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. 2021 Oct;5(10):1381-1390.
doi: 10.1038/s41562-021-01113-9. Epub 2021 May 13.

Tracking developmental differences in real-world social attention across adolescence, young adulthood and older adulthood

Martina De Lillo  1 , Rebecca Foley  1 , Matthew C Fysh  1 , Aimée Stimson  1 , Elisabeth E F Bradford  1   2 , Camilla Woodrow-Hill  3 , Heather J Ferguson  4
Affiliations

Tracking developmental differences in real-world social attention across adolescence, young adulthood and older adulthood

Martina De Lillo et al. Nat Hum Behav. 2021 Oct.

Abstract

Detecting and responding appropriately to social information in one's environment is a vital part of everyday social interactions. Here, we report two preregistered experiments that examine how social attention develops across the lifespan, comparing adolescents (10-19 years old), young (20-40 years old) and older (60-80 years old) adults. In two real-world tasks, participants were immersed in different social interaction situations-a face-to-face conversation and navigating an environment-and their attention to social and non-social content was recorded using eye-tracking glasses. The results revealed that, compared with young adults, adolescents and older adults attended less to social information (that is, the face) during face-to-face conversation, and to people when navigating the real world. Thus, we provide evidence that real-world social attention undergoes age-related change, and these developmental differences might be a key mechanism that influences theory of mind among adolescents and older adults, with potential implications for predicting successful social interactions in daily life.

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Conflict of interest statement

Competing interests

The authors declare no competing interests.

Figures

Figure 1
Figure 1. The proportion of time spent fixating each AoI in each condition and age group in the face-to-face conversation task.
The plots show raw data points, a horizontal line reflecting the condition mean, and a rectangle representing the Bayesian highest density interval. The top panels show the proportion of time spent fixating face features, body and background in the main analysis, and the bottom panels show the proportion of time spent fixating posters depicting averted gaze, direct gaze and a neutral (non-social) scene.
Figure 2
Figure 2. The proportion of time spent fixating each AoI in each age group in the navigation task.
The plot shows raw data points, a horizontal line reflecting the condition mean, and a rectangle representing the Bayesian highest density interval.
Figure 3
Figure 3. The proportion of time spent fixating people in each age group in the navigation task, controlling for the time that people were visible in the environment.
The plot shows raw data points, a horizontal line reflecting the condition mean, and a rectangle representing the Bayesian highest density interval.
See this image and copyright information in PMC

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