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Aging, Neuropsychology, and Cognition: A Journal on Normal and Dysfunctional Development Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/nanc20

Prospective memory in young and older adults: The effects of task importance and ongoing task load a

Rebekah E. Smith & R. Reed Hunt

a

a

Department of Psychology, The University of Texas at San Antonio, San Antonio, TX, USA Published online: 15 Aug 2013.

To cite this article: Rebekah E. Smith & R. Reed Hunt (2014) Prospective memory in young and older adults: The effects of task importance and ongoing task load, Aging, Neuropsychology, and Cognition: A Journal on Normal and Dysfunctional Development, 21:4, 411-431, DOI: 10.1080/13825585.2013.827150 To link to this article: http://dx.doi.org/10.1080/13825585.2013.827150

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Aging, Neuropsychology, and Cognition, 2014 Vol. 21, No. 4, 411–431, http://dx.doi.org/10.1080/13825585.2013.827150

Prospective memory in young and older adults: The effects of task importance and ongoing task load Rebekah E. Smith and R. Reed Hunt Department of Psychology, The University of Texas at San Antonio, San Antonio, TX, USA

ABSTRACT Remembering to perform an action in the future, called prospective memory, often shows age-related differences in favor of young adults when tested in the laboratory. Recently Smith, Horn, and Bayen (2012; Aging, Neuropsychology, and Cognition, 19, 495) embedded a PM task in an ongoing color-matching task and manipulated the difficulty of the ongoing task by varying the number of colors on each trial of the task. Smith et al. found that age-related differences in PM performance (lower PM performance for older adults relative to young adults) persisted even when older adults could perform the ongoing task as well or better than the young adults. The current study investigates a possible explanation for the pattern of results reported by Smith et al. by including a manipulation of task emphasis: for half of the participants the prospective memory task was emphasize, while for the other half the ongoing color-matching task was emphasized. Older adults performed a 4-color version of the ongoing color-matching task, while young adults completed either the 4-color or a more difficult 6-color version of the ongoing task. Older adults failed to perform as well as the young adults on the prospective memory task regardless of task emphasis, even when older adults were performing as well or better than the young adults on the ongoing color-matching task. The current results indicate that the lack of an effect of ongoing task load on prospective memory task performance is not due to a perception that one or the other task is more important than the other. Keywords: Prospective memory; Resources; Cost; Importance; Multinomial modeling.

The research was supported in part by Grant AG034965 from the National Institute on Aging. We thank Marisa Aragon, Andrew Bolisay, Ross DeForrest, Kathryn Dunlap, Immanuel Khachatryan, Sheila Meldrum, Amy Murray, Brittany Murray, Eric Olguin, Laura Randol, and Joe Tidwell for assistance with participant recruitment and data collection. This research was presented at the 2012 Cognitive Aging Conference in Atlanta, Georgia. Address correspondence to: Rebekah E. Smith, Department of Psychology, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA. E-mail: [email protected] © 2013 Taylor & Francis

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412 REBEKAH E. SMITH AND R. REED HUNT Prospective memory (PM) involves remembering to perform an action when the intended action cannot be carried out immediately, but instead must be performed at some point in the future. Remembering to take medication when you eat your breakfast, remembering to give your spouse a message when you return home, or remembering to pick up dry cleaning on the way home are examples of PM tasks and illustrate the importance of this type of memory in our everyday lives for both our health and for our social interactions. Importantly for our purposes, laboratory studies have found age-related differences across a variety of PM task demands (Kliegel, Jäger, & Phillips, 2008; see also Henry, MacLeod, Phillips, & Crawford, 2004). Prior studies have also found that the importance of the PM task plays an important role in PM performance (e.g., Smith & Bayen, 2004). The current experiment investigated how the importance of the PM task affects PM performance in young and older adults. As in prior research, we manipulated the importance of the PM task relative to the importance of the ongoing task. Because PM tasks outside the laboratory occur in the midst of other activities, laboratory based studies of PM typically embed the PM task in an ongoing task. For instance, participants may be asked to make a PM response when they see a particular word during an ongoing lexical decision task (Smith, 2003). Prior research has shown that instructions that emphasized the importance of either the PM task or the importance of the ongoing task can affect PM performance, with better PM performance when the PM task is emphasized (e.g., Smith & Bayen, 2004). The current experiment investigates the effects of task emphasis in young and older adults when the demands of the ongoing task are such that the older adults perform as well or better as the young adults on the ongoing task. This study was designed to investigate three issues. First, will older adults show differences in PM performance as a function of instructions that either emphasize the importance of the ongoing task or the importance of the PM task? Prior work has shown effects of task importance for both young (e.g., Kliegel, Martin, McDaniel, & Einstein, 2004; Smith & Bayen, 2004; but see also Kliegal, Martin, McDaniel, & Einstein, 2001) and older adults (Aberle, Rendell, Rose, McDaniel, & Kliegel, 2010; Ihle, Schnitzsphan, Rendell, Luong, & Kliegel, 2012; Schnitzspahn, Ihle, Henry, Rendell, & Kliegel, 2011). However, prior studies with older adults have largely focused on naturalistic tasks, diary studies, or time-based tasks. Timebased tasks are PM tasks that are to be performed at a particular clock time or after a set amount of time has elapsed (e.g., take medication at 2:00 or after 30 minutes has passed). Event-based tasks, such as that used in the current experiment, are to be performed when a particular event occurs in the environment (e.g., respond to a target word or stop when you see the post office).

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We are aware of just one prior laboratory study of the effects of task emphasis on event-based PM comparing young and older adults (Kliegel, Martin, & Moor, 2003; but see for instance, Altgassen, Zöllig, Kopp, Mackinlay, & Kliegel, 2007 for a laboratory study of the effects of importance on event-based PM that included older adults, but that did not examine age-related differences, and see Nied´zwie´nska & Barzykowski, 2012, for a study comparing social importance instructions with standard PM instructions). Kliegel et al. (2003) found no benefit of task emphasis for either their young or older participants. While ceiling effects limited interpretation of the results with young adults, older adults performed below ceiling, but, as noted by Kliegel et al. (2003), their study had limited power (there were just 12 participants in a cell) and their manipulation (essentially a hint of the importance of task switching) was relatively weak. Thus, while the findings from the previous non-laboratory studies and the study using a laboratory time-based task noted above indicate that older adults will benefit from a clear emphasis of importance, the current study will contribute important new information regarding the effects of task importance on both the event-based PM task and the ongoing task for both young and older adults. The second issue concerns the effects of task importance on the relative size of any age-related difference. In particular, we investigated age-related differences in the two importance conditions when older adults were performing as well or better than the young adults on the ongoing task. Specifically, we addressed the following question: When young and older adults have similar performance on the ongoing task, will the age-related difference in PM performance be similar in the CMI and PMI conditions, or will emphasizing the PM task reduce the age-related difference? In their recent study of time-based PM, both in the laboratory and using naturalistic tasks, Schnitzsphan et al. (2011) suggest that age-related limitations in cognitive function have a negative impact on performance to a greater extent in laboratory PM tasks than in naturalistic PM tasks because older adults may have reduced daily stressors outside of the laboratory, which in turn effectively serves to reduce the demands of the “ongoing task” of everyday life, and allows for motivation to play a greater role in older adults performance resulting in an age-benefit in the naturalistic task. In contrast, laboratory studies may be more demanding for older adults and this may prevent the older adults from benefiting from any greater level of motivation. The current experiment examines the effects of external motivation, in the form of task importance instructions, on event-based PM performance when young and older adults are matched with respect to ongoing task performance. In order to match young and older adults on ongoing task performance, we manipulated ongoing task load for young adults following methods used

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414 REBEKAH E. SMITH AND R. REED HUNT by Smith et al. (2012).1 The ongoing task used by Smith et al. (2012) was a color-matching task. On each color-matching trial, participants viewed rectangles, each in a different color, displayed one at a time for a brief duration in the center of a screen. The final rectangle was followed by a word and the participant’s task was to decide if the color in which the word was displayed matched any of the colored rectangles shown on that trial. As in Smith et al., we varied the difficulty of the ongoing task by manipulating the number of rectangles shown on each trial. Half of our younger participants completed the harder ongoing task condition with six rectangles on each trial, each a different color, shown for 300 ms each, while the other half of the young adults completed the easier version of the ongoing task with four different colors shown for 500 ms each. The latter condition with four colors also served as the ongoing task for the older adults.2 These conditions (Older 4-color, Young 6-color, and Young 4-color) were combined orthogonally with task emphasis (CMI and PMI). Finally, our design allows us to investigate one possible explanation for findings reported recently by Smith, Horn, and Bayen (2012). In the Smith et al. study, age-related differences in PM performance in favor of young adults persisted despite the fact that older adults out-performed the young adults on the ongoing task. Smith et al. noted, but did not empirically evaluate, the following explanation for their findings. It is possible that the manipulation of ongoing task load did not affect PM performance in Smith et al.’s study because the demands of the color-matching task, regardless of load, are such that participants, particularly older adults will not or cannot adjust the manner in which they allocate resources to the ongoing and PM tasks. Specifically, because the ongoing task requires maintaining information in working memory, participants may be disinclined to shift that information out of working memory in order to free up resources for processing required by the PM task. Smith and Bayen (2004) asked young participants to perform a PM task embedded in an ongoing color-matching task and manipulated the importance 1

2

We used the color-matching ongoing task with words as the PM target events in order to match the procedures in Smith et al. (2012). Furthermore, this non-focal task was used by Smith et al., and we continued to do so in the current study, because the goal of both studies is to investigate the nature of age-related differences when these differences do emerge, thus it is appropriate to select a task in which age-related differences are more likely to occur. Finally, many real world prospective memory tasks are non-focal tasks and therefore understanding how young and older adults perform these tasks is an important question for this area of research. Smith et al. (2012), applied a multinomial model of event-based PM (Smith & Bayen, 2004, 2006) and some parameter estimates for the older adults in their easier (2-color) version of the task were very high. We designed the study to allow for application of the model and we were concerned that if we used the easier ongoing task for older adults and also emphasized the importance of the ongoing task, parameter estimates would reach ceiling, which could complicate interpretation of our findings. Therefore, we selected the 4-color version of the ongoing task for our older adult participants.

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of the PM and ongoing task. Participants in the PMI condition of Smith and Bayen’s study showed higher PM task performance and poorer ongoing task performance relative to that of participants in a CMI condition. These data demonstrated that young adults can vary their allocation of resources between the ongoing color-matching task and the PM task. However, the Smith and Bayen study did not include older adults. It is entirely possible that older adults will not shift resources as a function of task emphasis in this particular task context. Older adults show a greater tendency toward errors of perseveration (e.g., Ridderinkhof, Span, & van der Molen, 2002). For instance, older adults tend to continue with an existing task set when they should instead switch to a newer task set in the Wisconsin Card Sorting Test (WCST; Grant & Berg, 1948; see West, 1996, for review). The color-matching task requires a response on every trial, and older adults may have difficulty switching from the ongoing color-matching task to the PM task. If older adults are less capable of shifting from the ongoing task to the PM task, instructions concerning task emphasis should not affect their PM performance in this task. METHOD Participants The 100 (55 female) young participants ranged in age from 17 to 25 years, while the 38 (21 female) older participants ranged from 60 to 93. Participants were recruited from Introductory Psychology classes or through newspaper advertisements and flyers and received either course credit or $20 as compensation. All participants were screened to exclude individuals with health problems such as stroke or heart attack that could affect memory performance. All participants included in the study reported their health to be either good or excellent. As shown in Table 1, older adults had more years of formal education and had more correct responses on the 30-item Gardner–Monge (1977) vocabulary test than did young adults, but young

TABLE 1. Means, standard errors, and age-group comparisons for participant characteristics and scores on the vocabulary and letter comparison tests Young

Age Education Vocabulary Letter Comparison ∗

F(1, 136) > 34.65, p < .001.

Older

M

SE

M

SE

ηp 2

19.3 13.3 11.7 35.3

0.12 0.07 0.34 0.65

68.4 15.1 17.8 22.9

1.22 0.48 0.86 0.78

.97∗ .20∗ .32∗ .46∗

416 REBEKAH E. SMITH AND R. REED HUNT adults outperformed the older adults on a letter comparison task, described below (Salthouse & Babcock, 1991).

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Design All older participants performed the 4-color version of the ongoing task. Young adults were randomly assigned to perform either the 4-color version or the 6-color version of the ongoing task. Participants in each of these three groups were assigned randomly to receive either instructions emphasizing the importance of the PM task (PMI instructions) or instructions emphasizing the importance of the CM task (CMI instructions). Materials and equipment Participants completed the study one or two at a time, with each participant seated at an individual computer station equipped with a touch screen monitor and response box. Presentation of stimuli and collection of responses was accomplished with a program created with E-Prime 2.0 software (Schneider, Eschman, & Zuccolotto, 2002). From the materials used in Horn, Bayen, Smith, and Boywitt (2011, Experiment 2A) and Smith et al. (2012), we selected 2 practice items, 16 baseline items, 36 filler items, and 3 PM target words (boys, maybe, record). The order in which words were shown was randomly determined, including the presentation of targets for encoding and appearance of the target words during the test block of the ongoing task. The filler items and target items were repeated in a different random order in the second half of the test block of the ongoing task for a total of 72 filler trials and 6 target trials. The distinction between the two halves of the test block had no relevance from the participants’ perspective and this refers only to the repetition of items after all items had been shown the first time. The two halves were presented as a single continuous block. Targets appeared on Trials 11, 24, 36, 51, 62, and 77 of the test block. The practice, baseline, and test phases each included an equal number of match and non-match trials, with the order of match and non-match trials determined randomly for each participant. The 4-color version of the task used the colors white, blue, green, yellow, and red. The colors magenta and cyan (a greenish-blue) were added for the 6-color version of the task. For match trials, an equal number of trials included a probe word color that matched the first, second, etc. color presented on a given trial. Additional details regarding display times and interstimulus intervals can be found in Table 2. Procedure Participants were instructed on use of the touch screen and response box prior to reading instructions for the color-matching task. Participants were informed that they would see 4 (or 6) colors one at a time in the center of the screen and that a word would follow the 4th (or 6th) color. Participants

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TABLE 2. Details of the ongoing task blocks for the 4- and 6-color versions of the task Ongoing-task details Ongoing task version

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4-color 6-color

Colors/Trial

Display duration

ISI

4 6

500 300

250 200

Note: Colors/trial = number of color rectangles on each color-matching trial; Display duration = time (in ms) that each color rectangle is shown; ISI = interstimulus interval (in ms) following each color rectangle display.

were asked to decide whether the color of the word matched any of the colors shown on that trial and to make their response by touching either the Yes button or No button on the screen, with each word appearing in a box shown slightly below and to the left and right, respectively, of the word, which appeared in the center of the screen. Participants completed two practice trials, followed by a block of 16 baseline trials. Participants were given opportunities to ask questions and could return to the instructions prior to starting either the practice trials or baseline block. The baseline block was followed by the PM instructions, which in turn were followed by a filler task, before participants completed the 72 trial test block of ongoing task trials. At the end of the baseline block, participants were given the following instructions for the PM task: “During the color-matching task we would like you to try to remember to perform another task. In a few moments you will learn three words. If you see any of these words in the color-matching task please try to remember to press the 1 key”. Participants were then asked to locate the 1 key on the response box. The response box was placed on the side of the touch screen corresponding to the participant’s dominant hand. The experimenter reviewed the instructions with the participant prior to target encoding. The three target words were shown on the screen simultaneously for 90 seconds. Although some prior studies have allowed participants to study the target words until the participant is able to freely recall all target words (e.g., Smith & Bayen, 2006, Exp. 1), others have given participants a set amount of time to encode the target words (e.g., Boywitt & Rummel, 2012; Smith & Bayen, 2006, Exp. 2). The latter option was selected in the current study for the following reason. In our everyday lives we may not have control over the time to encode intention related information, thus, there is an argument that allowing a set amount of time for encoding is ecologically valid. This approach is also advantageous for application of a multinomial model of event-based PM (Smith & Bayen, 2004, 2006; see Appendix). Following target encoding participants received either the PMI or CMI instructions. In the PMI conditions, participants were told that the PM task was the more important task and that they should try hard to remember to

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418 REBEKAH E. SMITH AND R. REED HUNT perform this task. Participants in the CMI condition were told that while we wanted them to remember the “1” task, the color-matching task was more important and they should try very hard to continue to do well on the colormatching task. The filler task followed PM instructions. Participants read instructions for a letter comparison task in which they were shown two letter strings and were to decide if the letter strings matched. Participants completed three sets of letter comparisons, with strings of three, six, and nine letters. Responses to the letter comparison task were made by touching the letter S for same or D for different on the touch screen. Scores (Table 1) were calculated by subtracting the number of incorrect responses from the number of correct responses made within 30 seconds for each set of letter strings. After the filler task, participants began the test block of 72 ongoing task trials. Participants were not reminded of the PM task. Upon completion of the test block of trials, participants were asked to recall the PM action. Participants (one in each age group) who made no PM responses and failed to recall the correct action were excluded and replaced. Participants also reported which task was most important. Participants in the PMI condition who said the CM task was most important or participants in the CMI condition who selected the PM task were excluded and replaced. Participants also completed a target recognition test in which they were shown the three target items and three filler items one at a time in a random order and made a yes/no decision regarding whether each word was a target word. Prior studies have used both recall (e.g., Einstein, Holland, McDaniel, & Guynn, 1992; Smith & Bayen, 2006) and recognition (e.g., Schnitzpahn, Horn, Bayen, & Kliegel, 2011; Smith et al., 2011) to evaluate post-task target memory. We selected a recognition test for the following reason. When participants are performing the PM task, participants must recognize, not recall, the target events, thus a post-task target recognition task is arguably a better measure of the memory processes involved in the primary task of interest. Finally, participants also completed a vocabulary test and health and demographics questionnaire.

RESULTS Ongoing task performance Results for accuracy and response times on the ongoing task can be found in Table 3. The current experiment included a baseline block prior to the introduction of the PM task. This provides new information about relative performance across age groups on the ongoing task when the ongoing task is performed without an embedded PM task, information that was not provided by the design used in Smith et al. (2012).

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TABLE 3. Prospective memory performance, post-task target recognition, and ongoing task performance

Task emphasis

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PMI

CMI

Prospective memory

Target recognition

Ongoing task

Group

N

M

SE

M

SE

M

SE

M

SE

Older Young 6-color Young 4-color Older Young 6-color Young 4-color

18 25 25 20 25 25

0.30 0.71 0.73 0.12 0.63 0.55

0.08 0.07 0.06 0.05 0.07 0.08

0.83 0.95 0.96 0.90 0.91 0.91

0.07 0.03 0.02 0.04 0.04 0.04

0.70 0.43 0.88 0.76 0.55 0.77

0.05 0.03 0.02 0.04 0.04 0.03

2167 1664 1723 1868 1667 1531

154 89 74 58 101 69

Notes: PMI = Prospective memory task emphasized; CMI = Color-matching task emphasized; Target recognition = Corrected hit rate on post-task target recognition test. One older adult in the PMI condition said “yes” to all items on the post-task target recognition test, resulting in a corrected hit rate of 0.00. When this participant is removed, the mean for this group is 0.88 with SE = 0.05.

Accuracy In keeping with prior research (e.g., Smith et al., 2012) the target trials and trials immediately following the target trials were excluded from the analysis of ongoing task performance to avoid finding a cost to the ongoing task resulting from just having performed the PM task. The first five trials of the test block were also excluded. As in Horn et al. (2011) and Smith et al. (2012), correct responses to match trials were considered hits and incorrect responses to non-match trials were considered false alarms and these measures were used to calculate the corrected hit rate (hits minus false alarms) as a measure of discrimination in the ongoing task. Baseline performance was not affected by task emphasis and this variable did not interact with group, Fs < 1, ps > .81. Not surprisingly, given that different ongoing tasks were used, there was an effect of group, F(2, 132) = 27.49, MSE = 0.04, p < .001, ηp 2 = .29. As expected, Tukey’s HSD demonstrated that young adults performing the 4-color task (M = 0.90, SE = 0.02) were more accurate on the ongoing task than either the young adults performing the 6-color task (M = 0.65, SE = 0.03) or the older adults (M = 0.64, SE = 0.04), ps < .001. Baseline performance did not differ between the older adults and the young adults in the 6-color condition, p = .973. In the test block, the effect of task emphasis was not significant, F < 1, p = .348, but the significant effect of group, F(2, 132) = 57.10, MSE = 0.03, p < .001, ηp 2 = .46, was qualified by a significant interaction of group and task emphasis, F(2, 132) = 6.51, MSE = 0.04, p 14.06, p < .001, ηp 2 s > .29. Post-hoc Tukey’s HSD were conducted for each emphasis condition. In the CMI condition, both the older adults and the young adults in the 4-color condition were more accurate than the young adults in the 6-color group, ps < .001, while the former two groups did not differ, p = .928. The advantage for the older adults, who performed the 4-color task, over the young adults performing the 6-color task replicates Smith et al. (2012) in which neutral instructions were used (i.e., neither task was emphasized). When the importance of the ongoing task is emphasized, older participants performed as well as the young participants on the 4-color task. This result contrasts with prior research using neutral instructions which has consistently produced an advantage on the ongoing 4-color task for young adults (e.g., Smith & Bayen, 2006; Smith et al., 2012), and potentially suggests that older adults in the previous studies emphasized the PM task over the ongoing task. However, this conclusion does not alter the important finding that older adults performed as well or better than the young adults on the ongoing task in the CMI condition, but continued to show an age-related deficit in PM performance. The results for the PMI condition followed the pattern seen previously with neutral instructions. Increasing the number of colors per trial from 4 to 6 decreased young adults’ ongoing task accuracy, p < .001. As in Smith et al. (2012), older adults performing the 4-color task were more accurate on the ongoing task than were the young adults performing the 6-color task, p < .001, but not as accurate as young adults performing the 4-color task, p = .001. Response times Response time (RT) analysis included only accurate trials and data were trimmed by removing trials with RTs less than 200 ms and more than 3 SDs from the individual participant’s mean for each trial type in each block. Trimming resulted in the exclusion of less than 1% of trials. Baseline RTs did not differ as a function of task emphasis and the emphasis manipulation did not interact with group, Fs < 1, p > .33. Tukey’s HSD test was used to investigate the main effect of group, F(2, 132) = 37.24, MSE = 412,567, p < .001, ηp 2 = .36. As in Smith et al. (2012), older adults (M = 2435, SE = 182) had longer RTs than either of young adult groups, ps < .001. The young adult groups did not differ from one another (M = 1389, SE = 30), p = .72. In the test block, color matching RTs were significantly faster in the CMI condition (M = 1676, SE = 49) than in the PMI condition (M = 1819, SE = 63), F(1, 132) = 4.66, MSE = 192,774, p < .033, ηp 2 = .03. This replicates, and extends to older adults, Smith and Bayen’s (2004) findings with young adults of an effect of task emphasis on RTs in the color-matching

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task. Group also affected RTs in the test block, F(2, 132) = 9.94, MSE = 192,774, p < .001, ηp 2 = .13, but the variables did not interact, F(2, 132) = 1.37, p = .25. As in the baseline block, older adults (M = 2010, SE = 82) had longer RTs than either of the young adult groups, ps < .002, and the two young adult groups did not differ (M = 1646, SE = 42), p = .897. This pattern replicates the findings reported in Smith et al. (2012).

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PM performance The proportions of PM targets to which participants pressed the “1” button3 are shown in Table 3. In no instance did a participant press a number button other than “1”. Performance was affected by task emphasis instructions, with higher performance when the PM task was emphasized (M = 0.61, SE = 0.04) than when the CM task was emphasized (M = 0.46, SE = 0.05), F(1, 132) = 6.57, MSE = 0.11, p = .012, ηp 2 = .05. The main effect of group was also significant, F(2, 132) = 25.06, MSE = 0.11, p < .001, ηp 2 = .28. Tukey’s HSD test indicated that the older adult group (M = 0.20, SE = 0.05) did not perform as well as either of the two young adult groups, ps < .001. The young adult 4-color group (M = 0.64, SE = 0.05) and the young adult 6-color group (M = 0.67, SE = 0.05) did not differ, p = .846. The variables did not interact, F < 1, p = .70, in the analysis of PM performance. The results show that both young and older adults allocate resources differentially depending upon task emphasis. In order to address the second question of interest (When young and older adults have similar performance on the ongoing task, will the agerelated difference in PM performance be similar in the CMI and PMI conditions, or will emphasizing the PM task reduce the age-related difference?), we conducted a follow-up analysis of PM performance that included just the older and young 6-color groups. As described above, comparisons of these groups showed a consistent advantage in ongoing task performance for the older adults, thus the older adults are out-performing the young adults on the ongoing task. If the pattern of results in Smith et al. (2012) had been due to the older adults’ perceiving the ongoing task to be more important, we might expect that the age-related difference in PM performance would be reduced when either the PM or the ongoing task is emphasized. In contrast to this proposal and as in the analysis with all groups, the 2 (group: older or young 6-color) × 2 (emphasis: PMI or CMI) ANOVA failed to show any indication of an interaction, F < 1, p =. 487, and separate planned comparisons of the older and young 6-color groups for each emphasis condition, produced large 3

Participants made a total of eight PM responses on trials other than the prospective memory target trials (i.e., PM responses on non-target trials). In no instances did these PM false alarms occur during the three trials immediately following any of the target trials.

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422 REBEKAH E. SMITH AND R. REED HUNT effect sizes in favor of the young adults in both emphasis conditions, ts > 3.88, ps < .001, Cohen’s ds > 1.18. The results demonstrate a robust age difference in both emphasis conditions suggesting that the age-related difference is not due to differential perceptions of task importance. We applied a multinomial model of event-based PM (Smith & Bayen, 2004) to investigate whether the differences (e.g., young vs. old, PMI vs. CMI) seen in observed PM performance were due to differences in the prospective component (remembering that something is to be done) or the retrospective component (remembering when the PM task is to be performed) or a combination of the two components. The model results (see Appendix) indicated that the age groups differed with respect to the prospective component, regardless of which task was emphasized. The model results for comparisons of task emphasis, age, and ongoing task load replicated prior findings (Horn et al., 2011; Smith & Bayen, 2004, 2006; Smith et al., 2011). Post task target recognition If a participant correctly identified a target word as a target this was considered a hit on the post task target recognition test. If the participant incorrectly called a non-target word a target, this was considered a false alarm. The corrected hit rate (hits minus false alarms) on the post-task target recognition test (M = 0.91, SE = 0.02) was not affected by task emphasis, F < 1, p = .78, or group, F(2, 132) = 1.62, p = .201, and the variables did not interact, F(2, 132) = 1.20, p = .276.4

DISCUSSION We investigated the effects of task emphasis on performance of a PM task embedded in an ongoing color-matching task in young and older adults. The task emphasis manipulation involved providing instructions that either emphasized the importance of the ongoing task or emphasized the importance of the PM task. The current findings replicate several important results from prior studies. For young adults, varying the number of colors on each trial of the color-matching task did not affect PM performance, replicating Horn et al. (2011) and Smith et al. (2012). This experiment also replicates the findings 4

In response to reviewer suggestions, we conducted an ANACOVA with target recognition corrected hit rate as the covariate and PM performance as the dependent variable. The main effects of group, p < .001, and task emphasis, p = .01, remained significant. Although the contribution of the covariate was significant, F(1, 130) = 9.57, MSE = 0.01, p = .002, ηp 2 = .07, this did not account for the effects for group and task emphasis. In addition, while the young adults performing the more difficult ongoing task with instructions that emphasized the ongoing task showed a positive correlation between target recognition and prospective memory performance that approached significance, r = .37, p = .065, no other groups demonstrated such a relationship, all ps > .29.

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from Smith et al. showing age-related differences in favor of young adults in PM performance, despite the fact that older adults performed the ongoing task as well or better than the young adults. The first question addressed by the current study was whether older adults would show differences in PM performance as a function of instructions that either emphasize the importance of the ongoing task or the importance of the PM task? Consistent with prior research using diary studies and naturalistic tasks or time-based tasks (Ihle et al., 2012; Schnitzspahn et al., 2011) we did find an effect of task emphasis on older adults’ PM performance. However, as noted in the introduction, the one prior laboratory study of event-based PM investigating the effects of task emphasis on PM performance for both young and older adults failed to show an effect of task emphasis for either group (Kliegel et al. 2003). As noted in the introduction, the Kliegel et al. study did not find a benefit of task importance for either young or older adults, but this study was limited in terms of power and the use of a relatively weak manipulation of task emphasis. The current study shows that older adults can vary the way in which they allocate attention between the ongoing and PM task as a function of task importance and that this affects performance on both the PM and the ongoing task. Thus, task importance can benefit older adults PM performance in a laboratory event-based PM task. The current study also addressed the question of whether, when young and older adults have similar performance on the ongoing task, age-related difference in PM performance will be similar in the CMI and PMI conditions, or will emphasizing the PM task reduce the age-related difference? The second question relates to a possible explanation for Smith et al.’s (2012) finding that older adults had poorer PM performance even when performing as well or better on the ongoing task relative to young adults, namely the possibility that older adults assume that the ongoing task is more important than the PM task. If so, under neutral instructions, such as those used by Smith et al., older adults would not switch resources to the PM task, and older adults’ PM performance would continue to lag that of younger adults even when the ongoing task is functionally easier for the older adult. This explanation leads to the prediction that the age-related difference in PM performance would be reduced in the PMI condition relative to the CMI condition. After verifying that the older adults were performing the ongoing task at least as well as the young adults in the 6-color group, we compared PM performance for the older adults and these young adults in the 6-color group. As shown by the comparisons of PM performance for the older adults and just the young adults who performed the 6-color version of the ongoing task, the interaction of age and task emphasis was not significant and the age effect was robust in both task emphasis conditions. Thus we can reject the hypothesis that older participants routinely treat the ongoing task as more important than the PM task under neutral instructions. Consistent with previous research

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424 REBEKAH E. SMITH AND R. REED HUNT (Kliegel et al., 2003), we find no evidence that a bias to perceive one task or the other as more important underlies the age-related differences seen in PM performance. As noted earlier, we further investigated the effects of age, task emphasis, and ongoing task load on the cognitive processes underlying observable PM using a multinomial modeling approach (Pavawalla, Schmitter-Edgecombe, & Smith, 2012; Schnitzpahn, Horn, Bayen, & Kliegel, 2012; Smith & Bayen, 2004, 2005, 2006). The modeling results, which can be found in Appendix, showed that age differences emerged in the prospective component of the task, but not in the retrospective component, thereby replicating prior applications of this model with both young and older adults (Horn et al., 2011; Smith et al., 2012). As proposed by Smith et al. (2012), our manipulation of the number of colors per trial likely increased a demand on working memory storage, without affecting the executive control demands of the task context. This explanation is consistent with a number of different theories of working memory (e.g., Cowan, 1988; Oberauer, 2002). For example in Baddeley’s (1986, 2007) multicomponent working memory system, increasing demands on one subsystem, for instance the phonological loop, theoretically has minimal impact on another subsystem such as the visual-spatial sketch pad. Smith et al.’s findings also dovetail with earlier work by Marsh and co-workers (Marsh, Hancock, & Hicks, 2002; Marsh & Hicks, 1998) showing that divided attention tasks that increase load, but that do not increase demands on executive control, do not affect PM performance. However, Smith et al. could not rule out the possibility that older adults failed to shift resources to the PM task because the nature of the ongoing task discouraged variations in the allocation of attentional resources, especially for older adults. The current experiment does address this issue. The ongoing color-matching task requires that information be maintained in working memory for making a decision about whether the color of the word matched one of the colors held in working memory. In contrast, an ongoing task in which participants make a response to a stimulus and then move on may be more amenable to switching from that task to the PM task. For instance, an ongoing lexical decision task requires that the stimulus be processed sufficiently to make a word/non-word decision, but the stimulus need not be maintained in working memory. In contrast, even when the demands of the ongoing color-matching task are reduced, the maintenance requirement is not eliminated and the need to maintain information may increase older adults’ already greater likelihood of errors of perseveration (e.g., Ridderinkhof et al., 2002). The alternative explanation that older adults may be less likely to switch from the color-matching task leads to the prediction that older adults would not show an effect of task emphasis on PM performance. In contrast to this prediction, older adults did show effects of

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task emphasis, with better PM performance in the PMI condition relative to the CMI condition. The task emphasis manipulation used in this experiment is relevant to a broader issue in PM research. While older adults often do not perform as well as young adults on laboratory PM tasks, the reverse pattern has been found in naturalistic PM tasks (Henry et al., 2004). One proposal is that older adults are more motivated to perform the naturalistic tasks, while young adults are less motivated to do so (Maylor, 2008; Phillips, Henry, & Martin, 2008). Consistent with this proposal, Aberle et al. (2010) found that providing a monetary incentive for performing a naturalistic PM task improved performance for young adults, eliminating the advantage for older adults seen when no incentive was provided. The older group in the Aberle et al. study showed no advantage when given an incentive, which was taken to indicate that the older adults are inherently more motivated to perform these tasks. More recently however, Ihle et al.’s (2012) diary study demonstrated that task importance was related to older adults’ performance on PM tasks that were personally relevant (see also Altgassen, Kliegel, Brandimonte, & Filippello, 2010, for study of social importance on a time-based PM task). Ihle et al. interpreted their findings, in light of the earlier study by Aberle et al., as indicating that older adults “may not respond to external incentives in general or monetary incentives in particular as much as younger adults” (p. 96). In the current study, the effect of task emphasis was just as great for the older adults as for the younger adults, as evidenced by the lack of any interaction of task emphasis and group. Thus the conclusion drawn by Ihle et al. should perhaps be modified to say that although older adults may be less affected by monetary incentives, external motivation can influence their performance in a fashion similar to that of young adults. This revised conclusion would also be consistent with prior studies showing that task importance can affect performance for older adults (e.g., Ihle et al. 2012). However, it is still the case that personally relevant tasks may be more influenced by importance than are laboratory tasks. The naturally occurring tasks investigated in the Ihle et al. diary study showed better performance for older adults relative to young adults, which could be attributable to older adults giving these tasks greater importance than do the young adults. In contrast, the current study found the opposite age-related difference in both importance conditions and it is possible that importance will have differential effects for the two age groups in naturalistic and laboratory tasks. (See also, Nied´zwie´nska & Barzykowski, 2012, for demonstration of negative effect of social importance on young adults’ PM performance.) Kvavilashvili and Fisher (2007; see also Schnitzspahn et al., 2011) suggest that outside of the laboratory older adults may benefit from a combination of higher motivation “and relatively undemanding and familiar ongoing tasks” (p. 129) allowing for performance in older adults that matches or

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426 REBEKAH E. SMITH AND R. REED HUNT exceeds that of young adults in non-laboratory tasks. Despite this advantage for older adults in naturalistic tasks, Kvavilashvili and Fisher go on to note that for laboratory tasks “although old participants may continue to be more highly motivated than young participants, they are usually asked to perform tasks that are unfamiliar and cognitively demanding. . .” (pp. 129–130). Our findings are consistent with Kvavilashvili and Fisher’s conclusions regarding laboratory tasks. Even when motivation to perform the PM task was higher for the older adults than for the young adults (comparing older adults in the PMI condition with young adults performing the 6-color task in the CMI condition), the older adults PM performance was lower than that of the young adults, p = .004, but the older adults were more accurate then these young adults on the ongoing task, p = .02. Taken together, this combination of findings supports Kvavilashvili and Fisher’s suggestion that the unfamiliarity of the laboratory task is particularly detrimental for the older adults and greater motivation cannot overcome this detriment. Although older adults may often find themselves in more familiar situations outside of the laboratory, at all ages we often must remember to perform PM tasks while engaged in other activities that are resource demanding (e.g., remembering to interrupt our drive home to stop at the store). With improving health and longevity individuals may remain in the workforce longer and may stay active longer into retirement, and thus, older adults may more frequently be asked to perform prospective memory tasks in situations in which their other ongoing activities are relatively demanding or unfamiliar. In any event, it is important to understand the factors that contribute to age-related differences, and ways to minimize those differences, when the situation does impose additional demands. The current experiment captures these types of situations and shows that importance of the PM task can benefit PM performance, although the age differences were not eliminated. SUMMARY AND CONCLUSION In summary, older adults out-performed the young adults in terms of accuracy on the ongoing color-matching task, but the age-related difference in PM performance in favor of the young adults persisted. Furthermore, age and task emphasis did not interact in the analysis of PM performance, either in the overall analysis with both young adult conditions, or in the comparison of just the young 6-color group with the older adult group, thus the age-related difference was consistent, regardless of task emphasis. Overall, the current behavioral (and modeling) results are consistent with investigations of both the behavioral and neural correlates of PM showing that the age-related differences in adulthood can be more strongly associated with differences in remembering that something needs to be done rather than in remembering when or what needs to be done (e.g., Cohen, West,

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& Craik, 2001; West & Bowry, 2005; Zöllig et al., 2007; but see also Reese & Cherry, 2002; Schnitzpahn et al., 2011; Zimmermann & Meier, 2006). In addition, the current findings demonstrate that this can be the case regardless of whether the ongoing task or the PM task is emphasized as the more important task. Additional research is needed to fully understand why the age-related difference is demonstrated, despite the older adults’ advantage on the ongoing task performance, but the current experiment does argue against the possibility that the age-related difference is due to differential perceptions of task importance in the two age groups. Original manuscript received 19 March 2013 Revised manuscript accepted 16 July 2013 First published online 14 August 2013

REFERENCES Aberle, I., Rendell, P. G., Rose, N. S., McDaniel, M. A., & Kliegel, M. (2010). The age prospective memory paradox: Young adults may not give their best outside of the lab. Developmental Psychology, 46, 1444–1453. Altgassen, M., Kliegel, M., Brandimonte, M., & Filippello, P. (2010). Are older adults more social than young adults? Social importance increases older adults’ prospective memory performance. Aging, Neuropsychology, and Cognition, 17, 312–328. Altgassen, M., Zöllig, J., Kopp, U., Mackinlay, R., & Kliegel, M. (2007). Patients with Parkinson’s disease can successfully remember to execute delayed intentions. Journal of the International Neuropsychological Society, 13, 888–892. Baddeley, A. D. (1986). Working memory. Oxford: Oxford University Press. Baddeley, A. D. (2007). Working memory, thought and action. Oxford: Oxford University Press. Boywitt, C. D., & Rummel, J. (2012). A diffusion model analysis of task interference effects in prospective memory. Memory & Cognition, 40, 70–82. Cohen, A., West, R., & Craik, F. I. M. (2001). Modulation of the prospective and retrospective components of memory for intentions in younger and older adults. Aging, Neuropsychology, and Cognition, 8(1), 1–13. doi:1382-5585/01/0801-001 Cowan, N. (1988). Evolving conceptions of memory storage, selective attention, and their mutual constraints within the human information-processing system. Psychological Bulletin, 104, 163–191. Einstein, G. O., Holland, L. J., McDaniel, M. A., & Guynn, M. J. (1992). Age-related deficits in prospective memory: The influence of task complexity. Psychology and Aging, 7, 471–478. doi:10.1037/0882-7974.7.3.471 Gardner, E., & Monge, R. (1977). Adult age differences in cognitive abilities and educational background. Experimental Aging Research, 3, 337–383. Grant, D. A., & Berg, E. (1948). A behavioral analysis of degree of reinforcement and ease of shifting to new responses in a Weigl-type card sorting problem. Journal of Experimental Psychology, 38, 404–411. Henry, J. D., MacLeod, M. S., Phillips, L. H., & Crawford, J. R. (2004). A meta-analytic review of prospective memory and aging. Psychology and Aging, 19, 27–39. Horn, S. S., Bayen, U. J., Smith, R. E., & Boywitt, C. D. (2011). The multinomial model of prospective memory: Validity of ongoing-task parameters. Experimental Psychology, 58, 247–255.

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428 REBEKAH E. SMITH AND R. REED HUNT Ihle, A., Schnitzsphan, K. M., Rendell, P. G., Luong, C., & Kliegel, M. (2012). Age benefits in everyday prospective memory: The influence of personal task importance, use of reminders and everyday stress. Aging, Neuropsychology, and Cognition, 19, 84–101. Kliegel, M., Jäger, T., & Phillips, L. H. (2008). Adult age differences in event-based prospective memory: A meta-analysis on the role of focal versus nonfocal cues. Psychology and Aging, 23, 203–208. Kliegel, M., Martin, M., McDaniel, M., & Einstein, G. (2001). Varying the importance of a prospective memory task: Differential effects across time- and event-based prospective memory. Memory, 9(1), 1–11. doi:10.1080/09658210042000003 Kliegel, M., Martin, M., McDaniel, M. A., & Einstein, G. O. (2004). Importance effects on performance in event-based prospective memory tasks. Memory, 12, 553–561. Kliegel, M., Martin, M., & Moor, C. (2003). Prospective memory and aging: Is task importance relevant? International Journal of Psychology, 38, 207–214. doi:10.1080/00207590244000205 Kvavilashvili, L., & Fisher, L. (2007). Is time-based prospective remembering mediated by self-initiated rehearsals? Role of incidental cues, ongoing activity, age, and motivation. Journal of Experimental Psychology: General, 136, 112–132. Marsh, R. L., Hancock, T., & Hicks, J. L. (2002). The demands of an ongoing activity influence the success of event-based prospective memory. Psychonomic Bulletin & Review, 9, 604–610. Marsh, R. L., & Hicks, J. L. (1998). Event-based prospective memory and executive control of working memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 24, 336–349. Maylor, E. (2008). Commentary: Prospective memory through the ages. In M. Kliegel, M. A. McDaniel, & G. O. Einstein (Eds.), Prospective memory: Cognitive, neuroscience, developmental, and applied perspective (pp. 217–233). New York, NY: Erlbaum. Moshagen, M. (2010). multiTree: A computer program for the analysis of multinomial processing tree models. Behavior Research Methods, 42, 42–54. Nied´zwie´nska, A., & Barzykowski, K. (2012). The age prospective memory paradox within the same sample in time-based and event-based tasks. Aging, Neuropsychology, and Cognition, 19, 58–83. Oberauer, K. (2002). Access to information in working memory: Exploring the focus of attention. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28, 411–421. Pavawalla, S. P., Schmitter-Edgecombe, M., & Smith, R. E., (2012). Prospective memory following moderate-to-severe traumatic brain injury: A multinomial modeling approach. Neuropsychology, 26, 91–101. Phillips, L. H., Henry, J. D., & Martin, M. (2008). Adult aging and prospective memory: The importance of ecological validity. In: M. Kliegel, M. A. McDaniel, & G. O. Einstein (Eds.), Prospective memory: Cognitive, neuroscience, developmental, and applied perspectives (pp. 161–185). Mahwah, NJ: Erlbaum. Reese, C. M., & Cherry, K. E. (2002). The effects of age, ability, and memory monitoring on prospective memory task performance. Aging, Neuropsychology, and Cognition, 9, 98–113. doi:10.1076/anec.9.2.98.9546 Ridderinkhof, K. R., Span, M. M., & van der Molen, M. W. (2002). Perseverative behavior and adaptive control in older adults: Performance monitoring, rule induction, and set shifting. Brain and Cognition, 49, 382–401. Salthouse, T. A., & Babcock, R. L. (1991). Decomposing adult age differences in working memory. Developmental Psychology, 27, 763–776.

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Schneider, W., Eschman, A., & Zuccolotto, A. (2002). E-Prime user’s guide. Pittsburgh, PA: Psychology Software Tools. Schnitzspahn, K. M., Horn, S. S., Bayen, U. J., & Kliegel, M. (2012). Age effects in emotional prospective memory: Cue valence differentially affects the prospective and retrospective component. Psychology and Aging, 27, 498–509. doi:http://dx.doi.org/10.1037/a0025021 Schnitzspahn, K. M., Ihle, A., Henry, J. D., Rendell, P. G., & Kliegel, M. (2011). The age-prospective memory-paradox: An exploration of possible mechanisms. International Psychogeriatrics, 23, 583–592. Smith, R. E. (2003). The cost of remembering to remember in event-based prospective memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 347–361. Smith, R. E., & Bayen, U. J. (2004). A multinomial model of event-based prospective memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 30, 756–777. Smith, R. E., & Bayen, U. J. (2005). The effects of working memory resource availability on prospective memory: A formal modeling approach. Experimental Psychology, 52, 243–256. Smith, R. E., & Bayen, U. J. (2006). The source of adult age differences in eventbased prospective memory: A multinomial modeling approach. Journal of Experimental Psychology: Learning, Memory, and Cognition, 32, 623–635. Smith, R. E., Horn, S. S., & Bayen, U. J. (2012). Prospective memory in young and older adults: The effects of ongoing task load. Aging, Neuropsychology, and Cognition, 19, 495–514. West, R., & Bowry, R. (2005). Effects of aging and working memory demands on prospective memory. Psychophysiology, 42, 698–712. doi:10.1111/j.1469-8986.2005.00361.x West, R. L. (1996). An application of prefrontal cortex function theory to cognitive aging. Psychological Bulletin, 120, 272–292. Zimmermann, T. D., & Meier, B. (2006). The rise and decline of prospective memory performance across the lifespan. The Quarterly Journal of Experimental Psychology, 59, 2040–2046. doi:10.1080/17470210600917835 Zöllig, J., West, R., Martin, M., Altgassen, M., Lemke, U., & Kliegel, M. (2007). Neural correlates of prospective memory across the lifespan. Neuropsychologia, 45, 3299–3314. doi:10.1016/j.neuropsychologia.2007.06.010

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APPENDIX: APPLICATION OF A MULTINOMIAL MODEL OF PROSPECTIVE MEMORY As can be seen in Table A1, older adults had lower estimates of P, even when the older adults performed better on the ongoing task in terms of accuracy (older vs. young 6-color). In both the PMI and CMI conditions the young 4-color and young 6-color groups differed on parameters measuring processes involved in the ongoing task, but the groups did not differ on parameters P and M. Thus, the pattern previously produced with neutral PM instructions (Horn et al., 2011; Smith et al., 2012) was found here. Finally, older adults and young adults performing the 4-color version of the task produced the expected pattern: emphasizing the PM task increased parameter P, replicating a prior demonstration of this pattern with young adults (Smith & Bayen, 2004) and providing the first such demonstration for older adults. Multitree (Moshagen, 2010) was used to conduct model analyses.

5.28 3.21 0.38 4.13 1.36 3.68

0.31 0.73 0.74 0.13 0.65 0.56

M

P

0.05 0.04 0.04 0.03 0.04 0.04

SE 0.94 0.97 0.98 0.87 0.97 0.98

M

M

0.04 0.02 0.01 0.09 0.02 0.02

SE 0.56 0.11 0.80 0.65 0.32 0.68

M

C1

0.03 0.03 0.02 0.03 0.03 0.02

SE 0.82 0.72 0.93 0.83 0.77 0.88

M

C2

0.02 0.02 0.01 0.02 0.02 0.02

SE

0.70 1.29 2.19 2.66 0.22 0.08 0.62 0.02 0.08

71.13a 51.59a 0.02 2.53 10.66a 2.02 10.03b

M

40.56a 42.24a

P

57.69a 0.69 291.13a 78.47a 4.55c 21.29a 15.96a

87.44a 45.21a

C1

C2

3.41d 4.47c 67.98a 17.14a 0.15 2.91d 6.55b

8.64b 23.05a

G2 (1) for model parameters

Notes: Values of G2 (4) less than 9.49 indicate a good fit of the model to the data in all conditions. P = probability of engaging in preparatory attentional processing. M = ability to discriminate between targets and non-targets. C1 and C2 = ability to detect that colors match or do not match, respectively. Values of G2 (1) greater than 3.84 indicate a significant difference in the parameter estimates for the two groups or conditions. a p ≤ .001, b p ≤ .01, c p < .05, d p < .10.

PMI:

Older vs. Young 6-color vs. Young 4-color Older CMI: vs. Young 6-color vs. Young 4-color PMI: Young 6-color vs. Young 4-color CMI: Young 6-color vs. Young 4-color Older: PMI vs. CMI Young 6-color: PMI vs. CMI Young 4-color: PMI vs. CMI

Comparison

G2 (4) overall model fit

TABLE A1. Goodness-of-fit statistics, parameter estimates, and parameter comparisons between groups

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Prospective memory in young and older adults: the effects of task importance and ongoing task load.

Remembering to perform an action in the future, called prospective memory, often shows age-related differences in favor of young adults when tested in...
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