Annals of behavioral medicine : a publication of the Society of Behavioral Medicine · 2020
Real Men Don't Cry: Skill Expressing Discrete Emotions Differentially Predicts Cardiovascular Disease Risk in Men and Women.
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Thompson Laura M, Tuck Natalie L, Pressman Sarah D, Consedine Nathan S
Аннотация
BACKGROUND: Expressing emotions effectively is central to social functioning and has links to health and cardiovascular disease (CVD) risk. Previous work has linked the ability to smile to lower CVD risk in men but has not studied other expressions or considered the context of these skills.
PURPOSE: To test whether the ability to express fear, anger, sadness, happiness, and disgust cross-sectionally predict CVD risk in both genders and whether links are moderated by the ability to decode others' emotional signals.
METHODS: A community sample of 125 men and women (30-75 years) provided trait emotion data before a laboratory visit where blood was drawn and performance-based assessments of the ability to signal and decode emotions were administered. Expressive accuracy was scored using FaceReader software. Projected CVD risk was calculated using Framingham, a New Zealand (NZ) specific, and Atherosclerosis CVD (ASCVD) risk algorithms.
RESULTS: Accuracy expressing happiness predicted lower projected risk, whereas greater accuracy expressing fear and sadness predicted higher risk. Gender frequently moderated these links; greater accuracy expressing happiness predicted lower risk in men but not women. Conversely, greater accuracy expressing fear predicted higher risk in men, whereas greater accuracy expressing sadness predicted lower risk in women but, again, higher risk in men. The ability to accurately decode others' emotions moderated some links.
CONCLUSIONS: The ability to signal emotion has complex links to health parameters. The ability to flexibly regulate expressions in accordance with gender norms may be one useful way of thinking about adaptive expressive regulation.
PURPOSE: To test whether the ability to express fear, anger, sadness, happiness, and disgust cross-sectionally predict CVD risk in both genders and whether links are moderated by the ability to decode others' emotional signals.
METHODS: A community sample of 125 men and women (30-75 years) provided trait emotion data before a laboratory visit where blood was drawn and performance-based assessments of the ability to signal and decode emotions were administered. Expressive accuracy was scored using FaceReader software. Projected CVD risk was calculated using Framingham, a New Zealand (NZ) specific, and Atherosclerosis CVD (ASCVD) risk algorithms.
RESULTS: Accuracy expressing happiness predicted lower projected risk, whereas greater accuracy expressing fear and sadness predicted higher risk. Gender frequently moderated these links; greater accuracy expressing happiness predicted lower risk in men but not women. Conversely, greater accuracy expressing fear predicted higher risk in men, whereas greater accuracy expressing sadness predicted lower risk in women but, again, higher risk in men. The ability to accurately decode others' emotions moderated some links.
CONCLUSIONS: The ability to signal emotion has complex links to health parameters. The ability to flexibly regulate expressions in accordance with gender norms may be one useful way of thinking about adaptive expressive regulation.