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George A. Bonanno

Researcher at Columbia University

Publications -  269
Citations -  35756

George A. Bonanno is an academic researcher from Columbia University. The author has contributed to research in topics: Grief & Psychological resilience. The author has an hindex of 76, co-authored 250 publications receiving 30634 citations. Previous affiliations of George A. Bonanno include University of Hong Kong & University of British Columbia.

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Beyond normality in the study of bereavement: Heterogeneity in depression outcomes following loss in older adults

TL;DR: Health, financial stress, and emotional stability emerged as strong predictors of variability in depression only for some trajectories, indicating that depression levels do not have a common etiology across all the bereaved.
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Complicated grief and deficits in emotional expressive flexibility.

TL;DR: Bereaved adults who lost their spouse 1.5-3 years earlier and a comparable sample of married adults exhibited deficits in expressive flexibility, and the CG group was less able to enhance and more able to suppress emotional expression relative to asymptomatic bereaved and married adults.
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Distress trajectories at the first year diagnosis of breast cancer in relation to 6 years survivorship.

TL;DR: To explore how initial trajectories of distress experienced during the first year following diagnosis with early‐stage breast cancer relate to subsequent long‐term psychosocial outcomes.
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When distress does not become depression: emotion context sensitivity and adjustment to bereavement.

TL;DR: Although positive emotions were beneficial regardless of context, context sensitivity for negative emotions at 4 months predicted fewer depression symptoms at 18 months, suggesting the capacity to shift negative emotion responses according to changing context may differentiate those individuals who will show improvements in depression symptoms over time from those who will showing chronic impairments.
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Stepping Off the Hedonic Treadmill: Individual Differences in Response to Major Life Events

TL;DR: This paper used latent growth mixture modeling to identify specific patterns of individual variation in response to three major life events (bereavement, divorce, and marriage) and found that a four-class trajectory solution provided the best fit for bereavement and marriage.