March 6, 2024 • 13 mins
In Episode 3 of "Fact Check Your Health," dive deeper with Katie and Sydney as they discuss the different types of health research studies. This episode is a treasure trove for anyone looking to understand the different types of studies and their impact on the health information we consume daily.
Katie and Sydney break down the scientific jargon, making sense of randomized controlled trials (RCTs), observational studies, systematic reviews, and meta-analyses using everyday language and relatable examples. They emphasize the importance of distinguishing between causation and correlation, explain the placebo effect and confounding factors, and provide practical tips for evaluating research findings. This episode equips listeners with the knowledge to better understand research claims and make informed health decisions.
Podcast Outline:
0:55 - Not all research is created equal
2:10 - Overview of experimental & observational studies
5:26 - What is a Randomized Controlled Trial (RCTs) and why they are the gold standard for research
6:30 - Placebo effect
8:35 - Confounding factors
9:40 - Example of a confounding factor
10:30 - How to determine if a study is an experimental study or observational study
11:05 - Systematic reviews and meta-analyses
12:40 - Episode recap
For more information and additional resources check out the Fact Check Your Health website at https://factcheckyourhealth.squarespace.com
Disclaimer: The information provided is for educational and entertainment purposes and is not intended as medical advice. For medical advice contact a licensed medical provider.
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Katie (00:03):
All right, welcome back to the third episode of Fact
Check your Health, the podcastwhere we break down all the
health research methods to makethem easy to understand.
I'm your host, katie, andjoining me today is my co-host,
sydney, so let's go ahead anddiv e in.
Sydney (00:15):
So before we start today's podcast, we just want to
do a quick recap on what wecovered in the first two
episodes.
Katie (00:21):
So in the first episode we covered ways to spot
unreliable information and someways to find reliable
information, and in the secondepisode we went through what
you'll see when you look at anacademic article and what all of
that information means.
Now in this episode we're goingto go into detail about how you
can figure out whichinformation you should believe,
which information you should beskeptical about, and give you
(00:42):
all the tools and resources youneed to be able to make that
evaluation on your own Right.
Sydney (00:48):
So today we're going to be explaining the different
types of research studies,because it's very important for
you to know that not allresearch studies are created
equal.
Just because somebody said, oh,a research study showed blah,
blah, blah, first off, even ifthey are interpreting it
correctly, the research studyitself might not be a very
strong study or it could beconflicting other studies that
have a stronger methodology.
(01:09):
I love talking about thisbecause you've all seen these
crazy documentaries that makethese claims based off research
studies, and today we're goingto explain to you why those
claims might not be accurate andhow to find a type of studies
that can actually answer thequestion that you're looking for
.
Katie (01:26):
And, like you said, it could be really confusing to
know what to believe.
So what we're going to do inthis episode is break down all
the different types of studiesand tell you the pros and cons
of each study type, and give youinformation on what the best
type of study is and what typeof studies you should be looking
for when you want to findhealth information.
Sydney (01:43):
Yeah.
So in my personal opinion, thismight even be the most
important episode that we have,because this is going to help
you really differentiate betweenall of the BS that's out there
and all of the conflictingstudies.
There's so many researchstudies that conflict each other
and it can make you feel likeresearch is unreliable, and
that's not true at all.
A well done study is veryreliable.
In fact, if you know how tojust find the best type of study
(02:05):
, then you can find thatreliable information and you can
make the best informed decisionpossible.
Generally speaking, there aretwo main categories that most
research studies fall under, andthese are experimental studies
and observational studies.
Katie (02:18):
So the first umbrella is experimental studies.
So, put simply, an experimentalstudy is typically going to be
a study that uses a controlgroup and an experiment group to
determine cause and effect.
So let's say, for example, thatyou're trying to determine
whether a new drug works.
You're going to compare a groupof people that receive that
drug with a group of people thatreceived a placebo drug or a
(02:40):
fake drug, and then you're goingto look to see if there was a
difference between the twogroups Exactly.
Sydney (02:45):
Now let's talk about another kind of study called an
observational study.
So, unlike experimental studies, observational studies instead
look at existing information tofind patterns and connections
between different variables orconcepts.
So, in simple words,observational studies don't
involve directly changing thingsor separating groups, like
experimental studies do.
(03:06):
Instead, researchers gatherdata from real life situations
and see how different factorsmight be linked.
For example, let's say we wantto know if drinking coffee is
connected to heart disease.
Instead of conductingexperiments and randomly
assigning participants to drinkcoffee or not, like researchers
would do in an experimentalstudy, in an observational study
(03:26):
they would instead collect datafrom a bunch of people and then
see if those who drink morecoffee also have heart problems.
Katie (03:33):
Yeah, exactly.
So these observational studiescan also come in different forms
so they could follow a group ofpeople over time, or they could
compare people that have acondition with people who don't
have a condition, or they couldlook at just specific moments in
time Exactly, and observationalstudies are important because
they help researchers findpatterns between different types
(03:55):
of variables or things ofinterest.
Sydney (03:57):
So, while experimental studies focus on cause and
effect, observational studieslook at how things are connected
in the real world.
We need them because a lot oftimes they're done when
conducting experimental studieswould be challenging or not
possible.
So there are many times inhealth research specifically
where it's difficult orimpractical to do an
experimental study.
So, like the example withcoffee and heart outcomes, if
(04:19):
you did an experimental studyyou would have to follow those
people for 40 years to see ifcoffee impacted their heart
outcomes.
But that's not really possible.
We can't actually follow peoplein a study in a randomized
experimental way for 40 years.
So in those scenarios,observational studies are a
valuable alternative to gainingimportant information and
insights.
Katie (04:39):
And another example of why you can't always do an
experimental study is becausesometimes it might be unethical
to require someone to dosomething.
So let's say, for example, thatwe're trying to figure out the
long-term effects of smoking onhuman health.
It would be pretty impracticaland unethical to assign
individuals randomly to eithersmoke cigarettes or not smoke
(04:59):
cigarettes for an extendedperiod of time, since asking
them to smoke a cigarettepotentially exposes them to
significant health risk.
So in this case, what you woulddo instead is you would do an
observational study, and thatway you could track people over
time and see if there'sassociation between smoking and
human health.
Sydney (05:16):
So now, that we've talked you through the two main
areas of studies.
Now it's important for us toexplain the strongest, or in
other words the gold standard,type of study.
So in the world of healthresearch, randomized controlled
trials, also referred to as RCTs, are going to be considered the
gold standard RCTs are superpowerful because they allow us
(05:36):
to determine cause and effect byusing a control group.
Katie (05:40):
So to just give a brief overview for someone who might
not be super familiar with thephrase randomized controlled
trial essentially what arandomized control trial is is
an experiment where you're goingto randomly assign people to
two different groups.
So one group is going toreceive the treatment or the
drug or whatever it is thatyou're testing, and then the
other group is going to get afake treatment or a placebo, and
(06:02):
then people are going to berandomly assigned to one of
those two groups.
So by randomly picking who getswhich treatment, we can make
sure that the groups are similarto start off with.
That way, at the end of thestudy, if we do see any
differences between the twogroups, we can say that that
difference is caused by thetreatment or the drug or
whatever it is that we'retesting and not some other
(06:22):
factor.
Sydney (06:23):
So, like Katie said, in randomized controlled trials
there will be a placebo groupwho gets a fake treatment.
This is important because youmay have heard of this before in
passing, but there's this thingcalled the placebo effect and
basically, if a person thinksthat they're getting any sort of
treatment, their symptoms, orwhatever the outcome is, will
improve just off the fact thatthey think that they're getting
(06:45):
a treatment.
This is the power of the humanbrain If you think you're going
to get better, you will getbetter.
Katie (06:50):
So that's why we have to have the placebo group and, to
put it in an example that I'msure we can all relate to
caffeine and coffee.
Several studies have been donethat look to see if caffeine
actually has an effect on peopleor whether sometimes the
placebo effect plays in there.
So if you're anything like me orSydney and you need that coffee
in the morning to give you alittle pick me up, usually even
(07:12):
just after the first one to twosips you already start to feel
more alive and that could be acase of the placebo effect.
So it might be that the caffeineactually isn't having that
effect, but it's more that bydrinking the coffee that placebo
effect is kicking in and you'refeeling the effects of
something, even if it's notactually making a difference.
So that's why a randomizedcontrolled trial is important,
(07:34):
because they're going to betesting a placebo compared to
the actual drug so that they canmake sure that any differences
they see they can actuallyattribute to that drug and not
just the placebo effect.
Ultimately, rcts are superimportant because they give a
strong evidence about what worksand what doesn't, and while
experimental studies are superpowerful, conducting long term
(07:55):
experiments can be reallychallenging, like Sydney
mentioned earlier.
That's why most studiesexamining long term health
outcomes are observational innature, because imagine trying
to assign people to alcohol ornon alcohol groups for 10 years.
That would be a very difficultthing to do.
Sydney (08:12):
Yeah.
So because of this, nutritionstudies are often observational
and this leads to ongoingdebates about the best diets for
long term human health, andthis is why you probably have
heard a plethora of mixedinformation.
You know vegetarian diets arebest for health, keto diets are
best for health, and they allseem to support their claims.
This is because we can prettymuch only do observational
(08:32):
studies with long term outcomesfor nutrition studies and
following that another downfallof observational studies can be
this thing called confoundingfactors.
Katie (08:41):
So let's say, for example , the studies that were done
forever ago that showed thatdrinking more wine led to
increased heart health.
But the thing is that in thatstudy, whenever it was done in
that period of time, drinkingmore wine was usually also
correlated with higher income.
So it might have been that itwasn't actually alcohol that was
leading to those improvementsin health, but it could have
(09:03):
been other factors that wererelated to that person's
socioeconomic status that wascontributing to that instead of
the alcohol.
Sydney (09:10):
Right.
So in the case of those studiesthey were confounding factors
like income and socioeconomicstatus.
So basically, just to defineconfounding factors, these are
other variables that caninfluence the relationship
between a predictor.
So the thing that we'restudying and the outcome,
confounding factors aretypically things like age,
gender, education and income.
So to break that down, into arelatable example.
Katie (09:33):
Let's say that you have a study investigating whether
being a Taylor Swift fan isrelated to having fewer wrinkles
.
So let's say that the studyfound that Taylor Swift fans on
average have fewer wrinkles thannon-Taylor Swift fans.
Sydney (09:47):
But unfortunately, what's probably going on in this
study is that liking TaylorSwift doesn't directly lead to
fewer wrinkles, but there's aconfounding variable of age.
So people who like Taylor Swifttend to be younger and since
younger individuals have fewerwrinkles, the observed
difference is due to age and notactually liking Taylor Swift,
Though I do believe Taylor Swiftwill keep me young forever, but
(10:10):
yeah.
Katie (10:10):
I definitely wish it was true that being a Swiftie would
lead to less wrinkles, butultimately, that's why RCTs, or
those randomized controlledtrials, are considered the best
research method, because byrecruiting participants who are
similar in terms of age, incomeand other factors, researchers
can keep those potentialconfounding factors as similar
as possible.
(10:30):
So now that we've talked aboutthe different studies, whenever
I'm reading a research abstract,how should I actually determine
what type of study it is?
That's a good question.
Sydney (10:39):
So, as a rule of thumb, if the abstract doesn't
explicitly mention that it's anexperimental study with a
control group, or it doesn't saythat it's an RCT.
It's likely an observationalstudy.
Observational studies might bereferred to in an abstract as
either an observational study ora more specific type of
observational study, like a casecontrol study, a cohort study
(11:00):
or a cross-sectional study, andthere might be a few exceptions
to this rule.
Katie (11:04):
So in addition to experimental studies or
observational studies, there'salso papers that are systematic
reviews or meta-analyses.
So in a nutshell, a systematicreview is basically like a
supercharged study that kind ofbrings together a lot of other
studies to give us a clearunderstanding of a specific
question or topic.
So basically in a systematicreview, the researcher is going
(11:25):
to go and find all of the goodquality studies that have been
done on a topic and then put allof that information together so
we can get a more accurate andreliable answer to that question
.
Meta-analyses are kind ofsimilar but a little bit
different, so I'll let Sydneydescribe what a meta-analysis is
Right.
Sydney (11:41):
So, in a similar process , meta-analyses take it just a
step further by then actuallycombining data from these
multiple studies and Doing astatistical analysis on all of
these data together.
So here's a simple explanationof how it works.
Imagine if you have a bunch ofstudies that have investigated
the same topic or researchquestion.
Each study might have differentfindings or results, but a
(12:02):
meta-analysis combines data frommultiple studies to get a more
reliable estimate of the overalleffect.
It helps identify patterns,evaluate the strength of
evidence and draw more confidentconclusions about a particular
research question or topic.
However, the strength dependson the quality of studies
included.
So a meta-analysis thatincludes strong studies like
RCTs are a more reliable sourceof information than a
(12:25):
meta-analysis that includesstudies like observational
studies.
Katie (12:29):
Whenever you're looking through PubMed or Google Scholar
, if you see a meta-analysis ora systematic review, that could
be a really good resource foryou to go to to get a summary of
all the information that's outthere on the topic.
So now just to recap everythingthat we've covered in today's
episode Experimental studies aregoing to be best for telling us
if whatever we're studyingactually causes something else,
(12:50):
whereas observational studiesobserve behaviors in the wild
and establish whether or notthere's patterns.
So, if available, we're goingto want to rely on a randomized
control trials, because they'rethe best source of information.
But if those sources aren'tavailable, observational studies
could also be great and,similarly, systematic reviews
and meta-analyses can also be areally good and reliable
(13:11):
resource.
Sydney (13:12):
So that concludes today's episode of fact.
Check your health.
Katie (13:15):
Join us next time as we teach you why the headline that
you're reading might bemisleading.
All right, welcome back to the third episode of Fact
Check your Health, the podcastwhere we break down all the
health research methods to makethem easy to understand.
I'm your host, katie, andjoining me today is my co-host,
sydney, so let's go ahead anddiv e in.
Sydney (00:15):
So before we start today's podcast, we just want to
do a quick recap on what wecovered in the first two
episodes.
Katie (00:21):
So in the first episode we covered ways to spot
unreliable information and someways to find reliable
information, and in the secondepisode we went through what
you'll see when you look at anacademic article and what all of
that information means.
Now in this episode we're goingto go into detail about how you
can figure out whichinformation you should believe,
which information you should beskeptical about, and give you
(00:42):
all the tools and resources youneed to be able to make that
evaluation on your own Right.
Sydney (00:48):
So today we're going to be explaining the different
types of research studies,because it's very important for
you to know that not allresearch studies are created
equal.
Just because somebody said, oh,a research study showed blah,
blah, blah, first off, even ifthey are interpreting it
correctly, the research studyitself might not be a very
strong study or it could beconflicting other studies that
have a stronger methodology.
(01:09):
I love talking about thisbecause you've all seen these
crazy documentaries that makethese claims based off research
studies, and today we're goingto explain to you why those
claims might not be accurate andhow to find a type of studies
that can actually answer thequestion that you're looking for
.
Katie (01:26):
And, like you said, it could be really confusing to
know what to believe.
So what we're going to do inthis episode is break down all
the different types of studiesand tell you the pros and cons
of each study type, and give youinformation on what the best
type of study is and what typeof studies you should be looking
for when you want to findhealth information.
Sydney (01:43):
Yeah.
So in my personal opinion, thismight even be the most
important episode that we have,because this is going to help
you really differentiate betweenall of the BS that's out there
and all of the conflictingstudies.
There's so many researchstudies that conflict each other
and it can make you feel likeresearch is unreliable, and
that's not true at all.
A well done study is veryreliable.
In fact, if you know how tojust find the best type of study
(02:05):
, then you can find thatreliable information and you can
make the best informed decisionpossible.
Generally speaking, there aretwo main categories that most
research studies fall under, andthese are experimental studies
and observational studies.
Katie (02:18):
So the first umbrella is experimental studies.
So, put simply, an experimentalstudy is typically going to be
a study that uses a controlgroup and an experiment group to
determine cause and effect.
So let's say, for example, thatyou're trying to determine
whether a new drug works.
You're going to compare a groupof people that receive that
drug with a group of people thatreceived a placebo drug or a
(02:40):
fake drug, and then you're goingto look to see if there was a
difference between the twogroups Exactly.
Sydney (02:45):
Now let's talk about another kind of study called an
observational study.
So, unlike experimental studies, observational studies instead
look at existing information tofind patterns and connections
between different variables orconcepts.
So, in simple words,observational studies don't
involve directly changing thingsor separating groups, like
experimental studies do.
(03:06):
Instead, researchers gatherdata from real life situations
and see how different factorsmight be linked.
For example, let's say we wantto know if drinking coffee is
connected to heart disease.
Instead of conductingexperiments and randomly
assigning participants to drinkcoffee or not, like researchers
would do in an experimentalstudy, in an observational study
(03:26):
they would instead collect datafrom a bunch of people and then
see if those who drink morecoffee also have heart problems.
Katie (03:33):
Yeah, exactly.
So these observational studiescan also come in different forms
so they could follow a group ofpeople over time, or they could
compare people that have acondition with people who don't
have a condition, or they couldlook at just specific moments in
time Exactly, and observationalstudies are important because
they help researchers findpatterns between different types
(03:55):
of variables or things ofinterest.
Sydney (03:57):
So, while experimental studies focus on cause and
effect, observational studieslook at how things are connected
in the real world.
We need them because a lot oftimes they're done when
conducting experimental studieswould be challenging or not
possible.
So there are many times inhealth research specifically
where it's difficult orimpractical to do an
experimental study.
So, like the example withcoffee and heart outcomes, if
(04:19):
you did an experimental studyyou would have to follow those
people for 40 years to see ifcoffee impacted their heart
outcomes.
But that's not really possible.
We can't actually follow peoplein a study in a randomized
experimental way for 40 years.
So in those scenarios,observational studies are a
valuable alternative to gainingimportant information and
insights.
Katie (04:39):
And another example of why you can't always do an
experimental study is becausesometimes it might be unethical
to require someone to dosomething.
So let's say, for example, thatwe're trying to figure out the
long-term effects of smoking onhuman health.
It would be pretty impracticaland unethical to assign
individuals randomly to eithersmoke cigarettes or not smoke
(04:59):
cigarettes for an extendedperiod of time, since asking
them to smoke a cigarettepotentially exposes them to
significant health risk.
So in this case, what you woulddo instead is you would do an
observational study, and thatway you could track people over
time and see if there'sassociation between smoking and
human health.
Sydney (05:16):
So now, that we've talked you through the two main
areas of studies.
Now it's important for us toexplain the strongest, or in
other words the gold standard,type of study.
So in the world of healthresearch, randomized controlled
trials, also referred to as RCTs, are going to be considered the
gold standard RCTs are superpowerful because they allow us
(05:36):
to determine cause and effect byusing a control group.
Katie (05:40):
So to just give a brief overview for someone who might
not be super familiar with thephrase randomized controlled
trial essentially what arandomized control trial is is
an experiment where you're goingto randomly assign people to
two different groups.
So one group is going toreceive the treatment or the
drug or whatever it is thatyou're testing, and then the
other group is going to get afake treatment or a placebo, and
(06:02):
then people are going to berandomly assigned to one of
those two groups.
So by randomly picking who getswhich treatment, we can make
sure that the groups are similarto start off with.
That way, at the end of thestudy, if we do see any
differences between the twogroups, we can say that that
difference is caused by thetreatment or the drug or
whatever it is that we'retesting and not some other
(06:22):
factor.
Sydney (06:23):
So, like Katie said, in randomized controlled trials
there will be a placebo groupwho gets a fake treatment.
This is important because youmay have heard of this before in
passing, but there's this thingcalled the placebo effect and
basically, if a person thinksthat they're getting any sort of
treatment, their symptoms, orwhatever the outcome is, will
improve just off the fact thatthey think that they're getting
(06:45):
a treatment.
This is the power of the humanbrain If you think you're going
to get better, you will getbetter.
Katie (06:50):
So that's why we have to have the placebo group and, to
put it in an example that I'msure we can all relate to
caffeine and coffee.
Several studies have been donethat look to see if caffeine
actually has an effect on peopleor whether sometimes the
placebo effect plays in there.
So if you're anything like me orSydney and you need that coffee
in the morning to give you alittle pick me up, usually even
(07:12):
just after the first one to twosips you already start to feel
more alive and that could be acase of the placebo effect.
So it might be that the caffeineactually isn't having that
effect, but it's more that bydrinking the coffee that placebo
effect is kicking in and you'refeeling the effects of
something, even if it's notactually making a difference.
So that's why a randomizedcontrolled trial is important,
(07:34):
because they're going to betesting a placebo compared to
the actual drug so that they canmake sure that any differences
they see they can actuallyattribute to that drug and not
just the placebo effect.
Ultimately, rcts are superimportant because they give a
strong evidence about what worksand what doesn't, and while
experimental studies are superpowerful, conducting long term
(07:55):
experiments can be reallychallenging, like Sydney
mentioned earlier.
That's why most studiesexamining long term health
outcomes are observational innature, because imagine trying
to assign people to alcohol ornon alcohol groups for 10 years.
That would be a very difficultthing to do.
Sydney (08:12):
Yeah.
So because of this, nutritionstudies are often observational
and this leads to ongoingdebates about the best diets for
long term human health, andthis is why you probably have
heard a plethora of mixedinformation.
You know vegetarian diets arebest for health, keto diets are
best for health, and they allseem to support their claims.
This is because we can prettymuch only do observational
(08:32):
studies with long term outcomesfor nutrition studies and
following that another downfallof observational studies can be
this thing called confoundingfactors.
Katie (08:41):
So let's say, for example , the studies that were done
forever ago that showed thatdrinking more wine led to
increased heart health.
But the thing is that in thatstudy, whenever it was done in
that period of time, drinkingmore wine was usually also
correlated with higher income.
So it might have been that itwasn't actually alcohol that was
leading to those improvementsin health, but it could have
(09:03):
been other factors that wererelated to that person's
socioeconomic status that wascontributing to that instead of
the alcohol.
Sydney (09:10):
Right.
So in the case of those studiesthey were confounding factors
like income and socioeconomicstatus.
So basically, just to defineconfounding factors, these are
other variables that caninfluence the relationship
between a predictor.
So the thing that we'restudying and the outcome,
confounding factors aretypically things like age,
gender, education and income.
So to break that down, into arelatable example.
Katie (09:33):
Let's say that you have a study investigating whether
being a Taylor Swift fan isrelated to having fewer wrinkles
.
So let's say that the studyfound that Taylor Swift fans on
average have fewer wrinkles thannon-Taylor Swift fans.
Sydney (09:47):
But unfortunately, what's probably going on in this
study is that liking TaylorSwift doesn't directly lead to
fewer wrinkles, but there's aconfounding variable of age.
So people who like Taylor Swifttend to be younger and since
younger individuals have fewerwrinkles, the observed
difference is due to age and notactually liking Taylor Swift,
Though I do believe Taylor Swiftwill keep me young forever, but
(10:10):
yeah.
Katie (10:10):
I definitely wish it was true that being a Swiftie would
lead to less wrinkles, butultimately, that's why RCTs, or
those randomized controlledtrials, are considered the best
research method, because byrecruiting participants who are
similar in terms of age, incomeand other factors, researchers
can keep those potentialconfounding factors as similar
as possible.
(10:30):
So now that we've talked aboutthe different studies, whenever
I'm reading a research abstract,how should I actually determine
what type of study it is?
That's a good question.
Sydney (10:39):
So, as a rule of thumb, if the abstract doesn't
explicitly mention that it's anexperimental study with a
control group, or it doesn't saythat it's an RCT.
It's likely an observationalstudy.
Observational studies might bereferred to in an abstract as
either an observational study ora more specific type of
observational study, like a casecontrol study, a cohort study
(11:00):
or a cross-sectional study, andthere might be a few exceptions
to this rule.
Katie (11:04):
So in addition to experimental studies or
observational studies, there'salso papers that are systematic
reviews or meta-analyses.
So in a nutshell, a systematicreview is basically like a
supercharged study that kind ofbrings together a lot of other
studies to give us a clearunderstanding of a specific
question or topic.
So basically in a systematicreview, the researcher is going
(11:25):
to go and find all of the goodquality studies that have been
done on a topic and then put allof that information together so
we can get a more accurate andreliable answer to that question
.
Meta-analyses are kind ofsimilar but a little bit
different, so I'll let Sydneydescribe what a meta-analysis is
Right.
Sydney (11:41):
So, in a similar process , meta-analyses take it just a
step further by then actuallycombining data from these
multiple studies and Doing astatistical analysis on all of
these data together.
So here's a simple explanationof how it works.
Imagine if you have a bunch ofstudies that have investigated
the same topic or researchquestion.
Each study might have differentfindings or results, but a
(12:02):
meta-analysis combines data frommultiple studies to get a more
reliable estimate of the overalleffect.
It helps identify patterns,evaluate the strength of
evidence and draw more confidentconclusions about a particular
research question or topic.
However, the strength dependson the quality of studies
included.
So a meta-analysis thatincludes strong studies like
RCTs are a more reliable sourceof information than a
(12:25):
meta-analysis that includesstudies like observational
studies.
Katie (12:29):
Whenever you're looking through PubMed or Google Scholar
, if you see a meta-analysis ora systematic review, that could
be a really good resource foryou to go to to get a summary of
all the information that's outthere on the topic.
So now just to recap everythingthat we've covered in today's
episode Experimental studies aregoing to be best for telling us
if whatever we're studyingactually causes something else,
(12:50):
whereas observational studiesobserve behaviors in the wild
and establish whether or notthere's patterns.
So, if available, we're goingto want to rely on a randomized
control trials, because they'rethe best source of information.
But if those sources aren'tavailable, observational studies
could also be great and,similarly, systematic reviews
and meta-analyses can also be areally good and reliable
(13:11):
resource.
Sydney (13:12):
So that concludes today's episode of fact.
Check your health.
Katie (13:15):
Join us next time as we teach you why the headline that
you're reading might bemisleading.
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