Nursing staff work scheduling intensity: effects on turnover and quality in nursing homes (win-TQ)

The National Institute on Aging awarded Texas State University $414,820 on September 1, 2026, under the Aging Research program (CFDA 93.866) to conduct a mixed-methods study examining the relationship between nursing staff work scheduling intensity and quality of care and turnover in nursing homes.

The project, titled "Nursing Staff Work Scheduling Intensity: Effects on Turnover and Quality in Nursing Homes (WIN-TQ)," will use national longitudinal nursing home datasets from 2021–2025 to analyze how intensive scheduling—operationalized as work schedule intensity (WSI) and comprising seven key indicators including extended workdays, insufficient rest between shifts, and overtime—relates to nursing home outcomes. The study is guided by the Job Demands–Resources framework and will examine relationships between WSI and nursing home quality using national administrative data, addressing a knowledge gap in how scheduling decisions affect nursing home outcomes given structural differences between nursing homes and hospitals, including nursing homes' reliance on certified nursing assistants as primary caregivers and strict round-the-clock staffing requirements.

The period of performance runs from September 1, 2026, through August 31, 2028. Performance takes place at Texas State University in San Marcos, Texas.

Abstract

Nursing home (NH) quality of care is directly linked to the availability and expertise of their nursing staff- registered nurses (RNS), licensed practical nurses (lpns), and certified nursing assistants (cnas). However, faced with an acute nursing shortage and regulatory pressure to increase staffing levels, NHS may increasingly depend on existing staff through intensive work scheduling such as longer shifts, shorter rest intervals, and consecutive workdays. While hospital- based research demonstrates that scheduling intensity adversely affects both quality of care and staff outcomes, few studies have systematically examined these relationships in NH settings. Importantly, our preliminary research shows that NH scheduling intensity is substantial and unevenly distributed across nursing staff types. NHS differ significantly from hospitals in important ways, including their reliance on cnas as primary caregivers and strict round-the-clock staffing requirements. Given these structural differences, the effects of scheduling intensity may be uniquely pronounced in NHS, yet nursing home leaders and regulators have limited evidence to understand how scheduling decisions affect NH outcomes. To address these important knowledge gaps, this mixed-methods study will use a national, longitudinal NH dataset to examine how scheduling intensity among nursing staff relates to quality of care and turnover, guided by the job demands- resources (JD-r) framework. We operationalize intensive scheduling as work schedule intensity (WSI), grounded conceptually in the nursing workforce literature. The WSI comprises seven key indicators from the payroll-based journal (PBJ) dataset, including extended workdays, insufficient rest between shifts, and overtime. Aim 1 will examine the relationship between WSI and NH quality using national administrative data from 2021-2025 (n ≈ 75,000 facility-year observations), and test whether resources (staffing intensity and staffing stability) moderate this association. Quality will be measured using the 15 individual quality measures from the care compare: five-star quality rating system, with disaggregated analysis allowing detection of differential effects across specific quality domains. Aim 2 will examine the relationship between WSI and turnover in NHS using both facility-level and individual-level analyses, and test whether resources (staffing intensity and staffing stability) moderate this association. Aim 3 will examine how directors of nursing (dons) and nursing staff perceive WSI and its consequences for organizational commitment, burnout, and resident care. This aim will enrich and contextualize quantitative findings and integration across data sources will follow best practices for mixed-methods research, including the use of joint displays to synthesize quantitative and qualitative insights. This study represents the first systematic operationalization of multidimensional scheduling intensity in NHS using nationwide longitudinal data. By quantifying WSI effects on quality and turnover, findings will identify evidence-based thresholds for scheduling practices that balance workforce sustainability with high-quality care. Results will directly inform staffing regulations, facility policies, and resource allocation decisions. This work advances NIA's mission to improve the quality of life and care for older adults in the united states.