THE ROLE of WORKING MEMORY CAPACITY in FALSE MEMORY a Thesis Presented to the Faculty of the Department of Psychology California

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THE ROLE OF WORKING MEMORY CAPACITY

IN FALSE MEMORY

A Thesis

Presented to the faculty of the Department of Psychology

California State University, Sacramento

Submitted in partial satisfaction of the requirements for the degree of

MASTER OF ARTS

Psychology

Lilian Edith Cabrera

SUMMER 2016

Lilian Edith Cabrera

THE ROLE OF WORKING MEMORY CAPACITY

IN FALSE MEMORY

A Thesis

Lilian Edith Cabrera

Approved by:

______, Committee Chair Jianjian Qin, Ph.D.

______, Second Reader Lawrence S. Meyers, Ph.D.

______, Third Reader Jeffrey Calton, Ph.D.

______Date

iii

Student: Lilian Edith Cabrera

I certify that this student has met the requirements for format contained in the University format manual, and that this thesis is suitable for shelving in the Library and credit is to be awarded for the thesis.

______, Graduate Coordinator ______Lisa M. Bohon, Ph.D. Date

Department of Psychology

Abstract

THE ROLE OF WORKING MEMORY CAPACITY

IN FALSE MEMORY

Lilian Edith Cabrera

The present study examined the effect of working memory capacity in false memory elicited by the DRM paradigm in two experiments (Experiment 1: N = 31, 80.6% female, age M = 21.29 years, SD = 4.26; Experiment 2: N = 29, 72.4% female, age M = 20.28 years, SD = 3.02). A concurrent digit load task was introduced to reduce available working memory capacity for the DRM task. The results of Experiment 1 revealed that false recall of critical lures was marginally higher when participants had a concurrent digit load task. While the initial increase in the digit load increased false recognition of critical lures, a further increase in the digit load reduced false recognition. In Experiment

2, participants were forewarned about the tendency of associative lists to elicit false memory of critical lures. Results from Experiment 2 demonstrated that while the concurrent digit load task did not affect false memory, warning instructions significantly reduced false recognition of critical lures.

______, Committee Chair Jianjian Qin, Ph.D.

______Date

ACKNOWLEDGEMENTS

First, I would like to express my sincerest gratitude to my graduate advisor, Dr.

Jianjian Qin, for the immeasurable amount of support, guidance, and immense knowledge that he provided throughout the completion of my thesis. His guidance throughout my thesis research and graduate education has been pivotal to my growth as a student. I would also like to thank my committee members, Dr. Lawrence Meyers and Dr. Jeff

Calton for their support in completing my thesis.

Finally, I would like to thank my mother, father, and sisters, for their unconditional love, support, and encouragement. They have been a great source of motivation to continue my academic journey. I would also like to acknowledge my best friend and partner in life, Joshua Haro, who has been an invaluable source of support and encouragement during this significant chapter in my life.

TABLE OF CONTENTS

Page

Acknowledgements ...... vi

List of Tables ...... ix

List of Figures ...... xi

Chapter

1. INTRODUCTION ...... 1

False Memory Research ...... 3

Proposed Mechanisms for False Memory ...... 12

The Role of Working Memory Capacity in False Memory ...... 18

The Present Study ...... 23

Hypotheses ...... 25

2. EXPERIMENT ONE ...... 27

Method ...... 27

Materials ...... 28

Procedure ...... 30

Results ...... 32

Discussion ...... 45

3. EXPERIMENT TWO ...... 48

Method ...... 48

Results ...... 49

Discussion ...... 62 vii

4. GENERAL DISCUSSION ...... 65

Appendix A. DRM Word Lists ...... 73

Appendix B. Participant Information Questionnaire ...... 76

Appendix C. Inventory of Memory Experience ...... 77

Appendix D. Warning Instructions ...... 83

References ...... 84

viii

LIST OF TABLES

Tables Page

1. The Effect of Concurrent Digit Load on Recall Performance ...... 36

2. The Effect of Concurrent Digit Load on Recognition Memory ...... 36

3. The Effects of Concurrent Digit Load and WMC on False Alarm Rate for

Critical Lures ...... 38

4. The Effect of Concurrent Digit Load on Sensitivity and Response Bias ...... 40

5. The Effects of Concurrent Digit Load and Word Type on Response Time (ms) . 42

6. Correlations between Memory Performance and Measures of Individual

Differences ...... 43

7. Correlations between SDT Indices and Measures of Individual Differences ...... 45

8. The Effect of Concurrent Digit Load on Recall Performance ...... 51

9. The Effects of Concurrent Digit Load, Warning Instructions, and WMC on

False Recall of Critical Lures ...... 53

10. The Effect of Concurrent Digit Load on Recognition Memory ...... 54

11. The Effects of Concurrent Digit Load, Warning Instructions, and WMC on

False Alarm Rate for Critical Lures ...... 56

12. The Effect of Concurrent Digit Load on Sensitivity and Response Bias ...... 58

13. The Effects of Concurrent Digit Load and Word Type on Response Time (ms) . 59

14. Correlations between Memory Performance and Measures of Individual

Differences ...... 60

15. Correlations between SDT Indices and Measures of Individual Differences ...... 62

LIST OF FIGURES

Figure Page

1. Flow chart of the study procedure...... 31

xi 1

Chapter 1

INTRODUCTION

Memory plays a crucial role in numerous aspects of everyday life. Our memory provides us with the ability to remember a range of information from day-to-day tasks to life events, allowing us to create a history of events that occur throughout our lifetime.

Although we can often trust the accuracy of our memory, memory can also be flawed. Two general ways that memory can fail include failing to remember something

(omission memory error), or remembering incorrectly (commission memory error)

(Roediger & McDermott, 2000; Schacter, 2001).

In the past few decades, a substantial amount of research has emerged examining false memory, a memory of an event that never occurred but that an individual mistakenly identifies as an event that happened (Lampinen, Neuschatz, & Payne, 1997).

To understand the occurrence of false memory, researchers have devised several procedures to elicit false memory. The most commonly employed procedure is the

Deese-Roediger-McDermott paradigm (DRM; Roediger & McDermott, 1995). The DRM paradigm has been adopted in a variety of domains, including neuroimaging, development, aging, and individual differences to examine the mechanisms underlying false memory and factors that influence false memory susceptibility. For example, previous research has demonstrated that older adults are at risk of experiencing lower levels of veridical memory and higher levels of false memory (Schacter, Koutstaal, &

Norman, 1997).

Despite much of the research focusing on the fallible nature of memory and the significant progress in understanding the processes that contribute to the occurrence of false memory, there are still important questions about the possible links between false memory and other memory processes. One of which is the role of working memory in false memory.

The focus of the present study was to examine how working memory, a limited- capacity system that is responsible for temporary storage and manipulation of information (Baddeley, 1992), plays a role in the creation of false memory. Previous studies have examined working memory capacity (WMC) as an individual difference factor that relates to false memory susceptibility (e.g., Peters, Jelicic, Verbeek, &

Merckelbach, 2007; Watson, Bunting, Poole, & Conway 2005). These studies have generally demonstrated that individuals with greater WMC tend to exhibit lower levels of false memory. Presumably, individuals with greater WMC have better source monitoring ability and consequently experience less false memory elicited in the DRM paradigm.

Although previous studies have focused on WMC as an individual difference factor, previous studies have yet to examine how directly manipulating WMC affects the creation of false memory in the DRM paradigm. For example, it may be possible to introduce a concurrent task that uses part of individual’s WMC, and therefore reduce the available WMC for the DRM task. The concurrent task can vary by how much information individuals have to store while simultaneously remembering DRM word lists. Examining how limiting individual’s WMC in the DRM paradigm influences false memory has implications for analogous situations in which an individual is distracted by

3 other tasks. Perhaps, as distractions increase, individuals may be more susceptible to false memory.

To lay the foundation for the present study, I will first provide a general overview of the research on false memory, followed by a discussion of the mechanisms that have been proposed as explanations for why false memory occurs. Next, I will discuss how working memory capacity has been linked to false memory, with source monitoring ability as a potential explanation, followed by what previous research on working memory capacity and false memory has demonstrated and how this research led to the present study.

False Memory Research

The Repressed Memory Debate

During the 1980s and early 1990s, as the number of adults claiming that they recovered repressed memories of childhood sexual abuse while in therapy increased dramatically, concerns regarding the validity of such recovered memories also increased.

When an alleged abuser denied the abuse and instead claimed that the memory was false and was implanted by a therapist, psychologists, as well the public, including the courts, struggled to understand the allegedly recovered memories (Partlett & Nurcombe, 1998).

When long-ago sexual abuse is alleged in absence of corroborating evidence, memory becomes the crucial element to examine. However, experimental psychologists and clinicians became divided on the validity of recovered memories (Brenneis, 1997;

Loftus, 1993; Ornstein, Ceci, & Loftus, 1998). On the one side of the debate, it was thought that repression was a defense mechanism that helps the individual to cope with a

4 traumatic experience such as sexual abuse. Repression was thought to “push” the traumatic memory out of consciousness rendering the memory for the traumatic experience inaccessible. However, the traumatic event may manifest itself through symptoms such as anxiety and sleep disturbances, despite the memory being out of consciousness (Alpert, Brown, & Courtois, 1998). Thus, when individuals seek therapy for such symptoms, a therapist’s task is to recover the repressed memory in order to help the individual. Furthermore, some argued that memory for a traumatic event is not subject to forgetting or distortion as ordinary memories are. Therefore, any retrieval techniques incorporated in therapy would not be able to distort memory of a traumatic event. On the other side of the debate, many cognitive psychologists argued that memory, even of a traumatic experience, is malleable due to memory’s constructive nature.

Memory researchers argued that many of the factors known to increase memory distortion in laboratory-based research were incorporated in therapy as techniques to recover memories, such as guided visualization, age regression, and hypnosis. The techniques were argued to be highly suggestive, which impose a risk for memory distortion or the creation of false memory. As such, it was possible that some of the

“recovered” repressed memories resulted from highly suggestive memory recovery techniques.

An important issue to address in the debate was whether it was possible to implant an entire memory for an event that in reality never occurred. Consequently, the repressed memory debate led to a surge of research examining the creation of false memory.

Demonstration of False Memory and Paradigms

False memory for childhood events. Loftus and Pickrell (1995) first published an experimental demonstration of implanting an entire false memory for an event that never happened in what later became known as the “Lost in a Shopping Mall” study. In the study, participants were first provided with short descriptions of four events that supposedly happened in their childhood and were instructed to write about the events in a booklet. After the participants returned the booklet to the researchers, they were interviewed about the events on two separate occasions and were asked to recall the events in as much detail as possible. Unknown to the participants, three of the events were true, but one was a false event of being lost in a shopping mall or large department store at the age of 5. The false event was constructed for each participant based on information provided by the participants’ relatives to increase the plausibility and was verified by the participants’ relatives as an event that did not occur. While many of the participants indicated that they did not remember being lost in a shopping mall (false event), 6 of the 24 participants claimed they “remembered” the false event, either fully or partially. At the end of the last session, when participants were debriefed and asked to choose which event may have been the false event, 5 of the 24 participants incorrectly indicated that one of the true events was false. Furthermore, even when participants were debriefed and told that the lost in a shopping mall event did not actually occur, some participants struggled believing the event did not occur.

The “Lost in a Shopping Mall” study provided empirical evidence that it was possible for adults to falsely remember an entire childhood event that did not actually

6 occur. Additional studies by other researchers using similar paradigms have demonstrated similar results that under certain conditions, individuals can provide memory reports of events that did not happen in their childhood (e.g., Herndon, Myers, Mitchell, Kehn, &

Henry, 2014; Hyman, Husband, & Billings, 1995; Qin, Ogle, & Goodman, 2008).

False memory of semantically associated lures in word lists. Additional evidence of false memory has been demonstrated with word lists in the Deese-Roediger-

McDermott (DRM) paradigm, which was first introduced by Deese (1959) and subsequently developed by Roediger and McDermott (1995). In the DRM paradigm participants are presented with lists of semantically associated words (e.g., bed, rest, awake, tired, dream, wake, snooze, slumber, snore, nap), each of which is strongly associated with a non-presented critical lure (e.g., sleep). Following the presentation of such lists, participants complete tests of free recall and/or recognition memory. In a free recall test, participants are asked to remember as many words as they can from the list that was just presented. Accuracy in true recall and the rate at which individuals produce the critical lure (i.e., false recall) is then measured. In a recognition memory test, participants are presented with a list of words consisting of words that were presented in the lists (studied words), non-presented words that are unrelated to any words from the lists (non-studied words), and non-presented words that are related to the studied lists

(critical lures). For each word, participants make a judgment whether the word is old

(studied), or new (non-studied). Old and new judgment accuracy is then examined. The typical finding is that people often falsely recall and/or falsely recognize the critical lure

(e.g., sleep) as a word that was presented in the study list.

The DRM paradigm has had a large influence in understanding the basic processes underlying false memory (Gallo, 2010). In addition, research incorporating the

DRM paradigm has increased awareness of the fallible and constructive nature of memory. Due to the relatively simple yet reliable method of creating a false memory of critical lures, the DRM paradigm serves as a useful tool to study the occurrence of false memory in a controlled laboratory setting.

Imagination inflation. Researchers have also examined how imagining events as a way to promote reliving an experience can affect memory for childhood events. For example, Garry, Manning, Loftus, and Sherman (1996) first asked participants to indicate how confident they were that a number of childhood events happened. Then, researchers asked the participants to imagine some of the events. After imagining the occurrence of some events, the participants provided new confidence levels. Garry et al. (1996) found that imagining the events increased individuals’ subjective ratings of the likelihood that the event actually occurred (i.e., imagination inflation effect).

The imagination inflation effect had implications for the use memory-retrieval tools that repeatedly requested an individual to imagine the occurrence of an event, such as law enforcement personnel asking suspects to imagine committing a crime, or therapists encouraging a client to imagine an abusive childhood event as a way of recovering hidden memories. The imagination inflation effect suggested that the use of memory-retrieval tools that encourage imagining the occurrence of an event could promote increased confidence that an event occurred, even though the event did not

8 actually occur. As such, images created through visualization could lead to increased false recollection.

Factors that Contribute to False Memory

In addition to demonstrating that it is possible to create a false memory, the DRM paradigm has been used to examine situations and individual difference factors that influence the creation of false memory.

Situational factors. In two experiments, McDermott (1996) examined how test delay (no delay vs. 30-second delay vs. 2-day delay) and multiple study/test opportunities affected false recall of critical lures. While introducing a 30-second delay between study and test decreased the proportion of studied items correctly recalled compared to a test with no delay, there was no difference in false recall of critical lures between a test with no delay and a test with a 30-second delay. On the other hand, introducing a 2-day delay between study and test led to both a decrease in correct recall and an increase in false recall of the critical lures compared to a free recall test administered with no delay and a

30-second delay (Experiment 1).

In Experiment 2, McDermott (1996) examined whether multiple study/test trials would allow participants to reduce false recall of critical lures. Participants were presented with lists five times, with each presentation followed by a recall test.

Participants then returned one day later and were instructed to recall as many items as possible from the lists they had learned in the previous session. During the same day of list presentation, learning for studied items increased across trials, as demonstrated by an increase in correct recall. In addition, false recall of critical lures reduced across trials,

9 although was not eliminated. One day after studying the list items, correct recall of studied items decreased, whereas false recall of critical lures increased. In summary, the results of Experiment 2 demonstrated that repeated opportunities to study lists reduced, although did not eliminate, false recall of critical lures. In addition, while repeated study and test improved list learning, items were forgotten after a one-day delay accompanied with an increase in false recall of critical lures.

Previous research has also examined whether individuals are willing to attribute a source to their recall of a critical lure. For example, Payne, Elie, Blackwell, and

Neuschatz (1996) presented participants with a videotape of two speakers (male or female) reading the lists of words (Experiment 3). During the study phase, participants were presented with a series of lists and were instructed to remember the words and which person spoke each word. After presentation of the lists, participants were asked to recall the words and to identify which person had spoken the items they had recalled.

Participants could either identify the speaker or indicate that they could not recollect who spoke an item. Although the percentage of items attributed to a source (i.e., male or female speaker) was higher for studied items (94%) compared to critical lures (87%), participants were still willing to attribute a large percentage of the recalled critical lures to a specific speaker. Thus, demonstrating that even when study words are presented with a distinct source, individuals not only continue to falsely recall items but also are willing to make a source attribution for the non-presented critical lures.

Researchers have also examined how the format in which studied items are presented affects the rate of false recall and recognition. For example, Israel and Schacter

(1997) presented one group of participants with words auditorily and visually (word-only condition), while another group was presented with words auditorily and as black and white line drawings (picture + word condition). Comparing the rate of false recognition between the two groups demonstrated that individuals who were presented with words auditorily and as drawings (picture + word condition) had lower level of false recognition. Subsequent research has also demonstrated that false recall and recognition is greater when simply presenting words auditorily compared to visually (e.g., Gallo,

McDermott, Percer, & Roediger, 2001; Pierce, Gallo, Weiss, & Schacter, 2005). These studies therefore suggest that false memory is also a function of the mode in which information is presented.

In addition, researchers have examined whether explicitly warning participants about the DRM illusion, can reduce false recall and/or recognition of the critical lures

(Gallo, Roberts, & Seamon, 1997; McDermott & Roediger, 1998). For example, Gallo et al. (1997) provided participants with detailed information of the false recognition effect prior to the presentation of the study lists. Participants were specifically told that the study lists were designed to try to make them falsely recognize related but non-studied words. The results demonstrated that when participants received warning instructions, they had lower false alarm to critical lures compared to participants who did not receive warning instructions, although the DRM illusion was not entirely eliminated. Therefore, suggesting that the DRM illusion is robust and difficult to avoid.

Individual difference factors. Researchers have also examined whether there are individuals who are more susceptible to DRM false memory. For example, previous

11 studies examining age-related differences in false memory elicited by the DRM paradigm have, in general, demonstrated that healthy old adults have lower levels of veridical memory but equal or higher levels of false memory, compared to young adults (Watson,

McDermott, & Balota, 2004). In addition, when comparing children (5-, 7-, and 11-year olds) to young adults, older children and adults showed higher rates of false memory, than younger children (Brainerd, Reyna, & Forrest, 2002).

Researchers have also examined how several cognitive and personality measures contribute to false memory elicited by the DRM paradigm. For example, Winograd,

Peluso, and Glover (1998) found that individuals who reported greater frequency of dissociative experiences, greater vivid mental imagery abilities, and more everyday memory failures had elevated levels of false recall and false recognition of critical lures in the DRM paradigm.

Additional research has also examined how higher order cognitive processes influence false memory susceptibility in the DRM paradigm. For example, there is a growing amount of research examining how individual differences in WMC play a role in

DRM false memory (Bixter & Daniel, 2013; Peters et al., 2007; Watson et al., 2005).

Watson et al. (2005) found that when individuals were forewarned about the nature of the

DRM task prior to studying the lists, individuals with greater WMC recalled fewer critical lures than individuals with lower WMC.

In summary, there is ample research demonstrating variations in false memory susceptibility, whether stemming from situational factors or individual differences. The resulting variations in false memory have led researchers to examine the underlying

12 mechanisms that potentially account for such differences. To understand the underlying mechanisms that lead to false recall or recognition of critical lures in the DRM paradigm, a fundamental starting point is to consider why memory is susceptible to errors.

Proposed Mechanisms for False Memory

Constructive Nature of Memory

Memory of events and information is not duplicative or a perfect representation of the original event or information. Instead, memory is reconstructive, as Frederic Charles

Bartlett (1932) hypothesized, built from our attitudes, reactions, and experiences. Bartlett was one of the first psychological researchers to experimentally demonstrate the constructive nature of memory by illustrating how memory of a story is affected by previous knowledge. Bartlett presented British participants with a Native American legend, The War of the Ghosts, and asked the participants to reproduce the story shortly after reading the story, and then again over a period of days, weeks, months, or years.

Bartlett found that participants rarely recalled all of the events and often changed the story as they tried to remember. When there were elements in the story that participants had difficulty remembering, participants filled the gaps in a manner that aligned with their cultural expectations of what should have happened, resulting in memory errors.

Thus, Bartlett argued that memories are reconstructions of past events guided by existing schemas. Although memory is not completely unreliable, Bartlett demonstrated that memory guided by preexisting knowledge structures, or schemas, can lead to memory errors.

Distortions of Memory

The constructive nature of memory is a fundamental reason for the occurrence of memory errors, distortions, and illusions (Johnson, Hashtroudi, & Lindsay, 1993;

Roediger, 1996; Schacter, Norman, & Koutstaal, 1998). During the 1970s, empirical research emerged demonstrating how memory for words, faces, and details of witnessed events could be distorted by misleading post-event information, termed as the

“misinformation effect” (e.g., Loftus, 1975; Loftus, Miller, & Burns, 1978; Loftus &

Palmer, 1974). In a typical misinformation experiment, participants are shown an event

(e.g., video of an automobile accident) and are then exposed to deliberately misleading information about what they saw. Participants are then tested for their memory of the witnessed event. Researchers then examine to what extent participants incorporate the misleading suggestions into their eyewitness reports.

For example, Okado and Stark (2005) demonstrated distortion of memory for simulated events after exposure to misinformation. Participants first saw several complex events, for example, a man stealing a girl’s wallet. Next, some of the participants received misinformation about the event, such as information that the girl’s arm was hurt in the process (rather than her neck). Finally the participants were asked to remember what they saw in the original event. Okado and Stark (2005) found that when many individuals were asked to recall what happened in the event, many claimed that they saw the misinformation details in the original event.

In addition to examining the misinformation effect for laboratory-based events, previous research has also examined the misinformation effect for memory of real-world

14 traumatic events. For example, Nourkova, Bernstein, and Loftus (2004) examined whether memory for the scene of a tragic terrorist bombing could be altered to include memory of wounded animals that were not seen. During the first session, all participants were asked to recall and write about two events: the 1999 attacks on Moscow apartment buildings and the 2001 attacks on the World Trade Center in New York. During the second session, occurring approximately 6 months after the initial session, half of the participants were assigned questions about the World Trade Center bombings, while the second half were asked about the Moscow bombings. Prior to recall during the second session, the researchers suggested that participants had mentioned a wounded animal when recalling the event during the first session and asked participants to provide more information. Although none of the individuals who were asked about the World Trade

Center incorporated the suggested event, 5 out of the 40 participants recalling the

Moscow bombings accepted the suggestion that they had seen and previously recalled a wounded animal. While the number of individuals who accepted the suggestion was a minority, the results nonetheless demonstrate that it is possible with only a small suggestion to alter memories for traumatic events.

Theoretical Frameworks

Source monitoring. The occurrence of memory distortions or false memory has been attributed to errors in determining the source of information. The memory editing or decision processes that are used to determine the origin or source of the activated information, is described within the Source Monitoring Framework (SMF; Johnson et al.,

1993). According to the SMF, different qualitative characteristics, such as perceptual,

15 semantic, temporal, and spatial details, are stored in memory at the time that an event is experienced. The average qualitative characteristics of an event in question can be used as evidence that the event is from one source versus another. For example, if an event in question carries rich and vivid perceptual details, the event would more likely be judged as being experienced rather than just imagined compared to an event that lacks perceptual detail. Source attribution can be based on a mixture of heuristic and systematic processes.

Heuristic judgments tend to be automatic and depend on qualitative characteristics of the memory, such as the amount of perceptual detail. Whereas systematic judgments are more deliberate, where the available information is scrutinized, often making a slower decision. A systematic judgment compares the memories of the event in question to memories one already holds, and involves reasoning, such as determining whether a memory seems plausible. Source judgments are typically made heuristically, however, both processes can provide a check for one another.

Reality monitoring. The type of source monitoring that is more relevant to the present study and is typically discussed when distinguishing between memories that originate from an external source, judged as “perceived,” and memories that result from an internal source, and thus judged as “imagined,” is reality monitoring (Johnson & Raye,

1981). Under some circumstances, reality monitoring can be difficult. For example, according to Johnson and Raye (1981), memories from an external source tend to contain more sensory, perceptual and contextual information but less information about cognitive processes. When memories are processed (encoded or retrieved), they may be susceptible to internal interpretations and elaborations that could potentially incorporate more

16 information about cognitive processes. Thus, the externally generated memory may resemble an internally generated memory. Conversely, an internally generated memory can resemble an externally generated memory by engaging in prolonged visualization, which increases the amount of sensory and perceptual details. In either case, the memory would become difficult to distinguish as either a memory that originated from an external source (perceived) or a memory that resulted from an internal source (imagined). Thus, errors in memory may be the consequence of a failure to discriminate the origin of the memory.

There are several theoretical explanations that have been proposed to specifically explain how a false memory is created in the DRM paradigm, including the activation- monitoring framework and fuzzy-trace theory.

Activation-monitoring framework. According to the activation-monitoring framework, when individuals are presented with a list of associated words there is an automatic spreading activation of non-presented words within the associative network

(Underwood, 1965). Thus, the non-presented, but strongly associated, critical lure becomes mentally activated (e.g., Roediger, Balota, & Watson, 2001). Once the critical lure has been activated, participants later falsely recall or recognize the critical lure because of a failure to correctly monitor the source of the item’s activation, an explanation consistent with the source monitoring framework.

Fuzzy-trace theory. The fuzzy-trace theory proposes that individuals form two types of mental representations about an event (Brainerd & Reyna, 1998). The first is a verbatim trace that contains contextual item-specific information of the event. The second

17 is a gist trace, which is a fuzzy representation of the event containing only general semantic information.

In the DRM paradigm, verbatim representations may be thought of as representations of specific details associated with the words presented in a list. On the other hand, a gist representation may correspond only to the general semantic content of the list items. When individuals are attempting to remember the words presented in a list, individuals may have difficulty consulting verbatim traces and instead rely on the general semantic content (i.e., gist trace). When individuals consult gist traces, false recall and false recognition may arise due to the semantic overlap between the critical lure and the gist representation of the DRM list (e.g., Payne et al., 1996).

Whether the critical lure is activated due to an automatic spreading activation or due to reliance on gist representations, in order for individuals to avoid falsely recalling or recognizing the critical lure as a studied word, individuals should be able to determine the origin of the information (e.g., Balota et al., 1999). In other words, individuals should be able to accurately determine the source of the word.

Individual Differences in False Memory Explained by Source Monitoring Ability

As previously discussed, individuals are likely to vary in false memory susceptibility. Given the central role source monitoring plays in avoiding false memory, previous studies demonstrating individual differences in false memory formation have suggested that the difference reflects variability in source monitoring ability (Peters et al.,

2007; Unsworth & Brewer, 2010; Watson et al., 2004). Thus, examining individual difference factors that affect source monitoring ability should also elucidate individual

18 differences in false memory formation. One factor that has been recently linked to source monitoring ability, and consequently false memory, is working memory capacity (Watson et al., 2005).

The Role of Working Memory Capacity in False Memory

Working Memory Capacity

Working memory refers to a limited-capacity system that is responsible for temporary storage and manipulation of information that is needed for complex cognitive tasks such as language comprehension, learning, and reasoning (Baddeley, 1992). The most recent working memory model to account for how we temporary store and manipulate information is thought to be a 4-component system (Baddeley, 2000). The phonological loop is specialized for holding verbal information for short periods of time; the visuospatial sketchpad is specialized for holding visual and spatial information; the central executive is responsible for the overall control of the working memory system by focusing, dividing, and switching attention to ensure that working memory resources are directed and used appropriately to accomplish task goals; and the episodic buffer is responsible for binding and integrating information from different sources within the working memory system to form a coherent memory episode.

Relationship Between WMC and Other Cognitive Functions

Given the nature of the central executive, working memory is involved in numerous cognitive tasks. Working memory capacity has been associated with fluid and crystallized intelligence (e.g., Engle, Tuholski, Laughlin, & Conway, 1999), language and reading comprehension, reasoning and problem solving (e.g., Engle, 2001). The

19 relationship between WMC and other cognitive tasks has been attributed to the overlap in the ability to simultaneously control attention to maintain information in an active, quickly retrievable state while suppressing other information to avoid distraction (Engle,

2002). Therefore, the key premise is that WMC is related to attentional control, in other words, maintaining cognitive representations, such as action plans, goal states, or other task-relevant stimuli in an active state in the presence of interfering information (Kane &

Engle, 2002).

In maintaining an attentional control perspective of WMC, individual differences in young adults’ WMC may influence behavioral performance in a cognitively challenging task that requires individuals to simultaneously store and process information in the midst of potentially interfering information (Unsworth, Redick, Heitz, Broadway,

& Engle, 2009). Therefore, one may expect WMC to affect the ability to perform in cognitively challenging tasks, such as source monitoring in the DRM paradigm.

Relationship Between WMC and False Memory

There is growing evidence that individual differences in WMC relate to false memory. An early examination of the role of WMC in false memory using the DRM paradigm was conducted by exploring whether individual differences in the WMC of young adults (high vs. low span) was related to false recall of the non-presented critical lures with warning instructions (present vs. absent) administered at encoding (Watson et al., 2005). In the warning condition, researchers forewarned participants that the associative lists were designed to elicit false memories for particular words that were never presented and encouraged participants to avoid recalling the non-presented critical

20 lure. In the no warning condition, participants were not given any warning but otherwise followed the same procedure. After participants were presented with a list, they completed a free recall memory test in which they were instructed to recall as many words as they could from the list that was just presented. Watson et al. (2005) found that in the no warning condition, low- and high-WMC individuals did not differ in false recall of the non-presented critical lures. However, in the warning condition, individuals with greater WMC recalled fewer non-presented critical lures than individuals with lower

WMC. Thus, Watson et al. (2005) provided evidence that individual differences in WMC are related to false memory susceptibility in the DRM paradigm.

Although Watson et al. (2005) only demonstrated a difference in false recall of the critical lure between low- and high-WMC individuals in the warning condition, subsequent research has examined the relationship between WMC and false memory without warning instructions. For example, in two studies, Peters et al. (2007) examined false recall and recognition of the critical lures in the DRM paradigm using additional measures of WMC. In the first study, WMC was measured through two simple span working memory tasks (i.e. forward and backward digit span). Although forward digit span scores were not significantly correlated with false recall or recognition, individuals with lower backward digit span scores (i.e., poor simple span working memory) had a higher level of false recall of critical lures and a greater proportion recognition of critical lures. In a second experiment, Peters et al. (2007) added a commonly used working memory capacity task (operation span; Turner & Engle, 1989) as a third measure of

WMC and only incorporated a recognition memory test. The findings of the second study

21 mirrored the first study in that only suboptimal backward digit span performance was related to elevated levels of false recognition of the critical lures.

Although the findings by Peters et al. (2007) did not replicate the link between

WMC measured by the operation span (OSPAN) task and false recall of the critical lure as Watson et al. (2005) found, the discrepancy could be in part related to methodological differences. For example, Peters et al. (2007) did not implement warning instructions, which are suggested to encourage individuals to actively employ cognitive control over false memory elicited by the DRM paradigm. In addition, Peters et al. (2007) did not incorporate a recall test in the second experiment to measure memory performance similar to Watson et al. (2005). Despite methodological differences, both Watson et al.

(2005) and Peters et al. (2007) suggest that individuals with greater WMC may have a lower occurrence of false memory compared to individuals with lower WMC.

Previous research examining the relationship between individual differences in

WMC and false memory using the DRM paradigm has also examined recollection experiences using the remember/know paradigm (Bixter & Daniel, 2013). In the remember/know paradigm, when participants judge words as old during a recognition test, remember responses are given to an item if the retrieval of that item is accompanied by a more conscious recollection of contextual details that were associated with the item at the time of encoding (Gardiner, 1988; Tulving, 1985). On the other hand, a know response, is given to an item if the retrieval of the item is based on a feeling of familiarity, even though no specific information about its prior occurrence can be recalled. In two experiments, Bixter and Daniel (2013) investigated the relationship

22 between individual differences in WMC, and susceptibility to false recognition of non- presented critical lures in the DRM paradigm and their accompanying subjective experiences. The only difference between the two experiments was that participants in

Experiment 1 were forewarned of the nature of the DRM paradigm in eliciting false memories for strongly associated words. In Experiment 1, Bixter and Daniel (2013) found that individuals with greater WMC had lower false recognition rates of the non- presented critical lures. In addition, individuals with greater WMC had a lower proportion of remember responses for critical lures falsely identified as studied words, indicating lower illusory recollection of critical lures compared to individuals with lower

WMC. However, these findings were not present when the forewarning was excluded

(Experiment 2). Thus, similar to Watson et al. (2005), explicitly forewarning participants provides an advantage for individuals with greater WMC in reducing rates of false recall or recognition of the non-presented critical lures.

In summary, previous research suggests that individuals with greater WMC have lower rates of false memory in the DRM paradigm. One possible explanation is that individuals with greater WMC may be better able to engage in source monitoring by identifying the words that are strongly associated to the presented list (i.e., non-presented critical lure) during encoding and labeling such words as lures that should be rejected as studied words. During a recall or recognition test, individuals with greater WMC may be better able to suppress the tendency to endorse critical lures as studied words.

In the previously discussed studies, WMC was treated as an individual difference factor, whereby WMC was measured and correlated with measures of false memory such

23 as false recall or recognition. In such tasks, what is important may be functional WMC, which can be determined by both the individual’s WMC and the cognitive demand of the task involved. For example, if an individual needs to perform a concurrent digit load task

(e.g., holding several random digits in working memory), then the functional or available working memory resources that the individual has remaining for the other task (e.g.,

DRM task) can be reduced. Therefore, it may also be possible for researchers to experimentally manipulate the functional WMC of individuals by manipulating the cognitive demand of a concurrent task in the DRM paradigm.

Previous research has incorporated a digit load task to manipulate WMC and examine performance on a range of tasks including learning, reasoning, and comprehension. For example, comprehension of prose passages was examined with a concurrent task requiring participants to remember sequences of digits ranging from 0 to

6 (Baddeley & Hitch, 1974). The 6-digit load significantly impaired level of comprehension indicating that performance can be affected by a concurrent digit load task. Therefore, in the present study a concurrent digit load task was used to manipulate

WMC.

The Present Study

The purpose of the present study was to further examine the role of WMC in

DRM false memory. Although previous studies have demonstrated that individuals with greater WMC exhibit lower levels of false memory, an additional question is whether manipulating the cognitive demand of a concurrent task that reduces available WMC for the DRM task results in higher levels of false memory. To reduce available WMC, a

24 concurrent digit load task was introduced to the DRM paradigm. The present study addressed the following questions in two experiments: Does increasing the concurrent digit load result in lower true memory and higher false memory? Does increasing the concurrent digit load result in lower source memory accuracy?

In addition, although some studies have only found a relationship between WMC and false memory when a warning is implemented (e.g., Bixter & Daniel, 2013; Watson et al., 2005), other research has demonstrated individual differences in false memory susceptibility between individuals with low- versus high-WMC without warning instructions (e.g., Peters et al., 2007) yielding mixed findings. Therefore, an additional goal for the present study was to examine how warning instructions, which inform participants of the tendency for the lists of words to elicit false recall or recognition of associated words, may also affect DRM false memory. The question that was addressed in the second experiment of the present study was whether warning instructions would result in lower false recall and recognition of the critical lures (false memory).

As previously mentioned, Watson et al. (2005) found that individuals with higher

WMC exhibited lower recall of critical lures when they were forewarned of the DRM illusion. Watson et al. (2005) suggested that by forewarning participants of the DRM illusion, participants are encouraged to encode and store each item on the list, while simultaneously attempting to identify the critical lure and monitor the critical lure as a non-presented word (a form of source monitoring). Individuals with higher WMC may be better able to engage in this simultaneous task, which may subsequently help them reduce false recall and recognition of critical lures. However, when a concurrent digit load task

25 reduces available WMC for the DRM task, it is possible that the concurrent task will affect the ability to monitor critical lures as non-studied words. Therefore, an additional question addressed in the second experiment of the present study is whether increasing the concurrent digit load inhibits the ability to avoid recalling or recognizing the critical lure.

Hypotheses

Working Memory Capacity

To manipulate available WMC, the DRM procedure was implemented with a concurrent digit load task. A 0-digit sequence, a 3-digit sequence, or a 6-digit sequence, was presented before each list, which participants were instructed to remember until the end of each list. Presumably, as the digit load increases, individuals have less of their

WMC available for the DRM task. I hypothesized that in the 6-digit load condition, correct recall and hit rate (true memory) would be lower, while false recall and false recognition of critical lures (false memory) would be higher compared to the 0- and 3- digit load conditions. In addition, I hypothesized that true memory would be higher, while false memory would be lower in the 0-digit load condition compared to the 3- and

6-digit load conditions.

Source Memory Accuracy

In addition to true and false memory, source memory was examined by including an external source monitoring task. Words were presented on either the left or right side of the computer screen. Participants were instructed to remember the words and whether the words appeared on the left or right side of the computer screen. I hypothesized that

26 source memory accuracy would be lower in the 6-digit load condition compared to the 3- and 0-digit load conditions. In addition, I hypothesized that source memory accuracy would be higher in the 0-digit load condition compared to the 3- and 6-digit load conditions.

Warning Instructions

Warning instructions were implemented in Experiment 2 of the present study to examine how knowledge of the DRM illusion affects false recall and recognition of the critical lures. The instructions were modeled after McDermott and Roediger (1998) and

Watson et al. (2005). I hypothesized that forewarning participants of the DRM illusion would reduce false recall and recognition of critical lures (false memory). In addition, I hypothesized that while warning instructions would allow participants to suppress false recall and recognition of critical lures, this ability would be affected by the concurrent digit load task. Specifically, I hypothesized that false recall and recognition would continue to be higher in the 6-digit load condition compared to the 0- and 3-digit load conditions.

Chapter 2

EXPERIMENT ONE

The purpose of Experiment 1 was to examine the role of working memory capacity in false memory elicited in the DRM paradigm. A concurrent digit load task was introduced to use a part of working memory capacity, therefore reducing available working memory capacity for the DRM task. I aimed to explore whether increasing the concurrent digit load would result in lower true memory and higher false memory by examining participants’ recall and recognition memory for DRM word lists.

The present experiment used a one-way (concurrent digit load: 0-digit sequence vs. 3-digit sequence vs. 6-digit sequence) within-subjects design. The dependent variables included correct recall, false recall of critical lures, false recall of other intrusions, hit rate, false alarm rate for critical lures, false alarm rate for noncritical new words, source memory accuracy, confidence level of response, and response time. In addition, I also evaluated participants’ true and false recognition using signal detection theory indices for sensitivity and response bias.

Method

Participants

Thirty-one undergraduates (females n = 25, males n = 6) from a large public university in northern California participated in the study in exchange for research credit.

The age of the participants ranged from 18 to 37 years (M = 21.29, SD = 4.26). The ethnicity of the participants was: Asian American or Pacific Islander (n = 6; 19.4 %),

African American (n = 4; 12.9 %), Hispanic, Latino, or Spanish (n = 10; 32.3 %),

Caucasian (n = 8; 25.8 %), other (n = 2; 6.5 %), or declined to state (n = 1; 3.2%).

Materials

Word Lists

Twenty-four DRM word lists of 12 words each were obtained from Roediger and

McDermott (1995), and Roediger, Watson, McDermott, and Gallo (2001). The words and the associated critical lure for each list are presented in Appendix A. For counterbalancing purposes, the 24 lists were divided into four sets of six lists so that, across participants, each list appeared equally at each of the three concurrent digit load conditions during the study phase and as new items on the recognition test. At study, participants were presented with a total of 18 lists. During the recognition test, new words were obtained from the fourth set of six lists.

Participant Information Questionnaire

The Participant Information Questionnaire contained four demographic questions: age, gender, ethnicity, and primary language (Appendix B).

Inventory of Memory Experience Questionnaire

The Inventory of Memory Experience1 (IME; Herrmann & Neisser, 1978) included a series of questions about how well individuals remembered or forgot everyday occurrences (Appendix C). The IME included eight questions on the R scale (how well

______

1An exploratory principal components analysis conducted on the IME resulted in two components that were consistent with the two subscales.

29 individuals remembered various experiences in everyday life) (IME-R; Cronbach’s α =

.79) and 24 questions on the F scale (how often individuals forgot various experiences in everyday life) (IME-F; Cronbach’s α = .88). R scale items were rated using a 7-point

Likert scale (1 = not at all, 7 = perfectly) while F scale items were rated on a separate 7- point Likert scale (1 = always, 7 = never). Higher scores on the R scale represent better self-perceived memory while higher scores on the F scale represent poor self-perceived memory.

Measure of Working Memory Capacity

The GoCognitive Online Working Memory Capacity test (Werner, 2008) consisted of 20 trials. Each trial consisted of a digit sequence, which participants were instructed to remember in a serial manner, resulting from a series of simple math problems. The online test records participants’ performance and provides a final score, which was used as a measure of individual working memory capacity. Higher scores represent greater working memory capacity.

Recognition Test

The recognition test consisted of 96 items, including 54 studied words (those in serial positions 1, 8, and 10 of the studied lists) and 42 non-studied words (18 critical lures from the studied lists, 6 critical lures from the non-studied lists, and 18 words from the non-studied lists, also in positions 1, 8, and 10). The 96 items were arranged into a random order, with the restriction that no more than three items of the same type appear consecutively. Two different random orders were used for the tests across participants.

Procedure

Study and Recall Phase

Participants completed the task individually using a 13-inch Macintosh laptop, which was programmed using the PsyScope Software (Cohen, MacWhinney, Flatt, &

Provost, 1993). During the study and recall phase, participants completed 18 trials (see

Figure 1). At the beginning of each trial, a digit sequence (3-digit sequence, 6-digit sequence, or no digit sequence) appeared on the center of the computer screen, which participants were instructed to memorize for a later serial recall test. Next, a list of words appeared either on the left or right side of the computer screen one by one at a constant rate of 1.5 seconds per word. After the last item of the list was presented, participants immediately recalled the digit sequence in a serial manner, and completed a free recall test for the words on the list. The participants had up to 1.5 minutes to recall as many words as they could from the list that was just presented. Participants completed three practice trials in order to become comfortable with the task.

Retention Interval

After participants completed the last trial, they completed filler tasks consisting of the Participant Information Questionnaire, Inventory of Memory Experience, and the

GoCognitive Online Working Memory Capacity test. Participants took approximately 15 minutes to complete all filler tasks.

Old/New Recognition and Source Memory Tests

Once participants completed the filler tasks, they completed a recognition test.

During the recognition test, each word appeared on the center of the computer screen one

31 by one. For each word that appeared, participants judged whether the word appeared on the left or right side of the computer screen at study or whether it was a new word (non- studied word) by pressing the L, R, or N key. Therefore, the judgment was a combined old/new and source judgment. After pressing the L, R, or N key, a 5-point confidence rating scale (1= not at all confident, 5 = very confident) appeared on the computer screen.

Participants pressed the corresponding number key to indicate their confidence level for the combined judgment. Participants were instructed to respond quickly but to try to avoid making mistakes. Response times (RTs) for the combined old/new and source judgments were automatically recorded by the PsyScope Software. Participants completed a practice recognition test in order to become comfortable with the task.

• 1. Digit load (0-, 3-, or 6-digit sequence) Study/Recall • 2. DRM word list Phase • 3. Serial recall test for digit sequence • 4. Free recall test for word list • 1. Participant Information Questionnaire Retention Interval • 2. Inventory of Memory Experience • 3. GoCognitive Online Working Memory Capacity test • 1. Presentation of word (old or new) Recognition Test • 2. Left/Right or New Judgment • 3. Confidence level

Figure 1. Flow chart of the study procedure.

Results

Data Coding and Preliminary Analyses

Performance on concurrent digit load task. Performance on the digit load task was calculated as the number of digits correctly recalled and then averaged across lists for each digit load condition. A one-way (concurrent digit load: 3- vs. 6-digit sequence) within-subjects ANOVA with the number of digits correctly recalled as the dependent variable indicated that participants held more digits in working memory in the 6-digit load condition (M = 4.18, SD = 1.19) compared to the 3-digit load condition (M = 2.63,

SD = .43), F(1, 30) = 60.54, p < .001, η2 = .67. Thus, participants had to devote more of their working memory capacity in the 6-digit load condition compared to the 3-digit load condition.

Performance on free recall test. Free recall scores included correct recall of studied words, false recall of critical lures, and false recall of other intrusions. Recall scores were averaged across lists for each digit load condition.

Performance on recognition test. For the recognition test, the following variables were assessed: hit rate, false alarm rate for critical lures, false alarm rate for noncritical new words, sensitivity and response bias for true and false recognition, source accuracy, confidence level, response time for studied words, response time for critical lures, and response time for noncritical new words.

Old/new recognition. Hit rate was calculated for studied words (i.e., words that appeared in the study phase). A score of 1 was assigned when the participants correctly judged a studied word as old (by selecting left or right), while a score of 0 was assigned

33 when the participants incorrectly judged a studied word as new. False alarm rates were calculated separately for critical lures associated with studied lists and noncritical new words. The false alarm rate for noncritical new words included both words from the non- studied lists and their associated critical lure. A score of 1 was assigned when participants mistakenly judged a non-studied word as old (by selecting left or right), while a score of

0 was assigned when participants correctly judged a non-studied word as new.

Signal detection theory indices. Signal detection theory (SDT) indices, d’ and β, were also calculated as an estimate of sensitivity and response bias, respectively, for old/new recognition memory (MacMillan & Creelman, 1991). Values of d’ vary between

0.00 to 1.00, with higher values indicating greater sensitivity, and a value of 0.50 indicating chance performance. Values of β vary between -1.00 to +1.00, with higher values indicating a more conservative response criterion and negative values indicating a liberal response criterion. The d’ and β indices were calculated by using the standard procedures. Adjusted scores were calculated for hit rate and false alarm rate when scores equal 1, n-.5/n; and when scores equal 0, .5/n, with n being the number of old or new items in both equations (Snodgrass & Corwin, 1988). Three sets of d’ and β were computed. The first set compared hit rate for studied words (true memory) with the false alarm rate for critical lures (false memory) (item specific memory-related). The second set compared hit rate for studied words (true memory) with the false alarm rate for noncritical new words (memory error) (item specific memory-unrelated). The third set treated the false alarm rate for critical lures associated with studied lists as “hits” (false

34 memory) and compared them with the false alarm rate for noncritical new words

(memory error) (gist memory) (Schacter, Israel, & Racine, 1999).

Source recognition. Source memory accuracy was conditioned on hit rate, in that calculations for source memory accuracy were only computed for studied words correctly recognized as old. Source memory accuracy was then calculated as proportion correct. A score of 1 was assigned when the participants attributed a word to the correct source (left or right), while a score of 0 was assigned when the participants attributed a word to the incorrect source.

Confidence. Confidence level for studied words was examined for the combined old/new and source judgment. Confidence level ratings were averaged across words for each digit load condition.

Response time. The average response time for the combined old/new and source judgment was examined for studied words, critical lures, and noncritical new words.

Response times were averaged across words for each digit load condition.

Main Analyses

For each dependent variable, a one-way (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) within-subjects ANOVA was conducted. Unless otherwise stated, any pairwise comparisons were examined with a Bonferroni adjustment.

Free Recall Performance

35 comparisons indicated that correct recall was higher in the 0-digit load condition compared to the 3-digit load condition, p = .002, and 6-digit load condition, p < .001 (see

Table 1). In addition, correct recall was higher in the 3-digit load condition compared to the 6-digit load condition, p < .001. Thus, the results suggest that as individuals had more digits to hold in working memory, the number of words correctly recalled from the list

(true memory) decreased.

False recall of critical lures. A one-way (concurrent digit load: 0- vs. 3- vs. 6- digit sequence) within-subjects ANOVA with false recall of critical lures as the dependent variable revealed no significant effect of concurrent digit load, F(2, 60) = 2.27, p = .11. However, when false recall in the 3- and 6-digit load conditions was combined and compared to the 0-digit load condition, the effect of concurrent digit load approached significance, F(1, 30) = 4.01, p = .054, η2 = .12. False recall of critical lures was marginally higher in the combined 3- and 6-digit load conditions (M = .30, SD = .20) compared to the 0-digit load condition. Thus, the results suggest that false memory of critical lures was higher when working memory was devoted to other tasks.

False recall of other intrusions. A one-way (concurrent digit load: 0- vs. 3- vs.

6-digit sequence) within-subjects ANOVA with false recall of other intrusions as the dependent variable revealed no significant effect of concurrent digit load, F(2, 60) = .78, p = .46.

Table 1

The Effect of Concurrent Digit Load on Recall Performance

Digit Load 0-digit sequence 3-digit sequence 6-digit sequence Correct Recall 6.05 (1.18) 5.51 (.93) 4.69 (1.29) False Recall Critical Lures .23 (.22) .31 (.22) .30 (.23) Other Intrusions .20 (.19) .16 (.25) .22 (.23) Note. Standard deviations are in parentheses.

Old/New Recognition Memory

Hit rate. A one-way (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) within- subjects ANOVA with hit rate for studied words as the dependent variable revealed no significant effect of concurrent digit load, F(2, 60) = .63, p = .53 (see Table 2).

Table 2

The Effect of Concurrent Digit Load on Recognition Memory

Digit Load 0-digit sequence 3-digit sequence 6-digit sequence Hit Rate .79 (.11) .80 (.10) .77 (.12) False Alarm Rate Critical Lures .74 (.22) .87 (.12) .78 (.22) Noncritical new words .26 (.22) .24 (.19) .25 (.20) Source Accuracy .64 (.14) .60 (.16) .60 (.15) Note. Standard deviations are in parentheses.

False alarm rates. A one-way (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) within-subjects ANOVA with false alarm rate for critical lures as the dependent variable revealed a significant effect of concurrent digit load, F(2, 60) = 6.70, p = .002, η2 = .18. Pairwise comparisons revealed that the false alarm rate for critical lures was higher in the 3-digit load condition compared to the false alarm rate in the 0-

37 digit load condition, p = .003, and 6-digit load condition, p = .04. No significant difference in false alarm rate emerged between the 0- and 6-digit load conditions, p = .74.

The results suggest that false memory was higher in the 3-digit load condition compared to the 0- and 6-digit load conditions but no significant difference in false memory emerged between the 0-and 6-digit load conditions (i.e., inverted U-shaped pattern).

To explore whether there were individual differences in the false alarm rate for critical lures based on WMC, the WMC scores were divided into 33rd and 66th percentiles in order to create a low, moderate, and high WMC group. A 3 (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) x 3 (WMC group: low vs. moderate vs. high) mixed ANOVA, was conducted with concurrent digit load as a within-subjects factor, WMC group as a between-subjects factor, and false alarm rate for critical lures as the dependent variable.

A significant effect of concurrent digit load emerged, F(2, 56) = 6.73, p = .002, η2 = .18, reflecting the same findings as the previous analysis. The main effect of WMC group was not significant, F(2, 28) = 1.50, p = .24. No significant interaction between concurrent digit load and WMC group emerged, F(4, 56) = 1.11, p = .36 (see Table 3). The results suggest there were no individual differences in the false alarm rate for critical lures based on WMC.

Table 3

The Effects of Concurrent Digit Load and WMC on False Alarm Rate for Critical Lures

Digit Load 0-digit 3-digit 6-digit sequence sequence sequence Total M (SD) M (SD) M (SD) M (SD) WMC Low (n = 10) .73 (.21) .87 (.11) .85 (.17) .82 (.05) Moderate (n = 10) .77 (.25) .92 (.12) .85 (.17) .84 (.05) High (n = 11) .71 (.21) .83 (.13) .67 (.27) .74 (.05) Total .74 (.22) .87 (.12) .78 (.22)

A one-way (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) within-subjects

ANOVA with false alarm rate for noncritical new words as the dependent variable revealed no significant effect of concurrent digit load, F(2, 60) = .21, p = .81.

SDT Analysis for Old/New Recognition

Item specific memory-related. To assess participants’ sensitivity to true memory compared to false memory, a one-way (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) within-subjects ANOVA with d’ as the dependent variable was conducted. The results revealed a significant effect of concurrent digit load, F(2, 60) = 3.27, p = .045, η2

= .10. While pairwise comparisons using a Bonferonni adjustment revealed no significant differences, LSD indicated that sensitivity to true memory was higher for words in the 0- digit load condition compared to words in the 3-digit load condition, p = .02 (see Table

4). No other significant differences emerged, ps > .05.

A similar one-way ANOVA was conducted to assess participant’s response bias with β as the dependent variable. No significant effect emerged, F(2, 60) = 1.00, p = .37.

Item specific memory-unrelated. To assess participants’ sensitivity to true memory compared to memory errors, a one-way (concurrent digit load: 0- vs. 3- vs. 6- digit sequence) within-subjects ANOVA was conducted with d’ as the dependent variable. No significant effect emerged, F(2, 60) = .41, p = .67.

A similar one-way ANOVA was conducted to assess participant’s response bias with β as the dependent variable. No significant effect emerged, F(2, 60) = .23, p = .80.

Gist memory. To assess participants’ sensitivity to false memory compared to memory errors, a one-way (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) within- subjects ANOVA was conducted with d’ as the dependent variable. A significant effect emerged, F(2, 60) = 5.49, p = .006, η2 = .15. Pairwise comparisons revealed that participants had greater sensitivity for words in the 3-digit load condition compared to words in the 0-digit load condition, p = .003. No other differences emerged ps > .17.

A similar one-way ANOVA was conducted to assess participant’s response bias with β as the dependent variable. No significant effect emerged, F(2, 60) = 1.96, p = .16.

Table 4

The Effect of Concurrent Digit Load on Sensitivity and Response Bias

Digit Load 0-digit 3-digit 6-digit sequence sequence sequence Item Specific Memory-Related d' .19 (.70) -.19 (.42) -.02 (.67) β 1.10 (.61) 1.29 (.54) 1.28 (.59) Item Specific Memory-Unrelated d' 1.58 (.74) 1.65 (.56) 1.55 (.55) β 1.26 (.88) 1.21 (.79) 1.32 (.94) Gist Memory d' 1.38 (.82) 1.84 (.63) 1.56 (.73) β 1.28 (.89) 1.00 (.68) 1.14 (.80) Note. Standard deviations are in parentheses.

Source Memory

Memory for the source of words (left vs. right) was examined for studied words accurately judged as “old.” A one-way (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) within-subjects ANOVA with source memory accuracy as the dependent variable revealed no significant effect of concurrent digit load, F(2, 60) = 1.17, p = .32

(see Table 2).

Confidence Level of Combined Judgment

A one-way (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) within-subjects

ANOVA with confidence level of combined old/new and source judgment as the dependent variable revealed a significant effect of concurrent digit load, F(2, 60) = 6.02, p = .004, η2 = .17. Pairwise comparisons revealed that participants were less confident for words in the 6-digit load condition (M = 3.09, SD = .60) compared to both the 3-digit load condition (M = 3.26, SD = .64) p = .03, and 0-digit load condition (M = 3.25, SD =

.64) p = .008. No difference emerged between the 0- and 3-digit load conditions, p =

1.00. The results suggest that when participants held more digits in working memory, they were less confident of their responses.

Response Time

A 3 (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) x 3 (word type: studied vs. critical lure vs. noncritical new) within-subjects ANOVA was conducted with response time for combined old/new and source judgment as the dependent variable. The main effect of concurrent digit load was not significant, F(2, 60) = .31, p = .73. The main effect of word type was significant, F(2, 60) = 18.28, p < .001, η2 = .20. No significant interaction between concurrent digit load and word type emerged, F(4, 120) = .12, p =

.98.

To examine the main effect of word type, pairwise comparisons were conducted and revealed that response time was faster for noncritical new words compared to studied words, p < .001, and critical lures, p < .001 (see Table 5). No significant difference emerged between studied words and critical lures, p = .45. Thus, the results suggest that participants were quicker at making a judgment whether noncritical new words were old or new. In addition, participants’ response time did not differ between studied words and critical lures.

Table 5

The Effects of Concurrent Digit Load and Word Type on Response Time (ms)

Digit Load 0-digit sequence 3-digit sequence 6-digit sequence Total Studied Words 3227.75 3358.01 3294.08 3293.28 (912.25) (970.65) (1016.39) (921.74) Critical Lures 3488.49 3485.44 3488.73 3487.55 (1096.97) (1264.79) (1576.66) (1104.63) Noncritical new 2653.04 2754.39 2657.42 2688.28 words (908.52) (957.26) (974.81) (843.54) Note. Standard deviations are in parentheses.

Individual Differences

To examine individual differences, Pearson correlation coefficients were calculated between WMC (measured by the GoCognitive Online Working Memory test), the two IME subscales (IME-F and IME-R), and performance on the DRM memory task

(see Table 6). The results revealed that individuals with greater WMC had higher overall correct recall and overall lower false alarm rate for noncritical new words. In addition, those who had poor self-perceived memory (i.e., scored higher on the IME-F) had higher source memory accuracy. Lastly, those who had better self-perceived memory (i.e., scored higher on the IME-R) had higher overall correct recall, higher false recall of critical lures in the 3- and 6-digit load conditions, higher false recall of other intrusions, higher hit rate in the 6-digit load condition, and were more confident in their responses.

Table 6

Correlations between Memory Performance and Measures of Individual Differences

WMC IME-F IME-R Correct Recall .40* .06 .33† False Recall of Critical Lures 0-digit load -.05 -.16 .16 3-digit load -.10 -.21 .35† 6-digit load -.23 -.10 .39* False Recall of Other Intrusions -.10 -.15 .51** Hit Rate 0-digit load -.07 .01 -.08 3-digit load -.09 -.04 -.14 6-digit load .24 -.08 .34† False Alarm of Critical Lures 0-digit load -.05 -.02 -.02 3-digit load -.06 -.09 .22 6-digit load -.21 .01 .19 Overall FA for Noncritical New Words -.33† -.07 -.06 Source Accuracy .07 .31† .12 Confidence Level -.13 -.28 .30† M (SD) 4.74 (1.12) 5.03 (1.19) 4.09 (1.04) Note. * p < .05, ** p < .01, two-tailed. † p < .05, one-tailed.

To examine individual differences in sensitivity and response bias, Pearson correlation coefficients were calculated between WMC (measured by the GoCognitive

Online Working Memory test), the two IME subscales (IME-F and IME-R) and the three sets of SDT indices for each concurrent digit load condition (see Table 7). The results revealed that individuals with greater WMC had greater sensitivity in distinguishing between studied words (true memory) and critical lures (false memory) (i.e., item specific memory-related) in the 6-digit load condition, studied words and noncritical new words

(memory error) (i.e., item specific memory-unrelated) in the 0- and 6-digit load conditions, and critical lures from noncritical new words (i.e., gist memory) in the 0-digit

44 load condition. Furthermore, individuals with greater WMC had a more conservative response criterion when comparing studied words to noncritical new words (i.e., item specific memory-unrelated) in the 0- and 3-digit load conditions and a more conservative response criterion when comparing false alarm rate for critical lures to false alarm rate for noncritical new words (i.e., gist memory) in the 0- and 3-digit load conditions.

In addition, those who had better self-perceived memory (i.e., scored higher on the IME-R) had lower sensitivity in discriminating studied words from critical lures (i.e., item specific memory-related) in the 3-digit load condition and a more conservative response criterion for studied words compared to critical lures in the 3-digit load condition.

Table 7

Correlations between SDT Indices and Measures of Individual Differences

WMC IME-F IME-R Item Specific Memory-Related 0-digit load d’ .00 -.04 -.03 β .10 .14 .07 3-digit load d’ -.02 .03 -.40* β .07 .03 .34† 6-digit load d’ .32† -.08 .06 β -.06 .03 -.01 Item Specific Memory-Unrelated 0-digit load d’ .34† -.07 .17 β .37* -.13 .03 3-digit load d’ .22 .08 -.14 β .31† .02 .01 6-digit load d’ .32† .00 .18 β -.06 .05 -.16 Gist Memory 0-digit load d’ .31† -.04 .18 β .35† -.18 .02 3-digit load d’ .22 .06 .15 β .31† .04 -.13 6-digit load d’ -.05 .07 .09 β .06 .09 -.22 Note. * p < .05, two-tailed. † p < .05, one-tailed.

Discussion

The purpose of Experiment 1 was to examine how manipulating WMC through a concurrent digit load task affected true and false memory in the DRM paradigm. I

46 predicted that as the digit load increased, individuals would have lower true memory (i.e., lower correct recall and lower hit rate), and higher false memory (i.e., higher false recall of critical lures and higher false alarm rate for critical lures).

Results from Experiment 1 demonstrated that the concurrent digit load task affected both true and false memory in the DRM paradigm. Consistent with my prediction, as the concurrent digit load increased from 0 digits to 3 and 6 digits, correct recall (true memory) decreased. In addition, false recall of critical lures (false memory) was marginally higher when participants had to perform a concurrent task (remembering

3- and 6-digit sequences) than when they did not (the 0-digit load condition).

When examining performance on the old/new recognition test, although hit rate was not affected by the concurrent digit load task, false recognition of critical lures (false memory) was significantly higher in the 3-digit load condition compared to both the 0- digit and 6-digit load conditions. However, no significant difference emerged between the 0- and 6-digit load conditions (i.e., an inverted U shape), demonstrating a somewhat paradoxical result. Although the increase in false recognition of critical lures from the 0- digit to 3-digit load condition was consistent with my prediction, the non-significant difference in false recognition between the 0-digit and 6-digit load conditions was contrary to my prediction. One possible explanation is that as the concurrent digit load increased from 0 to 3 digits, participants’ ability to determine the source of words

(studied vs. non-studied) was impaired and thus led to an increased false alarm to critical lure. However, further increase of concurrent digit load from 3 to 6 digits may have

47 limited the spreading activation of associated words and thus reduced the false alarm to critical lures.

Previous research examining the relationship between individual differences in

WMC and false memory in the DRM paradigm has found that individuals with higher

WMC exhibit lower levels of false memory (Bixter & Daniel, 2013; Peters et al., 2007;

Watson et al., 2005). However, the results have varied depending on whether participants are forewarned of the DRM illusion. Therefore, in a second experiment I explored whether forewarning participants of the DRM illusion can influence false memory susceptibility when WMC is manipulated through a concurrent digit load task.

Chapter 3

EXPERIMENT TWO

The purpose of Experiment 2 was to examine how forewarning participants of the

DRM illusion affects false memory elicited by the DRM paradigm when participants complete a concurrent digit load task. I aimed to explore if participants’ ability to avoid recalling or recognizing the critical lure would be hindered as the concurrent digit load increased.

Method

Participants

Twenty-nine undergraduates (females n = 21, males n = 8) from a large public university in northern California participated in the study in exchange for research credit.

The age of the participants ranged from 18 to 30 years (M = 20.28, SD = 3.02). The ethnicity of the participants was: American Indian, Eskimo, or Aleut (n = 1; 3.4 %),

Asian American or Pacific Islander (n = 5; 17.2 %), African American (n = 5; 17.2 %),

Hispanic, Latino, or Spanish (n = 5; 17.2 %), Middle Eastern (n = 1; 3.4 %), Caucasian (n

= 7; 24.1 %), multi-ethnic (n = 4; 13.8 %), or other (n = 1; 3.4 %).

Materials and Procedure

The materials and procedure used in Experiment 2 were identical to that of

Experiment 1 with the exception of warning instructions (see Appendix D). The warning instructions were modeled after the instructions used by McDermott and Roediger (1998) and Watson et al. (2005). Prior to the presentation of the first DRM list, participants were explicitly warned that the forthcoming lists were comprised of related words. Participants were told that all of the words in each list are associated to one common word and that when individuals are tested for their memory of the words, individuals often make the mistake of recalling the common word as a word that was presented. Participants were encouraged to avoid recalling the common word. To make the instructions more concrete, participants were provided with a practice list and were given the identity of the associated critical lure.

Results

Data Coding

The same data coding method used in Experiment 1 was used in Experiment 2 to code and calculate correct recall, false recall of critical lures, false recall of other intrusions, hit rate, false alarm rate for critical lures, false alarm rate for noncritical new words, source memory accuracy, confidence level, and SDT indices for old/new recognition memory.

Preliminary Analysis

3- vs. 6-digit sequence) within-subjects ANOVA with the number of digits correctly recalled as the dependent variable indicated that participants held more digits in working memory in the 6-digit load condition (M = 3.68, SD = 1.34) compared to the 3-digit load condition (M = 2.22, SD = .59), F(1, 28) = 37.03, p < .001, η2 = .57. Thus, similar to

Experiment 1, participants devoted more of their working memory in the 6-digit load condition compared to the 3-digit load condition.

Main Analyses

Free Recall Performance

Correct recall. A one-way (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) within-subjects ANOVA with correct recall as the dependent variable revealed a significant effect of concurrent digit load, F(2, 56) = 17.34, p < .001, η2 = .38. Pairwise comparisons indicated that correct recall was higher in the 0-digit load condition compared to the 3-digit load condition, p = .004, and 6-digit load condition, p < .001 (see

Table 8). In addition, correct recall was higher in the 3-digit load condition compared to the 6-digit load condition, p = .04. Similar to Experiment 1, as individuals held more

51 digits in working memory, the number of words correctly recalled (true memory) decreased.

Table 8

The Effect of Concurrent Digit Load on Recall Performance

Digit Load 0-digit sequence 3-digit sequence 6-digit sequence Correct Recall 5.37 (1.18) 4.66 (1.29) 4.28 (1.46) False Recall Critical Lures .21 (.24) .26 (.20) .23 (.21) Other Intrusions .29 (.40) .38 (.33) .37 (.47) Note. Standard deviations are in parentheses.

False recall of critical lures across experiments. In order to directly compare false recall of critical lures for the two experiments, data was combined across both experiments. In addition, the effect of concurrent digit load and individual differences in

WMC were examined. WMC scores were divided through a mean split to create a low (n

= 31) and high-WMC group (n = 28). A 3 (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) x 2 (warning instructions: present vs. absent) x 2 (WMC: low vs. high) mixed

ANOVA, was conducted with concurrent digit load as a within-subjects factor, warning instructions and WMC as between-subjects factors, and false recall of critical lures as the dependent variable. A significant main effect of concurrent digit load emerged, F(2, 110)

= 4.12, p = .019, η2 = .07. The main effect of warning instructions was not significant,

F(1, 55) = .76, p = .39. The main effect of WMC was not significant, F(1, 55) = .05, p =

.83. No significant interactions emerged, Fs < 1.69, ps > .19.

To examine the main effect of concurrent digit load, pairwise comparisons were conducted. The results revealed that false recall of critical lures was higher in the 3-digit load condition (M = .29, SD = .21) compared to the 0-digit load condition (M = .22, SD

= .23), p = .018. No significant difference emerged between the 3-digit load condition and 6-digit load condition (M = .26, SD = .22), p = .89 or between the 0-digit load condition and 6-digit load condition, p = .25. Thus, the results suggest that false recall of critical lures (false memory) tended to be higher in the 3-digit load condition.

Although no interactions were significant, ps > .19, planned comparisons were conducted for the three-way interaction. The results revealed that for those who received warning instructions, individuals with high-WMC had higher false recall of critical lures in the 3-digit load condition compared to the 0-digit load condition, p = .015 (see Table

9). No other significant differences emerged, ps > .05.

Table 9

The Effects of Concurrent Digit Load, Warning Instructions, and WMC on False Recall of Critical Lures

Digit Load 0-digit sequence 3-digit sequence 6-digit sequence M (SD) M (SD) M (SD) No Warning Instructions Low-WMC (n = 15) .25 (.20) .32 (.24) .33 (.27) High-WMC (n = 16) .21 (.25) .29 (.20) .26 (.19) Total .23 (.22) .31 (.22) .30 (.23) Warning Instructions Low-WMC (n = 16) .24 (.27) .23 (.22) .20 (.23) High-WMC (n = 12) .15 (.19) .34 (.14) .26 (.19) Total .20 (.24) .27 (.20) .23 (.21)

False recall of other intrusions. A one-way (concurrent digit load: 0- vs. 3- vs.

6-digit sequence) within-subjects ANOVA with false recall of other intrusions as the dependent variable revealed no significant effect of concurrent digit load, F(2, 56) = 1.00, p = .38, similar to the finding in Experiment 1.

Old/New Recognition Memory

False alarm rates. A one-way (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) within-subjects ANOVA with false alarm rate for critical lures as the

54 dependent variable revealed no significant effect of concurrent digit load, F(2, 56) = 1.37, p = .26. Unlike in Experiment 1, in the present experiment there was no evidence of concurrent digit load having an effect on the false alarm rate for critical lures.

A one-way (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) within-subjects

ANOVA with false alarm rate for noncritical new words as the dependent variable revealed no significant effect of concurrent digit load, F(2, 56) = 2.66, p = .08, similar to

Experiment 1.

Table 10

The Effect of Concurrent Digit Load on Recognition Memory

Digit Load 0-digit sequence 3-digit sequence 6-digit sequence Hit Rate .76 (.17) .73 (.13) .70 (.14) False Alarm Rate Critical Lures .60 (.28) .69 (.19) .63 (.20) Noncritical new words .28 (.18) .29 (.19) .21 (.20) Source Accuracy .64 (.16) .59 (.12) .61 (.13) Note. Standard deviations are in parentheses.

False alarm rate across experiments. Similar to the comparison of false recall of critical lures, a 3 (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) x 2 (warning instructions: present vs. absent) x 2 (WMC: low vs. high) mixed ANOVA, was conducted with concurrent digit load as a within-subjects factor, warning instructions and WMC as between-subjects factors, and false alarm rate for critical lures as the dependent variable.

The main effect of concurrent digit load was significant, F(2, 110) = 6.19, p = .002, η2 =

.10. Pairwise comparisons revealed that the false alarm rate for critical lures was higher in the 3-digit load condition (M = .78, SD = .18) compared to the 0-digit load condition

(M = .66, SD = .25), p = .005, and 6-digit load condition (M = .71, SD = .22), p = .04. No significant difference emerged between the 0- and 6- digit load conditions, p = .70. The main effect of warning instructions was also significant, F(1, 55) = 21.93, p < .002, η2 =

.27. Results revealed that the false alarm rate for critical lures was higher when participants were not forewarned of the DRM illusion (M = .80, SD = .22), compared to when participants received warning instructions (M = .62, SD = .20). The main effect of

WMC group approached significance, F(1, 55) = 3.52, p = .066, η2 = .04. Individuals with high-WMC had lower false alarm rate for critical lures (M = .65, SD = .24) compared to individuals with low-WMC (M = .76, SD = .20). Thus, the results suggest that false memory was higher for the 3-digit load condition. In addition, when participants were forewarned of the DRM illusion, they were able to reduce false alarm to critical lures, compared to participants who were not forewarned. Lastly, individuals with high-WMC tended to have lower false memory compared to individuals with low-WMC.

Although no interactions were significant, ps > .28, planned comparisons were conducted for the three-way interaction. The results revealed that for those who did not receive warning instructions, individuals with high-WMC had higher false alarm rate for critical lures in the 3-digit load condition compared to the 6-digit load condition, p = .032

(see Table 11). No other significant differences emerged, ps > .05.

Table 11

The Effects of Concurrent Digit Load, Warning Instructions, and WMC on False Alarm

Rate for Critical Lures

Digit Load 0-digit sequence 3-digit sequence 6-digit sequence M (SD) M (SD) M (SD) No Warning Instructions Low-WMC (n = 15) .76 (.23) .87 (.11) .84 (.16) High-WMC (n = 16) .72 (.22) .88 (.13) .73 (.26) Total .74 (.22) .87 (.12) .78 (.22) Warning Instructions Low-WMC (n = 16) .63 (.28) .71 (.20) .68 (.21) High-WMC (n = 12) .53 (.25) .65 (.18) .56 (.18) Total .58 (.27) .68 (.19) .63 (.20)

SDT Analysis for Old/New Recognition

Item specific memory-related. To assess participants’ sensitivity to true memory compared to false memory, a one-way (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) within-subjects ANOVA with d’ as the dependent variable was conducted. The results revealed no significant effect of concurrent digit load, F(2, 56) = 2.46, p = .10 (see

Table 12).

A similar one-way ANOVA was conducted to assess participant’s response bias with β as the dependent variable. No significant effect emerged, F(2, 56) = .36, p = .70.

A similar one-way ANOVA was conducted to assess participant’s response bias with β as the dependent variable. A significant effect emerged, F(2, 56) = 5.86, p = .005

η2 = .17. Pairwise comparisons revealed that individuals had a more conservative response criterion for true memory compared to memory errors in the 6-digit load condition compared to the 0-digit load condition, p = .002. No other significant differences emerged, ps > .08.

A similar one-way ANOVA was conducted to assess participant’s response bias with β as the dependent variable. A significant effect emerged, F(2, 56) = 4.20, p = .02,

η2 = .13. Pairwise comparisons revealed that individuals had a more conservative response criterion for false memory compared to memory errors in the 6-digit load condition compared to the 3-digit load condition, p = .043. No other significant differences emerged, ps > .10.

Table 12

The Effect of Concurrent Digit Load on Sensitivity and Response Bias

Digit Load 0-digit sequence 3-digit sequence 6-digit sequence Item Specific Memory- Related d' .51 (.74) .15 (.70) .19 (.67) β .98 (.41) 1.08 (.60) 1.07 (.45) Item Specific Memory- Unrelated d' 1.44 (.72) 1.30 (.69) 1.44 (.68) β 1.13 (.86) 1.18 (.70) 1.67 (1.00) Gist Memory d' .93 (.70) 1.16 (.71) 1.25 (.96) β 1.26 (.94) 1.18 (.57) 1.67 (.99) Note. Standard deviations are in parentheses.

Source Memory

Memory for the source of words (left vs. right) was examined for studied words accurately judged as “old.” A one-way (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) within-subjects ANOVA with source memory accuracy for studied words accurately judged as “old” as the dependent variable revealed no significant effect of concurrent digit load, F(2, 56) = .76, p = .47, similar to Experiment 1 (see Table 10).

Confidence Level of Combined Judgment

A one-way (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) within-subjects

ANOVA with confidence level of combined old/new and source judgment as the dependent variable revealed no significant effect of concurrent digit load, F(2, 56) = .49, p = .61. Unlike in Experiment 1, in the present experiment there was no evidence of concurrent digit load having an effect on confidence level.

Response Time

A 3 (concurrent digit load: 0- vs. 3- vs. 6-digit sequence) x 3 (word type: studied vs. critical lure vs. noncritical new) within-subjects ANOVA was conducted with response time as the dependent variable. The main effect of concurrent digit load was not significant, F(2, 56) = 1.01, p = .37. The main effect of word type was significant, F(2,

56) = 7.67, p = .001, η2 = .20. No significant interaction emerged between concurrent digit load and word type, F(4, 112) = .66, p = .62.

To examine the main effect of word type, pairwise comparisons were conducted and revealed that response time was faster for noncritical new words compared to studied words, p = .007, and critical lures, p = .018 (see Table 13). No significant difference emerged between studied words and critical lures, p = .74. Thus, similar to Experiment 1, participants were faster in their old/new and source judgment for noncritical new words compared to studied words and critical lures.

Table 13

The Effects of Concurrent Digit Load and Word Type on Response Time (ms)

Digit Load 0-digit 3-digit 6-digit Total sequence sequence sequence Studied Words 3086.10 3090.43 3073.60 3083.38 (789.66) (867.57) (760.92) (742.72) Critical Lures 3377.27 3301.71 3044.97 3241.32 (1464.69) (968.07) (964.16) (971.20) Noncritical new words 2628.02 2645.68 2639.53 2637.74 (1253.60) (903.07) (1477.72) (1111.61) Note. Standard deviations are in parentheses.

Individual Differences

(see Table 14). The results revealed that individuals with greater WMC had higher false recall for critical lures in the 3-digit load condition. In addition, those who had poor self- perceived memory (i.e., scored higher on the IME-F) had higher overall correct recall, higher hit rate in the 0-digit load condition, and lower false recall of other intrusions.

Table 14

Correlations between Memory Performance and Measures of Individual Differences

WMC IME-F IME-R Correct Recall -.13 .41* .09 False Recall of Critical Lures 0-digit load -.18 -.15 -.13 3-digit load .42* -.01 -.14 6-digit load .16 -.11 -.17 False Recall of Other Intrusions -.16 -.37† -.29 Hit Rate 0-digit load .26 .43* -.03 3-digit load -.21 .22 .22 6-digit load .06 .28 -.02 False Alarm of Critical Lures 0-digit load -.04 -.02 .00 3-digit load .15 .04 .02 6-digit load -.31 -.11 .01 Overall FA for Noncritical new words .14 .06 .06 Source Accuracy -.21 .20 .22 Confidence Level -.31 -.03 .04 M (SD) 4.56 (1.11) 4.08 (.90) 4.58 (1.01) Note. * p < .05, two-tailed. † p < .05, one-tailed.

To examine individual differences in sensitivity and response bias, Pearson correlation coefficients were calculated between WMC (measured by the GoCognitive

Online Working Memory test), the two IME subscales2 (IME-F and IME-R) and the three sets of SDT indices for each concurrent digit load condition (see Table 15). The results revealed that individuals with lower WMC had greater sensitivity in distinguishing between critical lures associated with studied lists (false memory) and noncritical new words (memory errors) (gist memory) in the 6-digit load condition. In addition, those who had poor self-perceived memory (i.e., scored higher on the IME-F) had greater sensitivity distinguishing between studied words (true memory) and critical lures (item specific memory-related) in the 0-digit load condition; and between studied words and noncritical new words (item specific memory-unrelated) in the 0-digit load condition.

Furthermore, those who had better self-perceived memory (i.e., scored higher on the

IME-R) had lower conservative response criterion in discriminating studied words from noncritical new words (i.e., item specific memory-unrelated) in the 3-digit load condition.

______

2An exploratory PCA conducted on the IME resulted in two components that were consistent with the two subscales (IME-R, Cronbach’s α = .70; IME-F, Cronbach’s α = .90).

Table 15

Correlations between SDT Indices and Measures of Individual Differences

WMC IME-F IME-R Item Specific Memory-Related 0-digit load d’ .24 .35† -.02 β -.28 -.10 .06 3-digit load d’ -.25 .10 .14 β .12 -.26 -.16 6-digit load d’ .28 .25 -.01 β -.25 -.06 .05 Item Specific Memory-Unrelated 0-digit load d’ .22 .35† -.02 β -.06 -.25 .02 3-digit load d’ -.22 .02 .05 β .03 -.23 -.35† 6-digit load d’ -.22 .11 -.05 β -.16 -.10 .02 Gist Memory 0-digit load d’ -.02 -.02 -.01 β .12 -.12 -.10 3-digit load d’ .03 -.08 -.10 β -.10 -.17 -.23 6-digit load d’ -.36† -.10 -.03 β -.07 -.04 .00 Note. † p < .05, one-tailed.

Discussion

The purpose of Experiment 2 was to examine the effect of warning instructions and WMC on false memory in the DRM paradigm. Specifically, the effect of a

63 concurrent digit load task on performance in the DRM paradigm was examined when participants were forewarned of the DRM illusion. I hypothesized that as the concurrent digit load increased, true memory would decrease (i.e., lower correct recall and lower hit rate) while false memory would increase (i.e., higher false recall of critical lures and higher false alarm rate for critical lures) despite warning participants of the DRM illusion. Furthermore, I predicted that even though false recall and recognition would increase when the concurrent digit load increased, false recall and recognition of critical lures would overall be lower compared to when participants were not forewarned of the

DRM illusion (Experiment 1).

Results from Experiment 2 demonstrated that the concurrent digit load task only affected true memory in the DRM paradigm when participants were warned of the DRM illusion. As the concurrent digit load increased from a 0-digit sequence to a 3- and 6-digit sequence, correct recall (true memory) decreased. False recall of critical lures was not affected by the concurrent digit load task. When examining performance on the old/new recognition test, hit rate and false alarm rate was also not affected by the concurrent digit load task.

To examine the effect of warning instructions on false recall and recognition of critical lures directly, false recall and recognition rates were examined across Experiment

1 and 2. In addition, to examine how individual differences in WMC may influence false recall and recognition, individuals were categorized as either having low- or high-WMC.

The results suggested that warning participants of the DRM illusion did not reduce false recall of critical lures (false memory). In addition, there were no individual differences in

64 false recall of critical lures between individuals with low-WMC and individuals with high-WMC. For false recognition, the results demonstrated that false recognition of critical lures was significantly lower when participants were forewarned of the DRM illusion (Experiment 2) across all digit load conditions. In addition, the difference in false recognition of critical lures between low- and high-WMC approached significance with high-WMC individuals having lower false recognition of critical lures.

Chapter 4

GENERAL DISCUSSION

Previous research has examined the relationship between individual differences in

WMC and susceptibility to false memory elicited by the DRM paradigm. The results have generally demonstrated that individuals with greater WMC have lower levels of false memory (Bixter & Daniel, 2013; Peters et al., 2007; Watson et al., 2005). The relationship between greater WMC and lower false memory has been attributed to source monitoring ability, a process that is central to avoiding false memory. Although there is growing evidence that individual differences in WMC are related to false memory, whether introducing a task that uses a part of WMC has an effect on false memory in the

DRM paradigm has yet to be examined. Therefore in the present study, the effect of

WMC on false memory elicited by the DRM paradigm was examined by introducing a concurrent digit load task in two experiments; with the first experiment examining the effect of concurrent digit load on false memory and the second experiment examining the effect of concurrent digit load and warning instructions presented before encoding, on false memory.

The overarching research question in the two experiments was whether introducing a concurrent task that uses a part of WMC would hamper source monitoring, and in turn lead to higher levels of false memory. In the present study, the concurrent task was to retain either a 0-, 3- or 6-digit sequence in working memory throughout the

66 presentation of a DRM word list. Thus, as the digit load increased, participants would have less available WMC for the DRM task.

In Experiment 1, the effect of concurrent digit load on true and false memory was examined through a free recall and recognition memory test. I predicted that as the concurrent digit load increased, correct recall and hit rate (true memory) would decrease, while false recall and recognition of critical lures (false memory) would increase. The results from Experiment 1 were generally consistent with my prediction. When examining performance on the free recall test, correct recall of the list words gradually decreased as concurrent digit load increased. In addition, false recall of critical lures was marginally higher when participants had a concurrent digit load task (i.e., 3- and 6-digit load conditions) than when participants did not have a digit sequence to remember (i.e.,

0-digit load condition). These results suggest that when part of individual’s working memory is devoted to a concurrent task, participants have lower levels of true memory and higher levels of false memory.

When examining old/new recognition performance, although hit rate was not affected by the concurrent digit load task, the false alarm rate for critical lures was significantly higher in the 3-digit load condition compared to both the 0- and 6-digit load conditions. However, no significant difference emerged between the 0- and 6-digit load conditions (i.e., an inverted U-shape pattern), demonstrating an interesting and unexpected finding. One possible explanation is that as the concurrent digit load increased from 0 to 3 digits, participants had less WMC to engage in source monitoring.

With participants’ ability to determine the source of words (studied vs. non-studied)

67 being impaired, participants exhibited an increased false alarm to critical lures (Johnson et al., 1993). When considering the activation-monitoring framework, false memory in the DRM paradigm may be explained as the failure to monitor the source of activated words resulting from spreading activation (Johnson & Raye, 1981; Roediger, Balota, &

Watson, 2001). When the concurrent digit load further increased from 3 to 6 digits, it is possible that that by remembering fewer words (as evidenced by lower correct recall), there was a limited spreading activation of strongly associated words. Thus, the spreading activation from the list words to the concept of the critical lures could have been diminished, resulting in lower false alarm to critical lures in the 6-digit load condition compared to the 3-digit load condition.

This result can also be explained by the fuzzy-trace theory. According to the fuzzy-trace theory, individuals form verbatim and gist traces about an event (Brainerd &

Reyna, 1998). Verbatim traces represent item-specific information about the event while gist traces represent only general semantic information of the event. In the DRM paradigm, verbatim traces may be thought of as representations of specific features or details associated with the list of words, while gist traces represent the general semantic content of the list items. If false memory elicited in the DRM paradigm is due to reliance on gist traces, then the critical lure would be endorsed as a studied word due to the semantic overlap with the gist representation of the DRM list (Payne et al., 1996). The results from Experiment 1 revealed that the number of words correctly recalled decreased as the digit load increased. Therefore, a possible explanation is that when participants had more digits to remember (6-digit load condition), and correct recall was significantly

68 lower, participants may not have encoded the general semantic theme of the lists as well as in lower concurrent digit load conditions (3- and 0-digit load conditions). As a result, false recognition of critical lures was lower in the 6-digit load condition.

In addition to old/new recognition memory, source memory accuracy was examined as the ability to remember whether words appeared on the left or right side of the computer screen. Therefore, the type of source monitoring that was examined was a form of external source monitoring. I predicted that as the concurrent digit load increased, source memory accuracy in the recognition memory test would decrease.

However, there was no evidence of concurrent digit load having an effect on source memory. Although remembering whether words were presented on the left versus right side of the computer screen (external source monitoring) could be used as evidence that an item was “old,” memory of external source is not central to the kind of source monitoring that is important for avoiding false memory. Therefore, it is possible for the concurrent digit load task to have affected false memory without affecting external source monitoring performance.

Several interesting individual differences emerged in Experiment 1. Individuals with greater WMC had higher overall correct recall and lower false alarm rates for noncritical new words. In addition, individuals with poor self-perceived memory of everyday experiences (higher IME-F scores) showed higher source memory accuracy. While, individuals with better self-perceived memory (higher IME-R scores) showed higher correct recall and false recall, higher hit rate, and exhibited greater confidence in their responses.

Overall, the findings from Experiment 1 suggest that the working memory capacity available for the DRM affects the creation of false memory. These findings have implications for situations in which individuals may be distracted by other tasks.

The purpose of Experiment 2 was to further examine the effect of WMC on false memory in the DRM paradigm when participants are forewarned of the DRM illusion. A warning manipulation informs participants that the forthcoming lists are comprised of related words that converge upon one common word that individuals often mistaken as having been presented. Participants are then encouraged to avoid making the mistake.

Previous studies examining individual differences in WMC and false memory in the

DRM paradigm have suggested that when individuals are forewarned of the DRM illusion, individuals with greater WMC have significantly lower levels of false memory compared to individuals with lower WMC. One proposed explanation for these results is that with warning instructions, participants need to identify critical lures that may be activated during encoding (i.e., activation in the activation-monitoring framework).

Furthermore, individuals need to mark the activated critical lures as words to be rejected when recalling or recognizing studied words (i.e., monitoring in the activation- monitoring framework) (e.g., Neuschatz, Benoit, & Payne, 2003). This strategy may aid participants to correctly monitor the source of the critical lures as being internally generated, rather than externally presented (i.e., reality monitoring; Johnson & Raye,

1981). Therefore, Watson et al. (2005) suggest that forewarning participants changes the

DRM into a dual task that requires participants to simultaneously store items in memory from the words lists while attempting to identify the critical lure. Therefore, it is possible

70 that individuals with greater WMC are better able to divide their attention between the two competing tasks, and subsequently reduce false recall and recognition of critical lures.

Therefore, in Experiment 2, I predicted that although false memory would be lower when participants were forewarned of the DRM illusion, false recall and recognition would be higher when part of participants’ WMC was used for the concurrent digit load task. In other words, the ability to reduce false recall and recognition of the critical lures would be inhibited when available WMC for the DRM task decreased.

Results from Experiment 2 partially supported my prediction. First, my prediction that false recall and recognition would be higher as the concurrent digit load increased was unsupported. The results revealed that false recall and recognition was not affected by the concurrent digit load task, a finding that was different from the results in Experiment 1.

To examine how warning instructions and concurrent digit load affected false memory in the DRM paradigm, false recall and false alarm to critical lures was compared directly between the two experiments using factorial ANOVAs. In addition, participants were divided into low- and high-WMC by a mean split of WMC scores. When examining false recall of critical lures, the results demonstrated that warning instructions did not reduce false recall of critical lures. In addition, there was no significant difference in false recall of critical lures between participants with low-WMC and participants with high-

WMC. However, false recall of critical lures was higher in the 3-digit load condition compared to the 0-digit load condition.

When examining false alarm to critical lures, the results demonstrated that false alarm to critical lures was significantly lower when participants were forewarned of the

DRM illusion, consistent with previous findings that forewarning participants reduces, although does not eliminate, false memory in the DRM paradigm (e.g., McDermott &

Roediger, 1998). The effect of concurrent digit load on false alarm rate was also significant, demonstrating the U-shaped pattern in Experiment 1. Lastly, individuals with high-WMC tended to have lower false alarm rate for critical lures compared to individuals with low-WMC, although the effect only approached significance, p = .066.

This finding is consistent with previous studies that individuals with high-WMC exhibit lower levels of false memory (Bixter & Daniel, 2013; Peters et al., 2007; Watson et al.,

2005).

The results of Experiment 2 suggest that while the concurrent digit load task had no effect on false memory when the participants were forewarned of the DRM illusion, the warning lead to lower levels of false recognition across all concurrent digit load conditions. Therefore, knowledge of the DRM illusion may have encouraged the participants to employ strategies to correctly monitor the source of information in order to reduce memory errors.

The present study had several limitations. First, the manipulation of source by presenting words on the left or right was a difficult task for participants. Although I hypothesized that source memory accuracy would be affected by the concurrent digit load task, the results of Experiment 1 and 2 revealed no significant effect of concurrent digit load on source memory accuracy. Although previous studies have incorporated a source

72 manipulation when presenting DRM lists, such as two different speakers (e.g., Payne et al., 1996), the present manipulation may have not represented two distinct external sources resulting in only slightly above chance performance for source memory accuracy in both experiments. With source memory performance being close to chance, the risk of a floor effect may have been elevated, possibly masking any potential effects of the concurrent digit load task on source memory. Therefore, in future research, the source monitoring task should be modified so that that the type of source monitoring that is central to the DRM task is assessed directly and performance on the task is not at chance.

Second, working memory capacity was measured through the GoCognitive

Online Working Memory Capacity test (Werner, 2008). Although the task of remembering a series of digits resulting from simple math problems reflects working memory as defined by Baddeley (1992), the test has not been empirically validated compared to other commonly used measures of WMC, (e.g., OSPAN task; La Pointe &

Engle, 1990; Turner & Engle, 1989). Furthermore, there was a relatively small sample size to adequately examine individual differences in WMC. Thus, future research should incorporate a better measure of WMC and have an adequate number of participants to better gauge how individual differences in WMC and the available WMC for the DRM paradigm influences susceptibility to false memory.

APPENDIX A

DRM Word Lists

Anger Black Bread Chair Cold Command mad white butter table hot order fear dark food sit snow army hate cat eat legs warm obey rage charred sandwich seat winter officer temper night rye couch ice performance fury funeral jam desk wet do ire color milk recliner frigid tell wrath grief flour sofa chilly general happy blue jelly wood heat shout fight death dough cushion weather halt hatred ink crust swivel freeze voice mean bottom slice stool air soldier calm coal wine sitting shiver harsh emotion brown loaf rocking Arctic attention enrage gray toast bench frost sharp

Doctor Flag Foot Fruit High King nurse banner shoe apple low queen sick American hand vegetable clouds England lawyer symbol toe orange up crown medicine stars kick kiwi tall prince health anthem sandals citrus tower George hospital stripes soccer ripe jump dictator dentist pole yard pear above palace physician wave walk banana building throne ill raised ankle berry noon chess patient national arm cherry cliff rule office checkered boot basket sky subjects stethoscope emblem inch juice over monarch surgeon sign sock salad airplane royal clinic freedom knee bowl dive leader cure pendant mouth cocktail elevate reign

Lion Mountain Music Pen River Rough tiger hill note pencil water smooth circus valley sound write stream bumpy jungle climb piano fountain lake road tamer summit sing leak Mississippi tough den top radio quill boat sandpaper cub molehill band felt tide jagged Africa peak melody Bic swim ready mane plain horn scribble flow coarse cage glacier concert crayon run uneven feline goat instrument Cross barge riders roar bike symphony tip creek rugged fierce climber jazz marker brook sand bears range orchestra red fish boards hunt steep art cap bridge ground pride ski rhythm letter winding gravel

Rubber Shirt Sleep Smell Soft Spider elastic blouse bed nose hard web bounce sleeves rest breathe light insect gloves pants awake sniff pillow bug tire tie tired aroma plush fright ball button dream hear loud fly eraser shorts wake see cotton arachnid springy iron snooze nostril fur crawl foam polo blanket whiff touch tarantula galoshes collar doze scent fluffy poison soles vest slumber reek feather bite latex pocket snore stench furry creepy glue jersey nap fragrance downy animal flexible belt peace perfume kitten ugly resilient linen yawn salts skin feelers stretch cuffs drowsy rose tender small

Stove Sweet Wish hot sour want heat candy dream pipe sugar desire cook bitter hope warm good well fire taste think oven tooth star wood nice bone kitchen honey ring lid soda wash coal chocolate thought gas heart get iron cake true range tart for furnace pie money

APPENDIX B

Participant Information Questionnaire

Researchers fill out:

Date ______Participant ID ______Condition______\

Please answer the following questions below:

1.) Your age ______

2.) Gender ______Male ______Female

3.) Ethnicity ______American Indian, Eskimo, or Aleut ______Asian American or Pacific Islander ______African American ______Hispanic, Latino, or Spanish ______Middle Eastern ______Caucasian ______Multi-ethnic ______Other 4.) Primary Language ______English ______Other (explain) ______

APPENDIX C

Inventory of Memory Experience

Participant ID ______

The following questions ask how well you REMEMBER various experiences in your life. Please rate your memory on the following seven-point scale, with 1 = Not at all and 7 = Perfectly. There are no correct or wrong answers to these questions. Please answer the questions as accurately as possible.

1 2 3 4 5 6 7 Not Barely Not so Fairly Very Almost Perfectly at all at all well well well perfectly ______1. Do you remember any toys that you had as a young child? (Don’t count any toys you have kept until now.) Think of whatever toy you remember the best. What was it like? How well do you remember what it was like?

1 2 3 4 5 6 7

2. Do you remember any time that your parents punished you as a young child? Think of whatever time you remember best. How well do you remember it?

1 2 3 4 5 6 7

3. Do you remember any time that you were sick or hurt as a young child? Think of whatever you remember best. How well do you remember it?

1 2 3 4 5 6 7

4. Do you remember any child you used to play with when you were a young child? (Don’t count brothers or sisters, or people you still know.) Think of whatever playmate you remember best. How well do you remember them?

1 2 3 4 5 6 7

5. Did you ever visit some place with friends and afterwards talk about the furniture or the decorations or other objects that were there? If so, how well did you remember them?

1 2 3 4 5 6 7

6. When you and your friends have seen the same movie or TV show, do you ever talk about it afterwards? If so, how well do you remember the show?

1 2 3 4 5 6 7

7. When you and your friends have been with some other person, do you or they ever talk afterwards about the clothes that person was wearing? If so, how well do you remember those clothes?

1 2 3 4 5 6 7

8. When you have seen something happen (an accident, an unusual event, etc.), do you ever talk about it with friends later? If so, how well do you remember what you have seen?

1 2 3 4 5 6 7

The following questions ask how often you FORGET various experiences in your life. Please rate your memory on the following seven-point scale, with 1 = Always and 7 = Never. There are no correct or wrong answers to these questions. Please answer the questions as accurately as possible. 1 2 3 4 5 6 7 Always Very Fairly About Now and Once in a Never often often half the then while time ______1. How often do you remember something that somebody said to you, but forgot just who said it?

1 2 3 4 5 6 7

2. If you go to the supermarket to buy four or five things (without a written shopping list), how often do you forget at least one of them?

1 2 3 4 5 6 7

3. How often do you discover, when you have just gone out, that you must return for something you had intended to bring but accidentally left behind?

1 2 3 4 5 6 7

4. When you put something away and then look for it a week or so later, how often do you forget where you had put it?

1 2 3 4 5 6 7

5. How often do you find that just when you want to introduce someone you know to someone else, you can’t think of their name?

1 2 3 4 5 6 7

6. Suppose you were going back to some place (such as a friend’s house) where you had only been once before. Would you have to ask for directions?

1 2 3 4 5 6 7

1 2 3 4 5 6 7 Always Very Fairly About Now and Once in a Never often often half the then while time

7. Think of the times when you have looked up a local number in the phone book. Some people begin to dial the number and then must look back at it again in order to finish dialing. How often does this happen to you?

1 2 3 4 5 6 7

8. Think of times when someone has given you directions to get to some unfamiliar place. How often do you forget the directions before getting there?

1 2 3 4 5 6 7

9. How often are you unable to find something that you put down only a few minutes before?

1 2 3 4 5 6 7

10. Think of times when you have recognized an actor (in a movie or TV show) as one whom you have seen in other shows before. When this happens how often do you fail to remember this actor’s name?

1 2 3 4 5 6 7

11. Think of times when you have gone to a room to do something or get something. How often do you get there and find that you can’t remember why you went?

1 2 3 4 5 6 7

12. Think of times when you have addressed a letter to someone, at an address that you had used several times before. How often do you find that you must look up the address again because you don’t remember it?

1 2 3 4 5 6 7

13. When someone says he has told you something already (at some earlier time), how often do you find that you have no recollection of his telling you any such thing?

1 2 3 4 5 6 7

1 2 3 4 5 6 7 Always Very Fairly About Now and Once in a Never often often half the then while time 14. Think of times when you have been introduced to people at a social gathering (a party, meeting, etc.) and happened to see them on the street a few days later. How often are you unable to remember their names although you know perfectly well when and where you met them?

1 2 3 4 5 6 7 15. When you go out to run a few errands (and don’t have them written down on a list), how often do you forget to do at least one of them?

1 2 3 4 5 6 7

16. When you are telling someone a joke or a story, how often do you forget the punch line or ending before you get to it?

1 2 3 4 5 6 7

17. Think of times when you have recognized an actor (in a movie or TV show) as one whom you have seen in other shows before. How often are you unable to remember where, or in what show, you saw the actor before?

1 2 3 4 5 6 7

18. People may be asked about something (such as a brand name, an address or an item in the news) and think they don’t know the answer; but when someone else gives the answer they realize that they knew it after all. How often does this happen to you?

1 2 3 4 5 6 7

19. When you have just asked a question, how often do you realize that you already knew the answer yourself?

1 2 3 4 5 6 7

20. When you are in a restaurant and want to speak to your waiter or waitress, how often do you forget what he or she looked like (so you don’t know which waiter or waitress to call)?

1 2 3 4 5 6 7

1 2 3 4 5 6 7 Always Very Fairly About Now and Once in a Never often often half the then while time 21. How often do you find, at the end of a conversation, that you forget to bring up some point or some question that you had intended to mention?

1 2 3 4 5 6 7

22. Think of times when you have been introduced to people at a social gathering (a party, a meeting, etc.) and have wanted to call them by name a few minutes later, how often do you find that you have already forgotten their name?

1 2 3 4 5 6 7

23. Think of times when you have called somebody on the phone, using a phone number that you had called several times before. How often do you find that you must look the number up again because you don’t remember it?

1 2 3 4 5 6 7

24. How often when someone mentions a name that sounds familiar to you (it “rings a bell”), do you find that you cannot identify it: that is, you can’t say whom the name belongs to, or why it seems familiar?

1 2 3 4 5 6 7

APPENDIX D

Warning Instructions

In this experiment, you will see lists of words presented on the computer screen. Your job is to try to remember the words you see. Your memory for each list will be tested immediately after each list is presented and then during one final test once all lists have been presented.

Each list that you will be presented with contains words that are related to each other. For each list, all of the words are associated with a common word. People often falsely remember the common word as having been on the list. To avoid this error, you should try to figure out what the word is that ties all the other words together and avoid recalling this common word when your memory of the list of words is tested. After each list, you will be asked to guess what the common word is.

For example, you might see the following words: town, crowded, state, capital, streets, subway, country, New York, village, metropolis, big, Chicago, suburb, county, urban.

In this case, city is the word that links all the above words but was not present in the list. Sometimes people mistakenly remember the word that links together all the others (e.g., city) even when it was not presented. Do not make this error.

References

Alpert, J. L., Brown, L. S., & Courtois, C. A. (1998). Symptomatic clients and memories

of childhood abuse. Psychology, Public Policy, and Law, 4(4), 941-995.

Baddeley, A. D. (1992). Working memory. Science, 255(5044), 556-559.

Baddeley, A. D. (2000). The episodic buffer: A new component of working memory?

Trends in Cognitive Sciences, 4(11), 417-423.

Baddeley, A. D., & Hitch, G. J. (1974). Working memory. In G.A. Bower (Ed.), Recent

advances in learning and motivation (Vol. 8, pp. 47–90). New York: Academic

Press.

Balota, D. A., Cortese, M. J., Duchek, J. M., Adams, D. A., Roediger, H. L., McDermott,

K. B., & Yerys, B. E. (1999). Veridical and false memories in healthy older adults

and in dementia of the Alzheimer’s type. Cognitive Neuropsychology, 16, 361–

384.

Bartlett, F. C. (1932). Remembering: A study in experimental and social psychology.

Cambridge University Press.

Bixter, M. T. & Daniel, F. (2013). Working memory differences in illusory recollection

of critical lures. Memory & Cognition, 41, 716-725.

Brainerd, C. J., & Reyna, V. F. (1998). When things that never happened are easier to

“remember” than things that did. Psychological Science, 9, 484-489.

Brainerd, C. J., Reyna, V. F., & Forrest, T. J. (2002). Are young children susceptible to

the false-memory illusion? Child Development, 73(5), 1363-1377.

Brenneis, C. B. (1997). Final report of APA Working Group on Investigation of

Memories of Childhood Abuse: A critical commentary. Psychoanalytic

Psychology,14, 531-547.

Cohen, J. D., MacWhinney, B., Flatt, M., & Provost, J. (1993). PsyScope: An interactive

graphic system for designing and controlling experiments in the psychology

laboratory using Macintosh computers. Behavioral Research Methods,

Instruments, & Computers, 25, 257-271.

Deese, J. (1959). On the prediction of occurrence of particular verbal intrusions in

immediate recall. Journal of Experimental Psychology, 58, 17-22.

Engle, R. W. (2001). What is working memory capacity?. In H. L. Roediger III & J. S.

Nairne (Eds.), The nature of remembering: Essays in honor of Robert G. Crowder

(pp. 297-314). Washington, DC: American Psychological Association.

Engle, R. W. (2002). Working memory capacity as executive function. Current

Directions in Psychological Science, 11, 19-23.

Engle, R. W., Tuholski, S. W., Laughlin, J. E., & Conway, A. R. (1999). Working

memory, short-term memory, and general fluid intelligence: a latent-variable

approach. Journal of Experimental Psychology: General, 128(3), 309-331.

Gallo, D. A. (2010). False memories and fantastic beliefs: 15 years of the DRM illusion.

Memory & Cognition, 38(7), 833-848.

Gallo, D. A., McDermott, K. B., Percer, J. M., & Roediger, H. L. (2001). Modality

effects in false recall and false recognition. Journal of Experimental Psychology:

Learning, Memory, and Cognition, 27(2), 339-353.

Gallo, D. A., Roberts, M. J., & Seamon, J. G. (1997). Remembering words not presented

in lists: Can we avoid creating false memories? Psychonomic Bulletin & Review,

4, 271–276.

Gardiner, J. M. (1988). Functional aspects of recollective experience. Memory &

Cognition, 16, 309–313. doi:10.3758/BF03197041

Garry, M., Manning, C. G., Loftus, E. F., & Sherman, S. J. (1996). Imagination inflation:

Imagining a childhood event inflates confidence that it occurred. Psychonomic

Bulletin & Review, 3(2), 208-214.

Herndon, P., Myers, B., Mitchell, K., Kehn, A., & Henry, S. (2014). False memories for

highly aversive early childhood events: Effects of guided imagery and group

influence. Psychology Of Consciousness: Theory, Research, And Practice, 1(1),

20-31. doi:10.1037/cns0000011

Herrmann, D. J., & Neisser, U. (1978). An inventory of everyday memory experiences.

In M. M. Gruneberg, P. E. Morris, & R. N. Sykes (Eds.), Practical aspects of

memory (pp. 35–51). New York: Academic Press.

Hyman, I. E., Husband, T. H., & Billings, F. J. (1995). False memories of childhood

experiences. Applied Cognitive Psychology, 9(3), 181-197.

doi:10.1002/acp.2350090302

Israel, L., & Schacter, D. L. (1997). Pictorial encoding reduces false recognition of

semantic associates. Psychonomic Bulletin and Review, 4(4), 577–581.

Johnson, M. K., Hashtroudi, S., & Lindsay, D. S. (1993). Source Monitoring.

Psychological Bulletin, 114, 3-28.

Johnson, M. K., & Raye, C. L. (1981). Reality monitoring. Psychological Review, 88,

67–85.

Kane, M. J., & Engle, R. W. (2002). The role of prefrontal cortex in working-memory

capacity, executive attention, and general fluid intelligence: An individual

differences perspective. Psychonomic Bulletin & Review, 9, 637–671.

Lampinen, J., Neuschatz, J., & Payne, D. (1997). Memory illusions and consciousness:

Examining the phenomenology of true and false memories. Current Psychology,

16, 181–224.

LaPointe, L. B., & Engle, R. W. (1990). Simple and complex word spans as measures of

working memory capacity. Journal of Experimental Psychology: Learning,

Memory, & Cognition, 16, 1118–1133.

Loftus, E. F. (1975). Leading questions and the eyewitness report. Cognitive Psychology,

7, 560-572.

Loftus, E. F. (1993). The reality of repressed memories. American Psychologist, 48, 518-

537.

Loftus, E. F., Miller, D. G., & Burns, H. J. (1978). Semantic integration of verbal

information into a visual memory. Journal of Experimental Psychology: Human

Learning and Memory, 4, 19-31.

Loftus, E. F., & Palmer, J. E. (1974). Reconstruction of automobile destruction: An

example of the interaction between language and memory. Journal of Verbal

Learning and Verbal Behavior, 13, 585–589.

Loftus, E. F. & Pickrell, J. E. (1995). The formation of false memories. Psychiatric

Annals, 25, 720-725.

MacMillan, N. A., & Creelman, C. D. (1991). Detection theory: A user’s guide. New

York: Cambridge University Press.

McDermott, K. B. (1996). The persistence of false memories in list recall. Journal of

Memory and Language, 35, 212–230.

McDermott, K. B., & Roediger, H. L., III (1998). Attempting to avoid illusory memories:

Robust false recognition of associates persists under conditions of explicit

warnings and immediate testing. Journal of Memory and Language, 39, 508–520.

Neuschatz, J. S., Benoit, G. E., & Payne, D. G. (2003). Effective warnings in the Deese–

Roediger–McDermott false-memory paradigm: The role of identifiability. Journal

of Experimental Psychology: Learning, Memory, and Cognition, 29, 35–41.

Nourkova, V., Bernstein, D. M., & Loftus, E. F. (2004). Altering traumatic memory.

Cognition and Emotion, 18(4), 575-585.

Okado, Y., & Stark, C. (2005). Neural activity during encoding predicts false memories

created by misinformation. Learning and Memory, 12, 3-11.

Ornstein, P. A., Ceci, S. J., & Loftus, E. F. (1998). Adult recollections of childhood

abuse. Psychology, Public Policy, and Law, 4(4), 1025-1051.

Partlett, D. F., & Nurcombe, B. (1998). Recovered memories of child sexual abuse and

liability. Psychology, Public Policy, and Law, 4(4), 1253-1306.

Payne, D. G., Elie, C. J., Blackwell, J. M., & Neuschatz, J. F. (1996). Journal of Memory

and Language, 35, 261-285.

Peters, M. J. V., Jelicic, M., Verbeek, H., & Merckelbach, H. (2007). Poor working

memory predicts false memories. European Journal of Cognitive Psychology, 19,

231-232.

Pierce, B. H., Gallo, D. A., Weiss, J. A., & Schacter, D. L. (2005). The modality effect in

false recognition: Evidence for test-based monitoring. Memory & Cognition,

33(8), 1407-1413.

Qin, J., Ogle, C. M., & Goodman, G. S. (2008). Adults’ memories of childhood: True and

false reports. Journal of Experimental Psychology: Applied, 14, 373-391.

Roediger, H. L., III (1996). Memory illusions. Journal of Memory and Language, 35(2),

76-100. doi:10.1006/jmla.1996.0005

Roediger, H. L., III, Balota, D. A., & Watson, J. M. (2001). Spreading activation and the

arousal of false memories. In H. L. Roediger III, J. S. Nairne, I. Neath, & A. M.

Surprenant (Eds.), The nature of remembering: Essays in honor of Robert G.

Crowder (pp. 95-115). Washington DC: American Psychological Association.

Roediger, H. L., III, & McDermott, K. B. (1995). Creating false memories: Remembering

words not presented in lists. Journal of Experimental Psychology: Learning,

Memory, and Cognition, 21, 803–814.

Roediger, H. L., III, & McDermott, K. B. (2000). Tricks of memory. Current Directions

in Psychological Science, 9, 123-127.

Roediger, H. L. III, Watson J. M., McDermott K. B., & Gallo D. A. (2001). Factors that

determine false recall: a multiple regression analysis. Psychonomic Bulletin &

Review, 8(3), 385-407.

Schacter, D. (2001). The seven sins of memory: How the mind forgets and remembers.

New York: Houghton Mifflin.

Schacter, D. L., Israel, L., & Racine, C. (1999). Suppressing false recognition in younger

and older adults: The distinctiveness heuristic. Journal of Memory and Language,

40, 1-24.

Schacter, D. L., Koutstaal, W., & Norman, K. A. (1997). False memories and aging.

Trends in Cognitive Sciences, 1(6), 229-236. doi:10.1016/S1364-6613(97)01068-

Schacter, D. L., Norman, K. A., & Koutstaal, W. (1998). The cognitive neuroscience of

constructive memory. Annual Review of Psychology, 49, 289-318.

doi:10.1146/annurev.psych.49.1.289

Snodgrass, J. G., & Corwin, J. (1988). Pragmatics of measuring recognition

memory: Applications to dementia and amnesia. Journal of Experimental

Psychology: General, 117, 34–50.

Tulving, E. (1985). Memory and consciousness. Canadian Psychology, 26, 1–12.

doi:10.1037/h0080017

Turner, M. L., & Engle, R. W. (1989). Is working memory capacity task dependent?

Journal of Memory & Language, 28, 127-154.

Underwood, B. J. (1965). False recognition produced by implicit verbal responses.

Journal of Experimental Psychology, 70(1), 122-129.

Unsworth, N., & Brewer, G.A. (2010). Individual differences in false recall: A latent

variable analysis. Journal of Memory and Language, 62, 19-34.

Unsworth, N., Redick, T. S., Heitz, R. P., Broadway, J. M., & Engle, R. W. (2009).

Complex working memory span tasks and higher-order cognition: A latent-

variable analysis of the relationship between processing and storage. Memory,

17(6), 635-654.

Watson, J. M., Bunting, M. F., Poole, B. J., & Conway, A. R. A. (2005). Individual

differences in susceptibility to false memory in the Deese-Roediger-McDermott

paradigm. Journal of Experimental Psychology: Learning, Memory, and

Cognition, 31, 76–85. doi:10.1037/0278-7393.31.1.76.

Watson, J. M., McDermott, K. B., & Balota, D. A. (2004). Attempting to avoid false

memories in the Deese/Roediger-McDermott paradigm: Assessing the combined

influence of practice and warnings in young and old adults. Memory & Cognition,

32(1), 135-141.

Werner, (2008). GoCognitive Working Memory Capacity [Computer program].

Retrieved from http://www.gocognitive.net/demo/working-memory-capacity

Winograd, E., Peluso, J. P., & Glover, T. A. (1998). Individual differences in

susceptibility to memory illusions. Applied Cognitive Psychology, 12, 5-27.