Webinar: HE 13: Epidemiological sleight of hand and Medically Unexplained Symptoms, David Tuller, Tues 18th Oct, 2022

Andy

Andy

Retired committee member
Join us on the 18th of October when Dr David Tuller, Senior Fellow in Public Health and Journalism at UC Berkeley’s Center for Global Public Health, will speak with us about the trope of ‘medically unexplained symptoms’ (MUS) and the bolstering of research findings to support the tenuous inferences that surround them. The talk will touch on a range of case studies, including ME/CFS, Long COVID, and POTS.

Register, https://www.eventbrite.com/e/he-13-...lly-unexplained-symptoms-tickets-432926684367
 
I've watched the first 30 minutes and I'm very glad I did. At last the random pieces relating to the variety of MUS terminology, problematic research, poor study design etc. have fallen into place like the final stages a jigsaw puzzle when you eventually start to see the whole picture. Thanks @dave30th for explaining it clearly with examples. I'm looking forward to the next bit.
 
Trial By Error: My Talk at Cambridge Last October on “Epidemiological Sleight-of-Hand: The Troubling Case of ‘Medically Unexplained Symptoms'”

"I gave a talk at Cambridge University last October called “Epidemiological Sleight-of-Hand: The Troubling Case of ‘Medically Unexplained Symptoms.'” More accurately, I gave the same talk on two successive days—October 18th and 19th–because of video malfunctions on the first day. I thought I’d written a post about it, but when I searched recently, I couldn’t find one. So here it is, belatedly."

https://virology.ws/2023/09/17/trial-by-error-my-talk-at-cambridge-last-october/
 
Thanks for posting.

David Tuller:

"Whatever these conditions are called, it has been my observation that investigators who focus on psycho-behavioral treatments for them routinely adopt highly problematic and sometimes even fraudulent practices in their clinical trials and epidemiological research.

"My talk at Cambridge was an effort to categorize some of these practices and provide key examples of each. The flaws I discuss generally lead to results that distort and misrepresent the true nature of what is happening with patients."

Would love to hear more, but unfortunately not able to watch/ listen to videos or handle the automatically generated captions or transcript.

Anyone feels up to provide a transcript that's better accessible?
 
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There will be an AI tool available now that can make a transcript of the video. I’m not sure which one.
 
dave30th said:
Is this done easily on youtube?
Click to expand...

You could ask the channel holder if they are able to get a transcript from the YouTube back end (channel tools) that they could share.

Anyone here who’s on a desktop computer (I’m not, mine is out of action) could try the following method, but I think you’d end up with a transcript that is broken up into many parts with time codes for each part, as seen in the video.



I’ve gone and used an app that uses OpenAI’s Whisper Speech-to-text API. I’ll post that in a reply to the above user.
 
MSEsperanza said:
Thanks for posting.

David Tuller:

"Whatever these conditions are called, it has been my observation that investigators who focus on psycho-behavioral treatments for them routinely adopt highly problematic and sometimes even fraudulent practices in their clinical trials and epidemiological research.

"My talk at Cambridge was an effort to categorize some of these practices and provide key examples of each. The flaws I discuss generally lead to results that distort and misrepresent the true nature of what is happening with patients."

Would love to hear more, but unfortunately not able to watch/ listen to videos or handle the automatically generated captions or transcript.

Anyone feels up to provide a transcript that's better accessible?
Click to expand...

Hello. I’ve given this a go using some free AI tools publically available.

The resulting transcript isn’t perfect but it’s pretty accurate. There are some parts with large unbroken and unpunctuated blocks of text unfortunately.

The speech-to-text tool I used can recognise pauses and replicate them in the text as commas, but given the way David speaks in the video it has transcribed the audio as being without pauses in some places.

So some sections are harder to read because of the lack of punctuation and very long run-on sentences.

There will be some errors in the text, I’ve not reviewed it all and I don’t have time to correct it.

Take a look right at the end to see one error that I’ve corrected in brackets to see what I mean.

Let me know how you get on with this.
 

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