Perceptual load and differences in distractibility

148 Word count: 2366 (all main text including the title and abstract) Address correspondence to: Nilli Lavie, Department of Psychology, University College London, Gower Street, London WC1E 6BT, UK Email: [email protected] Telephone: (44) 20 76795404 Fax: (44) 20 74364276 Perceptual load and differences in distractibility 3 Perceptual load has been found to be a powerful determinant of distractibility in laboratory tasks (Lavie, 2005). The present study assessed how perceptual load effects on distractibility in the laboratory relate to individual differences in the likelihood of distractibility in daily life. Sixty-one participants performed a response competition task in which perceptual load was varied. As expected, individuals reporting high (compared to low) levels of distractibility (on the “Cognitive Failures Questionnaire (CFQ): an established measure of distractibility in daily life) experienced greater distractor response-competition effects. Importantly, this relationship was confined to task-conditions of low perceptual load: high perceptual load reduced distractor interference for all participants, eliminating any individual differences. These findings suggest that the level of perceptual load in a task can predict whether individual differences in distractibility are found and that high load modifications of daily tasks may prove useful in preventing unwanted consequences of high distractibility. Perceptual load and differences in distractibility 4 High perceptual load makes everybody equal: Eliminating individual differences in distractibility with load The ability to ignore irrelevant distracting stimuli is of great relevance for everyday life as the effects of distraction on behavior can have a range of consequences, some detrimental, (e.g. during driving) and some simply detracting from the quality of life (e.g. during reading). It is therefore important to examine how attention theories that prescribe determinants of focused attention and conversely distractibility relate to people’s ability to ignore irrelevant distractors when focusing attention on relevant information in daily life. The load theory of attention suggests that a major determinant of focused attention and the ability to ignore irrelevant distractors is the level of perceptual load in a current task (e.g. Lavie, 1995; Lavie, Hirst, De Fockert & Viding, 2004). Although irrelevant distractors interfere with tasks of low perceptual load (e.g. involving just one relevant stimulus), such distractor interference is eliminated when the task performed involves higher perceptual load (e.g. involving six or more stimuli, see Lavie, 2005 for review). In order to examine how this theory relates to distractibility in everyday life we assessed how the effects of perceptual load on the individual magnitude of distraction in the laboratory relate to the extent to which each individual is likely to be distracted in daily life. The latter was measured with the Cognitive Failures Questionaire (CFQ, Broadbent, Cooper, Fitzgerald and Parkes, 1982): the most established measure for individual differences in distractibility in everyday life. Participants performed a typical perceptual load plus distractor task (e.g. Lavie, 1995; Lavie & Cox, 1997; Lavie & Fox, 2000) requiring them to search for one Perceptual load and differences in distractibility 5 of two target letters in displays of either low perceptual load (an angular target among circular place holders) or high perceptual load (angular target among five angular nontarget letters). An irrelevant peripheral distractor letter was also present on each display and participants tried their best to ignore it. The irrelevant distractor was either the same as the search-target in the display (compatible conditions) or the same as the other search-target (incompatible conditions). Distractor compatibility effects on target RTs indicate the extent to which people were distracted. The individual magnitude of distraction under conditions of low and high perceptual load was related to the individual CFQ scores. The CFQ requires the respondent to rate the frequency with which he/she experiences 25 common types of ‘cognitive failures’. For example: How often“Do you start doing one thing at home and get distracted into doing something else (unintentionally)? “ “Do you find you accidentally throw away the thing you want and keep what you meant to throw away – as in the example of throwing away the matchbox and putting the used match in your pocket? “ CFQ scores significantly correlate with ratings of the respondents by their spouses (Broadbent et al. 1982). Moreover, CFQ scores remain stable over time (Broadbent et al. 1982) and may even reflect a genetic predisposition, as the correlation of CFQ scores between monozygotic twin pairs is around 0.5, whereas this correlations drops to around 0.25 for dyzogitic twin pairs and 0.2 for parent-offspring pairs (Boomsma, 1998). Importantly high CFQ scores have been associated with increased frequency of car accidents (Larson & Merrit, 1991), injuries from falling (Larson, Alderton, Neideffer & Underhill, 1997), accidents at work among electrical workers (Wallace & Perceptual load and differences in distractibility 6 Vodanovich, 2003) and a clearly less detrimental failure but nonetheless one that detracts from quality of life: losing work when computing (Jones & Martin, 2003). These consequences of high distractibility suggest it is highly important to ask whether high perceptual load can prevent distraction for all people, even those that are highly distracted and are more likely to be involved in various accidents. We thus sought to establish that: Firstly, individual differences in the likelihood of daily-life distractibility relate to the individual magnitude of distraction in our laboratory task. Specifically, people that score high on the CFQ measure of daily-life distractibility were also expected to suffer from greater distractor effects in our task. Secondly, if high perceptual load can eliminate distraction for all, then, compared to those with low CFQ scores, individuals with high CFQ scores should show greater interference from the irrelevant distractor in conditions of low perceptual load but not in conditions of high perceptual load. Method Participants Sixty one volunteers (33 females) aged 19 to 38 years old (M = 25) from UCL subject pool participated in exchange for £4.Two participants ( one male) had 45% and 43% error rates in the high load condition and were therefore excluded from the analyses. Stimuli & Procedure Participants performed a perceptual load task closely based on Lavie & Cox (1997, Experiment 1, see also Lavie, 2005 for a stimulus figure). E-prime was used to present the stimuli on a 15 inch computer screen placed 60 cm away from the participants. Each trial started with a 500 ms presentation of a central fixation point immediately followed by a 100 ms presentation of the task display. The task display Perceptual load and differences in distractibility 7 consisted of a circle of six letters centered at fixation with a 1.6 o radius, plus a peripheral distractor letter, presented to the left or right of the circle, 1.4 o away from the nearest central circle letter. All the stimuli were presented in white on a black background. Each of the circle letters subtended 0.6 o by 0.4 o and the distractor letter subtended 0.8 o by 0.5 o . The search targets were X or N. Each letter-circle contained one target and the participants were instructed to indicate which of the target letters was present in the circle by pressing either the ‘0’ or the ‘2’ key on numerical pad of the computer as fast as possible while not sacrificing accuracy. The distractor letter was equally likely to be X or N and the participants were instructed to ignore the distractor. In the high load condition, the letters H, M, K, Z, W were placed randomly in the nontarget circle positions in a different order on each trial. In the low load condition the nontarget letters were all small Os (0.15 o ). Target position, distractor position and identity, and their combinations were counterbalanced. Following three slower example trials and twelve practice trials from each load condition, participants completed eight low load and high load blocks of 96 trials each in an ABBAABBA order. The Cognitive Failures Questionnaire (Broadbent et al., 1982) was then administered. Results Within-subject two-way ANOVAs of the correct RTs within 100 ms to 1500 ms and error rates showed significant effects for load (F (1, 58) = 224.988, p < .001, prep > .99, ηp 2 = .795 for RTs; F (1, 58) = 86.725, p < .001, prep > .99, ηp 2 = .599 for errors), distractor compatibility (F (1, 58) = 77.463, p < .001, prep > .99, ηp 2 = .572, for RTs; F (1, 58) = 45.228, p < .001, prep > .99, ηp 2 = .438, for errors) and their interaction, (F (1, 58) = 38.528, p < .001, prep > .99, ηp 2 = .399, for RTs; F (1, 58) = 11.610, p < .001, prep > .99, ηp 2 = .167, for errors.) As can be seen in Figure 1 this Perceptual load and differences in distractibility 8 interaction reflected that distractor compatibility effects were greater in the low load condition (for RTs, compatibility effect M = 28 ms, t (58) = -11.109, p < 0.001, prep > .99, d = -2.89; for errors compatibility effect M = 4.3%, t (58) = 7.417, p < 0.001, prep > .99, d = 1.95) than in the high load condition (for RTs, compatibility effect M = 6 ms, t (58) = -2.267, p = .027, prep = .91, d = -.60; for errors compatibility effect M = 1.7%, t (58) = 2.889, p =.005, prep =.97, d = .76 ). These findings provide a replication of the previous findings that perceptual load significantly reduces distractor effects (e.g. Lavie & Cox, 1997). Individual differences Participants were divided into high CFQ group versus low CFQ group with a median split of the CFQ scores (range = 19 82, median= 41, SD = 13.87) and a mixed model RT ANOVA with the between-subject factors of CFQ group and the within-subject factors of load and compatibility revealed no significant main effect of CFQ group (F (1, 57) = 2.414, p >.10, prep = .791, ηp 2 = .041) and no interaction between load and CFQ group (F < 1). These results indicate that the CFQ groups did not differ in their search performance or in the effects of load on search. Importantly, there was a significant interaction between distractor compatibility and CFQ group, F (1, 57) = 4.670, p <.05, prep = .90, ηp 2 = .076, indicating greater compatibility effects for the high CFQ group than the low CFQ group. Critically, this interaction was qualified by a three-way interaction between distractor compatibility, load and CFQ group, F (1, 57) = 4.831, p < .05, prep = .905, ηp 2 = .078. As predicted by the hypothesis that high perceptual load can eliminate distractibility for all people and as can be seen in Figure 2, distractor compatibility effects were greater for the high CFQ than the low CFQ group in the low load Perceptual load and differences in distractibility 9 condition (t (57) = -3.3, p < .01, prep .979, d = -.88), but not in the high load condition (t < 1). This result pattern was also characteristic of the correlations: CFQ score positively correlated with the magnitude of distractor compatibility effect under low perceptual load (Spearman rs = .22, p < .05, prep = .88, one-tailed), but not under high perceptual load (Spearman rs = .025, p >.4, prep = .55, one-tailed). The error results were not sensitive to reveal any effects or interactions with the CFQ groups (apart from a nonsignificant trend towards an interaction of CFQ and load, F (1, 57) = 3.1, p = .083, prep = .836, ηp 2 = .052, suggesting the increase in load to have generally been more detrimental to the accuracy of the high CFQ group than the low CFQ group, all p's > 0.1). General Discussion The present study establishes two important findings: Firstly, people who report being more distracted in every-day life also show greater distraction in our laboratory task: Irrelevant peripheral distractors produced a greater magnitude of response-competition effects for people with high (compared with low) scores on the CFQ measure of distractibility in daily life. This finding is important as the previous studies that assessed the relationship of CFQ and distractor effects in selective attention tasks (e.g. response-competition, Stroop-like, or negative priming tasks, Broadbent, Broadbent & Jones, 1986; Kramer et al, 1994; Martin, 1983; Tipper & Baylis, 1987; Vom Hofe, Mainemarre & Vannier, 1998; Bloem & Schmuck, 1999; Kane et al, 1994) have produced mixed results, have often used small samples, or mixed young and elderly populations and have not always precluded the possibility of eye movements in the task (see Larson & Perry, Perceptual load and differences in distractibility 1