Physical activity and facial affect recognition in older adults versus younger adults
- UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
- Samantha L. Dubois (Creator)
- Institution
- The University of North Carolina at Greensboro (UNCG )
- Web Site: http://library.uncg.edu/
- Advisor
- Jennifer Etnier
Abstract: The ability to successfully engage in social interactions requires social cognitive abilities, like emotion perception. The most prominent nonverbal cue used by humans to convey emotion is facial expressions, making facial affect recognition (FAR) an integral part of social interactions. Previous research has shown that compared to younger adults, older adults exhibit deficits in FAR. Since deficits in FAR are associated with impaired social functioning and social isolation, finding ways to preserve the FAR abilities of older adults is important for their health and quality of life. Physical activity has been shown to reduce cognitive declines associated with advancing age, but this research has only examined a subset of cognitive constructs, not including FAR. However, existing research provides evidence of several mechanisms through which physical activity may be positively associated with older adults’ FAR abilities. Furthermore, previous research with other populations has provided evidence that physical activity can benefit FAR, while also demonstrating a positive relationship between resting heart rate variability (HRV) indices of vagal tone and FAR. The purpose of this study was to collect cross-sectional data concerning the relationship between physical activity and FAR as well as resting HRV measures of vagal tone (root mean square of the successive differences, RMSSD; absolute power of the high-frequency band, HF power) and FAR in both younger and older adults. Younger adults (n=27) and older adults (n=16) self-reported their physical activity behavior using the Global Physical Activity Questionnaire (GPAQ), had their resting HRV measured using a Polar V800 chest monitor and receiver, and completed a FAR task using facial stimuli from the FACES database. RMANOVA revealed that the older adult group had a significantly slower overall response time compared to the younger adult group. Bivariate correlations were then conducted to investigate the relationship between physical activity, RMSSD, HF power, and FAR. Significant negative correlations between RMSSD, HF power, and response times were found, indicating that higher resting RMSSD and HF power were associated with faster response times. Finally, regression analyses were used with age category, physical activity and the interaction between age category and physical activity as predictors of FAR performance. Results revealed that neither physical activity or the interaction of age category and physical activity were significant predictors. Additional regression analyses were then conducted with age category RMSSD, HF power, and the interaction of age category with both RMSSD and HF power as predictors of FAR performance. Again, neither RMSSD, HF power, or the interaction of age category with either RMSSD or HF power were significant predictors of overall FAR performance. However, results revealed that HF power was a significant predictor of response time to angry facial stimuli. This study therefore provides preliminary evidence of relationships between physical activity, RMSSD, HF power, and FAR abilities. Since FAR deficits can negatively impact health and quality of life, future research is warranted to investigate the effect physical activity can have on the FAR abilities of older adults.
Physical activity and facial affect recognition in older adults versus younger adults
PDF (Portable Document Format)
1523 KB
Created on 5/1/2020
Views: 175
Additional Information
- Publication
- Thesis
- Language: English
- Date: 2020
- Keywords
- Facial Affect Recognition, Heart Rate Variability, Physical Activity
- Subjects
- Exercise $x Psychological aspects
- Heart beat $x Psychological aspects
- Aging $x Psychological aspects
- Emotion recognition
- Facial expression