Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Spatial navigation is one’s ability to travel through their environment to reach a goal location. Self-expansion is the motivation to increase one’s self-perception through engaging in novel activities. Our objective was to examine the relations among self-expansion, age, and navigation ability and investigate how one’s internal motivation may influence navigation performance across paradigms. Methods: In total, 33 younger adults (YAs; 19F, 14M, mean age = 25.0 ± 1.6) and 74 older adults (OAs; 52F, 22M, mean age = 69.5 ± 8.0) completed the following: Self-Expansion Preference Scale (SEPS), Wayfinding Questionnaire (WQ), Virtual Supermarket Task, Virtual Morris Water Maze (vMWM), and a Floor Maze Task (FMT). Mann–Whitney U tests and Spearman ρ correlations were used to examine differences in navigation performance between YAs vs. OAs and self-expanders vs. self-conservers, and relations among the measures, respectively. Results: YAs had lower vMWM completion times compared to OAs (p < 0.001). Self-expanders had better recall of the vMWM environment compared to self-conservers (p = 0.049), independent of age. Greater self-expansion in YAs was correlated with lower spatial anxiety (ρ = −0.356, p = 0.042) and faster completion of the FMT (ρ = −0.36, p = 0.042). Discussion: Our results build on established age-related deficits in navigation abilities to identify correlations of self-expansion and better performance in various navigation tasks. Independent of age, individuals with greater inclination towards self-expansion exhibit superior navigation abilities. Future research should explore underlying mechanisms driving these associations and investigate intervention strategies aimed at improving navigation skills in aging populations through increasing self-expansion.
Source: Brain Sciences
Authors: Melissa Ansara, MaKayla Duggan, Alana Schafer, Karina Villalobos, Alexis N. Chargo, Ana M. Daugherty, Taylor N. Takla, Nora E. Fritz
Institution: Wayne State University
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,654
OpenAlex ID: W4414240486
