Skip to main content
Have a personal or library account? Click to login
Recovery Across Different Temporal Settings: How Lunchtime Activities Influence Evening Activities Cover

Recovery Across Different Temporal Settings: How Lunchtime Activities Influence Evening Activities

Open Access
|Mar 2022

Figures & Tables

Figure 1

Study design. Daily data were collected twice a week, on Tuesdays and Thursdays. The intervention exercise was completed every day from Monday to Friday during the two intervention weeks. SMS = SMS questionnaire sent to participants’ cell phones; PP = pencil-and-paper questionnaire.

Table 1

Means, standard deviations, and zero-order correlations between study variables.

MSD1.2.3.4.5.6.7.8.9.
1. Work hours7.640.760.01–0.070.03–0.13**–0.07*–0.05–0.22**–0.21**
2. Park walkinga0.240.23–0.10–0.01–0.060.050.08*0.11**–0.040.04
3. Relaxation exerciseb0.210.240.29**–0.75**–0.16**0.030.030.050.030.07
4. Fatigue (1–7)3.811.15–0.010.04–0.02–0.28**–0.040.004–0.040.03
5. Positive affect (1–7)4.850.930.120.020.15–0.36**0.02–0.050.050.14**
6. Evening physical exercise0.570.37–0.06–0.04–0.04–0.180.080.42**–0.16**0.20**
7. Evening physical activity in nature0.310.33–0.200.01–0.07–0.27**0.140.32**–0.050.11**
8. Evening social activities1.971.07–0.11–0.05–0.05–0.25*0.22*0.090.110.18**
9. Evening relaxation (1–5)3.940.61–0.29**0.09–0.17–0.28**0.31**0.170.180.20

[i] Notes: Correlations below the diagonal are between-person level correlations (person means aggregated over the repeated daily observations; N = 97), correlations above the diagonal are within-person (day level) correlations (N = 970). a 0 = no, 1 = yes, a park walk during lunch break; b 0 = no, 1 = yes, a relaxation exercise during lunch break.

* p < 0.05, ** p < 0.01.

Table 2

Multi-level regression analyses.

VARIABLEEVENING PHYSICAL EXERCISEEVENING PHYSICAL ACTIVITY IN NATURAL SURROUNDINGSSOCIAL ACTIVITIES
MODEL 1MODEL 2MODEL 1MODEL 2MODEL 1MODEL 2
ESTSETESTSETESTSETESTSETESTSETESTSET
Intercept0.670.0710.340.690.0710.100.280.064.930.280.064.872.000.1711.642.060.1811.63
Within-person results
    Time (diary day)–0.010.01–1.90–0.020.01–2.22*0.0040.010.750.0030.010.530.010.010.810.020.021.41
    Work hours–0.040.02–1.81–0.040.03–1.48–0.020.02–1.31–0.030.02–1.46–0.270.04–6.02***–0.290.05–5.58***
    Park walkinga0.140.052.69**0.160.062.70**0.160.053.49***0.200.053.80***–0.100.11–0.84–0.120.12–0.97
    Relaxation exerciseb0.070.061.170.060.060.880.070.051.440.100.061.820.160.121.280.080.130.59
    Afternoon fatigue–0.010.02–0.70–0.00020.02–0.02–0.010.04–0.37
    Afternoon PAc–0.0020.03–0.09–0.030.02–1.320.020.050.38
Between-person results
    Work hours–0.020.06–0.44–0.050.06–0.84–0.080.05–1.72–0.100.05–2.10*–0.120.16–0.80–0.130.16–0.81
    Park walkinga–0.260.27–0.94–0.260.28–0.96–0.080.23–0.35–0.070.22–0.30–0.680.75–0.90–1.180.77–1.54
    Relaxation exerciseb–0.230.27–0.85–0.260.28–0.92–0.060.23–0.27–0.070.23–0.31–0.590.74–0.80–1.260.77–1.62
    Afternoon fatigue–0.080.04–1.97–0.090.03–2.86**–0.200.11–1.82
    Afternoon PAc0.010.050.290.030.040.620.260.141.86
Model fit statistics
    Level-1 intercept variance (SE)0.31(0.56)0.31(0.56)0.20(0.45)0.21(0.46)1.24(1.11)1.18(1.09)
    BIC1528.411367.121163.351078.332682.622324.95
    AIC1477.331299.951117.141015.952635.992261.96
    –2*log(lh)1455.331269.951097.14987.952615.992233.96

[i] Notes: All variables were measured at the day level. a 0 = no, 1 = yes, a park walk during lunch break; b 0 = no, 1 = yes, a relaxation exercise during lunch break. cPA = Positive affect. BIC = Bayesian Information Criterion; AIC = Akaike’s Information Criterion. When comparing nested models, the smallest indices indicate the best model fit.

* p < 0.05, ** p < 0.01, *** p < 0.001.

Table 3

Multi-level regression analyses predicting evening relaxation.

MODEL 1MODEL 2
ESTSETESTSET
Intercept3.880.1037.333.990.1039.50
Within-person results
    Time (diary day)0.010.011.130.010.010.81
    Work hours within–0.170.03–5.44***–0.090.04–2.51*
    Park walking withina0.150.081.880.140.091.59
    Relaxation exercise withinb0.140.091.640.090.100.95
    Afternoon fatigue within0.040.031.62
    Afternoon positive affect within0.110.042.99**
Between-person results
    Work hours between–0.200.09–2.31*–0.180.08–2.10*
    Park walking betweena–0.0040.42–0.01–0.460.39–1.18
    Relaxation exercise betweenb–0.280.42–0.65–0.840.40–2.12*
    Afternoon fatigue between–0.060.06–1.07
    Afternoon positive affect between0.240.073.34**
Model fit statistics
    Level-1 intercept variance (SE)0.75(0.86)0.76(0.87)
    BIC2143.741857.53
    AIC2092.391789.92
    –2*log(lh)2070.391759.92

[i] Notes: All variables were measured at the day level. a 0 = no, 1 = yes, a park walk during lunch break; b 0 = no, 1 = yes, a relaxation exercise during lunch break. BIC = Bayesian Information Criterion; AIC = Akaike’s Information Criterion. When comparing nested models, the smallest indices indicate the best model fit.

* p < 0.05, ** p < 0.01, *** p < 0.001.

DOI: https://doi.org/10.16993/sjwop.129 | Journal eISSN: 2002-2867
Language: English
Page range: 5 - 5
Submitted on: Jul 20, 2020
Accepted on: Feb 14, 2022
Published on: Mar 23, 2022
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services

© 2022 Marjaana Sianoja, Christine Syrek, Jessica de Bloom, Kalevi Korpela, Ulla Kinnunen, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.