Response Shift After CBT Targeting Severe Fatigue: Explorative Analysis of Three Randomized Controlled Trials, 2022, Müller, Knoop et al

"Response shift through reprioritization was indicated for the items “Physically, I feel exhausted” (CFS) and “I tire easily” (cancer, diabetes), which became less vs. more important to the measurement of fatigue, respectively."

For not just CFS but cancer and diabetes. Given all need to be in tune with their body's signals, and surely even Knoop must acknowledge it is an important sign for diabetes and cancer as a health flag, how did they get ethical approval for a therapy targeting people ignoring and switching off paying attention to this signal? Is it not just a fishing expedition?

I found it refreshing to have a few details said outright:

"CBT is based on the cognitive-behavioral model of fatigue, which states that disease and its treatment initially precipitate fatigue, while cognitive and/or behavioral variables perpetuate fatigue in the long-term [6, 8, 9]. The fatigue-perpetuating variables are largely transdiagnostic, that is, explain fatigue across various chronic conditions [10]."

I guess from this you assume that the 'trigger' e.g. 'initial virus they believe goes away' is what is counted as 'precipitate' for CFS. Importantly if this is now lumping with 'various chronic conditions' is this actually a recategorisation/redefinition of CF and CFS being 'the same thing'? Is this about where they draw these boundaries? A relevant change, because I remember as the new guidelines was coming out certain individuals in the Times comments saying 'but whatabout all those without PEM who the GP has to tell it's not ME/CFS after all and we have nothing for you' as the next fallacy to push. I can't help but think watching that attitude of many clinics with just saying 'yeah we just treat CFS' that's the sophist attitude of 'well we aren't going to change'.

"Treatment effectiveness is commonly evaluated through assessing changes in patient’s self-reported fatigue. A reduction in self-reported fatigue from pre- to post-treatment is taken to indicate a positive intervention effect: a reduction in fatigue severity. However, as CBT also directly targets patients’ cognitions about fatigue, it may also induce a change in the meaning that patients attach to their fatigue evaluation, which is also known as response shift."

SO to get the line "based on the cognitive-behavioral model of fatigue" with further detail of what they mean within that phrase, and what they mean by their CBT I'd hope that helps in unbundling and making more overt what the 'biopsychosocial' really is. Instead of the holistic bla.

And that the only 'proof' this presumption/assertion is true is based on testing something else EDIT* (ie 'is fatigue really important to you anyway?) in a very flawed but specific methodology-wise way.

It's peak Popper's theorem really, because long covid research has shown there are changes - and they are stretching credulity trying to say these are explained by emotional states when they had the virus. Their whole argument relies on how badly their own subject area has done on research for decades to make their claims untestable.

So you have to assume that the BPS model is believed because it represents an unfortunate instinctive thought pattern of some people who hold it up ie I believe it is nothing more than a bias or bigotry in itself and will be useful in defining historically 'that' - otherwise it would be unfeasible that noone checks before they claim 'it isn't anything else'.

And yes, it always frustrates me they rarely define it as 'their CBT' or 'this CBT' but often tend to play into the concept there is one CBT. As if all CBT is all based on such a model. And whatever you throw at people will work. To me that's about as specific as saying 'weekly injections'.
 
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And yes, it always frustrates me they rarely define it as 'their CBT' or 'this CBT' but often tend to play into the concept there is one CBT. As if all CBT is all based on such a model. And whatever you throw at people will work. To me that's about as specific as saying 'weekly injections'.

I had a course of CBT with an interested and motivated newly qualified Clinical Psychologist, based on the idea that I repeatedly over estimated how much I could do and my struggle with pacing was because I struggled to accept how limiting my PEM threshold actually is. In the short term I found it a positive experience that helped me accept my limited reliable activity levels and reduced the amount of PEM experienced.

This is CBT but it’s content is the complete opposite to PACE type CBT.

In the longer term, after my sessions with the Clinical Psychologist had ended, I did find myself mistaking the reduction of PEM for an improvement in my underlying health and tried to continue increasing activity levels which triggered, or at least which was associated with, a subsequent relapse, new symptoms and much restricted activity levels.
 
People give different answers when they're being observed. It's as simple as that. And if you're observed over a longer period, that will have an effect.

It's just training people to respond more positively.

The underlying problem is still the same.
I seem to remember a paper talking about the SF36 where they were even getting different answers depending on whether people filled them out at home or in a a medical setting as part of an appointment.
 
Wouldn't it be a whole lot easier to use CBT, on the test group, and objectively monitor whether activity levels changed (from pre-intervention/baseline) i.e. using actimetry (FitBit type devices)? Having established that the intervention didn't work then why not publish that and suggest that it's a waste of time?
OK, if you wish to be academic about the whole thing, then explain that unblinded/inadequately blinded studies are open to bias (if measured subjectively - questionnaires).

Even just data from a smartphone may be enough. I keep mine in my pocket all day and it records steps taken and when, speeds walked and stairs climbed. I did see one ML project where they published data sets (I think from phones) and people were developing models to detect sitting and standing etc.

I think looking at actimetry will be really important and its really easy these days,
 
Even just data from a smartphone may be enough. I keep mine in my pocket all day and it records steps taken and when, speeds walked and stairs climbed. I did see one ML project where they published data sets (I think from phones) and people were developing models to detect sitting and standing etc.

I think looking at actimetry will be really important and its really easy these days,

Your post sums up that failure to collect objective data shouldn't be tolerated - this crap shouldn't be funded by your government.
 
Even just data from a smartphone may be enough. I keep mine in my pocket all day and it records steps taken and when, speeds walked and stairs climbed. I did see one ML project where they published data sets (I think from phones) and people were developing models to detect sitting and standing etc.

I think looking at actimetry will be really important and its really easy these days,

Probably shouldn't tag you @Simon M but yea with phone data of the quality you describe, it might be a way to select a population to study - maybe even filter/cleanse the data from a GWAS study.

Guess it would add substantially to the cost - so you'd need a bigger grant to use this type of [mobile phone] data.

What's a "ML project"?
 
What's a "ML project"?

Sorry a machine learning project. People publish data sets with challenges associated with them to build models that predict results from the raw data.

Probably shouldn't tag you @Simon M but yea with phone data of the quality you describe, it might be a way to select a population to study - maybe even filter/cleanse the data from a GWAS study.

Guess it would add substantially to the cost - so you'd need a bigger grant to use this type of [mobile phone] data.

I was looking at my phone this morning and I can export data from the health app which seems to cover activity in chunks of between 5 mins and longer (I assume where activity is less) - that is for walking. So I think there is potential to collect and analyse data. I suspect more detailed info would be harder to get -maybe possible on android devices but apple may have more controls
 
Probably shouldn't tag you @Simon M but yea with phone data of the quality you describe, it might be a way to select a population to study - maybe even filter/cleanse the data from a GWAS study.

Guess it would add substantially to the cost - so you'd need a bigger grant to use this type of [mobile phone] data.

What's a "ML project"?
We wouldn’t have either budget or ethical approval for this.

But other researchers could apply to recruit from Decode ME participants who have consented to be approached about joining further research studies.

research is within also have the genetic data on these participants. That’s one of the beauties strengths of Decode ME – the creation of a large cohort which can then be approached about taking part in future studies, adding new data to the genetic data.
 
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