Date of Award

2022

Degree Type

Thesis

Degree Name

Master of Arts (MA)

Department

Psychology

Abstract

Depression negatively impacts the lives of many, and the rates are continuing to rapidly increase. Identifying patterns of modifiable affective psychological mechanisms that contribute to reducing depression symptoms is critical to improve the effectiveness of wellbeing interventions for individuals with depressive disorders. Depression has been characterized by valanced patterns of low positive affect and high negative affect, yet the extent to which these relative patterns of affectivity change in response to intervention remains less clear. The present study evaluated affective patterns in college students (n = 127) with elevated depression symptoms who participated in a randomized controlled trial (RCT) of a mindfulness-based intervention (MBI) delivered via a mobile application (app; Headspace). We used an exploratory approach to evaluate the role of affective patterns (e.g., positive affect, negative affect, and emodiversity) in facilitating a reduction in depression symptoms during the RCT. Results showed that only change in positive affect significantly mediated the relation between RCT study group and depression symptoms, such that an increase in positive affect was related to reduced depression symptoms for the treatment group. It is critical that future clinical science research identifies evidenced-based strategies and interventions that enhance the capacity for experiencing positive affect and emotions in individuals with depression symptoms.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.

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