Influence of Distraction on Task. Performance in Children and Adults

1 Influence of Distraction on Task Performance in Children and Adults Liza Timmermans S767534 Master thesis Augustus 2010 Faculty of Social and Behavioral Sciences Department of Developmental Psychology Tilburg University Begeleider: dr. O. van der Stelt Tweede beoordelaar: drs. W. Brinkmann

2 Abstract Previous studies found that children experience larger distractor effects on task performance than young adults, but only under conditions of low perceptual load. In this study the influence of distraction in children and adults in context of perceptual load theory of visual attention (Lavie, 1995) will be examined. Participants consisted of 16 adults (M = 21 years) and 9 children (M = 8 years) who completed three visual attention tasks differing in load. Each task was combined with two types of distraction. The results showed that distraction had a positive influence on the RTs of children and adults. On the other hand, distraction also increased the false alarm rates of both groups. Also, in contrast to perceptual load theory, a positive influence of distraction on hit rate was found in the high load task. It is concluded that both children and adults can experience negative as well as positive influence of distracting task irrelevant stimuli on task performance, depending on measures of performance and type of distraction. Keywords: Selective attention, distraction, development

3 Index Abstract 2 Index 3 Introduction 4 Attention 4 Development of selective attention 6 Present study 7 Method 8 Participants 8 Procedure 9 Data processing 11 Statistical analyses 11 Results 12 Reaction time 13 Hit rate 14 False alarm rate 15 Discussion 17 References 20

4 Introduction William James was one of the first psychologists who saw psychology as the study of mental activity (functionalism). Functionalists were interested in the functions of mental processes including, perception, memory, attention, and, consciousness. In his textbook, The Principles of Psychology, James (1890) described attention as follows Everyone knows what attention is. It is the taking possession by the mind, in clear and vivid form, of one out of what seem several simultaneously possible objects or trains of thought. Later, when functionalism was declined by behaviorism (in behaviorism the idea of studying internal mental processes is rejected), attention was no longer a main topic in psychology. In the nineteen fifties and sixties cognitive psychology emerged and attention became relevant again and has been a widely studied topic ever since. Attention is a cognitive function that refers to the ability to actively process specific stimuli. Selective attention is the generic term for those mechanisms which lead our experience to be dominated by one thing rather than another (Driver, 2001 p. 53). Selective attention is important for many other cognitive functions such as perception and memory. Attention is considered one of the basic abilities that is required to succeed in school (Huang-Pollock, Carr, & Nigg, 2002). Similarly, a deficit in attention is a hallmark symptom in multiple neurological and psychiatric disorders, such as attentiondeficit hyperactivity disorder (ADHD). More insight in these disorders is obtained by studying attention. Thus, the study of attention is important for theoretical as well as clinical reasons. Attention Traditionally there are two theories about selective attention: early selection theory and late selection theory. Broadbent s (1958) filter theory, which is a classical example of the early selection theory, states that there are two stages of perceptual processing. In the first stage physical features (such as color and orientation) are extracted for all incoming stimuli and in the second stage more complex features are extracted. This second stage is limited in capacity and a selective filter protects this stage from overload by only passing trough stimuli with a specific physical feature (Broadbent,

5 1958; Driver, 2001; Huang-Pollock et al., 2002). Thus, unattended stimuli are only processed as far as physical features and are temporarily stored in immediate memory, whereas attended stimuli are also processed at a semantic level and can be stored in the long term memory or can be used to react appropriately to the stimuli (Lachter, Foster, & Ruthruff, 2004). Important evidence for this theory comes from selective shadowing tasks that are used in many classical experiments. In such a task participants have to listen to two spoken messages at the same time and repeat (shadow) one, it appears that participants know very little about the non-shadowed message (Driver, 2001). On the other hand, the late selection theory states that all incoming stimuli receive automatic full perception and selection only occurs after semantic processing. Unattended stimuli are thus fully processed and limitations arise only at the levels of decision making and response selection (Deutsch & Deutsch, 1963; Driver, 2001). An important evidence for this theory is the so called own name effect which is found in dichotic listening tasks where the subject s name draws attention even if presented in the unattended ear (Driver, 2001). More recent theories on attention combine aspects of early selection theory and late selection theory. Lavie s (1995) perceptual load theory is the most important one. This theory states that perception is a limited process (as in early selection) and that perception is an automatic process (as in late selection). Whether selection is early or late depends on perceptual load. The concept of perceptual load implies not just increased difficulty but rather additional demands on (cognitive) systems and their capacity (Lavie, 1995). Lavie (1995) constructed an experiment to examine perceptual load theory. In this experiment participants had to respond to the identity of the target letter, x or z, that appeared in the central region of the screen. Far from the target letter, below or above the center, a compatible, incompatible or neutral distracter letter appeared. It is known that task irrelevant distracter stimuli shown simultaneously with or just before the task relevant stimuli interfere with the processing of the task relevant stimuli (Wetzel & Schröger, 2007). These distracter stimuli have multiple effects on performance, such as longer reaction times and more errors. The manipulation of load in Lavie s (1995) experiment appeared in the central region; in the low load condition only the target letter was shown in one of six positions and in the high load condition the other five positions

6 were occupied by neutral non target letters. The results showed that if perceptual load is low, there is perceptual capacity left and the distracter stimuli can be processed. In this case selection is late. If perceptual load is high, perceptual capacity may be exhausted and therefore less distracter stimuli will be processed and perceptual selection is early (Lavie, 1995; Lavie, 2005; Driver, 2001). Development of Selective Attention Research suggests that attention, like many other cognitive functions, involves developmental change. In their review, Plude, Enns, and Brodeur (1994) conclude that the development of attention is a complex pattern of growth and development rather than a single linear progression. From childhood till adulthood some aspects of attention will change significantly. Filtering and visual search, for example, change over the life span while other aspects (like orienting) will stay remarkably stable (Plude et al., 1994). The control over the processing of distracting stimuli is not completely mature in childhood, suggesting that children are more susceptible to distracting stimuli compared to young adults. For instance, when distraction is present the RTs of children were more prolonged than the RTs of adults (Wetzel, Widmann, Schröger; 2009). Furthermore, there are strong age-related improvements in the ability to focus on the central task and to ignore distracter stimuli (Plude et al., 1994; Tipper, Bourque, Anderson, & Brehaut, 1989). Maylor and Lavie (1998) applied the perceptual load theory to development and compared two groups, young adults (mean age 22.7) and older adults (mean age 73.0). Participants had to detect a target letter and ignore the incompatible or neutral distracter letter. In this study there were four conditions of load, either none, one, three, or five non target letters were displayed simultaneously with the target letter. The more letters appeared, the higher the load of the task. The results showed that compared to the young adults, older adults experienced a larger distracter effect, but only under conditions of low perceptual load. The distracter effect was reduced by set size four in the case of the older adults and by set size six for the younger adults. Huang-Pollock et al. (2002) also tested the perceptual load theory in combination with development. Children and young adults were tested using a task obtained from Maylor and Lavie (1998). The results showed that children as well as adults experienced

7 smaller interference effects from display load four to display load six. More specifically, children experienced large distracter effects from an incompatible distracter letter at low loads and for high loads these distracter effects were considerably smaller, and the resistance to distracter letters approached adult levels (Huang-Pollock et al., 2002). The same results of developmental change in selective attention are thus found in comparing young adults and older adults and children and young adults, indicating that the general developmental principle which states that effortful cognitive processes that consolidate later in life are more likely to regress in adulthood, pertains to selective attention (Huang-Pollock et al., 2002; Maylor & Lavie, 1998; Madden & Langley, 2003). Present Study In the present study the performance of children and adults will be compared in order to study the development of selective attention. Specifically, this study aims at clarifying whether children are more susceptible to distracting stimulus information than adults, and to determine whether these effects are most evident when the perceptual load of the task is low. Three discrimination reaction time tasks (go no go) that require attention will be completed by every participant. First, a color discrimination reaction time task in which participants have to respond only when the target stimulus has a specific color (red or green). Second, a category discrimination reaction time task in which participants have to respond only if the target stimulus belongs to a specific category (digits or letters). Finally, a conjunction of the two previous tasks in which participants have to respond to for example, green digits or red letters. These tasks have different loads, the color discrimination task has a low perceptual load and the other two tasks have at least higher loads. In this study the tasks will be combined with two types of task irrelevant distracting stimuli, first distracters in space, which will appear simultaneously with the task relevant stimulus. This type of distracter is used in multiple other studies for example Lavie (1995), Maylor and Lavie (1998), and Huang-Pollock et al. (2002). The second type of distracters is distracters in time, which will shortly appear just before the task relevant stimulus. This type of visual distracter has not been used in previous studies, but auditory stimuli played before the task relevant stimulus have been used. However,

8 these auditory stimuli showed opposing effects on task performance (SanMiguel, Linden, Escera, 2010). First, it is reported that an unexpected auditory stimulus (novelty) before the task relevant stimuli can be distracting, resulting in longer RTs and a lower hit rate (Parmentier, 2008; Parmentier, Elsley, & Ljungberg, 2010). On the other hand, it is reported that an auditory stimulus before the task relevant stimulus facilitates RT (Hackley & Valle-Inclán, 2003; Bertelson & Tisseyre, 1969; SanMiguel et al., 2010). In the present study the following hypotheses will be tested: H1: The distraction effect, of distraction in space as well as distraction in time, will be higher for children than for adults. H2: In line with Lavie s perceptual load theory, for both groups the distracter effect will be higher in the low load task compared to the high load tasks. Method Participants Participants consisted of 9 schoolchildren aged between 7.7 and 9.3 (M = 8.23 years, SD = 0.46; 6 girls and 3 boys), and 16 young adults aged between 18.6 and 27.2 (M = 21.06 years, SD = 2.06; 12 females and 4 males). The children were recruited from a local elementary school, after gaining written approval from the principal as well as from the children s parents. The young adults were undergraduate university students who received course credits in return for their participation. Written informed consent was obtained from the adult participants. Inclusion criteria required that participants were free of medical and substance abuse problems, had normal or corrected-to-normal vision, had no color-blindness, and had never used drugs, as assessed with behavior and health questionnaires and checklists by self-report (adults) or parental report (children). To exclude individuals with low intellectual abilities that may affect task performance, all participants had to score at least average on the Standard Progressive Matrices (Raven, Court, & Raven, 1992), a test of abstract reasoning associated with general intelligence.

9 Procedure All participants were tested individually and all followed the same procedure. The experiment, which lasted approximately 30 minutes, was presented on a laptop using E-prime 1.2 software. Each participant was seated in front of the computer screen with his or her right index finger on the right mouse button. Stimuli consisted of two sets alphanumeric characters (L, H, E, P and 7, 9, 3, 8), one set in the color red and the other in green. The distracters were black and white pictures of daily objects, persons, or animals, which are used in many other researches, obtained from Snodgrass and Vanderwart (1980). The stimuli and distracters were used in three different visual selection tasks (adapted from van der Stelt, Lieberman, & Belger, 2006). The tasks were all discrimination reaction time tasks with a difference in target defining properties. The tasks differ in perceptual load, the color discrimination task has a low perceptual load and the conjunction and category task have at least higher perceptual loads. In the color task participants had to make a discrimination based on color. This is a simple, easily distinguishable sensory dimension and probably involves early selection. In the category discrimination task the discrimination is based on category. This is a more complex, abstract (semantic) dimension and probably involves late selection. In the conjunction discrimination task the target stimuli were a conjunction of color and category and participants had to respond to, for example, green digits or red letters. The task relevant stimuli (target and non target) were presented successively in the middle of the screen against a white background for 200 ms. Target stimuli required a button press response and non target stimuli did not require any response. Each task involved a random mixture of infrequent (33%) target stimuli and frequent (66%) non target stimuli. The specific sensory cue (red or green) and the semantic cue (letter or digit) defining the target stimuli were counterbalanced across participants in each group. In these three tasks two types of distraction were presented. The presented task relevant stimuli were either preceded by four simultaneously presented task irrelevant distracter stimuli or by four simultaneously presented white squares (see Figure 1). This was a manipulation of distraction in time. Also, together with the task relevant stimuli either four task irrelevant distracter stimuli or four white squares were presented (see Figure 2). This was a manipulation of distraction in space. Thus, each trail started with a

10 fixation cross in the center of the screen for 600 ms. This was replaced by the display of distraction in time for 750 ms. Then this was replaced by the stimulus itself, with or without distraction in space, for 200 ms. In all three tasks, participants first received a practice trail of 20 stimuli before completing the actual experiment of 144 stimuli. Figure 1. Manipulation of distraction in time: Four task irrelevant distracter stimuli versus four white squares, presented briefly before (750 ms) the task relevant stimuli. Figure 2. Manipulation of distraction in space: Four task irrelevant distracter stimuli versus four with squares, presented simultaneously with the task relevant stimulus (in this example: E).

11 Data Processing The reaction times and two other performance measures, as described below, were subscribed to an E-DataAid file. Only correctly responded target stimuli with a reaction time longer than 200 ms and shorter than 1200 ms were accepted as valid responses and were used in further analyses. Performance measures consisted of three indices. First, the reaction time that is defined as the time between target onset and button press response. Second, the hit rate defined as the proportion of correct responses to target stimuli in relation to the total number of target stimuli presented. Third, the false-alarm rate that is defined as the proportion of incorrect responses to non target stimuli in relation to the total number of non target stimuli presented. Statistical Analyses All statistical analyses will be performed with PASW Statistics 17. This study is a mixed 3 (task: color, category, conjunction) x 2 (distraction in time [DT]: present or absent) x 2 (distraction in space [DS]: present or absent) x 2 (age group: children and adults) factorial design with one between subjects factor (age group) and three within subjects factors (task, distraction in time, distraction in space). A repeated-measures multivariate analysis of variance (MANOVA) will be executed on this design. Follow-up tests will be executed to locate significant interaction effects. The influence of sex on RT, hit rate, and false alarm rate was tested, but this variable was not significant in any way. Data values in the text represent means and an alpha level of.05 was used for all statistical analyses.

12 Results The mean performance data of children and adults are given in Table 1. This table shows that over all three tasks, with or without distracter stimuli, children have longer mean reaction times (522 ms), have lower mean hit rates (76.7%) and higher mean false alarm rates (13.6%), compared to the adults. Adults perform the best in all three tasks, with or without distracter stimuli, with a mean reaction time of 418 ms, 97.2% hit rate and 4.0% false alarm rate. Table 1. Performance data for children (n = 9) and adults (n = 16) Reaction time (ms) Hit rate (%) False-alarm rate (%) Task Distraction Children Adults Children Adults Children Adults Color Discrimination Category Discrimination Conjunction Discrimination Two distracters 449 (34) Distraction Time 449 (34) Distraction 478 Space (46) No distracters 468 (41) Two distracters 575 (79) Distraction Time 542 (50) Distraction 555 Space (71) No distracters 552 (42) Two distracters 544 (59) Distraction Time 532 (57) Distraction 560 Space (47) No distracters 554 (41) 367 (45) 360 (43) 351 (44) 364 (53) 455 (53) 452 (48) 443 (52) 450 (52) 441 (56) 451 (51) 432 (53) 445 (64) 96.5 92.0 96.9 93.5 66.7 (0.2) 69.7 (0.2) 68.7 (0.2) 57.5 70.1 69.6 (0.2) 70.7 (0.2) 68.3 (0.2) 98.0 99.0 97.6 99.0 97.8 96.5 96.4 94.4 95.8 96.4 97.1 97.7 1.9 2.6 4.0 2.8 27.4 (0.2) 24.7 (0.2) 27.3 (0.2) 21.4 (0.2) 11.0 13.8 14.1 12.1 1.0 0.0 1.0 0.0 6.4 7.0 6.8 5.5 8.1 3.3 4.8 4.2 Note. Data given represent means and SD (parenthesis).

13 Preliminary assumption testing, separately for all three performance indices, was conducted to check for normality, linearity, univariate and multivariate outliers, homogeneity of variance-covariance matrices, and multicollinearity. Two participants from the original data set were removed because they were detected as both univariate and multivariate outliers. Reaction Time The four way MANOVA (3 Task x 2 DT x 2 DS x 2 Group) produced a significant main effect for group, F(1, 23) = 37.0, p <.001, η p ² =.616, reflecting that children had a longer RTs than adults (522 ms vs. 418 ms), averaged across task, DT, and DS. There was also a significant main effect for task, Wilks Lambda =.082, F(2, 22) = 123.0, p <.001, η p ² =.918, reflecting a difference between task conditions (color = 397 ms, conjunction = 480 ms, category = 488 ms), averaged across DT, DS, and group. Follow up tests involving paired samples t-tests showed that the RT in the color task significantly differed from the conjunction task, t(24) = 12.2, p <.001, and from the category task, t (24) = 13.0, p <.001, which did not significantly differ from each other, t(24) = 0.9, p =.400. The three way and four way interactions were not significant but the two way interaction between group and DS was significant, Wilks Lambda =.833, F(1, 23) = 4.6, p =.042, η p ² =.167. Follow up analyses were performed to test the effect of DS separately for each group, when DT was absent. The effect of DS was significant for adults, Wilks Lambda =.721, F(1, 15) = 6.1, p =.026, η p ² =.288, but not for children, Wilks Lambda =.951, F(1, 8) = 0.4, p =.539, η p ² =.049. This indicates that there is an effect of DS for adults (DS present = 409 ms vs. DS absent = 420 ms). Inspection of the means show that the RT of adults was shorter when DS was present compared to DS absent. In other words, adults performed better when DS was present. To further explore the interaction between group and DS, follow up tests were performed to test the effect of group for both levels of DS, when DT was absent. The effect of group was significant for DS present, F(1, 23) = 40.0, p <.001, η p ² =.635, as well as DS absent, F(1, 23) = 34.2, p <.001, η p ² =.598. Children displayed longer RTs than adults when DS was present (531 ms vs. 409 ms) as well as when DS was absent

14 (525 ms vs. 420 ms). Inspection of these means show that the RTs of children and adults differ when DS was present and when DS was absent, however the differences between children and adults were smaller when DS was absent. The overall MANOVA also produced a significant two way interaction between group and DT, Wilks Lambda =.700, F(1, 23) = 9.9, p =.005, η p ² =.300. Follow up analyses were performed to test the effect of group for both levels of DT, when DS was absent. The effect of group was significant for DT present, F(1, 23) = 27.9, p <.001, η p ² =.548, as well as DT absent, F(1, 23) = 34.2, p <.001, η p ² =.598. Children displayed longer RTs than adults when DT was present (508 ms vs. 421 ms) as well as when DT was absent (525 ms vs. 420 ms). Inspection of these means show that the RTs of children and adults differ when DT was present and when DT was absent, however the differences between children and adults were smaller when DT was present. Hit Rate The four way MANOVA (3 Task x 2 DT x 2 DS x 2 Group) produced a significant main effect for group, F(1, 23) = 67.9, p <.001, η p ² =.747, reflecting that children had lower hit rates than adults (76.7% vs. 97.2%), averaged across task, DT, and DS. There was also a significant main effect for task, Wilks Lambda =.186, F(2, 22) = 48.1, p <.001, η p ² =.814, reflecting a difference between task conditions (color = 97.1%, conjunction = 87.0%, category = 85.3%), averaged across DT, DS, and group. Follow up tests involving paired sample t-tests showed that the hit rate in the color task significantly differed from the conjunction task, t(24) = 3.4, p =.002, and from the category task, t(24) = 3.8, p =.001, which did not significantly differ from each other, t(24) = 0.8, p =.457. The four way interaction was not significant but the three way interaction between group, DS, and DT was significant, Wilks Lambda =.787, F(1, 23) = 6.2, p =.020, η p ² =.213. Follow up analyses were performed to test the interaction between group and DS for each level of DT. When DT was present the interaction between group and DS was not significant, Wilks Lambda =.993, F(1, 23) =.2, p =.695, η p ² =.007. When DT was absent the interaction between group and DS was significant, Wilks Lambda =.797, F(1, 23) = 5.9, p =.024, η p ² =.203.

15 To locate the interaction between group and DS, when DT was absent, the effect of group was tested for both levels of DS. The independent-samples t-tests showed that when DS was present there was a significant group effect, t(9) = 5.6, p <.001, reflecting that children had a lower hit rate compared to adults (78.7% vs. 97.1%). When DS was absent there was also a significant group effect, t(9) = 5.8, p <.001, reflecting that children had a lower hit rate compared to adults (73.1% vs. 97.1%). Inspection of these means show that the hit rates of children and adults differ when DS was present and when DS was absent, however the difference between children and adults was smaller when DS was present. The overall MANOVA also produced a significant three way interaction between task, DS, and DT, Wilks Lambda =.721, F(2, 22) = 4.3, p =.027, η p ² =.279. Follow up analyses were performed to test the interaction between DS and DT separately for each task. The interaction between DS and DT was not significant in the color task, Wilks Lambda =.990, F(1, 24) = 0.2, p =.634, η p ² =.010, nor in the conjunction task, Wilks Lambda =.997, F(1, 24) = 0.1, p =.785, η p ² =.003, but was significant in the category task, Wilks Lambda =.818, F(1, 24) = 5.3, p =.030, η p ² =.182. Multiple paired samples t-tests were executed to locate the interaction between DS and DT in the category task. When DT was present the effect of DS was not significant, t(24) = 0.2, p =.860. When DT was absent the effect of DS was significant, t(24) = 2.2, p =.034, reflecting a higher hit rate when DS was present compared to DS absent (86.4% vs. 81.1%). When DS was present the effect of DT was not significant, t(24) = 0.1, p =.904. When DS was absent the effect of DT was significant, t(24) = 2.2, p =.041, reflecting a higher hit rate when DT was present compared to DT absent (86.9% vs. 81.1%). Inspection of these means show that in the category task when only one type of distraction was present, DT or DS, the participants had a higher hit rate. False Alarm Rate The four way MANOVA (3 Task x 2 DT x 2 DS x 2 Group) produced a significant main effect for group, F(1, 23) = 18.4, p <.001, η p ² =.445, reflecting that children had a higher false alarm rate than adults (13.6% vs. 4.0%), averaged across task, DT, and DS. There was also a significant main effect for task, Wilks Lambda =.295, F(2,

16 22) = 26.3, p <.001, η p ² =.705, reflecting a difference between task conditions (color = 1.3%, conjunction = 7.8%, category 13.2%), averaged across DT, DS, and group. Follow up tests involving paired sample t-tests showed that the false alarm rate in the color task significantly differed from the conjunction task, t(24) = 6.2, p <.001, and from the category task, t(24) = 4.2, p <.001, the conjunction and the category task also differed significantly from each other, t(24) = 2.6, p =.015. There was also a significant main effect for DS, Wilks Lambda =.822, F(1, 23) = 5.0, p =.036, η p ² =.178, reflecting a higher false alarm rate when DS was present compared to DS absent (8.1% vs. 6.8%), averaged across task, group, and DT. The three way and four way interactions were not significant but the two way interaction between group and task was significant, Wilks Lambda =.678, F(2, 22) = 5.2, p =.014, η p ² =.322. Follow up independent-samples t-tests were performed to test the effect of group for the three tasks, when DT and DS were absent. In the color task children had significant higher false alarm rates than adults (2.8% vs. 0.3%), t (9) = 3.70 p =.005, however, the differences in false alarm rates between children and adults were larger in the conjunction (12.1% vs. 4.2%), t(23) = 4.0, p =.001, and category task (21.4% vs. 5.5%), t(23) = 3.6, p =.002. Inspection of these means show that the false alarm rates of children and adults differ in every task, but in the category task the difference is the largest.

17 Discussion This study examined the performance of children and adults in multiple RT tasks. We tested whether children are more influenced by distracting stimuli compared to adults and whether the distraction effect is larger in the low load task compared to the high load task. Overall, children had significant longer RTs, lower hit rates, and higher false alarm rates compared to adults. These results are inline with previous studies on differences in task performance between children and adults (Kail, 1991; Huang-Pollock et al., 2002; van der Stelt, 2009). The first hypothesis that was tested was that the distraction effect, of distraction in space as well as distraction in time, would impair task performance mainly in children. The results showed that, when DS was absent, children had a lower RT when DT was present compared to DT absent, and adults did not. Thus, children experienced a positive influence of DT on RT. This type of distraction appeared just before the target stimulus and might have had the same positive influence as an unspecific warning, alerting signal, which has been long known to facilitate RT (Bertelson & Tisseyre, 1969; Hackley & Valle-Inclán, 2003). Opposed to the results found in relation to DT, adults had a lower RT when DS was present compared to DS absent, and children did not. Thus, only adults experienced a positive influence from DS on RT. In the hit rate analysis a significant three way interaction between group, DS, and DT was found. This interaction indicated that (when DT was absent) children had a higher hit rate when DS was present compared to DS absent, and adults did not. Thus, children experienced a positive influence from DS on hit rate. On the other hand, when DS was present adults as well as children had a higher false alarm rate compared to DS absent. For adults, the combination of a shorter RT and a higher false alarm rate when DS was present compared to DS absent implies a different response strategy when DS was present. The same goes for children, the combination of a higher hit rate and a higher false alarm rate when DS was present compared to DS absent implies a different response strategy when DS was present. For both groups DS elicits a more liberal response strategy resulting in more responses when DS was present compared to DS absent. Thus,

18 in both groups DS elicited no processing efficiency but rather a difference in task strategy. Taken all together, hypothesis I that the distraction effect, of distraction in space as well as distraction in time, will be higher for children than for adults can not be confirmed. Though children experienced a positive influence of DT, children and adults experienced influence of DS and, more importantly, we expected that the distracters would have a negative influence on performance and we found that the distracters mainly had a positive influence on performance. The second hypothesis tested, based on Lavie s (1995) perceptual load theory, was that for both groups the distracter effect will be higher in the low load task compared to the high load tasks. Overall, the RTs in the color task were shorter, the hit rates were higher and the false alarm rates were lower compared to the conjunction and category task, indicating that the color task has a lower perceptual load compared to the conjunction and category task. However, no significant interaction effects with task and distraction were found when analyzing RTs. Thus, based on these data the hypothesis can not be confirmed. On the other hand when analyzing the hit rates, a significant three way interaction between task, DS, and DT was found. This interaction indicated that in the category task (high load task) participants had a higher hit rate when one type of distraction, DS or DT, was present. However, according to perceptual load theory (Lavie, 1995), in high load tasks the influence of distracting stimuli should be smaller compared to low load tasks. This study found that distraction did have a (positive) influence in the high load task but not in the low load task. Thus these results also do not confirm the hypothesis that for both groups the distracter effect would be higher in the low load task compared to the high load task. The current finding that perceptual load theory is not confirmed is in contrast with multiple studies that did confirm perceptual load theory (Lavie, 1995; Maylor & Lavie, 1998; Huang-Pollock, 2002). The most important difference is that the tasks used in those studies typically were choice RT tasks. In those tasks the presented target stimulus needed the opposite motor response than the presented distracter stimulus. Thus, the distracter stimuli interfered with the stimulus response (S-R) translation (Ridderinkhof,

19 van der Molen, Band, & Bashore, 1997) whereas the distracters in our study did not affect the S-R translation. In sum, it seems like only children experience positive influence of DT on RT, whereas children and adults experience (positive and negative) influences of DS on task performance. Overall, it can be concluded that the influence of distraction on task performance is different for children and adults and is a function of type of distraction and measures of performance. Most importantly, this study showed that distraction can have a positive influence on task performance. In future studies this should be taken into account and it can no longer be presumed that distraction only has a negative influence on task performance. Furthermore, basic knowledge about the development of selective attention and the influence of distraction gains more insight in disorders in which a deficit in attention is a major symptom.

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