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Among high school students in the United States, cigarette smoking is down over 20% compared to the mid-1990s. Alcohol abuse and illegal drug use are also declining.
To prevent and treat substance abuse problems, scientists have to understand how and why they occur. Because there is more than one way to connect risk factors to substance use, scientists often have to take an indirect path that considers variables like parenting style or peer influences.
“Most research looks at the relationship between two variables – like risk taking and substance use – but there can be a lot happening in between, and those ‘third variables’ can cause the outcome,” said David MacKinnon, Foundation Professor of psychology at Arizona State University.
When a third variable transmits the effect of one variable to another, it is called mediation. Measuring the effects of third variables with mediation is a commonly used statistical method in biology, sociology, medicine and psychology.
Beginning in the late 1980s, MacKinnon started using and improving mediation analyses to better understand how drug prevention programs work. This type of research can uncover why some programs work for certain kids but not others. Mediation is now one of the most powerful tools used by scientists who develop interventions to prevent social, mental health, physical and academic problems.
Forty years ago, school-based programs were the most effective option to prevent drug use, especially for cigarette smoking. Understanding how the programs kept children from smoking required measuring how the program changed third variables. MacKinnon and his collaborators considered third variables like how tolerant the school environment was of drug use and whether smoking was considered socially acceptable by peers.
In the case of a school-based drug prevention program, a third variable like school environment transmits the program’s effects to drug use among students. Though this third variable lies along an indirect pathway between the prevention program and drug use, it is directly involved in causing drug use or abstinence.
“We knew the program worked, but I wanted to understand how,” MacKinnon said. “Mediation analysis lets researchers extract more information from the data, and this information lets us know how things work and how to make programs more powerful, efficient and shorter.”
MacKinnon has also used mediation analysis to understand how steroid prevention programs work for high school football players and health interventions work for firefighters.
Once researchers have information about how a prevention program changes third variables, they can assess how well a program works for people of different ages, ethnicities, genders and socioeconomic status. Researchers can also use information from mediation analyses to improve prevention programs by targeting new third variables.
MacKinnon’s path to bringing mediation to the field of prevention science includes attending Harvard University as a first-generation college student and a stopover in Spain, where he played a season of professional hockey for Futbol Club Barcelona after graduating.
While home from college, MacKinnon worked at a summer camp for children with mental health disorders and at an institute that served children with autism. Those experiences led him to quantitative psychology, combining his love of math and wanting to help people.
When MacKinnon suggested using mediation to understand how and for whom prevention programs work, he had recently earned his doctorate from the University of California, Los Angeles and was working at the University of Southern California Institute for Prevention. He joined the ASU Department of Psychology as a professor soon after, founding the Research in Prevention Lab. So far, MacKinnon’s work on mediation has led to nearly 200 publications and a Method to Extend Research in Time (MERIT) award from the National Institutes of Health, an honor given to only the handful of research programs that receive the highest possible rating. Since 2014, MacKinnon has twice been named in the top 1% of researchers based on the number of times his publications have been cited by others.
MacKinnon is a founding member of the Society for Prevention Research, which promotes research into the causes and prevention of social, mental health, physical and academic problems. Many, if not all, of the society members use mediation in their research.
Despite the widespread impact of his research, MacKinnon says without hesitation that what he is most proud of in his career is the success of his students.
In 2007, he won ASU’s Outstanding Mentor Award. One of the commenters for the award was JeeWon Cheong, who graduated with her doctorate in psychology from ASU in 2002 and is now a professor of psychology at the University of Florida.
“When I started working in his lab as a research assistant, I was a shy international student whose English was not fluent at all. Dave was extremely kind and patient. He always emphasized the positive, focusing on what I did well, while turning the negative into opportunities to handle the challenges in research,” Cheong said.
Another student, Oscar Gonzalez, said MacKinnon trained all his students to have a sense of independence while being a team player and insisting that their research should have a purpose, like helping prevention scientists.
“Dave MacKinnon saved my career. At the end of my first year of graduate school in 2014 my dear mentor and adviser Roger Millsap died, and Dave was immensely supportive and promptly invited me to join his lab,” said Gonzalez, who graduated with his doctorate in psychology from ASU in 2018 and is now an assistant professor of psychology at the University of North Carolina. “Dave’s excitement about work and science is contagious and is probably why I decided to follow a similar path. I’m now in my second year as a tenure-track assistant professor, and my admiration for Dave has grown exponentially now that I am on the other side of the desk.”
MacKinnon’s former students now work as professors at universities across the world, as data scientists in health care, in county and state departments of public health and the nonprofit sector.