Table 2.
Effect | n | Beta | Standard error | p-value | % Cortisol drop/hourA | |
---|---|---|---|---|---|---|
Intercept | 110 | –0.52 | 0.197 | 0.009 | ||
Time of day (diurnal effect) | 110 | –0.125 | 0.0119 | <0.0001 | 11.7% | |
Duration interval: length of NE (min) per quartileB | NE frequency for each minute in the interval | n/% of total sample | % Cortisol drop beyond diurnal effectA | |||
Q1: 7–14 min | 1,2,1,2,5,7,7,3 | 28/25.5% | –0.0864 | 0.0561 | 0.13 | 8.3% |
Q2: 15–20 min | 5,2,8,1,6,5 | 27/24.5% | –0.0375 | 0.0572 | 0.51 | 3.7% |
Q3: 21–30 min | 4,1,3,2,6,4,3,1,1,5 | 30/27.3% | –0.2048 | 0.0545 | 0.0003 | 18.5% |
Q4:>30 min | 1,1,2,1,1,1,1,2,1,2,1, 1,1,1,1,1,1,2,1,1,1 | 25/22.7% | –0.1214 | 0.0600 | 0.045 | 11.4% |
ACalculated as ebeta estimate – 1. BReported in minutes, calculated as proportion of an hour. Mixed models of log cortisol levels as predicted by diurnal effects (time of day) using a linear function and by duration of a nature experience using a step function. The step function estimates are calculated for each quartile interval (Q) separately and are not cumulative. This model explains 26.7% of level-1 residual [repeated measure] variance, and 45.9% of level-2 [subject-level] variance, and 53.4% of level-3 [timepoint-level] variance.