We report how we determined sample size, all data exclusions, all manipulations, and all measures in the studies **Power analysis** Study 1 - We calculated that a sample size of 300 respondents enables performing factor analyses on the data, according to the rule of thumb of 3-20:1 participant:variable ratio. In addition, it enabled us to detect at least one incidence of rare events with 1% frequency, with a power of 95% and alpha = .05. A sample size of N = 475, however, enables the detection of at least two incidences of events with 1% frequency with a power of 95% and alpha = .05 Study 2 - We calculated that a sample size of 300 respondents enables performing factor analyses on the data, according to the rule of thumb of 3-20:1 participant:variable ratio. In addition, it enabled us to detect at least one incidence of rare events with 1% frequency, with a power of 95% and alpha = .05. A sample size of N = 475, however, enables the detection of at least two incidences of events with 1% frequency with a power of 95% and alpha = .05 Study 3 - We calculated that a sample of at least N = 191 would enable the detection of correlations >= .20, with desired power of .80, if the alpha level is set at .05. This number of entities at level two is far larger than the number found to lead to biased estimates of the second-level standard errors in the hierarchical linear modeling (meaning a sample of 50 or less) (Mass & Hox, 2005) Study 4- A sample of n=1043 enables detecting the correlation of 0.10 with the power of 0.90 (with two-sided alpha level set at 0.05). Moreover, this sample size is adequate for assessing structural equation models (including confirmatory factor analysis) for which a sample size of n>200–500 is typically recommended (Brown, 2006; Kline, 2005). **Data exclusions** As responses to the questionnaires were not mandatory, there were some missing data in all four studies. To ensure consistency in reporting results, we opted to use the listwise deletion method. Additionally, to be included in the final sample, participants had to pass all embedded attention check items (e.g., To show you are paying attention, select the response X). Each study included three attention check items, except for Study 4, which had four of them. In study 1 74 participants were excluded (12.8% of the initial 580 participants), in Study 2 77 particpants (13.2% of the initial 583), 47 in Study 3 (17.6% of 267), and 123 in Study 4 (11.8% of 1044).