School of Medicine Publications and Presentations

HARMONY IN NUMBERS: UNRAVELING THE TAPESTRY OF SOCIAL BONDS THROUGH AN INNOVATIVE MODEL OF INTERACTION

Document Type

Conference Proceeding

Publication Date

2024

Abstract

Background: Social interaction is fundamental to the functioning of everyday life in both animals and humans. For instance, research on social interaction has revealed that a lack of it can lead to the development of altered behavioral effects such as depression, aggression, and anxiety (Andrade et al., 2023). Some datasets provide data on how much people interact with one another; however, the National Alzheimer's Coordinating Center (NACC) does not have this explicit metric included. To circumvent this limitation within the NACC dataset, the current study proposes the use of a latent variable for the measurement of social interaction.

Method: The current study will utilize data from +47,000 individuals in the NACC dataset to develop a latent variable model that assesses social interaction. The latent variable will consist of four questions from the NACC dataset which are: living situation, level of independence, type of residence, and ability to shop alone. A structural equation model was conducted to determine whether the model has a proper index of fit. The latent variable was compared to the observed variable of dependability using items from the Functional Assessment Scale.

Result:A chi-square analysis revealed high correlation between the variables (X2 (63, 128098 = 191601, p

Conclusion: The NACC dataset provides valuable information of health outcomes of older adults in the United States of America; however, the dataset lacks an important component which is measurement of social interaction. To our knowledge, the current study was the first that has attempted to create a direct way of measuring social interaction within the NACC dataset.

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Permanent Link: https://perma.cc/J4UD-8QBN

Publication Title

TARCC 2024 Scientific Symposium

Academic Level

faculty

Mentor/PI Department

Neuroscience

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