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

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

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,

& 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

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.

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;

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.