Investigating trajectories linking social cognitive capacity, bias, and social isolation using computational modeling

Despite theoretical emphasis on loneliness affecting social information processing, empirical studies lack consensus. We previously adopted a clinical science framework to measure the association between social cognitive capacity and bias and both objective and perceived social isolation in nonclinical participants. Our prior study found that while objective social isolation is linked to both social cognitive capacity and social cognitive bias, loneliness is associated only with the latter. This study extended our previous model using a computational approach to capture implicit cognitive processes. We replicated and extended our earlier findings with a new sample of 271 participants, using neuropsychological tasks and a dot-probe paradigm that was analyzed via Drift Diffusion Model. We presented two complementary trajectories of how social cognitive bias may arise: the increased propensity to engage with salient social stimuli or a decreased information processing capacity dependent on the presence or absence of potential social threats. Furthermore, we found evidence that loneliness is associated with the time needed for perceptual processing of stimuli, both directly and indirectly, via social cognitive bias. Taken together, the complex and context-dependent nature of information processing biases observed in the current study suggests that complex and multifaceted interventions should be implemented to counter social information processing biases in lonely individuals.

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Publication Details

Journal
Social Cognitive and Affective Neuroscience
Published
2024-12-19
DOI
https://doi.org/10.1093/scan/nsae088
Citations
3
Primary Topic
Mental Health Research Topics
Type
article
Field-Weighted Citation Impact
1.52

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article

Investigating trajectories linking social cognitive capacity, bias, and social isolation using computational modeling

Aleksandra Piejka, Marcelina Wiśniewska, Łukasz Okruszek, Marta Chrustowicz et al.
3 citations
Social Cognitive and Affective Neuroscience
Mental Health Research Topics
1.52
article

Investigating trajectories linking social cognitive capacity, bias, and social isolation using computational modeling

Aleksandra Piejka, Marcelina Wiśniewska, Łukasz Okruszek, Marta Chrustowicz, Szymon Mąka
article en
3 citations

Abstract

Despite theoretical emphasis on loneliness affecting social information processing, empirical studies lack consensus. We previously adopted a clinical science framework to measure the association between social cognitive capacity and bias and both objective and perceived social isolation in nonclinical participants. Our prior study found that while objective social isolation is linked to both social cognitive capacity and social cognitive bias, loneliness is associated only with the latter. This study extended our previous model using a computational approach to capture implicit cognitive processes. We replicated and extended our earlier findings with a new sample of 271 participants, using neuropsychological tasks and a dot-probe paradigm that was analyzed via Drift Diffusion Model. We presented two complementary trajectories of how social cognitive bias may arise: the increased propensity to engage with salient social stimuli or a decreased information processing capacity dependent on the presence or absence of potential social threats. Furthermore, we found evidence that loneliness is associated with the time needed for perceptual processing of stimuli, both directly and indirectly, via social cognitive bias. Taken together, the complex and context-dependent nature of information processing biases observed in the current study suggests that complex and multifaceted interventions should be implemented to counter social information processing biases in lonely individuals.

Social Cognitive and Affective NeuroscienceVol. 20(1)
Institute of Psychology (PL)
Narodowe Centrum Nauki, Narodowym Centrum Nauki
Reduced inequalities
Openalex Percentile: Top 15%
Mental Health Research Topics
1.52
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