We conducted two experiments in 2x2 designs, with two environment conditions: work-associated environment vs. a non-work-work-associated environment (varied between
subjects) and two task conditions: work-related vs. non-work-related decision making (within subjects). We did not manipulate task condition experimentally but assessed decision making in work-related vs. non-work-related decision contexts1. Design, measures, and assessment of the dependent variable and moderators were identical for both studies. Tasks and instructions were written in German. All of the data were recorded anonymously and participants signed informed consent statements. After completing the study, participants were fully debriefed and generated a personal code in order to be able to withdraw any data. Both experiments were conducted in compliance with the ethical standards of the American Psychological Association.
1 In addition to decision making tasks, two concentration tasks were included (Psychomeda Konzentrationstest, KONT-P, Satow, 2011; Zahlen-Symbol-Test, ZST, Tewes & Wechsler, 1991), as Experiments 1 and 2 were part of a larger research project. We do not report results at this point because they are extraneous to this study.
We measured decision making by means of 13 items which involved hypothetical situation dilemmas (SD). Items were construed following the 12 item choice dilemma questionnaire (CDQ) by Kogan and Wallach (1964). We excluded three items because they were culturally inadequate or no longer currently valid, but we added four items derived from Jackson et al. (1972) which measure monetary risk, physical risk, ethical risk, and social risk. We used items from the inventory of both questionnaires in order to cover a broad range of risk situations and life domains (i.e. investments, health, career, family).
In a pretest with n = 24 participants (20 female, age 22 – 56, M = 27.79, SD = 7.77), all 13 items were rated as to whether they describe a work-related vs. a non-work-related decision making task on a scale from 1 related) to 6 (non-work-related). A mean score was calculated for each item. With a cutoff of 3.5, an item with a mean of ≤ 3.5 was scored as ‘work-related decision making’ and an item with a mean of
> 3.5 was scored as ‘non-work-related decision making’. Ratings resulted in a quite evenly distribution of items. Seven items (N°1, N°3, N°7, N°10, N°11, N°12, N°13) were rated as being representative of work-related decision making, for example,
‘Imagine you are developing an innovative, promising business idea but you would have to quit your permanent position in order to realize it. However, it is uncertain if the idea will turn out to be profitable. Would you dare to quit your permanent position?’.
Six items (N°2, N°4, N°5, N°6, N°8, N°9) were rated as being representative of non-work-related decision making, for example, ‘Imagine you are at the airport waiting for the flight that takes you to your well-deserved vacation destiny but you are experiencing strong stomach pain. You could either ignore the pain hoping it will disappear by itself or miss the flight and go to see a doctor at the hospital. Would you dare to take the flight?’. Consequently, we calculated two different decision making scores by averaging the relevant items, resulting in a work-related decision making score and a non-work-related decision making score. The work-non-work-related decision making score (M = 3.11, SD = .96) and the non-work-related decision making score (M = 5.39, SD = .42) differed significantly, t(23) = -10.34, p <.001.
In the main study, participants were asked to decide for each of 13 hypothetical scenarios whether to engage in risky or non-risky behaviour. For each situational
most risky option was weighted with a score of 6 (also scores of 2,3,4,5, were assigned respectively). As described above, items were averaged as a work-related decision making score and a non-work-related decision making score.
2.3 Mood as a Moderator
Mood was assessed by means of the Aktuelle Stimmungs Skala (ASTS - English:
Current Mood Scale, Dalbert, 1992). The ASTS consists of 16 adjectives describing mood according to four categories (sadness, hopelessness, fatigue, and positive mood).
Participants rated how those adjectives fit their current mood on a 7-point Likert-scale.
Ratings of relevant adjectives were summed across 4 mood scales; higher values indicated a stronger expression of the mood category. The ASTS offers sufficient internal reliability with a Cronbach’s Alpha between α = .83 and α = .94 (Dalbert, 1992).Sadness, hopelessness, and fatigue were positively correlated (r = .46 – 74 in the laboratory; r = .34 – 78 in the field; Pearson correlation coefficient). Positive mood was negatively correlated with sadness, hopelessness, and fatigue (r = -.47 - -.36 in the laboratory; r = -.61 - -.41).
2.4 Activation of concepts
We included a free association task as a manipulation check at the end of the studies in order to check whether work-associated vs. non-work-associated environments were able to activate associated (work vs. non-work) concepts. Participants were asked to write down as many words or phrases that sprang to mind within one minute. Three independent blind raters rated the words in three categories and gave one of three scores: a 1 if the word or phrase was related to work, a -1 if the word or phrase was related to non-work or leisure, 0 if the word or phrase was neither related to leisure or non-work or if it was related to both equally. Inter-rater reliability was acceptable with a mean average measure ICC = .88 in the laboratory and ICC = .89 in the field
experiment (two-way random intraclass correlation, absolute agreement, cf. Shrout &
Fleiss, 1979).
2.5 Environment variables and demographic data
experiments, we asked participants to rate their agreement with following statements on a 5-point Likert-scale: ‘I associate the current surroundings with work’ and ‘I associate the current surroundings with leisure’. Higher values indicate higher association.
Demographic data of interest were gender, age, level of education, current state of employment (employed: yes or no), and professional status (two questions “I’m in a leading position” and “I have decision-making power”; rating from 1 to 5). In addition, we assessed individual experience with ubiquitous working (whether participants could decide where they work, when they work, and how often they work remotely. We also asked if they perceived that their work outcome benefitted from mobile working opportunities).
2.6 Analyses
We investigated differences between two groups by means of t-tests for independent samples. Univariate variance analyses were used to assess interaction effects.
Environment was treated as a two-stage factor (work-associated vs. a
non-work-associated). We did not manipulate task condition experimentally but assessed decision making in work-related vs. non-work-related decision contexts. Therefore we did not include it as a factor in the analyses but calculated separate models. We followed recommendations by Hayes (2012) in conducting moderation analyses with the help of PROCESS Modelling.
3. Study 1