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SRC Summer Internship Program Research Symposium. Tuesday July 27, 2010 12:30-2:00 p.m. ISR Building, Room 6050. The Survey Research Center is an equal opportunity employer that values diversity in the workplace. Agenda. Welcome Background Overall Purpose of Symposium
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SRC Summer Internship ProgramResearch Symposium • Tuesday • July 27, 2010 • 12:30-2:00 p.m. • ISR Building, Room 6050 The Survey Research Center is an equal opportunity employer that values diversity in the workplace.
Agenda • Welcome • Background • Overall Purpose of Symposium • 10 Minute Presentations (wide spectrum of topics) • Symposium Format • Closing Remarks • General Q/A
Acknowledgements • Sponsors: • Health and Retirement Study (3) • Life Course Development Program • Survey Methodology Program • Quantitative Methodology Program • Social Environment and Health Program • Partners: • Senior Staff Advisory Committee • SRC Administrators • Summer Institute & Program in Survey Methodology • Survey Research Operations • Inter-university Consortium for Political and Social Research • ISR and SRC Human Resources • SRC Computing • SRC Director’s Office
Work Ability Among Older Adults in the U.S. Melissa Worst The University of Detroit Mercy Gwenith G. Fisher, PhD Health and Retirement Study
Overview Work Ability Promotion of Work Ability Work Ability Index Finnish Adapted version in the HRS Preliminary Results Conclusions Future Research
Work Ability • Definition: a discrepancy between expected and actual behavior; a discrepancy between the worker’s abilities and job demands. • Finnish researchers - 1981 • Work ability – the need to determine how to keep ageing workers in the workforce. Tuomi, Ilmarinen, Martikainen, Aalto, and Klockars (1997)
Why We Care • The proportion of older workers in the workforce is growing. • By 2030 - 65+ will increase by 50%. • Number of workers aged 25 to 54 will increase by only 12%. (U.S. Census Bureau, 2004) • Whether people can work and how well they can perform their jobs.
Work Ability Cont. • Researchers have differentiated: • Worker’s ability – individual physical, mental, and social capacities. • Work Ability – the worker’s qualification to manage occupational demands. • If the demands are different from the worker’s qualifications, then strain occurs. • Strain – Physiological, psychological, and behavioral changes. Ilmarinen, Tuomi, Eskelinen, Nygard, Huuhtanen, and Klockars (1991)
Promotion of Work Ability • Activities which encourage higher levels of work ability. • Should focus on altering: • Work tasks • Work demands and the environment • Work organization and the work community • Health and functional capacity • Professional competencies Tuomi, Huuhtanen, Nykyri, and Ilmarinen (2001)
Work Ability Index • Finnish developed a measure for work ability. • Seven items - assess work related capacities • Predicts early departure from the workforce • Index scores = the sum of the scores from seven items: • Poor work ability = 7 - 27 • Moderate work ability = 28 - 36 • Good work ability = 37 - 43 • Excellent work ability = 44 - 49 Ilmarinen, Tuomi, and Klockars (1997)
Work Ability Index 1) Subjective estimation of current work ability compared with lifetime best. • 0= Very poor 10= Very good 2) Subjective work ability in relation to both physical and mental demands of the work. • 2= Very poor 10= Very good 3) Number of current diseases diagnosed by a physician. • 1=5 or more, 2= 4, 3= 3, 4= 2, 5= 1, 7= No disease • Tuomi, Vanhala, Nykyri, and Janhonen (2004), • Tuomi, Ilmarinen, Martikainen, Aalto, and Klockars (1997), Ilmarinen, Tuomi, and Klockars (1997)
Work Ability Index 4) Subjective estimation of work impairment due to diseases. • 1= Fully impaired 6= No impairment 5) Sickness absence during the past year. • 1= 100 days or more, 2= 25-99 days, 3= 10-24 days, 4= 1-9 days, 5= 0 days • Tuomi, Vanhala, Nykyri, and Janhonen (2004), • Tuomi, Ilmarinen, Martikainen, Aalto, and Klockars (1997), Ilmarinen, Tuomi, and Klockars (1997)
Work Ability Index 6) Own prognosis of work ability after two years. • 1= Hardly able to work, 4= Not sure, 7= Fairly sure 7) Subjective assessment of mental resources (psychological resources). • 1= Very poor 4= Very good • Tuomi, Vanhala, Nykyri, and Janhonen (2004), • Tuomi, Ilmarinen, Martikainen, Aalto, and Klockars (1997), Ilmarinen, Tuomi, and Klockars (1997)
Adapted Work Ability Index • 2008 Participant Lifestyle Questionnaire • Also called Psychosocial Leave-behind • Health and Retirement Study • Surveys a sample of older Americans • Four Items • Aligns with Finnish Work Ability Index
A. B. C. D.
Conclusions • Previously, no study has used a work ability index with a nationally representative American sample. • Respondent’s health is significantly related to their work ability. • Not difficult to see why work ability in individuals is important. • Could help determine how to support worker’s health in the US so they are better able to work longer.
Future Research • Replicating the results of other populations. • Examining the causal relationship between antecedents and work ability - how to improve the working and personal lives of Americans. • US - how work ability breaks down by demographic characteristics and occupational sectors. • Master’s thesis research question: What relationship does subjective age have with measures of work ability?
Questions Acknowledgements: Gwen Fisher George Myers and Anita Johnson SRC Interns
Virtual Humans as Survey Interviewers Roxanne Shooshani Survey Methodology Program Sponsor: Dr. Fred Conrad
Background • Virtual Humans: Embodied Conversational Agents, Animated Agents, here: Virtual Interviewers. • Graphical interface objects that interact with a user on a computer; sometimes have voice and gestures, often appearing as humans. • Used on website like Ikea’s and PayPal’s for help. • Not Avatars – there is no one operating them “behind the scenes”.
Human Interviewer Characteristics • Race of human interviewer known to affect answers to race-relevant questions (e.g., Davis et al., 2009). • Both White and Black Rs report more “pro-civil rights,” fewer racially conservative. opinions/behaviors to Black than White interviewer. • Gender of human interviewers known to affect answers to gender -relevant questions (e.g., Kane & Macauley, 1993). • Both male and female Rs report more “pro-feminist” answers to female than male interviewer. • Characteristics of automated interviewing systems are under researchers’ control. • Do VIs produce similar effects? Is social desirability as strong in a virtual setting vs. a real life one?
Contributions • Code respondents’ reasons for picking a particular interviewing agent into logical, organized categories for further data analysis. • Read the 1,735 open responses and identify possible categories of reasons. • Collaborated with Jason Deska, a Psychology major from Notre Dame University. • Perform preliminary analyses using these codes and other data from the study. • Conduct a literature review for background support on the differences between human-administered interviews and virtual-human administered interviews.
Example of Open Responses • Facial expression and voice were appealing. • I feel that she is more like me. • I like blondes! • Because she is a Black woman like myself and she looks young and hip but at the same time very mature.
The Sixteen Categories • Race • Voice • Audio • Appearance • Human • Familiarity • Similarity to Self • Attractiveness • Age • Comfort • Distinctiveness • Personality/ • Self-Presentation • No Preference • Other • No Answer • Gender
Frequencies • How many respondents used each of the sixteen categories to justify their choices?
P E R C E N T C O D E D Frequency of Categories Coded REASONS
Conclusions • Some analysis still remains for this study • But it is clear that virtual interviewers can sometimes have similar effects as human interviewers on respondents • Our findings are good and bad – We want to replicate the way human interviewers engage respondents but don't want to replicate social desirability effects. • Yet it can also improve future studies greatly since it is possible to control the interviewer’s race, gender, and quality of voice, for example.
Thank You Fred Conrad George Myers Anita Johnson The Survey Methodology Program Staff My Fellow SRC Interns Jason Deska
The Michigan Study of Life After Prison Madeline Lupei University of Michigan Social Environment & Health Jeffrey Morenoff & David Harding
Michigan Study of Life After Prison • Analysis of Michigan Department of Corrections (MDOC) administrative records • Analysis of records of parolees released from Michigan prisons in 2003 (population N = 11,069, sample n=3,689) • Purpose: understand how neighborhood context affects recidivism, employment, and substance use • Recidivism= criminal offenses committed by individuals convicted of a prior offense • Pilot Interview Study • Semi-structured interviews of 24 parolees began in 2007 (men) and 2008 (women) • Purpose: understand the reentry experience
Analysis of MDOC Administrative Records • 1/3 random sample of population of parolees released from Michigan prisons in 2003 (N=11,064), (n=3,689) • MDOC databases: • Corrections Management Information Systems (CMIS) • Offender Management Network Information system (OMNI) • Parole officers’ case notes on parolees
Geocoding Residential Addresses • ArcGIS • Standardizing addresses • Common types of mistakes • Washtenaw st Washtenaw ave • 48104 48105 • Ypislanti Ypsilanti • Latitude and longitude
What are we studying with data on residential mobility? • How often do parolees move? • How much of a problem is housing instability? • What type of neighborhoods are parolees moving into? • Are they ending up in the most disadvantaged neighborhoods and being stuck there for long periods of time? • Is there inequality among parolees in terms of the types of neighborhoods they “attain” or how hard it is to acquire stable housing? • Is there inequality by race or socioeconomic status? • What about other demographic characteristics (e.g., gender, age, marital status)?
Rates of Residential Mobility Which parolees move more often per year? Parolees with substance abuse problems Parolees known by MDOC to be mentally ill Parolees who have been to prison more times No differences by marital status, race, sex, education and urbanicity of first address
Neighborhood characteristics of average Michigan resident vs average parolee
Neighborhood inequality among returning parolees • Compared to White parolees, Black parolees move back to neighborhoods where… • Family poverty rate is 11% higher (only 4% higher in Washtenaw) • Unemployment rate is 5% higher (no significant difference in Washtenaw) • Median income is $11,189 lower (no significant difference in Washtenaw) • Percent of population that is Black is 47% higher (only %12 higher in Washtenaw) • Number of returning parolees per capita is over twice as high (no significant difference in Washtenaw)
Parolee Characteristics Which parolees live in poorer neighborhoods? • Black Parolees (big differences) • Older Parolees • Less Educated Parolees • Unmarried Parolees • Parolees with 5 or more prison stays No differences by gender, offense type, mental illness, number of children
Future Analysis • Why are some ex-prisoners successful in reentry while others recidivate? • How do neighborhood context and living arrangement predict substance abuse, employment and risk of recidivism? • Goal: Improve rates of successful reentry and reduce rates of recidivism
Acknowledgments Jeffrey Morenoff and David Harding Jay Borchert, Claire Herbet, Liz Johnston, Jonah Siegel George Myers and Anita Johnson SRC Interns
Dynamic Treatment Regimes in Economics Shulamite Chiu University of Michigan– Ann Arbor Eric Laber and Susan Murphy, PhD SRC - Quantitative Methodology Program
Background and Role • Background: • Economics B.A. from University of Michigan– Ann Arbor • Incoming Sustainable Systems M.S. student in SNRE • Aspiring to Economics PhD • Role: Linking dynamic treatment regimes in economics and statistics • Weekly presentations to the lab • Literature review
Current Applications of DTRs: Marlowe et al. (2008) • Marlowe’s adaptive drug court program • High risk if offender has either • “more severe antisocial propensities” OR • “treatment-refractory drug use histories”