Experiment 2 was designed as a quasi-experimental field study using an online survey.
We did not manipulate the environment but instead asked participants to do the study tasks either in a typical work-associated or a typical non-work-associated environment.
We conducted a row of manipulation checks and gathered the effects of several additional control variables in order to be able to control for as many confounding variables as possible.
4.2 Participants
In sum, 126 participants volunteered to fill in the online survey. Four participants were excluded from the analyses because they failed the manipulation checks (subjectively perceived environment did not fit the manipulated one). The remaining 122 participants had a mean age of 26.20 (SD = 6.78, range from 18 to 53), the majority (n = 79) were female. Participants were randomly assigned either to the work environment (n = 60) or to the non-work environment (n = 62) condition. Around two-thirds of participants had at least a part time job (n = 86), the others were students. The chance to win one of two 25€ vouchers was offered as an incentive.
4.3 Procedure and manipulation of the environment
First contact with participants happened through a short invitation to take part in the study. Those who volunteered were asked to register with their e-Mail address and were afterwards personally contacted with a standardized e-Mail. In the e-Mail participants received the link that led to the online survey and either received (randomly assigned) the instructions to open the survey link in a typical work-associated environment (e.g., work or home office) or in an environment that is typically not associated with work (e.g., in their garden, living room, ...). As soon as the participants were in the assigned
work-associated environment (depending on their instructions), and a manipulation check as described in the general method followed (rate associations of the environment with either work or leisure). The actual assessment started with five open questions that on the one hand were used as a manipulation check and on the other hand had the goal of assisting participants to fully immerse in their current environment, engaging consciously in the perception of their surroundings (1. Where are you? 2. What do you see 3. How is the atmosphere? 4. What did you do in the last half hour? 5. Do you have any other comments regarding your surroundings?). Next, the assessment of work-related and non-work-work-related decision making3 followed. The study ended with the assessment of control variables and demographic data (as described in the general method). Participants had to indicate whether they had filled out the survey with a PC/laptop, tablet, or smartphone. After finishing the survey, participants had the chance to submit their e-mail address in order to take part in the voucher lottery.
4.4 Results and discussion
Manipulation of environments
Regarding the closed question asking for associations of the environment with work vs.
non-work, the manipulation worked out as expected. Participants in the work environment generally associated the environment more with work (M = 5.07, SD = 1.69) compared to participants in the non-work environment (M = 2.40, SD = 1.02), t(120) = -10.61, p < .001. And the other way round, participants in the non-work environment associated the environment more with leisure (M = 4.95, SD = 1.68) compared to participants in the work environment (M = 1.93, SD = 1.10), t(120) = 11.67, p < .001. This also held true for the additional measurement at the end of the experiment (both p < .001 in the expected direction).
The free association task also indicated successful manipulation. Three participants are missing in the analyses as they did not insert a free association.
Participants in the work-associated environment mentioned more work-related words (M = -.07, SD = .18) than participants in the non-work-associated environment (M = .19, SD =.21), t(117) = -7.01, p < .001.
or non-work-related decision making, without considering mood. Hypothesis 1a was not confirmed, as work-related decision making did not differ between participants in the work-associated environment (M = 3.18, SD = .81) and participants in a non-work-associated environment (M = 3.12, SD = .62), t(120) = .45, p = .654. In addition, Hypothesis 1b was not confirmed, as non-work-related decision making only differed marginally between participants in the work-associated environment (M = 3.09, SD = .72) and participants in the non-work-associated environment (M = 3.33, SD = .69), t(120) = -1.87, p = .064.
Conditional effects of the environment
We did not find any significant conditional effect of environment on work-related decision making when we included mood into the model (all p > .441). However, the following three moods did influence the environmental effect on non-work-related decision making: a) high (one standard deviation above the mean) sad mood, b) high desperate mood, and c) low positive mood. The sad, desperate, and less positively tuned participants made more risky decisions in a non-work-associated environment than in a work-associated environment (see Figure 3). Note: the effect of the environment has to be treated with caution, as the confidence interval of the environment includes zero (see Table 2).
Table 2. Conditional effect of environment on non-work-related decision making.
a. Sad mood
Model summary R R2 MSE F Df1 Df2 p
.30 .09 .47 3.94 3 118 .010
b. Desperate mood
Model summary R R2 MSE F Df1 Df2 p
.29 .09 .48 3.74 3 118 .013
b se t p CIl CIh
Constant 3.55 .20 17.34 .000 3.15 3.96
Environment -.46 .28 -1.63 .105 -1.02 .09
Sad mood -.07 .03 -2.49 .014 -.13 -.01
Interaction .11 .04 2.74 .007 .03 .19
Model summary R R2 MSE F Df1 Df2 p .26 .07 .48 2.97 3 118 .035
Note. Sample size: n = 122; R = coefficient of correlation, R2 = coefficient of determination, MSE = mean squared error, F = F-Test statistics, Df = degrees of freedom, p = significance value, b = unstandardized beta coefficient, se = standard error, t = t-test statistic, CIl = lower confidence interval, CIh = higher confidence interval
Figure 3. Conditional effects of the environment on non-work-related decision making (from 1, no risk taking, to 6, high risk taking); separated for work-associated and non-work-associated environment. Lines show low (black), medium (grey), and high (dashed) sad moods (a), desperate moods (b), and positive moods (c). Lines marked with an asterisk * show significant effects.
a. b
c.
Control variables
We did not find any differences between the work and the non-work condition for gender, level of education, current state of employment, professional status, or experience with ubiquitous working (all p > .060) but for age between the work (M = 27.65, SD = 6.87) and non-work conditions (M = 24.81, SD = 6.45), t(120) = -2.36, p = .020). However as mean age was quite low in both groups, this difference is not of further interest.