Background: Previous studies have shown affective and physiological states in response to exercise as predictors of daily exercise, yet little is known about the mechanism underlying such effects.
Purpose: To examine the mediating effects of self-efficacy and outcome expectancy on the relationships between affective and physiological responses to exercise and subsequent exercise levels in endometrial cancer survivors.
Methods: Ecological momentary assessment (EMA) surveys were delivered up to eight 5- to 7-day periods over 6 months. Participants (n = 100) rated their affective and physiological states before and after each exercise session (predictors) and recorded their self-efficacy and outcome expectancy each morning (mediators). Exercise (outcome) was based on self-reported EMA surveys and accelerometer measures. A 1-1-1 multilevel mediation model was used to disaggregate the within-subject (WS) and between-subject (BS) effects.
Results: At the WS level, a more positive affective state after exercise was associated with higher self-efficacy and positive outcome expectation the next day, which in turn was associated with higher subsequent exercise levels (ps < .05). At the BS level, participants who typically had more positive affective and experienced less intense physiological sensation after exercise had higher average self-efficacy, which was associated with higher average exercise levels (ps < .05).
Conclusions: In endometrial cancer survivors, affective experience after exercise, daily self-efficacy and positive outcome expectation help explain the day-to-day differences in exercise levels within-person. Findings from this study highlight potentials for behavioral interventions that target affective experience after exercise and daily behavioral cognitions to promote physical activity in cancer survivors' everyday lives.
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http://dx.doi.org/10.1093/abm/kaz050 | DOI Listing |
JMIR Ment Health
December 2024
Faculty of Applied Computer Science, Augsburg University, Augsburg, Germany.
Background: The rise of wearable sensors marks a significant development in the era of affective computing. Their popularity is continuously increasing, and they have the potential to improve our understanding of human stress. A fundamental aspect within this domain is the ability to recognize perceived stress through these unobtrusive devices.
View Article and Find Full Text PDFInfant Behav Dev
December 2024
Department of Psychology, the University of Texas at Austin, Austin, TX 78712, United States.
Physical contact between infants and caregivers is crucial for attachment development. Previous research shows that skin-to-skin contact after birth and frequent baby wearing in the first year predict secure attachment at 12-months. This relationship is thought to be mediated by the activation of infants' parasympathetic nervous system through caregiver touch.
View Article and Find Full Text PDFSpectrochim Acta A Mol Biomol Spectrosc
December 2024
Hubei Key Laboratory of Cognitive and Affective Disorders, Institute of Biomedical Sciences, School of Medicine, Jianghan University, Wuhan, China. Electronic address:
Acetylcholinesterase (AChE) plays a vital role in various neurological diseases including brain disorders, neurotransmission alterations, and cancer. Developing effective methods to image AChE in biological samples is essential for understanding its mechanisms in biosystems. Here, we introduce a novel fluorescent probe CNA, that enables detection of AChE at 520 nm with rapid response time of 60 s and a detection limit of 0.
View Article and Find Full Text PDFBrain Inform
December 2024
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Affective computing is a key research area in computer science, neuroscience, and psychology, aimed at enabling computers to recognize, understand, and respond to human emotional states. As the demand for affective computing technology grows, emotion recognition methods based on physiological signals have become research hotspots. Among these, electroencephalogram (EEG) signals, which reflect brain activity, are highly promising.
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