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Thesis

Reference

Adult age differences in prospective memory performance: exploring the age prospective memory paradox

IHLE, Andreas

Abstract

La mémoire prospective consiste à se rappeler d'actions futures, à exécuter dans un délai plus ou moins court, tout en étant déjà engagé dans une autre activité. Trois décennies de recherche sur ce thème ont révélé un intéressant pattern de performances, qui varie en fonction de l'âge : Lorsque la mémoire prospective est étudiée en laboratoire, les jeunes adultes présentent de meilleurs résultats que les adultes âgés. Or, dans un contexte naturalistique, les adultes âgés présentent des résultats équivalents voire meilleurs que les adultes jeunes. Plusieurs explications ont été données à ce phénomène, appelé "paradoxe âge-mémoire prospective". Cependant, les résultats sont hétérogènes et ne permettent pas de tirer une conclusion unique. Pour cette raison, le but de la présente thèse est d'examiner certains arguments avancés pour expliquer ce paradoxe comme l'effet du degré d'importance des intentions, l'influence de la spécificité de l'ordre des tâches et l'impact du stress.

IHLE, Andreas. Adult age differences in prospective memory performance: exploring the age prospective memory paradox. Thèse de doctorat : Univ. Genève, 2013, no. FPSE 546

URN : urn:nbn:ch:unige-334262

DOI : 10.13097/archive-ouverte/unige:33426

Available at:

http://archive-ouverte.unige.ch/unige:33426

Disclaimer: layout of this document may differ from the published version.

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Section de Psychologie Sous la direction de Prof. Matthias Kliegel

Adult age differences in prospective memory performance:

Exploring the age prospective memory paradox

THESE

Présentée à la

Faculté de Psychologie et des Sciences de l’Education de l’Université de Genève

pour obtenir le grade de Docteur en Psychologie

par Andreas IHLE

de

Teterow, Allemagne Numéro d’étudiant : 12-335-311

Thèse No 546 GENEVE, novembre 2013

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Acknowledgement

At this point, I would like to thank the people who supported me during the time of this thesis.

First of all, I am very grateful to Prof. Matthias Kliegel for his comprehensive support, his scientific advice, and for giving me the opportunity to work with him and learn from him over the last years. Furthermore, I would like to express my thankfulness to Prof. David Bunce, Prof. Paolo Ghisletta, and Prof. David Sander for their willingness to evaluate my thesis.

In addition, I wish to thank my colleagues for their scientific support and for being such stimulating companions in the last years.

Most of all, I would like to thank my parents, Ricarda and Dietmar, my sister Ulrike, and especially Bianca, for supporting me all the time and encouraging me whatever I do.

Finally, I am very grateful to all participants taking part in the reported studies and the people who helped with data collection - this work would not exist without their help.

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Statement

The presented work is a cumulative dissertation consisting of three studies. It has been prepared as a self-contained work. All chapters were composed specifically for this dissertation.

The three studies are the following:

Study 1 (Chapter 4): Ihle, A., Schnitzspahn, K., Rendell, P. G., Luong, C., & Kliegel, M.

(2012). Age benefits in everyday prospective memory: The influence of personal task importance, use of reminders and everyday stress. Aging, Neuropsychology, and Cognition, 19(1-2), 84-101.

Study 2 (Chapter 5): Ihle, A., Hering, A., Mahy, C. E. V., Bisiacchi, P. S., & Kliegel, M.

(2013). Adult Age Differences, Response Management, and Cue Focality in Event-Based Prospective Memory: A Meta-Analysis on the Role of Task Order Specificity. Psychology and Aging, 28(3), 714-720.

Study 3 (Chapter 6): Ihle, A., Kliegel, M., Hering, A., Ballhausen, N., Lagner, P., Benusch, J., Cichon, A., Zergiebel, A., & Schnitzspahn, K. M. (2013). Adult age differences in prospective memory in the laboratory: Are they related to higher stress levels in the elderly? Manuscript submitted for publication.

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Contents

Abstract ... 1

1. Introduction ... 3

2. What do we already know about PM? ... 6

2.1 Definition and a first portrayal of PM ... 6

2.2 Classification of PM tasks ... 8

2.3 Adult age differences in PM - What is the age PM paradox? ... 9

2.4 Mechanisms of adult age differences in naturalistic PM ... 11

2.5 Mechanisms of adult age differences in laboratory PM ... 15

2.6 Adult age differences in PM - A cognitive aging perspective ... 21

3. Research aims and hypotheses ... 24

3.1 Does personal task importance, use of reminders, and everyday stress affect adult age differences in everyday PM? (Study 1) ... 24

3.2 Does task order specificity influence adult age differences in event-based laboratory PM? (Study 2) ... 25

3.3 Are adult age differences in laboratory PM attributable to age differences in stress level? (Study 3) ... 26

4. Study 1: Investigating the impact of task importance, reminders, and stress on adult age differences in everyday PM ... 28

4.1 Abstract ... 28

4.2 Introduction ... 28

4.3 Method ... 32

4.4 Results ... 36

4.5 Discussion ... 43

5. Study 2: Investigating the impact of task order specificity on adult age differences in event-based laboratory PM ... 51

5.1 Abstract ... 51

5.2 Introduction ... 51

5.3 Method ... 54

5.4 Results ... 58

5.5 Discussion ... 61

6. Study 3: Investigating the impact of stress on adult age differences in laboratory PM ... 65

6.1 Abstract ... 65

6.2 Introduction ... 65

6.3 Method ... 68

6.4 Results ... 72

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6.5 Discussion ... 75

7. General discussion ... 80

7.1 Discussion of research questions ... 80

7.1.1 Does personal task importance, use of reminders, and everyday stress affect adult age differences in everyday PM? (Study 1) ... 80

7.1.2 Does task order specificity influence adult age differences in event-based laboratory PM? (Study 2) ... 84

7.1.3 Are adult age differences in laboratory PM attributable to age differences in stress level? (Study 3) ... 85

7.2 Conceptual, applied, and methodological implications ... 86

7.2.1 The role of personal task importance and use of reminders in PM ... 86

7.2.2 The role of flexibility in the fulfillment of intentions ... 90

7.2.3 The role of stress in PM ... 94

7.2.4 Adult age differences in PM within the broader field of cognitive aging ... 96

7.2.4.1 Adult age differences in PM - A cognitive aging perspective ... 96

7.2.4.2 Adult age differences in PM - Alternative mechanisms... 116

7.2.4.3 Adult age differences in PM - A “naturalistic” perspective ... 121

7.2.4.4 Disentangling the age PM paradox ... 138

7.2.4.5 Can laboratory PM research and naturalistic PM research benefit from each other? ... 141

7.2.4.6 Can cognitive aging research benefit from PM research? ... 146

7.2.4.7 Adult age differences in PM and the broader field of cognitive aging - Conclusions ... 151

7.2.5 Applied implications ... 152

7.2.6 Methodological implications ... 154

7.3 Open questions and outlook ... 155

7.3.1 Mechanisms of age differences in everyday PM ... 155

7.3.2 Mechanisms of response management processes in PM ... 158

7.3.3 Exploring confounding mechanisms ... 159

7.4 Summary ... 162

8. References ... 164

Appendix ... 190

Appendix A Study-level effects (in the meta-analysis in Study 2) ... 190

Appendix B Résumé en français ... 201

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Abstract

Prospective memory (PM) is a key component for successfully realizing everyday tasks such as remembering to attend appointments or to post a letter on the way home.

Specifically, PM represents the ability to remember, initiate, and perform planned intentions (Einstein & McDaniel, 1990; Zeintl, Kliegel, & Hofer, 2007). Three decades of research on adult age differences in PM have revealed a remarkable pattern: When PM is assessed in laboratory settings, younger adults mainly show better PM performance compared to older adults, while in naturalistic settings, older adults are often as good as their younger

counterparts or even better (Henry, MacLeod, Phillips, & Crawford, 2004). Many attempts have been made to explain this so called “age prospective memory paradox” (Rendell &

Craik, 2000). For example, several task characteristics and age differences in motivation, in the use of compensatory strategies, or in features of older adults’ everyday life have been discussed and (partly) tested (Phillips, Henry, & Martin, 2008). However, results are

heterogeneous and so far inconclusive. Therefore, the overall goal of the present work was to extend the literature by further investigating several debated key mechanisms in PM

performance in general and in particular with respect to adult age differences. To provide a thorough examination, different types of PM tasks in different settings (i.e., the laboratory and the field) and different methodological approaches (i.e., diary, meta-analytic, and

experimental methods) were used.

With a diary approach, Study 1 examined everyday PM in younger and older adults and explored the role of personal task importance, use of reminders, and everyday stress as possible correlates of age-related PM performance in everyday life. Results demonstrated that the age benefit observed in experimenter-given tasks transfers to everyday PM and varies in dependence of motivational and cognitive factors. Study 2 used meta-analytic techniques to investigate whether event-based laboratory PM age effects differ by task order specificity to

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extend current conceptual views in PM research that so far focused on cue detection processes to post-retrieval response management processes as further sources of PM age effects in later phases of the PM process. Present findings suggest that both pre- and post-retrieval processes independently affect PM age effects. Study 3 focused on the recently discussed aspect that a laboratory testing situation per se may be more stressful for older adults and thereby might reduce their performance. To test whether this could explain age deficits in laboratory PM, younger and older adults performed a time-based PM task and stress levels were assessed during the experiment. Results indicate that stress plays a minor role in laboratory PM.

On the whole, the present work innovatively extends current conceptual views concerning the age benefit in real life PM and post-retrieval response management processes as further sources of PM age effects in later phases of the PM process. It clarified a number of open issues in the ongoing conceptual debate of underlying mechanisms in adult age

differences in prospective remembering in different task settings, and thereby takes a further step towards understanding age-related PM performance. Moreover, the present work has implications for the broader field of cognitive aging research. It underlines the necessity to explicitly consider the interplay of several cognitive and non-cognitive variables to fully explain and comprehend the multifaceted effects of aging, especially in complex cognitive behavior such as prospective remembering.

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1. Introduction

The colleagues got together for the team meeting in the conference room. It was time and they were just about to start when they realized that one of their senior colleagues was not there. When they found him in his office working busily, he admitted that he had

completely forgotten the meeting...

Why do we forget such important intentions?

Does this only happen in older age or also in younger adults?

Which factors determine whether plans are carried out successfully or not?

Prospective memory (PM) is the ability to remember, initiate, and perform planned intentions (Einstein & McDaniel, 1990; Zeintl, Kliegel, & Hofer, 2007). PM is a key component to successfully executing everyday tasks such as keeping appointments, paying the utility bill in time, or posting a letter on the way home. The importance of PM in this context becomes evident when considering that 50 to 80 percent of all everyday memory problems are (at least partly) attributable to PM failures (e.g., Crovitz & Daniel, 1984; Terry, 1988). This is an important issue, particularly with a focus on aging as developmental changes across the lifespan entail a decline in a variety of cognitive functions and an increase in

memory problems (Bolla, Lindgren, Bonaccorsy, & Bleecker, 1991; Salthouse, Atkinson, &

Berish, 2003). Hence, promoting PM plays a major role in supporting an independent life in older age. An example is health-related behavior such as remembering to attend medical appointments, to take medication according to a schedule, or to monitor indices of physical functions such as blood sugar level and blood pressure for which intact PM is essential (e.g., Liu & Park, 2004).

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The overall aim of the present work was to systematically investigate potential key mechanisms underlying adult age differences in PM performance in the laboratory and in a naturalistic setting. For this purpose, three studies using multiple methodological approaches (i.e., diary, meta-analytic, and experimental methods) were conducted. Selected mechanisms suggested by the literature as possibly underlying age differences in PM were investigated.

Beyond that, the present work aimed to clarify two open issues that so far have not been the focus in PM research but would entail important conceptual, applied, and methodological implications in the context of PM and aging: The first issue concerns the observation that there is only little known about PM in real life, and up to now it is unclear whether the age benefit found in naturalistic, but nevertheless experimenter-given PM tasks can be confirmed in real life PM with tasks naturally occurring in everyday life. This progress in PM research could be entitled “from lab to life”. The second issue concerns the fact that research on PM and aging so far focused on pre-retrieval phases in the PM process, and up to now

mechanisms in later phases such as response management processes as possible further sources of PM age differences have not been studied. This progress in PM research could be labeled “from intention initiation to intention execution”. Because of their potential for PM research, these two issues are emphasized in the present work.

In Chapter 2, an overview of PM in general is given, followed by a summary of previous research on adult age differences in PM as well as factors proposed to explain these effects. In Chapter 3, the research aims and hypotheses of the present work are specified. In the following three chapters, the conducted studies are reported. Specifically, Chapter 4 presents a diary study investigating the impact of personal task importance, use of reminders, and everyday stress on adult age differences in everyday PM performance. Chapter 5

describes a meta-analytic study testing whether different levels of task order specificity influence age effects in event-based laboratory PM. Chapter 6 reports an experimental study investigating the role of stress in laboratory PM with regard to adult age differences. Finally,

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in Chapter 7, the present findings are discussed, their conceptual, applied, and methodological implications are taken into account, and directions for future research are proposed.

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2. What do we already know about PM?

2.1 Definition and a first portrayal of PM

PM is defined as remembering to realize a planned action at a particular moment in the future while being engaged in an ongoing activity (Brandimonte, Einstein, & McDaniel, 1996;

Ellis, 1996; Ellis & Kvavilashvili, 2000). Everyday examples of PM are remembering to call a friend at his birthday, to attend the appointment at the hairdresser, or to take medication according to a schedule. A major feature of PM is that the intended action should be

performed after a certain delay between the formation of the plan and its realization, typically in a self-initiated way (Ellis, 1996). This entails the need to interrupt the activity currently ongoing to allow the execution of the intention (Ellis & Kvavilashvili, 2000). Moreover, PM tasks consist of two distinct components, a prospective and a retrospective component (Einstein & McDaniel, 1990, 1996). The prospective component concerns the self-initiation aspect in intention execution, that is, to remember that something has to be done,

prototypically just in the designated moment when this particular plan should be carried out (Ellis & Freeman, 2008). In comparison, the retrospective component refers to the content of the intention itself, that is, to remember what exactly has to be done. With regard to the aforementioned example of calling a friend at his birthday, these characteristic features of PM can be illustrated: The intention to congratulate may have been made a few days before the birthday, resulting in a delay between the initial intention to call him and the actual birthday.

With time having passed and that particular day having come, it may “pop” into mind that there was something to be done (i.e., prospective component), which is giving a particular friend a birthday call (i.e., retrospective component). Finally, currently ongoing activities need to be interrupted to allow for a successful realization.

With regard to this example, it is conceivable that successful PM requires correct processing of several subtasks in different stages. To specify this interplay of multiple

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components in prospective remembering in more detail, several distinct phases have been considered (Ellis, 1996; Kliegel, Martin, McDaniel, & Einstein, 2002; see also Kliegel, Altgassen, Hering, & Rose, 2011): Specifically, the four phases of intention formation, intention retention, intention initiation, and intention execution were proposed (see Figure 1).

Figure 1. Process model of PM (Kliegel et al., 2002).

In the first phase (i.e., intention formation), the intention to perform a certain action at a particular moment in the future is formed and encoded. This phase often involves forming a plan. The intention formation phase is followed by a period during which the intention is retained in memory. This so called intention retention phase imposes demands on long-term and episodic memory processes to conserve the intention. The third phase (i.e., intention initiation) refers to the appropriate moment in time at which the intended action should be initiated. In the final phase (i.e., intention execution), the intention finally needs to be carried out to perform the PM task properly. Additionally, evaluation of the accomplishment is needed to avoid unnecessary repetitions of already fulfilled intentions or to ensure future success of failed intentions (Ellis, 1996).

When considering this process model, PM failures can be traced back to certain sources as each phase places specific demands on cognitive functions. For instance, planning processes are required during intention formation. Retrospective memory is necessary during the intention retention phase (Kliegel et al., 2011). For an appropriate initiation, monitoring is necessary to detect the proper moment at which it is suitable to carry out the planned action (Smith & Bayen, 2004). To allow for a successful execution of the intended action, the

Intention

formation Intention retention

Intention initiation

Intention execution

Time

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ongoing activity has to be inhibited (Bisiacchi, Schiff, Ciccola, & Kliegel, 2009) and one has to switch to perform the intention, which demands cognitive flexibility (Kliegel, Mackinlay,

& Jäger, 2008b). Taken together, the process of prospective remembering is not a unitary operation but rather characterized by multiple process phases with specific demands on different cognitive functions (Kliegel et al., 2011).

2.2 Classification of PM tasks

The most prominent classification of PM tasks concerns the type of cue indicating that the appropriate moment has come to perform the PM action. Therefore, it is common to distinguish between time-based and event-based PM (Einstein & McDaniel, 1990, 1996).

Time-based PM tasks require an individual to perform a specified behavior at a specific time (e.g., an appointment at 7 p.m.) or after the passage of a given amount of time (e.g., an appointment in two hours). In comparison, event-based PM tasks require an individual to perform a specified behavior in response to an external cue (e.g., the appearance of the colleague for the appointment).

Another classification concerns the setting in which PM is assessed. The vast majority of PM studies was carried out in the laboratory and used a controlled background activity, the so called ongoing task (Einstein & McDaniel, 1990), in which the PM task is embedded. For example, Einstein and McDaniel (1990) asked participants to learn and recall word lists that were presented on a computer screen (ongoing task) and additionally to remember to press a pre-specified key whenever the target word appeared (PM task). Besides the laboratory, there are (much fewer) studies applying PM tasks in a naturalistic setting, that is, in participants’

everyday life. Typical examples are remembering to send a text message to the experimenter at a specific time (Schnitzspahn, Ihle, Henry, Rendell, & Kliegel, 2011) or to log the time periodically on an electronic organizer (Rendell & Thomson, 1993, 1999). In this context,

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everyday activities in which participants are engaged are considered as the pendant to the ongoing task in the laboratory. Further classifications of PM tasks concern for example different levels of cue focality and of task order specificity. These two factors were of particular interest for the present work and are therefore described in more detail below (cf.

Section 2.5).

2.3 Adult age differences in PM - What is the age PM paradox?

The question of whether performance in PM tasks declines in older age exists almost as long as research on PM itself. Already in early days of PM research, with only a handful of PM studies available yet, in his seminal framework on age effects within the general memory domain, Craik (1986) proposed that the demand on self-initiated retrieval of delayed

intentions leads to more effortful memory processes, likely resulting in substantial age deficits. For three decades, developmental psychologists have investigated adult age differences in laboratory PM using a variety of PM tasks, which resulted in an even more diverging pattern of findings: While some studies have found substantial age-related deficits in PM performance (e.g., d’Ydewalle, Bouckaert, & Brunfaut, 2001; Einstein, McDaniel, Richardson, Guynn, & Cunfer, 1995; Mäntylä, 1994; Maylor, 1996a; Park, Hertzog, Kidder, Morrell, & Mayhorn, 1997), others have revealed that older adults perform as well as their younger counterparts (e.g., Einstein & McDaniel, 1990; Jäger & Kliegel, 2008; Reese &

Cherry, 2002; West & Bowry, 2005). However, the first meta-analytic review on adult age differences in PM (Henry, MacLeod, Phillips, & Crawford, 2004) came to the conclusion that older adults generally show a lower performance than younger adults in laboratory PM tasks, hence confirming Craik’s (1986) initial postulation.

As already noted, PM research was not limited to the laboratory itself. Growing interest has been shown regarding the investigation of PM age differences also in the

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naturalistic setting. For this type of PM, Henry et al. (2004) concluded that older adults generally outperform the younger ones. This is a remarkable finding when considering the general PM age deficit in the laboratory, and it is even more surprising since the respective effect sizes reported in Henry et al. were of almost identical size (age deficits in laboratory PM: effect sizes rs = -.34 and -.39 for event- and time-based PM tasks, respectively; age benefits in naturalistic PM: effect sizes rs = +.35 and +.52 for event- and time-based PM tasks, respectively). This finding of contrasting age effects on PM tasks carried out in the laboratory versus in the naturalistic setting has been referred to as the “age prospective memory paradox” (Rendell & Craik, 2000).

It could be discussed that in their meta-analysis, Henry et al. (2004) compared age effects which were found in studies that focused either on laboratory or on naturalistic PM with tasks substantially differing between these two settings regarding several potentially important task parameters. Hence, the concern could be raised that it may be generally

difficult to compare laboratory and naturalistic PM tasks, as they differ in several dimensions.

However, the first study so far, which tested the age PM paradox in a single sample and used comparable tasks for laboratory and naturalistic PM, confirmed the paradoxical finding of age deficits in the laboratory and age benefits in the naturalistic setting (Schnitzspahn et al., 2011).

Because of the curiosity of this pattern, there is growing interest in finding

explanations to take the magic away from the age PM paradox. Concerning the PM age deficit in the laboratory, first models including factors possibly associated with PM performance in younger and older adults were developed and have been partially investigated. Concerning the PM age benefit in the naturalistic setting, no comprehensive model exists yet, but several suppositions were brought up, and single aspects have been examined. As the overall focus of the present work is to systematically investigate selected key mechanisms underlying adult age differences in PM performance in the laboratory and the naturalistic setting, in the

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following, an overview of the ongoing discussion regarding the factors that might contribute to PM performance in younger and older adults in the two settings is given.

2.4 Mechanisms of adult age differences in naturalistic PM

Reviewing the evidence on the age PM paradox, Phillips, Henry, and Martin (2008) summarized various factors that have been discussed in the literature as possible causes for the paradoxical pattern. Concerning the naturalistic setting, they supposed that older adults’

higher PM performance may be attributable to their larger experience with real-world PM tasks, with own memory failures, and with individual time management which may have resulted in the development and use of compensatory strategies to aid the fulfillment of intentions (Maylor, 1996b). Similarly, it is considered that older adults may have greater metacognitive awareness of how to achieve to remember to execute the future task (e.g., Schnitzspahn et al., 2011). Furthermore, it is hypothesized that age differences in attitudes to punctuality and in personality dimensions such as conscientiousness may cause age

differences in naturalistic PM (e.g., Dobbs & Reeves, 1996). Besides that, three other often suggested mechanisms, which are motivational aspects, the use of reminders, and everyday stress were of particular interest for the present work and are therefore described in more detail in this section.

Beyond these many factors discussed, Phillips et al. (2008) underlined the urgent need for studying age differences in naturalistic PM tasks that have high ecological validity, since research on this type of PM could give further important insights into the paradox. They differentiate between artificial tasks externally provided by an experimenter such as calling or posting messages to an experimenter at pre-specified times and “real” naturalistic PM tasks, which naturally occur in everyday life without interference of an experimenter such as keeping appointments, paying a bill in time, or calling a friend at his birthday. Although such

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real life PM examples are often cited in the literature when introducing PM, so far, studies exploring age benefits in naturalistic PM tasks have focused on the artificial experimenter- given task type, and there is surprisingly little known about age-related PM in the real life.

The few PM studies achieving high ecological validity were using medication adherence as the critical task. However, while some studies found that medication compliance is higher in older compared to younger adults (Schulz, O’Donnell, McDonough, Sasane, & Meyer, 2005;

Park et al., 1999), other studies reported an age deficit (Roe, Motheral, Teitelbaum, & Rich, 2000), or no age effect (Lorenc & Branthwaite, 1993). Phillips et al. argued that this

heterogeneity of results may be due to medication adherence being clearly dependent on many other social, physical, and cognitive factors and on the type of medication itself. Beyond that, they emphasized that it would be of interest to know more about everyday PM with a larger variety of intentions in younger and older adults. With regard to the very few and

inconclusive results in this context, it remains an open question whether the age benefit observed in experimenter-given naturalistic PM tasks generalizes to PM tasks naturally occurring in participants’ everyday life. Hence, the major focus of Study 1 was to clarify this important issue.

With regard to motivational aspects, one debated explanation is that older adults may be more motivated to successfully complete PM tasks that are implemented in their everyday life (Moscovitch, 1982; Patton & Meit, 1993; Rendell & Craik, 2000). In comparison, the level of motivation of younger participants to complete PM tasks among the other demands of everyday life may be relatively low. This is particularly likely to be the case for

undergraduate students completing studies for course credits, who represent the majority of younger participants in typical PM studies (Maylor, 1993b). Although this explanation is very widespread, systematic research on this topic is sparse. In a first study directly examining the motivational angle in experimenter-given naturalistic PM tasks in younger and older adults, Aberle, Rendell, Rose, McDaniel, and Kliegel (2010) used a monetary incentive to

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manipulate motivation. Results showed that this improved only younger adults, who then reached the performance level of older adults supporting low motivation as an explanation for younger adults’ inferior performance in naturalistic PM tasks. Further evidence comes from a recent study showing that higher a priori ratings of motivation to perform an experimenter- given naturalistic PM task in the older adults were correlated to subsequent higher PM performance (Schnitzspahn et al., 2011). Besides this first indication that motivational level contributes to age differences in naturalistic PM, it remains an open question whether this mechanism holds also for PM tasks naturally occurring in the everyday life of the participants.

A possibly important indication in this context could be a mechanism, which has been suggested as influential for real life PM performance in a study from Marsh, Hicks, and Landau (1998) focusing on younger adults only. They showed that younger adults realized important real life intentions more frequently than less important ones suggesting that important tasks raise the motivation for correct fulfillment. Study 1 set out to further investigate whether this mechanism found in younger adults could contribute to age differences in real life PM.

Another popular explanation for age benefits in naturalistic PM tasks is that older adults may use more external reminders such as a note in a calendar to cue PM retrieval (Phillips et al., 2008). Available results concerning the use of reminders in younger and older adults in naturalistic PM tasks are however mixed (Maylor, 1996b; Patton & Meit, 1993): In some studies with PM age benefits, older adults reported using more reminders (e.g., Jackson, Bogers, & Kerstholt, 1988), whereas in other studies, the younger ones reported more

frequent use of reminders (e.g., Dobbs & Rule, 1987; Rendell & Thompson, 1999). Rendell and Craik (2000) instructed participants not to use reminders in a naturalistic PM task. In a post-task debriefing interview, both younger and older participants reported generally low use of reminder strategies, whereas an age benefit in PM performance was still present. Moreover, Rendell and Thompson (1999) found that providing both age groups with an alarm in one

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condition and in another condition with instructions and the opportunity to link cues from their environment to the prospective action did not reduce the magnitude of the older adults’

superiority compared to younger adults in the naturalistic PM task. In line with these results, Phillips et al. (2008) concluded that there is remarkably little evidence supporting the popular idea that age benefits in naturalistic PM are caused by increased use of reminders. However, studies on naturalistic PM in younger and older adults concentrated on comparing both age groups with regard to PM performance and use of reminders on a group level and did not focus on possible direct associations of individual use of reminders with subsequent individual PM performance. In a study on naturalistic PM in older adults only, Maylor

(1990a) showed that those participants who used external reminders were more likely to fulfill the intended action than those relying only on internal cues (i.e., that the intention pops into mind on its own). Within this sample of older adults only, there was no age effect on PM performance. However, among those participants who used external memory cues, age was positively associated with PM performance, whereas in the minority of participants who relied only on internal cues, age was negatively associated with PM. Hence, it remains unclear whether there is a direct association of the use of reminders and PM performance on an individual level across different adult age groups and whether this explains age differences in naturalistic PM. A further open question concerns whether the use of reminders might

contribute particularly to age differences in real life PM. There, especially older adults may be more aware of their need for using reminders to aid the fulfillment of intentions. This

suggestion is supported by the finding that older adults seem to have greater knowledge of successfully using supportive strategies in terms of metacognitive awareness (Schnitzspahn et al., 2011). Hence, in the light of these open questions, Study 1 set out to further explore the impact of use of reminders on adult age differences in everyday PM.

A further common explanation for age benefits in naturalistic PM performance is that, compared to older adults, the life of younger adults is less structured, less predictable, more

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engaging, and busier (e.g., Henry et al., 2004; Maylor, 1996b; Rabbitt, 1996). Similarly, it is suggested that older adults have less distraction due to fewer occupations and daily activities through their retirement. This is an important issue since in most PM studies, younger adult university students are compared with retired older adults. Taken together, the suggested underlying mechanism is that older adults may be less stressed than younger adults and therefore can implement delayed intentions more accurately. However, findings regarding potential stress effects on naturalistic PM performance are inconclusive. On one hand, Rendell and Thompson (1999) found no difference in naturalistic PM performance between working and retired older adults. On the other hand, Schnitzspahn et al. (2011) observed that younger adults reported significantly more perceived everyday stress than older adults and everyday stress mediated age-related variance in the naturalistic PM task. Given the heterogeneity of previous results regarding the role of everyday stress in age-related PM performance, Study 1 aimed to further explore this issue. To clarify the role of stress also in the laboratory setting, Study 3 used an experimental approach to evaluate this issue in laboratory PM.

Taken together, various factors have been proposed to explain the age benefit in the naturalistic setting but previous results concern single aspects only, are heterogeneous and so far inconclusive. Therefore, the focus of Study 1 was to further investigate the impact of motivational aspects, use of reminders, and everyday stress on adult age differences in everyday PM performance using real life PM tasks with high ecological validity.

2.5 Mechanisms of adult age differences in laboratory PM

Concerning the laboratory setting, Phillips et al. (2008) suggested that older adults’

lower PM performance may be attributable to the nature of laboratory PM tasks and the used material: Compared to naturalistic settings, most laboratory PM tasks consist of highly

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abstract material with no context or emotional salience, which could be important in

explaining age differences (Ellis & Kvavilashvili, 2000; Rendell & Thompson, 1999). Lack of salience may lower the perceived importance of the PM task and hence could result in more PM failures (McDaniel & Einstein, 2000). Besides these assumptions, several task

characteristics were considered to be possibly associated with age differences in laboratory PM. One potential moderator of PM age effects could be the distinction between time- and event-based PM. With regard to underlying processes, compared to event-based PM, due to the absence of a specific cue, time-based PM is assumed to be particularly dependent on self- initiated mental activities such as active time monitoring (d'Ydewalle et al., 2001). Therefore, it has been argued that PM failures may be more likely in time-based than event-based PM and that age differences should more pronouncedly occur in time-based PM tasks (e.g.,

Einstein et al., 1995; Einstein & McDaniel, 1996; Maylor, 1996b). Henry et al. (2004) directly tested this assumption in their meta-analysis but did not find a significant difference in the size of PM age effects between time-and event-based PM tasks. Hence, the widespread opinion that time-based PM tasks might produce larger age effects was not supported.

Interestingly, Henry et al. found within event-based PM tasks that task demands on strategic processes affected PM age effects: Event-based PM tasks that imposed higher level of strategic demands were associated with larger age effects than event-based tasks with lower level of strategic demands. This finding of Henry et al. supports one of the most influential models in PM research, the multiprocess framework of event-based PM (McDaniel &

Einstein, 2000). Because certain features of this model were of particular interest for the present work, it is outlined in more detail in the following section.

In their multiprocess framework of event-based PM, McDaniel and Einstein (2000) postulated that prospective remembering can be supported either by controlled attentional processing or by relatively spontaneous initiation/retrieval of the target action. As aging is presumed to be associated with deficits in attentional capacities, this framework therefore

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predicts that the magnitude of age effects on event-based tasks will be determined by the extent to which the task depends on spontaneous versus controlled resource-demanding processing. McDaniel and Einstein (2000) suggested that the following factors may increase the strategic, controlled demands of PM paradigms and thus may increase any age deficits: (a) non-distinctive PM cues, meaning that they do not involuntarily capture attention through their appearance (as it would be the case for distinctive/salient cues such as unusual words, words with increased font size, or words in bold); (b) a weak association between the cue and the intended action, for example when the cue is a picture of a flower and the PM task is to remember to ring the bell whenever this target picture occurs (in comparison, a strong association would be the case for a picture of a bell as PM cue); or (c) a highly attention- demanding or engaging ongoing task posing relatively large demands on cognitive resources.

A fourth factor outlined in the multiprocess framework of event-based PM (McDaniel

& Einstein, 2000) that determines the degree to which controlled attentional processes are required (and hence influencing PM age effects), and which was of particular interest for the present work is cue focality. Focal PM tasks are those in which the ongoing task involves processing the defining features of the PM cues (e.g., keeping words in working memory while remembering to press a button whenever a specific word appears; Einstein & McDaniel, 1990). In this case, it is assumed that the PM cues are sufficiently processed during the

ongoing task to enable relatively spontaneous initiation/retrieval of the intended action. In contrast, nonfocal PM tasks are those in which the defining features of the PM cues are not part of the information being extracted in the service of the ongoing task (e.g., keeping words in working memory while remembering to press a button whenever the background of the screen shows a particular pattern; Park et al., 1997). In nonfocal tasks, prospective

remembering is thought to require considerable strategic attentional resources in order to carry out additional monitoring for PM cue detection. In line with these predictions, a meta- analytic study on the role of focal versus nonfocal cues in event-based PM (Kliegel, Phillips,

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& Jäger, 2008c) reported more pronounced age effects in nonfocal compared to focal PM tasks.

To identify further factors that are possibly associated with adult age differences in event-based PM, a recent conceptual discussion has extended the focus from (pre-retrieval) factors determining the demand on strategic monitoring for PM cue detection to later phases in the PM process after the cue has been successfully detected when participants must

navigate between completing the PM and ongoing task (e.g., Bisiacchi et al., 2009; Kliegel et al., 2011). Notably, across all areas of PM research, one important aspect of the experimental procedure varies across paradigms: whether the order of responses in terms of the ongoing and the PM task is predetermined or not. In other words, in some PM paradigms, a specified task order is instructed: Here, participants have to either immediately interrupt the ongoing task as soon as they encounter a PM cue and directly perform the PM action (e.g., by refraining from rating the target word and immediately hitting the PM key; Kliegel, Ramuschkat, & Martin, 2003) or make sure to respond first to the ongoing task and then immediately afterwards respond to the PM task (e.g., by first naming the picture event cue and then hitting the associated target PM key; Bisiacchi, Tarantino, & Ciccola, 2008). For an everyday life example, consider the following situation: One has to remember to post an urgent letter when passing a post office during the shopping tour. Here, a specified task order would be when the ongoing shopping tour has to be interrupted to post the letter as soon as passing the post office because it will close in two minutes and the letter has to go off that very same day. In contrast, other PM paradigms are instructed with no particular task order:

Here, participants are simply asked to remember and execute the associated PM action while also responding to the item in terms of the ongoing task and the order in which the participant carries these out is unrestricted. For example, Einstein and McDaniel (1990) instructed participants to memorize words and to press a designated key whenever a target word appeared (i.e., participants were free to execute the PM response immediately or after

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completing the ongoing task trial). In the real world, an example of a situation with no particular task order would be when one is flexible in posting the letter during the shopping tour as the post office will still be open for several hours.

Reviewing the literature regarding potential effects of task order specificity, compared to unspecified PM tasks, a specified order may produce larger PM age effects because it imposes additional demands on cognitive control to navigate the possible response options after retrieval of the PM cue. For example, inhibitory processes are needed to suppress the initial response tendency if it conflicts with the instructed order. This is likely to be

detrimental in older adults in particular, as there is evidence that inhibitory control demands negatively affect PM performance in older adults (e.g., Kliegel et al., 2008b). Likewise, Schnitzspahn, Stahl, Zeintl, Kaller, and Kliegel (2012b) showed that adult age differences in PM were explained by task-switching and inhibitory abilities. In comparison, an unspecified response situation may allow for greater freedom in the order in which one responds as it does not inherently require responding in a particular order. This lower demand on cognitive navigation of responses may make this type of PM task easier, especially for older adults. On the other hand, there is the alternative possibility that this freedom may impose response ambiguity, which could produce a response conflict between the two equal response options and hence may tax controlled attention (e.g., Goschke & Dreisbach, 2008) possibly resulting in large PM age effects. Taken together, concerning different levels of task order specificity, there is a fundamental difference in how PM is assessed. Since the moderating role of task order specificity on adult age differences in event-based PM is not clear, Study 2 set out to further investigate this issue. This extends current conceptual views in PM research that so far focused on cue detection processes to post-retrieval response management processes as possible further sources of PM age effects in later phases of the PM process - an issue that has not been examined before.

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Besides certain task characteristics that may affect age differences in PM, attempts to identify the underlying mechanisms in age deficits in laboratory PM also considered the testing situation itself. For example, Phillips et al. (2008) outlined that the higher performance of younger adults in the laboratory may be explained by younger adults’ (who are often students participating for course credit) greater experience with laboratory testing situations and with performing cognitive tests. Similarly, it is argued that laboratory PM tasks may be more stressful for older adults due to greater novelty of these testing procedures. Clearly, this might be a fundamental aspect in cognitive aging research when multiple age groups are compared. In this context, it has been suggested that contextual features of typical laboratory settings (due to greater novelty and unpredictability) evoke stress in older adults and that this may explain age-related cognitive deficits in the laboratory in general (Sindi, Fiocco, Juster, Pruessner, & Lupien, 2013). To formally examine this assumption, Sindi and colleagues implemented two laboratory testing conditions (i.e., favoring younger versus favoring older adults) and examined stress levels as well as immediate and delayed memory performance in younger and older adults. The two testing conditions differed with regard to several features (i.e., location, time of testing, age of experimenter, task type, and instruction). Compared with baseline cortisol level measured at home, cortisol concentrations for younger and older adults were on a comparable level in the testing condition favoring the elderly. However, stress level of older adults was increased in the testing condition favoring the young which represented a usual testing situation. Thus, this suggests that a traditional laboratory testing situation may indeed be more stressful for older adults. In addition, older adults’ forgetting rate in the delayed memory test was steeper in this testing condition, suggesting that stress caused by the testing environment may be a detrimental factor in the light of age deficits in cognitive

performance. This suggestion is in line with studies showing that the stress hormone cortisol negatively affects memory performance (e.g., Lee et al., 2007; Lupien et al., 1997) and more generally, that stress impairs cognitive functioning (e.g., Liston, McEwen, & Casey, 2009;

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Luethi, Meier, & Sandi, 2008; Oei, Everaerd, Elzinga, Van Well, & Bermond, 2006; Qin, Hermans, van Marle, Luo, & Fernandez, 2009) and links those effect to the laboratory test setting typically used in cognitive aging research.

In the light of the suggestions of Sindi et al. (2013), one could raise the question whether the age deficit in laboratory PM performance is (at least partly) attributable to increased stress levels in older adults evoked by the nature of the laboratory testing situation per se. First evidence that stress can influence PM performance in the laboratory comes from a study by Nater et al. (2006) on younger adults only showing that stress affected (though in this case enhanced) performance in a time-based PM task. Moreover, studies focusing on naturalistic PM suggest that perceived stress is negatively associated with PM performance (e.g., Schnitzspahn et al., 2011). So far, no study has directly tested the potential of laboratory testing situations for evoking stress and its possible effects on age differences in laboratory PM. Therefore, Study 3 set out to further explore the role of stress in laboratory PM in more detail.

2.6 Adult age differences in PM - A cognitive aging perspective

From a cognitive aging perspective, studying adult age differences in PM can be seen as an especially revealing topic. This is because prospective remembering is characterized by the dynamic interplay of different cognitive functions such as memory and executive

functions (Kliegel et al., 2011). Hence, investigating PM and aging allows studying age effects in the involved cognitive abilities and their interaction in a single situation. It is well- documented that performance in short-term, episodic, and working memory as well as in executive functions such as inhibition and task-switching (all of which are involved in the PM process) declines in aging (e.g., Bélanger, Belleville, & Gauthier, 2010; Bopp & Verhaeghen, 2005; Borella, Carretti, & De Beni, 2008; Mayr & Liebscher, 2001; Salthouse et al., 2003;

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Schnitzspahn et al., 2012b; Verhaeghen & Basak, 2005). Thus, it seems plausible that age deficits in laboratory PM are (at least partly) attributable to age deficits in cognitive functions that are involved in the PM process. In line with this assumption, several studies showed that age deficits in laboratory PM are associated with age deficits in certain cognitive measures, particularly working memory and cognitive control (e.g., Cherry & LeCompte, 1999; Reese &

Cherry, 2002; Salthouse, Berish, & Siedlecki, 2004; Schnitzspahn et al., 2012b; West &

Craik, 2001). However, although a substantial proportion of the age-related variance in PM is shared with other cognitive constructs, there is evidence that PM is partially independent of age-related differences in those variables (e.g., Salthouse et al., 2004; Zeintl et al., 2007).

Moreover, these studies also showed that PM is related to, but not identical with general cognitive abilities and other cognitive constructs such as processing speed, working memory, and retrospective memory. This suggests, although several cognitive functions are involved in the process of prospective remembering, a substantial amount of individual and age-related variance in PM is not explained by these cognitive measures alone. Thus, it is an interesting question which other abilities are involved in prospective remembering, how they determine PM age differences, and/or whether the interaction per se might constitute a novel,

measurable construct.

Moreover, although many cognitive abilities act together in the process of prospective remembering, the age decline in these underlying functions does not inevitably result in a PM age deficit: On the contrary, the age benefit in naturalistic PM tasks shows that there are situations in which older adults are able to successfully compensate cognitive age deficits to maintain a good performance. The fact that cognitive limitations can be compensated in certain domains of cognitive behavior such as the fulfillment of delayed intentions (despite Craik’s, 1986, proposal of a general age deficit in PM) is a fascinating pattern within the broader field of cognitive aging. Besides its conceptual importance, this is also relevant from an applied perspective to identify helpful strategies to enhance everyday cognitive

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performance, particularly in older adults. Moreover, in contrast to prospective remembering, in retrospective memory age deficits are found both in laboratory and naturalistic tasks (e.g., Light, 1991). Hence, the age benefit in naturalistic PM seems a unique pattern in the broader field of cognitive aging, further underlines the distinctiveness of the PM construct, and may stimulate the need for research targeting the origin of the age PM paradox even more.

One interesting question in this context is whether different factors contribute to the PM age deficit in the laboratory versus the age benefit in the field. Hence, it is important to disentangle the underlying mechanisms of the age PM paradox in both settings to better understand adult age differences in prospective remembering. It would be of further relevance to know whether understanding the mechanisms in one setting could give us a better

comprehension of the effects in the other one. This means whether research on naturalistic PM can benefit from laboratory findings and whether factors that are identified in the field can provide further important indications for laboratory PM research. Finally, in a broader perspective, it will be of interest to know whether the comprehension of those mechanisms in PM might then provide deeper insights into adult age differences in other cognitive domains and how PM research helps us to better understand cognitive aging. The present thesis set out to at least partially address these questions.

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3. Research aims and hypotheses

The overall aim of the present thesis was to systematically investigate potential key mechanisms underlying adult age differences in PM performance in the laboratory and the naturalistic setting. For this purpose, three research questions will be discussed in detail in the following sections. The first concerned whether the age benefit found in naturalistic

experimenter-given PM tasks can be confirmed in real life PM with tasks naturally occurring in everyday life. Moreover, a further aim in this context was to evaluate the role of three often suggested mechanisms, which are motivational aspects, use of reminders, and everyday stress in age-related real life PM performance. The second research question aimed to clarify whether different levels of task order specificity moderate age effects in event-based PM.

Finally, the third research question concerned the influence of stress in the context of the laboratory testing situation on age-related PM performance.

3.1 Does personal task importance, use of reminders, and everyday stress affect adult age differences in everyday PM? (Study 1)

As outlined above, the finding of adult age benefits in naturalistic PM is well- established (Henry et al., 2004). However, research has focused on experimenter-given PM tasks and up to now, results regarding age differences in real life PM are sparse,

heterogeneous, and so far inconclusive. Moreover, since the few studies available focused on medication adherence as the critical intention, there is no study so far examining adult age differences in everyday PM performance in a variety of tasks that naturally occur in everyday life. Taken together, it remains unclear whether the age benefit generalizes to everyday PM.

To clarify this open issue in PM research, the major aim of Study 1 was to examine whether PM performance of younger and older adults differs in real life PM tasks. For this purpose, fulfillment of planned intentions over five consecutive days was assessed in younger and

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older adults with a telephone-diary procedure. The respective intentions were those that naturally occurred in participants’ everyday life and represented a large variety of tasks.

A further aim of Study 1 was to investigate potential factors that may affect age differences in everyday PM. For this purpose, three often debated explanations for age benefits in naturalistic PM, which are motivational aspects, use of reminders, and everyday stress (Phillips et al., 2008), were chosen. Regarding the role of motivation, in Study 1, perceived task importance for each individual intention was assessed and it was evaluated whether the level of task importance was associated with the fulfillment of these intentions and whether task importance moderated PM age differences. Based on the findings of Marsh et al. (1998) and Aberle et al. (2010) suggesting that important tasks raise the motivation for correct fulfillment in younger adults and the findings of Schnitzspahn et al. (2011) that the superiority of older adults was attributable to higher motivational level, it was predicted that generally high levels of PM accuracy for very important intentions should emerge in both age groups and that age benefits should only - or more pronouncedly - occur in less important intentions. Concerning the influence of use of reminders and everyday stress, given the heterogeneous and so far inconclusive results in the literature, no directional predictions were formed. Taken together, Study 1 aimed to clarify the role of these three very often discussed mechanisms.

3.2 Does task order specificity influence adult age differences in event-based laboratory PM? (Study 2)

In the light of multiple phases and components of PM, the multi process model (Kliegel et al., 2002, 2011) and the multiprocess framework of event-based PM (McDaniel &

Einstein, 2000) provide important insights into which mechanisms may contribute to age differences in PM. Up to now, the major focus in research on event-based PM was on factors

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determining processes prior to PM retrieval such as more or less demands on strategic

monitoring to detect the PM cue. However, there is only little known about further sources of PM age effects in later phases of the PM process. Therefore, the aim of Study 2 was to extend current conceptual views in PM research that so far focused on pre-retrieval factors (such as cue focality) to later phases in the PM process when participants must navigate between completing the PM and ongoing task. A key factor in this context could be task order specificity - a factor that so far has not been studied. Therefore, Study 2 aimed to clarify the role of task order specificity as a potential moderator of PM age effects. For this purpose, a meta-analysis based on the available body of literature on adult age differences in event-based laboratory PM was conducted to test whether PM age effects differed between specified and unspecified PM tasks, as well as whether these differences varied by cue focality. Given the heterogeneous predictions one could draw from reviewing the literature, no directional predictions were formed.

3.3 Are adult age differences in laboratory PM attributable to age differences in stress level? (Study 3)

To explain age-related cognitive deficits in the laboratory in general, one recently discussed aspect is that the laboratory testing situation per se may be more stressful for older adults, thereby reducing their performance (Sindi et al., 2013). This suggestion nicely fits into the debate of which factors contribute to the observed age deficit in laboratory PM. As no one has ever examined this aspect for PM, Study 3 set out to examine whether the robust age deficits obtained in laboratory PM may be linked to age differences in stress levels in the laboratory. For this purpose, younger and older adults performed a time-based PM task. The aim was to examine whether the age deficit in laboratory PM can be confirmed with present data, to evaluate whether the typical laboratory assessment of PM evokes higher stress levels

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in older compared to younger adults, and to test whether stress levels were associated with age-related PM performance. In addition, as a novel exploration in this context, half of participants were randomized in a condition where they completed a relaxation intervention before assessment of PM. The aim was to examine whether this intervention can successfully reduce stress level in the laboratory and whether it has an effect on PM performance in general and/or PM age differences. In particular, it was hypothesized that the age deficit in laboratory PM can be confirmed with present data. Second, based on findings from Sindi et al. and from stress effects on cognitive functioning in general, it was predicted that compared to younger adults, stress levels of older participants are higher during the experiment and that stress level is negatively associated with PM performance. Moreover, it was expected that the relaxation intervention successfully reduces stress levels. Finally, it was hypothesized that the relaxation supports PM performance in general and furthermore decreases the age deficit.

Taken together, Study 3 aimed to extend the literature by exploring the role of stress in laboratory PM in more detail, thereby clarifying an open issue in the ongoing conceptual debate of underlying mechanisms in adult age differences in prospective remembering.

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4. Study 1: Investigating the impact of task importance,

reminders, and stress on adult age differences in everyday PM

4.1 Abstract

The present diary study examined everyday PM tasks in 20 younger and 19 older adults and explored the role of personal task importance, use of reminders, and everyday stress as possible correlates of age-related PM performance in everyday life. Results revealed an age benefit in everyday PM tasks. In addition, task importance was identified as a critical moderator of age-related PM performance. More frequent use of reminders and lower levels of stress were associated with better PM performance in general but did not contribute to age- related PM performance. Exploring further possible correlates of PM revealed that the strategy to reprioritize initially planned intentions was associated with age benefits in everyday PM. Results suggest that the age-related benefit observed in experimenter-given tasks transfers to everyday PM and varies in dependence of motivational and cognitive factors. Implications for theoretical models of PM and aging are discussed.1

4.2 Introduction

Remembering to implement planned intentions is referred to as PM (Zeintl, Kliegel, &

Hofer, 2007). Everyday examples of PM are remembering to switch off the stove after cooking, paying utility bills in time, or remembering to take medication according to schedule.

The vast majority of studies on age-related PM performance has been carried out in the laboratory (see Kliegel, Jäger, & Phillips, 2008c, for a recent meta-analysis) and used tasks like remembering to stop a clock seven minutes after the beginning of a trial (Rendell &

1 Concerning the reproduction of the three study articles, in some few cases, minor changes were made to the original language to maintain a coherent wording across the present thesis.

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Thomson, 1999) or remembering to press a pre-specified key when the PM target cue appears on the computer screen (Einstein & McDaniel, 1990). In their meta-analytic review, Henry, MacLeod, Phillips, and Crawford (2004) concluded that younger adults generally perform better than older adults in those laboratory-type PM tasks.

There are also - much fewer - studies applying PM tasks in a naturalistic setting (i.e., in the everyday life of the participant), such as asking participants to telephone the

experimenter at a specific time over two weeks (Moscovitch, 1982), to mail postcards to the experimenter (Patton & Meit, 1993), or to periodically log the time on an electronic organizer (Rendell & Thomson, 1993, 1999). For those naturalistic settings, Henry et al. (2004) showed that - somewhat surprisingly - older adults tend to outperform younger adults. Reviewing the evidence on this age benefit, Phillips, Henry, and Martin (2008) have recently stressed the urgent need for research on naturalistic PM tasks with high ecological validity. They differentiate between “real” naturalistic PM tasks which occur in everyday life without

interference of an experimenter (i.e., actual intentions participants make, try to remember, and fulfill at specific times or events) and more or less artificial tasks externally provided by an experimenter like calling or posting messages at pre-specified times. So far, studies exploring age benefits in naturalistic PM tasks have focused on the second task type and there is

surprisingly little known about age-related PM in the “real” naturalistic task type. Therefore, the first aim of the present study was to explore whether the age benefit found in previous naturalistic PM studies using experimenter-given PM tasks generalizes to “real” PM tasks occurring in the everyday life of the participants. For this purpose, in terms of methodology, the present study adopted a diary procedure.

Furthermore, the second aim of the present study was to go beyond the description of possible age differences in real life PM tasks and test for mechanisms underlying the

performance. As outlined above, there is little evidence concerning age-related PM in real life tasks. Thus, we revert to mechanisms that have been suggested to underlie the age benefit in

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naturalistic PM tasks. Further, a mechanism suggested as influential for real life PM performance in a study from Marsh, Hicks, and Landau (1998) focusing on younger adults only will be taken up.

Specifically, Marsh et al.’s (1998) data suggest that younger adults implemented more important real life intentions more frequently than less important ones. If one assumes that important tasks raise the motivation for correct fulfillment, this finding is in line with research on the role of motivation for the age benefit in naturalistic PM tasks. In a first study directly examining the motivational angle in experimenter-given naturalistic PM tasks in younger and older adults, Aberle, Rendell, Rose, McDaniel, and Kliegel (2010) used a monetary incentive to manipulate motivation. Results show that providing a monetary incentive improved only younger adults, who then reached the level of performance of older adults. Further evidence comes from a recent study showing that higher a priori ratings of motivation to perform an experimenter-given naturalistic PM task in the older adults were correlated to their subsequent higher PM performance (Schnitzspahn, Ihle, Henry, Rendell, & Kliegel, 2011).

In the light of these results, the present study explored personal importance of real life intentions as one possible moderator of age-related performance in those tasks. Our

predictions were based on considerations of Aberle et al.’s (2010) and Schnitzspahn et al.’s (2011) results on experimenter-given naturalistic PM performance in younger and older adults as well as Marsh et al.’s (1998) data on younger adults’ real life PM performance. Therefore, we predicted generally high levels of PM accuracy for very important intentions in both age groups and that age benefits should only or more pronouncedly occur in less important intentions.

Another explanation for age benefits in naturalistic PM tasks that was adopted and tested for age-related PM performance in real life tasks in the present study is that older adults use more reminders to cue PM retrieval (Phillips et al., 2008). Available results concerning the use of reminders in younger and older adults in naturalistic PM tasks are however mixed

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(Maylor, 1996b; Patton & Meit, 1993): In some studies older adults reported using more reminders (e.g., Jackson, Bogers, & Kerstholt, 1988), whereas in other studies younger adults reported more frequent use of reminders (e.g., Dobbs & Rule, 1987; Rendell & Thompson, 1999). Rendell and Craik (2000) instructed participants not to use reminders in a naturalistic PM task. In a post-task debriefing interview, both younger and older participants reported generally low use of reminder strategies, whereas an age benefit in PM performance was still present. Moreover, Rendell and Thompson (1999) found that providing both age groups an alarm in one condition and in another condition with instructions and the opportunity to link cues from their environment to the prospective action did not reduce the magnitude of the older adults’ superiority compared to younger adults on a naturalistic PM task. In line with these results Phillips et al. (2008) concluded there is remarkably little evidence supporting the popular idea that age-related benefits on PM in daily lives are caused by increased use of reminders. On the other hand, so far, PM tasks used in naturalistic studies mostly were artificial, experimenter-generated tasks and not intentions occurring in participants’ real life.

Thus, up to now, it is in fact unclear as to whether an effect of reminder use may emerge in everyday life intentions. Here, participants, especially older adults, may be more aware of their need for using reminders. Conceptually, such knowledge of successfully using supportive strategies can be considered as one component of metacognitive awareness.

Importantly, in a recent study, Schnitzspahn et al. (2011) revealed better metacognitive performance predictions in older adults regarding their naturalistic PM performance in an experimenter-given PM task. Moreover, an association of metacognitive judgments with age benefits in the naturalistic PM task was observed. The present study set out to further explore this issue, but given the heterogeneity of previous results on reminder and age-related PM performance, no straightforward predictions were formed.

A third explanation for age benefits in naturalistic PM performance that was tested in the current study with regard to its validity for real life PM tasks is that older adults may be

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