Daily Emotion Regulation Strategies and Depression in Dementia Caregivers: A Multimodal Approach
Spousal caregiving in the context of Alzheimer’s disease and related dementias (ADRD) is consistently associated with elevated risk for depression, yet depressive outcomes vary substantially across caregivers. Traditional models often conceptualize emotion regulation as a stable individual difference—treating certain strategies (e.g., reappraisal) as adaptive and others (e.g., suppression) as maladaptive. However, caregiving unfolds in dynamic, emotionally charged contexts where individuals frequently deploy multiple strategies across short time intervals. Understanding depression risk in this population may therefore require a more ecologically valid model of emotion regulation.
Dr. Eva Dicker (Seattle University) leads an MRI-funded project, Daily Emotion Regulation Strategies and Depression in Dementia Caregivers: A Multimodal Approach, that advances this line of inquiry by examining emotion polyregulation—the real-world sequencing and combination of strategies used to manage distress. Rather than isolating single regulatory techniques, the study investigates how caregivers navigate emotionally complex moments as they unfold, and which patterns of strategy use predict depressive symptoms over time.
Conceptually, the project situates caregiver depression within a process-oriented framework. Emotion regulation is treated not as a static trait but as a dynamic system shaped by cognitive capacity, contextual demands, and neurobiological vulnerability. In chronic stress environments such as dementia caregiving, the effectiveness of regulation strategies may depend less on the strategy itself and more on how flexibly it is deployed across situations.
Methodologically, the study integrates laboratory-based assessment with real-time, naturalistic data collection. During an in-lab baseline session, caregivers complete standardized questionnaires assessing depressive symptoms and caregiving burden, as well as cognitive assessments relevant to regulatory capacity (e.g., executive functioning). Resting-state electroencephalography (EEG) is also collected to examine neural markers associated with depression vulnerability and affective processing. This multimodal baseline establishes both psychological and neurophysiological profiles.
The core of the study involves two weeks of ecological momentary assessment (EMA) delivered via smartphone. Participants complete brief surveys multiple times per day capturing caregiving-related negative affect, specific emotion regulation strategies used (e.g., distraction, cognitive reappraisal, avoidance, problem-solving), perceived effectiveness, and concurrent depressive symptoms. This design allows fine-grained modeling of within-person variability in emotional experience and regulatory behavior, reducing reliance on retrospective reporting and increasing ecological validity.
Analytically, the project examines how distinct polyregulation patterns—such as flexible strategy switching versus repetitive reliance on a narrow set of strategies—predict daily depressive symptom fluctuations. The study also tests whether individual differences (e.g., cognitive ability, gender, race) moderate these associations, identifying subgroups for whom certain regulatory patterns may be particularly protective or risky. By linking neural indicators with real-time coping behavior, the research aims to clarify whether baseline neurobiological vulnerability shapes the effectiveness of everyday emotion regulation efforts.
The translational implications are substantial. Findings can inform the development of caregiver interventions that move beyond prescriptive “use this strategy” models toward training in regulatory flexibility—helping caregivers recognize when and how to shift strategies in response to changing emotional demands. Tailored supports could also be designed to account for cognitive capacity and contextual constraints, increasing feasibility and real-world impact.
By integrating neural, cognitive, and moment-to-moment experiential data, this study advances a multimodal model of caregiver depression risk. In doing so, it reframes emotion regulation in dementia caregiving as a dynamic, relational process embedded within the caregiving dyad—one that, if better understood, can inform more responsive and sustainable pathways to caregiver mental health.