From Houston to Hanukkah: The Psychological Benefits of New Experiences

Last week, after finishing a presentation at the National HIV Prevention Conference, I took a cross-country flight from Atlanta to Los Angeles (via Houston). After boarding the plane, I found my seat next to a middle-aged woman. To be courteous, I introduced myself to her. In a distinct Southern drawl, she told me her name was Laura and that she was flying home to Houston to spend Christmas with her family.

I nodded and began to arrange my carry-on items. I started a mental review of what had transpired at the conference: who I’d met, whether my presentation was successful, and what I had to do when I arrived home.

"Do you live in Houston?” Laura asked.

“No,” I said, welcoming the break in silence to learn about her life. I explained that I was returning from a meeting and was anxious to get home after a busy schedule of traveling the past few weeks.

“I understand,” she said. “I’m looking forward to the holidays to relax with my family. I planned to use this flight to do some Christmas shopping. Have you finished your Christmas shopping?”

 “Well, I’m Jewish. We celebrate Hanukkah,” I said. “So luckily, I’m already done with most of my shopping.”

“Oh,” she said. She opened her laptop, paused, and said, “That’s great. I know someone who’s Jewish.”

I laughed. “On behalf of our people, I hope he or she didn’t disappoint you,” I joked.     

Despite our apparent differences, we wound up talking throughout the flight—about her transition from an accountant to an event planner, my work as a behavioral scientist, and about life in Los Angeles vs. Houston. I realized that by the end of the two-hour flight we knew a lot about each other’s lives and beliefs. “You have to see the rodeo in the spring,” she said as we touched down in Houston. Before heading out, she handed me a piece of paper with her email address and phone number. “Come visit during March. My husband and I would love to show you a real Texas rodeo,” she said, with a wink and genuine warmth.

On the second leg of my trip, I thought a lot about Laura. Before meeting her, I would have thought we’d have little to talk about, no common ground. Her views and daily life were way out of alignment with my own, yet getting to know her turned out to be one of the highlights of my short trip.

Research has shown that we prefer to associate with people who think like we do. This tendency, known as confirmation bias, is the behavior of seeking or interpreting ideas in a way that favors personal beliefs. Finding ways to understand confirmation bias is a major feature of the work of Jonathan Haidt, author of The Righteous Mind. Dr. Haidt focuses on the world of politics, but his underlying theme is that relationships shouldn’t simply be about trying to sway or inform people. Rather, every relationship offers the opportunity to learn a new perspective—something I always try to keep in mind.

Being open to a conversation with a stranger on a plane (or on your local street corner) won’t cure the world’s ills, but it’s a start at uniting people from different backgrounds and cultures, and it might lead to a new friendship—or even the opportunity to attend a rodeo.

Sean Young, PhD, Reports Back from CDC HIV Conference on New Year's Resolutions

1. As a psychologist and researcher, what are the hardest New Years Resolutions for you to stick to?  Do you find that professional goals are easier to achieve than personal goals?

I wouldn't say the difficulty is broken down by professional goals vs personal ones. The great thing about psychology is that it doesn't care about domain. It doesn't care whether people are making resolutions to change business goals, health goals, relationship goals, or any other goals. What matters is the context of those goals, within the person, their surrounding, and their experience. That's a bit vague so I'll be more concrete.

The hardest New Years Resolutions to stick to are ones that require the biggest change in lifestyle to keep. If something is really tough to change, it will be tough to keep. If it's easy to change, it will be easier to keep. Take dieting as a resolution. My undergrad professor, Traci Mann, has done a lot of research and shown that diets don't work. Aside from biological reasons in people's genetics, most diets fail because they're diets, or big immediate changes in people's behaviors. They have been eating unhealthy food for a long time and decide that because it's the New Year, they'll have the ability to instantly change the way they eat. Most New Years Resolutions fail for the same reason. People want to instantly change something that has been part of their lifestyle for weeks, months, or years.

So the bad news is, New Years Resolutions need to be kept in perspective with how people have been living. If a person walks 50 steps a day, making a resolution to walk 10,000 steps a day won't last. The good news is, that there are ways to keep resolutions. People just need to keep them in perspective and make resolutions that are manageable. There are a lot of other ways to help keep on track based on our research. Some of these I mentioned in last week's Q and A, like the science of social. 

2. After attending the CDC's recent HIV prevention conference in Atlanta, do you find yourself shifting your own priorities to align with the research community as a whole?

I've realized I've been a researcher my whole life. It started long before my research assistant days at UCLA or doctoral work at Stanford. It started as a child as I loved learning about things and how they work. One of the most important things that I keep learning is that I need to always keep an open mind. I need to always listen to other people's ideas and perspective, no matter how crazy people might think they are, because I learn from them and it helps to guide my research. That's a broad answer to your question. The straight answer is, definitely. I'm constantly rethinking studies, research, and my own assumptions based on what I learn from the research community as well as everyone else. I learned a lot about people's perceptions of PREP at the HIV prevention conference in Atlanta and have been thinking about how technologies can be incorporated into Prep education and behavior change.

3. What are the main takeaways that you got from the CDC conference?  Where will HIV prevention be at this point in 2016?

The main takeaways is that although there is still a lot of work to do to reduce the spread of HIV, we've been getting some answers. Really importantly, we've been having support for controversial approaches from top officials, like the NIH director support use of Prep. For me, as a technology researcher wanting to find ways to predict, prevent, and change HIV risk, the main takeaways is that there is so much opportunity for tools to be used in this space. Researchers are very open to these tools but don't have the time to be aware of them. Because innovation and tech tools seem to always be at the forefront of how HIV is spread, we need to use that innovation to prevent and stop the spread of HIV. I'm excited that our team has the ability to do that and we're getting a great response from people all over the world who want to work with us and apply our research.

4. What steps can clinicians, families and societies take to remove the stigma from both HIV prevention pills and HIV testing?

Stigma is the belief that a person or thing is unwanted, disgraced, or or shameful. It can lead to a lot of negative consequences. When people are stigmatized they feel badly about themselves, they can lose their friends and family, their jobs, and can have worse health. When things are stigmatized, like getting an HIV test, it makes people to not want to do them. We've done a lot of studies on how stigma works and how it stops people from taking care of their health. (One of those studies you might like involved telling students they were at risk for a disease, and learning they they more or less convinced themselves they couldn't have contracted a disease if it was stigmatized).

Stigma is caused by lack of knowledge, lack of discussion, and lack of normalcy. The way to reduce or get rid of stigma is to educate people, make them aware of how stigma works, and make them see the stigmatized person or thing is common. For example, HIV testing is stigmatized. Just showing up to an HIV testing site could make people stigmatized. They could be judged by others in the clinic, by their doctors, by people seeing them getting tested. They could be judged as being "the type of people" who have HIV. To reduce this stigma, we can do things like talking about testing more, getting people to test more, and making testing more public so that people can see how many people test for HIV and that people from all ages, races/ethnic groups, and educational statuses test for HIV. That's great that so many people test, and it needs to be made more public. We found that stigma could be reduced by making the stigmatized thing (for example, testing) required. We also found that offering it in traditional settings like in vending machines may reduce stigma and get more people to test for HIV. 

5. What steps can Grindr, Tinder, Match.com and other online dating websites take to help prevent HIV?

These are dating/hook-up businesses and so they're less interested in preventing HIV than in their business, so I wouldn't expect them to make any major changes to help prevent HIV. Some of them are concerned about losing users if they try to promote HIV testing as they don't want to be branded as a public health site or place that is trying to get people to do anything other than find dating or hook-up partners. That being said, there are a few things they can do that could help prevent the spread of HIV and shouldn't negatively impact their business. First, they can be open to HIV researchers. Second, they can offer a feature that allows people to say if they have gotten an HIV test. Third, these sites and researchers can begin sharing data with each other to mutually find how to make their users safer and healthier.

Dr. Sean Young Report from NIH BD2K All Hands Grantee Event

1. What were your biggest take-aways from the BD2K All Hands Grantee event at the NIH?

The meeting focused a lot on data science approaches like creating new machine learning models. One researcher (Dr. Jiawei Han) who leads an expert group out of UI Urbana-Champaign had a poster showing some impressive new methods for data analysis methods. People were definitely interested in our approaches for social data also as they see the importance of data from new media being used to predict events and be used to solve real-world problems. I think the biggest take-away is that the "big data" area isn't going away anytime soon. The government and companies are putting a lot of resources behind studying this area and see huge potential in how it can change our life and work. It's always exciting being a part of an early movement where there is excitement and a lot of promise. Now that researchers know we have support, it's up to us to deliver on that promise.

2. Have you had specific feedback from the NIH on treating social media in a "serious," epidemiological research area? Did you find others at the BD2K event who are open to your ideas?

People are very open to the idea. Timing is great. I've been studying this area for over 10 years and it's actually the first time where almost everyone understands my research. That might sound crazy, but it's actually pretty common for researchers to be working on things that no one else understands, especially if it's related to technology. But people who used to question whether social media and technologies were a fad now so the tremendous amount of data from these technologies. They understand the area we're studying at a high level and when we show them specific examples of the things people say on twitter, or how people use wearable devices, they really get it. They understand our research, the potential of what we're building and studying, and how it can impact society. It's exciting to be able to share this with people.

3. Are there new or upcoming types of data that you would like to include in your research, that only the NIH can give you access to?

I have a call this morning with the Centers for Disease Control and Prevention (CDC). They're really interested in having us modeling ways to monitor and predict disease. They'll be supplying datasets of disease across the country. We're also looking into game forum datasets from people who play and are interested in video games. We have a lot of data stored and ready to go for analysis.

4. If you could explain the value of BD2K grants to a layman, how would you put it?  What kind of return on investment has there been?

Science is based on math and statistics, but statistics are dependent on data. If enough data aren't available, then the statistics won't mean anything. I was walking my dog the other day and she decided to do one of her infamous "i'm done walking" tricks where she drops to the ground in the middle of the walk and won't move. She's scared of the sound of trashtrucks, and whenever a trashtruck comes by she drops and tries to take cover. A woman saw me, crossed the street, and told me the fact that my dog was doing that means she has bad joints and I need to get her to the vet immediately. When I asked her why she said that, she explained to me that her 10 year old dog does this and has bad joints. She surmised that my dog must have bad joints too. She didn't seem willing to listen to the old correlation is not causation argument.

The point is, people often come to incorrect conclusions because they don't have enough data. A vet would be less likely to have made the conclusion the woman did about my dog, not because vets are smarter or even because they have studied this, but because they see many more of these cases and therefore have a lot more data points to know when dogs drop to the ground because they're scared and when they do it because they're injured. The area of "big data" promises to give us a lot more data in order to analyze trends and outcomes and have more accuracy in our conclusions. There's a huge opportunity for a return on investment in this area. It not only allows us to be more accurate, but as in our work, it provides us with the ability to predict events we couldn't have predicted before. That means the ability for huge social returns like preventing disease and reducing poverty, and financial returns like predicting the stock market and finding the right audience of customers who want to buy products.

5. During the event I noticed you live Tweeting.  Did the use of social media change the way that you and your fellow researchers interact at an NIH event?

Most NIH researchers, or scientists in general, aren't big on tweeting. Most researchers are interested in doing their work and leave it up to others who may want to get their work out to the public. I find it tough to tweet and learn and that same time but I try because I think it's important to let the world know about what is happening in the science, tech, and public health community and I enjoy interacting with them about it.

6. A lot of the researchers at the BD2K event were focused on genomics and phenotype data collection.  Do we need to import terminology like genotype and phenotype into the study of social media to gain more understanding from the research community?  Are those terms already being used?

Genomics is a big area of study among big data researchers for a few reasons, but the most important reason is that we have a LOT of genome data. In order to do big data research, we need a lot of data, so researchers interested in this area often gravitate toward genomics. A lot of the advanced learning models are built on genomics data. When we work with a researcher like our own Professor Wei Wang, an expert in data mining, she has expertise in genomics data. She brings that language with her to our work. I therefore think it's unavoidable when working with experts in big data to not use language often used in genomics research. That's a good thing because it's gives a common language that people can use, but social data are different than genomics data, so we'll need to develop our own variation of the language over time.

7. What kind of improvements or additions would you like to see added to next years BD2K All Hands Grantee event?

The point of the meeting was to encourage cross-collaboration and talking between different groups and researchers. Doing multi-disciplinary work is something that universities and government always talk about and encourage, but they don't usually provide incentives for doing it. For example, researchers are supposed to publish their research, but most of the top journals are focused on one area, for example, cardiology or social psychology, and the researchers reviewing the science for those journals don't usually have interest or experience in other areas. That means that researchers doing interdisciplinary work have a tougher time getting their work respected and known. The big data area is designed to be interdisciplinary. Next year's meeting could really move forward by creating incentives for researchers to publish interdisciplinary work, like dedicated top journals and funding for projects that bring together experts from different fields to solve important problems.