Cynthia Rohrbeck

Associate Professor

George Washington University

United States

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Cynthia Rohrbeck is an Associate Professor at The George Washington University in the United States. Her research focuses on college stressors, emotional support, and the psychological impacts of disasters and health on well-being. Recent articles explore themes such as the interaction between reinforcement sensitivity and student anxiety, as well as the use of Artificial Intelligence to assess subjective well-being across diverse populations.

Articles (10)

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2025

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2025

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2025

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2025

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2025

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2024

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2024

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2024

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2023

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2023

Collaborators (1)

Germano VERA CRUZ

Full Professor of Health Psychology

Université de Picardie Jules Verne

FRANCE

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Cynthia Rohrbeck

Research Interests

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Articles (10)

The best years of our lives? College stressors and reinforcement sensitivity interact when predicting worry and panic among students

The best years of our lives? College stressors and reinforcement sensitivity interact when predicting worry and panic among students

Optimism and emergency preparedness self-efficacy: Moderators of the relationship between perceived threat of disasters and COVID-19 anxiety symptoms

Using Artificial Intelligence to assess the impact of social, physical, and financial health and personality on subjective well-being in a representative, multinational sample of older European and Israeli adults

Using Artificial Intelligence to assess the impact of social, physical, and financial health and personality on subjective well-being in a representative, multinational sample of older European and Israeli adults

Age differences in emotional support buffering on the relationship between physical disability and psychological distress

Measuring personal emergency preparedness: validation and application of the emergency preparedness checklist

Measuring personal emergency preparedness: validation and application of the emergency preparedness checklist

Using artificial intelligence to identify the top 50 independent predictors of subjective well-being in a multinational sample of 37,991 older European & Israeli adults

Using artificial intelligence to identify the top 50 independent predictors of subjective well-being in a multinational sample of 37,991 older European & Israeli adults

Collaborators (1)

Germano VERA CRUZ

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