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Age effects on traffic sign comprehension
IATSSR-00223; No of Pages 8 IATSS Research xxx (2019) xxx
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IATSS Research
Research article
Age effects on traffic sign comprehension Philipp Schulz a,⁎, Kirsten Labudda c, Volkmar Bertke d, Silvana Bellgardt c, Sebastian Boedeker a,b, Stefan Spannhorst b, Stefan H. Kreisel a,b, Martin Driessen a,b, Thomas Beblo a, Max Toepper a,b a
Evangelisches Klinikum Bethel, Department of Psychiatry and Psychotherapy, Research Division, Remterweg 69-71, 33617 Bielefeld, Germany Evangelisches Klinikum Bethel, Department of Psychiatry and Psychotherapy, Division of Geriatric Psychiatry, Bethesdaweg 12, 33617 Bielefeld, Germany Department of Psychology, Bielefeld University, Universitätsstraße 25, D-33615 Bielefeld, Germany d DEKRA Automobil GmbH, Assessment Centre for Driving Fitness, Lange Straße 79, 32756 Detmold, Germany b c
a r t i c l e
i n f o
Article history: Received 25 February 2019 Received in revised form 20 September 2019 Accepted 2 October 2019 Available online xxxx Keywords: Traffic signs Symbol comprehension Ageing Older drivers Driving fitness Cognition
a b s t r a c t Ageing is associated with changes in cognitive functions that affect fitness to drive. However, little is known about age effects on traffic sign comprehension (TSC). In this study, we assessed 37 older and 29 younger healthy drivers with a standardised traffic sign test and a comprehensive neuropsychological test battery. Older drivers showed lower TSC speed and tended to interpret more recent traffic signs less accurately than younger drivers. Higher cognitive functioning was generally associated with better TSC performances in both groups. In older drivers, TSC speed was related to specific cognitive functions such as cognitive flexibility and inhibition. Our findings suggest that traffic signs should appear in time to meet age-related constraints in TSC processing speed and should put low demands on inhibitory skills and cognitive flexibility. However, our findings also suggest that cognitive abilities are important for TSC regardless of age. In addition, a periodic update of traffic sign knowledge appears to be necessary. © 2019 International Association of Traffic and Safety Sciences. Production and hosting by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
1. Introduction Due to demographic change, the proportion of older drivers rapidly increases. This raises questions about public safety, considering that ageing goes along with changes in driving-related sensory-motor and cognitive functions [1–4], which again are related to at-fault crashinvolvement [5], impaired driving competences [6], and on-road driving errors [7]. Surprisingly, there is little evidence whether and how ageing affects traffic sign comprehension (TSC), which is surprising since TSC is associated with the number of recent accidents involving older drivers [8] and requires cognitive skills which in turn are affected by ageing [1,9]. Traffic signs are very important for the organisation of road traffic [10,11]. They usually contain symbols to display relevant information for drivers in an easy, fast and unambiguous way [12]. Whether the interpretation of traffic signs is simple or not depends on specific details of ⁎ Corresponding author at: Evangelisches Klinikum Bethel, Department of Psychiatry and Psychotherapy, Research Division, Remterweg 69-71, D-33617 Bielefeld, Germany. E-mail address: [email protected] (P. Schulz). Peer review under responsibility of International Association of Traffic and Safety Sciences.
the sign (i.e. compatibility, uniformity) [11,13] and specific factors of the driver (i.e. age, education level, driving experience, cultural factors) [14]. Higher age of the driver, for example, is associated with reduced perceptual [15] and cognitive abilities such as semantic memory and executive functions both of which affect symbol [16] and traffic sign comprehension [17]. Several other studies suggest that the comprehension of warning symbols is impaired in older people, probably due to agerelated changes in selective attention, inhibitory efficiency, and the ability to form new associations [12,18,19]. Evidence about how ageing affects TSC is sparse. A Canadian research team examined age-related differences in a visual search paradigm by measuring speed and accuracy of traffic sign identification under easy and complex conditions (single-tasks and dual-tasks). They found that healthy older adults required more time to detect traffic signs because they had limited attentional resources under complex conditions compared to younger drivers [20]. Moreover, older individuals were less accurate, which was supported by the findings of another study under real-world conditions revealing accuracy differences between healthy older drivers and younger drivers in detecting and remembering traffic signs [21]. Shinar, Dewar, Summala and Zakowska [13] investigated different groups of active drivers from different countries. They presented 32 traffic signs on cards and asked the participants
https://doi.org/10.1016/j.iatssr.2019.10.001 0386-1112/© 2019 International Association of Traffic and Safety Sciences. Production and hosting by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Please cite this article as: P. Schulz, K. Labudda, V. Bertke, et al., Age effects on traffic sign comprehension, IATSS Research, https://doi.org/10.1016/ j.iatssr.2019.10.001
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for sign meaning using an open answer format. Results revealed that older drivers – at least in two countries – tended to show poorer accuracy rates than novice drivers, which was confirmed by more recent results indicating that older drivers recognise different traffic signs less accurately than younger drivers [22]. Age effects on TSC may also be associated with age-related changes in driving habits and driving experience. Moreover, the meaning of traffic signs is usually taught and internalised only once (i.e. at the time when the driving license is applied). Thus, older drivers may not be aware of recently introduced or modified traffic signs, which may result in misinterpretations and driving errors [11,14]. Supporting this, a study by Ng and Chan [23] revealed that TSC performance negatively correlated with the number of years of holding a driving license. They discussed that novices may be more aware of theoretical traffic sign knowledge due to the shorter time span from obtaining the driving license to the TSC performance test [23]. In sum, there is some evidence suggesting age effects on TSC performance. However, study results appear to be inconsistent [14]: Some studies revealed impaired TSC performance in older relative to younger drivers [13,21,24], whereas others did not [10,23]. Inconsistencies are probably due to differences in study design and age group differences. Notably, age effects on TSC performance more likely occur in samples in which age differences between groups are larger [24] than in samples with smaller age group differences [23]. Most studies examined age group differences in terms of TSC accuracy (i.e., percent of correct responses). However, in real-life road traffic, not only accuracy, but also the speed of TSC is relevant for safe traffic participation. Two previous studies reported an age-related decline in TSC processing speed [8,22]. Noteworthy, Stutts and colleagues [8] also found an association between processing speed in the traffic sign test and accident involvement. An age-related decline of processing speed [25], cognitive flexibility and working memory [1] may influence both, speed and accuracy of TSC [14]. However, to the best of our knowledge, no study has systematically investigated age effects on accuracy and speed of TSC in relation to cognitive functioning. 1.1. Rationale of the study In the current study, we therefore investigated group differences between younger and older drivers with respect to speed and accuracy performances in a standardised traffic sign test. Moreover, we aimed at the specification of the relationship between TSC and cognitive abilities. Due to the theoretical considerations in the introduction section, we expect lower TSC accuracy and lower TSC processing speed in older compared to younger drivers. Moreover, we assume that age-related accuracy differences are modulated by sign currency with older drivers showing lower accuracy rates than younger drivers particularly at more recent signs. Better TSC performances (i.e. accuracy and speed) should be associated with different cognitive functions such as higher psychomotor speed, executive functioning, semantic memory, and symbol processing skills. Further exploratory analyses addressed accuracy differences between age groups in interpreting different sign categories and specific traffic signs. 2. Materials and methods 2.1. Participants Initially, the study included a group of 40 older participants (N65 years) and a group of 32 younger participants (18–35 years). Younger participants were recruited via word-by-mouth and older participants via a local newspaper article. All participants had to meet following inclusion criteria: Currently active driver, valid driver's license, and an appropriate age for the group of younger or older participants.
Exclusion criteria were current diseases relevant for driving according to the German guidelines for the assessment of fitness-to-drive [26]; current mental disorders as identified by the screening questions from the structured clinical interview for DSM-IV [27] and international diagnosis checklists according to DSM-IV [28] as well as an intake of category III medication with a severe influence on driving fitness determined using the DRUID checklist (Driving under the influence of drugs, alcohol and medicines) [29]. Three younger participants had to be excluded from the study due to a recent loss of driving license (n = 1) or current substance misuse (n = 2). Two older participants were excluded from analysis due to currently diagnosed Mild Cognitive Impairment (MCI) [30]. Moreover, one older driver had to be excluded from analyses considering the case as a severe outlier (extremely low speed in the traffic sign test). Altogether, 37 older and 29 younger participants were included into data analyses (Table 1). Age groups differed with respect to years of school education (t(60.19) = 4.62, p b .001) and sex (Χ2(1) = 7.14, p b .01). However, due to differences between today's general school system and former systems, the average time of school education in years is not really comparable between younger and older participants. The higher proportion of male older drivers reflects the distribution of license owners in this age cohort. Nevertheless, possible confounding effects of demographic variables were excluded by statistical analyses (for more detail, please see section 3.3.4). 2.2. Experimental procedures All participants first provided information about demographic and driving-related data, then underwent an extensive neuropsychological assessment and finally completed the TSC test (for more detail please see sections 2.2.2 and 2.2.3). Written informed consent was provided prior to study start. The study protocol was approved by a local ethical review board in accordance with the Declaration of Helsinki. 2.2.1. Neuropsychological assessment To assess different cognitive functions such as psychomotor speed, visuospatial skills, executive functions and semantic memory, wellestablished neuropsychological paper-and-pencil tests were applied. Trail-Making Test parts A and B (TMT-A; TMT-B) were applied to assess psychomotor speed and nonverbal cognitive flexibility [31]. In both tests, parts A and B, the time in seconds was recorded for analyses. In order to assess verbal fluency and verbal cognitive flexibility, we applied two verbal fluency tasks [32]. In the first task, participants were asked to name as much words as possible beginning with the letter S within one minute. In the second task, participants were asked to name as much words as possible with alternating first letters H and T within one minute. For both tasks, the number of words was recorded for analyses. In order to assess reading speed, color naming and inhibition, we additionally used a short version of the Stroop color-word test [33]. Participants were asked to read a list of color words printed in black, Table 1 Sample characteristics. Demographic and driving-related data
Younger drivers
Older drivers
N Age Sex n = female (%) School education in years Years licensed Mileage per year
29 25.1 (2.8) 19 (65.5%) 12.3 (1.4)
37 76.2 (5.3) 12 (32.4%) 10.2 (2.3)
6.8 (2.5) 16,206.9 (10,546.3)
54.7 (6.2) 11,666.9 (6958.7)
t-statistic/Χ2-Statistic
p b .001 p b .01 p b .001 p b .001 p = .05
Note: Except for sex, all sample characteristics are shown as means and standard deviations.
Please cite this article as: P. Schulz, K. Labudda, V. Bertke, et al., Age effects on traffic sign comprehension, IATSS Research, https://doi.org/10.1016/ j.iatssr.2019.10.001
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Fig. 1. Items of the traffic sign test. Note: Correct response options are marked with an x. Error points per item are displayed in brackets. Sign category and the year of fist occurrence or last modification are displayed at the upper left and upper right corner of each item.
Please cite this article as: P. Schulz, K. Labudda, V. Bertke, et al., Age effects on traffic sign comprehension, IATSS Research, https://doi.org/10.1016/ j.iatssr.2019.10.001
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to name the print color of different bars, and to name the print color of different color words (red, blue, yellow, and green) as fast as possible (i.e., if the word green is colored in red, the correct answer is red). Processing time were recorded for analyses. To assess semantic memory performance, we applied a category fluency task (animal fluency) where participants are asked to name as much animals as possible within one minute [34], as well as a 15-item version of the Boston Naming test (BNT) where participants are asked to name different objects displayed on cards [35]. For statistical analyses, we used the total number of named words in the category fluency task and the sum of correct responses in the BNT, respectively. To assess general symbol processing, we applied the symbol processing task (SPT) [16]. The SPT consists of 18 items and requires choosing one of four symbols with the “best match” to a certain target symbol. Participants were asked to make their decision by pointing to the respective alternative. The SPT total score is calculated by the sum of correct responses. 2.2.2. Traffic sign comprehension (TSC) To assess TSC, we used a paper pencil multiple-choice traffic sign test with 22 items (Fig. 1). All items were extracted from exam questions of the official written part of the German driving test for novice drivers [36]. A traffic psychologist and a driving instructor selected the items in consideration of relevance, frequency of occurrence in urban areas and difficulty. Each item shows a traffic sign including three response options for its possible meaning. At least one of these response options is correct. For some items, however, two or three response options are correct. According to the official test guidelines in Germany, each item can only be solved correctly (correct response option(s) chosen, incorrect response option(s) not chosen) or incorrectly (correct response option(s) not or partially chosen and/or incorrect response option (s) chosen). Pre-defined error scores according to the official test forms ranging from two to four points weights each item as an indicator of its relative importance. If an item was solved incorrectly, participants received the respective error points. The possible sum of error points could range from 0 (best performance) to 60 (worst performance). According to an international classification of traffic signs, the 22 traffic signs were assigned to three categories [37]: Warning signs (3 items), signs giving order (13 items), and information signs (6 items). According to the history of traffic sign development, we also assigned the 22 traffic signs to the categories old signs (8 older signs introduced before 1957 and unmodified since then), middle-aged signs (10 signs introduced or modified in 1970) and new signs (4 more recent signs introduced in 1989 or later) [37]. Two trained psychologists applied the test by explaining the multiple-choice scoring scheme and asking the participant to complete the test as fast and correct as possible. All participants were asked to indicate their response (a,b,c) verbally. Time measurement started immediately after the instruction. Two main scores were collected for analyses: (1) The sum of error points (TSC accuracy); (2) the processing time in seconds for completing the TSC test as a measure of TSC speed. Noteworthy, the sum of error points and processing time in the traffic sign test did not correlate in both groups (p N .05). Other outcome variables were the average rates of correctly interpreted items in the subscales warning signs, signs giving order, and information signs as well as old, middle-aged, and new traffic signs. 2.3. Data analysis In a first step, we checked distributions for all relevant variables by graphical inspection of QQ-plots, histograms, and boxplots in both groups. Group comparisons of demographic and neuropsychological data were analysed by using Χ2 tests for categorical and t-tests for continuous data.
To examine group differences between older and younger drivers in TSC accuracy (mean sum of TSC error points) and processing time (TSC speed) in the traffic sign test, we performed t-tests for independent groups. To exclude effects of possible confounders (i.e. education, sex, mileage, and reading speed) on main outcomes (accuracy, processing time), partial correlations were used. Considering non-normal data distribution and variance heterogeneity between groups (assumptions for parametric analyses not met), the effect of sign currency on age-related accuracy differences was examined by an omnibus test of a mixed between x within subjects model using trimmed means and winsorised variances (Welch-James's F-statistic) with approximate degrees of freedom [38]. This method is a more conservative non-parametric alternative to a repeated measures analysis of variance (ANOVA). Within factor was sign currency (old signs vs. middle-aged signs vs. new signs), between factor was age group, the rates of items interpreted correctly served as dependent variables. Post-hoc Mann-Whitney U tests were utilised to specify the origin of the interaction effect. To examine age group differences in the interpretation of specific traffic sign categories, we calculated a 2 × 3 ANOVA as well as post hoc t-tests. Within factor of ANOVA was sign category (warning signs vs. signs giving order vs. information signs), between factor was age group, the rates of items interpreted correctly served as dependent variables. Exploratory analyses of age group differences in the interpretation of specific traffic signs included Χ2 tests. To examine associations between different outcomes in the traffic sign test (i.e. TSC accuracy and TSC speed) as well as between traffic sign test outcomes and cognitive functions, we calculated Pearson or Spearman correlations dependent on distribution characteristics. For the exploratory comparison of association strengths between traffic sign test scores and cognitive functions, we compared independent correlation coefficients [39,40]. We set the critical α at 0.05 using twotailed tests. Statistical analyses were run with the Statistical Package for the Social Sciences (SPSS version 20.0) and R (version 3.4.4) [41]. 3. Results 3.1. Driving-related data Older drivers held their licenses for 55 years on average (SD = 6.18) and drove 11,666 (SD = 6958.67) kilometers in the past year. Younger drivers held their licenses for 7 years on average (SD = 2.51) and drove 16,207 (SD = 10,546.26) kilometers in the past year. As shown in Table 1, groups differed with respect to years licensed (t(50.26) = −42.69, p b .001), and mileage (t(46.19) = 2.00, p = .05). 3.2. Neuropsychological data Group comparisons of cognitive functions are displayed in Table 2. Results revealed that older participants showed lower psychomotor speed than younger participants (t(64) = −5.31, p b .001) as indicated by slower TMT-A processing time (older: M = 41.41, SD = 12.67; younger: M = 26.86, SD = 8.53). Moreover, older participants showed poorer nonverbal cognitive flexibility (t(56.10) = −3.62, p = .001), as indicated by slower processing time in the TMT-B (older: M = 101.41, SD = 52.81; younger: M = 65.10, SD = 27.09), lower reading speed in seconds (older: M = 34.30, SD = 5.45; younger: M = 31.00, SD = 4.75; t(64) = −2.58, p b .05) as well as poorer inhibition (M = 92.47, SD = 27.49) than younger participants (M = 72.34, SD = 12.77; t(64) = −3.64, p = .001) as indicated by the increased time to complete the respective subtest of the Stroop color-word test. No significant group differences were found (all p N .10) for semantic memory (animal names, BNT), verbal fluency (S-words), verbal cognitive flexibility (H-T-words), color naming (Color Word Test) and symbol processing (SPT). In summary, older participants showed poorer
Please cite this article as: P. Schulz, K. Labudda, V. Bertke, et al., Age effects on traffic sign comprehension, IATSS Research, https://doi.org/10.1016/ j.iatssr.2019.10.001
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Table 2 Neuropsychological assessment. Neuropsychological domains (test)
Younger drivers (n = 29)
Older drivers (n = 37)
p-value
Psychomotor speed (TMT-A in seconds) Nonverbal cognitive flexibility (TMT-B in seconds) Verbal fluency (S-words) Verbal cognitive flexibility (H-T-Words) Reading speed (Color Word Test) Color naming (Color Word Test) Inhibition (Color Word Test) Semantic memory (Animal names) Semantic memory (BNT) Symbol processing (SPT)
26.86 (8.53) 65.10 (27.09) 14.93 (4.84) 13.83 (4.43) 31.00 (4.75) 46.97 (8.24) 72.34 (12.77) 25.28 (7.32) 14.72 (0.59) 16.72 (1.19)
41.41 (12.67) 101.41 (52.81) 15.86 (4.02) 14.86 (4.39) 34.30 (5.45) 47.14 (7.06) 92.47 (27.49) 24.65 (4.68) 14.43 (0.90) 16.33 (1.60)
b0.001 b0.001 n.s. n.s. b0.05 n.s. b0.001 n.s. n.s. n.s.
Note: n.s. = not significant, TMT = Trail Making Test, BNT = Boston Naming Test, SPT = Symbol Processing Task; Means and standard deviations are shown.
performances in processing speed and executive functions, whereas symbol processing, semantic memory performances and verbal abilities were similar to those of younger participants. 3.3. Traffic sign comprehension 3.3.1. Age group differences in TSC performance Fig. 2 displays group comparisons in traffic sign test performances. Between-group comparisons (Fig. 2) revealed no significant differences in the mean sum of error points between older (M = 24.27, SD = 8.18) and younger participants (M = 22.45, SD = 7.30). Older and younger participants interpreted about 60% of traffic sign test items correctly. However, older participants needed significantly more time (M = 333.08, SD = 103.08) than younger participants (M = 217.35, SD = 48.04; t(53.31) = −6.02, p b .001) to complete the traffic sign test. 3.3.2. TSC performance by sign currency Non-parametric omnibus test of a mixed between x within subjects model revealed a significant main effect of “sign currency” (WelchJames's F(2, 63.87) = 51.93, p b .001) indicating lowest accuracy at middle-aged signs relative to other sign categories across all participants. The main effect of “age group” did not reach statistical significance. The interaction effect of “age group” x “sign currency” was marginally significant (Welch-James's F(2, 53.72) = 3.09, p b .10), indicating that the effect of sign currency on TSC accuracy tended to differ between groups. In fact, exploratory post-hoc Mann-Whitney-U tests showed that older participants were less accurate (Fig. 2) in the interpretation of new traffic signs (M = 61%, SD = 24%, Mdn = 50%) than younger participants (M = 74%, SD = 17%, Mdn = 75%, U = 370.00, p b .05), whereas there were no age group differences in the interpretation accuracy of old and middle-aged traffic signs. 3.3.3. TSC performance by sign category Repeated-measures ANOVA revealed a significant main effect of “sign category” (F(1.5, 95.3) = 9.46, p = .001) indicating higher accuracy rates at signs giving order relative to warning and information signs across all participants. The main effect of “age group” and the interaction effect of “age group” x “sign category”, however, did not reach statistical significance. The results show that sign category similarly affects TSC accuracy in both age groups. 3.3.4. Possible confounding effects Since groups differed in terms of education, sex, mileage, and reading speed, we further calculated partial correlation analyses in order to exclude possible confounding effects. The factor age group significantly correlated with processing time in the traffic sign test (rpb = 0.37, p b .01) after controlling for sex, school education in years, mileage per year, and reading speed, indicating that the group of older participants needed more time. School education in years was found to be correlated with the sum of TSC error points (r = −0.28, p b .05) when
controlling for above variables, indicating that higher educated participants showed less errors (lower sum of TSC error points). 3.3.5. TSC performance at specific signs Table 3 shows that in 19 out of 22 items of the traffic sign test there were no significant accuracy differences between older and younger participants (all p values N.10). However, younger participants showed higher accuracy rates (89.7%, 93.1%, 75.9%) than older participants (62.2%, 54.1%, 48.6%) at items 4 (motorway entrance), 7 (traffic calming zone) and 11 (road works). Items 1 (left or right only), 10 (dead-end street), and 17 (ahead or right only) were very simple and interpreted correctly by nearly 100% of participants in both age groups. Items 3 (priority road) and 12 (bus/tramway stop) were very difficult and interpreted correctly by b18% of younger participants and by b12% of older participants, respectively. 3.3.6. Association between cognitive functions and TSC performance Table 4 shows associations between cognitive functions and traffic sign test performances as well as comparisons of correlation coefficients between groups. The pattern of correlation coefficients polarity appeared to be homogenous across age groups, indicating that a higher level of cognitive functioning was associated with better TSC performance regardless of age. In the group of older participants, processing time in the traffic sign test moderately correlated with non-verbal cognitive flexibility (TMT-B), inhibition (Color Word Test) and semantic memory performances (Animal Names, Boston Naming Test). In the group of younger participants, moderate correlations between the sum of error points in the traffic sign test and non-verbal cognitive flexibility (TMT-B), verbal cognitive flexibility (H-T-Words) and semantic memory (animal names) were observed. Comparisons of correlation coefficients between groups revealed only few differences: The correlations of verbal fluency (S-words) with the sum of error points (z = −2.58, p b .01) was higher in younger than in older participants, whereas the correlation of semantic memory (animal names) with processing time was higher in older than in younger participants (z = −2.09). 4. Discussion To the best of our knowledge, this is the first study examining age effects on TSC in consideration of cognitive functions using a standardised traffic sign test and comprehensive neuropsychological assessment. Most importantly, the current results revealed that older drivers show reduced TSC processing speed compared to younger drivers. Slightly constraints in the interpretation accuracy of traffic signs in older drivers, by contrast, are limited to more recent and some specific signs. Higher cognitive ability was associated with better TSC performance in both groups, suggesting that cognitive abilities are important for TSC regardless of age.
Please cite this article as: P. Schulz, K. Labudda, V. Bertke, et al., Age effects on traffic sign comprehension, IATSS Research, https://doi.org/10.1016/ j.iatssr.2019.10.001
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Fig. 2. Performance differences of older and younger participants in the traffic sign test. Note: Figs. A and B display group differences between older and younger drivers in the sum of TSC error points and processing time (higher scores indicate poorer performances for both outcomes). Figs. C and D display accuracy differences between age groups depending on sign currency and sign category. Mean values and standard deviations are shown for both groups separately. *p b .05, ***p b .001.
4.1. TSC processing speed As expected, older drivers showed lower TSC processing speed than younger drivers which is in line with results on age-related cognitive slowing [1,42]. In accordance with previous studies [8,22], our findings revealed that older drivers required about 35% more time than younger drivers to complete the traffic sign test, indicating an age-related reduction of TSC processing speed. Noteworthy, older drivers also showed lower reading speed than younger drivers, which could have affected processing time in the traffic sign test (given the multiple-choice response format). However, TSC processing time did not correlate with reading speed in both groups and the association between TSC processing speed and age remained significant after controlling for reading
speed. In addition, older compared to younger drivers showed poorer nonverbal cognitive flexibility and inhibition, both of which were associated with TSC processing speed in the group of older drivers. Consequently, lower TSC processing speed in older drivers appears to be affected particularly by speed-related executive functions (i.e. cognitive flexibility and inhibition) beyond the influence of reading speed. Latter findings fit a large body of evidence showing that reduced cognitive flexibility and inhibitory control are related to impaired driving fitness particularly in older adults [5,6,43]. Moreover, TSC processing speed was associated with semantic memory performance in older drivers, which is not surprising since semantic memory appears to be a relevant factor for general symbol comprehension in older adults [16]. However, there were no differences
Please cite this article as: P. Schulz, K. Labudda, V. Bertke, et al., Age effects on traffic sign comprehension, IATSS Research, https://doi.org/10.1016/ j.iatssr.2019.10.001
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Table 3 Accuracy differences between older and younger drivers at specific traffic signs. No.
Traffic signs (Scales)
Younger drivers (N = 29)
Older drivers (N = 37)
Χ2-statistic
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
Left or Right only (Order/Old) Priority over oncoming Traffic (Information/Middle-aged) Priority Road (Information/Middle-aged) Motorway Entrance (Information/Middle-aged) Maximum Speed 60kph (Order/Old) Give Priority to Vehicles from opposite Direction (Order/Middle-aged) Traffic calming Zone (Information/New) Unmarked Intersection with Priority from Right (Warning/Middle-aged) Pedestrians only (Order/Middle-aged) Dead-end Street (Information/Middle-aged) Road Works (Warning/Old) Bus/tramway stop (Order/Middle-aged) Ahead only (Order/Old) Pedestrian Crossing (Information/Middle-aged) Entry to 30 km/h zone (Order/New) Road narrows on both Sides (Warning/Old) Ahead or Right only (Order/Old) No stopping (Order/Middle-aged) End of 30 km/h Zone (Order/New) Turn Left (Order/Old) No Vehicles (Order/Old) Give Priority to Vehicles driving in the Roundabout (Order/New)
100% 27.6% 10.3% 89.7% 72.4% 86.2% 93.1% 41.1% 24.1% 100% 75.9% 17.2% 75.9% 48.3% 79.3% 48.3% 100% 72.4% 51.7% 34.5% 69.0% 72.4%
100% 37.8% 5.4% 62.2% 83.8% 89.2% 54.1% 43.2% 43.2% 97.3% 48.6% 10.8% 89.2% 40.5% 75.7% 51.4% 97.3% 81.1% 54.1% 29.7% 78.4% 62.2%
n.s. n.s. n.s. p b .05 n.s. n.s. p b .01 n.s. n.s. n.s. p b .05 n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.
Note: The rate of correct interpretation per item and group is displayed.
between older and younger drivers regarding semantic memory performance in the current sample. Taken together, above findings suggest that traffic signs should appear in time before a specific traffic situation occurs to meet agerelated constraints in TSC processing speed [15]. Moreover, traffic signs should put low demands on inhibitory skills and cognitive flexibility. 4.2. TSC accuracy On the basis of previous findings [13,21,22], we additionally assumed that older drivers show lower overall accuracy in the interpretation of traffic signs than younger drivers, which was not confirmed by the current results. Although the driver's exam of older adults was approximately 55 years ago, rates of correctly interpreted signs were as low as in younger drivers. Both groups showed very similar mean sum Table 4 Correlations between cognitive functions and traffic sign test performances as well as group comparisons of association strengths. Traffic sign test performances Sum of error points
Processing time
Cognitive functions (Test)
Y
O
p for Δ
Psychomotor speed (TMT-A) Nonverbal cognitive flexibilitya (TMT-B) Verbal fluency (S-Words) Verbal cognitive flexibility (H-T-Words) Reading speed (Color Word Test) Color naming (Color Word Test) Inhibitiona (Color Word Test) Semantic memory (Animal Names) Semantic memorya (BNT) Symbol processinga (SPT)
0.27 0.40⁎
0.30 0.30
n.s. n.s.
Y
O
p for Δ
0.13 0.14
0.20 0.35⁎
n.s. n.s.
−0.66⁎⁎⁎ −0.12 b0.01 −0.09 −0.28 −0.44⁎ −0.14 n.s. −0.33 −0.13
n.s. n.s.
0.06
0.26
n.s.
0.33
0.31
n.s.
0.16
0.24
n.s.
0.14
0.30
n.s.
0.12 −0.41⁎
0.26 n.s. −0.30 n.s.
0.30 0.20
0.38⁎ n.s. −0.33⁎ b0.05
−0.26 0.02
−0.21 n.s. −0.13 n.s.
−0.02 −0.41⁎ n.s. −0.02 −0.05 n.s.
a Spearman correlations are displayed; Y = younger drivers, O = older drivers, TMT = Trail Making Test, BNT = Boston Naming Test, SPT = Symbol Processing Task, n.s. = not significant, Δ = difference between correlation coefficients. ⁎ p b .05. ⁎⁎⁎ p b .001.
scores of error points, interpreted only about two third of traffic signs correctly and thus did not differ in overall TSC accuracy. In older drivers, TSC accuracy did not correlate with cognitive sub functions. In younger drivers, however, TSC accuracy was associated with cognitive flexibility and semantic memory performance, indicating the relevance of these cognitive domains for fast and accurate TSC. School education was associated with interpretation accuracy in the traffic sign test as well [15]. Contrary to our assumptions, however, general symbol processing accuracy was not related to TSC accuracy in both groups, which might be due to differences between SPT (pictograms, mainly based on semantic associations) and traffic sign test (traffic signs: additionally based on theoretical knowledge). In line with other studies [10,17,23], our results suggest that age does not necessarily affect overall theoretical knowledge about traffic signs and associated regulations. Instead, our findings highlight the necessity of a traffic sign knowledge update for all active drivers. Nevertheless, further analyses of sign currency revealed accuracy differences between older and younger drivers. Particularly, the comprehension of recently introduced traffic signs (traffic calming zone, give priority to vehicles in the roundabout, see Fig. 1 and Table 3) was somewhat more difficult for older drivers possibly reflecting that they did not learn the meaning of these signs during driving school. Contrary to sign currency, sign category did not differentially affect TSC accuracy in the two age groups. However, all participants regardless of age were more accurate in the interpretation of signs giving order than in the interpretation of warning and information signs. Besides somewhat lower TSC accuracy at more recent signs, older drivers interpreted the traffic signs motorway entrance, traffic calming zone, and road works less often correctly than younger drivers, which may be due to age-related changes in driving habits: Older drivers limit their mileage and driving range, they prefer to drive at daytime and in familiar areas, they rather live in rural areas, tend to avoid downtown traffic and drive on motorways more rarely than younger drivers [44]. All of these habits might affect the familiarity of certain signs for older drivers. Motorway-related traffic signs, for example, may be not as familiar to older as to younger drivers, simply because older drivers drive on motorways less often. Taken together, above results suggest an update of traffic knowledge for all active drivers. For older drivers, this may particularly apply to recently introduced signs. Moreover, age-related changes of driving habits should be taken into account.
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4.3. Conclusions and limitations Most importantly, the current findings revealed that older drivers show reduced TSC processing speed compared to younger drivers, whereas slight age-related constraints in TSC accuracy are limited to more recent traffic signs. Our findings imply that traffic signs should be placed soon enough to meet age-related constraints in TSC processing speed and should put low demands on inhibitory skills and cognitive flexibility. In addition, our results highlight the necessity of a periodic traffic sign update for all active drivers. For older drivers, this may particularly apply to recently introduced signs. Finally, the analysis of correlation patterns between various cognitive skills and different TSC outcomes indicated that overall higher cognitive functioning was associated with better TSC performance in both groups, suggesting that cognitive abilities are important for TSC regardless of age. Given the cross-sectional study design, however, statements on the causality of effects are not possible. Moreover, the sample may not be representative of the general population due to the relatively small sample size. Since not all traffic signs used in this study are internationally established, the study findings can only be partially generalized. Further research should include larger samples of younger and older drivers to confirm the external validity and robustness of our findings. Regarding ecological validity, it may be more valid to examine how drivers deal with traffic signs in real traffic. In fact, it cannot be ruled out that some drivers make the right decision in real traffic, although they do not fully understand the meaning of a sign. Vice versa, however, correct decisions in real traffic appear to be more likely, if the actual meaning of a sign is understood. Moreover, future research should focus on additional factors that may facilitate and accelerate on-road TSC such as visual perception, contrast or illumination. Declaration of Conflict of Interest The Authors declare that they have no conflict of interest. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Acknowledgements We would like to thank all participants who took part in our study. References [1] M. Toepper, Dissociating normal aging from Alzheimer’s disease: a view from cognitive neuroscience, J. Alzheimers Dis. 57 (2017) 331–352. [2] M. Karthaus, M. Falkenstein, Functional changes and driving performance in older drivers, Geriatrics 1 (2016) 12. [3] P. Schulz, S. Spannhorst, T. Beblo, C. Thomas, S. Kreisel, M. Driessen, M. Toepper, Preliminary validation of a questionnaire covering risk factors for impaired driving skills in elderly patients, Geriatrics 1 (2016) 5. [4] S. Spannhorst, M. Toepper, P. Schulz, G. Wenzel, M. Driessen, S. Kreisel, Advice for elderly drivers in a german memory clinic, Geriatrics 1 (2016) 9. [5] K.K. Ball, D.L. Roenker, V.G. Wadley, J.D. Edwards, D.L. Roth, G. McGwin, R. Raleigh, J.J. Joyce, G.M. Cissell, T. Dube, Can high-risk older drivers be identified through performance-based measures in a Department of Motor Vehicles setting? J. Am. Geriatr. Soc. 54 (2006) 77–84. [6] J.L. Mathias, L.K. Lucas, Cognitive predictors of unsafe driving in older drivers: a meta-analysis, Int. Psychogeriatr. IPA 21 (2009) 637–653. [7] K.J. Anstey, J. Wood, Chronological age and age-related cognitive deficits are associated with an increase in multiple types of driving errors in late life, Neuropsychology 25 (2011) 613–621. [8] J.C. Stutts, R.J. Stewart, C. Martell, Cognitive test performance and crash risk in an older driver population, Accid. Anal. Prev. 30 (1998) 337–346. [9] A. Brashear, F.W. Unverzagt, E.R. Kuhn, B.S. Glazier, M.R. Farlow, A.J. Perkins, S.L. Hui, Impaired traffic sign recognition in drivers with dementia, Am. J. Alzheimers Dis. Other Dement. 13 (1998) 131–137.
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IATSS Research
Research article
Age effects on traffic sign comprehension Philipp Schulz a,⁎, Kirsten Labudda c, Volkmar Bertke d, Silvana Bellgardt c, Sebastian Boedeker a,b, Stefan Spannhorst b, Stefan H. Kreisel a,b, Martin Driessen a,b, Thomas Beblo a, Max Toepper a,b a
Evangelisches Klinikum Bethel, Department of Psychiatry and Psychotherapy, Research Division, Remterweg 69-71, 33617 Bielefeld, Germany Evangelisches Klinikum Bethel, Department of Psychiatry and Psychotherapy, Division of Geriatric Psychiatry, Bethesdaweg 12, 33617 Bielefeld, Germany Department of Psychology, Bielefeld University, Universitätsstraße 25, D-33615 Bielefeld, Germany d DEKRA Automobil GmbH, Assessment Centre for Driving Fitness, Lange Straße 79, 32756 Detmold, Germany b c
a r t i c l e
i n f o
Article history: Received 25 February 2019 Received in revised form 20 September 2019 Accepted 2 October 2019 Available online xxxx Keywords: Traffic signs Symbol comprehension Ageing Older drivers Driving fitness Cognition
a b s t r a c t Ageing is associated with changes in cognitive functions that affect fitness to drive. However, little is known about age effects on traffic sign comprehension (TSC). In this study, we assessed 37 older and 29 younger healthy drivers with a standardised traffic sign test and a comprehensive neuropsychological test battery. Older drivers showed lower TSC speed and tended to interpret more recent traffic signs less accurately than younger drivers. Higher cognitive functioning was generally associated with better TSC performances in both groups. In older drivers, TSC speed was related to specific cognitive functions such as cognitive flexibility and inhibition. Our findings suggest that traffic signs should appear in time to meet age-related constraints in TSC processing speed and should put low demands on inhibitory skills and cognitive flexibility. However, our findings also suggest that cognitive abilities are important for TSC regardless of age. In addition, a periodic update of traffic sign knowledge appears to be necessary. © 2019 International Association of Traffic and Safety Sciences. Production and hosting by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
1. Introduction Due to demographic change, the proportion of older drivers rapidly increases. This raises questions about public safety, considering that ageing goes along with changes in driving-related sensory-motor and cognitive functions [1–4], which again are related to at-fault crashinvolvement [5], impaired driving competences [6], and on-road driving errors [7]. Surprisingly, there is little evidence whether and how ageing affects traffic sign comprehension (TSC), which is surprising since TSC is associated with the number of recent accidents involving older drivers [8] and requires cognitive skills which in turn are affected by ageing [1,9]. Traffic signs are very important for the organisation of road traffic [10,11]. They usually contain symbols to display relevant information for drivers in an easy, fast and unambiguous way [12]. Whether the interpretation of traffic signs is simple or not depends on specific details of ⁎ Corresponding author at: Evangelisches Klinikum Bethel, Department of Psychiatry and Psychotherapy, Research Division, Remterweg 69-71, D-33617 Bielefeld, Germany. E-mail address: [email protected] (P. Schulz). Peer review under responsibility of International Association of Traffic and Safety Sciences.
the sign (i.e. compatibility, uniformity) [11,13] and specific factors of the driver (i.e. age, education level, driving experience, cultural factors) [14]. Higher age of the driver, for example, is associated with reduced perceptual [15] and cognitive abilities such as semantic memory and executive functions both of which affect symbol [16] and traffic sign comprehension [17]. Several other studies suggest that the comprehension of warning symbols is impaired in older people, probably due to agerelated changes in selective attention, inhibitory efficiency, and the ability to form new associations [12,18,19]. Evidence about how ageing affects TSC is sparse. A Canadian research team examined age-related differences in a visual search paradigm by measuring speed and accuracy of traffic sign identification under easy and complex conditions (single-tasks and dual-tasks). They found that healthy older adults required more time to detect traffic signs because they had limited attentional resources under complex conditions compared to younger drivers [20]. Moreover, older individuals were less accurate, which was supported by the findings of another study under real-world conditions revealing accuracy differences between healthy older drivers and younger drivers in detecting and remembering traffic signs [21]. Shinar, Dewar, Summala and Zakowska [13] investigated different groups of active drivers from different countries. They presented 32 traffic signs on cards and asked the participants
https://doi.org/10.1016/j.iatssr.2019.10.001 0386-1112/© 2019 International Association of Traffic and Safety Sciences. Production and hosting by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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for sign meaning using an open answer format. Results revealed that older drivers – at least in two countries – tended to show poorer accuracy rates than novice drivers, which was confirmed by more recent results indicating that older drivers recognise different traffic signs less accurately than younger drivers [22]. Age effects on TSC may also be associated with age-related changes in driving habits and driving experience. Moreover, the meaning of traffic signs is usually taught and internalised only once (i.e. at the time when the driving license is applied). Thus, older drivers may not be aware of recently introduced or modified traffic signs, which may result in misinterpretations and driving errors [11,14]. Supporting this, a study by Ng and Chan [23] revealed that TSC performance negatively correlated with the number of years of holding a driving license. They discussed that novices may be more aware of theoretical traffic sign knowledge due to the shorter time span from obtaining the driving license to the TSC performance test [23]. In sum, there is some evidence suggesting age effects on TSC performance. However, study results appear to be inconsistent [14]: Some studies revealed impaired TSC performance in older relative to younger drivers [13,21,24], whereas others did not [10,23]. Inconsistencies are probably due to differences in study design and age group differences. Notably, age effects on TSC performance more likely occur in samples in which age differences between groups are larger [24] than in samples with smaller age group differences [23]. Most studies examined age group differences in terms of TSC accuracy (i.e., percent of correct responses). However, in real-life road traffic, not only accuracy, but also the speed of TSC is relevant for safe traffic participation. Two previous studies reported an age-related decline in TSC processing speed [8,22]. Noteworthy, Stutts and colleagues [8] also found an association between processing speed in the traffic sign test and accident involvement. An age-related decline of processing speed [25], cognitive flexibility and working memory [1] may influence both, speed and accuracy of TSC [14]. However, to the best of our knowledge, no study has systematically investigated age effects on accuracy and speed of TSC in relation to cognitive functioning. 1.1. Rationale of the study In the current study, we therefore investigated group differences between younger and older drivers with respect to speed and accuracy performances in a standardised traffic sign test. Moreover, we aimed at the specification of the relationship between TSC and cognitive abilities. Due to the theoretical considerations in the introduction section, we expect lower TSC accuracy and lower TSC processing speed in older compared to younger drivers. Moreover, we assume that age-related accuracy differences are modulated by sign currency with older drivers showing lower accuracy rates than younger drivers particularly at more recent signs. Better TSC performances (i.e. accuracy and speed) should be associated with different cognitive functions such as higher psychomotor speed, executive functioning, semantic memory, and symbol processing skills. Further exploratory analyses addressed accuracy differences between age groups in interpreting different sign categories and specific traffic signs. 2. Materials and methods 2.1. Participants Initially, the study included a group of 40 older participants (N65 years) and a group of 32 younger participants (18–35 years). Younger participants were recruited via word-by-mouth and older participants via a local newspaper article. All participants had to meet following inclusion criteria: Currently active driver, valid driver's license, and an appropriate age for the group of younger or older participants.
Exclusion criteria were current diseases relevant for driving according to the German guidelines for the assessment of fitness-to-drive [26]; current mental disorders as identified by the screening questions from the structured clinical interview for DSM-IV [27] and international diagnosis checklists according to DSM-IV [28] as well as an intake of category III medication with a severe influence on driving fitness determined using the DRUID checklist (Driving under the influence of drugs, alcohol and medicines) [29]. Three younger participants had to be excluded from the study due to a recent loss of driving license (n = 1) or current substance misuse (n = 2). Two older participants were excluded from analysis due to currently diagnosed Mild Cognitive Impairment (MCI) [30]. Moreover, one older driver had to be excluded from analyses considering the case as a severe outlier (extremely low speed in the traffic sign test). Altogether, 37 older and 29 younger participants were included into data analyses (Table 1). Age groups differed with respect to years of school education (t(60.19) = 4.62, p b .001) and sex (Χ2(1) = 7.14, p b .01). However, due to differences between today's general school system and former systems, the average time of school education in years is not really comparable between younger and older participants. The higher proportion of male older drivers reflects the distribution of license owners in this age cohort. Nevertheless, possible confounding effects of demographic variables were excluded by statistical analyses (for more detail, please see section 3.3.4). 2.2. Experimental procedures All participants first provided information about demographic and driving-related data, then underwent an extensive neuropsychological assessment and finally completed the TSC test (for more detail please see sections 2.2.2 and 2.2.3). Written informed consent was provided prior to study start. The study protocol was approved by a local ethical review board in accordance with the Declaration of Helsinki. 2.2.1. Neuropsychological assessment To assess different cognitive functions such as psychomotor speed, visuospatial skills, executive functions and semantic memory, wellestablished neuropsychological paper-and-pencil tests were applied. Trail-Making Test parts A and B (TMT-A; TMT-B) were applied to assess psychomotor speed and nonverbal cognitive flexibility [31]. In both tests, parts A and B, the time in seconds was recorded for analyses. In order to assess verbal fluency and verbal cognitive flexibility, we applied two verbal fluency tasks [32]. In the first task, participants were asked to name as much words as possible beginning with the letter S within one minute. In the second task, participants were asked to name as much words as possible with alternating first letters H and T within one minute. For both tasks, the number of words was recorded for analyses. In order to assess reading speed, color naming and inhibition, we additionally used a short version of the Stroop color-word test [33]. Participants were asked to read a list of color words printed in black, Table 1 Sample characteristics. Demographic and driving-related data
Younger drivers
Older drivers
N Age Sex n = female (%) School education in years Years licensed Mileage per year
29 25.1 (2.8) 19 (65.5%) 12.3 (1.4)
37 76.2 (5.3) 12 (32.4%) 10.2 (2.3)
6.8 (2.5) 16,206.9 (10,546.3)
54.7 (6.2) 11,666.9 (6958.7)
t-statistic/Χ2-Statistic
p b .001 p b .01 p b .001 p b .001 p = .05
Note: Except for sex, all sample characteristics are shown as means and standard deviations.
Please cite this article as: P. Schulz, K. Labudda, V. Bertke, et al., Age effects on traffic sign comprehension, IATSS Research, https://doi.org/10.1016/ j.iatssr.2019.10.001
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Fig. 1. Items of the traffic sign test. Note: Correct response options are marked with an x. Error points per item are displayed in brackets. Sign category and the year of fist occurrence or last modification are displayed at the upper left and upper right corner of each item.
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to name the print color of different bars, and to name the print color of different color words (red, blue, yellow, and green) as fast as possible (i.e., if the word green is colored in red, the correct answer is red). Processing time were recorded for analyses. To assess semantic memory performance, we applied a category fluency task (animal fluency) where participants are asked to name as much animals as possible within one minute [34], as well as a 15-item version of the Boston Naming test (BNT) where participants are asked to name different objects displayed on cards [35]. For statistical analyses, we used the total number of named words in the category fluency task and the sum of correct responses in the BNT, respectively. To assess general symbol processing, we applied the symbol processing task (SPT) [16]. The SPT consists of 18 items and requires choosing one of four symbols with the “best match” to a certain target symbol. Participants were asked to make their decision by pointing to the respective alternative. The SPT total score is calculated by the sum of correct responses. 2.2.2. Traffic sign comprehension (TSC) To assess TSC, we used a paper pencil multiple-choice traffic sign test with 22 items (Fig. 1). All items were extracted from exam questions of the official written part of the German driving test for novice drivers [36]. A traffic psychologist and a driving instructor selected the items in consideration of relevance, frequency of occurrence in urban areas and difficulty. Each item shows a traffic sign including three response options for its possible meaning. At least one of these response options is correct. For some items, however, two or three response options are correct. According to the official test guidelines in Germany, each item can only be solved correctly (correct response option(s) chosen, incorrect response option(s) not chosen) or incorrectly (correct response option(s) not or partially chosen and/or incorrect response option (s) chosen). Pre-defined error scores according to the official test forms ranging from two to four points weights each item as an indicator of its relative importance. If an item was solved incorrectly, participants received the respective error points. The possible sum of error points could range from 0 (best performance) to 60 (worst performance). According to an international classification of traffic signs, the 22 traffic signs were assigned to three categories [37]: Warning signs (3 items), signs giving order (13 items), and information signs (6 items). According to the history of traffic sign development, we also assigned the 22 traffic signs to the categories old signs (8 older signs introduced before 1957 and unmodified since then), middle-aged signs (10 signs introduced or modified in 1970) and new signs (4 more recent signs introduced in 1989 or later) [37]. Two trained psychologists applied the test by explaining the multiple-choice scoring scheme and asking the participant to complete the test as fast and correct as possible. All participants were asked to indicate their response (a,b,c) verbally. Time measurement started immediately after the instruction. Two main scores were collected for analyses: (1) The sum of error points (TSC accuracy); (2) the processing time in seconds for completing the TSC test as a measure of TSC speed. Noteworthy, the sum of error points and processing time in the traffic sign test did not correlate in both groups (p N .05). Other outcome variables were the average rates of correctly interpreted items in the subscales warning signs, signs giving order, and information signs as well as old, middle-aged, and new traffic signs. 2.3. Data analysis In a first step, we checked distributions for all relevant variables by graphical inspection of QQ-plots, histograms, and boxplots in both groups. Group comparisons of demographic and neuropsychological data were analysed by using Χ2 tests for categorical and t-tests for continuous data.
To examine group differences between older and younger drivers in TSC accuracy (mean sum of TSC error points) and processing time (TSC speed) in the traffic sign test, we performed t-tests for independent groups. To exclude effects of possible confounders (i.e. education, sex, mileage, and reading speed) on main outcomes (accuracy, processing time), partial correlations were used. Considering non-normal data distribution and variance heterogeneity between groups (assumptions for parametric analyses not met), the effect of sign currency on age-related accuracy differences was examined by an omnibus test of a mixed between x within subjects model using trimmed means and winsorised variances (Welch-James's F-statistic) with approximate degrees of freedom [38]. This method is a more conservative non-parametric alternative to a repeated measures analysis of variance (ANOVA). Within factor was sign currency (old signs vs. middle-aged signs vs. new signs), between factor was age group, the rates of items interpreted correctly served as dependent variables. Post-hoc Mann-Whitney U tests were utilised to specify the origin of the interaction effect. To examine age group differences in the interpretation of specific traffic sign categories, we calculated a 2 × 3 ANOVA as well as post hoc t-tests. Within factor of ANOVA was sign category (warning signs vs. signs giving order vs. information signs), between factor was age group, the rates of items interpreted correctly served as dependent variables. Exploratory analyses of age group differences in the interpretation of specific traffic signs included Χ2 tests. To examine associations between different outcomes in the traffic sign test (i.e. TSC accuracy and TSC speed) as well as between traffic sign test outcomes and cognitive functions, we calculated Pearson or Spearman correlations dependent on distribution characteristics. For the exploratory comparison of association strengths between traffic sign test scores and cognitive functions, we compared independent correlation coefficients [39,40]. We set the critical α at 0.05 using twotailed tests. Statistical analyses were run with the Statistical Package for the Social Sciences (SPSS version 20.0) and R (version 3.4.4) [41]. 3. Results 3.1. Driving-related data Older drivers held their licenses for 55 years on average (SD = 6.18) and drove 11,666 (SD = 6958.67) kilometers in the past year. Younger drivers held their licenses for 7 years on average (SD = 2.51) and drove 16,207 (SD = 10,546.26) kilometers in the past year. As shown in Table 1, groups differed with respect to years licensed (t(50.26) = −42.69, p b .001), and mileage (t(46.19) = 2.00, p = .05). 3.2. Neuropsychological data Group comparisons of cognitive functions are displayed in Table 2. Results revealed that older participants showed lower psychomotor speed than younger participants (t(64) = −5.31, p b .001) as indicated by slower TMT-A processing time (older: M = 41.41, SD = 12.67; younger: M = 26.86, SD = 8.53). Moreover, older participants showed poorer nonverbal cognitive flexibility (t(56.10) = −3.62, p = .001), as indicated by slower processing time in the TMT-B (older: M = 101.41, SD = 52.81; younger: M = 65.10, SD = 27.09), lower reading speed in seconds (older: M = 34.30, SD = 5.45; younger: M = 31.00, SD = 4.75; t(64) = −2.58, p b .05) as well as poorer inhibition (M = 92.47, SD = 27.49) than younger participants (M = 72.34, SD = 12.77; t(64) = −3.64, p = .001) as indicated by the increased time to complete the respective subtest of the Stroop color-word test. No significant group differences were found (all p N .10) for semantic memory (animal names, BNT), verbal fluency (S-words), verbal cognitive flexibility (H-T-words), color naming (Color Word Test) and symbol processing (SPT). In summary, older participants showed poorer
Please cite this article as: P. Schulz, K. Labudda, V. Bertke, et al., Age effects on traffic sign comprehension, IATSS Research, https://doi.org/10.1016/ j.iatssr.2019.10.001
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Table 2 Neuropsychological assessment. Neuropsychological domains (test)
Younger drivers (n = 29)
Older drivers (n = 37)
p-value
Psychomotor speed (TMT-A in seconds) Nonverbal cognitive flexibility (TMT-B in seconds) Verbal fluency (S-words) Verbal cognitive flexibility (H-T-Words) Reading speed (Color Word Test) Color naming (Color Word Test) Inhibition (Color Word Test) Semantic memory (Animal names) Semantic memory (BNT) Symbol processing (SPT)
26.86 (8.53) 65.10 (27.09) 14.93 (4.84) 13.83 (4.43) 31.00 (4.75) 46.97 (8.24) 72.34 (12.77) 25.28 (7.32) 14.72 (0.59) 16.72 (1.19)
41.41 (12.67) 101.41 (52.81) 15.86 (4.02) 14.86 (4.39) 34.30 (5.45) 47.14 (7.06) 92.47 (27.49) 24.65 (4.68) 14.43 (0.90) 16.33 (1.60)
b0.001 b0.001 n.s. n.s. b0.05 n.s. b0.001 n.s. n.s. n.s.
Note: n.s. = not significant, TMT = Trail Making Test, BNT = Boston Naming Test, SPT = Symbol Processing Task; Means and standard deviations are shown.
performances in processing speed and executive functions, whereas symbol processing, semantic memory performances and verbal abilities were similar to those of younger participants. 3.3. Traffic sign comprehension 3.3.1. Age group differences in TSC performance Fig. 2 displays group comparisons in traffic sign test performances. Between-group comparisons (Fig. 2) revealed no significant differences in the mean sum of error points between older (M = 24.27, SD = 8.18) and younger participants (M = 22.45, SD = 7.30). Older and younger participants interpreted about 60% of traffic sign test items correctly. However, older participants needed significantly more time (M = 333.08, SD = 103.08) than younger participants (M = 217.35, SD = 48.04; t(53.31) = −6.02, p b .001) to complete the traffic sign test. 3.3.2. TSC performance by sign currency Non-parametric omnibus test of a mixed between x within subjects model revealed a significant main effect of “sign currency” (WelchJames's F(2, 63.87) = 51.93, p b .001) indicating lowest accuracy at middle-aged signs relative to other sign categories across all participants. The main effect of “age group” did not reach statistical significance. The interaction effect of “age group” x “sign currency” was marginally significant (Welch-James's F(2, 53.72) = 3.09, p b .10), indicating that the effect of sign currency on TSC accuracy tended to differ between groups. In fact, exploratory post-hoc Mann-Whitney-U tests showed that older participants were less accurate (Fig. 2) in the interpretation of new traffic signs (M = 61%, SD = 24%, Mdn = 50%) than younger participants (M = 74%, SD = 17%, Mdn = 75%, U = 370.00, p b .05), whereas there were no age group differences in the interpretation accuracy of old and middle-aged traffic signs. 3.3.3. TSC performance by sign category Repeated-measures ANOVA revealed a significant main effect of “sign category” (F(1.5, 95.3) = 9.46, p = .001) indicating higher accuracy rates at signs giving order relative to warning and information signs across all participants. The main effect of “age group” and the interaction effect of “age group” x “sign category”, however, did not reach statistical significance. The results show that sign category similarly affects TSC accuracy in both age groups. 3.3.4. Possible confounding effects Since groups differed in terms of education, sex, mileage, and reading speed, we further calculated partial correlation analyses in order to exclude possible confounding effects. The factor age group significantly correlated with processing time in the traffic sign test (rpb = 0.37, p b .01) after controlling for sex, school education in years, mileage per year, and reading speed, indicating that the group of older participants needed more time. School education in years was found to be correlated with the sum of TSC error points (r = −0.28, p b .05) when
controlling for above variables, indicating that higher educated participants showed less errors (lower sum of TSC error points). 3.3.5. TSC performance at specific signs Table 3 shows that in 19 out of 22 items of the traffic sign test there were no significant accuracy differences between older and younger participants (all p values N.10). However, younger participants showed higher accuracy rates (89.7%, 93.1%, 75.9%) than older participants (62.2%, 54.1%, 48.6%) at items 4 (motorway entrance), 7 (traffic calming zone) and 11 (road works). Items 1 (left or right only), 10 (dead-end street), and 17 (ahead or right only) were very simple and interpreted correctly by nearly 100% of participants in both age groups. Items 3 (priority road) and 12 (bus/tramway stop) were very difficult and interpreted correctly by b18% of younger participants and by b12% of older participants, respectively. 3.3.6. Association between cognitive functions and TSC performance Table 4 shows associations between cognitive functions and traffic sign test performances as well as comparisons of correlation coefficients between groups. The pattern of correlation coefficients polarity appeared to be homogenous across age groups, indicating that a higher level of cognitive functioning was associated with better TSC performance regardless of age. In the group of older participants, processing time in the traffic sign test moderately correlated with non-verbal cognitive flexibility (TMT-B), inhibition (Color Word Test) and semantic memory performances (Animal Names, Boston Naming Test). In the group of younger participants, moderate correlations between the sum of error points in the traffic sign test and non-verbal cognitive flexibility (TMT-B), verbal cognitive flexibility (H-T-Words) and semantic memory (animal names) were observed. Comparisons of correlation coefficients between groups revealed only few differences: The correlations of verbal fluency (S-words) with the sum of error points (z = −2.58, p b .01) was higher in younger than in older participants, whereas the correlation of semantic memory (animal names) with processing time was higher in older than in younger participants (z = −2.09). 4. Discussion To the best of our knowledge, this is the first study examining age effects on TSC in consideration of cognitive functions using a standardised traffic sign test and comprehensive neuropsychological assessment. Most importantly, the current results revealed that older drivers show reduced TSC processing speed compared to younger drivers. Slightly constraints in the interpretation accuracy of traffic signs in older drivers, by contrast, are limited to more recent and some specific signs. Higher cognitive ability was associated with better TSC performance in both groups, suggesting that cognitive abilities are important for TSC regardless of age.
Please cite this article as: P. Schulz, K. Labudda, V. Bertke, et al., Age effects on traffic sign comprehension, IATSS Research, https://doi.org/10.1016/ j.iatssr.2019.10.001
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Fig. 2. Performance differences of older and younger participants in the traffic sign test. Note: Figs. A and B display group differences between older and younger drivers in the sum of TSC error points and processing time (higher scores indicate poorer performances for both outcomes). Figs. C and D display accuracy differences between age groups depending on sign currency and sign category. Mean values and standard deviations are shown for both groups separately. *p b .05, ***p b .001.
4.1. TSC processing speed As expected, older drivers showed lower TSC processing speed than younger drivers which is in line with results on age-related cognitive slowing [1,42]. In accordance with previous studies [8,22], our findings revealed that older drivers required about 35% more time than younger drivers to complete the traffic sign test, indicating an age-related reduction of TSC processing speed. Noteworthy, older drivers also showed lower reading speed than younger drivers, which could have affected processing time in the traffic sign test (given the multiple-choice response format). However, TSC processing time did not correlate with reading speed in both groups and the association between TSC processing speed and age remained significant after controlling for reading
speed. In addition, older compared to younger drivers showed poorer nonverbal cognitive flexibility and inhibition, both of which were associated with TSC processing speed in the group of older drivers. Consequently, lower TSC processing speed in older drivers appears to be affected particularly by speed-related executive functions (i.e. cognitive flexibility and inhibition) beyond the influence of reading speed. Latter findings fit a large body of evidence showing that reduced cognitive flexibility and inhibitory control are related to impaired driving fitness particularly in older adults [5,6,43]. Moreover, TSC processing speed was associated with semantic memory performance in older drivers, which is not surprising since semantic memory appears to be a relevant factor for general symbol comprehension in older adults [16]. However, there were no differences
Please cite this article as: P. Schulz, K. Labudda, V. Bertke, et al., Age effects on traffic sign comprehension, IATSS Research, https://doi.org/10.1016/ j.iatssr.2019.10.001
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Table 3 Accuracy differences between older and younger drivers at specific traffic signs. No.
Traffic signs (Scales)
Younger drivers (N = 29)
Older drivers (N = 37)
Χ2-statistic
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
Left or Right only (Order/Old) Priority over oncoming Traffic (Information/Middle-aged) Priority Road (Information/Middle-aged) Motorway Entrance (Information/Middle-aged) Maximum Speed 60kph (Order/Old) Give Priority to Vehicles from opposite Direction (Order/Middle-aged) Traffic calming Zone (Information/New) Unmarked Intersection with Priority from Right (Warning/Middle-aged) Pedestrians only (Order/Middle-aged) Dead-end Street (Information/Middle-aged) Road Works (Warning/Old) Bus/tramway stop (Order/Middle-aged) Ahead only (Order/Old) Pedestrian Crossing (Information/Middle-aged) Entry to 30 km/h zone (Order/New) Road narrows on both Sides (Warning/Old) Ahead or Right only (Order/Old) No stopping (Order/Middle-aged) End of 30 km/h Zone (Order/New) Turn Left (Order/Old) No Vehicles (Order/Old) Give Priority to Vehicles driving in the Roundabout (Order/New)
100% 27.6% 10.3% 89.7% 72.4% 86.2% 93.1% 41.1% 24.1% 100% 75.9% 17.2% 75.9% 48.3% 79.3% 48.3% 100% 72.4% 51.7% 34.5% 69.0% 72.4%
100% 37.8% 5.4% 62.2% 83.8% 89.2% 54.1% 43.2% 43.2% 97.3% 48.6% 10.8% 89.2% 40.5% 75.7% 51.4% 97.3% 81.1% 54.1% 29.7% 78.4% 62.2%
n.s. n.s. n.s. p b .05 n.s. n.s. p b .01 n.s. n.s. n.s. p b .05 n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s.
Note: The rate of correct interpretation per item and group is displayed.
between older and younger drivers regarding semantic memory performance in the current sample. Taken together, above findings suggest that traffic signs should appear in time before a specific traffic situation occurs to meet agerelated constraints in TSC processing speed [15]. Moreover, traffic signs should put low demands on inhibitory skills and cognitive flexibility. 4.2. TSC accuracy On the basis of previous findings [13,21,22], we additionally assumed that older drivers show lower overall accuracy in the interpretation of traffic signs than younger drivers, which was not confirmed by the current results. Although the driver's exam of older adults was approximately 55 years ago, rates of correctly interpreted signs were as low as in younger drivers. Both groups showed very similar mean sum Table 4 Correlations between cognitive functions and traffic sign test performances as well as group comparisons of association strengths. Traffic sign test performances Sum of error points
Processing time
Cognitive functions (Test)
Y
O
p for Δ
Psychomotor speed (TMT-A) Nonverbal cognitive flexibilitya (TMT-B) Verbal fluency (S-Words) Verbal cognitive flexibility (H-T-Words) Reading speed (Color Word Test) Color naming (Color Word Test) Inhibitiona (Color Word Test) Semantic memory (Animal Names) Semantic memorya (BNT) Symbol processinga (SPT)
0.27 0.40⁎
0.30 0.30
n.s. n.s.
Y
O
p for Δ
0.13 0.14
0.20 0.35⁎
n.s. n.s.
−0.66⁎⁎⁎ −0.12 b0.01 −0.09 −0.28 −0.44⁎ −0.14 n.s. −0.33 −0.13
n.s. n.s.
0.06
0.26
n.s.
0.33
0.31
n.s.
0.16
0.24
n.s.
0.14
0.30
n.s.
0.12 −0.41⁎
0.26 n.s. −0.30 n.s.
0.30 0.20
0.38⁎ n.s. −0.33⁎ b0.05
−0.26 0.02
−0.21 n.s. −0.13 n.s.
−0.02 −0.41⁎ n.s. −0.02 −0.05 n.s.
a Spearman correlations are displayed; Y = younger drivers, O = older drivers, TMT = Trail Making Test, BNT = Boston Naming Test, SPT = Symbol Processing Task, n.s. = not significant, Δ = difference between correlation coefficients. ⁎ p b .05. ⁎⁎⁎ p b .001.
scores of error points, interpreted only about two third of traffic signs correctly and thus did not differ in overall TSC accuracy. In older drivers, TSC accuracy did not correlate with cognitive sub functions. In younger drivers, however, TSC accuracy was associated with cognitive flexibility and semantic memory performance, indicating the relevance of these cognitive domains for fast and accurate TSC. School education was associated with interpretation accuracy in the traffic sign test as well [15]. Contrary to our assumptions, however, general symbol processing accuracy was not related to TSC accuracy in both groups, which might be due to differences between SPT (pictograms, mainly based on semantic associations) and traffic sign test (traffic signs: additionally based on theoretical knowledge). In line with other studies [10,17,23], our results suggest that age does not necessarily affect overall theoretical knowledge about traffic signs and associated regulations. Instead, our findings highlight the necessity of a traffic sign knowledge update for all active drivers. Nevertheless, further analyses of sign currency revealed accuracy differences between older and younger drivers. Particularly, the comprehension of recently introduced traffic signs (traffic calming zone, give priority to vehicles in the roundabout, see Fig. 1 and Table 3) was somewhat more difficult for older drivers possibly reflecting that they did not learn the meaning of these signs during driving school. Contrary to sign currency, sign category did not differentially affect TSC accuracy in the two age groups. However, all participants regardless of age were more accurate in the interpretation of signs giving order than in the interpretation of warning and information signs. Besides somewhat lower TSC accuracy at more recent signs, older drivers interpreted the traffic signs motorway entrance, traffic calming zone, and road works less often correctly than younger drivers, which may be due to age-related changes in driving habits: Older drivers limit their mileage and driving range, they prefer to drive at daytime and in familiar areas, they rather live in rural areas, tend to avoid downtown traffic and drive on motorways more rarely than younger drivers [44]. All of these habits might affect the familiarity of certain signs for older drivers. Motorway-related traffic signs, for example, may be not as familiar to older as to younger drivers, simply because older drivers drive on motorways less often. Taken together, above results suggest an update of traffic knowledge for all active drivers. For older drivers, this may particularly apply to recently introduced signs. Moreover, age-related changes of driving habits should be taken into account.
Please cite this article as: P. Schulz, K. Labudda, V. Bertke, et al., Age effects on traffic sign comprehension, IATSS Research, https://doi.org/10.1016/ j.iatssr.2019.10.001
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4.3. Conclusions and limitations Most importantly, the current findings revealed that older drivers show reduced TSC processing speed compared to younger drivers, whereas slight age-related constraints in TSC accuracy are limited to more recent traffic signs. Our findings imply that traffic signs should be placed soon enough to meet age-related constraints in TSC processing speed and should put low demands on inhibitory skills and cognitive flexibility. In addition, our results highlight the necessity of a periodic traffic sign update for all active drivers. For older drivers, this may particularly apply to recently introduced signs. Finally, the analysis of correlation patterns between various cognitive skills and different TSC outcomes indicated that overall higher cognitive functioning was associated with better TSC performance in both groups, suggesting that cognitive abilities are important for TSC regardless of age. Given the cross-sectional study design, however, statements on the causality of effects are not possible. Moreover, the sample may not be representative of the general population due to the relatively small sample size. Since not all traffic signs used in this study are internationally established, the study findings can only be partially generalized. Further research should include larger samples of younger and older drivers to confirm the external validity and robustness of our findings. Regarding ecological validity, it may be more valid to examine how drivers deal with traffic signs in real traffic. In fact, it cannot be ruled out that some drivers make the right decision in real traffic, although they do not fully understand the meaning of a sign. Vice versa, however, correct decisions in real traffic appear to be more likely, if the actual meaning of a sign is understood. Moreover, future research should focus on additional factors that may facilitate and accelerate on-road TSC such as visual perception, contrast or illumination. Declaration of Conflict of Interest The Authors declare that they have no conflict of interest. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Acknowledgements We would like to thank all participants who took part in our study. References [1] M. Toepper, Dissociating normal aging from Alzheimer’s disease: a view from cognitive neuroscience, J. Alzheimers Dis. 57 (2017) 331–352. [2] M. Karthaus, M. Falkenstein, Functional changes and driving performance in older drivers, Geriatrics 1 (2016) 12. [3] P. Schulz, S. Spannhorst, T. Beblo, C. Thomas, S. Kreisel, M. Driessen, M. Toepper, Preliminary validation of a questionnaire covering risk factors for impaired driving skills in elderly patients, Geriatrics 1 (2016) 5. [4] S. Spannhorst, M. Toepper, P. Schulz, G. Wenzel, M. Driessen, S. Kreisel, Advice for elderly drivers in a german memory clinic, Geriatrics 1 (2016) 9. [5] K.K. Ball, D.L. Roenker, V.G. Wadley, J.D. Edwards, D.L. Roth, G. McGwin, R. Raleigh, J.J. Joyce, G.M. Cissell, T. Dube, Can high-risk older drivers be identified through performance-based measures in a Department of Motor Vehicles setting? J. Am. Geriatr. Soc. 54 (2006) 77–84. [6] J.L. Mathias, L.K. Lucas, Cognitive predictors of unsafe driving in older drivers: a meta-analysis, Int. Psychogeriatr. IPA 21 (2009) 637–653. [7] K.J. Anstey, J. Wood, Chronological age and age-related cognitive deficits are associated with an increase in multiple types of driving errors in late life, Neuropsychology 25 (2011) 613–621. [8] J.C. Stutts, R.J. Stewart, C. Martell, Cognitive test performance and crash risk in an older driver population, Accid. Anal. Prev. 30 (1998) 337–346. [9] A. Brashear, F.W. Unverzagt, E.R. Kuhn, B.S. Glazier, M.R. Farlow, A.J. Perkins, S.L. Hui, Impaired traffic sign recognition in drivers with dementia, Am. J. Alzheimers Dis. Other Dement. 13 (1998) 131–137.
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Please cite this article as: P. Schulz, K. Labudda, V. Bertke, et al., Age effects on traffic sign comprehension, IATSS Research, https://doi.org/10.1016/ j.iatssr.2019.10.001