麻豆淫院

The relationships between different people can change over time, as the result of their life choices, internal or external experiences and various other factors. Some people develop a greater tendency to avoid others in their lives, including friends, colleagues, family members and acquaintances.

Researchers at Icahn School of Medicine at Mount Sinai recently set out to test the hypothesis that social avoidance could be quantified as people's navigation in an abstract social space. Their paper, published in Communications Psychology, for studying and probing people's social avoidance.

"This work grew out of the idea that the way that people often talk about navigating social relationships鈥�'climbing the ladder' at work, or 'growing distant' from a friend鈥攎ight be more than a metaphor," Matthew Schafer, first author of the paper, told 麻豆淫院.

"Recent research, including some of our own prior work, suggests the brain uses map-like representations to understand the world and make decisions, even in abstract social situations.

"We wanted to test the hypothesis that social avoidance can be understood as a form of navigation within an abstract social space defined by two social dimensions: 'affiliation' (e.g., warmth, friendliness) and 'power' (e.g., dominance, control)."

Many past psychology studies focusing on social avoidance utilized self-report measures that asked participants to share their feelings, thoughts or attitudes about their social lives. Schafer and his colleague Daniela Schiller employed an alternative experimental paradigm, asking their study participants to take part in a "choose your own adventure" style game and observing their behavior.

"We put nearly 800 online participants into the position of having just moved to a new town, with no job, no friends and no place to live, where they had to interact with people and navigate the social situations to accomplish these goals," explained Schafer.

"Unbeknownst to the participants, the choices they made in the interactions changed the relationships in terms of affiliation and power. For example, declining to share personal information with a character would reduce the affiliation in the relationship, while complying with an overbearing and direct request from a character would reduce the participant's power."

After participants had taken part in this choice-based online game, they were asked to complete a questionnaire that prompted them to share information about their real-world feelings and behaviors. Schafer and Schiller subsequently analyzed the behavior of participants while they were playing the game using a geometry-based approach.

The researchers examined the locations of characters in the game within a grid that modeled these affiliations and power relations. These locations on the grid were calculated as the average of the participants' choices in the game on these two dimensions (i.e., affiliation and power).

"Finally, we compared these locations to the participants' questionnaire answers," said Schafer.

"Our most exciting finding is that we can quantify social avoidance through naturalistic behavior: people higher in self-reported social avoidance consistently made low affiliation and low power choices in our game, as we expected.

"This wasn't just a fluke鈥攚e saw the same result clearly across two large groups, and this pattern was specific to social avoidance, rather than general mood or compulsivity. The participants also described the game characters more negatively when asked to write about them afterwards."

Interestingly, Schafer and Schiller found that the "social distance" participants created between characters in the game they played mirrored their real social lives, as they were described in their self-report questionnaires. Specifically, the real-world social networks of participants who created more social distance between characters were found to be smaller and less diverse.

The experimental paradigm used by this team of researchers could serve as a powerful tool for studying social avoidance, framing it not only as a feeling, but also as a tangible social navigation strategy. In the future, it could help to gather valuable new insights, which could in turn inform the development of new interventions designed to improve people's social interactions.

As part of their next studies, Schafer and Schiller plan to continue building on their proposed experimental methods, while also using them to assess the social avoidance of individuals diagnosed with specific disorders. For example, they would like to use the same online game employed in their recent experiment to investigate the social difficulties of individuals diagnosed with social anxiety disorder.

"We also want to examine this behavior in clinical populations whose social difficulties are part of their diagnosis, like in autism or addiction, to better understand these conditions," added Schafer.

"We also want to make the game more realistic, for example, by using AI for more realistic character interactions, because watching behavior directly may offer richer insights beyond surveys. Ultimately, we see this approach as helping us track changes in social behavior over time, perhaps even during therapy, as a tool to better understand how social avoidance and its treatment manifests in social interactions."