Applications to Health
Our lab is engaged in several social media and technology projects that use experiments, surveys, and social media data to study health promotion in the areas of HIV, harm reduction associated with drug use, and lifestyle.
Over two decades of NIH-sponsored grants, our lab has been discovering and applying theoretical principles to curb disease in areas related to HIV and other healthy lifestyle change.
Our lab is strongly committed to applying psychological and communication theory to the benefit of society, and have concentrated our efforts in modifying behaviors that pose risks to individual and population-level health.
- Designing nationwide programs to reduce the HIV and hepatitis C harm of the opioid epidemic in rural areas by bringing together communities and health agencies
- Designing methods to automatically disseminate of health messages to different types of counties in the United States
- Predicting the course of the HIV epidemic as a function of policies and communications
- Understanding how to change multiple behaviors
- Uncovering the complex effects of fear-based strategies in health communication
Despite its bad press, we have not found many conditions in which not highlighting risk or fear is better than doing so.
Unfortunately, health interventions attract those who already engage in healthy behaviors.
In HIV prevention interventions, we are often preaching to the choir. We find that studies tend to enroll people who are already engaging in prevention.
To attract a population, don’t sell change.
To increase enrollment in HIV-prevention interventions, it’s better to tell people that the intervention will give them choices, but that they may not change. We applied this program in health departments in Florida and empowering potential recipients to resist the intervention if they so wanted worked better than telling them that the intervention would work.
To attract a population to participate in interventions, go slowly.
It is better to get people to participate in minimalist interventions like reading a brochure first, and then move on to more to more intensive experiences, like watching an entire video or enrolling in counseling. A foot-in-the-door approach is the best way to get people on a path to healthier habits.
To increase the participation of women in health promotion interventions, use gender-targeted materials.
Even though, on average, men will read materials targeted for women or men, women respond better to materials that are targeting women.
On average, men enroll in health interventions for instrumental reasons and women for emotional ones.
Men are more likely to enroll in HIV interventions when financial incentives are greater. Women, on the other hand, are more likely to enroll when the interventions can also fulfill the need to discuss emotional issues.
Targeting is not as effective when people suspect that the targeting is prejudiced.
For stigmatizing health conditions, targeting messages around race can elicit negative emotions among African-Americans and decrease exposure.
To retain a population in a health intervention, sell the secondary but important benefits rather than change.
Even though a “soft sell” works to attract people to participate in a program, to retain them in an HIV-prevention intervention, you need a different approach. Rather than empowering, it is better to remind them of all the non-health benefits of participating. Will contact with a counselor help them to get the job they want? Can the hospital help with housing?
Moderation messages are better at anticipating people’s behaviors, and, therefore, are more successful.
Telling teenagers not to drink at all backfires but only after they drink. We must design messages anticipating the future behavior of an audience.
Future oriented tweets correlate with lower HIV prevalence in a region.
Yes, an analysis of the language of tweets in US counties shows that this is the case correcting for demographics.
Action tweets also correlate with lower HIV prevalence in a region.
The more that action words like “go” are used in tweets sent from a particular geographic region, the better the region is at curbing the spread of HIV. We think that activism in the region, or hope, correlates with healthier behavior.
Packaging actions or inactions is better for behavioral change.
When you’re trying to change several behaviors, you may be more successful if you decide to change either several actions or several inactions. However, mixing action and inaction goals appears to be counterproductive probably because action and inaction goals engage different brain structures.
Twitter can be used to measure beliefs, attitudes, and intentions to protect from infection with the Zika virus.
A hybrid, top-down/bottom-up approach to topical analysis of tweets over the course of the Zika epidemic showed that these topics correlate with beliefs, attitudes, and intentions. This was measured via a 30-week national survey conducted by the Annenberg Public Policy Center. One conclusion is that we can replace expensive survey methods with social media analyses, which work particularly well for attitudes and intentions.
Vaccine attitudes and behaviors are affected by tweets about vaccination fraud.
At the Annenberg Public Policy Center, 3,000 Americans reported their attitudes and behavior with respect to the flu vaccine over the course of a year, and our lab also collected tweets about vaccines. In locations where many tweets centered around vaccine fraud, big pharma, and children, people in those counties were less likely to get a flu shot in the months to come. However, this association was absent when people had discussions about vaccines with family and friends. Talking with family and friends can debunk misconceptions in the health domain.
The Affordable Care Act increased HIV Screening and led to more new diagnoses of HIV infections.
“Obamacare” actually led to decreases in HIV infections immediately after the policy implementation. We believe this took place because people without care could now be offered HIV tests, which led to earlier diagnoses and presumably linkage to care too. We came to this conclusion by comparing states with and without Medicaid expansion before and after the policy was implemented.
Altruism leads to greater vaccination in less crowded areas.
In a nationally representative longitudinal survey conducted at the Annenberg Public Policy Center and two laboratory experiments, we found that people are more likely to vaccinate to protect others when they reside in or think of low-density environments (i.e., non-metropolitan regions with lower population density and a less crowded store) than when they reside in or think of high-density ones (i.e., metropolitan regions with higher population density and a more crowded store). What drives the difference is that individuals in low-density environments believe that their behavior matters more than do their high-density counterparts.
In a health emergency, social media can raise the alarm but legacy media can teach the public what to do.
In our analysis of the Zika crisis, messages about Zika on social media raised risk perceptions but intentions and behaviors changed in response to the more extensive communication of legacy media.
Living in areas with more sexual minorities can protect their health through associations with more tweets about HIV.
Rates of Men Who Have Sex with Men appear to lead to more HIV tweets in a region, in-person communications about PrEP, and, ultimately, actual PrEP use.
Areas with greater religious attendance and more punitive religious leaders’ norms about drug policy have more punitive and less protective attitudes toward drug policy.
The rural opioid epidemic is of great concern for our lab. We have found that religious denomination does not affect whether you support incarceration, paying for treatment, or syringe exchange programs. However, if you attend religious services more and think that your religious leaders favor punitive policies, so do you. In those cases, you also favor protective policies like paying for treatment and providing people who inject drugs with clean syringes. Learn more.
Photo Credits (from top): iStock / Natali_Mis, iStock / Courtney Hale, Shutterstock / Marc Bruxelle, iStock / FG Trade