Mar 22, 2021 · An everyday example of proactive interference is when you get a new mobile phone number, as your memory for your old number disrupts your attempts to remember your new number. Keppel and Underwood (1962) examined the effect of proactive interference on long-term memory, in an experiment that resembles Peterson and Peterson (1959). ... In a later experiment, Szpunar, McDermott, and Roediger (2008) directly tested the idea that testing protects against the buildup of proactive interference. In two experiments, subjects studied five lists composed of words that were interrelated across lists or words that were unrelated to one another. ... Oct 10, 2023 · This is an example of retroactive interference. Evaluation. Although proactive and retroactive interference are reliable and robust effects, there are a number of problems with interference theory as an explanation of forgetting. First, interference theory tells us little about the cognitive processes involved in forgetting. ... Results from two experiments revealed that prior experience with proactive interference (PI) diminished PI’s effects for both young and older adults. Participants were given two rounds of experience, with different materials, in a situation that produced PI. ... That theory fails to incorporate a cue-specific basis for interference. Participants choose to provide lower judgments across the experiment on the basis of a more general belief about list-wise PI. They base their judgments on this general belief even when there is no discernable interference present (Experiment 2). ... Feb 12, 2024 · Laboratory experiments play a crucial role in investigating proactive interference by meticulously controlling variables in controlled settings to replicate memory scenarios. Field research, on the other hand, ventures into real-world environments, offering a more ecologically valid understanding of how interference impacts memory retention in ... ... constant and tested whether proactive interference effects varied with manipulations of similarity along other dimen-sions. Together, the results point to similarity along task-relevant dimensions as a critical factor in producing proac-tive interference. Experiment 1 The purpose of Experiment 1 was to test whether recent ... ference. Here we review the results of experiments using approaches from cognitive neuroscience to reveal a pattern of brain activity that is a signature of proactive interference. Many of these results derive from a single paradigm that requires one to resolve interference from a previous experi-mental trial. ... Nov 19, 2010 · In three experiments, we examined the mechanisms by which prior experience with proactive interference (PI) diminished its effects. Cued recall tasks conforming to an A–B, A–D paradigm were used to induce PI effects. Experiment 1 showed that reduced PI was not due to a reduction in attention to the source of PI. Experiment 2 revealed that participants’ awareness of PI effects on memory ... ... May 1, 2012 · The proactive-interference functions observed in our experiment have implications for the vast majority of memory studies using small stimulus sets, because proactive interference rapidly builds and saturates (e.g., Keppel & Underwood, 1962). ... ">

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Proactive Interference - Keppel and Underwood (1962)

Last updated 22 Mar 2021

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Proactive interference occurs when old information stored in long-term memory, interferes with the learning of new information.

This usually occurs when the new information is similar to the old information. An everyday example of proactive interference is when you get a new mobile phone number, as your memory for your old number disrupts your attempts to remember your new number.

Keppel and Underwood (1962) examined the effect of proactive interference on long-term memory, in an experiment that resembles Peterson and Peterson (1959).

Participants were presented with meaningless three-letter consonant trigrams (for example, THG) at different intervals (3, 6, 9 second, etc). To prevent rehearsal the participants had to count backwards in threes before recalling.

Keppel and Underwood found that participants typically remembered the trigrams that were presented first, irrespective of the interval length.

They concluded that the results suggest proactive interference occurred, as memory for the earlier consonants, which had transferred to long-term memory, was interfering with the memory for new consonants, due to the similarity of the information presented.

  • Proactive Interference
  • Retroactive Interference
  • Keppel and Underwood (1962)
  • Long-Term Memory

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Proactive and Retroactive Interference: Definition and Examples

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

Interference is an explanation for forgetting in long-term memory, which states that forgetting occurs because memories interfere with and disrupt one another; in other words, forgetting occurs because of interference from other memories (Baddeley, 1999).

This idea suggests that information in long-term memory may become confused or combined with other information during encoding thus distorting or disrupting memories.

There are two ways in which interference can cause forgetting :

1. Proactive interference (pro=forward) occurs when you cannot learn a new task because of an old task that had been learnt.  When what we already know interferes with what we are currently learning – where old memories disrupt new memories.
2. Retroactive interference (retro=backward) occurs when you forget a previously learnt task due to the learning of a new task. In other words, later learning interferes with earlier learning – where new memories disrupt old memories.

Proactive and retroactive Interference is thought to be more likely to occur where the memories are similar, for example: confusing old and new telephone numbers.

Chandler (1989) stated that students who study similar subjects at the same time often experience interference.

Previous learning can sometimes interfere with new learning (e.g. difficulties we have with foreign currency when travelling abroad).

Also, new learning can sometimes cause confusion with previous learning. (Starting French may affect our memory of previously learned Spanish vocabulary).

Key study: Postman (1960)

Aim : To investigate how retroactive interference affects learning.  In other words, to investigate whether information you have recently received interferes with the ability to recall something you learned earlier.

Method : A lab experiment was used. Participants were split into two groups.  Both groups had to remember a list of paired words – e.g. cat – tree, jelly – moss, book – tractor.

The experimental group also had to learn another list of words where the second paired word if different – e.g. cat – glass, jelly- time, book – revolver.  The control group was not given the second list. All participants were asked to recall the words on the first list.

Results : The recall of the control group was more accurate than that of the experimental group.

Conclusion : This suggests that learning items in the second list interfered with participants’ ability to recall the list.  This is an example of retroactive interference.

Although proactive and retroactive interference are reliable and robust effects, there are a number of problems with interference theory as an explanation of forgetting.

First, interference theory tells us little about the cognitive processes involved in forgetting.  Secondly, the majority of research into the role of interference in forgetting has been carried out in a laboratory using lists of words, a situation which is likely to occur fairly infrequently in everyday life (i.e. low ecological validity).  As a result, it may not be possible to generalize from the findings.

Baddeley (1990) states that the tasks given to subjects are too close to each other and, in real life; these kinds of events are more spaced out.

Nevertheless, recent research has attempted to address this by investigating “real-life” events and has provided support for interference theory.

However, there is no doubt that interference plays a role in forgetting, but how much forgetting can be attributed to interference remains unclear (Anderson, 2000).

Anderson, J. R. (2000). Learning and memory: An integrated approach . New York: John Wiley & Sons.

Baddeley, A. D., & Logie, R. H. (1999). Working memory: The multiple-component model. In A. Miyake & P. Shah (Eds.), Models of working memory (pp. 28±61). Cambridge, UK: Cambridge University Press.

Chandler, C. C. (1989). Specific retroactive interference in modified recognition tests: Evidence for an unknown cause of interference. Journal of Experimental Psychology: Learning, Memory, and Cognition , 15, 256-265.

Underwood, B. J., & Postman, L. (1960). Extraexperimental sources of interference in forgetting. Psychological Review, 67(2) , 73.

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Learning to diminish the effects of proactive interference: Reducing false memory for young and older adults

Larry l jacoby, christopher n wahlheim, matthew g rhodes, karen a daniels, chad s rogers.

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Correspondence concerning this article should be addressed to L. L. Jacoby, Department of Psychology, Washington University, St. Louis, MO 63130 ( lljacoby@artsci.wustl.edu ).

Results from two experiments revealed that prior experience with proactive interference (PI) diminished PI’s effects for both young and older adults. Participants were given two rounds of experience, with different materials, in a situation that produced PI. Comparisons with a control condition showed that the effects of PI on accuracy and on high-confidence intrusion errors (false memory) were reduced on the second round, as compared with those on the first. Also, the ability of confidence to diagnose accuracy of responding improved across rounds. Effects of prior experience with PI depended on feedback given at the time of test (Experiment 1). At least in part, the diminishment of PI resulted from participants’ allocating more attention to interference items during study in the second round than in the first (Experiment 2). Implications of the results for interpreting age differences in PI and false memory are discussed.

Proactive interference (PI) refers to the reduction in memory performance for recently learned information resulting from the prior learning of related materials and has been shown to play an important role in forgetting (for a review, see Anderson & Neely, 1996 ). Investigations of PI have traditionally used a paired-associate learning procedure, in which interference is created by holding cues constant, with the responses being changed between two lists (A–B, A–D). Performance in this interference condition is compared with that in a control condition for which both cues and responses are changed between lists (A–B, C–D) or for which participants first “rest” and then learn cueresponse pairs (rest, C–D). The magnitude of PI effects is indexed as the difference in cued-recall accuracy between the control and interference conditions on the final test.

Errors resulting from PI can take the form of a first-list response intruding when participants are asked to produce the response paired with a cue in the second list. Older adults are more susceptible to such interference than are young adults because of their lessened ability to avoid making erroneous responses that have been made highly probable by prior experience (see, e.g., Hasher, Zacks, & May, 1999 ; Hay & Jacoby, 1999 ; May, Hasher, & Kane, 1999 ). Older adults are also more likely to produce intrusion errors that result from PI with high levels of confidence (for a review, see Dodson & Krueger, 2006 ; Jacoby, Bishara, Hessels, & Toth, 2005 ; Jacoby & Rhodes, 2006 ; Kelley & Sahakyan, 2003 ). Confidence in intrusion errors is important because older adults’ high confidence in such errors makes them vulnerable to memory slips and memory scams ( Hay & Jacoby, 1999 ; Jacoby et al., 2005 ). An intrusion error is likely to be acted on only if it is held with a high level of confidence. For example, memory for taking a daily medicine yesterday might intrude as a high-confidence memory of having taken the medicine today, a false memory that results in failure to take the medicine today.

The goal of our experiments was to determine whether PI could be reduced by providing participants with multiple experiences dealing with PI. Although the importance of PI effects is widely known, prior research has not examined whether people can adapt their processing in ways that allow them to avoid or, at least, diminish such effects. It is of interest to determine whether older (as well as younger) adults can do so. Older adults have been held to be deficient in inhibitory processes (e.g., Hasher et al., 1999 ), less likely to engage in deeper processing of the sort necessary for memory (e.g., Craik & Byrd, 1982 ), and less able to engage in recollection as a means of avoiding interference effects (e.g., Hay & Jacoby, 1999 ). Deficits of these sorts might result in older adults’ being less able to benefit from prior experience with PI than are young adults.

Investigation of the effects of prior experience with interference on false memory has also been neglected. Although there have been many findings of false memory that originates from interference, it has not been determined whether such effects would persist across extended experience with the procedures used to produce them. We were particularly interested in determining whether older adults could learn to avoid false memories in the form of high-confidence intrusion errors that result from interference effects. Success in decreasing older adults’ susceptibility to PI and in reducing false memories resulting from PI would increase understanding of the bases for PI, as well as of age-related differences in memory, and would potentially have import for applied purposes.

To investigate effects of experience, we examined PI across a pair of lists (A–B, A–D for interference items), presented a pair of two new lists (E–F, E–G), and tested again for PI. The effects of multiple experiences dealing with PI were examined by comparing both accuracy and confidence on the second encounter with PI to results from the first encounter with PI.

We employed a procedure that was introduced by Hay and Jacoby (1996) . Specifically, the participants were first exposed to a list of semantically related word pairs (e.g., knee–bone), with each pair being presented three times. Following this training phase, the participants studied a list of word pairs. A third of the studied pairs (facilitation items) were identical to those presented during the training phase (e.g., knee–bone). For another third of the items (interference items), the right-hand member of a studied pair differed from that of a pair that had been presented during the training phase (e.g., knee–bend). These interference items were characterized by high levels of PI and are thus of primary interest. The remaining third of the studied pairs (control items) had not been presented during the training phase. Following the study phase, the participants were given a cued recall test and made a confidence judgment for each item. Test items consisted of a cue word and word fragment that could be completed with either the target or the alternate response that appeared during the training for interference items (e.g., knee–b_n_).

The test procedure of presenting a cue word along with a fragment of the response was meant to restrict responses to the target word and the alternate word that would serve to complete the fragment with an associatively related word. This was intended to increase PI and allow us to better examine effects of PI on intrusion errors. Including both facilitation and interference pairs within a list accords with experience outside the laboratory, in that one usually encounters cues requiring responses that are consistent with their prior responses inter-mixed with those for which prior experience serves as a source of PI. Intermixing facilitation and interference pairs was expected to increase PI. Also, including facilitation items discourages a strategy of generating both responses to a cue and then producing the less familiar one as a means of avoiding interference effects. Adopting that strategy might enhance performance on interference pairs but would reduce accuracy for facilitation pairs.

In order to improve accuracy and reduce high-confidence intrusions, half of the participants were provided with feedback following each test trial (Experiment 1; cf. Rebok & Balcerak, 1989 ). The feedback was structured in a manner that depended on confidence judgments. Specifically, participants were instructed to treat each confidence judgment as a wager that they had correctly recalled the studied item. A running score was made visible on all trials. Participants were told that, for each correct answer reported, their point total would increase by a number equivalent to their confidence rating, whereas each incorrect answer would decrease their score by that same number. We expected that providing feedback in this way would serve to diminish the effects of interference and likewise reduce reported confidence when intrusions were produced. Participants were administered two rounds of the procedure, with different materials being used in each round, allowing a comparison of performance for the first versus second round of testing. Another group received the same procedure, with the exception that they did not receive feedback. Participants in the no-feedback condition were simply instructed to make confidence judgments without being told to treat those judgments as a wager. We expected the presence of feedback to be important, particularly for older adults. Older adults were expected to be more likely to produce high-confidence intrusion errors than were young adults and, therefore, to be more reliant on feedback to reveal their errors.

As was anticipated, the results of Experiment 1 revealed that prior experience with PI did indeed diminish its effects for both older and young adults. Having had prior experience with PI, older adults were dramatically less likely to produce false memories in the form of high-confidence intrusion errors.

We conducted Experiment 2 in order to gain insight into the means by which experience with PI allowed participants to diminish its effects.

EXPERIMENT 1

Participants.

Forty-eight young and 48 older adults were recruited from the Washington University Psychology Department subject pool. Participants in each age group were randomly assigned to the two feedback conditions (24 participants each). The mean age did not differ significantly between the feedback and no-feedback conditions for either older (74.58 vs. 75.58 years) or young adults (19.92 vs. 19.13 years). Participants were tested individually and received course credit (young adults only) or $10 per hour.

Design and Materials

A 2 (feedback: feedback vs. no-feedback) × 3 (item type: facilitation vs. control vs. interference) × 2 (round: 1 vs. 2) × age (young vs. older) mixed design was used. Item type and round were manipulated within subjects; feedback and age were between-subjects variables.

Materials consisted of 156 three-word sets. Each set contained a cue word (e.g., knee) and two related responses (e.g., bone, bend). Groups were created such that, across items, the average length and strength of association of each response with the cue was equated. Both responses could complete the same word fragment (e.g., b_n_). Six groups of 24 sets served as critical items; the remaining sets served as buffers. Each group was balanced for frequency and length of cues and responses. The groups were counterbalanced across conditions, so that each occurred equally often in each of the within-subjects conditions.

Item types were created by varying the relationship of the pairs in the training (List 1) and study (List 2) lists. For facilitation items, the cues and responses were the same in Lists 1 and 2. For the interference items, the cues were the same in both lists, but the responses changed from List 1 to List 2 (e.g., knee–bone, knee–bend). Control items were only presented in the study list. Test items consisted of a cue word and word fragment that could be completed with either the target or an alternate response that appeared during training for interference items (e.g., knee–b_n_).

On each round, List 1 consisted of 48 pairs presented three times each (144 total), and List 2 consisted of 24 items from each of the three item types (72 total). Both lists were presented in random order. An additional three pairs were presented at the beginning and end of the study list to serve as primacy and recency buffers. Test lists contained 24 items of each type (72 total) and were presented in a fixed random order with the restriction that no more than three items from the same condition were presented consecutively.

The training phase (List 1) occurred first. The participants were told that they would see word pairs that would be repeatedly presented and that they were to read each pair aloud. Pairs were presented for 2 sec each, followed by a 1,000-msec interstimulus interval (ISI). After List 1 was completed, participants began the study phase (List 2). They were told that they would see word pairs that they would need to remember for a later memory test and were instructed to read each pair aloud. Each pair was presented for 2 sec, followed by a 1,000-msec ISI.

At the time of test, participants were told that a cue paired with a word fragment would be presented (e.g., knee–b_n_). They were instructed to complete the fragment with the word that was paired with the cue word in the study phase. Participants were given 10 sec to provide a response aloud. Next, they were asked to provide a confidence rating on a scale from 1 ( not very confident ) to 5 ( very confident ) that the item had been studied in List 2. Participants were encouraged to use the full range of the scale. Four practice trials were given prior to test. All responses were recorded by the experimenter.

For participants in the no-feedback condition, a new test item was presented, following each confidence rating. In contrast, participants in the feedback condition were given corrective feedback following each item in both rounds of the experiment. Participants given feedback were told to treat their confidence rating as a wager based on the likelihood that their answer was correct. Participants gained or lost points equal to their confidence rating for correct and incorrect responses, respectively. A message regarding the accuracy of each response was displayed following the confidence rating, and points were added or deducted from a running tally. Participants were encouraged to earn as many points as possible. After the first round, participants in the feedback condition were shown their cumulative score for that round. Both groups completed the entire procedure a second time with a new set of items.

Results and Discussion

Preliminary inspection of the results revealed that the probability of correctly responding to items in the facilitation condition was near ceiling, so we analyzed the results from that condition separately from performance in other conditions. Our primary interest was in whether prior experience with PI would diminish its effects, particularly for false memory (intrusion errors at the highest level of confidence).

Diminishing effects of PI were evidenced by a significant interaction between rounds (first vs. second encounter with PI) and item type (control vs. interference) in the probability of intrusion errors. Having found an interaction of that sort, we analyzed effects separately for control and interference items. The probability of producing either the target or its alternate was extremely high for facilitation (.97), control (.92), and interference items (.97), so errors other than producing an alternate response as an intrusion error did not enter into the analyses. We do not report significant main effects of variables when an interaction involving the variables was significant. The significance level for all tests was set at p < .05.

An analysis of the number of correct responses in the facilitation condition revealed only a significant effect of age [ F (1,92) = 12.85, MS e = .17, η p 2 = .12 ]. The probability of producing a correct response for facilitation pairs was higher for young adults (.93) than for older adults (.87). An additional analysis of performance in the facilitation condition examined effects on the joint probability of producing a correct response and reporting the highest level of confidence (5) in its accuracy. Analysis of those results ( Table 1 ) revealed only a significant effect of feedback [ F (1,92) = 6.14, MS e = .41, η p 2 = .06 ]. Providing feedback increased highest confidence, accurate responding for both young and older adults. Neither the main effect of round nor any other main effect or interaction approached significance. The lack of a significant effect of round on responding to facilitation items is important in that it suggests that participants did not reduce their attention to the training list in the second round as a means of reducing PI. Had they done so, one would expect to find a reduction in high-confidence, accurate responding in the facilitation condition across rounds. More important, the results reveal the importance of feedback for increasing confidence in correct responses. As will be seen, feedback was also important for reducing confidence in erroneous responses.

Probability of Correct Recall (PCR) Held in Highest Confidence for Facilitation Items As a Function of Round, Feedback, and Age

Prior experience with PI diminished its effects on intrusion errors, as evidenced by a highly significant interaction of item type (control vs. interference) and round [ F (1,92) = 9.46, MS e = .09, η p 2 = .10 ]. The results from a separate analysis of performance in the control condition revealed only a significant interaction of age and feedback [ F (1,92) = 7.10, MS e = .08, η p 2 = .07 ]. This interaction was produced by the age difference in the probability of an intrusion error being smaller in the feedback condition (.15 and .20 for young vs. older adults, respectively) than in the no-feedback condition (.12 and .25 for young vs. older adults, respectively). Neither the effect of round nor any interaction with round approached significance in the analysis of performance on control items.

Our primary interest was in intrusion errors in the interference condition ( Table 2 ). Older adults produced more intrusion errors on interference items (.51) than did young adults (.30) [ F (1,92) = 60.88, MS e = 2.09, η p 2 = .40 ]. In contrast to results for the control condition, the effect of round was highly significant for the interference condition [ F (1,92) = 20.86, MS e = .24, η p 2 = .19 ], with the probability of an intrusion error being lower in the second round (.37) than in the first round (.44). Inspection of the results in Table 2 suggests that, for older adults, the effect of prior experience with PI did more to diminish its effects in the feedback condition than in the no-feedback condition. However, the relevant interaction did not approach significance.

Probability of List 1 Intrusions (PLI) on Interference Items As a Function of Age, Round, and Feedback

The effects of prior experience on false-memory errors were of particular interest because people are likely to act on such errors. False-memory errors are measured as the joint probability of producing an intrusion error and holding the highest level of confidence (5) in the accuracy of the erroneous response. For purposes of comparison, errors held at the highest level of confidence were analyzed for control pairs. Responding to the cue from a control pair with the alternate to the target (the response that, for an interference pair, was presented in List 1 and served as a source of PI) was counted as an intrusion error. The interaction of type of pair (control vs. interference) with round was highly significant [ F (1,92) = 24.35, MS e = .10, η p 2 = .21 ].

A separate analysis of performance on control pairs revealed that high-confidence intrusions were rare because the alternate response had not been presented in List 1 but occurred with a higher probability for older adults (.056) than for young adults (.012) [ F (1,92) = 20.94, MS e = .09, η p 2 = .19 ]. The reduction from Round 1 (.038) to Round 2 (.030) in the probability of a highest confidence intrusion error to control pairs was exceedingly small but approached significance [ F (1,92) = 3.36, MS e = .003, p = .07, η p 2 = .04 ]. The effect of prior experience on false-memory errors for interference pairs was much larger.

An analysis of false-memory errors for interference pairs ( Table 3 ) revealed that older adults were much more likely to make such errors than were young adults [ F (1,92) = 95.15, MS e = 2.46, η p 2 = .51 ] and also revealed a large decrease in the probability of false-memory errors across rounds [ F (1,92) = 32.47, MS e = .24, η p 2 = .26 ]. The triple interaction of round, feedback, and age approached significance [ F (1,92) = 3.76, MS e = .03, p = .056, η p 2 = .04 ]. Further analyses examined results separately for young and older adults. The analysis of results for young adults showed that they were more likely to produce false-memory errors when feedback was provided [ F (1,46) = 7.92, MS e = .07, η p 2 = .15 ]. More important, the round × feedback interaction was significant for older adults [ F (1,46) = 4.88, MS e = .06, η p 2 = .10 ] but did not approach significance for young adults ( F < 1). As is shown in Table 3 , for older adults, the decrease in false-memory errors across rounds occurred only in the condition that received feedback, whereas the provision of feedback was unimportant for the effect of round on the performance of young adults.

Probability of List 1 Intrusions (PLI) Held at the Highest Level of Confidence (False Memories) As a Function of Age, Round, and Feedback

The decrease in the probability of high-confidence intrusion errors across rounds might reflect an overall improvement in the ability to use confidence judgments to discriminate between correct responses and errors. Additional analyses examined the extent to which confidence judgments differed between correct recalls and errors, separately for control and interference items. For control items, young adults were more confident in their correct recall of target items (4.05) than in their errors (2.40), as were older adults (4.14 vs. 3.09). However, the difference in confidence between correct recalls and errors was greater for young adults than for older adults [ F (1,86) = 17.94, MS e = 8.29, η p 2 = .17 ], largely because of older adults’ greater confidence in their errors. Confidence in responses was higher in the first round (3.49) than in the second round (3.34) [ F (1,86) = 7.62, MS e = 2.04, η p 2 = .08 ], but the interaction of round with confidence in correct recalls versus errors did not approach significance ( F < 1). That is, the effects of prior experience did not increase the usefulness of confidence judgments for discriminating between correct recall and errors on control items.

Not surprising, confidence judgments for interference items ( Table 4 ) discriminated less well between correct recalls (4.29) and intrusion errors (3.82) than did confidence judgments for control items (4.08 vs. 2.76) [ F (1,82) = 126.58, MS e = 31.20, η p 2 = .61 ]. As was found for control items, older adults’ confidence judgments for interference items discriminated less well between correct recalls and errors than did those of young adults [ F (1,86) = 53.15, MS e = 13.58, η p 2 = .38 ]. More important, for interference items, prior experience with PI improved the usefulness of confidence judgments for distinguishing between correct recalls and errors, but only when feedback was given. The interaction of confidence in correct recall vs. intrusion errors with round and feedback for performance on interference items was significant [ F (1,86) = 6.81, MS e = 1.66, η p 2 = .07 ]. An analysis of performance in the feedback condition revealed that the difference between confidence in correct recalls and intrusion errors was greater in the second round than in the first round, due to a reduction in confidence for intrusion errors [ F (1,42) = 11.24, MS e = 2.69, η p 2 = .21 ]. For the no-feedback condition, in contrast, the corresponding interaction did not approach significance ( F < 1). Rather, round only had the effect of equally reducing confidence in correct recalls and intrusion errors [ F (1,44) = 4.27, MS e = .92, η p 2 = .09 ].

Confidence Ratings for Correct Recalls and Intrusion Errors on Interference Items As a Function of Age, Round, and Feedback

In sum, the results revealed that prior experience with PI diminished its effects for both young and older adults. For older adults, there was a tendency toward the reduction in intrusion errors being larger when feedback was provided. The probability of false-memory intrusion errors held with the highest level of confidence was greater for older than for young adults and was reduced by prior experience with PI. However, for older adults, this reduction in false memory occurred only when feedback was given. For both young and older adults, prior experience with PI increased the ability of confidence judgments to distinguish between correct recalls and intrusion errors in the interference condition, but only when feedback was given.

It might be argued that the reduced PI on the second round occurred because participants paid less attention to the list that served as a source of interference on the second round as compared with on the first round. Against that possibility, reduced attention to the first list would be expected to reduce performance on facilitation items as well as reducing interference. An effect of round was not found for facilitation items, even when performance was examined for correct responses given with highest confidence, which were far from a ceiling level of performance. Furthermore, for older adults, a reduction in intrusion errors produced at the highest level of confidence occurred only when feedback was given. Also, the effects of prior experience with PI on the ability of confidence judgments to distinguish between correct recalls and intrusions was restricted to interference items and occurred only when feedback was given. The specificity of these effects argues against the possibility that the diminishment in PI resulted from a general reduction in attention to the list that served as the source of PI. Experiment 2 provides evidence that allows further specification of how experience with PI serves to diminish its effects.

EXPERIMENT 2

In Experiment 2, we sought to replicate the finding that prior experience with PI diminishes its effects. Given the importance of feedback found in Experiment 1, all of the participants received feedback in Experiment 2. In contrast to Experiment 1’s design, the participants in Experiment 2 were informed about the makeup of the study list, being told that the list would include interference and facilitation pairs as well as control pairs. Despite their having been warned about the presence of interference pairs, we did not expect participants to be aware of the greater difficulty of such pairs until Round 2, after prior experience with PI.

Having become aware of the difficulties that interference pairs produce for later memory performance as a result of a prior encounter with PI, participants might pay special attention to interference pairs during study in the second round, so as to diminish the effects of PI. We examined this possibility by employing a self-allocated study-time procedure. Prior research has shown that learners generally allocate more study time to difficult items than to easy items when there are no time constraints on the study episode (for a review, see Son & Metcalfe, 2000 ). Item difficulty has typically been manipulated by varying the strength of association between a cue and its response, whereas our interest was in differences in difficulty produced by interference effects. Study time served as an index of the extent to which participants monitored item difficulty across item types (see, e.g., Koriat, Ma’ayan, & Nussinson, 2006 ). We expected that study time would not differ for the interference and control conditions in the first round. However, in the second round, as a result of feedback in the first round, participants were expected to monitor their study in ways that revealed interference pairs as being more difficult than control pairs and, therefore, to devote more study time to interference pairs. Greater attention to interference pairs during study might serve to better support later memory performance in ways that diminish the effects of PI.

Experiment 2 was also designed to determine whether effects of prior experience with PI on confidence judgments would affect participants’ ability to withhold intrusion errors by not responding when given the opportunity to do so. After being forced to respond to each test item, participants gave a confidence judgment and were then given the option to volunteer or withhold their response (cf. Koriat & Goldsmith, 1996 ). This option provided an opportunity for participants to withhold incorrect responses to interference items and further diminish, or even eliminate, PI effects. For volunteered responses, participants were awarded 5 points for correct responses and penalized 15 points for incorrect responses. For responses that were withheld, no feedback was given, and points were neither awarded nor penalized. We expected that the option to withhold responses would allow participants to further diminish the effects of PI, particularly in Round 2.

Participants were 24 young adults (mean age = 20.25 years) and 24 older adults (mean age = 74.50 years) recruited from the Washington University Psychology Department subject pool. Participants were tested individually and received course credit (young adults only) or $10 per hour.

The design and materials in Experiment 2 were identical to those in Experiment 1, but with the exceptions described below. A 2 (age: young vs. older) × 3 (pair type: facilitation vs. control vs. interference) × 2 (round: 1 vs. 2) mixed design was used. Age was a between-subjects factor, and pair type and round were manipulated within subjects. The number of pairs was reduced to shorten the length of the experiment in order to accommodate the procedural changes. Materials consisted of 132 word triples. Six sets of 20 triples were rotated through conditions, with the remaining triples being used as buffers. Training lists comprised 20 pairs of each type. Buffers were used for practice tests that preceded the actual tests in each round.

The procedure was the same as in Experiment 1, but with the following exceptions. The training phase (List 1) in each round included fewer pairs (40 critical, 4 buffers = 132 total presentations). Prior to the study phase, the participants were informed about the nature of the study pairs in relation to those presented in the training phase. They were told to study each pair until it had been learned completely and to click on a box labeled “Next” displayed below each pair in order to move on, once they had finished studying. All ISIs were set to 500 msec.

At the time of test, the participants were given cue–fragment pairs in the same manner as in Experiment 1 (e.g., knee–b_n_) and were instructed to complete the fragment with the response presented in the study phase. The participants were then asked to rate their confidence, on a scale from 0 ( wild guess ) to 100 ( certain correct ), that their response matched what they had studied. The participants were encouraged to use the full range of the scale.

Following their confidence judgments, the participants were given the option to report or withhold their responses. For reported responses, they were awarded 5 points for each correct response and penalized 15 points for each incorrect response. No points were gained or lost for withheld responses. Participants were encouraged to maximize their point total by reporting only responses for which they were sufficiently confident of being correct. A running score was displayed in the upper right-hand corner of the screen. Corrective feedback was not provided for withheld responses.

We begin by reporting the results that replicate those found in Experiment 1. Next, we examine the effects of prior experience with PI on the ability to withhold intrusion errors so as to increase the accuracy of responding. Finally, we report effects on the allocation of study time to show that participants increase the amount of study time devoted to interference pairs following prior experience with PI. As in Experiment 1, the probability of producing either the target or its alternate was extremely high for facilitation (.98), control (.96), and interference items (.97), so errors other than producing an alternate response did not enter into the analyses.

Analysis of performance in the facilitation condition did not yield any significant effects. Performance was near ceiling for both young (.93) and older adults (.91). An additional analysis of performance in the facilitation condition examined effects on the joint probability of producing a correct response and reporting the highest level of confidence in its accuracy ( Table 1 , bottom rows). That analysis did not reveal any significant effects. As in Experiment 1, round did not influence responding on facilitation items, suggesting that attention to List 1 was not reduced across rounds. This is important for dismissing the possibility that diminished effects of PI across rounds result from reduced attention to List 1, the source of PI. A reduction in attention of that sort would be expected to reduce performance on facilitation pairs, as well as to reduce interference for interference pairs.

More important, the analysis of intrusion errors in the control and interference conditions revealed a significant interaction between item type (control vs. interference) and round [ F (1,46) = 8.17, MS e = .08, η p 2 = .15 ], showing that prior experience with PI diminished its effects. For items in the control condition, only the effect of age was significant [ F (1,46) = 5.49, MS e = .06, η p 2 = .11 ]. The probability of an intrusion error on control items was higher for older adults (.13) than for young adults (.08). Neither the effect of round nor any interaction with round approached significance.

Performance on interference items was of greater interest ( Table 2 , bottom row). Fewer intrusion errors were produced for interference items in the second round than in the first [ F (1,46) = 20.04, MS e = .28, η p 2 = .30 ]. Also, young adults produced fewer intrusion errors than did older adults [ F (1,46) = 4.78, MS e = .19, η p 2 = .09 ].

As in Experiment 1, our primary interest was in whether experience with PI would reduce the probability of false memory, defined as an intrusion error accompanied by 100% confidence. False memory was significantly reduced by prior experience, as evidenced by a highly significant interaction between round and item type (control vs. interference) [ F (1,46) = 14.75, MS e = .04, η p 2 = .24 ]. An analysis of performance on control items revealed that the probability of highest confidence errors was greater for older adults (.029) than for young adults (.001) [ F (1,46) = 10.54, MS e = .02, η p 2 = .19 ]. The effect of round was also significant, although the probability of highest confidence errors for control pairs differed little between the first and second rounds (.022 vs. .008) [ F (1,46) = 5.59, MS e = .004, η p 2 = .11 ]. As is shown in the bottom row of Table 3 , the probability of false memory for interference pairs was much higher for older (.15) than for young adults (.06) [ F (1,46) = 10.34, MS e = .24, η p 2 = .18 ]. Also, for interference pairs, the probability of false memory was greatly reduced on the second round (.07), as compared with the first round (.14) for both young and older adults [ F (1,46) = 28.34, MS e = .13, η p 2 = .38 ].

A further analysis of confidence judgments examined their ability to distinguish between correct recall of target items and intrusion errors. An analysis of confidence judgments for responses to control items revealed only that participants’ confidence in their correct recalls (.72) was higher than that in their intrusion errors (.42) [ F (1,25) = 61.29, MS e = 2.42, η p 2 = .71 ]. Neither the effect of age nor that of round approached significance ( F s < 1). In contrast, an analysis of confidence judgments for responses to interference items ( Table 4 , bottom row) showed that experience with PI increased the ability of confidence judgments to distinguish between correct recalls and intrusion errors for both young and older adults, as evidenced by a significant interaction between response (correct recall vs. intrusion error) and round [ F (1,43) = 9.59, MS e = .13, η p 2 = .18 ]. However, older adults’ confidence judgments for interference items discriminated less well between correct recall and intrusion errors than did those of young adults [ F (1,43) = 7.11, MS e = .19, η p 2 = .14 ], largely because of the older adults’ higher confidence in their intrusion errors.

When given the opportunity to withhold responses, the probability of a response being withheld, regardless of whether or not it was correct, was lower for facilitation items (.11) than for either control (.22) or interference items (.16) [ F (2,92) = 30.02, MS e = .28, η p 2 = .40 ]. An analysis that included only control and interference items revealed a significant interaction between age and item type [ F (1,46) = 4.93, MS e = .05, η p 2 = .10 ]. Young adults differed little from older adults in their probability of withholding a response to an interference item (.16 vs. .17) but were much less likely to withhold a response to a control item (.18) than were older adults (.25).

Did prior experience with PI increase the probability of withholding intrusion errors to interference items? It did so for young adults, but not for older adults, as evidenced by a significant interaction of age and round [ F (1,43) = 5.93, MS e = .35, η p 2 = .12 ]. For young adults, the probability of withholding an intrusion error for interference items was higher on the second round (.46) than on the first round (.22). In contrast, the probability of older adults withholding an intrusion error to interference items was identical on the two rounds (.21).

As compared with forced report, allowing participants to withhold responses (free report) increased the accuracy of recall in the control and interference conditions, and there was a tendency toward this increase being larger for young adults than for older adults [ F (1,46) = 3.64, MS e = .01, p = .063, η p 2 = .07 ]. Across conditions, the probability of an error was higher for young adults when recall was forced rather than free (.16 vs. .12), whereas the corresponding difference for older adults was somewhat smaller (.23 vs. .21). The pattern was the same when the results were analyzed separately for interference items. The probability of an intrusion error for young adults was higher when recall was forced rather than when it was free (.24 vs. .20), and there was a tendency toward that difference being smaller for older adults (.33 vs. .32), but the interaction only approached significance [ F (1,46) = 3.10, MS e = .01, p = .09, η p 2 = .06 ]. No other interactions involving report option, including the interaction with round, approached significance.

As in Experiment 1, prior experience with PI diminished its effects. Examination of participants’ allocation of study time is revealing, with regard to the basis for this increased resistance to PI. As is shown in Table 5 , participants spent less time studying facilitation pairs than they did either control or interference pairs, and the amount of study time devoted to facilitation pairs decreased across rounds. More important, the interaction of round with item type (control vs. interference) was significant [ F (2,92) = 6.95, MS e = 2,845,578.22, η p 2 = .13 ]. The significant interaction arose from study time allocated to control items decreasing across rounds, whereas study time allocated to interference items increased across rounds [ F (1,46) = 7.72, MS e = 1,922,400.75, η p 2 = .15 ]. There was also a tendency for older adults to devote more study time to items in all conditions than did young adults (5,482 vs. 5,081 msec), but, because of the high variability of study time, neither that difference nor any interaction with age approached significance ( F s < 1). The differential effects of round suggest that both young and older adults became aware of the greater difficulty of interference items, so they increased the amount of study time devoted to those items in the second round. It is likely that their doing so was at least partially responsible for the diminished effects of PI.

Study-Time Allocation (in Milliseconds) As a Function of Round, Item Type, and Age Group in Experiment 2

Note—Observations exceeding 2.5 SD s above or below the mean in each within-participants condition were trimmed prior to analysis. Less than 2% of all observations were excluded.

To measure the relation between self-allocated study time and accuracy of responding, gamma correlations between study time and accuracy were computed for each participant (see Nelson, 1984 ) and then analyzed by means of an ANOVA. The analysis of those correlations revealed only a marginally significant effect of item type [ F (2,38) = 2.78, MS e = .43, p = .07, η p 2 = .13 ]. There was an inverse correlation between study time and accuracy for facilitation pairs (−.14), whereas the correlation was not significant and slightly positive for control (.05) and interference (.04) pairs. The overall correlation was near zero. The inverse correlation for facilitation pairs suggests that participants were able to identify pairs that would be easily recalled and devoted little study time to those pairs.

The generally low correlation between study time and accuracy might be surprising. Instead, one might expect a positive correlation between study time and accuracy because experimenter-controlled increases in study time typically increase accuracy. However, the lack of correlation is not surprising if one realizes that, ideally, the amount of study time devoted to an item should depend on its difficulty, with study time devoted to an item’s being greater the higher its judged difficulty for recall. Allocating study time in this way would reduce the correlation between study time and accuracy and produce a zero correlation if there were differences in item difficulty and participants were sufficiently able to recognize and overcome those item differences by means of their allocation of study time ( Koriat et al., 2006 ; cf. Nelson & Leonesio, 1988 ). Due to the complexities created by item differences, along with the possibility of qualitative changes in study, it would be difficult to detect changes in the relation between study time and accuracy across rounds.

GENERAL DISCUSSION

Experience with PI diminishes its effects. Both experiments revealed a significant interaction with round, such that intrusion errors to interference items decreased across rounds, whereas performance on control items remained unchanged. Older adults were generally more reliant on feedback than were young adults, which is not surprising, since older adults were much more prone to produce high-confidence intrusion errors. There was a trend toward the reduction in intrusion errors for older adults’ being larger in Experiment 1 when feedback was provided, and older adults’ reduction in false memory—defined as intrusion errors held at the level of highest confidence—was observed only when feedback was provided.

For both young and older adults, the increase across rounds in the extent to which confidence judgments were diagnostic of correct responding occurred only when feedback was provided. Feedback was provided for all conditions in Experiment 2, and results from that experiment replicated those of Experiment 1 by showing a decrease in false memory as a result of prior experience with PI, along with an increase in the extent to which confidence judgments were diagnostic of correct responding. The decrease in false memory gained from prior experience with PI was substantial. For older adults, the probability of false memory was almost halved from the first round to the second round (.20 vs. .11) in Experiment 2.

When given the option to withhold responses in Experiment 2, young adults were more likely to withhold false recalls on the second round than on the first round; older adults were not. Neither young nor older adults substantially increased the accuracy of their responding under conditions of free, as compared with forced, responding. In contrast, Kelley and Sahakyan (2003) found that both young and older adults were able to greatly increase their accuracy under conditions of free responding. There are a number of differences between our experiments and theirs. Most important, perhaps, are the payoffs for correct and false recall that were employed. We awarded 5 points for each correct response that was volunteered, and we penalized by subtracting 15 points for each error that was volunteered, whereas Kelley and Sahakyan awarded 25 cents for each correct response and penalized $2.50 for each incorrect response. Perhaps our awards and penalties were simply not extreme enough to result in participants’ imposing a criterion for volunteering responses that would substantially increase their accuracy of responding. In this vein, confidence judgments, particularly for young adults, appeared to be sufficiently diagnostic of correct responding on the second round to allow them to greatly increase their accuracy by withholding responses if they had adopted a more stringent criterion for responding.

We believe that our experiments are the first to show that experience with PI can diminish its effects—including false memory. We find it striking that minimal training can have a substantial impact. Much of the work on memory accuracy and aging has primarily drawn conclusions from a single session of performance. The data from the present study suggest that, if older adults are given feedback (cf. Balota, Duchek, Sergent-Marshall, & Roediger, 2006 ; Rebok & Balcerak, 1989 ) and another opportunity to be tested, they can demonstrate improvements in performance. The implications of this are important in showing that older adults’ accuracy and confidence are both open to remediation and in providing further evidence that older adults’ susceptibility to false memories can be ameliorated (cf. McCabe & Smith, 2002 ). It is important that the probability of false memory that originates from PI can be reduced, because PI is a common source of false memories.

How did experience with PI reduce false memory? One might suggest that reductions in confidence for intrusion errors to interference items occurred because participants became more risk averse as a consequence of high-confidence errors. A risk-aversion hypothesis would posit a generalized reduction in confidence, with participants reducing their confidence for all items across rounds. However, confidence for correct responses to facilitation pairs did not decrease across rounds. Also, the extent to which differences in confidence judgments were diagnostic of the accuracy of responses did not change across rounds for control items. Rather, those effects of prior experience with PI were selective to interference items. Thus, a risk-aversion hypothesis would have to rather implausibly assume that participants became more conservative on only a subset of the items (i.e., interference items) presented randomly throughout the test. Furthermore, the risk-aversion hypothesis would not account for the overall reduction in intrusion errors across rounds that was observed when responding was forced, as it was in Experiment 1 and in the forced-recall condition of Experiment 2. Yet another account would hold that the reduction of PI across rounds resulted from reduced attention to the training list, which served as a source of PI, on the second round. As discussed in conjunction with Experiment 1, the specificity of effects of prior experience on PI weighs against that account.

Effects of prior experience with PI on the self-allocation of study time observed in Experiment 2 suggest that prior experience with PI resulted in a change in the encoding of interference items across rounds. Although informed of the relationship between lists, participants were apparently unaware of the greater difficulty of interference items until after they had experienced PI.

In a similar vein, Benjamin (2003) showed that participants gave higher judgments of learning for recognition of high- than of low-frequency words in an initial study session, predicting a pattern of performance that was opposite to that observed. However, after experience with a recognition test in the first session, participants correctly predicted that their recognition-memory performance would be better for low-frequency words in a second session.

For PI, awareness of the greater difficulty of interference items resulted in the amount of study time devoted to interference pairs increasing across rounds, with the result that substantially more study time was devoted to interference pairs than to control pairs on the second round. Furthermore, there may have been both qualitative and quantitative differences in encoding processes across rounds that were selective to interference pairs. As a result of prior experience with PI, participants may have adapted their encoding of interference pairs in ways that provided greater support for later recollection. Similarly, participants in Experiment 1 may have devoted more attention to interference pairs in the second round and adapted their encoding processes to better deal with PI, although they were unable to devote more time to studying those pairs.

Participants’ responding on the first round may have relied heavily on a fluency heuristic ( Jacoby et al., 2005 ; Jacoby & Dallas, 1981 ), reporting items that came to mind most easily. This would be reasonable for facilitation items, but it would also have the consequence of leading participants to report the most accessible and, therefore, incorrect answer for interference items. However, having gained experience with PI, participants may have modified their encoding of interference pairs in ways that made them better able to shift from heavy reliance on fluency to other, more diagnostic bases for memory, such as reinstating prior encoding context to recollect prior details from study. Thus, the basis for participants’ confidence in their responses may have undergone a qualitative shift from a heavy reliance on judged fluency in the first round to greater reliance on recollection in the second round, resulting in increased accuracy and a reduction in confidence for errors. That is, the diminished effects of PI can be seen as reflecting a qualitative shift toward greater reliance on recollection as a basis for memory and confidence.

It is noteworthy that older adults were as able as young adults to diminish effects of PI as a result of prior experience with PI. Experiments by Hay and Jacoby (1999) and by Jacoby, Debner, and Hay (2001) used a process-dissociation procedure to show that older adults’ greater vulnerability to PI resulted from their lessened ability to recollect the occurrence of particular events. Hay and Jacoby (1999) showed that, given supportive conditions, older adults were able to benefit from distinctive contextual information as a means of enhancing recollection. Results from the present experiments suggest that older adults’ ability to recollect can also be enhanced by means of training aimed at diminishing the effects of PI. The possibility that older adults’ ability to recollect particular events was improved by training to diminish the effects of PI is consistent with results from other experiments (e.g., Jennings & Jacoby, 2003 ; Jennings, Webster, Kleykamp, & Dagenbach, 2005 ) that have enhanced older adults’ ability to recollect by training under conditions of high interference. In general, training under conditions of high interference holds promise as a means of improving ability to recollect, thereby reducing false memory.

Given the results of our experiments, it may be useful to revisit procedures that have been shown to produce dramatic false remembering (for reviews, see Loftus, 2004 ; Roediger, 1996 ). Many of the studies on false memory have drawn conclusions from a single session of performance. The dramatic levels of false memory found in those studies might not have persisted across repeated applications of the procedures used to produce them. As in the case of PI, the effectiveness of the procedure might diminish as a function of prior experience. For example, it might be more difficult to mislead people to falsely remember having been lost in a mall if they have had prior experience being misled in a similar way (cf. Loftus, 1997 ).

The results of our present experiments suggest that being forewarned of a manipulation that could produce false memory may not be sufficient to avoid its effects. Being told that the study list included interference pairs did not diminish the effects of PI, but prior experience with PI did. More generally, prior experience in situations that produce false memory might diminish the likelihood of false memory in similar situations. Being forewarned and experienced might allow one to be forearmed against such effects.

Acknowledgments

The research reported in this article was supported by National Institute on Aging Grant AG13845. We thank Sarah Arnspiger, Nancy Byars, Carole Jacoby, Emily Norwood, and Rachel Teune for their assistance with data collection.

Contributor Information

Matthew G. Rhodes, Colorado State University, Fort Collins, Colorado

Karen A. Daniels, University of North Carolina, Wilmington, North Carolina

Chad S. Rogers, Washington University, St. Louis, Missouri

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Understanding Proactive Interference in Psychology: Effects and Implications

proactive interference experiment

Have you ever struggled to remember new information because of old memories interfering with your ability to learn? This phenomenon is known as proactive interference, a concept studied in psychology that can have significant effects on memory and learning.

In this article, we will explore how proactive interference works, its role in memory processes, the effects it can have on our ability to learn and remember, strategies to overcome it, real-life implications, and how researchers study and measure this cognitive phenomenon.

Let’s dive into the fascinating world of proactive interference and its impact on our daily lives.

  • Proactive interference can make it difficult to learn new information and lead to forgetting previously learned information.
  • Certain strategies, such as using cues and retrieval techniques, can help overcome proactive interference.
  • Understanding proactive interference has real-life implications in education, the workplace, and everyday life and can be studied through laboratory experiments, field studies, and brain imaging techniques.
  • 1 What Is Proactive Interference?
  • 2.1 What Is The Role Of Memory In Proactive Interference?
  • 3.1 Difficulty In Learning New Information
  • 3.2 Forgetting Previously Learned Information
  • 3.3 Confusion And Frustration
  • 4.1 Using Cues And Retrieval Techniques
  • 4.2 Time Spaced Learning
  • 4.3 Avoiding Similar Information
  • 5.1 In Education And Learning
  • 5.2 In The Workplace
  • 5.3 In Everyday Life
  • 6.1 Laboratory Experiments
  • 6.2 Field Studies
  • 6.3 Brain Imaging Techniques
  • 7.1 What is proactive interference in psychology?
  • 7.2 How does proactive interference affect memory recall?
  • 7.3 What are the effects of proactive interference on learning?
  • 7.4 Can proactive interference be beneficial?
  • 7.5 What factors influence the degree of proactive interference?
  • 7.6 How can one reduce the effects of proactive interference?

What Is Proactive Interference?

Proactive interference refers to the phenomenon where old memories interfere with the ability to recall new information or tasks.

This interference occurs when previously learned information disrupts the recall of newer memories. For example, imagine trying to remember a new phone number, but constant recollection of your old phone number keeps popping up, making it difficult to retain the new one.

Studies have shown that proactive interference can significantly impact memory recall efficiency and learning. In a classic experiment by McGeoch and McDonald (1931), participants were asked to memorize lists of words, with the findings demonstrating that memory recall decreased with each new list due to interference from previous memories.

How Does Proactive Interference Work?

Proactive interference operates based on the interference theory, influencing cognitive processes during memory recall, both in laboratory settings and real-life events.

Interference theory suggests that when information stored in memory competes with other, similar information, it can lead to proactive interference. This means that older information hinders the recall of newer information. For example, when attempting to remember a friend’s new phone number, previous phone numbers stored in memory can interfere and impede the successful retrieval of the new number.

What Is The Role Of Memory In Proactive Interference?

Long-term memory plays a crucial role in proactive interference, as the process of forgetting and encoding information influences the interference effect.

When new information is encoded into long-term memory, it interacts with existing knowledge structures. This can lead to proactive interference, where previously learned information disrupts the recall of newer memories. Through the process of consolidation, newly acquired memories are integrated and stabilized in the neural network.

Memory consolidation plays a vital role in determining the extent of proactive interference. The forgetting curve illustrates how memory retention decreases over time, highlighting the importance of effective encoding and consolidation for long-term memory formation.

What Are The Effects Of Proactive Interference?

The effects of proactive interference include difficulties in recalling new tasks due to the interference caused by previously learned information or tasks.

Proactive interference can be particularly challenging when trying to learn similar tasks or information that share common elements with what has been previously learned. For instance, imagine learning to play the piano after having learned how to play the guitar. The finger positions and chord progressions from playing the guitar may interfere with the new piano skills, making it harder to remember the correct notes and sequences. This phenomenon occurs because the brain tends to mix up or overlap similar memories, leading to confusion and errors in recall.

Difficulty In Learning New Information

Proactive interference can lead to difficulties in learning new information, as existing memories can disrupt the encoding and retention of fresh data.

This phenomenon occurs when previously learned information interferes with the acquisition of new knowledge. For instance, if someone is trying to remember a new address but keeps recalling an old one, proactive interference is at play. According to a study published in the Journal of Experimental Psychology, proactive interference can significantly impair the ability to remember new information over time.

To combat proactive interference, individuals can utilize strategies like spaced repetition and semantic encoding. Spaced repetition involves revisiting information at increasing intervals, allowing the brain to strengthen the memory trace effectively. On the other hand, semantic encoding involves associating new information with pre-existing knowledge, aiding in better retention and recall.

Forgetting Previously Learned Information

Proactive interference can result in the forgetting of previously learned information, aligning with aspects of decay theory in memory consolidation.

When new information interferes with the retrieval of old memories, it creates a challenge for the brain to access the earlier stored data. This phenomenon mainly occurs when there is a similarity between the new and old memories, leading to confusion and disruption in recalling specific details. Proactive interference can impede the successful retrieval of memories that were encoded earlier, causing a deterioration in one’s ability to access past experiences accurately.

Confusion And Frustration

Proactive interference can induce confusion and frustration in individuals as cognitive processes are disrupted by the interference between old and new information.

This phenomenon occurs when previously learned information interferes with the retrieval of newly learned information, leading to memory errors and difficulty in distinguishing between the two. For example, imagine trying to recall a new phone number that is very similar to an old one you have memorized; the interference from the old number could cause confusion and lead to errors in dialing.

Similarly, in everyday situations, proactive interference can occur when trying to recall a password that has been changed multiple times, causing frustration and errors in accessing the desired account. This cognitive interference can also impact academic performance when students are studying similar subjects, leading to the mixing up of facts and concepts.

How To Overcome Proactive Interference?

Overcoming proactive interference involves strategies such as proactive inhibition and engaging in overlearning to strengthen memory consolidation processes.

Proactive inhibition is a technique where individuals deliberately suppress previously learned information to make room for new memories. By actively preventing old memories from interfering with the recall of new information, one can improve memory accuracy and retention.

Overlearning, on the other hand, involves rehearsing material beyond the point of initial mastery. This method helps encode information more firmly in long-term memory, making it less susceptible to interference.

Using Cues And Retrieval Techniques

Employing cues and retrieval techniques can aid in overcoming proactive interference, with mnemonic devices serving as effective memory aids.

By utilizing cues effectively, individuals can attach new information to pre-existing memories, making it easier to recall during retrieval. For instance, using context-dependent cues such as studying in the same room where the information will later be recalled can improve memory retention.

Visual cues like color-coded notes, mind maps, or images can trigger specific memories, making associations stronger and retrieval smoother. Mnemonic devices, such as acronyms or acrostics, serve as creative tools to remember complex information in a more organized and memorable manner.

Time Spaced Learning

Implementing a time-spaced learning approach can counteract proactive interference by optimizing study schedules and enhancing retention among participants.

Time-spaced learning, also known as spaced repetition, involves spacing out study sessions over time rather than cramming all the information at once. This technique allows the brain to strengthen memory recall by repeatedly exposing it to the material at strategic intervals. Research shows that this method not only improves long-term memory retention but also reduces the likelihood of forgetting information due to interference effects.

Avoiding Similar Information

To minimize proactive interference, individuals can avoid exposing themselves to overly similar information that may trigger interference, thus preserving memory accuracy.

One way to recognize and avoid similar information that could lead to proactive interference is by utilizing distinct categories when learning new material.

For example, when studying different languages, categorizing vocabulary based on language origin can help prevent confusion and interference.

Practicing spaced retrieval, where information is revisited at spaced intervals, can also enhance differentiation and reduce interference.

By varying study methods and contexts, individuals can create unique memory traces, making it easier to retrieve specific information without interference.

What Are The Real-life Implications Of Proactive Interference?

Proactive interference has significant implications in various real-life scenarios, impacting education, workplace performance, and how individuals process events in their daily lives.

Students encountering proactive interference may find that previously learned information makes it challenging to absorb new material, leading to confusion and slower learning progress. In work environments, individuals might struggle to adapt to new procedures or methods due to interference from previously internalized techniques. This phenomenon can hinder productivity and efficiency, affecting overall job performance. In the context of memory, proactive interference can distort the recollection of events, causing individuals to mix up details or attribute information to the wrong sources.

In Education And Learning

In education, proactive interference can hinder the learning process by interfering with memory recall and retention, affecting students’ ability to absorb new information effectively.

Proactive interference occurs when older memories disrupt the retrieval of newer information, leading to confusion and difficulty in comprehension. This phenomenon can be particularly challenging in academic settings where students are constantly exposed to a barrage of new material. Due to proactive interference, students may struggle to remember key concepts or apply learned knowledge in assessments.

Fortunately, educators can employ various strategies to mitigate the impact of proactive interference on learning outcomes. One approach is to incorporate frequent reviews and spaced repetition techniques into their teaching methods. By revisiting previously covered material at regular intervals, students can strengthen their memory consolidation and overcome interference.

Creating diverse learning experiences such as hands-on activities, group discussions, and multimedia presentations can help counteract the effects of proactive interference. Engaging students in varied tasks that require different types of memory encoding can enhance their ability to retrieve information accurately.

In The Workplace

Proactive interference in the workplace can disrupt cognitive processes, potentially affecting decision-making, task performance, and overall productivity, as demonstrated in research studies.

For instance, imagine a scenario where an employee is trying to learn a new software program that is similar to one they previously used. Due to proactive interference, their prior knowledge may interfere with the new learning process, leading to confusion and slower mastery of the new system. This interference can also occur during meetings when employees mistakenly recall information from a previous project that is irrelevant to the current discussion, leading to misunderstandings and inefficiencies in communication.

In Everyday Life

In everyday life, proactive interference contributes to the forgetting curve and influences how individuals recall and process real-life events, shaping their memory of personal experiences.

For instance, imagine trying to remember a new phone number but constantly confusing it with an old one you have been using for years due to proactive interference. This interference occurs when previously learned information disrupts the recall of new information.

This phenomenon impacts not only short-term memory retrieval but also long-term memory formation. It can be seen when you struggled to recall the details of a recent vacation after reminiscing about a similar trip taken in the past.

Proactive interference can lead to inaccuracies in memory, causing individuals to merge details from different events or misattribute information. This can be observed in eyewitness testimonies where subtle suggestions or prior knowledge can distort the accuracy of events recalled.

How Can Proactive Interference Be Studied And Measured?

Studying proactive interference involves utilizing various methods such as laboratory experiments, field studies, and advanced brain imaging techniques to measure cognitive processes and memory effects.

Laboratory experiments play a crucial role in investigating proactive interference by meticulously controlling variables in controlled settings to replicate memory scenarios.

Field research, on the other hand, ventures into real-world environments, offering a more ecologically valid understanding of how interference impacts memory retention in everyday contexts.

Neuroimaging technologies like fMRI and PET scans delve deeper into the neural mechanisms underlying proactive interference, revealing valuable insights into brain activity patterns during memory tasks and helping unravel the complexities of memory interference phenomena.

Laboratory Experiments

Laboratory experiments offer controlled environments with participants to study memory consolidation processes affected by proactive interference, providing valuable insights into cognitive mechanisms.

By manipulating variables and minimizing external influences, researchers can isolate the impact of proactive interference on memory retention, enabling a deeper understanding of how competing information interferes with encoding and retrieval.

Proactive interference typically occurs when previously learned information disrupts the recall of new material. These experiments also allow for the exploration of strategies or interventions that may mitigate the effects of interference, shedding light on memory enhancement techniques. The controlled nature of lab studies ensures data reliability and reproducibility, essential for drawing scientifically valid conclusions about memory processes.

Field Studies

Field studies examine proactive interference in real-world contexts, analyzing how individuals encounter interference during events and activities, offering practical insights into memory processes.

These studies play a crucial role in understanding how memory functions in the complexities of daily life.

For example, research conducted at a busy train station revealed that people often experience proactive interference when trying to recall new information while being bombarded with announcements and visual distractions.

Similarly, studies at shopping malls have shown how competing information can disrupt memory retention, as individuals struggle to remember a list of items amidst vivid displays and promotional offers.

Brain Imaging Techniques

Advanced brain imaging techniques like fMRI and EEG are employed to study the neural mechanisms involved in proactive interference, providing a deeper understanding of interference theory and memory processes.

By utilizing fMRI, researchers can visualize brain activity by measuring changes in blood flow, thus pinpointing specific brain regions activated during memory recall tasks affected by proactive interference.

On the other hand, EEG allows for the measurement of electrical activity in the brain, offering insights into the timing and coordination of neural responses associated with interference effects.

Neuroimaging studies have revealed that interference effects involve intricate interactions between the prefrontal cortex, hippocampus, and other brain regions crucial for memory encoding and retrieval.

Frequently Asked Questions

What is proactive interference in psychology.

Proactive interference refers to the phenomenon where previously learned information interferes with the ability to learn and recall new information. It occurs when old memories or knowledge disrupts the formation of new memories.

How does proactive interference affect memory recall?

Proactive interference can make it difficult to remember new information, as the old memories or knowledge get in the way. This can lead to forgetting or recalling incorrect information.

What are the effects of proactive interference on learning?

Proactive interference can hinder the ability to learn new information, as the old memories or knowledge interfere with the encoding process. This can result in slower learning and lower retention of information.

Can proactive interference be beneficial?

While proactive interference is often seen as a negative effect, it can also be beneficial. It helps in the formation of schemas, which are mental representations of knowledge, and allows for faster processing of information.

What factors influence the degree of proactive interference?

The degree of proactive interference can be influenced by the similarity of the old and new information, the strength of the old memories, and the time between learning the old and new information.

How can one reduce the effects of proactive interference?

To reduce proactive interference, one can practice retrieval strategies, such as spaced learning and interleaving, which involve revisiting and mixing up old and new information. Additionally, focusing on the most relevant information and avoiding distractions can also help.

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Nicholas Reed is a theoretical psychologist who explores the philosophical underpinnings of psychological theories and practices. His writings examine the assumptions, values, and questions at the heart of psychology, encouraging a deeper understanding of the discipline’s broader implications for knowledge and society. Nicholas’s articles are for those intrigued by the conceptual and existential dimensions of psychology.

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Experience with proactive interference diminishes its effects: mechanisms of change

  • Published: 19 November 2010
  • Volume 39 , pages 185–195, ( 2011 )

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proactive interference experiment

  • Christopher N. Wahlheim 1 &
  • Larry L. Jacoby 1  

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In three experiments, we examined the mechanisms by which prior experience with proactive interference (PI) diminished its effects. Cued recall tasks conforming to an A–B, A–D paradigm were used to induce PI effects. Experiment 1 showed that reduced PI was not due to a reduction in attention to the source of PI. Experiment 2 revealed that participants’ awareness of PI effects on memory performance increased with experience, resulting in a shift in encoding processes. Experiment 3 demonstrated that changes in encoding provided additional support for recollection that further enhanced participants’ ability to constrain their retrieval processing to the appropriate source of information at the time of test. These results can be interpreted as showing that experience with PI enhances awareness of its effects and allows individuals to adjust their learning and retrieval strategies to compensate for such effects.

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Avoid common mistakes on your manuscript.

Proactive interference (PI) is a potent source of forgetting. For serial learning, Underwood ( 1957 ) reviewed experiments in which the effects of PI were examined and found that the probability of recall decreased dramatically from .80 when there was no preceding list to approximately .20 following 20 preceding lists. Paired-associate learning also shows large effects of PI (for a review, see Anderson & Neely, 1996 ). The question we ask in this article is whether participants are unaware of the effects of PI during a first encounter with PI but become aware of its effects and successfully implement procedures to diminish those effects during a second encounter with PI. Although the effects of PI are widely known by memory researchers, little has been done to investigate people’s ability to diminish its effects. Findings of an ability to adapt learning in ways that diminish the effects of PI are important for gaining a better understanding of the effects of PI and, potentially, hold import for applied purposes.

In commonplace situations, people show knowledge of PI effects by taking actions to avoid such effects. For example, in card games, it is common for the dealing of cards to pass around the table, creating the problem of remembering who dealt last so as to decide whose turn it currently is to deal. This problem is typically solved by playing with two decks of cards, with one of the decks being placed in front of the person who is to deal next while the other deck is being dealt. However, rather than being generally aware of effects of PI, such awareness might be restricted to particular situations. For card playing, it is likely that problems produced by PI were discovered as a result of experience in the situation, and only then were steps taken to eliminate its effects. Similarly, combating PI in a list-learning situation might depend on prior experience in the situation of a sort that makes people aware of its effects.

To our knowledge, the only investigation of ability to diminish PI as a result of prior experience with its effects was done by Jacoby, Wahlheim, Rhodes, Daniels, and Rogers ( 2010 ). Participants in their experiments were given two rounds of experience with PI in a paired-associate learning task. In each round, two lists were presented, with the relation between the pairs within the lists being varied. To measure PI, performance in an interference condition that presented the same cue but a different response for the two lists (A–B, A–D) was compared with that in a control condition for which both the cue and the response (rest, C–D) occurred only in list 2. Other pairs in the second list retained the response from the first list (A–B, A–B). This facilitation condition was meant to encourage attention to list 1 items during both of the two rounds and also to encourage carryover of responses between the two lists, increasing PI. Test items consisted of a cue word and a word fragment that could be completed with either the target or its competing response that appeared in list 1 for interference items. This was intended to further increase PI and to allow effects in the form of intrusion errors to be examined better. The procedure for the second round was the same as that for the first, except that new materials were used (e.g., for interference pairs, E–F, E–G).

The results from the experiments by Jacoby et al. ( 2010 ) revealed that PI was diminished on the second, as compared with the first, encounter with PI for both young and older adults. Experiment 2 in that series provided results that suggested that participants became aware of PI only as a result of experience with its effects. A self-allocated study time procedure was employed to examine differences in study time for control and interference pairs. It was found that participants did not spend more time studying interference pairs than control pairs in round 1 but did so in round 2—presumably, as an attempt to diminish the effects of PI that they became aware of in round 1. The probability of intruding a list 1 response as an error when attempting to recall the list 2 response for interference pairs was lower on the second than on the first round. As important, confidence judgments were educated by prior experience, such that the difference in confidence between correct recalls and intrusion errors was larger on the second round than on the first round. The probability of an intrusion error being held at the highest level of confidence decreased across rounds for both young and older adults. This reduction in high-confidence intrusion errors is important because PI is likely to have a deleterious effect in everyday situations only when confidence in the accuracy of erroneous responses is high (e.g., Hay & Jacoby, 1996 ).

The goals of the experiments reported in the present article were to replicate the results reported by Jacoby et al. ( 2010 ) for young adults and to further explore the means by which prior encounters with PI diminish its effects. An anonymous reviewer of the article by Jacoby et al. ( 2010 ) suggested that the reduction in PI observed in their experiments might have resulted from reduced attention to list 1 during the second, as compared with the first, round. Against that possibility, performance on facilitation pairs in which both the cue and the response were the same for the two lists (A–B, A–B) did not worsen across rounds, whereas a reduction in attention to list 1 would be expected to produce an effect of that sort. Regardless, Experiment 1 in the present study more directly tested whether memory for list 1 items decreased across rounds. To anticipate, the results of Experiment 1 revealed that prior experience with PI diminished its effects, even though there was no decrease in memory for list 1, the source of PI, across rounds. Experiments 2 and 3 further investigated the means by which prior experience with PI reduced its effects.

Experiment 1

In Experiment 1, we examined the possibility that the reduction in PI as a result of prior experience found by Jacoby et al. ( 2010 ) was due to reduced attention to list 1 items in the second round. To more directly test that account, cued recall of a small set of filler items from list 1 was tested immediately following the presentation of list 1 on each of the two rounds. The filler items that were tested did not overlap across rounds, nor did they overlap with the critical items used to manipulate the relationship between items in lists 1 and 2. As in the experiments by Jacoby et al. ( 2010 ), the critical items maintained the same response across lists (A–B, A–B), had the same cue but a different response in the two lists (A–B, A–D), or were control items and appeared only in the second list (rest, C–D).

The goal of testing filler items was not to examine the effects of prior testing on PI but, rather, was to examine memory for list 1 items so as to detect any reduction in attention to list 1 items across rounds. Reduction in PI across rounds in the condition that included tests of filler items from list 1 was compared with that in a condition that did not include such tests—a condition that was the same as that used by Jacoby et al. ( 2010 ). Given that Jacoby et al. ( 2010 ) showed no effects of round on recall of facilitation items (i.e., A–B, A–B pairs), we expected testing of list 1 items to reveal that memory for list 1 would not change across rounds and also expected the reduction in PI across rounds to be the same for tested and nontested conditions. This pattern of results would provide evidence that the reduction in PI across rounds was not due to reduced attention to list 1.

However, testing filler items from list 1 might increase list differentiation for the nontested critical items and, so, produce differences in PI between the tested and nontested conditions. Tulving and Watkins ( 1974 ) found that testing memory for paired associates influenced the accessibility of list 1, as compared with list 2, responses in an A–B, A–D paradigm when participants were asked on a final test to recall responses from both lists. When the first list was tested, participants were better able to remember the most recent responses (i.e., D > B), but the opposite was true (i.e., D < B) when the first list was not tested. Recent investigations of PI (Brewer, Marsh, Meeks, Clark-Foos, & Hicks, 2010 ; Szpunar, McDermott, & Roediger, 2008 ) have shown that testing decreases PI in free recall learning. In contrast to experiments showing testing effects on PI, we only tested filler items, not the critical items that were used to examine the effects of PI. Any reduction in PI produced by testing filler items should be revealed by differences in PI between the tested and nontested conditions.

Participants

Seventy-two Washington University undergraduates participated in exchange for course credit or $10/hr. Thirty-six participants were randomly assigned to each between-subjects group (list 1 test: present vs. absent). All the participants were tested individually.

Design and materials

A 3 (item type: facilitation vs. control vs. interference) × 2(round: first vs. second) × 2 (list 1 test: present vs. absent) mixed design was used. Item type and round were manipulated within subjects, and presence vs. absence of list 1 test was manipulated between subjects. The materials consisted of 152 three-word sets that included one cue word (e.g., knee ) and two associatively related responses (e.g., bone , bend ). The bulk of these sets were selected from the norms reported by Jacoby ( 1996 ), and the remaining sets were created from the norms reported by D. L. Nelson, McEvoy, and Schreiber ( 1998 ). The responses in each set had the same number of letters and could complete the same word fragment (e.g., b _ n _). Six groups of 20 sets served as critical items, and two groups of 10 sets served as items to be tested in the list 1 test condition (these items were included but not tested in the test-absent condition). The remaining 12 sets served as buffers and practice items. Groups of items were matched on word frequency and length of cue and response words. The groups were rotated through each of the within-subjects conditions, resulting in six formats. Three primacy and three recency buffers served as practice items on each round of testing and remained constant across formats.

In the test-present group, each round consisted of four phases: list 1, list 1 test, list 2, and list 2 test. The test-absent group included the same phases, with the exception that filler items from list 1 were not tested in either round. List 1 consisted of 54 word pairs (e.g., knee bone ), including 4 pairs used as buffers in list 2, 10 pairs to be tested after list 1, and 40 critical pairs. Each pair appeared three times each, for a total of 162 presentations. List 2 consisted of 66 word pairs (six buffers, 60 critical items). Three buffers appeared at the beginning and end of the list to prevent primacy and recency effects. Twenty critical pairs represented the facilitation, the control, and the interference conditions. The facilitation pairs were the same as those in list 1 (e.g., knee bone , knee bone ), the control pairs appeared exclusively in list 2 (e.g., lamb wool ), and the interference pairs consisted of cues from list 1 paired with new responses that appeared only in list 2 (e.g., apple core , apple worm ). Each list 1 test consisted of 10 cues paired with word fragments, and each list 2 test consisted of 66 pairs arranged in the same manner. The fragments (e.g., apple _ or _) could be completed with either the target word or its competitor from an interference pair (e.g., core , worm ). Cue–fragment pairs were selected such that only the target and its competitor would complete the fragment with a word that was associatively related to the cue. The six buffer pairs from study were used for practice, and the remaining 60 pairs served as critical items.

All the stimuli were presented in white lowercase letters on a black background in the center of a computer screen. In list 1, word pairs were presented three times each in a fixed random order, with the restriction that no more than three pairs from the same condition were presented consecutively. Each pair was presented for 2 s, followed by a 500-ms interstimulus interval (ISI). Participants were instructed to read each word aloud quickly and accurately.

Participants in the test-present group were then presented with cue–fragment pairs in random order, and were told to complete the fragment with the target that was paired with the cue in list 1. Items remained on the screen until a response was made, followed by a 500-ms ISI. No effort was made to equate the spacing between lists 1 and 2 in the list 1 test-present versus test-absent groups, because the list 1 test was quite short (i.e., 10 items).

In list 2, pairs were presented in random order for 2 s, followed by a 500-ms ISI. Participants were instructed to read the pairs aloud and to study them for an upcoming memory test. Finally, on the list 2 test, cue–fragment pairs were presented in a fixed random order, with the restriction that no more than three pairs from the same condition were presented consecutively. Pairs remained on the screen until a response was made and were followed by a 500-ms ISI. Participants were instructed to complete the fragments with targets from list 2. Following each of their responses, participants made confidence judgments regarding the likelihood that their response was correct on a scale from 0 ( wild guess ) to 100 ( certain correct ). All responses were made aloud and were recorded by the experimenter. Participants were then given corrective feedback following each response. For target responses, “Correct” appeared in green ink, whereas “Incorrect” appeared in red ink for nontarget responses. The entire procedure was then repeated in a second round with a new set of materials.

Results and discussion

Preliminary inspection of the results revealed that the probability of correctly responding to items in the facilitation condition was near ceiling, and, so, we analyzed results from that condition separately from performance in other conditions. Our primary interest was in whether prior experience with PI would diminish its effects. Diminishing effects of PI would be evidenced by a significant interaction between round (first vs. second encounter with PI) and item type (control vs. interference) in the probability of intrusion errors. Responding to the cue from a control pair with the alternate to the target (the response that, for an interference pair, was presented in list 1 and served as a source of PI) was counted as an intrusion error for purposes of comparison with intrusion errors to interference items. The probability of producing either the target or its alternate was extremely high for facilitation (.98), control (.94) and interference (.98) items, and, so, errors other than producing an alternate response as an intrusion error did not enter into the analyses.

The probability of a correct response for items tested from list 1 was near ceiling and did not differ between round 1 and round 2 (.97 vs. .97), t < 1. On the test of memory for list 2, performance for facilitation items was near ceiling and did not differ depending on whether or not items that appeared only on list 1 had been tested (.92 vs. .91) and did not differ across rounds 1 and 2 (.92 vs. .92), F s < 1. These results allow one to dismiss the possibility that any reduction in PI across rounds was caused by reduced memory for list 1, the source of PI, across rounds.

The analysis of intrusion errors revealed that PI was reduced across rounds. A 2 (test) × 2 (item type) × 2 (round) ANOVA revealed a significant interaction between round and item type (control vs. interference), F (2, 140) = 9.82, \( \eta_p^2 = .{12} \) . Further analysis revealed significantly more intrusion errors in the interference condition in the first (.38) than in the second (.33) round, t (71) = 2.93, d = 0.36. The main effect of whether or not list 1 items were tested did not approach significance, F (1, 70) = 1.19, nor did the interaction of prior testing with item type or rounds, F s < 1. Consequently, the results were collapsed across those groups for display in the top section of Table  1 . As is shown in that table, the probability of an intrusion error decreased across rounds for interference pairs but did not do so for control pairs.

We examined the extent to which confidence judgments were diagnostic of correct responding by measuring the resolution of confidence judgments. Resolution refers to the item-level correlations between confidence and accuracy. These correlations provide information regarding how well confidence judgments discriminate between items that were correctly, as compared with incorrectly, recalled. That is, they provide an estimate of the extent to which high-confidence judgments are associated with correct responses and low-confidence ratings are associated with incorrect responses. Positive gamma correlations indicate effective discrimination between correct and incorrect responses. Note that in subsequent analyses, gamma correlations could not always be computed for all the participants, as a result of a constant value on one of the variables. That is, gamma correlations could not be computed in cases in which recall performance was perfect or when the same confidence judgment was given for all the items. Consequently, the degrees of freedom are lower in some analyses than would be expected, given the sample size.

To assess resolution, we computed the gamma correlations for each combination of conditions and then entered those correlations into an ANOVA (see T. O. Nelson, 1984 , for a detailed rationale for using gamma). The results from that analysis revealed a significant interaction between item type and prior testing of list 1, F (1, 67) = 4.82, \( \eta_p^2 = .07 \) . As is shown in Table  2 , resolution was higher for control pairs than for interference pairs. For the group without prior tests of list 1, this difference in resolution was decreased by resolution’s increasing for interference pairs from round 1 to round 2, particularly for interference items. We replicated the finding of an increase in resolution for the interference condition across rounds in Experiment 2. In contrast, the results for the group that had a prior list 1 test showed a slight decrease in resolution between rounds 1 and 2 for both control items and interference items. We have no explanation for this finding of a slight decrease in resolution for interference items, and it was not replicated in later experiments. As will be seen, however, we do find a significant decrease in later experiments in the resolution of confidence judgments for control pairs across rounds.

In sum, the results of Experiment 1 provide evidence that prior experience with PI reduces its effects and that the reduction is not due to reduced memory for the source of PI. The probability that items presented in list 1 would be recalled did not differ across rounds, whereas it would be expected to do so if attention were reduced in the second round.

The lack of an effect of testing on PI contrasts with recent findings that testing reduces PI in free recall learning (e.g., Brewer et al., 2010 ; Szpunar et al., 2008 ). There are many differences between our experiment and their experiments. Among those differences is the fact that we examined PI in the learning of paired associates, whereas they examined free recall learning. Also, we included facilitation pairs (i.e., A–B, A–B pairs), and the presence of those pairs might have reduced the list differentiation that would otherwise have resulted from testing. Most important, perhaps, we tested only filler items, not the critical items used to assess PI. In contrast, those finding testing effects on PI tested items that were used to assess PI.

Experiment 2

In Experiment 2, we returned to the procedure of not testing memory for list 1, so as to replicate the results reported by Jacoby et al. ( 2010 , Experiment 2). As did they, we used a self-allocated study time procedure to show that prior experience with PI was required for participants to become aware of and reduce its effects. The major difference between our experiment and theirs was that they used a free versus forced responding technique (Koriat & Goldsmith, 1996 ) for tests of PI, whereas we did not do so. We did, though, use a modified form of that technique in Experiment 3, which is described when that experiment is introduced.

Jacoby et al. ( 2010 ) found that study time did not differ for interference and control pairs in the first round, showing that participants were unaware of memory difficulties produced by PI. However, in the second round, as a result of prior experience with PI, participants devoted more time to studying interference pairs than to studying control pairs, so as to diminish the effects of PI. The attempt was successful in that PI was reduced in the second round, as compared with the first. As important, the ability of confidence judgments to discriminate between correct responses and intrusion errors for interference items improved across rounds. Jacoby et al. ( 2010 ) interpreted these results as evidence for a qualitative change in the basis for responding across rounds. They argued that participants relied more heavily on source-constrained retrieval in the form of recollection in the second round, whereas the less constrained fluency with which a response came to mind was the primary basis for responding in the first round.

Analyses of the results from the present experiment examined differences in the resolution of confidence judgments in order to gain evidence of a qualitative change in the basis for confidence across rounds. As was described earlier, the resolution of confidence judgments measures the extent to which confidence in a response predicts its accuracy at the level of individual items. We expected an interaction between item type (control vs. interference) and rounds to be produced by a qualitative change in the basis for confidence across rounds. Participants’ confidence judgments in the first round were expected to rely heavily on a fluency heuristic (Jacoby, Bishara, Hessels, & Toth, 2005 ; Jacoby & Dallas, 1981 ), with the highest confidence held for responses that most easily came to mind. Reliance on fluency would provide a valid basis for confidence judgments for control items, because a competitor was not presented for those items earlier. However, for interference items, reliance on fluency would result in erroneous confidence in intrusion errors, because of encounters with the intruding response during list 1. In the second round, having gained experience with PI, participants were expected to shift from heavy reliance on fluency to the ability to recollect the list 2 presentation of a tested item, a more valid basis for confidence in responses to interference items. A qualitative change in bases for confidence of this sort would result in improved resolution of confidence judgments across rounds for interference items. In contrast, for control items, shifting away from reliance on fluency might produce the opposite effect of reducing resolution, because fluency serves as a valid basis for confidence in responses to control items. Abandoning this valid basis for confidence might reduce resolution for control items, because fluency may serve as a basis for high confidence in responses whose prior study encounter could not be recollected.

Twenty-four Washington University undergraduates participated in exchange for course credit or $10/hr. All the participants were tested individually.

Design, materials, and procedure

The design, materials, and procedure were identical to those used in Experiment 1, with the following exceptions. No items were employed for tests of memory for list 1 responses, resulting in a total of 132 three-word sets (e.g., knee - bone , bend ). In both rounds, list 1 included 44 items presented 3 times each, for a total of 132 presentations. In addition, study time for list 2 items was allocated by participants. Participants were informed about the relationship between list 1 and list 2 pairings and were told to study the pairs presented in list 2 until they had been completely learned. Participants pressed the space bar upon completion of studying each pair.

As was found in Experiment 1, performance on facilitation items was near ceiling (.95) and did not differ across rounds. The probability of producing either the target or its alternate was extremely high for facilitation (.99), control (.99), and interference (.99) items, and, so, errors other than producing an alternate response as an intrusion error did not enter into the analyses.

The middle section of Table  1 shows that the pattern of intrusion errors was similar to that found in Experiment 1. PI effects were diminished by prior experience, as is shown by a significant interaction indicating that the difference between intrusion errors for control and interference conditions was smaller in the second round than in the first, F (1, 23) = 13.62, \( \eta_p^2 = .37 \) . Also, self-paced study had a tendency to further diminish PI, in comparison with the results obtained in Experiment 1, which employed a fixed study time procedure.

As was predicted, the resolution of confidence judgments, as indexed by the gamma correlation between confidence and accuracy, increased across rounds for the interference condition (.39 vs. .57) but decreased slightly across rounds for the control condition (.86 vs. .82), F (1, 15) = 8.14, \( \eta_p^2 = .35 \) . This finding provides evidence that participants profited from prior experience with PI by shifting the bases for confidence judgments from reliance on a fluency heuristic in the first round to reliance on ability to recollect in the second round. As was described earlier, a shift of this sort would increase the resolution of confidence judgments for interference items but would reduce resolution for control items. To anticipate, this pattern of results was replicated in Experiment 3.

The opposite effects of prior experience with PI on resolution for control and interference items provides evidence of a qualitative shift in the bases for confidence that was aimed toward reducing high-confidence erroneous responses. Reliance on ability to recollect, rather than on fluency, as a basis for confidence would serve to reduce high-confidence errors to interference items and, so, would increase the resolution of confidence judgments in that condition. In contrast, for control items, fluency serves as a valid basis for confidence, and, so, its abandonment would decrease the resolution of confidence judgments for that condition. These opposite effects on the resolution of confidence judgments cannot be accounted for by positing a quantitative shift involving familiarity or any other single basis for confidence.

Prior experience with PI resulted in participants’ altering their study of interference pairs. The pattern of study time allocation (Table  3 ) revealed that study time reflected item difficulty across item types better in the second round than in the first round. Study time did not differ between the control condition and the interference condition in the first round, whereas less time was spent on items from the control condition than on those from the interference condition in the second round, F (1, 23) = 8.93, \( \eta_p^2 = .28 \) . The least amount of study time was allocated to items in the facilitation condition in both rounds, F (1, 23) = 24.80, \( \eta_p^2 = .52 \) . Finally, the overall amount of study time decreased from the first round to the second round, F (1, 23) = 11.27, \( \eta_p^2 = .33 \) .

Overall, these results replicate the results reported by Jacoby et al. ( 2010 , Experiment 2). Allowing self-allocated study time further diminished the effects of PI in round 2, as compared with the results in Experiment 1, in which study time was experimenter controlled and, typically, less than was self-allocated by participants. Furthermore, the resolution of confidence judgments for interference items increased across rounds but slightly decreased across rounds for control items. Whereas we examined resolution, Jacoby et al. ( 2010 ) examined the effects of prior experience on differences in confidence judgments for correct responses and intrusion errors. Corresponding analyses of differences in confidence judgments for correct responses and errors in the present study revealed a pattern of results consistent with those in Jacoby et al. ( 2010 ) but are not reported in detail because they provide no new information. The increase in study time for interference, relative to control, pairs shows that participants became aware of the greater difficulty of interference items as a result of prior experience with PI and increased their study time as an attempt to overcome the effects of PI.

The overall reduction in study time across rounds suggests that prior experience with PI, as well as with the form of test, produced qualitative, as well as quantitative, changes in encoding processes. It is noteworthy that the probability of an error did not increase across rounds for facilitation and control items and substantially decreased for interference items, although the amount of time devoted to study decreased in the second round for all conditions. These shifts in study time provide evidence that participants became aware of the effects of PI and, consequently, modified their encoding strategies to better support recollection at the time of test.

What was the basis for the allocation of study time across types of pairs (facilitation, control, and interference pairs)? One possibility is that after gaining experience with PI, study time was allocated on the basis of the ease with which an alternative response came to mind. Doing so would result in additional study time being allocated to interference items, which had a readily accessible competitor. Alternatively, participants may have relied on their ability to detect a change in responses between list 1 and list 2 as a basis for allocating study time. With this strategy, little study time would be allocated to a facilitation pair that was recognized as having the same response as in list 1, whereas additional time would be allocated to an interference pair that was recognized as having a changed response.

Experiment 3

The results of Experiment 2 provided evidence that prior experience with PI reduced its effects by producing a shift from reliance on fluency to greater reliance on recollection as a basis for responding and confidence in responses. Experiment 3 was designed to further examine the mechanisms underlying the reduction of PI by exploring changes in retrieval processes. Experiment 3 was similar to Experiment 2, with one change being that study time was held constant, as in Experiment 1. Also, participants were given the option of withholding responses. After being forced to respond to each test item, participants gave a confidence judgment and were then given the option to volunteer or withhold their response (e.g., Koriat & Goldsmith, 1996 ). This option made it possible for participants to withhold incorrect responses to interference items so as to further diminish PI effects (cf. Jacoby et al., 2010 , Experiment 2).

In addition to being forced to respond to each test item, participants were told that they were to retrieve the list 2 response but should also report any other candidate responses that came to mind prior to the response that they output. They were told to stop producing candidates when they thought that the list 2 response had been reached. This was done to measure how often participants reported that a competing list 1 response came to mind prior to or simultaneously with the target response from list 2 (cf. Halamish, Goldsmith, & Jacoby, 2008 ). Doing so is useful for understanding how experience with PI reduces its effects. One possibility is that experience results in participants being more likely to use source memory to reject a competing response after it comes to mind (cf. Johnson, Hashtroudi, & Lindsay, 1993 ; Winograd, 1968 ). On this source memory account, the reduction in PI that results from prior experience is produced by participants’ improved ability to reject a strong competitor (i.e., a list 1 response) after it comes to mind. Alternatively, the results of Experiment 2 suggest that the reduction of PI by prior experience was produced by participants’ learning to constrain retrieval processes so as to recollect the list 2 response. Heavier reliance on recollection would be expected to result in the competing response being less likely to come to mind (cf. Jacoby, Debner, & Hay, 2001 ; Jacoby, Shimizu, Velanova, & Rhodes, 2005 ).

Both the source memory and recollection accounts predict that the number of intrusion errors to interference pairs will decrease across rounds but will do so for different reasons. Examining changes in PI across rounds separately for cases in which an alternative response did or did not come to mind provides a means of choosing between the two accounts. The source memory account focuses on response competition and holds that prior experience improves the ability to choose the target over other responses that come to mind. The prediction is that when alternatives to a produced response are reported as having come to mind, the probability of the produced response being correct will increase across rounds. In contrast, the recollection account holds that prior experience increases ability to constrain retrieval processes such that only the target response comes to mind. The prediction is that when no other responses are reported as having come to mind, the probability of the produced response being the correct one will increase across rounds.

The design, materials, and procedure were identical to those used in Experiment 2, with the following exceptions. The study duration for items in list 2 was fixed at 2 s in both rounds. At the time of test, participants were told that their primary task was to retrieve the responses presented in list 2. In addition, participants were told to report any other responses related to cues that fit the fragments as they came to mind during retrieval of list 2 responses. Participants were allowed to produce a maximum of two candidate responses and were told to stop once they thought that the list 2 response had been given. This was done in an attempt to restrict participants’ candidate production to intraexperiment responses. Participants reported the candidates aloud, and an experimenter typed them onto the computer screen.

After giving their final responses, participants rated their confidence aloud, using the same scale as that in Experiments 1 and 2. Next, participants were given a report option that allowed them to either volunteer or withhold responses. A screen appeared that read “Report?” with the options to respond yes or no aloud. Participants were told that they should volunteer responses only when they felt sufficiently confident that the responses were correct. As an incentive to use the report option to maximize their memory accuracy, five points were added to a running total for correct volunteered responses, whereas 15 points were deducted for incorrect volunteered responses. For withheld responses, no points were gained or lost, and no feedback was provided. The running point total was displayed in the upper right-hand corner of the screen.

As was found in Experiments 1 and 2, performance on facilitation items was near ceiling (.91) and did not differ across rounds. The probability of producing either the target or its alternate was extremely high for facilitation (.98), control (.95), and interference (.99) items, and, so, errors other than producing a list 1 intrusion did not enter into the analyses.

In the following analyses, forced-report tests include all the responses given at the time of test, whereas free-report tests include only the volunteered responses. The probabilities of an intrusion error for the forced- and free-report tests are shown in Table  4 . Performance for facilitation pairs was near ceiling, and, so, there was little room for free report to improve accuracy for that condition. An analysis that included only the control and interference conditions revealed that allowing free report did more to increase accuracy of responding for control items than for interference items, F (1, 23) = 8.07, \( \eta_p^2 = .26 \) . The triple interaction of report option, round, and item type (control vs. interference) only approached significance, F (1, 23) = 2.88, p = .10, \( \eta_p^2 = .11 \) , suggesting that there was a tendency for the accuracy advantage gained by allowing free report for control items, as compared with interference items, to be larger in round 1 than in round 2. However, the results reported by Jacoby et al. ( 2010 ) gave a priori grounds for analyzing results separately for free versus forced responding, although the relevant interaction only approached significance. These further analyses revealed that although intrusions on interference items decreased across rounds for both forced and free report, the difference was significant only for free report, t (23) = 2.17, d = 0.35. The results are similar to those reported by Jacoby et al. ( 2010 ) in suggesting that the option to not respond allowed participants to further diminish the effects of PI.

An analysis of gamma correlations between confidence judgments and accuracy on the forced-report test revealed a significant interaction between item type (control vs. interference) and round, F (1, 19) = 7.00, \( \eta_p^2 = .27 \) . The resolution of confidence judgments increased across rounds for interference items (.31 vs. .43) but decreased across rounds for control items (.75 vs. .60). The form of the interaction is the same as that found in Experiment 2. Again, the interaction provides strong evidence of a qualitative change in the basis for confidence across rounds. A quantitative change cannot account for the opposite effects of prior experience with PI on resolution for control and interference items.

Decreased reliance on a fluency heuristic as a basis for confidence would decrease the resolution of confidence judgments for control items, because fluency serves as a valid basis of confidence for those items. Although recollection can be considered a more certain basis for confidence than is fluency, the failure to recollect does not always lead to incorrect responses. That is, fluency can still drive accurate responding in the absence of recollection for control items. Thus, confidence judgments that take fluency and recollection into account are likely to be more accurate assessments of memory performance than are those based on recollection success. In contrast, a decrease in reliance on fluency, along with increased reliance on recollection, as a basis for confidence for responses to interference items would increase the resolution of confidence judgments for interference items, because fluency is often a misleading basis for confidence in interference situations.

The reduction in resolution across rounds for control items was larger in Experiment 3 than in Experiment 2. This likely resulted from the requirement at test to report any responses that came to mind prior to the response that was output. That requirement, along with prior experience with PI, likely encouraged the abandonment of reliance on a fluency heuristic for confidence, to the disadvantage of the resolution of confidence judgments for responses to control items. In turn, the increase in resolution across rounds was smaller for interference items in Experiment 3 than in Experiment 2. This difference can be explained as arising because the self-allocated study time procedure employed in Experiment 2 allowed greater opportunity to overcome the effects of PI by studying in ways that enhanced later recollection.

Analysis of whether another response came to mind prior to the response that was output is informative with regard to means by which experience with PI diminished the probability of an intrusion error for interference items. Increased reliance on recollection during the second round was expected to increase the probability that a produced response was correct when no alternative response was reported as having come to mind. The probability of participants’ saying that another response came to mind prior to the response that they output on tests for interference items was low on both round 1 and round 2 (.35 vs. .31).

When the conditional probability of an intrusion error given that no other response came to mind prior to the response that was output was examined, the probability of an intrusion for interference items decreased across rounds (.43 vs. .34), t (23) = 2.21, d = 0.39. This result is in accord with the expected heavier reliance on recollection during the second round than during the first (i.e., the source-constrained retrieval account). In contrast, the source-monitoring account predicts that the reduction in PI across rounds results from an increased ability to successfully resolve response competition by choosing the correct response when alternative responses have also come to mind. Against that account, when alternatives to the correct response were reported as having come to mind, there was little decrease in the probability of an intrusion error across rounds (.30 vs. .28), t (21) < 1.

An unexpected finding was that the probability of an intrusion error for interference items was lower when another response came to mind prior to the response that was output than when another response did not come to mind, F (1, 21) = 5.93, \( \eta_p^2 = .22 \) . We return to discussion of this unexpected finding after further considering conclusions that can be drawn regarding the recollection and source memory accounts of reduced PI.

Although reliance on source memory in rejecting a competing response after it comes to mind might play some role, our results provide evidence that increased reliance on recollection is largely responsible for prior experience with PI diminishing its effects. When only one response comes to mind for a test item in the interference condition, that response is likely to be the competitor if one relies upon overall strength, because of the multiple presentations of the competitor in list 1. However, as a result of prior experience with PI, participants became more likely to engage in source-constrained retrieval, so as to recollect the list 2 response (i.e., the target). Doing so increased the probability of their producing the target without other alternatives coming to mind. That is, participants shifted from reliance on a less-constrained fluency basis for responding in round 1 to greater reliance on recollection as a basis for responding in round 2. The reduction in intrusion errors across rounds when alternative responses did not come to mind converges with the effects of prior experience on the resolution of confidence judgments in providing evidence for a shift toward heavier reliance on recollection.

Why was the probability of an intrusion error lower when other responses were reported as having come to mind? One possibility is that source memory might sometimes serve to reject a competitor after it comes to mind. An incorrect response’s coming to mind as a competitor for the target would be more advantageous than would having an intrusion error be sufficiently strong as to be produced without the target’s coming to mind. A high percentage of the responses that were produced without other responses coming to mind were intrusion errors. Obviously, the target’s not coming to mind made it less likely to be produced as a response, as compared with the case in which it came to mind along with alternative responses. Although the probability of recollection increased across rounds, a less constrained, strengthlike basis for responding still played a role in the second round, as evidenced by the high probability of an intrusion error being presented without an alternative response coming to mind. The recall advantage of other items’ coming to mind might reflect the strengthlike basis for responding.

An alternative possibility is that the advantage of other items’ coming to mind might result from participants’ reliance on mediation processes for correct responding to interference items. The materials in our experiments were selected to produce an overlap in letters between a target and its alternative response, so as to allow both to be a possible completion for the same word fragment. As well as this orthographic similarity, for some pairs, there was an associative relation between a target word and its competitor. In this vein, Barnes and Underwood ( 1959 ) investigated retroactive interference with the materials being such that list 1 and list 2 responses were associatively related (A–B, A–Bʹ) and found evidence that access to list 1 response was sometimes mediated by the list 2 response. Although extraexperimental associations between list 1 and list 2 responses could potentially account for the benefit of another response’s coming to mind prior to a final response, the average forward-associative strength between list 1 and list 2 responses (see D. L. Nelson et al., 1998 ) for items in our experiments was quite low (.03). Thus, the advantage of other responses’ coming to mind may have reflected mediation processes. However, such mediation played little, if any, role in the increased resistance to PI across rounds. The probability of other responses being reported as having come to mind did not increase across rounds, nor was there a substantial decrease across rounds in the probability of an intrusion error when other responses were reported as having come to mind. Either one or both effects would be expected had mediation played a role in the reduction of PI across rounds.

General discussion

The results from our experiments replicate the results reported by Jacoby et al. ( 2010 ) by showing that prior experience with PI diminished its effects. In addition, Experiment 1 provided evidence that the reduction in PI across rounds did not occur because of reduced attention in the second round to list 1, the source of PI. Ability to recall list 1 responses was shown to be near ceiling and to not change across rounds. The results from Experiments 2 and 3 converge to produce strong evidence that prior experience reduces its effects by means of a shift toward heavier reliance on recollection as a basis for responding. That shift reflects both a change in encoding and a change in retrieval processes.

Changes in the allocation of study time revealed that participants became more sensitive to the difficulty of interference items after experience with PI. Participants did not devote more time to interference than to control items in the first round, but did so in the second round ( Experiment 2 ). Participants were more aware of PI effects in the second than in the first round and compensated for those effects by devoting more study time to interference than to control items. In addition to a quantitative shift, it is likely that there was also a qualitative shift in encoding processes. Less study time was devoted to all the items in the second round, yet accuracy for interference items increased across rounds. One possibility is that participants studied items in ways that allowed them to better encode the list membership of items during the second round.

The resolution of confidence judgments in the interference condition improved as a result of prior experience with PI. In contrast, the resolution of confidence judgments for control items decreased or was unchanged across rounds. The finding that the resolution of confidence judgments in the interference condition improved across rounds provides evidence that prior experience with PI resulted in a shift away from a fluency heuristic (e.g., Benjamin, Bjork, & Schwartz, 1998 ; Kelley & Lindsay, 1993 ) to reliance on the success of recollection as a more valid basis for confidence. Further evidence of a shift in bases for confidence is provided by the finding that monitoring the resolution of confidence judgments decreased across rounds for control items. This reduction would be expected if participants switched to reliance on recollection success, reducing reliance on less constrained accessibility of a response. The fluency with which a response comes to mind is a valid basis for confidence for control pairs but is a misleading basis of confidence for interference pairs. For interference pairs, if one is not constraining retrieval in ways that support recollection, the competing response is likely to fluently come to mind.

Finally, in Experiment 3, reductions in PI did not result from increased use of source memory to reject a competitor after it came to mind. Instead, as a result of prior experience with PI, participants more often produced the list 2 response without the competitor even coming to mind. The increase in the probability of a target response’s coming to mind as the only response would be expected if experience with PI had the effect of encouraging participants to rely on recollection as a basis for responding. Recollection relies on preretrieval processes that employ the source of the target to elaborate the cues provided by retrieval so as to restrict access to the target item (e.g., Jacoby, Shimizu et al., 2005 ; Jacoby, Kelley, & McElree, 1999 ). This source-constrained retrieval, which operates prior to memory access, contrasts with postaccess source monitoring. Source monitoring serves to edit potential responses after they come to mind so as to withhold candidate responses that did not originate from the target source (e.g., Koriat & Goldsmith, 1996 ).

The results from the present experiments converge with those from earlier experiments in showing that success in avoiding the negative effects of PI depends on engaging in successful recollection. Hay and Jacoby ( 1999 ) examined the effects of PI by using procedures similar to those used in the present experiments. However, conditions were changed so as to implement a process dissociation procedure for estimating the probability of recollection. They gained evidence suggesting that PI results from a form of bias that has an effect only when recollection fails. Jacoby et al. ( 2001 ) reported similar results and related recollection to the subjective experience of remembering.

By emphasizing encoding processes in combination with retrieval processes, we join Postman and Underwood ( 1973 ) in their evaluation of the importance of list differentiation for identification of the list membership of a response after it comes to mind. They wrote that ". . . the critical factor is not the subject’s ability to identify the list membership of whatever responses do occur but rather the mechanism governing the availability of alternative response repertoires for recall" (p. 24). We agree, as do our data. Learning to diminish the effects of PI relies more on enhancing recollection so as to prevent a competing response from coming to mind than on source memory, the ability to identify the list membership of a response after it comes to mind.

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Christopher N. Wahlheim and Larry L. Jacoby, Department of Psychology, Washington University in St. Louis, MO. This research was supported by Binational Science Foundation Grant 2005356 and by a James S. McDonnell Foundation 21st Century Science Initiative in Bridging Brain, Mind, and Behavior Collaborative Award. We thank Sarah Arnspiger, Rissa Ivens, Miranda Lindberg, Danielle Hirschfeld, Carlee Beth Hawkins, Carole Jacoby, and Rachel Teune for their assistance with data collection. Correspondence concerning this article should be addressed to Christopher N. Wahlheim, Department of Psychology, Washington University, St. Louis, MO 63130. E-mail: cnwahlheim@gmail.com.

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Wahlheim, C.N., Jacoby, L.L. Experience with proactive interference diminishes its effects: mechanisms of change. Mem Cogn 39 , 185–195 (2011). https://doi.org/10.3758/s13421-010-0017-4

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Processes of proactive interference were explored using the pigeon as a model system of memory. This study shows that proactive interference extends back in time at least 16 trials (and as many minutes), revealing a continuum of interference and providing a framework for studying memory. Pigeons were tested in a delayed same/different task containing trial-unique pictures. On interference trials, sample pictures from previous trials reappeared as test pictures on different trials. Proactive-interference functions showed greatest interference from the most recent trial and with the longer of two delays (10 s vs. 1 s). These interference functions are accounted for by a time-estimation model based on signal detection theory. The model predicts that accuracy at test is determined solely by the ratio of the elapsed time since the offset of the current-trial sample to the elapsed time since the offset of the interfering sample. Implications for comparing memory of different species and different types of memory (e.g., familiarity vs. recollection) are discussed.

Keywords: comparative psychology, memory, time perception, cognitive processes, signal detection theory

The study of short-term memory has a history of focusing on decay and forgetting in order to account for performance decreases over time ( Baddeley, 1992 ; Brown, 1958 ; Peterson & Peterson, 1959 ). Capacity-limited models of short-term memory continue this trend of focusing on decay and forgetting (e.g., Atkinson & Shiffrin, 1968 ; Cowan, 2001 , 2005 ; Rensink, 2002 ). A limited-capacity short-term memory would rapidly turn over as other stimuli in the environment are encountered. By contrast, no decline in memory performance (i.e., no memory decay or short-term turnover) was found by Keppel and Underwood (1962) on the first tests of stimuli, but substantial declines occurred, particularly at longer delays, after only three repetitions of those stimuli. The authors concluded that repeating the same stimuli produced proactive interference on subsequent trials and thereby caused the observed decline in memory performance.

Proactive interference has been shown in recognition-memory procedures using small sets of repeating stimuli with humans and (nonhuman) animals when stimuli to be identified as “different” (from the to-be-remembered stimuli) have been seen on the immediately preceding trial (e.g., Makovski & Jiang, 2008 ; Roberts & Grant, 1976 ). It is somewhat remarkable that any stimulus-specific interference effects were discernible in these studies because the stimuli from these small sets had been seen hundreds of times, which likely produced near-saturation of proactive interference. To more thoroughly explore proactive interference—that is, explore proactive interference from stimuli further back in time than just the preceding trial—requires that the background level of proactive interference on baseline trials be lowered by using a large stimulus set and minimizing stimulus repetitions. If the background level of proactive interference is minimized, then the effects of controlled interference can be judged against a baseline of no interference to reveal the extent and limits (e.g., the capacity) of different types of memory (e.g., short-term and long-term memory) with and without proactive interference, which will perhaps lead to improved comparisons of memory among species.

In same/different and serial-probe-recognition tasks, proactive interference occurs when previously seen sample pictures are later re-presented as test pictures on trials with nonmatching sample pictures (i.e., different trials). Having seen the test picture previously tends to create confusion as to whether this picture was the sample picture in the current trial or in some previous trial. In the experiment reported here, we used a large set of pictures (1,024 pictures of man-made objects, natural objects, animals, scenes, etc.) selected to be trial unique for at least 2 weeks of testing (except for stimuli on the proactive-interference tests). We tested interference of memory at two delays by systematically placing interfering stimuli 1, 2, 4, 8, or 16 trials prior to interference tests in a delayed same/different task with trial-unique baseline trials. Surprisingly, interference was greater at the longer delay, despite the interfering stimuli being encountered considerably further in the past than at the shorter delay.

The 4 pigeons in the current study were trained to perform a delayed same/different task with pairs of pictures (selected from the set of 1,024 pictures; for more details, see Subjects and Apparatus in the Supplemental Material available online; also see Katz & Wright, 2006 , for a similar training procedure). The pigeons pecked a sample picture presented in the upper half of a computer screen 20 times (a fixed-ratio 20, or FR 20, schedule), and then the screen went blank. Following a delay, a test picture plus a white rectangle were presented in the lower half of the screen (see Fig. 1 ). If the two pictures were the same, then a peck to the test picture was correct; if they were different, then a peck to the white rectangle was correct. All the pigeons showed accurate transfer to novel stimuli, demonstrating abstract-concept learning. They were then trained extensively, with increasing delays between the offset of the sample picture and the onset of the test picture, prior to proactive-interference testing at 1-s and 10-s delays.

Fig. 1

Example trial sequence for proactive-interference testing. In this example, an interference stimulus is presented as the sample on trial n − 1. This same stimulus appears again on the next trial ( n ) as the test stimulus. The correct response on trial n is a “different” response (a peck to the white rectangle). However, having seen this stimulus on the previous trial increases the chances of an error (making a “same” response by pecking the test picture) due to confusing the previous sample (on trial n − 1) with the current sample (on trial n ). On each trial, pigeons were required to peck the sample picture 20 times (a fixed-ratio 20, or FR 20, schedule) before the delay began. The relative sizes of the pictures, white rectangle, and monitors in this illustration are not to scale.

Proactive-interference testing began with a block of 24 sessions at the 1-s delay, followed by a block of 24 sessions at the 10-s delay. We then repeated these tests (using different interference pictures and picture sequences) to assess reproducibility and any effects of testing order. Each daily session consisted of 64 trials with five interference tests (one test each at the 1-, 2-, 4-, 8-, and 16-trial separations). Trials other than those of the interference tests (i.e., same and different baseline trials) contained randomly selected (without replacement) pictures from the 1,024-picture set. There were overall totals of 32 same and 32 different trials in each session. Pictures used to test for interference had not been presented for at least 10 sessions (2 weeks) and had not been used as previous interference-test pictures.

Figure 2 shows the major results from the proactive-interference tests. The percentage of correct responses was analyzed in a three-way Testing Order (first two blocks, second two blocks) × Delay (1 s, 10 s) × Interfering-Stimulus Separation ( n − 1, n − 2, n − 4, n − 8, n − 16, no-PI) repeated measures analysis of variance (ANOVA). For the no-PI, baseline condition, only different -trial performance was used in this and other analyses because PI trials were different trials (see Statistical Analyses of Baseline Performance in the Supplemental Material ). This analysis showed significant main effects of delay, F (1, 3) = 25.95, p < .016, η p 2 = .896; interfering-stimulus separation, F (5, 15) = 19.91, p < .001, η p 2 = .869; and the Delay × Interfering-Stimulus Separation interaction, F (5, 15) = 4.05, p < .017, η p 2 = .574. There was no significant effect of testing order, F (1, 3) = 1.1, p > .37, and there were no interactions between testing order and other factors, F s < 1.02; therefore, results from the two tests at each delay were combined in Figure 2 (see Statistical Analyses of Baseline Performance in the Supplemental Material ).

Fig. 2

Mean results of 4 pigeons on the same/different task at 1-s and 10-s delays between the offset of the sample stimulus and onset of the test stimulus. Percentage correct is shown as a function of the number of trials separating the interfering stimulus and the test. On the left of the x -axis, “ n − 1” refers to the condition in which the interfering stimulus occurred on the immediately preceding trial. On the right of the x -axis, “no-PI” refers to the no-interference, or different -trial baseline, condition. Error bars represent standard errors of the mean.

At the shorter delay of 1s ( Fig. 2 ), there was a 17.1% interference effect for stimuli presented on the immediately preceding two trials ( n − 1, n − 2) relative to baseline (no-PI) accuracy, t (3) = 4.22, p < .025. This interference effect largely dissipated when the interfering picture was presented 16 trials prior to test: Performance was 80.2% accurate with the 16-trial interfering-stimulus separation, compared with 84.7% in the no-PI (baseline) condition, t (3) = 1.99, p > .14. Trend analyses confirmed that accuracy significantly increased as a function of the number of intervening trials for both the 1-s and the 10-s delays, F s(1, 3) > 14.54, p s < .04.

At the longer delay of 10 s ( Fig. 2 ), the interference effect for stimuli presented on the immediately preceding trial ( n − 1) was much greater (41.7%), t (3) = 5.4, p < .013, than at the shorter delay of 1 s (17.1%). As trial separation at the 10-s delay gradually increased from 1 to 16 trials, accuracy rose a substantial 30% (from 37.0% to 67.7%, respectively), t (3) = 5.94, p < .011. Nevertheless, there was still an 11% interference effect for stimuli presented 16 trials prior (and 16 min prior) to the test (see Elapsed Times in the Supplemental Material ). It is important to note that below-chance performance (37% in this case) is meaningful because proactive interference could theoretically have driven accuracy to 0%.

Our finding of greater interference of memory at the longer (10-s) delay than at the shorter (1-s) delay is counterintuitive. Although the interfering stimuli at the 10-s delay were encountered more distantly in the past than were the interfering stimuli at the 1-s delay (> 200 s more distantly for n − 16; see Elapsed Times in the Supplemental Material ), they nevertheless produced greater interference. Encountering stimuli more distantly in the past should, according to models of decay or limited capacity, translate to more forgetting and therefore less interference. But just the opposite occurred.

We used a model based on signal detection theory to explain why the longer (10-s) delay produced greater interference. A direct consequence of this model is that interference depends on time ratios, not absolute times. According to the model, the subject retrieves memory of sample pictures, including not only the most recent sample picture but also other recently viewed sample pictures. However, the subject’s memory about when these sample pictures were seen is “noisy,” which results in some probability of the subject mixing up the temporal order of the current and a past sample picture. When a sample picture from a previous trial is identified as a match to the current test picture, the subject may erroneously make a “same” response.

The internal representation of elapsed time is assumed to follow the well-known Weber-Fechner law, or log scale of time ( Buhusi & Meck, 2005 ; Gibbon, 1977 ), and to vary from trial to trial, as shown in Figure 3a . The subject makes its decision on a given trial according to a likelihood ratio determined on the basis of noisy evidence and a criterion for responding “same” or “different.” Therefore, the model accounts for response biases (“same” or “different” biases); in addition, it incorporates a measure of random guessing, because pigeons’ performance (like that of other nonhuman animals) is seldom 100% accurate. Performance is predicted to depend only on the ratio of the time elapsed since the offset of the current sample (i.e., delay time, denoted T C ) to the time elapsed since the offset of the interfering sample (denoted T I ; see Elapsed Times in the Supplemental Material ). The model is expressed in the following equation:

where PC model is the proportion of correct responses predicted by the model, erf is the error function, g is the guessing rate, b is the response bias, and σ is the standard deviation of the noise (for the derivation, see Signal Detection Theory Model of Proactive Interference in the Supplemental Material ). The model was fit to the functions for both the 1-s and the 10-s delay, simultaneously for each subject, which provided considerable constraint to each fit. The means of the individual fits are shown in Figure 3b (see Model Fitting in the Supplemental Material for individual subjects’ fits). The model provides an excellent quantitative match ( R 2 = .95) to the proactive-interference functions from both delays and also, importantly, to the results for the no-PI condition.

Fig. 3

Model and data fit. In our signal detection model of proactive interference (a), the signal is given by the difference between the log of the retention-delay time (log T C ) and the log of the time between the offset of the interfering sample presented in a previous trial and the onset of the test-trial picture (log T I ). The observer’s internal representation of elapsed time is noisy, as indicated by the width of the normal distributions. The graph (b) shows the mean model fit to the data from Figure 2 . The model was fit simultaneously to the proactive-interference functions for both delays for each individual subject. On the right of the x -axis, “no-PI” refers to the no-interference, or different -trial baseline, condition. The shaded areas show 1 SEM of the individual fits (see Model Fitting in the Supplemental Material ).

According to this model, proactive interference should be equally affected by viewing time, intertrial-interval time, response time, and reinforcement (reward or punishment) time. One implication of this model is that increased processing of the current sample should not, in itself, combat proactive interference (i.e., facilitate discrimination of old from new) any more than should an equivalent amount of time added to the intertrial interval. Another implication is that time-outs following incorrect responses (popular in the training of animal subjects) should hasten learning by reducing proactive interference, in addition to any effect of delaying the time to the next opportunity for reinforcement—a popular explanation in animal learning.

It is important to note that the data cannot be explained by alternative familiarity models, which assume that the subject simply reports whether the test stimulus was or was not seen before, including models based on decaying familiarity. According to such models, performance would depend only on the absolute time from the interfering stimulus, not the critical time ratio shown here.

Explaining memory on the basis of time ratios has a substantial history in human-memory research for effects occurring within individual trials, including stimulus-distinctiveness effects (e.g., Cowan, 2001 , 2005 ; Murdock, 1960 ; Nairne, Neath, Serra, & Byun, 1997 ), primacy effects (e.g., Bjork, 2001 ; Nairne et al., 1997 ; Neath, 1993 ), and recency effects (e.g., Glenberg, Bradley, Kraus, & Renzaglia, 1983 ; Howard & Kahana, 2002 ). Our results show that time ratios are crucial well beyond the current trial and account for effects on memory resulting from events that occurred as many as 16 trials prior.

Some human-memory researchers have used a time-distance metaphor of telephone poles appearing closer together as they recede into the distance to explain these effects (e.g., Nairne, 2002 ). Although this time-distance metaphor has previously been applied to events within single trials, it can also be applied to the proactive-interference effects observed in our study, which spanned several trials. The first (nearest) telephone pole would be the test stimulus on the test trial, and the second pole would be the sample stimulus on that test trial. Consequently, the gap between these first two poles would be 10 times greater for the 10-s delay condition than for the 1-s delay condition. This greater gap (i.e., the 10-s delay) would make the second pole (the sample on the test trial) relatively closer to the other poles receding into the distance, thereby making the current-trial sample more confusable with past samples and more vulnerable to proactive interference.

Although our experiment and model are based on tests of pigeon memory, implications of these findings may extend well beyond pigeons and familiarity. We argue that pigeons are not limited to indiscriminate familiarity because proactive interference dissipates after several (e.g., 16) trials and its dissipation did not result from forgetting, as shown by the robust proactive interference at these same trial numbers at the longer (10-s) delay.

The proactive-interference functions observed in our experiment have implications for the vast majority of memory studies using small stimulus sets, because proactive interference rapidly builds and saturates (e.g., Keppel & Underwood, 1962 ). Studies of pigeon and monkey memory using only two colored stimuli (which repeat in different combinations as samples and distractors over many trials and sessions) have shown nearly complete forgetting in as short a time as 30 s (e.g., Overman & Doty, 1980 ; Roberts & Grant, 1976 ; see Wright, 2007 , for review). Additional evidence from Overman and Doty’s (1980) study, however, showed that this apparent rapid forgetting was actually due to interference, not forgetting. In two follow-up studies, these authors showed that tests with larger stimulus sets (100 or more pictures) reduced repetition of stimuli across trials, which in turn reduced interference and dramatically improved memory performance (85% accuracy at 180-s delays and even ≥ 70% accuracy at a 24-hr delay). Likewise, animal list-memory studies with small stimulus sets (6 pictures) showed relatively mediocre (70%) 3-item memory performance ( Devine & Jones, 1975 ; Sands & Wright, 1980 ), but increasing the size of the stimulus sets (to 111 pictures) reduced stimulus repetition and proactive interference and dramatically improved memory performance (from 70% accuracy to 93% accuracy; Sands & Wright, 1980 ). These comparisons show that repeating stimuli from small stimulus sets has a powerful and detrimental effect on animal memory performance.

Studies of human memory, including popular change-detection studies conducted to evaluate human memory capacity (e.g., 4 ± 1 items), also typically use small stimulus sets—for example, six colored squares, letters, polygons, or shaded cubes (e.g., Alvarez & Cavanagh, 2004 ; Eng, Chen, & Jiang, 2005 ). However, proactive interference is only rarely evaluated in such studies (but see Hartshorne, 2008 ; Makovski & Jiang, 2008 ). Although the typical use of short retention delays (0.5–1.0 s) in these change-detection studies would tend to minimize interference, the short stimulus-presentation times and intertrial intervals (e.g., 0.5 s) would tend to enhance interference. Perhaps systematically manipulating these time variables and testing proactive interference in change-detection studies might reveal that proactive interference can affect visual short-term memory capacity. Any effects of long-term memory on capacity, including proactive interference, would pose challenges for fixed-capacity theories of visual short-term memory (cf. Brady, Konkle, & Alvarez, 2011 ; Cowan, Johnson, & Saults, 2005 ; Hintzman, 2011 ).

Supplementary Material

Acknowledgments.

The authors would like to thank Jacquelyne J. Rivera, Thomas A. Daniel, Adam M. Goodman, and John F. Magnotti for their assistance with data collection and Anne B. Sereno, Saumil Patel, and L. Caitlin Elmore for their comments and suggestions on an earlier draft of this manuscript.

This research and the preparation of this article were supported by National Institutes of Health Grants R01MH072616 and R01MH091038 (to A. A. W.) and R01EY020958 (to W. J. M.).

Declaration of Conflicting Interests

The authors declared that they had no conflicts of interest with respect to their authorship or the publication of this article.

Supplemental Material

Additional supporting information may be found at http:/pss.sagepub.com/content/by/supplemental-data

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    Mar 22, 2021 · An everyday example of proactive interference is when you get a new mobile phone number, as your memory for your old number disrupts your attempts to remember your new number. Keppel and Underwood (1962) examined the effect of proactive interference on long-term memory, in an experiment that resembles Peterson and Peterson (1959).

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    Feb 12, 2024 · Laboratory experiments play a crucial role in investigating proactive interference by meticulously controlling variables in controlled settings to replicate memory scenarios. Field research, on the other hand, ventures into real-world environments, offering a more ecologically valid understanding of how interference impacts memory retention in ...

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