Table 4.

Nightly sleep predicting next-day experiences in 2 employee samples

Sleep predictors (each cell is a separate model)	Positive affect Unstd. B (95% CI)	Negative affect Unstd. B (95% CI)	Positive work event OR (95% CI)	Positive non-work event OR (95% CI)	Work stressor OR (95% CI)	Non-work stressor OR (95% CI)
Industry 1 replicate (131 IT employees)
	Ndays = 862	Ndays = 862	Ndays = 505	Ndays = 869	Ndays = 505	Ndays = 869
1. Sleep quality	0.094 (0.035, 0.154)**a	−0.051 (−0.080, −0.021)***a	1.000 (0.652, 1.533)	1.104 (0.810, 1.503)	0.616 (0.422, 0.899)*a	0.737 (0.556, 0.977)*b
2. Sleep duration	0.041 (0.009, 0.074)*a	−0.004 (−0.020, 0.012)	1.206 (0.920, 1.580)	1.042 (0.879, 1.234)	0.766 (0.608, 0.964)*b	1.031 (0.886, 1.199)
Industry 2 replicate (181 extended care employees)
	Ndays = 1060	N days = 1060	Ndays = 410	N days = 1060	N days = 410	N days = 1060
1. Sleep quality	0.124 (0.075, 0.173)***a	−0.022 (−0.055, 0.010)	2.930 (1.705, 5.035)***a	1.079 (0.826, 1.408)	0.668 (0.442, 1.011)†	0.721 (0.568, 0.915)**a
2. Sleep duration	0.016 (−0.008, 0.039)	−0.005 (−0.019, 0.010)	1.051 (0.839, 1.316)	1.029 (0.911, 1.163)	0.883 (0.722, 1.080)	0.910 (0.813, 1.020)

Note.Sleep quality and sleep duration were tested in separate models as predictors of each daily experience outcome. Models also controlled for age, gender, race (White vs. non-White), day in study (Day 0, Day 1, …, Day 7), work day (yes/no), insomnia in the past month, and outcome variable (e.g., affect, positive event, stressor) measured on the prior day. The positive affect analyses included additional covariates for prior- and same-day negative affect, and the negative affect analyses included covariates for prior- and same-day positive affect.

^***p < 0.001,

^**p < 0.01,

^*p < 0.05,

^†p < 0.10

^aEffect remained significant at p < 0.05 after correcting for multiple comparisons

^bEffect was marginally significant at p < 0.08 after correcting for multiple comparisons