How to Improve Services to Minority Populations: The VR Perspective Presented by Chrisann Schiro-Geist and Emer Broadbent Please stand by. We are waiting for our speakers. >> LAUREL: Good afternoon. This is Laurel Richards with ILRU in Houston. Welcome to our webcast today. We've got an excellent topic to cover relating to increasing services or improving services for people who are typically underserved or underrepresented in programs serving disabled people. We have an important set of points to cover. First I want to give you just a bit of information on the mechanics of this website. Being live, there is always unexpected things to cover, lightening storms or just being dropped out of the webcast. If that happens and you sort of get disconnected, you can try to get connected again the same way you got on in the first place or you can call our office. We have got people on standby to provide technical assistance for anything you need. 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For those of you who are in the future who are reading this or listening to this from our archives and it's quite often there's a big level of traffic for us for people who go to the archives and listen. Go ahead and call that technical assistance number to. Captioning is being converted to text so it can be read along with it as a transcript. Now you will also notice on your Media Player that there's a place if you have a question, I think it's on real player it says click here if you want to submit a question. What happens is if you have a question during the presentation, you click that button and your software program comes up, the one you use for E-mail. It's preaddressed to webcast@ilru.org and you have to type in your question. Then hit send and it goes to our staff, when the presents asks for questions they'll get them at that time and Smith as often as you want and we will get to them when we can. Today's presentation is how to improve services to minority populations. That's people who speak different languages or English is not their first language, people who are from different ethic backgrounds than traditionally. In many cases, it includes people who live in rural communities and people who are isolated in rural areas. Now the presentation is going to look at research findings from the point of view or the arena of rehab. But, in fact, the information is going to be applicable to not only rehab counselors but people working at centers for independent living and other service providers. It's universal type information and it's going to be very useful. Our presenters are Chrisann Schiro-Geist and Emer Broadbent. Chris is senior vice pro vest for academic affairs at University of Memphis. And a full professor in the department of counseling, educational psychology and research. Emer is assistant professor in social work at University of Memphis as well. Emer has a double, a master's agree in social administration and a law degree. I think your shot first Emer, if I recall correctly from Shakespeare. First let's kill the lawyers. I would like to turn it over to the two of you to take us through this very important presentation on a subject that has always been of high interest to those of us who work in living fields and I know people working in rehab and medical and vocational rehab. So please, Chris and Emer, welcome to our webcast today. >> CHRISANN: This is Chris. I'm going to do most of the talking because Emer is not feeling real well today and his voice is not real well with. I'm going to ask him to jump in when he feels strongly about something and want to participate. >> EMER: Thank you Chris. >> CHRISANN: And hope apply we will get through. This is a project that Emer and I have been working on for quite a while. It's a project that originated as part of the institute at the institute of Illinois at Urbana-Champaign. But the piece that's important about this is the whole concept of what are the psychosocial variables that identify somebody who really is interested in returning to work. Let me give you some of the history of this. Our colleague from RUCKERs university. He is the prime move behind the creation of the ticket to work. I'm sure many of you understand that it is the program that the Social Security administration created to help persons who are receiving Social Security and SDI benefits move from benefit takers to people who would be in competitive employment and taxpayers again and getting back into the system. For years we have known that few people move from the Social Security aid recipient positions back to competitive employment. When they have done studies, it usually comes up that less than half the people come off of Social Security roles because they are competitively employed now. People do come off the role because they die or other things about their life changes in one way or another. But competitive employment has been way down the food chain. So along with the ticket to work legislation which was passed in 1999, which is an incentive program using for profit employer networks to help people get people with disabilities back to employment. People receiving SDI benefits back to competitive employment. In that law was embedded that there would be several studies done to study the effect of these various expensive and well-put together programs. Social Security wanted to know if they were going to get a return for their money for investing in the program. One requirement was there be a study done to what would happen if you intervened early in the process. Before someone actually got their benefits, but while they were in the process, they were applicants for benefits but not received them. What if you started looking at those people because the belief is once they Centerpoint Energy the benefit they don't have the incentive to work. But work with them while in applicant status and likely to get benefits and can you get them back to competitive employment at that stage? That's what they mean by early intervention. We have to clarify that because when we say the word early intervention a lot of things come to your mind. But this is very specific early intervention in the process of helping people to get back to competitive employment while her seeking simultaneously to become recipients of support payments. Anyway. We to understanding some of these legal man dates to delivering these services. That would be all part of the ticket to work mandate. The importance of early intervention strategies for enabling people with disables to gets back to the labor mark and the methodologies to identify applicants who are already disabled but they could get back to work. So at the research institute at Illinois we had to come up with and that was how to determine if you were a person likely to receive benefits. They look like they are going to be severely enough to receive benefits but also people who could work on a program to return to work. So in spite of the research of the return to work it's shown little progress to get back to work. Because the disability research institute has funding, it would be a likely application to create the program of how this intervention would happen. So we were given that assignment and Emer and I were assigned to the part of that that would develop this criteria for participation in the program. How could we help pick the people who even though they were disabled would be good candidates to return to work. Of course, the act itself, to refresh your memory on this. It was credited in 1999 and signed into law. It increased the beneficiary choice of obtaining more options for rehabilitation and vocational services. It removed barriers that required people with disabilities to chews between health care benefit and is work. So if you remember part of the ticket to work act was to keep people to keep their medical benefits up to eight years after their return to competitive employment. This was very important because over the 20 or 30 years before, the ticket to work was signed, consistently what we would hear when we had focus groups and brought consumers of services together, well, I would go back to work but I'm afraid to lose my medical benefits. So part of the ticket to work act if it was going to be successful had to be protecting those medical benefits and it does protect those benefits for up to eight years. A person can stay on Medicare or Medicaid. If they had work, they will be on the insurance plan that their job provides. Also the ticket to work incentive act assured that more Americans with disabilities would have the opportunity to purchase in the work force and get their benefits. So this particular early intervention project would identify presumably the disabled candidates to return to work. It would persuade such candidates to participate in the return to work and get benefits. Who would provide the service and is how would they be paid for and the relationship of this project be? So the economist used real data and looked at the last three years of the Social Security administration and they created some models. They love to create models. So they created a model for selecting probably beneficiaries, selecting people who would be likely to return to work candidates and the project in its completion would provider assistance to return to work. We're going to skip to the very end but let me tell you those projects are actually happening in some states right now. But this was kind of how we got there. It's important to understand how we got there because we don't yet know if outcome but getting there was important. So the first task is to decide who are about likely to become candidates. They looked at administrative data. They looked at family income, the amount of money that they have working. They looked at real cases to create the models. How much money were they getting from Social Security and the ultimate ares of the determination. They looked at medical information and treatment history of the people who had applied in that three-year period before the project was initiated. They looked at whether they had disables of drug addictions and tests they had taken in the last years and the disability codes and what were the second and primary diagnoses. What the words said about the client. A lot of times we get busy checking boxes on forms and we don't look at the content of what's actually in these files. And they're wonderful techniques where you can scan them into a computer and let the computer search for you. Some of this was only possibly in 23002 and 2003. I would take years to reach the conclusions they came to. Another thing they looked alternate was the past employment of the people who were recipients if they had past employment. They looked at how much they had earned, what weights they lifted at work. Their bending, lifting, requirements had been. They looked at the job descriptions. How long they worked and whether they had skills, job transferable skills. They looked at the training ask educational levels. If highest educational level and if they had attended vocational school. The age, gender, marital status, number of children, whether they were divorced or not and race. Then a whole bunch of other activities. Could they do household at this times, recreational activities, social limitation. They were interested in the time when the disability started and when the person stopped working and the time from onset of disability as perceived by the clients and when they filed for payment. So a variety of information. Medical, educational, demographic and miscellaneous. And they started to build the model. It was the create the model for becoming a beneficiary. When they looked at all that stuff the things that were significant were the age. Obviously, the older they were they would get benefits if they were closer to retirement age and the age which they became disabled. They looked at their earnings. It's obvious to Mae but not to everybody, if the person is going to receive as much money, receiving disability payments as they did when they were working, what's the incentive to return to work because you go do have the limitation of your disability. They look at the functions of your disability. They looked at whether they had a mental impairment or just physical impairment and when the first started and when they stopped working. When they got the disability and when they stopped working was significant. So they started stream instruments and what predicted them was the probability of being a beneficiary by using the data points I talked about and so you could take a new case. They looked at the old cases and said you can take a new case based on this model and put in age, whether or not there was a mental illness, date of stopping work, number of functional limitations and the probability of becoming a beneficiary. That took that activity even with the modern technology and the scanning and the ability to use high technology took about a year. What they decided was they didn't want to use probabilities that were low. I mean, if the probability of a person receiving benefits were 50/50, then they wouldn't be good candidates for the study. So they decided to set the probability of becoming a beneficiary at 70% or higher. So the people allowed into the study were those who had a 70% chance of getting benefits using the formula. So the excitement here was this was the first time this piece of the law, which was not the part of the law, but part of what was signed into law in 99. Any other return to work activities at that point in time would have been about 2003 when we started working on this. You can start working with people after they started receiving benefits. That's a problem because once people are getting those monthly checks, there's a big disincentive right there to not give that up. Health benefits was important but getting the money was a disincentive in not taking a risk. Now the other thing you have to remember is that in the Ticket to Work Act, if people work with an employer network or a provider to try to get back to work and they were not successful, they can go right back on benefits. They don't have to start the process all over again and wait a couple years to get back on benefits. So that was another incentive. This piece of legislation without the whole ticket to work legislation would never have worked. So we had to start with the whole package. So, some of the incentives they were going to offer to these applicants was cash stipends, and getting them while working to get to work. They would get Medicare and Medicaid immediately without having to wait for it. And actually the people who are in the real study are all SSDI, so they all would be receiving Medicare. That's the easier group to work with because they have a work history. And then they would have to agree to participate in the demonstration. So they wouldn't be randomly assigned. Other benefits is they would aid them in return to work. For instance, if they needed some medical assistance or needed a job coach or whatever -- pretty much a lot of openness of what benefits would be given and paid for by Social Security to these people who are volunteers for the study. So, also in the study as it is finally now happening, there's a control group. There's no bad things being done to the control group. They're just following the normal path that they would. They are available to work with an EN just like everybody else is. The other would be to set up a treatment model for return to work. The hope is when this project is completed is that it will really revolutionize the determination process. It will help us intervene at an early stage and maybe change the course of people's lives. This ability to predict whether a person is going to receive benefit and is therefore labeled disabled was a wonderful piece of research in itself. Under the Social Security act, the definition of disability is limited to the inability to engage in substantial gainful activity, which now is about $850 a month. If you are working and you are receiving more than $850 a month, you are not going to be eligible for benefits. That's an important thing to keep in mind also. The next thing was how do we pick the candidates? How do we pick the people who are likely to receive benefits will also be interested in returning to work? So this is where the -- where we come into the study in determining some of the variables that are involved in picking these likely candidates who in spite of the fact that they have a disability but will want to engage in a program of back to work. One thing is we have to make sure that, again, these people know they are part of a study. That they are assured of their ethical situation that they are making an informed choice. The whole project had to decide what was the maximum you could spend on a client and then what would be the number of inducements do get them to join. There were three models that are piloted. A community support model where a person would be blazeed in a tentative employment place. One would be innovative model and they would get anything they asked for and another would be a contingent fee. You couldn't spend more on the project than would be reasonable profits to the government. That's all happening and being decided out there. One thing, why do we just have to pick likely applicants? Why not pick everybody and randomly assign them to these projects. There's a legal issue. First of all, you can try this with people who are at least presumed to have a disability. Like if somebody walked in the Social Security office and signed up and had no disability, legally you couldn't work with them at all. So you have to make a presumption of disability. You have to have some data about the mental and psychological problems. If you did it that way, if you just gave this project to everybody who walked in the door, then they would be like a rehab agency. Not really doing anything different from our rehab. Taking people with a disability and having to provider some service to them. So as we said before, the algorithm to select the person was created and we also had to come up with some selection method for who would get in the program and be set by field persons. We had to be able to work with information that was easy to get and easy to substantiate. We worked with demographics. Again, they worked with the nature of the disabling condition and the new piece was motivation to return to work. And a couple things that were important was the participate voluntary and if there were benefits the person would sever it at the end of the study and of course, the probability of getting a job and what would those jobs pay if the person did get them. Again, the difference between the amount of money they are getting and the incentive of the job have to be pretty close at least if not the pay being the job higher. So there are all sorts of ways we work on insuring ethical informed choice. Neither the applicant nor Social Security should be disadvantaged by any of this research and the kinds of incentives had to be decided again. Would they give them cash, insurance, et cetera and of course, the person to stay with the program in the pilot stage. Again, the person who was going to be put into this -- the government couldn't lose money either. So that was really important in the long run. So we talked about the three models. Emer, any comments while we move forward? >> EMER: It was interesting to work with the economists and to try to figure out the difference between their ivory tower. They (inaudible) >> CHRISANN: That's their job and that's why they partnered with other people. So anyway, we looked in the literature and we found 20 questions that seemed to be coming up again and again in various studies that were motivational questions. Then we pulled together different focus groups in stakeholders in the Social Security determination process. We had groups of beneficiaries that we talked to, we had rehab personnel we talked to, we had community service providers, we pulled together script from the health determination places, the medical decision-makers, quality assurance people and the office of hearing and appeals and a group of claims representatives. We presented them with the 20 questions and we talked about the questions and we said, what else other than these questions that we got out of the literature would you think would be a motivational question we could ask somebody that would help us predict who would be likely candidate toss return to work. Surprisingly after we worked on this for six months, our numbers increased up to 38 questions. So we now had 38 questions to determine whether it was acceptable and reliable. But our colleague, the economists said it was way too long. They didn't want 38 questions because they would never get people able to administrate that at the field office. You need to get it down to about seven questions. Five to seven questions at the most. So the next thing we did was talked about those questions and had a group of people from the Illinois vocational rehabilitation services central office help us with them. We had hypothetical studies that were taken from real cases and we mixed them up so people didn't get the same cases. There were two male and two female cases. One a high probability and return to work, moderate probability and one low probability. And we said if you read these case and is look at these questions, which of them would predict the outcomes? And each person got two cases randomly assigned. So the respondents read the case studies and completed the instrument. We got a high return to us in the cases. So we prepared the data analysis. We did the correlation coefficient and we did data reduction down to eight items, could get it down to seven, so we got it down to eight items which weighed on seven factors that accounted for the variance. So now you are waiting for what the factors are? Here they are. About 30% of the variance in the return to work questionnaire are people who answered questions about motivation and willingness to go back to work. So if the person answered in several instances that they wanted to go back to work or they were motivated to go back to work, that was the most significant factor. People actually say I want to go back to work. >> EMER: Don't forget, this is a test. >> CHRISANN: These are the disability determination people predicting the outcome. The second variable is satisfaction with and stability of past relevant work. So if the person -- hypothetical person had a consistent work history, had worked before, had worked without a lot of holes in their work history and had been satisfied -- the questions they endorsed had to do with satisfaction. What was the next variable in terms of weight. That accounted for about 10% of the variance. The next one was if the person really saw themselves as a person who could accomplish something and an effective person. That accounted for almost 7% of the variance. The next variable was positive orientation to work for money. The question had to do with whether you want to work and make money or not. If people saw paper money important to you it accounted for over 5% of the incentive. The next one was adequate medical care. If they had adequate medical coverage they would perceive as successful. On the ticket to work, this was not an issue. We were predicted for people not yet receiving benefits but applicants. The next one was skills. People who were perceived to have skills that they could transfer to work situations. That was about 4%. One we thought that was really fun and was almost 4% of the variance, but if they were not involved in a lawsuit. I think you could see if you were applying for benefits because you had been in a car accidents and having a lawsuit, you might not be as enthusiastic in returning back to work until that lawsuit was resolved. Or if it was a workers comp, that might affect your willingness to participate in the return to work activity. So the next step then, was could the -- did it have validity to it in a hypothetical situation, could we really transfer this to live respondents? So the next thing that has taken us about three years because we took people at intake and followed them through the placement was using real applicants. We were just very lucky to have the state of Iowa state of disability services agree to help us collect the data so we had over 700 respondents from the state of Iowa that participated in this. We had staff training where we went out and trained the rehab counselors how to administer the instrument and go through the direction. This was done at the time of intake. In the course of that summer we had over 700 who agreed to help us and agreed to be part of the study. This was a pretty large data base compared to what most of our colleagues get to work with. We did a couple interesting things. That first summer before anybody was actually placed, we also had the counselors who were the administrates predict if this client would return to work. In effect, they were predicting whether the person would go back to work hypothetically. So just give us a yes/no if the client would go back to work or not. Then we followed the clients for three years until it was likely that most people would be done with their services and would be working or not. I'm going to let Emer talk a little bit if he's feeling up to about some of the nuances that he noticed because he did more staff training and closer to the actual data collection. You want to talk a little bit about that? >> EMER: Sure. One thing I thought that was good about this was the enthusiasm of the VR counselors. They wanted to be involved, they wanted to be a part of something that might help their consumers. I thought that was very positive because sometimes, you know, my perception is that VR counselors are kind of jaded. What else can I tell you? We had the instrument administered for three months and close to all of the new entries into the IOF system in that three-month period of time was important for us to have that sample of people who started at the same time so that we could follow them until the logical time that they would be done with rehabilitation. >> We should stop to see if there are any questions at this time before we get into some of the findings. >> LAUREL: I think Sharon is collecting questions. >> SHARON: There are no questions at this time. >> LAUREL: I have some but they can wait until it's a bit later. >> CHRISANN: Of course, we had great results and we had one paper published about just getting to the point of the hypothetical and that period in rehab. This has been a very long, long project to get it done the right way. But the paper that we're working on now that we are preparing for publication is the result of the data that was collected over the three years. But one of the interesting things that happened the first summer when we collected just whether -- based on the predictors that we had whether there was any correlation between them or whether the clients would go back to work. I guess when we looked at the ones who had gone back to work in that period of time was about four months. There was no correlation. The prediction that both rehab counselors made and whether they returned to work were not correlated. So sometimes they thought the person was going to go back and they didn't and sometimes they said this person is not going to return back to work and they did. At that point in time without having the benefit of the whole picture, it was really hard to predict. It was impossible in the study. We had about 500 of the rehab counselors respond to that part of the study. Anyway, we were not daunted. We kept chugging. So just to give you some of the flavor of what we have found out after three years, one is if the customer was receiving SSDI as opposed to SSI, there was a weak relationship to the customer being less likely in the work force. So the money piece was a huge disincentive. In Iowa it was working well. They were working with providers to make sure they were receiving the services they needed to return to work and sharing the profits. So one of the states the ticket wasn't going over well because the VR was close to it. There was a very weak relationship between return to work if the person was receiving SSDI, which was the higher level of benefits. They get twice as much as people who get SSI. So again, fur receiving a decent benefit and getting say a couple thousand a month, there was a weak relationship in returning to work. This is not a big surprise. I'm sure those who work with clients that it is a critical issue. I think we need to take it into account unless we are going to be able to provide jobs that are more sophisticated and can really be perceived by the client as an improvement over their situation. If money received in disabilities is a disincentive. Another finding is that people who received the ticket were about 40% as likely to end up in the work force as people who didn't receive a ticket. Emer, you want to tell us about that one since you were looking at the data? >> EMER: Yeah, um, in other words, if you have a ticket, you are less likely to go back to work. >> CHRISANN: So this is the one that's comparing -- this one you were comparing ticket recipients versus people who were receiving services who were not eligible. >> EMER: Correct. I don't know the why of it but getting the ticket seemed to correlate with them not returning to work. >> CHRISANN: We can hypothesize about a number of things. If you had a ticket, it meant you were severely disabled to the level that you had been adjudicated unable to work in the national economy. So ticket takers were more disabled than a client who is not a ticket taker. So one issue here is the client is more disabled and the medical conditions are more likely to prevent them from returning to work than people who are severely disabled but less severely disabled than those who had tickets. So in the VR system we have people who are disabled and not receiving SSDI and SSI benefits. If you had a ticket, you were severely, severely disabled. Whereas other clients in the VR who were not ticket recipients were eligible by the nature of their disability but not as severely disabled. So it could be the medical condition itself that is giving us that facts. Or it could be giving us the financial disincentives. If you were a ticket holder with some income and you don't have a ticket holder and don't have income, you might be more willing to go back to work. >> EMER: Right. One of the problems with research is you can believe you have the understanding of what the relationship is but you never really can tell why things don't happen. There is no relationship. It's hard to pinpoint what it is that keeps it from happening. >> CHRISANN: Another finding is there is a positive correlation between age of the client and competitive employment. And that the older the client is -- other than retirement age -- the more likely they are do go back to work. This one could be connected to the way we provide services because if we have a younger client, often the tendency of rehab is to send them to training or to college or community college before they place them. In voc rehab the counselors have the luxury of providing training services so maybe they'll keep those clients four years -- nobody in our study was more than three, but they might be in a training program. So youth did not necessarily predict a quick return to work. Whereas if you had a client who was older, say their mid-40s, you might say well they have some skills and could go into placement. We know the correlations but not the causality. It's not a surprising finding in finding out the different placements we get from the ticket and those from rehab would be much more likely to train them to a training program in rehab meaning there would be closure eventually because there's a training piece to it but delayed the closure. Whereas the ENs would want them to go back to work as quickly as possible to get their fees. >> EMER: Also, what is the different between a young customer and an old customer. A young person may have a severe condition earlier on. If someone who is young who is coming into the system is more likely to have a severe problem -- >> CHRISANN: Because they are identified at 16 or something. And one of the differences could be the issue of a disability that you had to overcome all your life rather than an acquired disability. Some of those very basic social factors around that. One finding that I think is interesting was that gender was not correlated to success. Men didn't get jobs more often than women, nor did women get more than men in the study. Having the ticket, as we mentioned was negatively correlated to returning to work and we found no racial differences between the subpopulation. Of course, Iowa is not a state with huge numbers of minority clients but that was accounted for in the way that the study was done and in the statistics. So we didn't find any racial differences, which is interesting. Often we make assumptions about people who are a minority status and in this particular approach when we were using -- looking at return to work issues, there were no racial differences. Emer, you want to comments some more on some of the findings at this point? >> EMER: I guess nothing more. We asked questions that resulted in more questions that I hope we will have the opportunity to continue to explore. I would like to see this study replicated in a state like Tennessee, where we are now, that has a lot of difference -- I would like to see where we have more differences in ethnicity, in education and overall economic climate. I think we would see more differences. Excuse me, I have to cough. So I don't think we can move on this with. >> CHRISANN: I definitely think it's time to open up to questions. >> SHARON: There are no questions at this time. >> LAUREL: Just a quick question, just a couple. >> CHRISANN: You wanted to ask about the economics part of it? >> LAUREL: I wanted to get back to the point where the breakdown of 5% people would want to return to work for the money and 5% with adequate medical care. The factors that predicted factors for people wanting to return to work or being able to return to work. The last one on the lawsuits I didn't get the percentage on that. >> EMER: 3.8%. >> CHRISANN: Don't forget the fact that it pops up at all, it is more significant than the rest of it. It's a smaller weight but it's still a significant weight. So it will be interesting -- that piece alone you can have a nice paper on it. >> LAUREL: I think the third one was it 7% on self-efficacy. >> CHRISANN: It's a psychosocial variable where they see themselves as effective. They can make changes in their life, they are not helpless. >> EMER: They are capable of providing for themselves. They don't see the world as dictating to them. They can decide their own fate. >> CHRISANN: Closer to control rather than external. >> LAUREL: The in project. >> CHRISANN: I think this beautifully reflects many of the values that we hold in the independent movement in terms of seeing yourself as an effective person and wanting to change. The high weight on the motivational piece. >> LAUREL: And it reflects the surveys about people wanting to return to work but were apprehensive about loss of benefits of different kinds. Now just to recap, am I correct that the model was produced and then was it about several counselors then made these predictions? >> CHRISANN: Well, the piece that we did in Iowa, the counselors -- the people who administered the questionnaires said right now before the people go back to work, do you think based on their responses to the questionnaire that they are going to go back to work or not? 500 of the 700 filled that out and unfortunately they could not predict. >> LAUREL: Isn't that interesting. >> CHRISANN: There was no correlation between -- I mean they couldn't pick it out positively or negatively. So we couldn't make assumptions. These counselors were making assumptions about which clients would go back to work or not. We have to trust the system that if we created a good plan, it almost has its own outcome. Or there are so many other variables that intervene from the point of intake to the point of placement that that may really confound the issue. The person maybe highly motivated and feel they are capable of making changes but maybe there are some external forces keeping them from working. Maybe a medical intervention. >> LAUREL: The factor of the counselor, I'm sure it must be difficult to divorce what your basis of assumption from helping and making a decision about whether one would be successful. Presumably this has impact in day-to-day operations for rehab counselors. >> CHRISANN: I think so. The fact that we have this large database that we are working with is different. There are a lot of these studies but they are usually small, 30, to 50. So if you have 700 pieces of data and have the counselor predictions on 500 of those. I think this is the kind of thing we need to write several papers on. Right now we need to get the other one done. >> LAUREL: Are there applications regarding policy that come out of this? >> CHRISANN: This was really paid for as a policy piece. The idea was to be able to have a policy around who would be the first people to receive these pilot programs and how could you ethically predict the correct people to let into the study or not. There are pieces and the pilot programs. Now if the pilot programs are successful and if indeed the protocols turn out to be ones that are reliable, it really could be a way of deciding who would be let into high-risk programs in terms of spending more money on them rather than the usual amount that's spent. If you could invest a little more money and move the person along faster into their approximating in the their search for employment I think that would help. What's the point where you are spending the right amount of money and getting the right amount of return on it. Emer made an interesting comment. You don't think about people with disabilities the same way. But they think about them as projections and numbers, not necessarily -- >> LAUREL: I think of people with disabilities I think of the rest of us human beings. >> CHRISANN: I think getting to the break even point is a critical piece because that's how they justify what they do. Where sometimes there are tangibles we talk about. Like a longer relationship with a younger client. Maybe a piece that's a real factor that gets them back to work. You might be encouraged from an economic perspective to give up too soon. >> LAUREL: The economists of this team did they -- >> CHRISANN: Some bought into your motivation piece and some were well we'll put this in because it's politically correct to do that. We convinced them when we applied for the money. But I would say they ranged from people thought the most important part and we'll do a motivational piece on it, too. >> LAUREL: The lack of correlation between the model and what they anticipated would be the predictors -- am I correct after the three-year study they weren't accurate or they weren't totally based -- there wasn't a large correlation? >> CHRISANN: We did the prediction after two so there was no correlation. The people who actually found jobs were not necessarily predicted to be the ones who went back to work by their counselors >> LAUREL: What does that mean to the study or the model? >> EMER: What does it mean about practiced wisdom. Or is it wisdom just to recognize that people's capacity is beyond our ability to actively predict that we need to rely on the individual's volition -- and open-minded with each person with whom we work. >> CHRISANN: I think the bottom line is you should never cut anybody off too soon because it might just be a couple more months of service that will put them over the edge. We can't predict -- we can predict with these factors, a statistical prediction but a human person counselor cannot necessarily predict. It just talks a lot to limitation. The other thing is when we discovered these principles, we used them. The one I commented on, if you are shooting too low and talking about getting them into a minimum wage job, it looks like from our measurable piece of the study that they are not going to do it. They're not going to go back to work if they would only make 2 or 3 thousand more than they would if they stayed at home. They have to make money for the incentive. But use the factors in the study, the findings in the study rather than your assumptions about people. So just getting somebody back to any job is not necessarily going to be -- even though it might be a closure to butt a person back to a minimum wage job, but it's not going to get them off benefits based on what we came up with. So now they'll have their permanent lifetime noncompetitive job making working just to keep them so they don't lose their benefits. Is that we want for our clients or maximize their potential? >> LAUREL: And get benefits. >> CHRISANN: Right. >> LAUREL: I was amazed about the project where they put in the onset and the data points and you would come out presumably with -- well these people you can take first because they scored higher, et cetera, did they see that as widespread application? >> CHRISANN: One thing that is acute about that model is because it in a formula is you can make it a strong predictor or a weak predictor. The study being piloted in five states now they went with 70% chance that you would get benefits. If you wanted to be really safe, you could move it up to 90% sure but you would have less people to work with. So they can then manipulate the formula to let more or less people into the study. If you want to be really safe and go 90% sure, unfortunately then, because it usually means the disability is more severe, you might get lower on the motivational factors. So you have to play between the two. The physical and financial variables against the motivational factors but you can adjust the study any way you want it. You can have a higher rate of prediction or lower rate of prediction. >> LAUREL: That's interesting. The model is pretty neat. How long when eligibility determinations are made for SSI or SSDI, is it a fairly lengthy process? >> CHRISANN: Some people wait up to two years from the point of application. Sometimes even longer than that when the hearings and appeals process is backed up. About 40% of the people getting their benefits initially because their case is so clear. But the other 60% wait a long time through the various steps in the process and if they have to wait for a hearing, it can easily be over a year unless the case is expedited. One of the reasons the ticket to work was set up with this automatic return was so that people wouldn't have to go through all that waiting again. So if they choose to work on a return to work program and it fails for whatever reason, they get sicker or they can't make it to the training program, or whatever, they go right back on benefits. They don't lose their benefits while they're trying to get back to work. Even if they go back to work and they don't succeed, they'll go back on benefits immediately. >> LAUREL: That's a terrific piece. >> CHRISANN: I don't think they could have done it without that because just almost nobody would that I can that risk otherwise. >> LAUREL: Do we know how the ticket to work program has faired since 1999? >> CHRISANN: It's up for reauthorization and the word on the street is it will be reauthorized. Some people were worried that it wouldn't make it. But there's been some changes in it. The amounts of money that the employment networks have been adjusted to make it more of an incentive. That's been improved. It's real sporadic. Where people have embraced it, it's been very, very successful. In states where there's been opposition to it and most is from voc rehab because they see it on an infringement but we were lucky with Iowa because that's the state where it's done quite well and it's worked successfully for the good of the clients. >> LAUREL: Wish they had a greater mix of diversity. I'm with you, Emer, going to Tennessee. >> EMER: I think we could get much more interesting information here, especially having to do with minority status. >> LAUREL: What's the next step besides writing papers? Is this part of the study completed and now you are at the point of writing up the findings and disseminating those and talking about those or is there more to the hands-on part? >> CHRISANN: I don't think we're going to be collecting any more data because our contact person in Iowa has retired. But I think we need to look at it a bunch of different ways. I'm really anxious to find out how the pilot studies out in the real world are doing in terms of whether they increased a half percent to even one percent. Because there's so much money involved in this, if you doubled the current rate of return to work, you would be saving taxpayers hundreds of thousands of dollars. >> LAUREL: I thought you had a half of percentage point. I know that can't be true. >> CHRISANN: No that's it. A half go off the role to competitive employment. It's very low. >> EMER: If you consider how hard the people have to work to qualify for it, the people need to be in a pretty tough situation. I'm not saying how hard they have to work but -- >> CHRISANN: That number has been looked at several times. It wasn't just a one time study. Social Security assesses that almost annually and the numbers have not gone up significantly. >> LAUREL: So it's fairly consistent over a number of years. >> CHRISANN: Yes. Not just a one time assessment. >> LAUREL: I know three pilot tests or models going on, do we know where they are? I know you said the results haven't come in yet and I take it the Iowa study was innovative model. >> CHRISANN: Yes. >> LAUREL: Do we know anything else or when they'll have findings for us to look at? >> CHRISANN: It was a two year program and it finally got off the ground so we have another year to go on that. That would be another piece to really follow up on and see which model was most effective. And it has to do with the control groups. It would be really interesting if the control group was as good as models. What we do know is once people get used to those checks coming in, it's hard to get them to return to competitive employment. So if you anticipate that and start them in a return to work program early, it is intuitive to be a difference. That's why we do research. >> LAUREL: That's right. For those of us who would like to get more information on this, do you have some recommend readings and I presume the paper you have done has been published, is that available or how could people obtain that? >> CHRISANN: The one just published? >> LAUREL: Yeah. >> CHRISANN: Hold on a second and I will try to get you that. The one that we're writing up now is going to be in the forensic analysis the American vocation ole of experts journal. It has to be peer reviewed and they are interested in the results so we hope they'll like the paper we present. >> LAUREL: If I can get the citations from you we can post them on the web and any other resources that you might want us to watch out for we can list that up there as well. It's an important study and it's good to have the data. >> CHRISANN: Since we're working diligently writing the paper we have those resources collected for you because we have to have them for the paper. >> LAUREL: Sharon, do we have -- I suspect this new research may not have stimulated a lot of questions yet, stimulated on one's own about the implications for me. >> CHRISANN: It is a lot of information. It takes a while the digest it. >> SHARON: I have one question. If there any equation as to what Iowa is doing correctly to help the minority populations. Is there any indication -- actually is there any indication what Iowa is doing correctly that's categorize a reduction and lack of services to minority populations? >> LAUREL: So what is Iowa doing correctly to reduce lack of services to minority populations. >> EMER: I don't think we asked that question. >> CHRISANN: Yeah. We don't know. What we do know is there was no difference between the persons of color and anyone else in terms of the return to work rate. But that was a little bit of a surprise, as I said, because the popular impression says that individual uniqueness is a factor to get bark to work. >> LAUREL: So there may not be a factor in the service perspective, it just may be that Iowa did something right. >> CHRISANN: The reason we could collect this data is because Iowa was one of the states that right away embraced the concept of the ticket to work partnership with voc rehab instead of trying to fight it. Maybe that attitude of doing anything they can do get clients back to work makes it more positive for everybody. >> LAUREL: Sharon, was that our last one? >> SHARON: That was definitely it. I know you did want to mention the on line. >> LAUREL: Thank you Sharon. Emer and Chris, if you don't have anymore, I thought I might do a close. It's moving on to 2:30. I want to make sure that I'm not stepping on your toes with regard to other things you might want to close with. >> CHRISANN: Maybe you will invite us back in another year when we have looked at it in a couple ways and have more findings. >> LAUREL: Consider it done. Let us know when and we will have it up here. It's interesting study and it's an indication of how research can be used -- for those who aren't researchers, it's interesting to see how research can be applied at a practical level and come up with results. >> CHRISANN: Thank you for having us as always. >> LAUREL: Emer, I hope you feel better. I would like to close today. One thing, as Sharon reminded me, ILRU will be having an online course on cultural diversity that's going to start, I think, in September and I believe if you would like to have more information on that, it's a good online course about a four to six weeks and we have considerable experience in doing online programs and I think have had good success. This one you can go to the ILRU home page and under training, click on that, and then I believe it will be one of the listings in the online training courses and one of the them will be cultural diversity. When we do surveys on issues that are important to people in independent living when we ask about the needs, always in the top ten and we've been doing this for years, and so this course will speak to issues that are usually important. Again, online course, I believe starts in September, four to six weeks long -- probably six weeks -- registration is in August. For more information go to our web page and click on training and online training. Now this presentation we had today was part supported by the rehabilitation institute for underrepresented population. That's a consortium and here at ILRU we are working with Madan Kundu and ad in Baton Rouge. It's a historically black university and they are doing excellent work in this field. The funding comes through Title II of the Rehab Act. This authorized NIDRR to support research and to support dissemination of research findings to the key stakeholders. I always think of those of us who aren't researchers but have an interest in but a need to use the findings that these researchers are coming up with, like our colleagues today. It's important information that's being found by the research projects funded by NIDRR and our appreciation goes to the institute for funding these kinds of information dissemination packages. So thanks to NIDRR. And in closing, our webcast team is important to this whole process. We have Rob Dickehuth, who is the center for collaborative and interactive technologies at Baylor College of Medicine. He's like the one who's making the audio that's coming through these telephone lines and the broadcast out over real player and Media Player on your individual computers. And our captioner today is Lauren -- Lauren I'm sorry I blacked on your last name. Lauren Kellmann. This is going to be archived and you can come back to this same URL web page and the audio is going to be there, you can click on it. The transcript you can see scrolling along is going to be converted into a text transcript, it will be there. And also about the presenters and the citations for the papers that Chris and Emer are working on and have completed. So do check back there. You would go to our home page and click on webcast and from there click on archives. There are many other presentations that you might find useful. Many of those are part of this rehabilitation research institutes under represented populations. Finally at ILRU our team is Marj Gordon, Sharon Finney, who is or host today, rose shepherd, Dawn Heinsohn, so thanks to all of you and to those of you in the audience, thank you for tuning in today and see you at our next webcast, thank you all and good afternoon.