>>JOANN: Hello and welcome to today's webcast, brought to you by the Center on Knowledge
Translation for Disability and Rehabilitation Research (or KTDRR) at American Institutes
for Research and the University of Kansas' Research & Training Center on Independent
Living project for Promoting Interventions for Community Living (known as (RTC/PICL).
The Center on KTDRR and the RTC-PICL are both funded by the National Institute on Disability,
Independent Living and Rehabilitation Research (or, NIDILRR) in the U.S. Department of Health
and Human Services, Administration for Community Living.
I am Joann Starks, with the Austin office of American Institutes for Research (or A-I-R).
I also want to thank my colleagues Shoshana Rabinovsky and Steven Boydston, who are helping
with the logistics today.
In today's webcast, Multifaceted Interventions for Improved Community Participation Among
Adults with Disabilities, our presenters will discuss the systematic review carried out
by a team from the RTC project, Promoting Interventions for Community Living.
This review contributes to research identifying multifaceted interventions that are effective
in facilitating increased community participation for adults with disabilities.
Technical assistance from the Center on KTDRR Helped support the review team activities
in order to submit the review to the Campbell Collaboration Disability Coordinating Group.
Now I'd like to introduce our speakers as listed on the slide.
Judith Gross, PhD., is at the Indiana institute on disability and community.
Previously she was assistant research professor at the University of Kansas working with the
research and training center on independent living.
In that capacity she led the team that conducted the systematic review of multi faceted interventions
leading to community participation outcomes for a NIDILRR grant on Promoting Interventions
for Community Living.
Jean Hall, Ph.D., is director of the Research and Training Center on Independent Living
and a senior scientist in the Life Span Institute at the University of Kansas.
Nationally recognized for her research related to healthcare employment and independent living
for people with disabilities, Dr. Hall is leading the current study of intervention
that promote community participation and she will be available during the question and
answer part of the presentation.
Amalia Monroe-Gulick, MLS, is a member of the team assisted with design and implementation
of multiple library searches for systemic and scoping reviews including the present
systematic review.
Chad Nye, Ph.D. is a consultant and conducted the data analysis for the systematic review
team.
He is a former executive director of the Center for Autism and Related Disabilities and processer
at University of Central Florida, College of Public Health and Affairs and he has over
20 years experience in meta analysis and systematic reviews in the area of disability.
I am representing the center on KTDRR on behalf of principal investigator and project director
Dr. Kathleen Murphy.
Now, let's get started.
Again, if you have any questions during the presentation, please put them in the chat
box and we'll hold them over to answer at the end.
I will now hand things over to Judith Gross.
Judith?
>> JUDITH: Thanks, Joann and thanks to everyone online who has joined us today.
We appreciate it.
On the screen now is our agenda for the next hour.
First, we will discuss why one would conduct a systematic review or meta analysis.
Next, we'll talk about the partnerships that supported this research.
Then we'll discuss what we did, how we did it, and what we learned, and finally we'll
discuss the implications of our findings and have some time for question and answer at
the end.
So why conduct a systematic review or meta analysis?
So first and foremost, a systematic review provides us with a formal structured approach
to reviewing all of the relevant and best available literature on a specific topic or
outcome of interest.
It provides this nice overview of the current state of the literature.
And it is systematic in its process in that the procedures for conducting the review are
clearly defined in advance making them replicable while also minimizing bias.
A systematic review can be qualitative or quantitative, but regardless the procedures
for determining inclusion and method of analysis are still determined in advance and well documented.
Systematic reviews, the studies included in systematic reviews are screened for quality
to ensure that the findings of a large number of studies can be defined, the procedures
for determining for inclusion in the study must address both issues of content relevance
as well as research quality.
In addition, peer review is a key part of the process of the procedures in our systematic
review.
So, in order to conduct a systematic review to get that overview of the current state
of the literature, we must have some clearly defined inclusionary and exclusionary criteria,
an explicit search strategy, so one that is structured and taking into account the differences
in the databases you're looking in.
It also needs to have a systematic coding and analysis, so something that is consistently
done throughout researchers at the study.
And a systematic review should include a meta analysis whenever possible.
A meta analysis is the only one when we conduct a statistical analysis of the income and outcome
of interest.
We can use statistics to combine those outcomes and look at the overall effects of the treatment.
So, by combining the samples of the individual studies that overall sample size then increased
and that increases statistical power of the analysis as well as the estimates of those
treatment effects.
So how did partnership support this research?
When Joann was introducing, she mentioned that KTDRR had helped with supporting this
research.
So, I had previously worked at the University of Kansas with the research and training center
on promoting intervention for community living and conducting a review of the literature
was a part of their grant project plans that they had to conduct to implement their program
for promoting community intervention.
So, in that work we partnered with a university librarian who worked with the center multiple
times on other projects, as well as had a research assistant and used the grant dollars
to help fund the systematic review as required in one of our grant activities.
Joann?
>> JOANN: Thanks, Judith.
The center on KTDRR is funded by NIDILRR to promote the use of high quality disability
research that is relevant to the needs of the intended audience including people with
disabilities and their families, researchers and policymakers, among others.
Technical assistance activities are designed to support the knowledge translation efforts
of NIDILRR grantees and we provide individualized assistance for any NIDILRR grantee interested
in developing systematic reviews and research synthesis sees.
KTDRR worked with the Kansas team to submit the Campbell Collaboration Disability Coordinating
Group.
The Collaboration is an international organization that promotes positive social and economic
change through the production and use of systematic reviews and other evidence synthesis for evidence-based
policy and practice.
The coordinating groups are responsible for the production, scientific merit, and usefulness
of Campbell's statistic reviews.
The requirements of a Campbell review are considered the gold standard of systematic
reviews and KTDRR provided in kind assistance to support statistical work and research assistance
to help the team to meet Campbell's high standards.
The title and protocol for the review are available in the Campbell library and we anticipate
the final review will be published there very soon.
KTDRR staff worked closely with Campbell's disability coordinating group by volunteering
in some leadership roles.
KTDRR also has a cadre of consultants with a range of experience in providing research
and systematic reviews.
The KTDRR Web site also provides free access to numerous online resources and training
materials.
Interested NIDILRR grantees can contact KTDRR for additional information at KTDRR.org/TA.
Thanks, and back to you Judith.
>> JUDITH: Thanks, Joann.
With the support of KTDRR, we were able to take what was originally just a systematic
review, which was a part of our work on community participation, and turn it into a meta analysis.
KTDRR provided some of the consulting support that was needed to be able to conduct the
meta analysis.
So, what exactly did we do then?
So, for our work on community participation, we had actually conducted two studies as a
part of the systematic review because we had multiple research questions of interest.
First, we conducted a meta analysis of 15 quantitative studies to determine the effectiveness
of multi faceted interventions in promoting community participation.
However, it was also within our research interest to learn more about the nature of those interventions.
So, we also conducted a qualitative analysis of the content of those 15 articles, in addition
to two quantitative articles whose data could not be included in the meta analysis and three
qualitative articles that we had also found in our search.
We qualitatively analyzed the content of these articles to better identify the intervention.
The results of the qualitative study are not included in that analysis being presented
today but are presented in a separate research article.
So how did we do it?
So first we needed to define the outcome we were really looking at.
So, community participation is huge.
It encompasses many different things.
We had to look carefully and think about how we defined the terms, what was a community
participation outcome, what constituted a community-based setting?
What exactly did we mean by multi faceted interventions?
Much as we were looking through the literature, that in itself was defined differently in
different ways, in different articles.
So, we worked closely with our scientist consumer advisory planet to clearly define the target
for our very view.
The Research and Training Center on Promoting Interventions for Community Living had a scientist
and consumer advisory panel that that supported providing advice on the review as well as
helping us to answer key questions or concerns that we had with what should be included or
what those inclusionary or exclusionary criteria really should be.
So, for the purpose of this review, we had to find multi faceted interventions as an
intervention that seeked to address two or more individual or environmental characteristics
in different domains.
So, what that meant, two or more individual character livings might mean changing something
about the person such as enhancing their knowledge or skills or changing their behavior or perceptions
or attitudes.
Environmental character livings included changing something about the people, places or things
in the environment in which that person interacts.
And we specifically sought out different domains because it became difficult to think about
how to distinguish something as multi faceted, because we had a lot of different opinions
on what that actually looked like.
So, by defining it as the multi faceted intervention as addressing different domains it made it
much clearer as to what actually counted as a multi faceted intervention.
So, by that we meant that it could be an intervention that targeted, say, social skills and employment
skills or transportation and access to community, you know, engaging in community recreation
activities.
So, we're looking specifically that the intervention would address two different domains in that
person's life.
So, who did we include?
Who were the participants in these studies?
So, all of our participants in the studies were 18 years of age or older, identified
as having one or more disabilities.
So, we did not distinguish, it was not a disability specific study, it was cross disability and
when we considered aging population, disability is defined a little differently when we enter
aging populations.
So, we defined it by limitations and activities of daily living and instrumental activity
of daily living.
We also our participants another way that we chose to limit or target focus our study
was to limit our participants to those who had exited the secondary education high school
setting and services.
So specifically, this excludes transition service activities that the students may be
engaged in while still enrolled in secondary education.
>> AMALIA: Thank you.
So, the first step in the search process after working with the outcomes and participants
was to identify the electronic databases we were going to use.
So, after reviewing 15 databases and publisher journal package we selected three databases
for our initial searching, pub med, Web of science, psych and bow.
The process of building the search took some time.
We eventually decided on two search concepts, disabilities and interventions.
And the goal was to ensure that all types of disabilities that were included in the
search results while excluding irrelevant results and database provided subject and/or
classification limiters were utilized to reduce the number of results since our review search
was really broad.
For example, the use of limiters was very necessary in Web science because that database
does not have a controlled vocabulary feature.
Two additional databases, ProQuest and these sees global and policy file were also later
searched to identify potential relevant gray literature.
And the results of all searches were exported into end note and deduplicated for review
process, search strategies, and results for documented in Excel.
And now back to Judith who then will discuss the next step in the process.
>> JUDITH: Thanks, Amalia.
So, after we had conducted the search that took quite a bit of collaboration among ourselves
as a research team as well as going back to our scientist and consumer advisory panel
when we would run into vocabulary challenges.
Ultimately, we ended up with 4,742 articles from those searches and we reviewed all of
those by abstract and title and there are at least two researchers who were involved
in each review stage of the articles.
So, after reviewing those 4,742 articles, we figured out we had maybe 186 left that
we really needed to look more carefully at that full text to make sure that they met
our criteria for inclusion and met our definition for community participation outcomes as well
as determining whether or not it was a multi faceted intervention.
Out of those 186 we ended up reviewing 37 for methodological quality.
As of 37 we ended up with 15 studies, 15 quantitative studies that were measuring outcomes related
to community participation that could be included in the meta analysis.
So, when we talked about community participation we had a couple of ways in which we were defining
community participation outcomes.
So, we had primary outcomes which were those with direct access to the community.
So, things like employment or postsecondary education, community recreation activities
or housing, activities that or outcomes that very clearly were placed within the community,
that it was easy to say this is a community participation outcome.
However, in our research we know there are a lot of outcomes strongly associated with
community participation, whether it's community participation is known to be associated with
them or seems to be a dimension of community participation, such as physical health.
We know that if somebody has strong physical health they're more likely to access the community.
Same goes for being self-determined or having a social network or a high quality of life.
We looked at those other outcomes as what we consider to be dimensions of community
participation.
So, we knew were associated with community participation but maybe were not maybe correctly
located within the community.
Chad, you want to talk about the analysis?
>> CHAD: Okay.
So, we used the comprehensive meta analysis software, consider.
MA for our meta analysis aspect of it.
That software allows us to take the coding form that we use to define participate study
characteristics, outcome characteristics and analyze them according to those categories
of independent variables.
We got 74 effect sizes generated from the 15 studies.
We were able to combine or aggregate some of those data that we'll present here in a
few minutes.
The studies found some positive effects, primarily in the employment mental health and quality
of life studies.
Two other studies that met criteria for inclusion but weren't included in the data analysis
part because, but we were unable to convert the base data into metric that would be analyzable
by meta analysis process, effect size calculations.
So, our 15 studies the studies we could generate an effect size based on the data presented.
Judith?
>> JUDITH: Thanks.
What did we learn from our study?
One of the things that was fairly interesting in our findings was that much of the participants
had a disability that makes executive functioning a challenge.
Two of our studies had participants identified as having a TBI.
Seven focused on people with mental health needs, four focused on those who were aging
and having acquired disabilities with aging and one focused on individuals with developmental
disabilities and another study did not report the disability of their participants.
That became an interesting piece to observe because many of the multi faceted interventions
being used in these 15 studies were specifically cognitive coaching component.
So, it may have been something to help improve memory or increase some sort of executive
functioning organizational skills or management of some sort.
There were a number of countries represented.
One from U.S., one Italy, China, Australia, and two from Germany.
So, we had an international representation as well.
General study characteristics of those 15 studies, they were we had searched from 2000
to 2016 but the 15 studies fell in that range of 2000 to 2014.
Seventy four effect sizes were computed with a mean of five and a range of one to 22 and
the length mean of treatment was 27 weeks and that ranged from four weeks to 105 weeks:
And they don't have a detailed number because I've been struggling with getting a piece
of software to open where that data is stored but I do know in our treatment groups we had
well over 2,000 participants in total and is well over 1400 in the control group, but
there are a number.
I don't have exact numbers on that.
So, we had a good participant size to work with as well.
Chad, you want to share about our other findings?
>> CHAD: Okay.
So, a little observation.
Sometimes we looked at research and published work kind of in attempt to identify a specific
answer to a problem or clinical setting, patient, et cetera, and for a single patient, sometimes
for a group, sometimes we're successful in finding that answer.
Often though we're not because have a hard time finding a study or a result that matches
the condition we're working in.
At best we get partial answers.
Sometimes we get no answers.
What I find is that a lot of times leaders for the meta analysis are disappointed that
they don't seem to have a specific answer to their questions they're about treatment.
They only end up with an incomplete answer.
So, I'd point this out to say that systematic review and meta analysis is intended to summarize
existing research in a way that allows us to have kind of a cumulative picture if you
happen of the available research on a particular topic.
And to do it in a way that kind of focuses our understanding of what we know, what we
don't know, what needs to be done or should be done to advance the knowledge base.
So, we don't typically find a specific inconvertible evidence result in a meta analysis.
In fact, what we really have is kind of an average statement.
So, more information we have and the closer we get to some level of specificity at least
some of the time so it's that sort of mind I'm starting this part of a presentation to
say what we have here is a statement of the current state of what we believe anyway, it
represents our knowledge of our multi faceted intervention.
So, this slide shows you the individual studies, the effects size is hedge's G, smaller studies
so they are more equitably included in the aggregation of the data.
The lower and upper limits, 95 percent in the p value.
So, if you notice there are under the hedge's G, effect size, there are three studies that
have negative effects.
That's for the study.
What that is saying basically it's saying that the treatment group performed less well
I want to say that differently.
Control group did better than the treatment group.
That's probably not an answer we're looking for.
In the other studies where you find the positive effect size and a positive lower limit and
upper limit such as the Gutman study here we know that the treatment condition performed
significantly better than did the control condition of patient participation.
When you take that same principle and apply it over here, look at the lower limit where
you have negative effect sizes.
In this case about I think eight studies here have negative effect studies.
In fact, what it's saying is the result could be such that the control group would have
performed better than the experimental group.
You see that in the fact the P values are not statistically significant.
Somebody's going to ask or say, well, yeah, but the overall effect is positive, lower
limit's positive, upper limit's positive.
That comes as a result of the grouping, the aggregation.
Now, this is not data that we're going to hang our hat on.
This is kind of a personal thing as much as anything.
So, I can get a look at the individual studies and their overall results keeping in mind
that in effect what we're doing is taking a view from 30,000 feet where we've included
or not things randomized trial or quasi experimental trial, not accounting for differences in participant
characteristics such as numbers of the participants or participant classifications.
So, all of the independent variables in that form that we use to collect about the characters
and studies are just lumped together.
He gives me kind of a place to begin.
With that in mind, let's take a look at some of the more specifics and at least a few of
the ones that we have dealt with to this point.
I've set up a sample from each much these categories, a couple of design characteristics
that look at are there differences in treatment effects based on the scientific rigor of the
design, treatment characteristics, length of treatment is one that we're always interested
in and outcome characteristics here, the outcomes that were measured that showed significant
or nonsignificant differences and so the number of studies then associated with each of these
outcomes.
So, you might see here there are some studies with one or two studies.
Remember, we can do a meta analysis with two studies, but just as you would not make confirming
kind of draw confirming kind of conclusions based on two subjects in the study, we wouldn't
do that either with meta analysis.
What it does do is gives us sort of an inkling, if you happen, or potential direction, same
with the acceptable studies, we can calculate an effect size, but it's not provide us a
single result that is confirming physician.
These are the results for the employment outcome.
In our study here, we had five studies that identified as randomize trials.
Take a second to look at that one.
One study that has negative effects all the way across.
Even though it has a positive effect.
You notice the range, from a minus 1.12 to as high as a .89.
There's a fair amount of variability there but when we combine these studies just based
on the design, we still end up with a nonsignificant treatment effect.
You might say, well, what does that mean?
Well, it means that the issue at least in terms of design may be a factor in explaining
some of the results that we have generated in employment to the employment outcomes.
Let's take a look at one of those potential ones.
One of the things we wanted to look at was a method of analysis.
Did the intention to treat the ITT methodology differ from those studies that used a test
only treatment procedure?
That is an intention to treat everybody gets a prepost measure even if they don't complete
the study.
There's an attempt at least to estimate what the results would be if a person had completed
the study.
And the test only treat it means we only assess preimpose those participants who had data
available for that purpose.
Or before and after.
The intention to treat shows a non-statistically nonsignificant effect.
That is, the treatment groups didn't do as well as the groups in those studies whereas
on the test only it was a pretty significant effect and it was fairly large.
The interesting thing about this is that it gives us at least the attempt to make some
kind of a judgment here about the impact of the method of analysis, you might say if you
knew the success the intervention of those participating in the better invention, this
might employment results for people with disabilities who might has a significant impact on their
performance.
If you view the intentions to treat kind of analysis, a representative of a more real-world
representative of nature and interventions and training programs and instructions in
general where people meet the program, drop out for whatever reason then the results are
not nearly as impressive.
So that's our attempt at least to look at one of the design factors.
We looked at length of treatment.
In the five studies these were the way they broke down.
Now, one to ten weeks and 20 plus weeks is somewhat arbitrary.
It's really a four weeks for the remaining from 54 to 105 weeks are.
But there is potentially anyway the idea that the shorter interventions resulted in a larger
more effective outcome which would not be overly surprising.
The question might be raised is, yes, but interventions often take longer now particularly
when you're dealing with subjects with disabilities that it defined in effect.
These studies suggest at least there's some question anyhow about the effectiveness of
the interventions based on the length of treatment as that treatment is extended over a period
of weeks beyond 20 weeks.
There is another studies that dealt with employment results.
These were studies where the experimental group was compared to another treatment.
I call it a treatment one versus two.
We didn't include these in comparison we're aggregating across all outcomes because they're
very different approach to the assessment of effectiveness.
Think of it like this, you have treatment A and treatment B being compared but you have
no studies to know that treatment A in fact is effective, nor do you have studies that
show treatment B is effective.
These studies have taken treatment A and B and are simply looking at is one more or less
effective than the other.
The result being as you might expect there are some for which there's no difference between
the two studies and in Cook's case we got a significant difference for that outcome.
There are only two studies like this and both not significant for that purpose.
All three of them show a result but two are not significant.
So, there were follow up assessments for employment in two of the studies, however, they both
use different post treatment measurement kinds, so we couldn't really collapse them, and one
study had a significant effect while the other did not.
This is the situation where you really only have one study, so an aggregation of those
studies is probably not warranted here.
Doesn't provide us any really useful information.
Quality of life was another category where we got some significant result but is only
two studies that reported outcomes of quality of life.
One was an RCT where there was the experimental control and aging they reported the significant
effect with an effect size that's approaching a large effect.
The remaining study used the comparison of two interventions, an experimental intervention
and a comparison of treatment one and treatment two and again was not significant.
Mental health, there were only two studies.
They were dealt with, but they were both RCT.
They assessed mental health for aging patients and in this case the G is a statistically
negative result, suggesting that control group perform better than the treated group.
At least in terms of mental health outcomes we didn't find a positive effect for the condition.
For adult education or learning there was one study as a comparison study again of treatment
one and treatment two.
We're assessing social skills and tasks and interpersonal skill development in a more
formalized training program classroom type of setting with the psychiatric group, yielding
a significant group difference for these participants, a fairly large effect size.
That's of interest at least to me because the average human effect from intervention
is some have reported about a .5 standard deviation or a G.5 would be considered a typical
outcome.
So whatever is going on in this study potentially has some effects that are beyond what we might
otherwise expect at least as a reader of this or interpreter of this I'd say maybe went
to look at this particular study and see what they're doing and try to assess what it is
that might be driving that and follow that through with other studies that have some
sort of similar process or design and act to their study, their research.
Okay.
So, we got nonsignificant outcomes in these other five categories that were listed earlier
in Judith's presentation.
That is, the results did not show an advantage of the intervention in which these outcomes
were measured for the control for the experimental group that it was a nonsignificant result
or comparison.
Judith, I think it's back to you.
>> JUDITH: Thanks, Chad.
Appreciate it.
So, what are the implications of what we found?
So, we found there's limited support for the effectiveness of multi faceted interventions
but there is some performance that need for more research to determine effectiveness broadly
as well as specifically in relation to community participation of adults with disabilities.
So, as I mentioned earlier, we looked at community participation fairly broadly.
We included things like employment, continued adult learning, housing, civic involvement,
recreation, navigating the community, those are all outcomes we consider to be direct
access to our participation in the community.
But we also looked at dimensions of community participation such as quality of life that
we had mentioned or improved health.
So, as we think about multi faceted interventions with he found the most support in employment
and employment as we know has a lot of context in it that are supportive of that may require
multiple interventions to address, for instance, people need transportation to work.
There is just general employability skills.
There's also those soft skills that folks need to have to be employed narrow focus,
so maybe targeting specifically employment and
looking for a group of adults with similar disabilities may kind of focus this study
a little more for like a next step to focus maybe on those populations who need that additional
support in the areas of executive functioning and on some of those more concrete outcomes
like employment.
When we look at practice that is something else to mention.
When we consider somebody's employment in the community, we need to look at a lot of
things.
There are a lot of barriers that come up, for example, to people being employed, whether
it's accessible transportation or social skills or having work experience or there is other
actual hands on work skills learning a specific task for a job.
All of those can lend themselves to multiple points of intervention and so when we looked
at multi fast settled interventions we thought of them as things that could happen to multiple
points of intervention where we know people need support in order to get to their outcomes,
whether it's employment or living in the community.
So, with the multi faceted interventions that would be a thing to think of in practice is
how do we use those interventions to improve those skills with an ultimate goal of increasing
community participation?
And so, in considering the research on those, you want to make sure there are measures going
to not only measure the impact of the intervention but that targeted outcome we're looking for
as well.
Any questions or comments?
>> JOANN: Well, thank you very much, Judith.
We do have a couple of questions that we've received.
So also I'd like to introduce Dr. Jean Hall who's here to help answer our questions.
And the first question I've got is was there a way to distinguish if any of the groups
that develop, conducted or for people with disabilities.
>> JUDITH: So, none of the studies that were conducted were developed or conducted by people
with disabilities and none of the ones that were included in the study indicated that
there was any like support in regards to the research as far as participant participants
supporting development of the research.
So, I think that was the interesting thing to look into but that did not come up in any
of the articles that we had.
>> JOANN: Thanks very much for answering that one, Judith.
I was wondering Chad, could you clarify what an effect size is for those of us non-researchers?
>> CHAD: Okay.
Effect size is the measurement of the effectiveness of an intervention or a treatment or instruction
on a particular variable between two groups.
I sometimes use the aspirin ibuprofen model.
Does aspirin work better than ibuprofen?
Well, I think ibuprofen is the only thing to use.
My wife think it's aspirin.
We fine the studies that have a compared ibuprofen to people who didn't take anything for their
headaches.
I hate headaches.
My wife finds all the studies for aspirin and sure enough we find out they both are
effective.
So, the effect size at least is saying those two medications or headaches seem to work.
The assessment of the effectiveness of ibuprofen or aspirin then is another level of study
where you compare subjects who have been treated with both does one work better than another.
So, you got two levels to kind of think about, the effect and effectiveness of intervention.
>> JOANN: Thank you very much.
We also had a question about the interventions that you discussed earlier, Chad.
Can you give some examples of what some of those interventions were?
I know it may be a little hard to pull them up, but that is the question.
>> CHAD: I think Judith can probably define that better than I can.
>> JUDITH: Sure.
Yeah, I can give you a couple examples.
So one example would be there was a study focused on improving employment outcomes and
it had a vocational services component and it was working with veterans who identified
as having mental health needs and there was also a cognitive study component of it that
helps work on things like time management, organizing and planning and kind of being
able to being structured tasks.
That helps with that cognitive component that we've discussed.
There were other studies, let me see if I can find another good example here.
So, have another study focused on individuals with brain injury and it has outcomes on mental
health and it was trying to improving patients' access to the community and trying to think
of some others here.
Let's see.
Find one that's not employment.
We have so many that's focused on employment.
Oh, the supported education one.
That focused on I a adults with psychiatric disabilities and that incorporated a have
a supported education program so it incorporated some occupational therapy services and focused
on helping individuals who attended to be able to manage some of that the level of organization
that was needed to complete the program as well as support individuals to participate
in the program.
Some of the occupational therapy skills focused more on that executive functioning again and
helping folks to access the services and participate in education.
>> JOANN: Great.
Thank you.
Here's another question.
What would you suggest to researchers designing multi faceted intervention studies to make
sure that they can provide evidence of efficacy?
>> JUDITH: I would say making sure you have good measurement tools would be one so that
you're surely measuring the outcomes of interest and the impact of the intervention.
Chad, recommendations?
>> CHAD: Yeah, that would be a prime consideration.
I think the other is to define the population carefully and in the area of disabilities
it's not that you can do that with exacting, but you can describe it so that selection
is better characterized, I guess, for the reader.
I think you also need to look at the real question that's being asked and whether or
not the tools that you would use for assessing the nature of the outcome, quality of the
outcome are really appropriate and are really good tools.
There's some debate in the literature about whether or not standardized measures should
be used over observational.
In part that's kind of a clinical practice question.
If you don't have good tools at a standardized level then you have to deal with what you
have.
Measurements important and design preparation is important.
How you handle dropouts, how do you handle people that don't complete?
Do you have enough subjects in the data pool to be able to generate the kind of results
you're hoping for?
>> JOANN: Thank you.
Judith, did you see the follow up question about the social skills intervention if you
recall if it was a CBT and also if it's impossible to get sole citations of the articles included
in the review?
>> JUDITH: I don't remember if it was a CBT, but yes, we can make sure that you get full
citation.
>> JOANN: Okay, thanks.
We've only got about four minutes left here, but I think we can maybe squeeze in another
question.
What research gaps do you think are the most important to address in the near future?
>> JUDITH: I think with regard to multi faceted interventions there's just not a lot of research
that's looking at interventions in this way.
There is and how we define it is different.
So, there was one other systematic review in I think it was the Campbell collaboration
library that covered multi faceted interventions but was defining them differently than we
did.
So, I think that part of that would be as we're looking towards how do we use multi
faceted interventions that can help us to address, you know, the person, environment
context issues that just making sure that we're figuring out how we can clearly define
that and having consistency in that across studies.
So, it's a multi faceted I know it's one we as a research team really struggled with,
like this multi faceted or not.
And sometimes we went round and round in circles trying to sort through that.
So, I think clearly identifying that piece of how people are defining multi faceted,
we found that we had to get very specific in breaking that down and then really seeking
out opportunities to test whether or not multi faceted interventions are more equative.
Because we know that there are so many points in time that there's never just one factor
that makes something work, right?
Our research is designed often to test one variable here or there but there's often so
many things that so many factors and so many contexts that feed into somebody being successful
or an intervention working well.
I think that clearly tapping into that piece and trying to parse out whether or not multi
faceted interventions are truly impactful for which populations are they impactful.
So, majority of our studies tended towards individuals who needed some help with executive
functioning in managing tasks or organizing their day.
So perhaps that is a key population to start this more focused research with.
>> JOANN: Okay, well thank you very much Judith.
We are just about out of time.
I see we have one more question.
I don't know if we can squeeze that in.
What quality of life measurement tools were popping up most frequently in your analysis
of content for populations with disability?
>> I don't remember.
I'm sorry.
>> Okay, well maybe that's something >> I can look them up.
>> We can follow up by e mail after this.
We will be sending out an e mail to everyone once we have this ready for archiving viewing
and so we can answer that question maybe at that time.
So, I want to thank everybody for being here today.
And that's especially Judith Gross, Amalia, and Chad Nye for sharing information about
this groundbreaking systematic review and for everyone who is registered we will be
sure to let you know when the final review is published with the Campbell collaboration.
We hope you'll take a few minutes to give us some feedback about the webcast by filling
out a brief evaluation form.
The link is here on this slide.
It will also be posted in the chat box and we will send out that e mail with an evaluation
link for everyone who can't get to it today.
So, I want to thank everyone for coming today.
I also want to thank the AIR and University of Kansas staff who helped with planning and
logistics and of course we want to thank NIDILRR for their support to offer these webcasts
and other events.
Look forward to seeing you at the center's next event which will Thursday November 1st
at 1:00 p.m. eastern.
We are hosting a preconference Webcast entitled KP101 an introduction to knowledge translation
or how to become Impactastic.
We also want to invite you to register for our 2018 online conference coming up next
week during the afternoons of Monday, Wednesday, and Friday November 5th, 7th, and 9th.
Please visit our webcast at WWW.KTDRR.org for more details.
Good afternoon and thank you very much.
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