All right,
welcome everyone to the AOMT hands-on,
hands-off podcast.
My name is Lina McDaniel.
I'm a physical therapist.
I'm a fellow of AOMT and I
am just thrilled to have
you all today join us.
I think it's gonna be a great episode.
We are so fortunate today to
have Dr. Kasper Nimm from Denmark.
He's a chiropractor and
senior researcher at the
Spine Center of Southern Denmark.
He's an assistant professor
at the University of Southern Denmark,
where he completed his PhD
in twenty twenty one.
Welcome, Casper.
Thank you.
Yeah.
So just to kick off the
episode a little bit,
we do want to focus on one
of your recent publications.
But before we get into that,
can you just introduce
yourself a little bit to
our audience and tell them
briefly about your
background as a clinician, a chiropractor,
and then as a researcher?
And what are your
professional roles right now?
Yes, absolutely.
That's not a problem.
And thank you for having me.
I really appreciate the invitation.
It's going to be a lot of fun.
So you said my clinical background,
which is actually an interesting story.
So I'm educated from the
University of Southern Denmark,
which is an unorthodox chiro program,
I would say,
because it's based one
hundred percent in a medical faculty.
So we study alongside medical students,
which also means that some of the
raw philosophy of the
chiropractic profession
that it has in the background, right?
We don't really have that in
there and we're really well
integrated into the healthcare system.
So clinically,
I worked almost my entire
career at a hospital diagnosing patients.
So I actually don't have
that much experience with
hands-on treatment.
And it's interesting because
a lot of my research is
centered around that.
So I always get the
discredit from the
clinicians that I don't
understand this because I'm
not doing it in real life.
I don't see all the
potential and stuff like that.
But I'm always flipping around saying,
well,
I always I also don't have that bias,
you know, that I that I see it works.
I can be completely, you know,
objective and just, you know,
stay within the limits of the data.
And I do think there's some
there's some benefits to that,
although I do appreciate
clinician researchers as well.
But
mostly what I'm doing now
I'm still doing a lot of
manual therapy research uh
different related projects
but to be honest it's all
my hobby projects at the
moment all of my funded
research is mostly related
to more healthcare
utilization and you know
long-term patient courses
and mapping those and more
into the world of epidemiology I'm
slowly evolving into that.
But I still love doing the
manual therapy work,
and it's a lot of fun.
And sometimes, you know,
good stuff happens,
like the paper we're coming into now,
right?
A completely unfunded
project we just all did in
our spare time.
It was a fun and frustrating process,
to say the least.
Wow, that's incredible.
And it's amazing to hear
that lead off into this
study because of what a
massive study was and just
thinking about all the
aspects of it and how many
people were involved.
So, well, great.
Well, let's jump into it.
I want to hear more about
your perspective on it and
kind of the background behind it.
The main publication that we
do want to highlight and
talk about today is a recent publication,
a twenty twenty five
article in title the
effectiveness of spinal
manipulative therapy and
treating spinal pain does
not depend on the application procedures,
a systematic review and
network meta analysis.
So this paper that just came out,
just quite a lot to it and
really rich with
opportunity to kind of pull
some findings from this.
And we'd love to hear about it.
Can you briefly describe the study,
the design and kind of the
underpinnings of this study for us?
Yeah, absolutely.
And if I'm allowed to,
I'll go a little bit back in time.
because ever since I was a
student and I graduated eight years ago,
so it's, I don't want to admit it,
but it's a few years ago now,
but I was always very
critical of this notion
that we were taught that
you could do spinal
palpation and then feel, you know,
wherever the dysfunction was,
and then you could hit, you know,
exactly at that segment.
And that would help, you know,
basically cure people sometimes.
Right.
And it's, um,
And I was really challenged
then when I got into clinical practice,
because I have been in
chiropractic practice for a little bit.
So I thought that was quite difficult.
So when I led into my PhD,
which was actually
to be honest, when I was young,
back in twenty sixteen, seventeen,
we wanted to predict
responses to to spinal repulation.
I'm just going to call it SMT.
We wanted to predict
responses of SMT using pain
sensitivity and spinal
stiffness as like
biomarkers on where to get the treatment.
And what we really noticed
when we looked at the data
was that it was like
the participants in our
study got the exact same treatment.
They completely changed
identical of each other, those two groups,
as in completely identical,
as it was the complete same
treatment we gave them.
And that really opened up
the door of looking more into that.
So we did the first original
review as part of my PhD
back in twenty twenty,
which was published in Scientific Reports,
where we looked at the
target site and didn't see
any differences.
And when we published that, we had a
like a huge critique from a
lot of clinicians,
both physios and chiros.
Everyone kind of hated me a little bit,
you know, at least in public.
Private, I got a lot of positive feedback,
but in public,
everyone disliked the study.
So some of the critique
points that we got there,
we did in another JOSPT
review that we published in
in twenty twenty three,
where we looked at it,
we removed some of the
heterogeneity from the
original study and then
focused a little bit more
on a certain population and
found the exact same thing again.
But we were still only
looking at one aspect of it,
which was the target selection.
So over the last couple of years,
this network meta-analysis
approach really came up and
there has been a lot of
network meta-analysis.
I think like almost...
I think in it was something
from to there was almost
four hundred network
meta-analysis published on MSK research.
So it exploded all of a
sudden and it does allow
mathematically that you can
actually compare two
different interventions
that are not being directly
compared within the same study.
So that's the indirect evidence.
There's a whole bunch of
statistics that goes behind that,
which I won't get into too
much here today.
But this did allow us to
actually classify all of
the different SMTs that
were delivered in studies
and then compare those
classifications to each other,
which meant that we could
look at other things now
than just target selection.
We could also look at the thrust specifics,
and we could even look at
the region where it was provided.
And those were the three
things we went with.
So we took, we basically, we wanted to,
yeah, sorry.
Casper, I think all that's great.
I just want to interrupt you
briefly because in reading this study,
I'm familiar with some of
these terms that you're using,
but just for our listeners
who may be less familiar,
could you briefly define SMT for us?
And then can you briefly
define the target?
What do you mean when you say target?
Yes, of course.
Sorry.
Yeah, no, SMT, we define,
I don't think there's a
quite clear definition,
but basically it's the
cracking manual therapy.
So it's the manual therapy
that has a high thrust and
a low amplitude.
sorry, high velocity, low amplitude.
And it often results in a cracking sound.
So we actually, in this study,
excluded like other types
of mobilization.
If you follow the Maitland criteria,
maybe the listeners are
more familiar with that.
This will be a grade five mobilization.
So it was only the popping
manual therapy that we use
for this SMT definition.
Sometimes mobilizations are
being put in there, but for our study,
we just looked at the cracking therapies,
so to speak.
um and and when I say target
and thrust what I mean is
by target I mean where
where do you decide on
where to give the treatment
so there's a like this huge
literature and even
profession specific debate
about where to do it and it
can go with like the
classic thing at least in
chiro practice is that you
palpate the spine and then
you find these dysfunctions
that the fixed joints or the
lock joints typically around the facet,
and then you manipulate it,
you make it go the little cracking sound,
you get the first of the
bubble and those theories
that we can get into if you
really want to,
and that improves the patients.
And you have to deliver it
at the exact right spot, right?
Because everyone can make
their back say crack,
but it's not in the right spot.
That's the whole theoretical
foundation around it.
So when I say target, that's what I mean.
That's basically where
exactly is the intervention?
Where is SMT being targeted on the spine?
And, and if you go with thrust,
which we also looked at,
that could be like,
was it a specific thrust?
Do you try to hit a single
vertebral segment or was it
more of a generalized thrust?
Like you wanted to,
to manipulate an entire lumbar region,
for instance.
And the region, I think it's,
we split it up into the region of pain.
So that could be low back
pain patients with, you know,
manipulated at the lumbar spine.
But it could also be, let's say,
patients with cervical,
like neck pain who were
treated in the thoracic spine.
That could be the non-symptomatic region.
So that's how we define regions.
So those are the three
things that we wanted to
assess in this review here,
where we could only look at
the target earlier.
Great.
Thank you.
I think that really helps.
Can you speak a little bit
more about how this study
then came about?
I kind of got you off track,
but thanks for those
definitions to kind of clarify.
Yeah, you're welcome.
Yeah, it's always when you, you know,
you got to speak to a broad audience.
Sometimes everybody doesn't
really understand what SMT is.
I mean, sometimes we can't even define it.
So it's a good point.
Um, so the study came, came about in,
I believe,
I had the idea about doing this.
And then I, um, I engaged Carson Yule,
who's a professor at the
university of Southern Denmark.
He's also a physio.
He has done a lot of systematic reviews.
He's like an expert on systematic reviews.
And I told him about the
idea and he really liked it.
And then we pretty much got going.
Then we got a senior team together.
So we got Chad Cook,
who I'm sure most of your
listeners are familiar with.
We got Chad involved in it.
And then we got Jan Hartwiesen,
who's a professor also at
the University of Southern
Denmark at Cairo.
He has done extensive work
in the low back pain field.
He was an author on the Lancet series,
for instance.
So a very good guy.
And then we also included Steven Pearl,
which I think your
listeners probably won't know.
He's also a chiro by
training and he's retired now, but
he has a, he has a mind of his own.
Like he knows every theory,
every treatment.
He is just, he, he's a sponge.
He remembers everything.
So we included him as well in the, as,
as the senior team.
And then we had to find, you know,
people to actually do the work.
Cause we all know that
professors don't really do a lot of work.
So, so we had to get a huge review team.
And originally I was,
I know another reason,
but I'm a part of the car fellowship,
which is like, um, international, uh,
like,
uh I want to say research
and leadership
international cairo program
so we had we were fourteen
people in the program so we
got a bunch of them in and
then we realized holy moly
this is going to be a lot
more work than we
anticipated so we got more
people involved in it and
that's where megan
donaldson came in for
instance uh also with a armed um
And at every point,
we wanted to keep it very
interdisciplinary.
That was very important for
us because some of the
critique that we got,
especially from Kairos from
our prior reviews, was that, well,
all of this work was done by physios.
which was actually most of
the other studies that we included.
But here we had a
possibility to include from
all types of different
professions because we
looked at it more broadly.
So we also wanted to make
sure that we had a very
broad and interdisciplinary
and international team as well.
So we also had a sports science guy.
We had a lot of, like you said,
I think we were eighteen authors.
So we had a lot of different
people in there.
That's really what it took to get it done.
It was a huge process when
we got it going.
The search was big and then
the data extraction was
enormous because we had to
extract a lot of things to
classify these different
SMT interventions.
So yes,
a lot of process that I think we
worked on it maybe a year
and a half before we
attempted to submit it somewhere.
So it was quite a lot of
work to get it done.
Yeah, it's amazing.
Just an enormous data set.
So going through kind of the
introduction there were.
I believe in your final sample,
a hundred and sixty one total studies.
Eleven little over eleven
thousand total subjects included in this.
Um, can you speak to how you.
Managed that large of a data
set and your choices of
some of these statistical
methods to analyze the data.
And then I think you
mentioned some of the
variables that you were studying.
But what were your main outcomes?
As we're looking at,
as a result of these procedures.
Yeah, let's start from the beginning.
How do we manage it?
Luckily,
I'm a quite organized and
structured guy when it
comes to data management.
I'm also pretty sufficient
with the statistical
software program that we used.
But it was really, really difficult.
And it was reported in just
a number of different ways.
So there was a lot to keep
track on when we actually got the data.
It took some time to prepare
the data for analysis.
And then the analysis itself
took maybe ten seconds.
So that was kind of a bummer,
but probably took two
months to get there.
That's the thing about data
cleaning that as non researchers,
you often don't appreciate
as much because you're like, oh,
You get the results,
but sometimes the results
take months to even get to
a point where you can analyze the data.
So that took quite a lot of work.
I also had to really
understand this network
meta-analysis thing,
which is quite different
than a normal meta-analysis
from a math standpoint.
So I had to put my head into that as well.
So that really did take a lot of time.
Yes.
And then we extracted, like I said,
a bunch of information.
And for outcomes,
we decided quite early on that, you know,
because we knew we were
going to end up with a broad,
very heterogeneity kind of
study sample here.
So we went with the two
outcomes that we had at
least knew that probably
the majority would publish,
which would be pain
intensity and some kind of
disability measure.
So that was the two outcomes
that we selected.
And then we were
strategic and saying that we
will only look at right
after the treatment.
So right after the treatment,
like the intervention,
if it was twelve sessions,
it would be after that twelve sessions,
that would be the short-term outcomes.
And then we had the long-term outcomes,
which was the closest thing
to twelve months.
So those were the outcomes
that we selected,
which meant that we had to
do a lot of analyses
because we did a lot of
networks and each network
had to be repeated for
different outcomes at
different time points.
Which is why the study got
so all the paper got so
enormous as it did.
Right.
Yeah, absolutely.
So after all of that,
after collecting all of that data,
what did you all find?
Well, I think we found a number of things.
The first thing that kind of
pops up is that we mirrored
what the other systematic
reviews have found,
which was really positive
because our systematic
review here was more broad than,
let's say, Sidney Rubenstein,
who published a systematic
review on chronic low back
pain back in twenty twenty nineteen.
That was probably the
biggest or that probably
that was the biggest review
to date published in BMJ
back in twenty nineteen.
And that was a little bit more concrete.
Ours included, you know, different regions,
a lot of different techniques, different,
you know, durations of pain.
We had both acute and
chronic pain in there.
So that's why we ended up
with so many studies and so
many participants.
So we were happy to see, first of all,
that all results actually mimicked,
sorry,
mirrored what they found,
which is that SMT seemed to
be as effective as other interventions,
recommended interventions,
such as exercise and other
manual therapies.
There was no real difference there.
And also that SMT was, you know,
a little bit more effective
than non-recommended therapies, like say,
putting yourself in traction or...
uh like ultrasound for
instance and like stuff
that is no longer being
recommended in clinical
guidelines what we did
found that was different
from a lot of the other
reviews was that when we
compared to sham treatment
we actually found quite a
larger effect of smt
compared to other studies
And I think part of that is due to the,
we had to pool some
different placebo studies together.
So one could be a real setup
where you completely mimic
the intervention.
And the other one could be
like a detune ultrasound
thing that you just put on patients.
And from a contextual standpoint,
which we'll talk more about later,
those are very different.
And we also know that from a
paper published in pain last year,
that there's quite a big
difference in the effect
sizes between those two
different placebos.
So.
That's probably why we found
those results.
So that was the first thing we found.
And then we looked at,
we basically used different
ways of categorizing the target,
the thrust and the region.
And then we compared all of
those with each other based
on this advanced and complex statistics.
So we got a result out and
that result was very clear.
Like it worked and it really
didn't matter how you used it.
Like there were no real
differences between any of
the SMT interventions.
It reached statistical
significance a couple of times,
but it was still a somewhat
small effect size.
So basically saying that SMT
seems to work as well as
other recommended therapies,
but how you do it.
It didn't explain any of the
variation in the outcome data.
So there was no difference whether,
let's take an example,
whether you used a
completely generalized
thrust or whether you were
trying to be like sniper
specific on that vertebral segment,
didn't matter.
Even if you did it in the
region where people came in,
like let's say a neck patient came in,
you manipulated the neck or
you manipulated their thoracic spine.
There was a lot of studies that did that.
Also no difference in neck
pain outcomes or neck
disability outcomes.
And we actually found,
but that's not what we want to conclude,
because I'll get to that in a second.
But we actually found that a
completely nonspecific approach,
a generalized thrust to the
non-symptomatic region
actually appeared to be the
most effective way of doing it.
But because of the way that
the study was set up,
we said that clinicians,
and that's the main takeaway,
that clinicians can
basically do whatever they
want to and expect to get
the same results.
So we shouldn't dive into
the different philosophies
or theoretical frameworks
for this type or this type.
At least on average,
it seems to be that there
is no real difference.
And we found one last thing,
which I might add,
which was that as expected,
because normally in systematic review,
you should do a great
approach to assess the
certainty of the evidence.
And normally,
you want to get high certainty evidence.
That's what's going to
change clinical practice.
basically which rarely
happens in spine research
unfortunately and it also
didn't happen here we
actually got low certainty
evidence more or less all
the way through and that it
is really explained by a
few things first of all we
used you always assist risk
of bias in these randomized
trials that we included and
here we were very stringent
we used cochran's which is
the recommended tool and we
were quite hard so we used
cochran's way of doing it and cochrane is
It's like the guidebook on
how to do reviews, basically,
which meant that almost all
of the studies were
categorized as having a
high risk of bias just
because you cannot really blind it.
And all the outcomes we
looked at were subjective.
So I would say,
my pain is now three out of
ten instead of five out of
ten or whatever.
And that's all a subjective
opinion that can be biased
by a lot of different things.
It kind of makes sense, right?
So that pumped the certainty
of the evidence.
It downgraded it, I would say.
And then we also saw some inconsistencies.
So there were some
comparisons that we did.
And I don't want to get too technical here,
where we had a study that
did a direct comparison.
So let's say an RCT that
compared SMT to exercise, for instance.
And that would show one result.
And then based on all these
advanced mathematics,
when we looked at the indirect evidence,
so that would be if we
took what the computer
decided is probably the
effect of manipulation over exercise.
Those two could differ a bit.
So that's what we call inconsistency.
And we also had a little bit of that.
And it was mostly related to
when we compared SMT to
other interventions.
So again,
basically saying that the
outcomes we looked at are
all over the place,
which did impact the
certainty of our evidence.
But we still,
and I don't know if you want
to ask about this later,
but we actually still conclude that,
and we just wrote a blog to
JOSBT about this,
where we explained this,
in in more detail which
didn't fit into the
original paper we still
believe that this has an
impact on education
specifically and also on
clinical practice because
it's not only this paper
that says that we had the
other reviews we have
individual trials we have
mechanistic research saying
that you can't really
control forces or at least
control where where the
forces are delivered like
for instance if you were to
quantify where the popping
sounds occur they occur all
over the spine even
multiple places away and
only like half the time
they actually occur on this
segment um so so this this
aligns really well with
with mechanistic research
with other reviews with
individual trials and also
to be honest with a more
modern understanding of
pain science and how back
pain is fluctuating and how
complex pain really is.
It also goes along really well with that.
So we still think that our
conclusions holds a lot of
recommendations that we
hope will be implemented different places,
despite the low certainty
evidence from a more
statistical standpoint,
if that makes sense.
Yeah, I think so.
Thank you for the
explanation and description of results.
The first thing that kind of comes to mind,
and I don't mean this in a negative way,
but being a fellowship
trained in AOMT and just
having some conversations
with colleagues about these
sorts of things,
we like to think that our
training allows us to
deliver maybe different
levels of manual therapy
skills than colleagues who
maybe didn't go through
residency training or
fellowship training or just
don't have the experience.
What are your thoughts on
the potential impact or implications of,
as you yourself mentioned,
just the large data set and
potentially the
heterogeneity of the
different studies that were included?
Was there any way that you
were able to control for or account for.
The type of treatment delivered,
whether it was from a trained clinician,
and then can you speak to
maybe the breakdown of.
Different applications of
these treatments from a chiropractic.
Standpoint is probably your your lens,
but also the chiro
philosophy versus physical therapy.
Do you think that.
Made a difference and I again.
Acknowledging that,
including both of those professions,
because we both utilize
that as a treatment
technique and trying to
span conclusions from
application of this
treatment is important.
But do you think that
limited your ability to
conclude definitively
things based across the board?
I don't know.
Yeah, no, I know what you mean.
There were two really
important questions there.
One about the AOM training
and all that stuff,
like to get those qualifications.
Let's get back to that a
little bit because I do
want to answer that.
We can take the study first.
Obviously,
the effects that we see here are
all average defects.
So it might be that there
are certain outliers where
this matters a whole lot
and other outliers where it
really doesn't matter at all.
but on average,
there was no real difference in it.
And that's currently the
only way that we can look
at it is using the average data.
And then you asked about,
I would say we, first of all,
our study was,
despite the large number of studies,
was not really powered to
look at whether different
professions differed or
whether the experience of
different professions,
if that mattered for outcomes.
There were some other
studies out there where
they look at the experience
of people and how that matters,
and it doesn't seem to
matter a great deal,
which also boils down to
the complexity of measuring
pain in real life.
It is quite complex.
And even just to understand
that and interpret it as a
research participant, very difficult.
And then I would say we
deliberately also didn't
want to compare clinicians
against each other because
there are a lot of other
factors that are involved
here into the effect of these studies.
So let's say like the
smaller sample sizes of some studies,
for instance,
that's something that probably matters.
Risk of bias may matter as well.
But we did,
and I haven't talked about this yet,
but the paper is about a couple of pages.
But then our supplementary material,
our appendix,
is actually three hundred
and forty pages.
So we did we did numerous
additional analyses kind of
to validate or verify some
of these findings.
And some of the things that
we looked at that didn't matter was,
you know,
where did the patient have pain?
What was the pain duration?
But it was all more patient
specific criteria.
We didn't really look at the
at the, at the clinician itself, but
And I kind of don't want to do it,
to be honest,
because I don't want to set
Kairos up against physios.
I don't think that makes any sense.
We should probably be better
at collaborating than
fighting each other.
And it doesn't really have any impact,
I would say,
on clinical practice because
we all know on an everyday basis,
if patients, they like to go to Kairos,
they'll go to Kairos.
If they want to go to physios,
they'll go to physios.
And if one thing doesn't work for them,
maybe they'll switch.
But
The risk of going back to a
provider is who you see first,
most likely.
So I would kind of hate
doing research like that,
especially on this type of database.
And when I say all this,
and I get back to your first question,
which I thought was really
good about the AOMD
classification and
postgraduate education and all that,
I do think that matters greatly.
So there are two points in
all of this that we haven't
been able to assess.
And one,
if you want to start with the
biomechanics, is false modulation skills.
So for instance, the more trained you are,
you would understand that
some patients need a little bit more push,
some patient needs a little less push,
some patients maybe don't
want to be pushed at all.
So that controlling of forces,
and I don't mean where
right now where it's being delivered,
but by hand forces, how much
you know, how much of your mass,
your body mass you use when
you deliver the treatment.
I think that matters some,
maybe not for clinical outcomes,
but it definitely matters for safety.
And I think it matters for
patient comfort as well.
And also for participant comfort,
not provider comfort.
And that's the next thing to go into here,
because I think a lot of
this is being driven by
contextual factors, to be honest,
where manual therapy in
general is a very powerful
contextual factor.
Like you you lay down,
you're being examined and
you something is being done
and the patient can
obviously hear and feel
that something happens.
And, you know,
if it says at least in Cairo
field and I guess also in
physios from some of the
conversations I had,
whenever it says that popping sound,
you always get a little bit.
Yes, that was really good.
Right.
You got a good response.
And that response,
that rubs off on the patient.
Obviously, it does.
And they will get up and say, yeah,
I can feel I move much better now.
And all of that probably has
more to do with context
than what actually happens
inside the spine.
And that is something that
is being portrayed better by,
and this is just me.
I don't have any data on this.
This is just me speculating.
But I would say that is
easier to sell if you are
an experienced clinician
who trained this and has a
high confidence.
You can easily build up this
therapeutic alliance.
You can more easily wrangle
your different techniques,
your force modulation skills,
and all of that.
I think that matters to a certain degree.
And stuff like that is just
difficult to learn because
you need to be comfortable
doing it and confident doing it.
That way, you know,
patients will also be
confident and comfortable
in you doing it.
And that will lead to better outcomes.
But again, that has nothing to do with,
you know, the way you do it,
which is why we make the
argument that clinicians,
experienced clinicians such as yourself,
you can go out, you know,
practicing tomorrow or next
Monday and you can do whatever you want.
probably won't matter a whole lot.
You can try to be as
specific and as concrete as you want,
whether you're a physio or
a chiro or whatever it is.
But for the future clinicians,
I think we are basically
looking into a major
paradigm shift of the way
that we teach manual therapy.
into an approach where we
have to look at it,
I want to say the word holistically,
even though I hate that word,
because there's so many
negative associations with it,
but we have to see the whole person.
We have to understand how
these contextual factors
impact the patient,
how it impacts our treatment.
And then we have to learn,
we still have to learn like motor skills,
how to modulate forces.
We still have to be
confident in the way that we do it.
I still think like palpation,
it has an effect on people
just like palpating, you know, feeling,
getting a sense of the
structure and tissue and
texture of the patient.
Like, is this someone who I need to be,
you know,
put a little bit more mass into
or should I back off a little bit?
Some of those things are
still very important to teach,
but teaching stuff like, oh,
you want to move the bone
this way or that way,
or you want to hit this
angle because then you will hit the,
you will impact the disc
rather than the facet joints.
That is all just outdated information.
And we need to update that across,
I would say like worldwide
across all institutions
that teach rather undergrad
or post-grad that teach
manual therapy skills,
at least when it comes to
this popping sound that we
investigated SMT.
So that would be my very
long answer to your two
slightly complicated questions,
if that makes sense.
And I don't know if you agree or not,
but it's my point, at least,
based on all this data that
I have looked at over the last,
I want to say, ten years.
Yeah,
definitely follow what you're
describing and excellent answers, Casper.
I think also,
and this is not different
than I think a lot of the
philosophy that our
listeners or the listeners
are familiar with this podcast.
In fact,
a more recent publication on the
definition of orthopedic
manual physical therapy and
that paper was recently
published and I believe
Jason Silvernail was on for
an interview to discuss that and how
So OMPT is exactly what you're saying,
not just the application of
the hands-on technique,
but it's all these other
things that go into it.
It's the clinical reasoning.
It's the choice of technique.
It's the contextual factors.
It's setting it up for the
patient and what you do before,
what you do after,
how you weave it into your
treatment and plan of care.
I think that that is really,
really important and great
thing to bring up as we're
trying to integrate that
into our educational
settings just to increase
the skill of our clinicians
that we have coming out of those.
That's great.
Can I add one thing?
Sorry.
Yeah, please do.
We're looking into a world
now where we understand the
complexity of low back pain a lot better.
We've done a lot of
trajectory research over these last
I want to say, twenty,
maybe thirty years to see
how much it actually varies
over time and how, you know,
back in the day we had this definition,
acute and chronic low back
pain doesn't really make sense anymore.
It's either episodic low
back pain or recurrent low
back pain or simply
persistent low back pain.
But, you know,
back pain is never like this,
just high all the time.
It fluctuates up and down,
which means that we are
looking into a way that
people need to learn how to self-manage.
And we have to shift our
education and research and
clinical reasoning into
understanding how can we
take this apparently
effective intervention?
And that is that is, you know,
probably in the way that
most people understand it
is pretty far away from
self-management strategies
and implement that into a
way where we can use it as
a self-management strategy,
where we can reduce the flares,
maybe the pain flare ups.
Something like that.
And we don't really have a
great understanding of that
at the moment.
And I think that's
definitely where we need to move ahead.
We have to understand that
better because we are
looking into a world where
back pain is growing more
and more and people have to
learn how to self-manage it
because we cannot cure it.
Yeah, I think that's excellent.
So it leads into my last question.
I can talk to you all day.
I think this is fascinating,
but last question for you
is kind of looking ahead
and based on the findings
from this study that we
spent a lot of time talking about,
but then also based on the
other research that you're involved in,
what do you see really now
as some of the gaps in the
literature and where we
need to focus future research efforts?
If you talk,
SMT specifically,
I would say there are gaps
all over the place.
There's a huge area of
simply research waste,
a lot of bad trials, underpowered trials.
There's very low funding to
the area as well.
So that's probably the reason.
So I think gaps, we could talk.
I could say anything,
and there would be a gap in it.
Like, let's say, for instance,
if you really wanted to
conclude whether it
mattered to be highly specific or not,
we would need a really
high-powered trial with
hundreds of people in it to
really estimate whether
those two things were the same.
But based on all of this research,
I would say that's not
something that we should do,
and we shouldn't fund that either.
Because we have to look at
SMT more as having a widespread effect.
That's probably the best way
to describe it.
So even though that's a gap,
that's not a gap that I
would recommend people to
follow because it will be
more of the same.
If you do it properly,
the two outcomes will be
the same for the two groups.
That's just the way it'll
work in nine out of ten times.
And then, like I said before,
how to implement this into
self-management strategy,
long-term care plans,
how to better provide treatment for,
I would say,
the elderly as well is
something that's going to
be really interesting over
this next couple of years here.
As the population grows older,
like a lot of
And also, to be honest,
at least in Denmark,
and I assume it's the same all around,
that all the people,
they want to do more.
They have more money.
They have more resources.
So they want to live their
life to the fullest when
they retire even.
So there's going to be a
high demand on how to
make these patients, not patients,
but these elderly citizens,
how to make them function
in a day-to-day basis.
I think that's going to be
super interesting and
something that we really do
need to research.
And I would still say,
specifically for SMT mechanisms,
it's still really
interesting and we need
more and we need better research,
simply put, on it.
And we need to
know follow a string where
we you know find something
experimentally like
biomechanically or
neurophysiological and then test that
all the way to a clinical population.
We need programs that does this.
And it's probably not to
understand how to give the treatment,
but more like who is the
responders of the treatment?
Who should we provide this
to and who should we do
something different to?
I think that's going to be
some of the main things
that we have to work on
over these next couple of years.
Maybe my entire career, who knows?
But that's definitely
something that we need to look at,
which we at the moment
don't really have any idea of.
And not just related to this,
you could look at exercise,
which is much more research
than manual therapy.
They also struggle to come
up with definitions of
trying to predict responders, basically.
Very difficult.
Great.
Well, Casper, again,
thank you so much for
joining us on the Hands On,
Hands Off podcast.
It's been a joy listening to you,
learning from you,
and we will definitely be
following your future work.
So thanks so much.
I appreciate it.
Thank you for having me.
Absolutely.