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Social Network Analysis With Ashton Verdery
October 10, 2018
In our latest podcast, Ashton Verdery, assistant professor of sociology and demography at Penn State, discusses social network analysis (SNA). One increasingly important use of SNA is to study marginalized populations who are otherwise hard to sample. In health, behavioral, and social sciences, SNA has been used to examine how people relate to one another; how relationships affect the flow of items such as diseases, goods, information, or behaviors; how individual positions in broader network structures affect the risks of contracting diseases, hearing of opportunities, or generating new ideas; and more. In this podcast, Ashton explains the value and challenges of SNA in a behavioral health context. He also discusses projects from his research, including his work studying the heroin crisis in Pennsylvania, kidney transplant candidates, and migrant populations.
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00:31—What is social network analysis (SNA) and why do it?
03:51—Why does SNA interest you?
05:46—Why is SNA valuable in behavioral health?
09:00—Do policy changes affect migrants’ social networks?
13:15—What are the methodological challenges in SNA?
19:17—How are the social network questions different and similar in your research projects on kidney transplants and your research on the heroin crisis?
New Book on Advanced Topics in MOST
August 8, 2018
In podcast 33, Methodology Center Director Linda Collins and Faculty Affiliate Kari Kugler discuss the new book from Springer that they edited, Optimization of Behavioral, Biobehavioral, and Biomedical Interventions: Advanced Topics. This is the second book on the multiphase optimization strategy (MOST) to be published this year. MOST is an engineering-based framework for optimizing interventions that has been developed by Linda and her collaborators over the past 14 years. In this podcast, Linda and Kari explain the concepts behind and rationale for each of the chapters in the book. Both the book and the podcast explore topics ranging from the development of a conceptual model to the use of concepts from control systems engineering.
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01:08—The differences between the two books on MOST
02:19—Developing a conceptual model for an intervention
04:54—Factorial experiments and types of experimental designs
08:35—Multi-level factorial designs
10:11—Adaptive interventions and MOST
11:38—Control systems engineering in MOST
13:29—Coding data for analysis
16:00—Cost effectiveness analysis in MOST
18:25—Mediation analysis in MOST
20:00—The future of MOST
. (2018). Optimization of behavioral, biobehavioral, and biomedical interventions: Advanced topics. New York, NY: Springer.
Collins, L. M. (2018). Optimization of behavioral, biobehavioral, and biomedical interventions: The multiphase optimization strategy (MOST). New York, NY: Springer.
Audiobook Excerpt: Preface to Linda Collins' Book on MOST
May 17, 2018
In this special edition podcast, Methodology Center Director Linda Collins reads the preface to her new book from Springer, Optimization of Behavioral, Biobehavioral, and Biomedical Interventions: The Multiphase Optimization Strategy (MOST). MOST is an engineering-based framework for optimizing interventions, developed by Linda and her collaborators over the past 14 years. In the preface, Linda explains the problem with the current state of intervention research and describes what MOST is and how it can help us address the problem. Then, she explains the content of the book. For researchers who are interested in optimizing interventions, this podcast succinctly introduces the need for and advantages of MOST; the podcast will enable listeners to decide whether to read the entire book.
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References for the Book and the Articles Discussed in the Podcast
Collins, L. M. (2018). Optimization of behavioral, biobehavioral, and biomedical Interventions: The multiphase optimization strategy (MOST). New York, NY: Springer. Visit Springer's website
"In the United States and worldwide, billions of dollars have been spent to develop behavioral, biobehavioral, and biomedical interventions (hereafter referred to simply as interventions) to prevent and treat health problems, promote health and well-being, prevent violence, improve learning, promote academic achievement, and generally improve the human condition. Numerous interventions are in use that are successful in the sense that they have demonstrated a statistically and clinically significant effect in a randomized controlled trial (RCT). However, many are less successful in terms of progress toward solving problems. In fact, after decades of research, as a society we continue to struggle with the very issues these interventions have been designed to ameliorate. Only very slow progress is being made in many areas; in some, the problem continues to worsen. Let us consider two examples in the public health domain, both from the Healthy People goals set every ten years by the United States Centers for Disease Control and Prevention (CDC)..."
New Book on MOST With Linda Collins
February 26, 2018
In this podcast, Methodology Center Director Linda Collins discusses her new book from Springer, Optimization of Behavioral, Biobehavioral, and Biomedical Interventions: The Multiphase Optimization Strategy (MOST). MOST is an engineering-based framework for optimizing interventions that has been developed by Linda and her collaborators over the past 14 years. In the podcast, she describes how MOST can help advance intervention research. She then explains the structure of MOST, using an example from an intervention to help overweight adults lose weight. Finally, she discusses why now is the right time for this book to be published.
00:50—The problem with the status quo in intervention design
03:04—Defining "optimization" and "MOST"
06:57—Describing the phases of MOST
07:39—The preparation phase
11:26—The optimization phase
15:54—The evaluation phase
19:22—How Linda’s thinking about MOST has evolved
21:23—Why is now the right time for this book?
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References for the Book and the Articles Discussed in the Podcast
Collins, L. M. (2018). Optimization of behavioral, biobehavioral, and biomedical Interventions: The multiphase optimization strategy (MOST). New York, NY: Springer.
Pellegrini, C. A., Hoffman, S. A., Collins, L. M., & Spring, B. (2014). Optimization of remotely delivered intensive lifestyle treatment for obesity using the multiphase optimization strategy: Opt-IN study protocol. Contemporary Clinical Trials, 38(2), 251-259.
Pellegrini, C. A., Hoffman, S. A., Collins, L. M., & Spring, B. (2015). Corrigendum to "Optimization of remotely delivered intensive lifestyle treatment for obesity using the multiphase optimization strategy: Opt-IN study protocol." Contemporary Clinical Trials, 45, 468-469.
Collecting Data in Schools with Zena Mello
January 15, 2018
In a relaxed and engaging conversation, Zena Mello, associate professor of psychology at San Francisco State University, discusses the opportunities, complications, obligations, and challenges associated with collecting data in public high schools. She explains the different experiences she had developing relationships and working in two schools that are only minutes apart geographically but sharply divergent in terms of the educational resources available. Her research investigates how adolescents think about time and how that thinking relates to their substance use and other risky behavior.
00:32—Gaining access to high schools for collecting data
12:20—Introducing graduate students to a low-income high school
18:52—Maintaining a relationship with a high school administration
23:30—Gaining access to a high-income high school
30:31—Future directions of Zena’s research
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The Past, Present, and Future of Prevention with Mark Greenberg
November 14, 2017
Mark Greenberg is one of the founders of prevention science as a recognized field. In 1998, he founded The Edna Bennett Pierce Prevention Research Center and served as its director until 2013. In this podcast, he talks with host Aaron Wagner about the founding of the center, its connection to The Methodology Center, the future of prevention science, and more.
00:37—The genesis of The Edna Bennett Pierce Prevention Research Center and the field of prevention science
06:07—Connections between The Edna Bennett Pierce Prevention Research Center and The Methodology Center
08:15—Mark’s research career
11:22—The impact Edna Bennett Pierce has on the field of prevention research
13:10—The future of prevention research
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Getting Started with Secondary Data Analysis
June 11, 2017
Secondary data analysis is a high priority for many funding agencies as they try to maximize the information gleaned from funded studies. In this podcast, Methodology Center Research Associate Kate Guastaferro and Methodology Center Data Manager Loren Masters discuss some of the issues and requirements associated with getting access to existing data. This podcast is intended for graduate students or investigators who are new to secondary data analysis. Along with the podcast, users can download an outline of the steps required before conducting a secondary data analysis.
02:14—Working with restricted data for qualified researchers
03:53—Working with IRBs
06:50—Data protection plans
11:10—Getting added to existing data use agreements
12:20—Identifying data sets available for secondary analyses
13:22—Working on data from your prior institution
15:47—Potential problems in data procurement
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Steps for getting started in secondary data analysis
Ambulatory Assessment with Michael Russell
January 23, 2017
In our latest podcast, Methodology Center Research Associate Michael Russell discusses ambulatory assessment and his pilot project examining self-report data during heavy drinking. In the project, Michael is combining ecological momentary assessment (EMA) of self-reported alcohol use with continuous data from ankle bracelets that measure alcohol intoxication levels through contact with the skin. He is investigating the accuracy of using EMA self-reports as a proxy for such intoxication measures during real-world drinking episodes. He discusses his thoughts on the challenges and opportunities of such data collection, and talks about some of his research using these and other intensive longitudinal data (ILD).
00:33—Developing an interest in methods
03:07—Ambulatory assessments for understanding substance use
06:29—Examining the accuracy of self-report data on alcohol use
08:30—Practical issues with ambulatory assessment studies
10:09—Methodological issues with ambulatory assessment studies
13:36—Implications for working with IRBs
15:40—Future of ambulatory assessment
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Practical Advice on LCA with John Dziak
December 1, 2016
Latent class analysis (LCA) is a widely used tool for identifying subgroups in a population. Many researchers have questions about how to conduct an LCA as responsibly and accurately as possible. In our latest podcast, John Dziak discusses important points to consider when conducting an LCA, like how to tell when an analysis is successful and how to make sure your model is properly identified. John is a Methodology Center research associate who studies LCA, and he is the lead developer of our LCA software, including PROC LCA. Note: this podcast is a companion piece to podcasts 15 and 16 with Stephanie Lanza and Bethany Bray. If you are new to LCA, you may want to start with Podcast 15.
00:30—What is LCA for?
01:15—Why would someone use LCA?
02:27—How does LCA work?
04:20—How do I select a model?
07:39—How do I know if my LCA worked?
13:45—How do I select items for my model?
18:20—What "percent identified" of random starts is high enough?
19:23—When should I use a higher value in NSTARTS?
20:13—What should I do if my model won’t converge?
23:00—When should I use the RESTRICT option?
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Methodological Innovation in HIV Prevention Research with Cara Rice
September 7, 2016
In this short podcast, Methodology Center Postdoctoral Research Associate, Cara Rice, discusses her research examining HIV-risk behavior among sexual minorities. She describes her work collecting survey data among high-risk populations and her application of new methods to these data. As part of the Methodology Center, Cara has recently used both LCA and TVEM to understand more about the profiles of behavior that increase HIV risk among men who have sex with men (MSM).
00:30—Becoming an HIV researcher
05:45—Applying methods to HIV research
09:34—Collecting extremely personal data
12:03—Applying TVEM to HIV-risk data
14:40—The future of Cara’s research and HIV research
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Live from SPR
July 5, 2016
At this year's Annual Meeting of the Society for Prevention Research, we gathered reflections from presenters and attendees and edited them into a short podcast. Learn a little about the conference, or if you were there, relive it. (Maybe you'll hear yourself in the background.) Topics are wide-ranging and include the value of the conference, time-varying effect modeling, and e-cigarettes. Interviewees include Claire Mawditt, Yvonne Terry-McElrath, Michael J. Parks, Jessica Braymiller, and Michael Russell.
01:04—Claire Mawditt, conference attendee
2:13—Yvonne Terry-McElrath, presenter on alcohol use across the lifespan
4:00—Michael Parks, attendee of TVEM and smoking session
6:08—Jessica Braymiller, attendee of marijuana and e-cigarette session
7:35—Michael Russell, presenter on TVEM and smoking
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Download the transcript for Podcast 24
Using MOST to Improve STI Prevention
with Kari Kugler and Amanda Tanner
January 27, 2016
In this podcast, we discuss the application of the multiphase optimization strategy (MOST) to the development of an online intervention to reduce sexual risk behavior among college students. Host Aaron Wagner speaks with Kari Kugler, Methodology Center investigator, and Amanda Tanner, assistant professor of public health education at University of North Carolina at Greensboro (UNCG), about the project which is funded by the National Institute on Alcohol Abuse and Alcoholism.
In this study, the researchers will use MOST to strengthen intervention components aimed at reducing risky drinking, risky sex, and their co-occurrence, and then using the strengthened components to form an optimized intervention. The principal investigator of the project is Methodology Center Director Linda Collins. David Wyrick, associate professor of public health education, leads the team at UNCG.
01:07—What public health problem does the grant address?
03:57—Definition of multiphase optimization strategy
06:45—Other applications of MOST
07:41—Why use MOST on this project?
10:37—How will this project encourage college students to make better decisions?
13:06—Why an online intervention?
14:02—What is incorrect about the term "risky sex?"
15:53—What else should people know about MOST?
16:46—The quality of the project team
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Download the transcript for Podcast 23
Getting Started with TVEM
with Stephanie Lanza and Sara Vasilenko
September 15, 2015
This podcast will introduce interested scientists to time-varying effect modeling (TVEM). Host Aaron Wagner talks with Methodology Center Investigators Stephanie Lanza and Sara Vasilenko about the new types of questions scientists can answer by applying TVEM to existing data or to new studies. Sara and Stephanie have been at the forefront of both applying TVEM and training scientists to use TVEM. Multiple participants from their TVEM workshop in June already have submitted TVEM manuscripts to journals. In this 25-minute podcast, they provide the introduction needed to determine whether could be useful in your work.
00:00 – Introductions
00:52 – Defining TVEM
02:07 – Time-varying versus time-invariant effects
04:00 – Questions TVEM can answer
07:08 – Why a “Year of TVEM?”
09:56 – Data and TVEM
11:00 – TVEM and ecological momentary assessments
13:03 – TVEM and panel data
15:41 – When not to use TVEM
20:12 – Getting started
23:32 – TVEM SAS macro
Podcast on Career Awards, Big Data, mHealth, and Causal Inference
with Donna Coffman
May 5, 2015
In this podcast, we talk with Methodology Center Investigator Donna Coffman about the K01 award she received from the National Institutes of Health (NIH) Big Data to Knowledge (BD2K) initiative. Topics include the emergence of big data in NIH-funded research and the practical aspects of applying for a K award. Donna also explains her research on analyzing biosensor data from a parenting study and how her move into big data integrates with her research on causal inference.
00:00 – Introduction
00:48 – What is a K Award? / Overview of Donna’s K01
03:56 – Training plan in Donna’s K
05:50 – Donna’s background
06:58 – Analyzing biosensor data
09:02 – Causal inference and big data
10:18 – Big data in social, behavioral, and health sciences
11:54 – Applying for a K01
14:05 – Most important attribute of a K01 application
Podcast on Postdoctoral Training in Methods and Prevention
with Melissa Boone, Michael Russell, and Sara Vasilenko
February 26, 2015
In this podcast, we discuss the Prevention and Methodology Training (PAMT) program, which is a collaboration between The Methodology Center and The Bennett Pierce Prevention Research Center. Host Aaron Wagner talks with Melissa Boone, Michael Russell, and Sara Vasilenko, all current or former PAMT postdoctoral fellows. The opportunities and unique features of the program are discussed in under 20 minutes. PAMT also trains Penn State graduate students as predoctoral fellows, but that aspect of the program is not discussed in the podcast. For more information about PAMT predoctoral and postdoctoral fellowships, contact Bethany Bray.
00:00 – Introduction
00:54 – What is PAMT? (Melissa Boone)
01:27 – Melissa’s research and her motivation for joining PAMT
03:26 – What’s unique about PAMT (Melissa Boone)
05:06 – Why do a postdoc rather than seek a job? (Melissa Boone)
06:21 – Michael’s research and motivation for joining PAMT
07:31 – Working with prevention and methodology mentors (Michael Russell)
09:07 – Who should apply for PAMT? (Michael Russell)
09:40 – How will PAMT help you in your future? (Michael Russell)
10:19 – Sara’s research and her motivation for joining PAMT
14:00 – Advantage of training in methods and prevention (Sara Vasilenko)
15:30 – How PAMT prepares you for a research career (Sara Vasilenko)
Adaptive Interventions and Personalized Medicine
with Susan Murphy
November 4, 2014
In our latest podcast, Amanda Applegate interviews Susan Murphy, Methodology Center principal investigator, Herbert E. Robbins Distinguished University Professor of Statistics, research professor at the Institute for Social Research, and professor of psychiatry at the University of Michigan. The discussion focuses two topics, the sequential, multiple assignment, randomized trial (SMART), which allows scientists to develop adaptive interventions, and the just-in-time, adaptive intervention (JITAI), which uses real-time data to deliver interventions as needed via mobile devices. Susan’s MacArthur Fellowship is also discussed; the podcast was recorded before she was elected to the Institute of Medicine of the National Academies.
00:00 – Introduction
01:01 – MacArthur Foundation "Genius Grant"
03:31 – Two SMARTs in the field (one to develop an adaptive intervention for alcohol abuse and one to develop an adaptive intervention for helping clinics implement an intervention effectively)
12:44 – The just-in-time, adaptive intervention (JITAI)
18:34 – The future of SMART and JITAI
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Download the transcript for Podcast 19