"Bias in research: the rule rather than the exception?" referenced piece by 2 Elsevier editor

[Dolphin]

September 17 article. Just a general article, no reference to ME/CFS specifically, although parts could certainly be relevant.

Shorter than most papers (1633 words which includes counting reference numbers). I didn't notice any math/stat or biological terms, although I suppose a piece like this could be perhaps a little abstract for the odd person who hasn't read anything about the area.

Dr Kevin Mullane and Dr Mike Williams, two of the editors of the Elsevier journal, Biochemical Pharmacology, discuss some of the causes and prevalence of bias in the fields of biomedical research - and the implications for the wider research community.

http://editorsupdate.elsevier.com/i...-research-the-rule-rather-than-the-exception/

 

[Esther12]

Bias in research, where prejudice or selectivity introduces a deviation in outcome beyond chance, is a growing problem, probably amplified by:

• the competitive aspects of the profession with difficulties in obtaining funding;
• pressures for maintaining laboratories and staff;
• the desire for career advancement (‘first to publish’ and ‘publish or perish’); and, more recently,
• the monetization of science for personal gain.

As cause of bias, I think that the animosity around CFS (much of it prompted by earlier bias!) is likely to be a factor with research in this area.

Imagine if the PACE trial had released the original recovery criteria, where any increase in 'recovery' rates for CBT and GET may not have reached statistical significance. People would have been rightfully furious. That these interventions were being confidently promoted to patients long before there was a sufficient evidence base makes it much harder for those responsible to now release honestly presented data showing how little use they are.

 

[Simon]

Thanks, Dolphin
Some highlights for my benefit:

...the adoption of certain practices can blur the distinction between valid research and distortion – between "sloppy science", "misrepresentation", and outright fraud [1].

...Bias in research, where prejudice or selectivity introduces a deviation in outcome beyond chance

Especially liked this from Sydney Brenner, one of the founders of molecular biology, who said

much research has become "low input, high throughput, no output science" [4].

2. Bias by design reflects critical features of experimental planning ranging from the design of an experiment to support rather than refute a hypothesis; lack of consideration of the null hypothesis

...Another important consideration in experimental design is the control of potentially confounding factors that can influence the experimental outcome indirectly.

I think this fits more in the sloppy than the deliberate, and much of it is probably subconcious - but still bad science.

In the stats course I did, the (psychology) prof was very critical even of using the null hypothesis: for him what you needed to show that your idea wasn't 'better than nothing' but better than some credible alternative. And I think that lack of searching for plausible alternative explanations is a big problem in CFS research. Just one example is lazy interpretation of 'negative personality' findings, which ignore the likely effect of illness on the way people answer questions (eg my life has no meaning) - when the questionnaires involved were developed in healthy populations.

Finally, I loved this quote:

3. Bias by misrepresentation. Researchers are an inherently optimistic group – the 'glass half full' is more likely brimming with champagne than tap water.

 

[alex3619]

Esther12 , is there call for a short paper using the early PACE criteria, and giving an adjusted outcome? Can this be done without the raw data? I suspect not.