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A podcast series produced by The Methodology Center providing information on the Center’s methods, applications, and events.
Social Network Analysis With Ashton Verdery
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.
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
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.
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
Audiobook Excerpt: Preface to Linda Collins’ Book on MOST
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.
References for the Book and the Articles Discussed in the Podcast
“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
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?
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
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
The Past, Present, and Future of Prevention with Mark Greenberg
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
Getting Started with Secondary Data Analysis
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
Ambulatory Assessment with Michael Russell
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
Practical Advice on LCA with John Dziak
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?
Methodological Innovation in HIV Prevention Research with Cara Rice
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