M Topf1, S Thompson. 1. School of Nursing, University of Colorado Health Sciences Center, Denver 80262, USA.
Abstract
OBJECTIVE: The purpose of this study was to test the hypothesis that hospital noise-induced subjective stress would interact with other subjective environmental and personal stress in a relationship with poorer patient sleep. METHODS: A secondary data analysis was done using correlations and hierarchical multiple regression. Ninety-seven cardiac patients participated after transfer from critical care to a general unit. The independent variables were assessed with Topf's 24-item Disturbance Due to Hospital Noise Scale and 5-point items for other environmental stress (ie, bed, lights) and personal stress (ie, pain, anxiety). Sleep was evaluated with the Verran and Snyder-Halpern Sleep Scale. RESULTS: Hierarchical multiple regression led to a multiple R of 0.435 (P <.01). An interaction term, subjective noise stress x subjective bed stress x subjective pain x subjective anxiety accounted for a significant amount of sleep variance (12%, F = 13.63, P =.000). Subjective bed stress x subjective pain accounted for an additional 5% (F = 6.4, P =.013). CONCLUSIONS: Studies using research designs that assess relationships between multiple patient stress variable interactions and sleep or other stress-related outcomes may produce more accurate results than studies on the independent effects of different types of stress.
OBJECTIVE: The purpose of this study was to test the hypothesis that hospital noise-induced subjective stress would interact with other subjective environmental and personal stress in a relationship with poorer patient sleep. METHODS: A secondary data analysis was done using correlations and hierarchical multiple regression. Ninety-seven cardiac patients participated after transfer from critical care to a general unit. The independent variables were assessed with Topf's 24-item Disturbance Due to Hospital Noise Scale and 5-point items for other environmental stress (ie, bed, lights) and personal stress (ie, pain, anxiety). Sleep was evaluated with the Verran and Snyder-Halpern Sleep Scale. RESULTS: Hierarchical multiple regression led to a multiple R of 0.435 (P <.01). An interaction term, subjective noise stress x subjective bed stress x subjective pain x subjective anxiety accounted for a significant amount of sleep variance (12%, F = 13.63, P =.000). Subjective bed stress x subjective pain accounted for an additional 5% (F = 6.4, P =.013). CONCLUSIONS: Studies using research designs that assess relationships between multiple patient stress variable interactions and sleep or other stress-related outcomes may produce more accurate results than studies on the independent effects of different types of stress.
Authors: Gari D Clifford; Ikaro Silva; Benjamin Moody; Qiao Li; Danesh Kella; Abdullah Chahin; Tristan Kooistra; Diane Perry; Roger G Mark Journal: Physiol Meas Date: 2016-07-25 Impact factor: 2.833