lack of openness to academic challenge and evaluation by other investigators, and the absence of established scientific processes in theory development and testing (Shermer, 2002; Gardner, 1957). They are also often characterized by arguments that the proponents of their discipline are besieged by a narrow-minded positivist scientific community, medicine or “big-pharma” or that a modern-day conspiracy/inquisition is hard at work to undermine them (or in the most extreme cases all of these arguments are used). Just because your paranoid….

Separating pseudoscience from science is far from easy, and the demarcation between science and pseudoscience has caused much debate in nursing and other health disciplines. For example many postmodern approaches to nursing knowledge such as Parse’s human-becoming theory (Parse, 1992) have been presented as alternative “caring science” but by any objective scientific perspective they represent pseudoscience. Pseudoscientific beliefs are also big business representing million dollar industries. They are even widespread, amongst university and public school science teachers and the media, and are evident in expert testimony, environmental policies, and even science education (Hobson, 2001). Of course, the best way to be able to identify pseudoscience is to know as much as possible about the real thing; in this case science.


Quasi-science is a term also sometimes encountered, and is difficult to separate from pseudoscience. We may consider that quasi-science resembles science, having some of the form, but not all of the features of scientific inquiry. Quasi-science involves an attempt to use a scientific approach but where development of a scientific theoretical basis or application of scientific methodologies is insufficient for the work to be determined as an established science. Differentiating quasi-science from pseudo-science or bad-science is complex and there is certainly some overlap, as some quasi-science falls into the realm of pseudoscience. But, generally quasi-science can be considered work involving commonly held beliefs in popular science but where they do not meet the rigorous criteria of scientific work. This is often seen with “pop” science that may blur the divide between science and pseudoscience among the general public, and may also be seen in much science fiction. For example ideas about time-travel, immortality, aliens and sentient machines are frequently discussed in the media, although there is insufficient empirical basis for much of this to be seen as scientific knowledge at this time. Quasi-science does not normally reject, or purport to be a new/alternative science and may be developed with an application of rigorous scientific methods into scientific work.

And lastly we have….

Bad Science

Bad science is simply scientific work that is carried out poorly or with erroneous results due to fallacies in reasoning, hypothesis generation and testing or the methods involved. Science, like any endeavor can be carried out badly, and often with the most noble motives. Occasionally scientists deliberately mislead for personal gain (and not always from their fortified secret island base), but in most cases bad science results from errors in the scientific process. Sometimes these errors are the result of poor practices, or the researchers unconscious imposition of their beliefs (looking for the answer they believe in). Science is an extraordinary process but as we have seen is not perfect, and has one notable flaw; it is carried out by people who are themselves unavoidably influenced by their own beliefs, and who are sometimes trained insufficiently and make mistakes (Barker, 2007).

This categorization seems to work for me, but I’d be interested on others ideas.



Barker, B. R. (2007). Snake oil science: The truth about complementary and alternative medicine Oxford ; Oxford University Press.

Gardner, M. (1957). Fads and fallacies in the name of science . New York: Dover Publications.

Hobson, A. (2001). Teaching relevant science for scientific literacy. Journal of College Science Teaching, 30(4), 23-243.

Parse, R. R. (1995). Illuminations: The human becoming theory in practice and research . Sudbury, Mass.: Jones and Barlett Publishers.

Shermer, M. (2002). Why people believe weird things: Pseudoscience, superstition, and other confusions of our time (2nd ed.). New York: Henry Holt.


Science, seas and saving the world.

No, no, it’s me that needs to apologise for lateness! It was my turn to blog, but life rather caught up with me over the last few weeks. Anyhow, you get two this week both related to events that we have attended.

Although not in New York, last night I attended the inaugural professorial lecture by Professor Camille Parmesan, who has just started working at Plymouth University, having come from the University of Texas where her work has concentrated on the evidence and impact of climate change, particularly in marine environments. She was part of the Intergovernmental Panel on Climate Change (IPCC) that won the Nobel Prize a few years back.

Her lecture was fascinating, but exceptionally worrying. She initially concentrated on marine ecosystems about which we don’t have too much long-term data but the more recent stuff is far more robust and detailed. The news is not good to put it mildly.  The maps she showed of fish population collapses in the North Atlantic where startling. Current density maps would not even register on the scales used on such maps from 30 years ago. Populations have declined by orders of magnitude. As she pointed out this has far more to do with over-fishing, but she went on to show that removing fish ‘weakens’ the ecology of the system making it less resilient to climate change. Fish have a vital role in helping systems adapt to change, without them the seas are far more vulnerable to algal blooms, eutrophic enrichment and eventual ecological collapse.

Well. OK, that’s bad news for the fish (oh and marine mammals, crustacean, corals etc etc) but we had the good sense to get out of the seas millions of years ago. We live on the land, we’ll be alright. Well, unfortunately not. As in the second half of the lecture she presented some of the up to date data from the IPCC. She started with the famous IPCC graph of the range of predicted global temperature changes.  Of course we’re a good 10 to 15 years into those predictions now and she showed that based on data from the last decade we can now abandon the lower ranges. The mid range prediction of a 2oC rise in temperature by 2100 is now the lower.  The upper of 4oC is now the mid, and so on.

So, what does a 2oC temperature change (remember, the lowest prediction now) look like? Well, this would mean we’d lose 30% of species presently on the planet (even higher in marine ecosystems.)  This is not through the direct increase in temperature, but a complex range of biogeographical factors such as shifts in food chains, disruption to breeding cycles and simply being unable to move to where they could survive, because of immobility or geographical barriers (such as deserts, oceans or mountain ranges). Well, OK, so a few things I’ve never seen before die out, big deal. Oh, by the way sea level would rise by 1 metre threatening most coastal, or low lying cities (New York, London, Paris etc) and countries (Holland, Bangladesh, to name a couple of the most densely populated countries in the world).

The 4oC change (mid-range prediction) is even more profound. At this point we look to lose 70 – 80% of all species on the planet (all corals become extinct – the sea becomes too warm). To her credit, she resisted ‘painting futures’ but rather looked back at the geological record. There have been a few times in the geologically recent (say 500,000 years) where temperatures have been 2oC higher than today. To find temperatures 4oC higher, you have to go back 4 million years. A time at which a good deal of life present today hadn’t even evolved. The phrase she used to describe a 4oC increase in temperature has stayed with me; “At this point we have a different world”.

Now Professor Parmesan was only talking about the ecology of the planet, not the social, economic and political implications for humankind, which of course are equally, if not more, profound.

She did however, briefly put some data up concerning present consumption, the most intriguing being the ‘Day in the Life of a German” (not sure why a German). This was a graph of energy usage across the day. It starts with them getting up and putting the kettle on, making breakfast, turning on the radio, all of which are small peaks. Then the central heating comes on and the graph spikes. Not all that unexpected, but there is a second even bigger spike in the afternoon. This is the point when they ate a bowl of strawberries. The energy consumption of growing ‘out of season’ fruit (and salad leaves) is huge. Heating a double glazed, insulated house is one thing; heating 1000 kms of polythene-covered greenhouses is something else.

Of course science has a huge role to play. Accurate and increasingly precise data has been collected, collated and analysed by the international scientific community. The minority of dissenting voices is so small now (even on the political right) that they can be ignored. Predictions are only that, but monitoring the change provides irrefutable data and allows us to evaluate our detrimental or remedial actions.

David Orr has argued that so bad has the crisis become that Universities should exclusively teach courses that can contribute directly to overcoming these huge global issues. Any thing else is irrelevant. It’s hard to disagree. Education is a key point, but individual responsibility isn’t far behind. I don’t mean just recycling paper, or turning lights off (although that’s useful) but rather in the scientific community we really need to look at what we’re using our training for? Why did we become scientists in the first place? I doubt if it was to help destroy the world. Perhaps each night on the bus home, we should ask ourselves “What have I done as part of my work today to help save the world?” With all our rational understanding of climate change and its implications for our children, I wonder what your answer would be.

Science and health informatics, what is the evidence on cost efficiency?

Apologies for the delayed posting, as I have been away at a health informatics conference in the USA (alas I didn’t win the mega-millions lottery as some may have begun to suspect).

The conference presented a number of interesting papers. An interesting theme (apart from the use of Prezi as an alternative to PowerPoint by the hippest and coolest presenters; something I still don’t quite get, as apart from zooming in and out it doesn’t seem to actually offer anything new, call me an old tusker, but there you go), was the massive expenditure on a variety of health-information projects across the USA and elsewhere in the economically developed world.

Fundamentally these projects are working towards establishing electronic health records (EHR), electronic medical records (EMR), and health information transfer/exchange (HIT/E) and interoperability.  The goals of these projects are certainly worthy, and usually include establishing national electronic health record/information exchange and transfer, reducing administrative workload and improving patient safety and health outcomes. On patient safety, there are plenty of horror stories of nursing and medical errors due to poor communication killing people under medical care (e.g. the Josie King case), and any systems that can improve this aspect of health would seem a good area to invest research dollars.

My question is though, is this multi-billion dollar (literally) investment in health care really the best use of our very limited health care and research budgets? The evidence for cost-efficiency is remarkably spares. There is good evidence that investment in health informatics can improve outcomes (typically in the order of 4-8%) but virtually none on how efficient this is compared to expenditure on other healthcare interventions (such as tackling chronic diabetes, heart disease, stroke, mental health issues or even obesity). As a segment of health expenditure it seems to represent a huge and expanding area where the benefits are very specifically only to the country involved. There is rarely some international work.

So this raises the age-old question, why does scientific enquiry still tend to focus on areas that are politically attractive, or result in outcomes that are not widely generalizable to other contexts. That is not to say this isn’t important work, but the ratio of expenditure to results in this field to date does seem highly questionable, compared with to other areas of scientific endeavour. Particularly when you consider the cost of this compared to that spent on fighting malaria. Food for thought.