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Thanks for spotting that.

There were also a couple of studies on catastrophizing by the research team of Jo Nijs. They have a background in pain research so that is probably why they had an interest in the concept. In two of their studies, patients had to estimate how much fatigue they would have following stair...

More info on catastrophizing and ME/CFS That first study on catastrophizing in 1995 was done by Rona Moss Morris. She also developed the cognitive and behavioural responses to symptoms questionnaire (CBRQ) which is the tool that has been used to most to measure catastrophizing in ME/CFS patients...

I think several forum members contributed to the Stanford project 'Rename Catastrophizing' from which I used several quotes. The project was posted in this thread: https://www.s4me.info/threads/rename-pain-catastrophizing-stanford-study-survey.15337/

Would be interesting to hear other thoughts about this: are there parts in the text that you disagree with or that we overlooked? There is some info that did not easily fit into the blog (otherwise it would be too long) and that I hope to post here in this thread in the coming days.

Twitter summary here: 1) New blog post about catastrophizing and why this term risks blaming patients by mislabeling their symptoms as exaggerated negative thoughts. 2) Catastrophizing has been a popular topic because it is one of the most consistent psychological predictors of adverse pain...

Catastrophizing, time to ditch the term? Catastrophizing, a cognitive distortion that amplifies the perceived threat of symptoms, has been at the center of cognitive-behavioral models of pain and fatigue. In recent years, however, researchers argued that the concept has been misapplied and that...

Yes I suspect the data refutes rather than validates previous finding on 2-day CPET. Haven't been able to analyse everything but it looks like the authors did two types of significance tests: They looked at changes over time (from day 1 to day 2) in each group separately and calculated an...

I think the problem might be that people would interpret PEM very differently.

So there must be quite a few who reported that they returned to their normal activities at month 1-3, but not at 12 months.

Someone also pointed out to me that the effect sizes reported for VO2 (ml/min) are sometimes quite different than for VO2, (ml/kg-1 min-1). For example In Table 3, for the matched pairs at the anaerobic threshold, ME/CFS patients had an effect size of 0.16 for VO2 (ml/min) but an effect size of...

The authors wrote: I see that Heart Rate (HR) is included as a variable in the data, but no the percentage of age-predicted maximum heart rate. Did anyone find something about this in the paper or data, or how they might have calculated this?

I've tried to use JASP, the statistical program Keller et al. used and it gave the same result as the method explained in the quote above. If I calculate the mean and std I get the same results as in the paper so I don't think I've made an error in data extraction. Anyone who can explain the...

Interesting graphs @forestglip, the red ME/CFS dots seem scattered around the blue HC ones without a clear pattern. Has anyone been able to replicate their calculation of effect sizes? For example for VO2 (ml.kg−1.min−1) at maximal exercise, they report mean values for the ME/CFS group of 20.8...

Already had a quick peak and it seems that there is quite a lot of overlap between the two groups if you plot the difference between day 1 an day 2. Here's for example the workload at the ventilatory threshold for the total sample, which in the past showed the biggest differences. (EDIT: The...

Yes you're right these aren't that small. I had misread and assumed that most statistically 'significant' findings would have very small effect sizes < 0.2 SD which doesn't seem the case. Apologies for the confusion (will EDIT my first post above).

For blood traits, these are the ones that had a Cohen's D > 0.2 for both males and females:

Aha, thanks!

No expert here, but I'm afraid these are mainly small differences inflated because of the enormous sample sizes. For blood traits, for example they report data of 1,455 patients and 131,303 controls. In such context, statistical significance does not mean much as even minor differences that are...

Just noticed that this paper did control for fatigue in a separate analysis (table 4, ANCOVA adjusted for fatigue, age and illness duration). As expected, the effect size dropped from 0.41 to 0.07 and the difference in all-or-nothing behavior between groups was no longer significant.