Effects of Spacing of Item Repetitions in Continuous Recognition ...

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Experimental Aging Research: An International Journal Devoted to the Scientific Study of the Aging Process Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/uear20

Effects of Spacing of Item Repetitions in Continuous Recognition Memory: Does Item Retrieval Difficulty Promote Item Retention in Older Adults? a

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Aslı Kılıç , William J. Hoyer & Marc W. Howard

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Department of Psychology, Syracuse University, Syracuse, New York, USA Version of record first published: 22 Apr 2013.

To cite this article: Aslı Kılıç , William J. Hoyer & Marc W. Howard (2013): Effects of Spacing of Item Repetitions in Continuous Recognition Memory: Does Item Retrieval Difficulty Promote Item Retention in Older Adults?, Experimental Aging Research: An International Journal Devoted to the Scientific Study of the Aging Process, 39:3, 322-341 To link to this article: http://dx.doi.org/10.1080/0361073X.2013.779200

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Experimental Aging Research, 39: 322–341, 2013 Copyright # Taylor & Francis Group, LLC ISSN: 0361-073X print=1096-4657 online DOI: 10.1080/0361073X.2013.779200

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EFFECTS OF SPACING OF ITEM REPETITIONS IN CONTINUOUS RECOGNITION MEMORY: DOES ITEM RETRIEVAL DIFFICULTY PROMOTE ITEM RETENTION IN OLDER ADULTS?

Aslı Kılıc¸ William J. Hoyer Marc W. Howard Department of Psychology, Syracuse University, Syracuse, New York, USA Background=Study Context: Older adults exhibit an age-related deficit in item memory as a function of the length of the retention interval, but older adults and young adults usually show roughly equivalent benefits due to the spacing of item repetitions in continuous memory tasks. The current experiment investigates the seemingly paradoxical effects of retention interval and spacing in young and older adults using a continuous recognition memory procedure. Methods: Fifty young adults and 52 older adults gave memory confidence ratings to words that were presented once (P1), twice (P2), or three times (P3), and the effects of the lag length and retention interval were assessed at P2 and at P3, respectively. Results: Response times at P2 were disproportionately longer for older adults than for younger adults as a function of the number of items occurring between P1 and P2, suggestive of age-related loss in item memory. Ratings of confidence in memory responses revealed that older adults remembered fewer items at P2 with a high degree of certainty. Confidence Received 7 March 2012; accepted 17 June 2012. This work was supported by grants AG11451 and AG034464 from NIA and grant MH069938 from NIMH. The authors thank Kim Talbott for assistance with data collection, Peter G. Kelley for assistance with the programming algorithms for stimulus presentation, and Matthew Prull for comments on an earlier draft. Aslı Kılıc¸ is now at the Department of Psychology, Koc¸ University, Istanbul, Turkey. Marc W. Howard is now at the Department of Psychology, Boston University, Boston, Massachusetts, USA. Address correspondence to William J. Hoyer, Department of Psychology, 430 Huntington Hall, Syracuse, NY 13244, USA. E-mail: [email protected]

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ratings given at P3 suggested that young and older adults derived equivalent benefits from the spacing between P1 and P2. Conclusion: Findings of this study support theoretical accounts that suggest that recursive reminding and=or item retrieval difficulty promote item retention in older adults.

Older adults show an age-related decline in memory performance when compared with young adults. Specifically, a meta-analysis by Verhaeghen, Marcoen, and Goossens (1993) reported that the effect size of the difference between young adults and older adults was about
0.7 SD in studies using measures of recognition memory and about
1.0 SD in studies using recall and cued recall measures. And, more recently, a meta-analysis by Old and Naveh-Benjamin (2008) produced an effect size of about
0.7 SD for the age difference in item memory and an effect size of about
0.9 SD for the age difference in associative memory. Consistent with the general finding of an age-related decline in memory, age-comparative studies of item memory in continuous recognition tasks typically show an age-related deficit associated with the length of the retention interval (e.g., Ferris, Crook, Clark, McCarthy, & Rae, 1980; Le Breck & Baron, 1987; Poon & Fozard, 1980; Rugg, Mark, Gilchrist, & Roberts, 1997). However, roughly age-equivalent benefits due to the increased spacing between repetitions are typically observed in studies of continuous recognition (e.g., Rugg, 1997) and continuous cued recall (e.g., Balota, Duchek, & Paullin, 1989; Logan & Balota, 2008). The memory benefits associated with the spacing of item repetitions are of substantial theoretical as well as practical import, but little is known with any certainty about how or why age-equivalent benefits accrue under conditions of distributed practice. Theoretical frameworks based on item repetitions and recursive reminding (e.g., Hintzman, 2004, 2010) and theoretical frameworks that call attention to the memory benefits that result from deficient processing or retrieval difficulty at P1 (presented once) are particularly relevant to the understanding of spacing effects (e.g., Benjamin & Tullis, 2010; Karpicke & Roediger, 2007; Pyc & Rawson, 2009). In the present study, we consider the notion that recursive reminding serves to attenuate age-related retrieval deficits and the notion that age-related retrieval difficulty serves to promote or potentiate item memory in older adults. We assess the effects of the spacing of item repetitions (lag lengths) and retention intervals for repeated items in a fully crossed design in young adults and older adults in a continuous recognition task. Choices about the details of procedure followed methods used in several classic studies examining the effects of the

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spacing of repetitions on continuous recognition performance in young adults (e.g., Glenberg, 1976; Hintzman, 1969; Hockley, 1982; Shepard & Teghtsoonian, 1961). The procedure used in the present study is illustrated in Figure 1. Target words were presented once (P1), twice (P2), or three times (P3) and were systematically interspersed among other words. Participants rated their confidence about whether a word was previously encountered (‘‘old’’) or not (‘‘new’’) using a 9-point scale. Lag refers to the number of intervening items between P1 and P2 and retention interval refers to the number of intervening items between P2 and P3. Item memory diminishes as a function of time elapsed since study, and item memory is enhanced for items that are repeated in a spaced or distributed fashion. These two seemingly paradoxical effects associated with the recency and spacing of item repetitions are among the most ubiquitous findings in memory science. The recency effect refers to the general finding that item memory performance declines as a function of the length of time elapsed between study and test (e.g., Ebbinghaus, 1885=1913). The spacing effect refers to the general finding that performance improves when repetitions of target items are presented in a distributed fashion rather than consecutively (e.g., Benjamin & Tullis, 2010; Cepeda et al., 2009; Cepeda, Vul, Rohrer, Wixted, & Pashler, 2008; Glenberg, 1976; Landauer & Bjork, 1978; Melton, 1967). The spacing effect has been observed in hundreds of empirical studies with children (e.g., Vlach, Sandhofer, & Kornell, 2008), college students (e.g., Cepeda et al., 2008; Karpicke & Roediger, 2010), and older adults either with or without diagnosed neuropathology (e.g., Balota, Duchek, Sergent-Marshall, & Roediger,

Figure 1. Illustration of the lag and retention interval (RI) manipulations used in the current experiment. Lag refers to the number of items occurring between the first two presentations. RI refers to the number of items occurring between the second and the third occurrences.

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2006; Hillary et al., 2003). At first glance, it seems odd that item memory would be enhanced as a function of the length of the lag between study repetitions (within the limits of the durability of items in memory), considering that item memory is usually attenuated as a function of the length of interval between study and test. In a study representative of the paradoxical effects of recency and spacing, Glenberg (1976) observed a recency effect in recognition memory at P2 and P3; hit rate at P2 decreased as a function of lag length and hit rate at P3 decreased as a function of length of the retention interval. In addition, Glenberg observed a spacing effect in recognition memory at P3; hit rate increased as a function of lag length when the interval between P2 and P3 was not too short. When item repetitions were too closely spaced, hit rate at P3 decreased as a function of lag length. Thus, for the short retention intervals, a recency effect (as a function of lag) occurred at P3 instead of a spacing effect. However, when the retention interval between the last two repetitions was relatively long, the benefit of spacing across the first two repetitions increased at P3. A number of explanations are available to account for the beneficial effects of distributed practice (e.g., see Benjamin & Tullis, 2010). At least three accounts (the recursive reminding hypothesis, the deficient processing hypothesis, and the retrieval difficulty hypothesis) are relevant to explaining spacing and recency effects in older adults. First, in the recursive reminding hypothesis, repetitions strengthen memory (Hintzman, 2004, 2010). When events or items are repeated, individual instances are necessarily distributed across presentations at different times. In Hintzman’s work, repetitions of an item activate previous repetitions (i.e., reminding). It can be argued that the benefits and phenomenological experience of reminding are absent under conditions in which a particular item is presented twice at a spacing of zero (massed practice) or at very short intervals in which items are temporally indistinguishable, because the first presentation was still in working memory at the time of the second presentation. When the spacing between item repetitions is greater (but not too long so as to exceed capacity), the second presentation makes contact with the first presentation through reminding, and strengthens item memory. In older adults, it is possible that such remindings serve to attenuate or remediate an age-related retrieval deficit. Second, in the deficient processing hypothesis, the length of the interval between repetitions is presumed to have a positive effect the efficiency of item processing at P2 (e.g., R. A. Bjork & Allen, 1970; Braun & Rubin, 1998; Cuddy & Jacoby, 1982; Greene, 1989). In this account, if the interval between two repetitions of an item is relatively

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short, relatively less processing effort is required for item recognition at P2. Thus, shorter lags produce traces that are relatively weaker than ones that are laid down at longer lags between item repetitions. Second, in the retrieval difficulty hypothesis, it is presumed that effortful item retrieval promotes or potentiates item memory at P2 (e.g., Benjamin & Tullis, 2010; Logan & Balota, 2008; Pavlik & Anderson, 2005). According to another account, the study-phase retrieval hypothesis, memory benefit of spacing has to do with recognizing items as repetitions at P2; this hypothesis goes to the point of explaining observed differences between distributed and massed practice (e.g., Braun & Rubin, 1998). Other theoretical models of distributed practice effects, especially variants of the prominent contextual and encoding variability hypothesis that emphasize the degree of change in item-context relations, do not address the subtle relations between age-related memory functioning and the spacing of item repetitions absent context manipulations of associative memory (e.g., see Benjamin & Tullis, 2010). Undoubtedly, optimal spacing benefits in continuous recognition involve a variety of intraindividual factors and task factors that influence item memorability at P2 (e.g., Pavlik & Anderson, 2005). In regard to age-related spacing effects, for example, the temporal aspects of item memorability and the degree to which an item trace persists are known to be age sensitive (e.g., Howard, Kahana, & Wingfield, 2006; Kahana, Howard, Zaromb, & Wingfield, 2002; Maddox, Balota, Coane, & Duchek, 2011). Maddox et al. used a continuous cued recall task to examine the role of forgetting in producing a benefit of expanded over equal-spaced retrieval schedules in young and older adults. In the continuous cued recall task used by Maddox et al., participants were given a word pair (e.g., horseJUMPED) for 4.5 s, and later given cued recall trials (horse-?) in which the first word in the pair served as a cue for recall of the associated target. Maddox et al. observed that the degree of benefit produced by expanded schedules depended on the extent to which the spacing conditions did not happen to exceed the limits of age-related forgetting in the early retrieval attempts. The temporal-span limits of remembering were substantially different for young adults and older adults; specifically, two intervening items between early retrieval attempts produced a substantial amount of forgetting in older adults, but up to five intervening items produced hardly any forgetting in young adults. Maddox et al. demonstrated that the memory benefits associated with spacing can be maximized by incrementally expanding lag lengths while not exceeding the limits of successful retrieval in older adults. Indeed, intervention studies that have used procedures

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designed to stretch item memory spans have demonstrated significant benefits in older adults (e.g., Bailey, Dagenbach, & Jennings, 2011; Jennings & Jacoby, 2003). However, it is important to point out that even unsuccessful retrieval attempts may enhance item learning and memory performance (e.g., Kornell, Hays, & Bjork, 2009). A substantial body of evidence suggests that item testing per se promotes memory (e.g., E. L. Bjork & Storm, 2011; Karpicke & Roediger, 2007; Storm, Bjork, & Storm, 2010; Tse, Balota, & Roediger, 2010). Thus, in the procedure of the current study, given that each item presentation is essentially a test that requires a response confidence rating, P2 is not only an assessment point but also serves as a reminder and as a stimulus event that may potentiate item memory to the extent that retrieval is difficult. Further, age-sensitive spacing effects may also be influenced by optimal or desired level of challenge or difficulty, such that the memory benefits associated with spaced retrieval may be strongest when retrieval is difficult (e.g., see Benjamin & Tullis, 2010; Logan & Balota, 2008; Onyper, Hoyer, & Cerella, 2008; White, Cerella, & Hoyer, 2007). Benjamin and Tullis (2010) incorporated the premise that the act of retrieval potentiates memory, and that the degree of potentiation is positively related to the difficulty of item retrieval in their statistical model of distributed practice. Consider also the findings from several event-related potential (ERP) studies of age-related differences in item processing during memory performance that lend support to the premise that item forgetting at P1 may potentiate later item memory performance (e.g., Rugg et al., 1997; Van Strien, Verkoeijen, Van der Meer, & Franken, 2007). Rugg et al. used ERPs and an accuracy measure in a continuous recognition procedure in which words were repeated twice at lags (retention intervals) of either 1 or 8–12. Young adults and older adults showed comparable decreases in percent correct as a function of lag. But the ERP data revealed age-related differences in repetition effects. Young adults showed repetition effects (attenuated N400) in both lag conditions, and these effects were smaller at the longer lags. The ERP data for older participants showed repetition effects only at the shorter lag. The lack of repetition effects at the longer lags in the ERP data of the older adults could mean that items at P2 were processed as if they were presented for the first time. The design of the current study permits a complete factorial description of the effects of lags and retention intervals on continuous recognition performance in young and older adults. In order to evaluate recognition memory largely independently of guessing, we collected recognition ratings on a 9-point scale and restricted our

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attention to the highest rating. It is expected that an age-related deficit in item memory will be observed at P2, expressed as lower response confidence ratings for older adults than young adults, consistent with age-general findings. Further, based on the hypothesis that item retrieval difficulty potentiates item memory, no age-related differences in confidence ratings are predicted at P3 if response confidence ratings at P2 are lower for older adults than for younger adults. This prediction is derived from the idea that older adults experience more difficulty compared with young adults in retrieving the item at P2 when the lag between P1 and P2 is longer. This decrease in the ability to retrieve the items at longer lags may result in better encoding as the items are presented the second time. Then, the spacing effect observed at P3 could be comparable in young and older adults because older adults encode the items presented at P2 with longer lags as well as their younger counterparts. METHODS Participants Fifty young adults were recruited from the human subjects pool of the Department of Psychology at Syracuse University and participated in exchange for course credits. Fifty-two older adults were recruited from the subject registry of the Adult Cognition Lab at Syracuse University. Young adult participants had a mean age of 18.78 years (SD ¼ 1.18) and had a mean educational level of 12.72 years (SD ¼ 1.03). Older adult participants had a mean age of 72.69 years (SD ¼ 5.94) and had a mean educational level of 14.90 years (SD ¼ 2.48). Older adults had a mean self-reported general health score of 2.4 (SD ¼ 0.81) using a scale from 1 (excellent) to 5 (poor). Materials Stimuli were English words, all nouns with four to eight letters. Word lists were constructed from the MRC Psycholinguistics Database (Coltheart, 1981). Words were presented one at a time in capital letters and at the center of a 19-inch monitor. Procedure Each participant received five blocks of words, and each block consisted of a list of 315 words. Word lists were systematically assembled

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using a list construction algorithm that enabled the manipulation of the spacing between the three repetitions of items. The lists that were used in the current study were sampled from all possible lists that met the selected criteria for the lag manipulation; lists that did not meet the criteria were rejected. In the accepted lists, sets of 78 words were presented three times and 65 words were presented only once as filler items. On average, 151 words (M ¼ 150.91, SD ¼ 2.04) were given at Presentation 1 (P1). Of these words, on average, 86 words (M ¼ 85.70, SD ¼ 1.85) were presented twice (P2) and 78 words (M ¼ 78.38, SD ¼ 0.69) were presented three times (P3). There were no more than 20 words in each five-block session that were presented for a second time across blocks, and these words were not repeated more than twice. Lags were chosen to represent ranges of 1–3, 6–10, and 40–56 within blocks; retention intervals were chosen to represent ranges of 6–10, 16–22, and 40–45 within blocks. To avoid the possible confounding of practice-related changes in response criteria and the placement of items within a block, the list construction algorithm ensured that the proportion of repeated items was between 45 and 55 percent within each of 10 equally spaced bins. Thus, in each of 10 bins, on average half of the items were presented for the first time and half were repeated items. Only those words that were presented three times within a block were analyzed. On average, each participant was presented with 43 words in each lag=retention interval category. For each word, participants were instructed to rate their confidence that the item had previously been presented using a scale ranging from 1 (certainly new) to 9 (certainly old). As a guideline, participants were advised to use a rating of 1–4 for the first presentation of a word, a rating of 6–9 for repeated words, and a rating of 5 if they had no clue about whether or not the word was a repeat. Stimuli were displayed until the participant responded. Participants received on-screen messages to avoid making too-slow responses immediately after a response longer than 7.5 s, and to avoid making too fast responses immediately after a response shorter than 200 ms. The mean response time across all participants and all lag and retention ranges was 1462 ms (SD ¼ 945). RESULTS The data from Block 1 were considered practice, and were discarded. The distributions of the confidence ratings taken from Blocks 2 to 5 were sorted by lag and retention interval for P1, P2, and P3; these

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Figure 2. Response distributions at P1, P2, and P3 for young (left panel) and older (right panel) adults.

data are shown in Figure 2 by age group. The data of primary interest were the P(9) responses at P2 and P3. The P(9) data at P1, P2, and P3 were fit to separate, multilevel linear regression models with lags and retention intervals as withinsubject factors and age as a between-subjects factor. Lag, retention interval, the interaction terms, and the intercept were all allowed to vary across participants. Log-transformed response times at P2 and P3 were fit to the same multilevel regression linear model. The presentation of the results is organized in terms of the effects observed at P1, P2, and P3. Confidence Ratings at P1 Table 1 shows P(9) responses at P1 by lag and retention interval for each age group. Data are arrayed by lag and retention interval ranges for ease of comparison with the data in Tables 2 and 3. The data at P1 should not show reliable effects of lag or retention interval because these variables refer to the numbers of items occurring between P1 and P2, and between P2 and P3, respectively. Because the correct response to the first presentation of an item should be P(1), or ‘‘certainly no,’’ the data shown in Table 1 are false alarms. Results of the multilevel model revealed that P(9) did not vary as a function of lag or retention interval.1 There was a main effect of age, 1 The absence of any reliable effects of lag and retention interval at P1 can be taken to suggest the absence of changes in response bias across the test session.

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Table 1. Mean P(9) responses at P1

Retention interval 6–10 16–22 40–45

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RI mean

Young

Old

Lag

Lag

1–3

6–10

40–56

Lag mean

1–3

6–10

40–56

Lag mean

.07 (.01) .08 (.01) .07 (.01) .07 (.01)

.08 (.01) .08 (.01) .09 (.01) .08 (.01)

.07 (.01) .09 (.01) .08 (.01) .08 (.01)

.07 (.01) .08 (.01) .08 (.01) .08 (.01)

.04 (.01) .04 (.01) .04 (.01) .03 (.01)

.04 (.01) .04 (.01) .04 (.01) .04 (.01)

.04 (.01) .04 (.01) .04 (.01) .03 (.01)

.04 (.01) .04 (.01) .04 (.01) .04 (.01)

Note. Data are arrayed by lag and retention interval ranges for comparisons with Tables 2 and 3; data should not differ by lag and retention interval ranges because these variables refer to the effects of the numbers of items occurring between P1 and P2, and between P2 and P3, respectively. Entries indicate false-alarm rates because all of the words are ‘‘new’’ at P1 and P(9) is the highest confidence ‘‘old’’ response. Numbers in parentheses are standard errors of the mean.

F(1, 606) ¼ 7.93, p < .01; false-alarm rates were higher for young adults (M ¼ .08, SE ¼ .01) than for older adults (M ¼ .04, SE ¼ .01, d ¼ .55). Table 2. Mean P(9) responses at P2 by lag and retention interval ranges for young and older participants

Retention interval 6–10 16–22 40–45 RI mean

Young

Old

Lag

Lag

1–3

6–10

40–56

Lag mean

1–3

6–10

40–56

Lag mean

.85 (.03) .84 (.03) .83 (.03) .84 (.03)

.76 (.03) .76 (.03) .77 (.03) .76 (.03)

.68 (.04) .68 (.04) .68 (.04) .68 (.04)

.76 (.03) .76 (.03) .76 (.03) .76 (.03)

.85 (.04) .84 (.04) .84 (.04) .84 (.03)

.67 (.03) .64 (.03) .66 (.03) .65 (.03)

.50 (.03) .51 (.03) .49 (.04) .50 (.03)

.67 (.03) .66 (.03) .66 (.03) .66 (.03)

Note. Numbers in parentheses are the standard errors of the means. Lag refers the numbers of items that were presented between P1 and P2. Retention interval refers to the numbers of items that were presented between P2 and P3, and thus any influence on the data in this Table is uncontrolled. Probability of highest confidence responses decreases as a function of lag length, especially for older adults (i.e., entries in bold).

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Table 3. Mean P(9) responses at P3 by lag and retention interval ranges for young and older participants

Retention interval 6–10 16–22

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40–45 RI Mean

Young

Old

Lag

Lag

1–3

6–10

40–56

Lag mean

1–3

6–10

40–56

Lag mean

.82 (.04) .78 (.04) .74 (.04) .78 (.04)

.84 (.04) .80 (.04) .78 (.04) .81 (.04)

.84 (.04) .82 (.04) .77 (.04) .81 (.04)

.83 (.04) .80 (.04) .76 (.04) .80 (.04)

.79 (.04) .69 (.04) .61 (.04) .70 (.04)

.81 (.04) .74 (.04) .67 (.04) .74 (.04)

.79 (.04) .73 (.04) .67 (.04) .73 (.04)

.79 (.04) .72 (.04) .65 (.03) .72 (.03)

Note. Entries in parentheses are the standard errors of the mean. For young and older adults, the probability of highest confidence responses increased from lag ranges of 1–3 to 6–10 (i.e., a spacing effect, entries in bold).

Confidence Ratings at P2 Table 2 shows mean P(9) responses at P2 by lag and retention interval for each age group. Because the correct response at P2 is ‘‘certainly old,’’ the data in Table 2 are hit rates at the most stringent criterion. It can be seen that the P(9) responses decreased monotonically as a function of lag in both age groups. The results from the multilevel model revealed a main effect of lag, F(2, 606) ¼ 97.82, p < .01. Simple contrasts showed that the hit rate for lag range 1–3 was greater than the hit rate for lag range 6–10, F(1, 606) ¼ 163.02, p < .01, d ¼ .55, and that the hit rate for lag range 6–10 was greater than the hit rate for lag range 40–56, F(1, 606) ¼ 141.19, p < .01, d ¼ .46. The interaction between lag range and age was significant, F(2, 606) ¼ 12.81, p < .01, indicating that the decrease in hit rates as a function of length of the lag range was steeper for older adults than for younger adults. Contrasts revealed that the age difference in hit rates was significant at lag range 40–56, F(1, 606) ¼ 7.62, p ¼ .01, and approaches significance at lag range 6–10, F(1, 606) ¼ 2.98, p ¼ .08. Thus, at P2, memory confidence decreased in both age groups as the lag length between P1 and P2 increased (i.e., a recency effect), and the decrease in confidence was greater for older participants than for younger participants when the lags were between 40 and 56.2 2 The same pattern of results was obtained in an analysis that excluded the primacy buffer in each block. The primary buffer consisted of all of the occurrences of the first 10 items on each list.

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We explored the possibility that these findings were an artifact of age-related differences in response criteria per se by fitting the same multilevel model to the data from the subsamples of young adults (n ¼ 9) and older adults (n ¼ 9) that did not differ in terms of false alarms at P1. This analysis examined the effects of age, lag, and the interaction of age and lag on P(9) responses at P2, and revealed no main effect of age, a main effect of lag, F(2, 96) ¼ 42.95, p < .001, and an interaction between age and lag, F(2, 96) ¼ 7.42, p ¼ .001. Results of this analysis reveal no evidence to suggest that the age-related recency deficit was an artifact of response bias.

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Response Latencies at P2 As can be seen in Figure 3, mean response times at P2 lengthened as the lag ranges between P1 and P2 increased in both age groups, F(2, 98) ¼ 139.98, p < .01. The lengthening of response times at P2 as a function of lag is consistent with previous reports of lower ratings of response confidence at longer lags (e.g., Hockley, 1982; Ratcliff & Murdock, 1976; Ratcliff & Starns, 2009). It is important to note that the lengthening of mean response times as a function of lag length is associated with an increase in the usage of the ratings other than P(9); participants used responses of 1–8 more frequently and used P(9) less frequently at the longer lags. Consistent with Ratcliff and Murdock (1976) and others, response times were longer for

Figure 3. Mean response times at P2 as a function of lag for younger and older adults. Older adults showed longer response times at P2. Error bars represent the standard error of the mean.

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lower-confidence ratings at the middle of the scale and response times were shorter for high-confidence ratings, F(8, 517) ¼ 93.09, MSE ¼ 0.06, p < .01. Response times were characteristically longer for older participants (M ¼ 1410 ms) than for younger participants (M ¼ 1107 ms), F(1, 98) ¼ 42.36, p < .01. Note that because the lag between P1 and P2 can be expressed either as units of time or as numbers of intervening items, these data show that the time taken to respond to a lag of n items was longer for older adults than for younger adults. As can be seen in Figure 3, the lengthening of response times due to retrieval difficulty was greater for the older participants than the younger participants. Response times for the older adults were disproportionately longer at the longer lags, compared with young adults participants. The age and lag interaction was significant, F(2, 98) ¼ 7.66, p < .01. Confidence Ratings at P3 Table 3 shows mean P(9) responses by lag range and retention interval for each age group. The statistical model confirmed the observations that confidence ratings are lower for less recent items and that confidence ratings decline more for older adults than for younger adults as a function of lag. Mean P(9) responses collapsed across lag ranges decreased as a function of retention intervals for both age groups, F(2, 606) ¼ 60.67, p < .01. Simple contrasts showed that hit rates were higher for retention interval (RI) 6–10 than for RI 16–22, (F(1, 606) ¼ 68.79, p < .01, d ¼ .21); further, hit rates were higher for RI 16–22 than for RI 40–45 (F(1,606) ¼ 75.15, p < .01, d ¼ .20). The age and retention interval interaction was significant, F(2, 606) ¼ 7.47, p < .01. The decrease in the hit rate from RI 6–10 to RI 16–22 was steeper for older adults than for younger adults, F(1, 606) ¼ 10.33, p < .01. And the decrease in hit rate from RI 16–22 to RI 40–45 was steeper for older adults than for younger adults, F(1, 606) ¼ 7.34, p < .01. In addition to the recency effect with respect to RI, a spacing effect with respect to lag was observed. As can be seen in Table 3, P(9) averaged across retention intervals increased more for the longer lags for the shorter lags, F(2, 606) ¼ 28.09, p < .01. Inspection of the data by lag ranges revealed that the P3 hit rate was lower for lags 1–3 than for longer lag ranges, F(1, 606) ¼ 51.25, p < .01, d ¼ .16. Thus, retention was better at P3 as the number of items intervening between P1 and P2 increased. As can be seen in Table 3, hit rates did not differ significantly at the shortest retention interval; the interaction of retention interval and lag was significant, F(4, 606) ¼ 4.17, p < .01. The spacing

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Figure 4. Left panel: Mean P(9) responses at P2 as a function of lag for younger and older adults. Recency effect was larger for older adults than for younger adults. Right panel: Mean P(9) responses at P3 as a function of lag for younger and older adults. The spacing effect was roughly parallel for younger and older adults. In both panels, P(9) responses for each lag range were averaged over all the retention intervals. Error bars represent the standard error of the mean.

effect was observed at the longer retention interval ranges (for RI 16–22, F(1, 606) ¼ 23.73, p < .01 and for RI 40–45, F(1, 606) ¼ 44.85, p < .01). We again explored the possibility that findings were an artifact of age-related differences in response criteria by conducting separate fits of the multilevel model to the data from the subsamples of young adults (n ¼ 9) and older adults (n ¼ 9) that did not differ in terms of false alarms at P1. This analysis examined the effects of age, lag, retention interval, and the interaction of age and retention interval on P(9) responses, and revealed effects of retention interval, F(2, 96) ¼ 22.49, p < .001, lag, F(2, 96) ¼ 6.04, p < .01, and an interaction between age and retention interval, F(2, 96) ¼ 4.9, p < .01. Figure 4 depicts the older and young participants mean P(9) averaged over the longer retention interval ranges as a function of lag range at P2 (left panel) and P3 (right panel). Figure 4 shows an interaction between lag range and age at P2 (left panel) but no interaction at P3 (right panel). Confidence ratings decline more for older adults than for young adults at P2 but ratings are not different for the young and older adults at P3 as a function of lag for the longer retention intervals.3 3

A similar pattern of qualitative results was obtained in an analysis that excluded participants who had a probability higher than .9 of responding 9 to the second presentation of the words.

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DISCUSSION This experiment produced a complete set of data that describes age-related effects in the relations between recency and spacing and item recognition memory in a continuous recognition procedure. Word lists were systematically assembled using a list construction algorithm that enabled the manipulation of the spacing between the three repetitions of items. The findings were clear. The results revealed recency effects at P2 and at P3 for both young adults and older adults, and an age-related deficit in the effects of lag and retention interval on item memory. That is, compared with young adults, older adults showed larger declines in the probability of responding ‘‘certainly old’’ as a function of lag at P2, and larger declines in the probability of responding ‘‘certainly old’’ as a function of retention interval at P3. In addition to these age-sensitive recency effects, beneficial effects of spacing were observed for young adults and older adults at P3. The probability of giving high confidence responses at P3 increased from the shortest lag ranges to the longer ones. These findings suggest that age-related item processing difficulties may serve to potentiate item memory. Along these lines, Maddox et al. suggested that age-related differences in forgetting rates produce the benefits of expanded over equal-spaced retrieval in older adults. In the discussion below, we briefly consider procedural differences between studies as we compare the findings of the current study with findings from related studies. Next, we consider possible explanations, and take the position that the retrieval difficulty hypothesis and the processing deficit hypothesis are supported by our findings—the seemingly paradoxical observations of an age-related deficit in the recency effects at P2 and P3, and an age-equivalent benefit of spacing at P3. As reviewed earlier, findings from previous age-comparative studies of item memory in continuous recognition tasks reveal an age-related deficit associated with the length of the retention interval (e.g., Ferris et al., 1980; Le Breck & Baron, 1987; Poon & Fozard, 1980; Rugg et al., 1997). Of these studies examining age effects in continuous recognition, only Rugg et al. examined spacing effects and recency effects in young and older adults. Rugg et al. found roughly age-equivalent benefits due to the increased spacing between repetitions. Age-equivalent spacing effects have been observed in several studies of continuous cued recall (e.g., Balota et al., 1989, 2006; Logan & Balota, 2008), but memory performance in these studies involved associative binding as well as item processing. The findings of the present study add uniquely to the literature in that both

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recency and spacing effects were observed in item recognition memory. One limitation of our findings is that the effect sizes related to age benefits were small. That is, for the age differences at P2, Cohen’s d for lags 1–3, 6–10, and 40–56 were .01, .49, and .82, respectively. For the age differences at P3, Cohen’s d for lags 1–3, 6–10, and 40–56 were .47, .37, and .46, respectively. The pool of theoretical explanations that can reasonably account for the observation of age-equivalent memory benefits associated with the spacing of item repetitions is small. Hintzman’s (2004, 2010) concept of recursive reminding provides a useful account of spacing effects in memory studies, and provides a general account of the spacing effects observed in the present study. The concept of recursive reminding is based on findings with young adults demonstrating that repetition dissociates from exposure duration and other factors to strengthen memory (Hintzman, 2004, 2010). When events or items are repeated, individual instances are necessarily distributed across presentations at different times. Depending on spacing, repetitions of an item can trigger recollections of previous instances of the item (i.e., reminding) that are available for later retrieval. In their statistical model of the distributed practice, Benjamin and Tullis (2010) drew on Hintzman’s conception of a recursive reminding mechanism. The Benjamin and Tullis model is based on the principle that the second presentation of the item elicits reminding of the first presentation. Memory for the subsequent presentations is potentiated because the traces include memory for previous presentations. These principles suggest that retrieval during study repetitions benefits memory to the degree that it is difficult. The benefits and phenomenological experience of reminding are absent under conditions in which a particular item is presented twice at a spacing of zero (massed practice) or at very short intervals in which items are temporally indistinguishable, because the first presentation was still in working memory at the time of the second presentation. Under conditions in which the spacing between item repetitions is greater (but not too long so as to exceed capacity), the second presentation makes contact with the first presentation through reminding, and results in the experience (recollection) that the item occurred more than once. Our results can be taken as support for the concept of recursive reminding as it applies in general terms to age-comparative data. Theories that emphasize the role of age-related differences in item processing difficulty as an antecedent factor that drives subsequent item processing retention also apply to the findings of the present study. Indeed, it is our view that theories of distributed practice that invoke deficient processing and retrieval difficulty as antecedents of

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enhanced retention provide the most plausible type of account for the age-equivalent spacing effects observed in the findings reported here. However, such an account requires further testing and refinement. Specifically, it remains to be determined if young and older adults derive different amounts of memory benefit from the spacing of the item repetitions per se or from the demands and motivations associated with the retrieval process. These potentially age-sensitive sources of the effect should be teased apart in future work. Further, item-level analyses that allow examination of the effects of processing difficulty for a particular item on its subsequent memory would be useful for explicating the bases of the relations between item processing difficulty and the spacing of item repetitions. REFERENCES Bailey, H., Dagenbach, D., & Jennings, J. M. (2011). The locus of the benefits of repetition-lag memory training. Aging, Neuropsychology, and Cognition, 18, 577–593. doi: 10.1080=13825585.2011.591921 Balota, D. A., Duchek, J. M., & Paullin, R. (1989). Age-related differences in the impact of spacing, lag, and retention interval. Psychology and Aging, 4, 3–9. doi: 10.1037=0882-7974.4.1.3 Balota, D. A., Duchek, J. M., Sergent-Marshall, S. D., & Roediger, H. L., III. (2006). Does expanded retrieval produce benefits over equal-interval spacing? Explorations of spacing effects in healthy aging and early stage Alzheimer’s disease. Psychology and Aging, 21, 19–31. doi: 10.1037=0882-7974.21.1.19 Benjamin, A. S., & Tullis, J. (2010). What makes distributed practice effective? Cognitive Psychology, 61, 228–247. doi: 10.1016=j.cogpsych.2010.05.004 Bjork, E. L., & Storm, B. C. (2011). Retrieval experience as a modifier of future encoding: Another test effect. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37, 1113–1124. doi: 10.1037=a0023549. Bjork, R. A., & Allen, T. W. (1970). The spacing effect: Consolidation or differential encoding. Journal of Verbal Learning and Verbal Behavior, 9, 567–572. doi: 10.1016=S0022-5371(70)80103-7 Braun, K., & Rubin, D. C. (1998). The spacing effect depends on an encoding deficit, retrieval and time in working memory. Evidence from once-presented words. Memory, 6, 37–65. doi: 10.1080=741941599 Cepeda, N. J., Coburn, N., Rohrer, D., Wixted, J. T., Mozer, M. C., & Pashler, H. (2009). Optimizing distributed practice: Theoretical analysis and practical implications. Experimental Psychology, 56, 236–246. doi: 10.1027=1618-3169.56.4.236 Cepeda, N. J., Vul, E., Rohrer, D., Wixted, J. T., & Pashler, H. (2008). Spacing effects in learning: A temporal ridgeline of optimal retention. Psychological Science, 19, 1095–1102. doi: 10.1111=j.1467-9280.2008.02209.x Coltheart, M. (1981). The MRC Psycholinguistic Database. The Quarterly Journal of Experimental Psychology A: Human Experimental Psychology, 33A, 497–505.

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