Supplemental Materials
The Longer-Term Effects of a Brief Hazard Perception Training Intervention in Older
Drivers
by M. S. Horswill et al., 2015, Psychology and Aging
http://dx.doi.org/10.1037/a0038671
Table A1
Descriptive Statistics of the Sample by Condition
Trained no
booster
71.05 (6.88)
Placebo
Age (years)
Trained with
booster
72.32 (4.87)
Years with open driving licence
52.23 (4.32)
51.05 (7.66)
54.33 (6.85)
Kilometres per year
11763.64
(6886.74)
10892.73
(7300.02)
9213.04
(6939.36)
Sex
45.5% female
36.4% female
37.5% female
Modified Mini Mental State
Examination (out of 100)
Own a computer
94.45 (4.57)
94.9 (4.22)
94.91 (3.19)
95.50%
95.50%
83.30%
Prior experience with computer
Simple spatial reaction time (s)
95.50%
0.82 (0.16)
100%
0.89 (0.24)
87.50%
0.82 (0.11)
73.46 (6.04)
Table A2
Means and Standard Deviations of Hazard Perception Test Response Times (s), With ANOVA
Results, After Matching Placebo Group Participants to Individuals in the Training Condition
by Pre-Intervention Hazard Perception Response Times
Training
Conditions
M (SD)
Placebo
Condition
M (SD)
Time × Group
interaction
Time main effect
Group main effect
(N = 24)
(N = 24)
Pre-intervention
hazard
perception test
5.01
(0.63)
4.84
(0.80)
Immediately
following
intervention
4.32
(0.94)
4.72
(0.74)
F(1,46) = 9.47,
MSE = 0.21, p <
0.01, 2 = 0.17
F(1,46) = 19.29,
MSE = 0.21, p <
.001, 2 = 0.30
F(1,46) = 0.30,
MSE = 1.04, p =
.587, 2 = 0.01
One month
following
intervention
4.44
(0.81)
4.75
(0.71)
F(1,46) = 4.42,
MSE = 0.30, p =
.043, 2 = 0.09
F(1,46) = 9.17,
MSE = 0.30, p =
.004, 2 = 0.17
F(1,46) = 0.13,
MSE = 0.80, p =
.729, 2 < 0.01
Three months
following
intervention
4.46
(0.89)
4.72
(0.58)
F(1,46) = 5.09,
MSE = 0.23, p =
.034, 2 = 0.10
F(1,46) = 11.4,
MSE = 0.23, p =
.002, 2 = 0.20
F(1,46) = 0.07,
MSE = 0.86, p =
.801, 2 < 0.01
Note: Due to the difference in pre-training hazard perception response times between the
training and placebo groups in the present study, we matched 24 participants from the
combined training groups (i.e., both training with booster and training without booster) with
the 24 participants in the placebo group, based on pre-intervention hazard perception
response times. The matching was done using the following rules:
(1) Each member of the control group in turn was matched with the member of the
combined training groups who had the closest pre-intervention hazard perception test
response time (excluding training group participants who did not complete one of the
hazard perception tests).
(2) We allocated matches working from the participant with the fastest preintervention hazard perception test response time in the control group to the slowest
(but note that matching slowest to fastest did not change the outcomes of these
analyses).
(3) If the closest match for any participant had already been allocated to another
individual in the control group, then we instead used the next closest match (whether
faster or slower).
(4) If the next closest match had also already been allocated, then we chose the next
closest match (repeating until an unallocated participant was identified).
It was found that the training effect (time × group interaction) was significant for all three
post-intervention tests, consistent with the analyses from the full sample.
Table A3
Means (and Standard Deviations) of Hazard Perception Response Times (s) for Training and
Placebo Groups Across the Four Hazard Perception Tests Used in the Study (Full Sample)
Trained
Placebo
6.01 (1.64)
4.89 (1.54)
4.23 (1.83)
4.66 (1.42)
1 month after intervention
4.55 (1.53)
4.72 (1.36)
3 months after intervention
4.92 (1.85)
4.66 (1.1)
Pre-intervention hazard perception
response time
Immediate post-intervention hazard
perception response time
Table A4
The Effect of Training on Hazard Perception Test Hit Rates. Means (and Standard
Deviations) of Hazard Perception Hit Rates for Training and Placebo Groups Across the
Four Hazard Perception Tests Used in the Study
Training
Conditions
M (SD)
Placebo
Condition
M (SD)
Time x Group
interaction
Time main effect
Group main effect
(N = 51)
(N = 24)
Pre-intervention
hazard
perception test
74%
(11%)
80%
(11%)
Immediately
following
intervention
86%
(12%)
81%
(9%)
F(1,73) = 20.16,
MSE = 0.01, p <
.001, 2 = 0.22
F(1,73) = 26.22,
MSE = 0.01, p <
.001, 2 = 0.26
F(1,73) = 0.13,
MSE = 0.02, p =
.715, 2 < 0.01
One month
following
intervention
82%
(10%)
83%
(16%)
F(1,73) = 2.66,
MSE = 0.01, p =
.112, 2 = 0.04
F(1,73) = 13.94,
MSE = 0.01, p =
.001, 2 = 0.16
F(1,73) = 2.54,
MSE = 0.02, p =
.117, 2 = 0.03
Three months
following
intervention
80%
(13%)
82%
(9%)
F(1,73) = 4.33,
MSE = 0.01, p =
.053, 2 = 0.06
F(1,73) = 8.51,
MSE = 0.01, p =
.005, 2 = 0.10
F(1,73) = 2.26,
MSE = 0.02, p =
.149, 2 = 0.03
Note: The hazard perception tests used in this study were not designed to yield hit rates as a
performance measure. Traffic conflicts were chosen to optimize response time as the
outcome, which meant only including events to which most participants would respond
eventually. As a result, hit rates were not predicted to be sensitive to any interventions,
consistent with our previous work. However, we still calculated hit rates (proportion of traffic
conflicts responded to) as a secondary outcome measure in case any effects emerged that
might have consequences for the interpretation of the response time findings. As can be seen
in Table A4, training condition participants responded to a higher proportion of items than
their baseline, in comparison with placebo, immediately post-intervention. However, the
effect of training on hit rates was not significant at 1 month and 3 months.
Figure A1. Change in hazard perception hit rates following the interventions (postintervention minus pre-intervention), where a positive value indicates that hit rate has
increased following the interventions. Error bars are standard errors of the mean.