Supplemental Materials
Honesty-Humility Under Threat: Self-Uncertainty Destroys Trust Among the Nice Guys
by S. Pfattheicher & R. Böhm, 2017, Journal of Personality and Social Psychology
http://dx.doi.org/10.1037/pspp0000144
2
Content
Instructions I1: Instructions of the game used in Studies 1-2
Instructions I2: Instructions of the game used in Study 3
Instructions I3: Instructions of the game used in Study 4a and 4b
Instructions I4: Screenshot of the applied self-uncertainty-manipulation
Table T1: Cronbach’s α, means, standard deviations of the HEXACO scales (Studies 1-5)
Table T2: Predicting trust by the HEXACO scales, the condition and their interactions using
multivariate logistic regression analyses (Study 2)
Table T3: Analyses of the full model in Study 2 including trust, Honesty-Humility, the
condition, and the mediator (social expectations)
Table T4: Predicting trust by the HEXACO scales, the condition and their interactions using
multivariate logistic regression analyses (Study 3)
Table T5: Analyses of the full model in Study 3 including trust, Honesty-Humility, the
condition, and the mediator (social expectations)
Table T6: Predicting trust by the HEXACO scales, the condition and their interactions (Study
4a)
Table T7: Predicting social expectations by the HEXACO scales, the condition and their
interactions (Study 4a)
Table T8: Analyses of the full model in Study 4a including trust, Honesty-Humility, the
condition, and the mediator (social expectations)
Table T9: Predicting trust by the HEXACO scales, the condition and their interactions (Study
5b)
Table T10: Information on dropouts
Figure F1: Trust in the police as a function of Honesty-Humility and the experimental
condition (Study 5b).
3
I1: Instructions of the Trust Game used in Studies 1&2
In the following, we want you to take part in a decision making game including money. You
can rule out any financial loss in this study. Please note that 1 out of 15 participants in the
decision making game will be paid off, that is, 1 out of 15 participants will receive a bonus
depending on the decisions made in the game. The random selection of participants who will
receive a bonus is made at the end of the study. Please read the following instructions
carefully.
Allocation of players:
For this game you have been randomly paired with another real worker. One of you will be
Player 1 and the other will be Player 2. This decision is made by chance. The other player
will never know your worker ID and you will not know the other player's worker ID. In addition
to your basic payment of the HIT, each player could receive a bonus depending on the
decisions made in the game.
4
Rewards:
In the game, your decision may affect the final payoff of the other participant, just as the
decision of the other participant may affect your final. The graph below shows the conditions
of the game. There are two “roles” in the game: “Player 1” and “Player 2”. Player 1 chooses
between Option L and Option R.
If Player 1 chooses Option R the game ends, and Player 1’s final payoff will be $6. Player
2’s final payoff will be $2.
If Player 1 chooses Option L, then the payoffs are determined by Player 2’s choice:


Specifically, if Player 2 selects Option A, then Player 1 receives $2 and
Player 2 receives $18.
Otherwise, if Player 2 selects Option B then Player 1 gets $10 and
Player 2 gets $10.
When Player 1 makes the choice s/he will not know the choice of Player 2.
5
Back to the decision making game. Remember: For this game you have been randomly
paired with another real worker. One of you will be Player 1 and the other will be Player 2.
This decision is made by chance:
IN THIS GAME YOU ARE PLAYER 1
Thus, you can choose between Option L and Option R:
Please make your decision:
I choose Option L
I choose Option R
6
I2: Instructions of the Trust Game used in Study 3
In the following, we want you to take part in a decision making game including money. You
can rule out any financial loss in this study. Please note that 1 out of 15 participants in the
decision making game will be paid off, that is, 1 out of 15 participants will receive a bonus
depending on the decisions made in the game. The random selection of participants who will
receive a bonus is made at the end of the study. Please read the following instructions
carefully.
Allocation of players:
For this game you have been randomly paired with another real worker. One of you will be
Player 1 and the other will be Player 2. This decision is made by chance. The other player
will never know your worker ID and you will not know the other player's worker ID. In addition
to your basic payment of the HIT, each player could receive a bonus depending on the
decisions made in the game. In this game, each player receives a basic endowment of $2.
7
Rewards:
In the game, your decision may affect the final payoff of the other participant, just as the
decision of the other participant may affect your final. The graph below shows the conditions
of the game. There are two “roles” in the game: “Player 1” and “Player 2”. Player 1 chooses
between Option L and Option R.
If Player 1 chooses Option R the game ends, and Player 1’s final payoff will be $6. Player 2’s
final payoff will be $0 (so Player 2’s payoff decreases from $2 [basic endowment] to $0).
If Player 1 chooses Option L, then the payoffs are determined by Player 2’s choice:


Specifically, if Player 2 selects Option A, then Player 1 receives $2 and
Player 2 receives $18.
Otherwise, if Player 2 selects Option B then Player 1 gets $10 and
Player 2 gets $10.
When Player 1 makes the choice s/he will not know the choice of Player 2.
8
Back to the decision making game. Remember: For this game you have been randomly
paired with another real worker. One of you will be Player 1 and the other will be Player 2.
This decision is made by chance:
IN THIS GAME YOU ARE PLAYER 1
Thus, you can choose between Option L and Option R:
Please make your decision:
I choose Option L
I choose Option R
9
I3: Instructions of the Trust Game used in Study 4a and 4b
Im Folgenden werden Sie ein ökonomisches Spiel spielen, bei dem Sie Geld verdienen
können. Jeder 15. Proband bekommt den Verdienst in diesem Spiel am Ende der Studie in
bar und anonym ausgezahlt.
Spielregeln:
Alle Teilnehmenden dieser Studie sind in Zweier-Gruppen aufgeteilt. Das heißt, Sie werden
einem anderen realen Teilnehmenden dieser Studie zugewiesen. In jeder Zweier-Gruppe gibt
es zwei Rollen: Teilnehmer 1 und Teilnehmer 2. Sie werden via Computer entweder der Rolle
von Teilnehmer A oder der Rolle von Teilnehmer B zugewiesen.
Teilnehmer 1 erhält 5 Euro. Teilnehmer 2 erhält keinen Geldbetrag (d.h. 0 Euro). Teilnehmer
A kann nun zwischen 0 und 5 Euro an Teilnehmer 2 überweisen.


Der Betrag, den Teilnehmer 1 an Teilnehmer 2 überweist, wird verdreifacht.
Der Betrag, den Teilnehmer 1 nicht an Teilnehmer 2 überweist behält Teilnehmer A für
sich.
Danach hat Teilnehmer 2 die Möglichkeit, von dem verdreifachten Betrag beliebig viel Geld
an Teilnehmer A zurück zu überweisen.
Nach der Entscheidung von Teilnehmer 2 können keine weiteren Entscheidungen von
Teilnehmer 1 und Teilnehmer 2 getroffen werden.
Ein Beispiel:



Teilnehmer 1 hat 5 Euro. Von diesen 5 Euro behält er 2 Euro für sich und überweist 3
Euro an Teilnehmer 2.
Teilnehmer 2 erhält dann 9 Euro (die überwiesenen 3 Euro mal 3)
Von den 9 Euro kann Teilnehmer 2 etwas an Teilnehmer 1 zurück überweisen
(zwischen 0 und 9 Euro).
10
I4: Screenshot of the applied self-uncertainty-manipulation.
11
Table T1: Cronbach’s α, mean values, standard deviations of the HEXACO scales (Studies 1-5)
α
Honesty-Humility
Emotionality
Extraversion
Agreeableness
Conscientiousness
Openness
.70
.78
.89
.83
.79
.78
Study 1
M
SD
4.77
4.12
4.37
4.51
5.28
4.98
0.94
1.06
1.32
1.12
0.89
1.01
α
.78
.82
.84
.80
.83
.84
Study 2
M
SD
4.61
4.18
4.23
4.46
4.96
4.90
1.07
1.08
1.13
1.00
1.00
1.12
α
.75
.80
.83
.82
.80
.82
Study 3
M
SD
4.52
4.32
4.18
4.28
5.04
4.94
1.00
1.03
1.05
1.04
0.91
1.05
α
.78
.74
.83
.83
.74
.70
Study 4a
M
SD
4.65
4.05
4.74
4.47
4.94
4.53
1.09
0.99
1.04
1.08
0.88
0.98
α
.76
.79
.80
.75
.80
.82
Study 5b
M
SD
4.65
4.24
4.29
4.36
5.20
4.60
1.03
1.04
1.00
0.95
0.95
1.20
12
Table T2: Predicting trust by the HEXACO scales, the experimental condition and their
interactions using logistic regression analyses (Study 2)
constant
Conditio
E
int_1
coeff
.9318
-.2066
.1021
-.2276
se
.1506
.3011
.1393
.2785
Z
6.1890
-.6862
.7333
-.8174
p
.0000
.4926
.4634
.4137
LLCI
.6367
-.7967
-.1709
-.7735
ULCI
1.2269
.3835
.3751
.3182
constant
Conditio
X
int_1
coeff
.9403
-.2304
-.0165
.1293
se
.1495
.2989
.1334
.2668
Z
6.2896
-.7709
-.1240
.4848
p
.0000
.4408
.9013
.6278
LLCI
.6473
-.8163
-.2780
-.3935
ULCI
1.2333
.3554
.2449
.6522
constant
Conditio
A
int_1
coeff
.9553
-.2457
.0952
-.3360
se
.1499
.2998
.1564
.3125
Z
6.3724
-.8196
.6089
-1.0754
p
.0000
.4124
.5426
.2822
LLCI
.6615
-.8332
-.2114
-.9484
ULCI
1.2492
.3418
.4018
.2764
constant
Conditio
C
int_1
coeff
.9478
-.2272
.0855
-.0579
se
.1491
.2982
.1528
.3054
Z
6.3550
-.7620
.5598
-.1897
p
.0000
.4461
.5756
.8495
LLCI
.6555
-.8117
-.2140
-.6564
ULCI
1.2401
.3573
.3851
.5405
constant
Conditio
O
int_1
coeff
.9485
-.2484
.0987
.0374
se
.1497
.2992
.1339
.2677
Z
6.3381
-.8300
.7367
.1396
p
.0000
.4065
.4613
.8890
LLCI
.6552
-.8349
-.1638
-.4873
ULCI
1.2418
.3381
.3611
.5620
Note. Variables were not mean-centered. Coding of Condition: 0 = Control condition, 1 =
Uncertainty condition. int_1 refers to the interaction between the respective HEXACO scale
and the experimental condition.
Table T3: Analyses of the full model in Study 2 including trust, Honesty-Humility, the experimental
condition, and the mediator (social expectations).
************* PROCESS Procedure for SPSS Release 2.01 beta ****************
Written by Andrew F. Hayes, Ph.D.
http://www.afhayes.com
**************************************************************************
Model = 8
Y = trust
X = Conditio
M = SocialEx
W = HonestyH
Sample size
225
**************************************************************************
Outcome: SocialEx
Model Summary
R
.1790
R-sq
.0320
F
2.4390
df1
3.0000
df2
221.0000
p
.0654
Model
coeff
1.3883
2.6323
.4834
-.6046
constant
Conditio
HonestyH
int_1
se
.8786
1.2369
.1878
.2613
t
1.5802
2.1281
2.5748
-2.3138
p
.1155
.0344
.0107
.0216
LLCI
-.3431
.1946
.1134
-1.1195
ULCI
3.1198
5.0699
.8535
-.0896
Interactions:
int_1
Conditio
X
HonestyH
**************************************************************************
Outcome: trust
Coding of binary DV for analysis:
trust Analysis
.00
.00
1.00
1.00
Logistic Regression Summary
-2LL
Model LL
McFadden
209.4516
57.3774
.2150
CoxSnell
.2251
Nagelkrk
.3241
n
225.0000
Model
constant
SocialEx
Conditio
HonestyH
int_2
coeff
-3.7048
.5871
2.4217
.6935
-.6091
se
1.1973
.1053
1.5506
.2692
.3428
Z
-3.0943
5.5765
1.5618
2.5762
-1.7766
Interactions:
int_2
Conditio
X
HonestyH
p
.0020
.0000
.1183
.0100
.0756
LLCI
-6.0514
.3808
-.6173
.1659
-1.2810
ULCI
-1.3582
.7935
5.4607
1.2212
.0629
14
******************** DIRECT AND INDIRECT EFFECTS *************************
Conditional direct effect(s) of X on Y at values of the moderator(s)
HonestyH
Effect
SE
Z
p
LLCI
3.5406
.2652
.4585
.5783
.5636
-.6335
4.6129
-.3879
.3566
-1.0878
.2779
-1.0868
5.6851
-1.0410
.5607
-1.8566
.0647
-2.1399
ULCI
1.1638
.3110
.0579
Conditional indirect effect(s) of X on Y at values of the moderator(s)
Mediator
SocialEx
SocialEx
SocialEx
HonestyH
3.5406
4.6129
5.6851
Effect
.2887
-.0919
-.4726
Boot SE
.2458
.1708
.2715
BootLLCI
-.1534
-.4432
-1.0966
BootULCI
.8366
.2366
-.0263
Values for quantitative moderators are the mean and plus/minus one SD from mean.
Values for dichotomous moderators are the two values of the moderator.
**************************************************************************
Indirect effect of highest order interaction
Mediator
SocialEx
Effect
-.3550
SE(Boot)
.1815
BootLLCI
-.7647
BootULCI
-.0463
15
Table T4: Predicting trust by the HEXACO scales, the experimental condition and their interactions using
logistic regression analyses (Study 3)
constant
Conditio
E
int_1
coeff
1.2813
-.2212
.3553
-.5869
se
.1860
.3733
.1824
.3665
Z
6.8885
-.5926
1.9485
-1.6013
p
.0000
.5535
.0514
.1093
LLCI
.9167
-.9530
-.0021
-1.3052
ULCI
1.6458
.5105
.7127
constant
Conditio
X
int_1
coeff
1.2308
-.1205
-.0249
.0993
se
.1780
.3564
.1695
.3401
Z
6.9155
-.3380
-.1468
.2920
p
.0000
.7353
.8833
.7703
LLCI
.8820
-.8191
-.3570
-.5674
ULCI
1.5796
.5781
.3073
.7660
constant
Conditio
A
int_1
coeff
1.2255
-.1144
-.0417
-.4447
se
.1788
.3579
.1750
.3505
Z
6.8549
-.3196
-.2381
-1.2688
p
.0000
.7492
.8118
.2045
LLCI
.8751
-.8160
-.3847
-1.1316
ULCI
1.5758
.5872
.3013
.2422
constant
Conditio
C
int_1
coeff
1.3333
-.2206
.1581
-1.4189
se
.1949
.3912
.2210
.4437
Z
6.8417
-.5639
.7154
-3.1977
p
.0000
.5728
.4744
.0014
LLCI
.9514
-.9873
-.2751
-2.2886
ULCI
1.7153
.5461
.5913
-.5492
constant
Conditio
O
int_1
coeff
1.2299
-.1170
.1020
-.1633
se
.1784
.3572
.1719
.3440
Z
6.8958
-.3275
.5935
-.4749
p
.0000
.7433
.5528
.6349
LLCI
.8803
-.8170
-.2348
-.8375
ULCI
1.5794
.5831
.4389
.5108
Note. Variables were not mean-centered. Coding of Condition: 0 = Control condition, 1 = Uncertainty
condition. int_1 refers to the interaction between the respective HEXACO scale and the experimental
condition.
16
Table T5: Analyses of the full model in Study 3 including trust, Honesty-Humility, the experimental
condition, and the mediator (social expectations).
************* PROCESS Procedure for SPSS Release 2.01 beta ****************
Written by Andrew F. Hayes, Ph.D.
http://www.afhayes.com
**************************************************************************
Model = 8
Y = trust
X = Conditio
M = SocialEx
W = HonestyH
Sample size
181
**************************************************************************
Outcome: SocialEx
Model Summary
R
.2897
R-sq
.0839
F
5.4067
df1
3.0000
df2
177.0000
p
.0014
Model
coeff
.1369
3.6884
.7513
-.8432
constant
Conditio
HonestyH
int_1
se
.9048
1.2507
.1910
.2701
t
.1513
2.9492
3.9328
-3.1223
p
.8799
.0036
.0001
.0021
LLCI
-1.6487
1.2203
.3743
-1.3762
ULCI
1.9226
6.1566
1.1282
-.3103
Interactions:
int_1
Conditio
X
HonestyH
**************************************************************************
Outcome: trust
Coding of binary DV for analysis:
trust Analysis
.00
.00
1.00
1.00
Logistic Regression Summary
-2LL
Model LL
McFadden
116.2610
77.4221
.3997
CoxSnell
.3480
Nagelkrk
.5297
n
181.0000
Model
constant
SocialEx
Conditio
HonestyH
int_2
coeff
-4.4606
1.2295
2.5135
.5556
-.5339
se
1.7768
.2093
2.2671
.4068
.5175
Z
-2.5104
5.8739
1.1087
1.3657
-1.0317
Interactions:
int_2
Conditio
X
HonestyH
p
.0121
.0000
.2676
.1720
.3022
LLCI
-7.9431
.8193
-1.9299
-.2418
-1.5482
ULCI
-.9781
1.6398
6.9569
1.3529
.4804
17
******************** DIRECT AND INDIRECT EFFECTS *************************
Conditional direct effect(s) of X on Y at values of the moderator(s)
HonestyH
Effect
SE
Z
p
LLCI
3.5130
.6379
.6232
1.0237
.3074
-.5835
4.5180
.1014
.4950
.2048
.8380
-.8689
5.5229
-.4352
.8016
-.5428
.5879
-2.0064
ULCI
1.8593
1.0716
1.1360
Conditional indirect effect(s) of X on Y at values of the moderator(s)
Mediator
SocialEx
SocialEx
SocialEx
HonestyH
3.5130
4.5180
5.5229
Effect
.8928
-.1491
-1.1911
Boot SE
.5225
.3596
.6120
BootLLCI
-.0323
-.8464
-2.4661
BootULCI
1.9384
.6000
-.0471
Values for quantitative moderators are the mean and plus/minus one SD from mean.
Values for dichotomous moderators are the two values of the moderator.
**************************************************************************
Indirect effect of highest order interaction
Mediator
SocialEx
Effect
-1.0368
SE(Boot)
.4388
BootLLCI
-1.9636
BootULCI
-.3112
18
Table T6: Predicting trust by the HEXACO scales, the experimental condition and their interactions
(Study 4a)
constant
E
conditi
int_1
coeff
4.1155
-.0883
-.5444
.1191
se
.6430
.1566
1.0276
.2459
t
6.4001
-.5635
-.5298
.4842
p
.0000
.5741
.5972
.6291
LLCI
2.8427
-.3983
-2.5784
-.3677
ULCI
5.3884
.2218
1.4896
.6058
constant
X
conditi
int_1
coeff
3.7868
-.0045
-.3917
.0684
se
.7621
.1574
1.1147
.2299
t
4.9690
-.0285
-.3514
.2974
p
.0000
.9773
.7259
.7666
LLCI
2.2783
-.3160
-2.5982
-.3868
ULCI
5.2954
.3070
1.8148
.5236
constant
A
conditi
int_1
coeff
3.1858
.1313
.7151
-.1761
se
.6784
.1489
1.0216
.2221
t
4.6960
.8818
.7000
-.7926
p
.0000
.3796
.4853
.4295
LLCI
1.8429
-.1634
-1.3071
-.6158
ULCI
4.5287
.4259
2.7372
.2636
constant
C
conditi
int_1
coeff
4.3475
-.1195
.2773
-.0653
se
.9131
.1843
1.3596
.2706
t
4.7614
-.6482
.2039
-.2414
p
.0000
.5181
.8387
.8096
LLCI
2.5401
-.4843
-2.4140
-.6010
ULCI
6.1549
.2454
2.9686
.4704
constant
O
conditi
int_1
coeff
2.3003
.3228
2.1055
-.4794
se
.7363
.1581
1.1233
.2427
t
3.1241
2.0416
1.8744
-1.9750
p
.0022
.0433
.0632
.0505
LLCI
.8428
.0098
-.1180
-.9599
ULCI
3.7577
.6358
4.3289
.0011
Note. Variables were not mean-centered. Coding of Condition: 0 = Control condition, 1 = Uncertainty
condition. int_1 refers to the interaction between the respective HEXACO scale and the experimental
condition.
19
Table T7: Predicting social expectations by the HEXACO scales, the experimental condition and their
interactions (Study 4a)
constant
E
condi
int_1
coeff
4.2371
.1386
-.6161
.0939
se
.7490
.1824
1.1969
.2864
t
5.6572
.7596
-.5147
.3279
p
.0000
.4490
.6077
.7436
LLCI
2.7546
-.2226
-2.9852
-.4731
ULCI
5.7197
.4997
1.7531
.6609
constant
X
condi
int_1
5.1231
-.0712
-1.7033
.3161
.8868
.1831
1.2971
.2676
5.7771
-.3891
-1.3131
1.1814
.0000
.6979
.1916
.2397
3.3677
-.4337
-4.2708
-.2135
6.8785
.2912
.8643
.8458
constant
A
condi
int_1
2.8459
.4393
.0408
-.0642
.7639
.1676
1.1503
.2501
3.7254
2.6208
.0354
-.2565
.0003
.0099
.9718
.7980
1.3338
.1075
-2.2363
-.5593
4.3580
.7711
2.3178
.4309
constant
C
condi
int_1
4.4578
.0675
-.3562
.0283
1.0737
.2168
1.5988
.3183
4.1518
.3113
-.2228
.0891
.0001
.7561
.8241
.9292
2.3325
-.3616
-3.5209
-.6016
6.5831
.4965
2.8086
.6583
constant
O
condi
int_1
coeff
3.8571
.2047
.6397
-.1859
se
.8750
.1879
1.3348
.2885
t
4.4082
1.0896
.4792
-.6444
p
.0000
.2780
.6326
.5205
LLCI
2.1251
-.1672
-2.0026
-.7569
ULCI
5.5891
.5767
3.2819
.3851
Note. Variables were not mean-centered. Coding of Condition: 0 = Control condition, 1 = Uncertainty
condition. int_1 refers to the interaction between the respective HEXACO scale and the experimental
condition.
20
Table T8: Analyses of the full model in Study 4a including trust, Honesty-Humility, the experimental
condition, and the mediator (social expectations).
************** PROCESS Procedure for SPSS Release 2.16.1 *****************
Written by Andrew F. Hayes, Ph.D.
www.afhayes.com
Documentation available in Hayes (2013). www.guilford.com/p/hayes3
**************************************************************************
Model = 8
Y = trust
X = conditi
M = soex
W = HH
Sample size
127
**************************************************************************
Outcome: soex
Model Summary
R
.3430
R-sq
.1177
MSE
2.1812
F
5.4671
df1
3.0000
df2
123.0000
p
.0015
Model
coeff
1.9074
2.5342
.6323
-.6028
constant
conditi
HH
int_1
se
.7482
1.1790
.1592
.2462
t
2.5494
2.1495
3.9709
-2.4479
p
.0120
.0336
.0001
.0158
LLCI
.4264
.2004
.3171
-1.0902
ULCI
3.3883
4.8679
.9475
-.1153
Product terms key:
int_1
bed
X
HH
**************************************************************************
Outcome: trust
Model Summary
R
.5790
R-sq
.3352
MSE
1.2037
F
15.3799
df1
4.0000
df2
122.0000
p
.0000
Model
constant
soex
conditi
HH
int_2
coeff
.9429
.4282
2.5636
.1698
-.5425
se
.5703
.0670
.8921
.1256
.1873
t
1.6535
6.3929
2.8736
1.3514
-2.8963
p
.1008
.0000
.0048
.1791
.0045
LLCI
-.1860
.2956
.7976
-.0789
-.9133
ULCI
2.0719
.5608
4.3296
.4185
-.1717
Product terms key:
int_2
conditi
X
HH
******************** DIRECT AND INDIRECT EFFECTS *************************
Conditional direct effect(s) of X on Y at values of the moderator(s):
HH
Effect
SE
t
p
LLCI
3.5627
.6308
.2823
2.2340
.0273
.0718
4.6504
.0406
.1964
.2070
.8364
-.3481
5.7381
-.5495
.2836
-1.9374
.0550
-1.1109
ULCI
1.1897
.4294
.0120
21
Conditional indirect effect(s) of X on Y at values of the moderator(s):
Mediator
soex
soex
soex
HH
3.5627
4.6504
5.7381
Effect
.1656
-.1151
-.3959
Boot SE
.2034
.1190
.1753
BootLLCI
-.2102
-.3925
-.8155
BootULCI
.6089
.0899
-.1212
Values for quantitative moderators are the mean and plus/minus one SD from mean.
Values for dichotomous moderators are the two values of the moderator.
----Indirect effect of highest order product:
Mediator
soex
Effect
-.2581
SE(Boot)
.1360
BootLLCI
-.5744
BootULCI
-.0360
******************** INDEX OF MODERATED MEDIATION ************************
Mediator
soex
Index
-.2581
SE(Boot)
.1360
BootLLCI
-.5744
BootULCI
-.0360
22
Table T9: Predicting trust by the HEXACO scales, the experimental condition and their interactions
(Study 5b)
constant
E
conditi
int_1
5.9106
-.1681
.2492
-.0723
.6976
.1621
1.0145
.2326
8.4731
-1.0373
.2457
-.3107
.0000
.3016
.8063
.7566
4.5299
-.4889
-1.7587
-.5326
7.2913
.1527
2.2572
.3881
constant
X
conditi
int_1
5.4071
-.0463
.9544
.2023
.8051
.1842
1.0805
.2455
6.7157
-.2512
-.8833
.8243
.0000
.8021
.3788
.4114
3.8135
-.4108
-3.0930
-.2835
7.0008
.3182
1.1843
.6882
constant
A
conditi
int_1
4.1364
.2535
.1650
.0048
.8475
.1960
1.1492
.2591
4.8807
1.2935
-.1436
.0185
.0000
.1982
.8861
.9853
2.4590
-.1344
-2.4395
-.5081
5.8138
.6414
2.1096
.5176
constant
C
conditi
int_1
3.4156
.3480
.1941
-.0584
1.0012
.1914
1.3461
.2552
3.4116
1.8188
.1442
-.2288
.0009
.0714
.8856
.8194
1.4340
-.0307
-2.4703
-.5636
5.3972
.7268
2.8584
.4468
constant
O
conditi
int_1
6.6112
-.3002
.2121
.0190
.6767
.1403
.9376
.1973
9.7692
-2.1392
-.2262
.0964
.0000
.0344
.8214
.9234
5.2718
-.5779
-2.0678
-.3714
7.9507
-.0224
1.6436
.4094
Note. Variables were not mean-centered. Coding of Condition: 0 = Control condition, 1 = Uncertainty
condition. int_1 refers to the interaction between the respective HEXACO scale and the experimental
condition.
23
Table T10: Information on dropouts
Agreed to participate and responded to
the very first item
Completed HEXACO
N in the experimental condition
N in the control condition
Completed assessment of Trust
Study 1
Study 2
Study 3
Study 4a
Study 4b
Study 5a
Study 5b
158
152
n.a.
n.a.
150
270
254
112
113
225
200
194
88
93
181
128
128
63
64
127
194
n.a.
99
95
194
309
302
n.a.
n.a.
300
158
150
66
62
128
24
Figure F1: Trust in the police as a function of Honesty-Humility and the experimental condition (Study
5b). Low Honesty-Humility refers to 1 SD below the mean; high Honesty-Humility refers to 1 SD above
the mean.