Nurse Staffing Hours, Staffing Mix, and Depressive Symptoms Among Long-Stay Nursing Home Residents

Introduction: Depression is common among long-stay nursing home residents and may be influenced by facility-level care environments. This study examined whether nurse staffing hours per resident per day were associated with depressive-symptom rates, and whether these associations varied across staffing role.

Methods: This cross-sectional, facility-level study used publicly available April 2026 Centers for Medicare & Medicaid Services nursing-home data. The outcome was measured as the four-quarter average percentage of long-stay residents with depressive symptoms, identified from MDS-based quality measure code 408. Staffing and facility characteristics were obtained from provider information files. Two multivariable ordinary least squares regression models were estimated. The first examined total nurse staffing hours per resident per day. The second decomposed total staffing hours into registered nurse, licensed practical/vocational nurse, and nurse aide hours, with all three measures entered the model simultaneously. Both models controlled for the number of certified beds, occupancy rate, and nursing case-mix index.

Results: The final sample included 13,826 nursing homes. Mean depressive-symptom rate was 12.22%, and mean total staffing hours was 3.83 hours per resident per day. In the total staffing model, each additional staffing hour was associated with a 6.80 percentage-point lower depressive-symptom rate (p<0.001; adjusted R²=0.279). In the staffing mix model, all staffing roles were significantly associated with lower depressive-symptom rates: registered nurse hours (β=-10.73, p<0.001), licensed practical/vocational nurse hours (β=-15.76, p<0.001), and nurse aide hours (β=-2.74, p<0.001). The staffing mix model had an adjusted R² of 0.299.

Conclusions: Higher nurse staffing was associated with lower depressive-symptom rates among long-stay nursing home residents. Differences by staffing role suggest that staffing composition may provide additional insight beyond total staffing hours alone. Because this study was cross-sectional, the findings reflect association rather than causation and should be interpreted with caution.