Wednesday, December 4, 2024
12/4/2024
Abstract Most caregiving responsibilities for persons with Alzheimer’s disease and related dementias (ADRD) fall on their family members. While we know types of tasks caregivers are responsible for, and have described styles of caregiving, it remains unclear how processes used by caregivers impact outcomes for their care recipient. Missed care is a term from health services which describes care that is left undone because of a decision made in light of other factors. Our preliminary data suggest that missed care is a frequent and daily experience in ADRD family caregiving. Therefore, using a concurrent mixed-methods triangulation design, we aim to more clearly understand processes that contribute to missed care within ADRD family caregiving. The well-established missed care model contextualizes the decision to skip care and points to situational antecedents (e.g., time demands, resource scarcity) and internal processes (i.e., values) that impact nurses' decision-making on how to prioritize care, including decisions to skip needed care. Our underlying hypothesis is that similar decision- making processes can be identified within ADRD family caregiving. In Aim 1, we will enroll a sample of ADRD family caregivers recruited from the local health system (N=225) to complete daily diary surveys characterizing their day. Data will be analyzed using multi-level structural equation modeling to evaluate our application of the Missed Nursing Care Model to family caregiving. In Aim 2, we will use a grounded theory design with in-depth interview data collected from a subset of participants (N=35) to produce a theoretical description of decision- making related to care provision and prioritization. In Aim 3, we will triangulate the data to create a data-driven model to explain multi-factorial daily decision-making that leads to missed care in ADRD family caregiving. Distinguishing the process of decision-making (Aim 2) from its underlying contextual factors (Aim 1) will identify the underlying processes contributing to missed care. This body of data will inform a novel data-driven theoretical model describing mechanisms leading to missed care events in ADRD family caregiving. This model will serve as an intervention framework, highlighting actionable intervention targets. Our results have the potential to significantly impact the family caregiving field by advancing its conceptual paradigm – moving from merely defining the tasks for which family caregivers are responsible, to illuminating the decision-making process that determines how they provide care in real-life contexts. This will permit a better alignment of future policies and interventions with caregiver needs. An innovation of this work is its combination of micro-longitudinal data with grounded theory analysis, which we surmise will lead to a more ecologically valid reflection of key processes in day-to-day caregiving.
HHS’ Tracking Accountability in Government Grants System (TAGGS) website provides access to detailed descriptions of grants, loans, aggregated direct payments and other types of financial assistance awarded by the HHS Operating Divisions (OPDIVs) and the Office of the Secretary Staff Divisions (STAFFDIVs).
