A community for Scientific Skepticism:
Scientific skepticism or rational skepticism, sometimes referred to as skeptical inquiry, is a position in which one questions the veracity of claims lacking empirical evidence.
Do not confuse this with General Skepticism, Philosophical Skepticism, or Denialism.
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"A wise man proportions his belief to the evidence." -David Hume
A better breakdown https://www.advocate.com/health/hilary-cass-nhs-report-debunked#toggle-gdpr
And edited this one too https://www.tandfonline.com/doi/full/10.1080/26895269.2024.2328249
Ms Reed is not an objective source. Nor does it appear she has much experience with systematic reviews. Indeed she repeats many of the "myths" such as the one about 98% of studies being thrown out.
"A closer inspection of the reviews released alongside the Cass report reveals that 101 out of 103 studies on gender-affirming care were dismissed for not being of "sufficiently high quality," "
That is a lie.
Lastly, it seemingly endorses restrictions on transgender people under the age of 25, stating that they should not be allowed to progress into adult care clinics.
This is another lie from Ms Reed. I am beginning to think this "debunking" article you've shared is actually the original source of most of the myths being peddled on social media.
It's not a lie, they were mostly dismissed even according to your own article, they were dismissed and synthesized into one conclusion. That is still dismissal.
101 of 103 studies were not dismissed. All systematic reviews classify their source studies based on the quality of the work. Of the 103, two were classed as high quality, 58 as moderate quality and the remaining 43 as low quality. For synthesis, only high and moderate quality studies were drawn on. That's more than half, not 2%.
So yes, Erin is lying.
You can't say she's lying until we do a systemic review of why the Cass study dismissed everything but 2 studies for the numbers it used to reach its conclusion. You can't say she's lying without that review no more than I can support Erin by reading each study that was dismissed. What I can tell you is that dismissing that many studies is not normal scientific analysis. It reeks of bias.
You can't say she's lying until we do a systemic review of why the Cass study dismissed everything but 2 studies
This is the lie. They didn't dismiss all but two studies, they actually included 60. More than half of the 103 studies identified for the review.
So yes, Erin, and now yourself, are peddling a lie.
What I can tell you is that dismissing that many studies is not normal scientific analysis.
It's key part of synthesising multiple sources into a meta-analysis. Including poor quality studies dilutes the quality of the overall analysis.
It reeks of bias.
By design, it's biased towards higher quality research.
Synthesis is a paragraph summary inclusion ONLY, it means they didn't use data from the study, it is dismissal. I'm done arguing that with you.
They have absolutely used the data from those 60 studies. You can read where they say explicitly that in the report if you cared to.
You are utterly mistaken and firm on your conviction, these are not the qualities of skepticism.
"Don't seek refuge in the false security of concensus"
That's not what synthesis means. I've written synthesis reports before and the data you include from those reports once you have dismissed them as inaccurate, it is an entirely selective process of whatever you want to include from them. We even have a phrase for it in law, Summarily dismissed.
And of the 103 reviewed they included data from 60. It is a lie to say they "dismissed all but two."
Legalese is irrelevant. A systematic review of scientific literature is a different beast to "writing a few synthesis reports".
So you don't know what you are talking about. Gotcha.
Synthesis reports in a scientific study when presenting data, are the parts of the report where you explain why you are dismissing data, so in this case ~98% of the data or studies. So what you just said is ~98% of the data was included in the synthesis report. that's not inclusion of the data. That's selective inclusion to support a conclusion. A normal scientific study can't dismiss 98% of available data. That reveals bias.
You can read the reviews for yourself
https://adc.bmj.com/content/early/2024/04/09/archdischild-2023-326669
Let me know where you find the bit where they dismiss 101 out of 103 papers.
Hint, they didn't. It is lying to say they dismissed 98% of the studies they looked at.
Read it. Their only inclusion in the report is to half explain why the were discluded, exactly what I said. Most of the dismissals are unscientific, not supported by a statistical analysis of why it was discluded. Data doesn't become unreliable just because it is incomplete.
That report is absolutely rife with white washing and selection bias, I'd expect a scientific review of trans literature and studies to be a book at this point not 32 pages dismissing 98% of the data. It's frankly insulting to anyone that's read or written any number of scientific studies.
They did not dismiss 98% of the data.
Putting 98% of the relevant available data in a supplementary table like 4 is not including the data.
Supplementary Table 4 (from the first review) is a list of each of the 53 studies included in the review and how they were scored based on the Newcastle-Ottawa scale.
The "data" is in supplementary tables 3, 5, 6 and 7. Only studies that were scored as low quality were excluded from the synthesis.
"They dismissed 98% of data" is a lie.
No it's not. None of the dismissals are statistically/ scientifically supported, and the data they present is blurbed and incompletely presented in a way that isn't inclusive of what those studies actually say.
Nothing was dismissed at all (and "statistics" has nothing to do with it so curious to mention it).
Studies were scored for quality on the well established Newcastle-Ottawa Score. High and Moderate quality studies were included in the synthesis. Low quality studies were not, but their outcomes are still reported.
Outcomes from each study were included in tables 3, 5, 6 and 7.
'They dismissed 98% of the data" remains a lie.
You can't remove a study from a scientific paper without having statistical analysis to back it up. Each of those removed studies all had a statistical analysis of how confident they remained in their data even with the gaps. Because there aren't completed 100% studies in science it just doesn't happen so you use the data you have and test it for a confidence value you obtain using statistics. And the idea that some trans people don't make it to the completion of a study due to personal reasons or even suicide isn't that rare. Not using 98% of the data because of that would be stupid.
You can't remove a study from your a scientific paper without having statistical analysis to back it up.
You can of course. Statistics are not required to explain why a self selective Facebook poll is low quality while a multi centre 5 year study with followup and compartor is of a much higher quality.
Each of those removed studies all had statistical analysises of how confident they remained in their data even with the gaps.
Studies are also scored low on quality if, for example, they don't control for important sociodemographic confounders. Study that do control these, will have more reliable results.
You can read how the scoring works in supplementary material 1.
Not using 98% of the data because of that would be stupid.
"They dismissed 98% of the data" remains a lie. Repeating it doesn't change anything.
"You can of course. Statistics are not required to explain why a self selective Facebook poll is low quality while a multi centre 5 year study with followup and compartor is of a much higher quality".
That's wrong when you are trying to be scientifically correct. A science paper without that math isn't science my dude. And comparing trans healthcare data to Facebook polls is ridiculous
It's remarkably common in systematic reviews, a feature even. You give the impression that this is a new or foreign concept to yourself and are just encountering these ideas for the first time.
Search on pubmed or the bmj or the Cochrane library for other systematic reviews using the Newcastle-Ottawa score. You'll trip over them.
And comparing trans healthcare data to Facebook polls is ridiculous
One of the studies reviewed recruited patients over Facebook and polled them.
"They dismissed 98% of the data" remains a lie.
Again I've written these reports. It is absolutely not common practice to disclude data without scientific reason and analysis. It is explicitly taught not to do it that way in college. And it is not scientific to do that without a statistical threshold and confidence analysis of your reasoning.
Again I've written these reports.
I am forced to strongly doubt this given your whole misunderstanding of the basic concepts on assessing methodical quality..
Certainly, you've never authored a systematic review for a reputable medical journal.
But don't take my word for it...
It is absolutely not common practice to disclude data without scientific reason and analysis.
You mean such as using a method like the Newcastle-Ottawa score to assess data quality?
It is explicitly taught not to do it that way in college.
If your college course covered systematic reviews and didn't include a review of study assessment methods, ask for a refund.
And is not scientific to do that without a statistical threshold
Statistics are not required to assess that a study without a comparator is weaker than one with.
"They dismissed 98% of data" remains a lie.
The Newcastle method is not seen as a scientific basis for dismissal on its own.
98% of the data was dismissed in the synthesis and was not used to reach the conclusion that there wasn't enough scientific evidence to support transition when 98% of the science says that is wrong.
And every scientific paper is expected to be comprehensive on its subject matter and/or thesis.
It's not used for "dismissal" it's used to score studies on their likelihood of bias. Studies without appropriate controls for example are more susceptible to bias than those with.
98% of the data was dismissed in the synthesis
Demonstrably false, only low quality studies were excluded from the synthesis which account for less than half of the 103 reviewed. A lie is a lie no matter how often repeated.
and were not used in the conclusion that there wasn't enough scientific evidence to support transition when 98% of the science says that is wrong.
That's not what the conclusions say, for example:
Synthesis of moderate-quality and high-quality studies showed consistent evidence demonstrating efficacy for suppressing puberty
And
Evidence from mainly pre–post studies with 12-month follow-up showed improvements in psychological outcomes
"They dismissed 98% of data" remains a lie.