Daily Gender and Cognition: A Person-Specific Behavioral Network Analysis

Abstract

Gender is person-specific, and it influences and is influenced by a breadth of multidimensional psychological factors, including cognition. Directionality is important for research on gender and cognition, as debate surrounds, for instance, whether masculine self-concepts precede spatial skills, or whether the reverse is true. In order to provide novel insights into the individualized nature of these relations, a person-specific network approach devised by Peter Molenaar and the first author – group iterative multiple model estimation for multiple solutions (GIMME-MS) – was applied to 75-day intensive longitudinal data on gender self-concept (i.e., femininity-masculinity, instrumentality, and expressivity) and cognition (i.e., mental rotations and verbal recall) from 103 young adults. GIMME-MS estimates individualized networks that contain same-day and next-day directed relations, prioritizing relations common across participants. It is ideal for analyzing behavioral time series with unclear directionality, as it generates multiple solutions from which an optimal one is selected. GIMME-MS revealed notable heterogeneity in the presence, direction, and nature of relations from gender self-concept to cognition (∼26% of participants) and vice versa (∼21% of participants). Findings are wholly novel in revealing the person-specific nature of gender and its cognitive dynamics, yet somehow, unsurprising given the revolutionary corpus of Peter Molenaar.

Keywords:

• GIMME
• idiographic
• intensive longitudinal design
• spatial skills
• verbal skills

Article information

Conflict of interest disclosures: Each author signed a form for disclosure of potential conflicts of interest. No authors reported any financial or other conflicts of interest in relation to the work described.

Ethical principles: The authors affirm having followed professional ethical guidelines in preparing this work. These guidelines include obtaining informed consent from human participants, maintaining ethical treatment and respect for the rights of human participants, and ensuring the privacy of participants and their data, such as ensuring that individual participants cannot be identified in reported results or from publicly available original or archival data.

Funding: A. Beltz was supported by the Jacobs Foundation. D. Kelly was supported by a Katz Fellowship from the Institute for Social Research at the University of Michigan.

Role of the funders: None of the funders or sponsors of this research had any role in the design and conduct of the study; collection, management, analysis, and interpretation of data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.

Acknowledgments: The authors thank all past and present members of the M(SD) Lab at the University of Michigan for their tireless assistance with data collection, management, and processing as well as the participants who made this research possible. The ideas and opinions expressed herein are those of the authors alone, and endorsement by the authors’ institution is not intended and should not be inferred.