Block 4 · Debates & Research
Individual decompression, risk factors, data collections — where are the hottest debates right now?
Introduction
Set your computer, do a rough plan, and drop in — great.
But behind all of that sits a lot of science:
the decompression models we dive with were developed decades ago, and have been modified again and again ever since.
New findings appear, new questions arise — and sometimes a new hype rolls through the tech community
and occasionally reaches recreational diving too… and then takes a long time to fade out again.
Where do you find relevant information today, how do you evaluate it,
and what consequences do you want to draw for your own diving?
In this block we can’t cover every debate — but we’ll show a few representative examples
and how to keep learning on your own.
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Log in nowOverview: how to read research in a useful way
Despite decades of work, our knowledge about decompression is still limited. Why?
Partly because, with modern models, DCS is relatively rare.
The models were validated empirically — and that “knowledge of acceptable limits” came at a cost:
people experienced symptoms, and the lessons learned from that are part of what makes diving as safe as it is today.
Some additional, more recent studies have also provided insights into riskier or less risky profiles.
But research hits a hard boundary where you would deliberately expose people to an unacceptable risk.
So today, research often looks for many other measurable signals after a dive,
rather than focusing only on the endpoint “DCS”.
And because decompression research is niche, studies often involve very few participants —
so you can never be fully sure an effect isn’t just noise.
If you keep that in mind, it becomes clear why loud claims like
“Anyone who got DCS was definitely dehydrated / definitely had a PFO / definitely did the second dive deeper than the first…”
usually cannot be properly supported.
How do you tell whether something is solid or not?
One warning sign is a classic:
Loud, simple truths are almost always wrong.
There are good reasons why scientific results are often phrased carefully:
you found another clue, another puzzle piece — not “the big answer”.
If you want to learn more, look for sources that write soberly and cautiously — and that can support their claims. There are some blogs that do that well. You can read studies yourself — we explain how in a blog post. And by now, AI can be a strong research tool — if you use it properly.
Blog post: Reading studies
The Theoretical Diver
dekoblog.ch
InDepth: A Technical & Professional Diving Magazine
Individual decompression
What if you knew how susceptible you personally are to DCS —
and could simply adjust the profile to match?
It’s a beautiful idea, and it’s exactly what an entire line of research is trying to move toward.
What can we measure during the dive and after the dive — and could those measurements help us learn what “best decompression”
might look like on an individual level?
What could “individual decompression” mean?
Alessandro Marroni from DAN Europe (and others) has a big dream:
collect data on a diver’s physiological responses already during the dive —
and react immediately if decompression is starting to become critical.
What would have sounded completely utopian decades ago could become reality in the coming years.
But what would it take?
First, you’d need a way to monitor the body underwater.
Progress in this area is rapid: smartwatches that work underwater already exist,
and bubble detection can also be done in-water in some setups.
The second challenge is interpretation:
what do the measurements actually mean?
Which values are real indicators that DCS is developing — or that risk is sharply increasing —
and which are just normal, non-dangerous physiological responses to a dive?
There are plausible hypotheses — but right now, they are not strong enough to turn into clear, reliable recommendations
based on specific metrics.
The biggest missing piece is: enough data to demonstrate relationships between particular factors and DCS.
Below we take a quick look at individual metrics that might, in the future, feed into “individual decompression” concepts.
General risk factors are discussed in the next section.
Risk factors
As soon as people talk about “individual decompression”, the question of personal risk factors appears almost inevitably:
age, sex, body type, fitness, sleep, hydration, alcohol — the list is long, familiar, and intuitively plausible.
It’s tempting to assume that decompression could be improved significantly if we simply took these factors into account consistently.
But when you look closer, the picture becomes much blurrier.
For many factors there are hints, but rarely robust quantitative relationships.
BMI is often mentioned, but says little about body fat percentage or physiologically relevant characteristics.
Fitness is generally considered protective — without a clear definition of which type of fitness matters,
or how it translates into a measurable effect.
The evidence remains similarly vague for smoking, alcohol, or sleep deprivation:
the physiological mechanisms are plausible, but empirical evidence is limited and often context-dependent.
Even with nitrox — often perceived as “safer” — the core effect is trivially explained:
less inert gas uptake. That does not replace a nuanced view of overall decompression stress.
Organizations like DAN have been pointing out for years that individual risk factors are real,
but cannot be quantified reliably.
That creates a tension between the desire for personalized decompression and what we actually know.
The question is therefore less whether individual factors play a role —
and more how sensibly they can currently be translated into concrete decisions —
and where that translation inevitably becomes speculative.
In the end, only a few factors can be considered clearly relevant: age, cold during the decompression phase, and exertion during and after the dive. A PFO also increases the risk for certain forms of DCS. But because DCS is overall rare, it’s hard to say whether the risk is “twice as likely” or “three times as likely” — the absolute risk remains low.
What we know about DCS risk factors
The “perfect” gradient factors
The scientific debate on gradient factors is somewhat asymmetric.
For the upper gradient factor, there is now a relative consensus:
lower GF High values limit maximum supersaturation in shallow depths
and increase the safety margin toward the end of the ascent —
at the cost of longer decompression.
The question of a “better” or “worse” GF High is therefore less theoretical:
lower is safer for decompression.
The decision ultimately depends on how much extra time you are willing to invest,
and what you consider an acceptable residual risk.
The discussion is much more open around the lower gradient factor.
GF Low primarily influences the depth of the first stop and the distribution of decompression time.
Very low values — which lead to early deep stops — are viewed much more critically today than a few years ago.
There is no stable scientific consensus here;
evaluation depends strongly on profile type, gas, exposure duration,
and the underlying physiological assumptions.
Current practice tends to keep GF Low not far below GF High —
but we are still far from a true consensus.
On top of that, much research comes from the military —
and they rarely dive using Bühlmann + gradient factors.
That means there are very few studies with few participants
that actually examine profiles expressed in gradient factors.
Accordingly, solid conclusions are still thin.
Supporting research: data collections
We’ve seen how hard it is to get meaningful data.
Signals of decompression stress are collected in small studies;
DCS cases are analyzed, but remain rare.
The US Navy occasionally runs relevant studies — but those are guided by military interests
and often translate only partially to recreational diving.
That’s why data collections and incident reports that never show up in insurance statistics matter so much.
If we can analyze many real-world dive profiles —
and capture even mild symptoms that resolve again —
we may get insights that actually become statistically meaningful.
If you want to help make real-world dive data available for analysis,
you can upload it via a DAN platform: the Diver Safety Guardian.
Besides the profile, it asks for a few additional data points —
and you receive an evaluation of your own dive.
Participating means supporting relevant research without creating much extra work for yourself.
Diver Safety Guardian
Why is it good to have more data? So that, in the second part of this quiz, you can find the best possible information. Test again how well you can research.