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Funded by the National Institutes of Health/Centers for Disease Control and Prevention

Funding years: 2010-2020

This proposal is for the planning and conduct of the next ten years of the National Survey of Family Growth (NSFG), with interviewing to be conducted continuously from June 1, 2011 through May 31, 2019. The awarded contract will cover a ten-year period, from September 2010 through May 2020, and include eight years of data collection and three data releases. Working closely and collaboratively with the NCHS/NSFG work team to develop materials and specifications, we shall conduct all the necessary activities, including sample design, pretest, CAPI programming, hiring, supervising and training interviewers, data processing, data file preparation, and data file documentation, for a complete national survey. It is anticipated that the NSFG will be done indefinitely as a continuous national survey, in which interviewing is done every year, producing approximately 5,000 in-person interviews per year with men and women 15-44 years of age, in English and Spanish. Over the life of this proposal, about 40,000 men and women will be interviewed in person in 8 years. This proposal also provides for the preparation and release of up to 3 public use data files.

The National Survey of Family Growth (NSFG) is part of a series of face-to-face surveys based on national probability samples that began in 1955. From 1955-1995, the surveys were limited to women of reproductive age. The University of Michigan is currently the contractor for the NSFG Cycle 6 and The 2006-10 NSFG (Cycle 7). Cycle 6 was conducted beginning in 2002 using a national sample of men and women 15-44; and “The 2006-10 NSFG,” a continuous sample of men and women 15-44. In each NSFG, respondents have been interviewed in person in their own homes by trained professional female interviewers. In Cycles 6 and 7, the NSFG has been conducted using Computer-Assisted Personal Interviewing (CAPI) and Audio Computer-Assisted Self-Interviewing (Audio CASI). CAPI and Audio CASI is being used again in this proposal.

Link: http://www.psc.isr.umich.edu/research/project-detail/34976

PI: Mick Couper

 

 

2014 CBSSM Research Colloquium and Bishop Lecture (Myra Christopher)

Thu, May 15, 2014 (All day)
Location: 
Vandenberg Meeting Hall (2nd floor), The Michigan League, 911 N. University, Ann Arbor, MI

2014 CBSSM Colloquium and Bishop Lecture featuring Myra Christopher

The Center for Bioethics and Social Sciences in Medicine (CBSSM) Research Colloquium was held Thursday, May 15, 2014 at the Vandenberg Meeting Hall (2nd floor), The Michigan League, 911 N. University Ave, Ann Arbor, MI 48109.
 

The CBSSM Research Colloquium featured the Bishop Lecture in Bioethics as the keynote address.  Myra Christopher presented the Bishop Lecture with a talk entitled: "The Moral Imperative to Transform the Way Pain is Perceived, Judged and Treated." Myra Christopher holds the Kathleen M. Foley Chair in Pain and Palliative Care at the Center for Practical Bioethics.

The 2014 Research Colloquium presenters:

  • Andrew G. Shuman, MD, Assistant Professor, Department of Otolaryngology, University of Michigan: "When Not to Operate: The Dilemma of Surgical Unresectability"
  • Phoebe Danziger, MD, University of Michigan Medical School: "Beliefs, Biases, and Ethical Dilemmas in the Perinatal Counseling and Treatment of Severe Kidney Anomalies"
  • Kathryn L. Moseley, MD, MPH, Assistant Professor, Pediatrics and Communicable Diseases, University of Michigan: "Electronic Medical Records: Challenges for Clinical Ethics Consultation"
  • Helen Morgan, MD,  Department of Obstetrics and Gynecology, University of Michigan: "Academic Integrity in the Pre-Health Undergraduate Experience"
  • Tanner Caverly, MD, MPH, Health Services Research Fellow, Ann Arbor VA Medical Center and Clinical Lecturer, University of Michigan: "How Transparent are Cancer Screening & Prevention Guidelines about the Benefits and Harms of What They Recommend?"
  • Susan D. Goold, MD, MHSA, MA , Professor of Internal Medicine and Health Management and Policy, School of Public Health, University of Michigan: "Controlling Health Costs: Physician Responses to Patient Expectations for Medical Care"
 

 

Funded by Robert Wood Johnson Foundation

Funding Years: 2014 - 2016.

The Robert Wood Johnson Foundation Clinical Scholars Program at the University of Michigan has established a rigorous curriculum, with enhanced and mentored research practicum and exciting opportunities to engage in community-based and partnered participatory research. The curriculum is based on adult learning theory and integrates research theory and practical applications. This curriculum will fulfill requirements for a Master's Degree in Health and Health Care Research, a degree program that was designed specifically to meet the needs of the Clinical Scholars at the University of Michigan. These above courses make up the central components of the first year of Clinical Scholars Program at the University of Michigan. The second year of the Clinical Scholars Program is primarily devoted to research, with the Scholars' Research Committee continuing as an advisory committee. Education in the second year focuses more closely to each Scholar's specific needs. In the second year the Scholars also participate in a "Work-in-Progress Seminar" led by one of the Program Directors. Throughout all years of the program, Scholars participate in the Clinical Scholars noon health Seminar. This is a weekly 1.5 hour seminar which will alternate between presentation of research findings by Scholars, faculty, or invited guests, and presentations about health policy by Michigan faculty and invited guests. All Scholars are expected to attend the seminar each week, as well as the CSP Leadership, most Core Faculty, and selected guests.

PI(s): Rodney Hayward

Co-I(s): Matthew Davis, Gary Freed, Mary Ellen Heisler, Timothy Hofer, Joel Howell, Theodore Iwashyna, Eve Kerr, Joyce Lee, Richard Lichtenstein, Laurence McMahon Jr, Caroline Richardson, Mary AM Rogers, Sanjay Saint, Antonius Tsai, Michael Volk, Sara Waber

Funded by National Institutes of Health; National Institute of Mental Health

Funding Years: 2012-2017

This project will test a practical intervention that uses low cost technologies to activate depressed patients' existing social networks for self-management support. The intervention links patients with a "CarePartner" (CP), i.e., a non-household family member or close friend who is willing to support the patient in coordination with the clinician and any existing in-home caregiver (ICG). Through weekly automated telemonitoring, patients report their mood and self-management status, and receive tailored guidance on self-management. The CP receives a corresponding update along with guidance on how to best support the patient's self-management efforts, and the primary care team is notified about clinically urgent situations. The intervention will be tested among depressed primary care patients from clinics serving low-income and underinsured patients, whom the intervention was especially designed to benefit. Specific Aim 1 is to conduct a randomized controlled trial to compare the effectiveness of one year of telemonitoring-supported CP for depression versus usual care (control) on depression severity. Specific Aim 2 is to examine key secondary outcomes (response and remission, impairment, well-being, caregiving burden, healthcare costs) and potential moderators. Specific Aim 3 is to use a mixed-methods approach to enrich our interpretation of the statistical associations, and to discover strategies to enhance the intervention's acceptability, effectiveness, and sustainability. If the intervention proves effective without increasing clinician burden or marginal costs, then its subsequent implementation could yield major public health benefits, especially in medically underserved populations.

PI(s): James Aikens

Co-I(s): Michael Fetters, John Piette, Ananda Sen, Marcia Valenstein, Daniel Eisenberg, Daphne Watkins

Does order matter when distributing resources? (Jun-03)

Should people with more severe health problems receive state funding for treatment before people with less severe health problems? See how your opinion compares with the opinions of others.

Imagine that you are a government official responsible for deciding how state money is spent on different medical treatments. Your budget is limited so you cannot afford to offer treatment to everyone who might benefit. Right now, you must choose to spend money on one of two treatments.

  • Treatment A treats a life threatening illness. It saves patients' lives and returns them to perfect health after treatment
  • Treatment B treats a different life threatening illness. It saves patients' lives but is not entirely effective and leaves them with paraplegia after treatment. These patients are entirely normal before their illness but after treatment will have paraplegia.

Suppose the state has enough money to offer Treatment A to 100 patients. How many patients would have to offered Treatment B so that you would have difficulty choosing which treatment to offer?

How do your answers compare?

The average person said that it would become difficult to decide which treatment to offer when 1000 people were offered Treatment B.

What if you had made another comparison before the one you just made?

In the study, some people were asked to make a comparison between saving the lives of otherwise-healthy people and saving the lives of people who already had paraplegia. After they made that comparison, they made the comparison you just completed. The average person in that group said it would take 126 people offered Treatment B to make the decision difficult. The differences are shown in the graph below

Why is this important?

The comparison you made is an example of a person tradeoff (PTO). The PTO is one method used to find out the utilities of different health conditions. These utilities are basically measures of the severities of the conditions. More severe conditions have a lower utility, and less severe conditions have a higher utility, on a scale of 0 to 1. Insurance companies, the government, and other organizations use these utilities as a way to decide which group to funnel money into for treatments.

On the surface, it seems like basing the money division on the severity of a condition is a good and fair method, since theoretically the people who are in the greatest need will be treated first. However, the PTO raises issues of fairness and equity that aren't accounted for in other utility elicitation methods like the time tradeoff (TTO) and rating scale (RS).

For example, when asked to decide how many people with paraplegia would have to be saved to equal saving 100 healthy people, many people say 100; that is, they think it is equally important to save the life of someone with paraplegia and a healthy person. Going by values obtained using the TTO or RS, an insurance company may conclude that 160 people with paraplegia (using a utility of .6) would have to be saved to make it equal to saving 100 healthy people. This would mean that less benefit would be gotten by saving someone with paraplegia, and thus they might not cover expenses for lifesaving treatments for people with paraplegia as much as they would for a healthy person. The PTO shows that many people would not agree with doing this, even though their own responses to other utility questions generated the policy in the first place.

For more information see:

Ubel PA, Richardson J, Baron J. Exploring the role of order effects in person trade-off elicitations. Health Policy, 61(2):189-199, 2002.

CBSSM investigators Holly Witteman, Andrea Fuhrel-Forbis, Angela Fagerlin, and Brian Zikmund-Fisher, along with CBSSM alumni Peter Ubel and Andrea Angott will give a plenary talk at the Society for Medical Decision Making's 32nd Annual Meeting in Toronto on Monday, October 25.  The talk is titled, "Colostomy is Better than Death, but a 4% Chance of Death Might Be Better Than a 4% Chance of Colostomy: Why People Make Choices Seemingly At Odds With Their Stated Preferences." 

Abstract:

Purpose: When asked for their preference between death and colostomy, most people say that they prefer colostomy. However, when given the choice of two hypothetical treatments that differ only in that one has four percent chance of colostomy while the other has four percent additional chance of death, approximately 25% of people who say that they prefer colostomy actually opt for the additional chance of death. This study examined whether probability-sensitive preference weighting may help to explain why people make these types of treatment choices that are inconsistent with their stated preferences.

Method: 1656 participants in a demographically diverse online survey were randomly assigned to indicate their preference by answering either, “If you had to choose, would you rather die, or would you rather have a colostomy?†or, “If you had to choose, would you rather have a 4% chance of dying, or would you rather have a 4% chance of having a colostomy?†They were then asked to imagine that they had been diagnosed with colon cancer and were faced with a choice between two treatments, one with an uncomplicated cure rate of 80% and a 20% death rate, and another with an uncomplicated cure rate of 80%, a 16% death rate, and a 4% rate of colostomy.

Result: Consistent with our prior research, most people whose preferences were elicited with the first question stated that they preferred colostomy (80% of participants) to death (20%), but many then made a choice inconsistent with that preference (59% chose the treatment with higher chance of colostomy; 41% chose the treatment with higher chance of death). Compared to the first group, participants whose preferences were elicited with the 4% question preferred death (31%) over colostomy (69%) more often (Chi-squared = 24.31, p<.001) and their treatment choices were more concordant with their stated preferences (64% chose the treatment with higher chance of colostomy; 36% chose the treatment with higher chance of death, Chi-squared for concordance = 36.92, p<.001).

Conclusion: Our experiment suggests that probability-sensitive preference weighting may help explain why people’s medical treatment choices are sometimes at odds with their stated preferences. These findings also suggest that preference elicitation methods may not necessarily assume independence of probability levels and preference weights.


Funded by National Institutes of Health; National Insitute on Drug Abuse

Funding Years: 2012-2017

This application seeks a five-year continuation of the panel data collections of the Monitoring the Future (MTF) study, an ongoing epidemiological and etiological research and reporting project begun in 1975. In addition to being a basic research study, MTF has become one of the nation's most relied upon sources of information on trends in illicit drug, alcohol, and tobacco use among American adolescents, college students, and young and middle-aged adults. This application seeks continuation of the mail follow-up surveys of high school graduates (augmented with internet options) at modal ages 19-30, 35, 40, 45, 50, and now 55. The companion main application seeks to continue the in-school data collections and to support the analysis of all of the data in the study, including past and future panel data. (NIDA requests that the study seek continuation funding through two separate applications, as it has done in the last two rounds.)
The study's cohort-sequential longitudinal design permits the measurement and differentiation of three types of change: age (developmental), period (historical), and cohort. Each has different determinants, and all three types of change have been shown by MTF to occur for most drugs. Factors that may explain historical trends and cohort differences also are monitored. MTF is designed to document the developmental history and consequences of drug use and related attitudes from adolescence through middle adulthood, and to determine the individual and contextual characteristics and social role transitions that affect use and related attitudes. Research on risk and protective behaviors for the transmission of HIV/AIDS among adults ages 21-40 also will be continued. All of this work will be extended to new years, cohorts, and ages under this application and the companion main application. The study will examine the importance of many hypothesized determinants of drug use (including attitudes and beliefs and access), as well as a range of potential consequences (including physical and psychological health, status attainment, role performance, and drug abuse and dependence). Impacts of some policy changes on adolescents and young adults will be evaluated, including those of the new FDA cigarette labeling requirements. MTF will experiment with the use of internet response methods and pursue several new approaches to making its panel data more accessible to other investigators.
The study's very broad measurement covers (a) initiation, use, and cessation for over 50 categories and sub-categories of licit and illicit drugs, including alcohol and tobacco; (b) attitudes and beliefs about many of them, perceived availability, and peer norms; (c) other behaviors and individual characteristics; (d) aspects of key social environments (home, work, school) and social role statuses and transitions; and (e) risk and protective behaviors related to the spread of HIV/AIDS. Results will continue to elucidate drug use from adolescence through middle adulthood (including the introduction of new drugs) with major implications for the policy, research, prevention, and treatment agendas.

PI(s): Mick Couper

Co-I(s): Lloyd Johnston, Patrick O'Malley, John Schulenberg, Megan Patrick, Richard Miech

Leaving the Emergency Room in a Fog (Sep-09)

Consider this scenario:

Alfred made a visit to his local Emergency Room. What was his diagnosis? What did the medical team do for his problem? What was he supposed to do to continue care at home? And what symptoms was he supposed to watch for to alert him to return to the ER?

Alfred woke up at 4 am on Sunday morning with pain in his left foot. That place where his new running shoes had rubbed a raw spot earlier in the week was getting worse. By 9 am, the foot was red and swollen, with a large oozing sore, and Alfred decided to go to the Emergency Room at his local hospital.

Late on Sunday afternoon, Alfred returned home from the ER. He crutched his way into the house and collapsed on the sofa. His teenage son quizzed him.

"What did they say was wrong?"
"Oh, an infection," replied Alfred.
"Well, what did they do for it?"
"I think they cut a chunk out of my foot," said Alfred.
"Whoa! Did they give you any medicine?"
"Yeah, a shot," said Alfred.
"And what’s with the crutches?"
"I’m supposed to use them for a while," said Alfred, looking annoyed.
"How long a while?"
"It’s written down," said Alfred, digging a crumpled sheet of paper out of his pocket.
"Says here you should take some prescription and elevate your left leg for two days."
"Two days? I have to go to work tomorrow," groaned Alfred.
"And you’re supposed to go back to the ER if you have a fever or pain in your leg. Where’s the prescription?"
"Here, look through my wallet. Maybe I stuck it in there," said Alfred.
The good news is that Alfred recovered completely, with some assistance and cajoling from his son. But how common is it for people who go to the Emergency Room to be foggy about what happened and what they should do once they leave the ER?
What do you think is the percentage of ER patients who do not understand at least one of the following: their diagnosis, the emergency care they received, their discharge care, or their return instructions?
 
  • 38%
  • 48%
  • 78%
  • 88%

How do your answers compare?

A recent study in the Annals of Emergency Medicine found that 78% of emergency room patients showed deficient comprehension in at least one of these areas:
 
  • Diagnosis
  • Emergency care that was given
  • Post-ER care needs
  • Symptoms that would require a return to the ER
51% of patients showed deficient comprehension in two or more areas. Only 22% of reports from patients were in complete harmony with what their care teams reported in all four areas. The biggest area of misunderstanding was in patients' post-ER care needs, such as medications, self-care steps, follow-up from their regular doctors, or follow-up with specialists.
 
Even more alarming is that, according to the study, "most patients appear to be unaware of their lack of understanding and report inappropriate confidence in their comprehension and recall." The patients were quite sure of what they knew 80% of the time—even when what they knew was not right.
 
These results suggest that Emergency Room teams need to do a better job of making sure that patients go home with clear information and instructions—and that patients and their loved ones shouldn't leave until they fully comprehend their situation.
 
Lead author Kirsten G. Engel, MD, conducted this study, "Patient Comprehension of Emergency Department Care and Instructions," with Michele Heisler, MD, Dylan M. Smith, PhD , Claire H. Robinson, MPH, Jane H.Forman, ScD, MHS, and Peter A. Ubel, MD, most of whom are affiliated with CBDSM.
 
The researchers carried out detailed interviews with 140 English-speaking patients who visited one of two Emergency Departments in southeast Michigan and were released to go home. These interviews were compared with the patients' medical records, and the comparisons revealed serious mismatches between what the medical teams found or advised and what the patients comprehended.
 
"It is critical that emergency patients understand their diagnosis, their care, and, perhaps most important, their discharge instructions," says Kirsten Engel, a former UM Robert Wood Johnson Clinical Scholar who is now at Northwestern University. "It is disturbing that so many patients do not understand their post-Emergency-Department care, and that they do not even recognize where the gaps in understanding are. Patients who fail to follow discharge instructions may have a greater likelihood of complications after leaving the Emergency Department."
 
Peter A. Ubel, the study's senior author, agrees: "Doctors need to not only ask patients if they have questions, but ask them to explain, in their own words, what they think is wrong with their health and what they can do about it. And patients need to ask their doctors more questions, and even need to explain to their doctors what they think is going on."
 
Read the article:

 

Is your well-being influenced by the guy sitting next to you? (Nov-03)

Rating your satisfaction with your life may not be a completely personal decision. See how your satisfaction rating may be influenced by others.

When answering this question, imagine that there is someone in a wheelchair sitting next to you. They will also be answering this question, but you will not have to share your answers with each other.

How satisfied are you with your life in general?

Extremely satisfied 1       2       3       4       5       6       7       8       9       10 Not at all satisfied

How do you compare to the people surveyed?

You gave your life satisfaction a rating of 1, which means that you are extremely satisfied with your life. In a study done where people with a disabled person sitting next to them wrote down their life satisfaction on a questionnaire, they gave an average life satisfaction rating of 2.4, which means they were very satisfied with their lives.

What if you'd had to report your well-being to another person instead of writing it down?

In the study, half the people had to report their well-being in an interview with a confederate (a member of the research team who was posing as another participant). When the participants had to report in this way, and the confederate was not disabled, the participants rated their well-being as significantly better than those who reported by writing it on the questionnaire in the presence of a non-disabled confederate (2.0 vs. 3.4, lower score means higher well-being). The scores given when reporting to a disabled confederate elicited a well-being score that was no different than that when completing the questionnaire in the presence of a disabled confederate (2.3 vs. 2.4).

Mean life satisfaction ratings, lower score means higher satisfaction
Mode of rating well-being Disabled confederate Non-disabled Confederate
Interview (public) 2.3 2.0
Questionnaire (private) 2.4 3.4
What caused the difference in well-being scores?

When making judgments of well-being, people (at least in this study) tend to compare themselves to those around them. This effect is seen more when well-being was reported in an interview than when the score was privately written down, due to self-presentation concerns. A higher rating was given in public so as to appear to be better off than one may truly feel. Note that the effect was only seen in the case where the confederate was not disabled. While well-being ratings were better overall with a disabled confederate, there was no difference between the private and public ratings. Social comparison led to a better well-being judgment, but it appears that the participants were hesitant to rate themselves too highly in front of the disabled person for fear of making the disabled person feel worse.

Why is this important?

Subjective well-being is a commonly used measure in many areas of research. For example, it is used as one way to look at the effectiveness new surgeries or medications. The above studies show that SWB scores can vary depending on the conditions under which they are given. Someone may give a response of fairly high SWB if they are interviewed before leaving the hospital, surrounded by people more sick than they are. From this, it would appear as though their treatment worked great. But suppose that they are asked to complete a follow-up internet survey a week later. Since they do not have to respond to an actual person face-to-face, and without being surrounded by sick people, they may give a lower rating than previously. Is this because the treatment actually made their SWB worse over the longer term, or simply because a different method was used to get their response? The only way to really know would be to use the same methodology to get all their responses, which might not always be feasible. These are important considerations for researchers to keep in mind when analyzing results of their studies. Are the results they got the true SWB of their participants, or is it an artifact of how the study was done? And is there a way to know which measure is right, or are they both right which would lead to the conclusion that SWB is purely a momentary judgment based on a social context?

For more information see:

Strack F, Schwarz N, Chassein B, Kern D, Wagner D. Salience of comparison standards and the activation of social norms: Consequences for judgements of happiness and their communication. British Journal of Social Psychology. 29:303-314, 1990.

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