This article was published in Scientific American’s former blog network and reflects the views of the author, not necessarily those of Scientific American
Early next year, 350 or so Penn State students and staff, as well as local retirees and others, will wander around State College, Pa., for three weeks, pausing intermittently to drop their heads down as they tap on smart phones to answer detailed questions about how they feel immediately after nearly every social interaction they have.
The potential for Nittany collisions aside, the tappers will be engaging in a novel $1-million research project designed to paint a rich, nearly real-time picture of how people experience their everyday interactions and maybe teach them how to be happier. Rather than aiming for a random sample to generate tedious trend results or one model that only describes the average behavior of all subjects or subsets of them (how bored I am of people protesting, "Not me!" when told of population results), the researchers plan to use the data to generate 350 models—one for each individual in the study.
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So if you're a subject in this study, it'll be the sociological or psychological equivalent to having your genome sequenced. You're going to know the excruciating details of how irrationally you respond to life, minute-by-minute, scenario-by-scenario.
The smart phones will be loaded with software that prompts subjects to regularly describe what happened in an interaction and their perceptions of their general, cardiovascular and gastrointestinal health, as well as whether specific interaction made them feel angry, happy, sad, etc., and whether they perceived the others involved as cold or friendly, dominant or submissive.
Study leader Nilam Ram, trained in quantitative psychology, studies longitudinal change in humans. "I come from a tradition of life-span developmentalists who started promoting change rather than stability in the 1970s, well, really it goes further back than that, but we're promoting a closer look at individual-level changes rather than population-level changes," he explains. "New technology is allowing us to push that perspective to the limit, and even in a mind exercise, consider that there is only one individual. How would you study that individual?"
Large-scale surveys have revealed a great deal in the past several decades about typical interpersonal relations. And observations of family dynamics in the laboratory, where subjects are hooked up to devices that read their physiology during play activities or heated discussions have revealed some fine-grain details of what goes on in our bodies and minds when we engage in life's recurring dust-ups.
In between are the highly non-linear social spaces where people actually experience their daily lives, and it has been hard for social scientists to find acceptable methods in today's environment of clenched-jaw human subjects committees to collect rich data on "in vivo" subjects in uncontrived settings. Smart phones are a technological solution to that problem, as they can be carried with us at all times—no lab-coated technician need wait behind a two-way mirror.
In a future iteration of this study, Ram plans for subjects also to wear small, quarter-sized monitors that record heart rate and other physiological functions. They would transfer the data via Bluetooth to a smart phone that then sends the data, along with information about the environment, wirelessly to a server. There, the data could be analyzed instantaneously and "an appropriate intervention message," Ram says, would be prepared and sent right back to the subject—real-time coaching.
So as well as gaining stronger scientific insights into a specific individual's day-to-day experiences, the findings could also be applied to improving individuals' overall health and well-being.
"Engineers have developed a whole set of methodology that takes in information in real time, say from a plane that is flying, models how the plane moves, and suggests adjustments that can be made, a little turn left, a little turn right, to keep the plane on track," Ram says. "We think the same ideas can be applied to human behavior. Our objective is to model how individuals 'fly' along, and then make suggestions for adjustments."
"For example, if we find in the stream of data we collect that an individual has a tendency to withdraw every time he or she meets with his or her boss, we can begin providing some guidance that may help those interactions go more smoothly. Ideally we might even be able to deliver those 'micro-interventions' right on the cell phone—with a text message appearing that says, "Okay, just take a couple of deep breaths and be assertive.'"
Will subjects be willing to divulge all this private information and do all the required data entry? Ram says the initial subjects will be highly motivated people who are interested in interpersonal issues and like contributing to scientific discovery.
"It's a pretty demanding study and over the course of one and a half years these people will learn a lot about themselves," Ram says.
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