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Age Differences in Prospective Memory: A Further Evaluation of the Executive Framework

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Title: Age Differences in Prospective Memory: A Further Evaluation of the Executive Framework
Language: English
Authors: Zhao, Xin, Fu, Junjun, Ma, Xiaofeng, Maes, Joseph H. R.
Source: Journal of Cognition and Development. 2019 20(5):680-701.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 22
Publication Date: 2019
Document Type: Journal Articles
Reports - Research
Descriptors: Age Differences, Memory, Executive Function, Age Groups, Children, Adolescents, Adults, Task Analysis, Interference (Learning), Responses, Inhibition, Predictor Variables, Performance, Foreign Countries, Color, Reaction Time, Visual Stimuli
Geographic Terms: China
Assessment and Survey Identifiers: Stroop Color Word Test
DOI: 10.1080/15248372.2019.1648268
ISSN: 1524-8372
Abstract: According to the executive framework of prospective memory (PM), age-related differences in PM performance are mediated by age-related differences in executive functioning (EF). The present study further explored this framework by examining which specific components of EF are associated with PM differences between and within three age groups. A group of children (7-9 years; N = 108), adolescents (12-14 years; N = 112), and adults (17-23 years; N = 106) performed focal- and non-focal event-based PM (EBPM) tasks, a time-based PM (TBPM) task, and tasks measuring EF components. Differences between age groups in focal EBPM, non-focal EBPM, and TBPM performance were mediated by, respectively, differences in interference control and response inhibition, performance on the ongoing task, and differences in working memory and response inhibition. However, within-age group analyses only revealed WM updating as significant predictor of TBPM performance in the adolescent group. These results support and further qualify the executive framework of PM. The differences in outcome dependent on the examined age range might be important for explaining mixed results of previous studies regarding the precise EF components underlying age-related PM task performance differences.
Abstractor: As Provided
Entry Date: 2019
Accession Number: EJ1233912
Database: ERIC
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  Value: <anid>AN0139548399;7m701oct.19;2019Nov09.05:17;v2.2.500</anid> <title id="AN0139548399-1">Age Differences in Prospective Memory: A Further Evaluation of the Executive Framework </title> <p>According to the executive framework of prospective memory (PM), age-related differences in PM performance are mediated by age-related differences in executive functioning (EF). The present study further explored this framework by examining which specific components of EF are associated with PM differences between and within three age groups. A group of children (7–9 years; N = 108), adolescents (12–14 years; N = 112), and adults (17–23 years; N = 106) performed focal- and non-focal event-based PM (EBPM) tasks, a time-based PM (TBPM) task, and tasks measuring EF components. Differences between age groups in focal EBPM, non-focal EBPM, and TBPM performance were mediated by, respectively, differences in interference control and response inhibition, performance on the ongoing task, and differences in working memory and response inhibition. However, within-age group analyses only revealed WM updating as significant predictor of TBPM performance in the adolescent group. These results support and further qualify the executive framework of PM. The differences in outcome dependent on the examined age range might be important for explaining mixed results of previous studies regarding the precise EF components underlying age-related PM task performance differences.</p> <p>Prospective memory (PM) refers to the ability to realize a delayed intention by "remembering to remember" to perform a future action (Ellis, [<reflink idref="bib14" id="ref1">14</reflink>]). PM is crucial for many daily-life tasks and involves different phases, specifically, the formation, retention, initiation, and execution of the intention (Kliegel, Martin, McDaniel, & Einstein, [<reflink idref="bib22" id="ref2">22</reflink>]). PM has a retrospective component, remembering <emph>what</emph> specific action to perform, next to a prospective component, remembering <emph>that</emph> a specific action must be performed (Einstein & McDaniel, [<reflink idref="bib13" id="ref3">13</reflink>]). In addition, a distinction can be made between event-based PM (EBPM) and time-based PM (TBPM), which refers to the type of cue that triggers execution of the intended action (Brandimonte, Einstein, & McDaniel, [<reflink idref="bib5" id="ref4">5</reflink>]). In EBPM, this concerns an external cue, such as when remembering to buy bread upon passing a bakery. In TBPM, the intention has to be realized at a specific time or period of time, such as to remember to take medicine in time.</p> <hd id="AN0139548399-2">PM and executive functions</hd> <p>According to an influential theory in the field, the multiprocess theory, PM tasks may require relatively automatic or strategic processes, depending, among other factors, on features of the task (McDaniel & Einstein, [<reflink idref="bib32" id="ref5">32</reflink>]). For example, an EBPM task involving a salient external cue that already is in the focus of attention given the ongoing task (OT) that one is engaged in and that one has to interrupt to perform the intended action (a <emph>focal</emph> EBPM task) may require relatively few cognitive resources. Instead, an EBPM task involving a memory cue that is outside of one's focus of attention while performing a relatively engaging OT (a <emph>non-focal</emph> EBPM task), and a TBPM in which there is no external cue at all and the initiation of the intention must be self-generated, demand much more strategic processes. Regarding the nature of these strategic processes, another dominant view is that they concern executive functions (EFs; e.g., Kliegel, Altgassen, Hering, & Rose, [<reflink idref="bib20" id="ref6">20</reflink>]). EFs refer to effortful, higher-order cognitive processes that control lower-order processes, enabling planful, goal-directed behavior (Diamond, [<reflink idref="bib11" id="ref7">11</reflink>]). EFs consist of more basic components, specifically working memory (WM) monitoring and updating, inhibition, and task-switching (Miyake et al., [<reflink idref="bib33" id="ref8">33</reflink>]). One or more of these components are assumed to play a role in the different phases of PM (Kliegel et al., [<reflink idref="bib20" id="ref9">20</reflink>]). Specifically, formation of the intention may depend on planning abilities, in turn requiring WM updating, for example, in case of the updating of OT requirements with PM requirements. Usually, during the PM retention phase, an alternative activity is performed, the OT and WM resources might also be challenged especially when this task involves a high maintenance load (Ballhausen, Schnitzspahn, Horn, & Kliegel, [<reflink idref="bib2" id="ref10">2</reflink>]). The intention initiation phase requires the monitoring for event and/or time cues (WM monitoring and updating). Finally, the actual execution of the intention in the final phase requires the individual to inhibit performing the OT and to switch to the PM task.</p> <hd id="AN0139548399-3">Age differences in PM and association with EF development</hd> <p>Studies examining the development of PM capacity across the lifespan have revealed an inverted U-shaped function (e.g., Kliegel, Mackinlay, & Jäger, [<reflink idref="bib21" id="ref11">21</reflink>]; Zimmermann & Meier, [<reflink idref="bib47" id="ref12">47</reflink>]; Zöllig et al., [<reflink idref="bib48" id="ref13">48</reflink>]). Given the presumed role of EFs in PM, and the fact that EFs also show a clear developmental trajectory (which may differ for the EF components, e.g., Best, Miller, & Jones, [<reflink idref="bib4" id="ref14">4</reflink>]; Diamond, [<reflink idref="bib11" id="ref15">11</reflink>]; Huizinga, Dolan, & Van der Molen, [<reflink idref="bib16" id="ref16">16</reflink>]; Lee, Bull, & Ho, [<reflink idref="bib24" id="ref17">24</reflink>]), a plausible hypothesis is that age-related differences in PM are mediated by age-related differences in EFs (Mahy, Moses, & Kliegel, [<reflink idref="bib28" id="ref18">28</reflink>]). This hypothesis has been largely supported by previous research, although the results are mixed as to the exact EF component(s) that may explain the age-related PM differences. These mixed results are likely due to the use of different PM tasks (e.g., focal or non-focal EBPM, or TBPM tasks; differences in OT requirements), or differences in the examined age groups. The latter may, for example, imply that in some studies, particular EF components may already have been fully developed in all groups included in the study, precluding any potential of these EFs to explain age-related PM performance differences. An additional factor may be the use of different tests to measure the different EF components. These tests may differ in the exact process(es) that they measure and may be more or less process pure.</p> <p>Previous studies used a variety of PM tasks, such as EBPM, TBPM, or both. They also largely differed in the type of EFs studied and/or in the EFs found to explain age differences in PM performance, such as WM updating, inhibition, switching, planning, and/or a combination of more than one EF (e.g., see, Kerns, [<reflink idref="bib18" id="ref19">18</reflink>]; Kretschmer, Voigt, Friedrich, Pfeiffer, & Kliegel, [<reflink idref="bib23" id="ref20">23</reflink>]; Mackinlay, Kliegel, & Mäntylä, [<reflink idref="bib26" id="ref21">26</reflink>]; Mäntylä, Grazia Carelli, & Forman, [<reflink idref="bib30" id="ref22">30</reflink>]; Mahy & Moses, [<reflink idref="bib27" id="ref23">27</reflink>]; Mahy, Moses, & Kliegel, [<reflink idref="bib29" id="ref24">29</reflink>]; Shum, Cross, Ford, & Ownsworth, [<reflink idref="bib38" id="ref25">38</reflink>]; Voigt et al., [<reflink idref="bib41" id="ref26">41</reflink>]; Ward, Shum, McKinlay, Baker-Tweney, & Wallace, [<reflink idref="bib42" id="ref27">42</reflink>]; Yang, Chan, & Shum, [<reflink idref="bib43" id="ref28">43</reflink>], for studies examining children within the age range of 4−14 years; Azzopardi, Juhel, & Auffray, [<reflink idref="bib1" id="ref29">1</reflink>]; Gonneaud et al., [<reflink idref="bib15" id="ref30">15</reflink>]; Martin, Kliegel, & McDaniel, [<reflink idref="bib31" id="ref31">31</reflink>]; Schnitzspahn, Stahl, Zeintl, Kaller, & Kliegel, [<reflink idref="bib37" id="ref32">37</reflink>]; Zuber, Kliegel, & Ihle, [<reflink idref="bib49" id="ref33">49</reflink>], for studies covering the age range of 18−95 years). No clear pattern of results emerges from these studies.</p> <p>Although most of these studies had at least one measure for each of the three basic EFs, some only examined WM updating or switching (Azzopardi et al., [<reflink idref="bib1" id="ref34">1</reflink>]; Voigt et al., [<reflink idref="bib41" id="ref35">41</reflink>]). Moreover, it is questionable whether the tasks used to measure the different EFs are all process pure and measure the same constructs (e.g., using the n-back, backward digit-span, visuospatial matrix monitoring, and running memory tasks to measure WM, anti-saccade, go/no-go, stop-signal, Stroop, Simon, and random letter generation tasks to tap inhibition, and category classification, trail-making, card-sorting, and category fluency tests to assess shifting ability). For example, inhibition is a broad concept that entails several different types, among which are interference control and behavioral inhibition. These types are subserved by distinct neuronal systems (Nigg, [<reflink idref="bib34" id="ref36">34</reflink>]; Stahl et al., [<reflink idref="bib39" id="ref37">39</reflink>]). Concerning the issue of process (im)pureness, tasks like the random letter generation task, used to assess behavioral inhibition (Gonneaud et al., [<reflink idref="bib15" id="ref38">15</reflink>]), and the card-sorting and fluency tests, used to measure shifting, likely involve other EF components (such as WM) and associated neural structures (e.g., Buchsbaum, Greer, Chang, & Berman, [<reflink idref="bib7" id="ref39">7</reflink>]; Huizinga et al., [<reflink idref="bib16" id="ref40">16</reflink>]; Miyake et al., [<reflink idref="bib33" id="ref41">33</reflink>]; Oomens, Maes, Hasselman, & Egger, [<reflink idref="bib35" id="ref42">35</reflink>]). An final feature of the previous PM studies is that they differ in the age ranges examined, with a somewhat underrepresentation of young teenagers (approximately 12−16 years of age).</p> <p>A general, tentative conclusion that could be drawn from these previous studies is that, across age ranges and types of PM examined, WM updating is one of the most frequently found EF component acting as a mediator in the association between age and PM performance. This is in line with evidence suggesting that WM updating is involved in most PM phases and has the most prolonged developmental trajectory, with no further improvements occurring in late adolescence or young adulthood (also depending on the complexity of the task; e.g., Best et al., [<reflink idref="bib4" id="ref43">4</reflink>]; Huizinga et al., [<reflink idref="bib16" id="ref44">16</reflink>]). Inhibition is the next EF component relatively frequently found to have a mediating role. Although this component is sometimes claimed to reach maturity earlier than is the case for WM updating and switching (Diamond, Davidson, Amso, & Anderson, [<reflink idref="bib12" id="ref45">12</reflink>]), inhibition, as measured by relatively process-pure tasks such as the go/no-go and flanker tasks, has been found to reach mature levels relatively lately, up to young adulthood (see Best & Miller, [<reflink idref="bib3" id="ref46">3</reflink>], for a review). Moreover, both interference control and response inhibition are strongly linked to WM (Tiego, Testa, Bellgrove, Pantelis, & Whittle, [<reflink idref="bib40" id="ref47">40</reflink>]). Finally, from those studies that did include a switching ability measure, only a small minority of studies found this aspect of EF to have a mediating role, and this role may perhaps be limited to non-focal EBPM and TBPM tasks (see also below).</p> <hd id="AN0139548399-4">Present study</hd> <p>Given the limitations of previous research, we aimed to further investigate age-related differences in PM and to assess to what extent these are mediated by specific EFs. In our study, we focussed on three age groups, together covering the ages 7−23 years, including the age group of 12 to 14-year-olds that had been somewhat underrepresented in previous research. Each participant performed the same three PM tasks, a focal and non-focal EBPM task and a TBPM task, to assess to what extent age differences and possible mediation effects generalize across types of PM task. Moreover, we used a battery of common and relatively process-pure EF tasks that allowed us to cover the three main EF components of WM (both updating and more simple WM maintenance capacity processes), inhibition (both response inhibition and interference control), and switching. From the inhibition tasks, we also derived a measure of general response speed that was also assessed as potential predictor or mediator of PM task performance. We hypothesized that WM would be the most consistent and strongest mediator of age-related PM task performance differences for at least the (more demanding) non-focal EBPM and TBPM tasks. As indicated above, WM updating is assumed to play a role in most of the different stages of PM and full maturation of WM is assumed to not have been reached yet in the younger participants. The next function expected to play an important role is inhibition, specifically interference control. We hypothesized this function to be especially involved in focal EBPM task performance. During the OT of a focal EBPM task, attention is fully directed to the very same stimuli that partly also constitute the PM cue(s). Upon encountering a PM cue, the participant must suppress attention to the OT-related aspects of the stimulus (i.e., stimulus feature and related response) to perform the PM task (see Zuber et al., [<reflink idref="bib49" id="ref48">49</reflink>], for a similar line of reasoning and supporting empirical evidence using a sample including older adults). Concerning the mediating potential of the switching factor, one may expect this factor to play a larger role in the more cognitively demanding non-focal EBPM and TBPM tasks, and less so in focal EBPM tasks. The former two tasks require a more active monitoring of the external or internal environment for PM cues, in turn demanding a frequent shift of attention away from, and back to, the OT (see also Zuber et al., [<reflink idref="bib49" id="ref49">49</reflink>]).</p> <p>In addition to analyses directed at explaining differences in PM performance between age groups, we also performed corresponding analyses for each age group separately. The reason for this is that it is at least theoretically possible that a given EF can significantly explain between but not within-age-group PM performance differences. For example, suppose that the developmental trajectory of a given EF that is critically involved in the PM task under investigation is such that it is not much developed in the examined youngest age group, intermediately developed in the second-youngest age group, and fully developed in the oldest age group. In this case, this EF may significantly explain between-age-group PM performance differences. However, because of floor and ceiling effects with respect to individual differences in that EF, this may not be the case when performing within-age group analyses targeting the youngest and oldest age groups.</p> <hd id="AN0139548399-5">Method</hd> <p></p> <hd id="AN0139548399-6">Participants</hd> <p>The original sample consisted of 120 children, 120 adolescents, and 120 university students. Most of the participants were from the Han population (95%, 90%, and 88% of the children, adolescents, and adults, respectively). The remaining participants were from minority populations, such as Hui, Zang, Yi, or Dongxiang Chinese. All children and adolescents were recruited from schools located in Lanzhou city, China, after having received permission from the educational bureau of Lanzhou city. The students were recruited from Northwest Normal University with the help of ads. From the children and students that were approached, approximately 20–30% did not wish to participate; for the adolescents, this rate was about 10%. Twelve children, 8 adolescents, and 14 students did not complete all tasks and their data were removed from the data set. The mean age of the remaining 108 children (62 girls; 46 boys) was <emph>M</emph> = 8.07 years (<emph>SD</emph>= 0.59; range: 7–9 years), of the remaining 112 adolescents (63 women) <emph>M</emph> = 13.35 years (<emph>SD</emph> = 0.75; range: 12–14 years), and of the 106 students (55 women) <emph>M</emph> = 19.66 years (<emph>SD</emph> = 1.17; range: 17–23 years). All participants had normal or corrected-to-normal vision, were not color blind, had no known history of psychiatric or neurological disease (assessed through (self-)report by the adults or the children's and adolescents' caretakers and teachers), and had not participated in a similar study before. All student participants or primary caretakers of the children and adolescents signed informed consent forms. All individuals participated voluntarily and received small gifts, such as pencils and paper notebooks, upon completion of the tasks. The study was approved by the Ethics Committee for Psychological Experiments of Northwest Normal University and in accordance with the guidelines described in the Declaration of Helsinki. All experimental manipulations were performed in accordance with the approved guidelines.</p> <hd id="AN0139548399-7">Materials</hd> <p></p> <hd id="AN0139548399-8">Prospective memory tasks</hd> <p></p> <hd id="AN0139548399-9">EBPM task</hd> <p>This task was adapted after the PM task used by Zuber et al. ([<reflink idref="bib49" id="ref50">49</reflink>]). The OT consisted of a 2-back WM-updating task. Briefly, white capital letters (A, D, F, H, K, M, O, R, T, and Z) were serially presented against a black background, in the same pseudo-randomized order for each participant. Each letter was surrounded by its own colored frame (e.g., red, yellow, or pink). Participants had to decide whether the current letter was the same as the letter presented two trials back (OT). The participant could respond by either pressing the "L" key for "yes" or the "S" key for "no". Trial Block 1 was initiated after a practice phase. This block only consisted of the OT in which 13 of the 50 stimuli were 2-back "hits". Performance on this trial block, expressed as the proportion of trials with a correct response (correctly identified 2-back "hits" and "non hits") was used as measure of WM-updating capacity (see below). Trial Blocks 2 and 3 each consisted of 50 OT trials, with 11 2-back hit items. Embedded within these OT trials were four focal and four non-focal trials. For about one half of the participants, the focal trials were presented in Block 2, and the non-focal trials in Block 3; the reverse mapping of trial type to trial block was in effect for the remaining participants. On focal trials, which were indicated by the appearance of the letters A and D in the OT, the participant had to press the space bar rather than to respond according to the OT. On non-focal cue trials, the participant was required to respond by pressing the space bar upon seeing a letter that was surrounded by either a red or yellow frame (which were always the letters A and D, respectively). Focal and non-focal cues were never 2-back hit stimuli. The main dependent measures from this task were the proportion of correct EBPM responses (correct space bar responses) on the focal and non-focal cue trials (see Zuber et al., [<reflink idref="bib49" id="ref51">49</reflink>], for further details).</p> <hd id="AN0139548399-10">TBPM task</hd> <p>TBPM was assessed using a task modeled after that described by Cona, Arcara, Tarantino, and Bisiacchi ([<reflink idref="bib9" id="ref52">9</reflink>]). Strings of five capital letters were displayed in a pseudo-randomized order. The first, third, and fifth letters were always identical. The letters in the second and fourth position, the target letters, were either identical (e.g., DFDFD) or not (e.g., DFDGD). The participant had to press "D" if the target letters were identical, and "K" if they were not. During the task, the participant had to estimate the duration of the experiment since its onset in steps of 1 min (in the practice phase of the task) or 5 min (in the experimental phase). After reaching a target time, the participant was required to press the "L" key. The participant had to try to make this response as close to the target time as possible. To help estimate elapsed time, the participant could press the "S" key. This caused the appearance of a digital clock for 2 s, displaying the time since the start of the experiment. The experiment began with a practice block of 36 trials, which was repeated until the participant reached an accuracy level of more than 80%. The target times in this block were 1 and 2 min. A correct PM response was defined as an "L" response that occurred within 5 s of the target time. A trial started by presenting a fixation cross for 800 ms, followed by a 100-ms empty screen. Next, a string was displayed until the participant responded, with a maximum of 1600 ms, followed by a 1000-ms blank screen. During the next experimental trials, which were presented in 10 blocks of 36 trials each, the target times were 5, 10, 15, 20, and 25 min (across all blocks). The main dependent measure was the proportion of target-time "trials" with a correct response.</p> <hd id="AN0139548399-11">EF tasks</hd> <p>The EF tasks are briefly described below; for further details see Zhao, Chen, and Maes ([<reflink idref="bib45" id="ref53">45</reflink>]) and Zhao, Wang, and Maes ([<reflink idref="bib46" id="ref54">46</reflink>]). In addition to these tasks, the participants also performed an IQ test but the corresponding data were not used because of the use of different tests for the age groups, complicating a direct comparison.</p> <hd id="AN0139548399-12">Running memory tasks (RM)</hd> <p>These tasks were used as WM measure. In each task, series of single digits ranging from 0 to 9 were consecutively and randomly displayed. The length of the series was 5, 7, 9, or 11 digits. Each series length was presented six times. The order of presentation of the different series lengths was random. The participant had to sequentially remember the last three presented digits. A blank bar was presented after the final digit of the current series, indicating that the participant had to enter the last three digits using the keyboard. There were two task versions that differed in the presentation time of each digit, which was 1750 ms in the first task (hereafter: RM-long task) and 750 ms in the second task (hereafter: RM-short). The RM-long task was held to tap more into WM updating than the RM-short task (see Bunting, Cowan, & Saults, [<reflink idref="bib8" id="ref55">8</reflink>]; but see Broadway & Engle, [<reflink idref="bib6" id="ref56">6</reflink>]). A relatively long presentation time encourages the participant to actively monitor and update the incoming digits. A short presentation time prevents the participant from using this type of active processing and instead encourages recall from a passive storage. Evidence for this suggestion was obtained by correlation analyses using the Block 1 2-back task performance of the EBPM task (see below). For each task, one point was assigned for each correct digit put into the correct serial position. The number of points was converted to proportion correct responses and used as dependent measure in the analyses.</p> <hd id="AN0139548399-13">2-back (WM) task</hd> <p>As a second WM-updating task, we used trial Block 1 from the EBPM task described above. This block consisted of the OT in which 13 of the 50 stimuli were 2-back hit trials. The dependent measure from this task was the proportion of trials with a correct response (correctly identified 2-back "hits" and "non hits").</p> <hd id="AN0139548399-14">Go/no-go (GNG) task</hd> <p>This task was used to measure response inhibition. On each trial, participants were presented with either the letter X or Y. They were instructed to press the "J" key as fast as possible to one of the two letters (go trials) but to not press the key to the other letter (no-go trials). The letter X, presented on 50% of the trials, was the "go-letter" during the first two trial blocks; the letter Y, presented on 50% of the trials, was the go-letter during the final two trial blocks. Two dependent measures were taken from this task. The first was the mean response time (RT) on go-trials, which was used as measure of general cognitive speed. The second measure was the difference between the number of correct responses on go trials ("hits") and the number of incorrect responses to no-go trials ("false alarms"), with a high score reflecting a strong inhibition capacity.</p> <hd id="AN0139548399-15">Stroop colour-word interference (stroop) task</hd> <p>This task was used to assess interference control. Chinese characters representing one of two colors were printed in a color that was either congruent or incongruent with the color indicated by the character (congruent and incongruent trials, respectively). On neutral trials, a string of hash decks was printed in one of two colors. The participant had to indicate the color of the character or hash decks as fast as possible by pressing corresponding keys. The dependent measure was the proportion increase in RT when comparing neutral and incongruent trials, excluding trials with an incorrect response and RTs < 150 ms. A high score reflects poor interference control.</p> <hd id="AN0139548399-16">Flanker task</hd> <p>This task was used as additional measure of interference control. On each trial, participants were shown five fish in a row. On congruent trials, the orientation of all fish was the same (left or right); on incongruent trials, the direction of the center fish differed from that of the flanking fish. The participant had to indicate as quickly and accurately as possible the direction of the middle fish by pressing corresponding keys. The dependent measure was the proportion of RT increase from congruent to incongruent trials, excluding trials with an incorrect response and RTs < 150 ms. A high score reflects weak interference control.</p> <hd id="AN0139548399-17">Switching task</hd> <p>This task was used to assess task-switching capacity. On each trial, one of the digits 1−9, except 5, was presented in the center of the screen. For each digit, the participant had to make one of two types of judgment, reflecting two different tasks. On the magnitude judgment task (Task A), indicated by the digit having a red color, the participant had to indicate by appropriate key-press responses whether the current digit was larger or smaller than 5. On the parity judgment task (Task B), marked by a blue color of the digit, participants had to indicate whether the digit was odd or even. There were single-task trial blocks (either only Task A or B) and mixed-trial blocks trials (alternation of Tasks A and B). Within mixed-trial blocks, there were trials implicating a task repetition (non-switch trials) and trials implicating a task switch (switch trials). The main dependent measure was the switch cost: the proportion RT increase from non-switch to switch trials, excluding trials with an incorrect response and RTs < 150 ms and > 4000 ms. A high score reflects a poor switching ability.</p> <hd id="AN0139548399-18">Procedure</hd> <p>All participants completed the tests on six consecutive days: the IQ test on Day 1, the flanker and go/no-go tasks on Day 2, the Stroop and RM-long tasks on Day 3, the RM-short and switching tasks on Day 4, the EBPM tasks on Day 5, and the TBPM task on Day 6.</p> <hd id="AN0139548399-19">Data analysis</hd> <p>One adolescent consistently made an incorrect response on all neutral trials of the Stroop task and a Stroop-interference score could not be computed. Data were analyzed using SPSS 25 software. The outcome measures from the diverse tasks were first exmined for age group differences using analysis of variance (ANOVA), with subsequent Bonferroni post hoc tests in case of a significant group effect. For each of the ANOVAs, we first computed Cook's distance to identify influential data points, using a cut off value of D > 0.5 and removed the corresponding data points (the same was done for the regression analyses described hereafter; in practice this concerned elimination of 1–7 data points per analysis). For the Stroop, flanker, and switching tasks we also examined performance in terms of response accuracy rather than RTs. The corresponding analyses revealed that the children had a lower performance accuracy than the adolescents, who performed worse than the adults. This held for each of the different trial types within each of these tasks. However, in terms of a proportion performance decrement measure (specifically: from neutral to incongruent trials for the Stroop, from congruent to incongruent trials for the flanker, and from non-switch to switch trials for the switching task), there were no significant age differences, except for the flanker task, for which the children displayed a larger performance decrement than the adolescents, who showed a larger decrement than the adults. Therefore, the conclusions based on the results of the RT analyses reported below were not compromised by speed-accuracy tradeoffs. Subsequently, we assessed the association among the outcome measures (either expressed as eta or zero-order correlations), using a Bonferroni correction to control for multiple correlation analyses and after removing outlying scores (defined as >3 times the interquartile range) for each of the variables; in practice this concerned max. 7 data points for each variable. Next, we performed hierarchical regression analyses using focal and non-focal EBPM, and TBM performance as criterion. In the between-age-group analyses, we entered the dummy-coded age groups, with the adult participant group as reference, as predictors in Step 1, added general response speed (based on the mean RT of the go-trials of the GNG task) and OT performance in Step 2, and finally included the value on the outcome measures of the cognitive tasks in Step 3. Similar regression analyses were performed for each age group separately. Finally, using the SPSS PROCESS macro, we performed formal mediation analyses to test mediation of the association between age groups and PM task performances by each of the EF and non-EF task outcome measures. In these analyses, either focal EBPM, non-focal EBPM, or TBPM task performance served as criterion, age group served as a categorical independent variable (dummy coded), and all of the task measures as (potential) mediators (in one model). We used bootstrapping (5000 samples) in combination with 95% bias-corrected confidence intervals (CIs). Mediation by a specific variable was considered significant if the CI associated with the indirect effect corresponding to the target variable did not contain zero.</p> <hd id="AN0139548399-20">Results</hd> <p></p> <hd id="AN0139548399-21">Group differences</hd> <p>Table 1 shows the mean of the different outcome measures for each age group and the results of the ANOVAs. A significant group difference was found for all measures, although the effect size for the non-focal EBPM, Stroop, flanker, and switching tasks was relatively small. For each task, the children performed worse or slower than the adolescents (<emph>p</emph> =.02 for the TBPM task; other <emph>p</emph>s < 0.001) except for the switching task, on which the children displayed a <emph>lower</emph> switch cost than the adolescents (<emph>p</emph> <.001), and the focal and non-focal EBPM, Stroop, and flanker tasks, for which there was no significant difference between the two groups. The children performed worse or slower on each of the tasks compared to the adult participants except for the Stroop and switching tasks, on which the children showed a <emph>smaller</emph> interference effect and switch cost than the adults (<emph>p</emph>s < 0.05 for the Stroop, flanker, and switching tasks; other <emph>p</emph>s < 0.001). Finally, the adolescents showed worse or slower responding on each of the tasks than the adults (<emph>p</emph>s < 0.001) except for the RM-short, Stroop, flanker, and switching task, for which the difference was not significant.</p> <p>Table 1. Descriptive measures and outcome of ANOVAs evaluating group differences.</p> <p> <ephtml> <table><thead><tr><td /><td>Children <italic>M</italic> (<italic>SD</italic>) <italic>95% CI</italic></td><td>Adolescents <italic>M</italic> (<italic>SD</italic>) <italic>95% CI</italic></td><td>Adults <italic>M</italic> (<italic>SD</italic>) <italic>95% CI</italic></td><td>F</td><td>p</td><td>η<sup>2</sup></td></tr></thead><tbody><tr><td>EBPM/focal</td><td>0.12 (0.19) [0.08−0.16]</td><td>0.20 (0.28) [0.14−0.25]</td><td>0.50 (0.36) [0.44−0.57]</td><td>54.04</td><td><.001</td><td>.25</td></tr><tr><td>EBPM/focal-OT</td><td>0.50 (0.19) [0.46−0.53]</td><td>0.61 (0.17) [0.58−0.65]</td><td>0.82 (0.11) [0.80−0.84]</td><td>110.85</td><td><.001</td><td>.41</td></tr><tr><td>EBPM/non-focal</td><td>0.40 (0.34) [0.33−0.46]</td><td>0.42 (0.35) [0.35−0.48]</td><td>0.63 (0.29) [0.57−0.69]</td><td>16.29</td><td><.001</td><td>.09</td></tr><tr><td>EBPM/non-focal-OT</td><td>0.44 (0.19) [0.40−0.47]</td><td>0.56 (0.19) [0.52−0.59]</td><td>0.71 (0.17) [0.68−0.75]</td><td>60.10</td><td><.001</td><td>.27</td></tr><tr><td>TBPM</td><td>0.13 (0.21) [0.09−0.17]</td><td>0.25 (0.29) [0.19−0.30]</td><td>0.62 (0.38) [0.54−0.69]</td><td>75.11</td><td><.001</td><td>.32</td></tr><tr><td>TBPM-OT</td><td>0.69 (0.15) [0.66−0.72]</td><td>0.83 (0.13) [0.80−0.84]</td><td>0.94 (0.04) [0.94−0.95]</td><td>136.18</td><td><.001</td><td>.46</td></tr><tr><td>WM-2Back</td><td>0.57 (0.18) [0.54−0.61]</td><td>0.68 (0.15) [0.65−0.70]</td><td>0.88 (0.09) [0.86−0.89]</td><td>118.56</td><td><.001</td><td>.42</td></tr><tr><td>RM-short</td><td>0.71 (0.20) [0.68−0.75]</td><td>0.89 (0.10) [0.87−0.91]</td><td>0.92 (0.09) [0.90−0.93]</td><td>68.16</td><td><.001</td><td>.30</td></tr><tr><td>RM-long</td><td>0.74 (0.18) [0.71−0.77]</td><td>0.89 (0.08) [0.88−0.91]</td><td>0.95 (0.06) [0.94−0.96]</td><td>94.68</td><td><.001</td><td>.37</td></tr><tr><td>GNG-Hits-FA</td><td>0.69 (0.17) [0.66−0.72]</td><td>0.88 (0.10) [0.86−0.90]</td><td>0.95 (0.03) [0.95−0.96]</td><td>149.45</td><td><.001</td><td>.49</td></tr><tr><td>GNG-GoRT</td><td>523.53 (52.14) [513.53−533.52]</td><td>454.69 (44.18) [446.42–462.96]</td><td>426.10 (36.45) [419.08–433.12]</td><td>133.88</td><td><.001</td><td>.45</td></tr><tr><td>Stroop</td><td>0.03 (0.11) [0.01−0.05]</td><td>0.07 (0.14) [0.04−0.09]</td><td>0.08 (0.11) [0.06−0.10]</td><td>4.40</td><td>.01</td><td>.03</td></tr><tr><td>Flanker</td><td>0.06 (0.07) [0.04−0.07]</td><td>0.04 (0.07) [0.03−0.05]</td><td>0.03 (0.05) [0.02−0.04]</td><td>5.20</td><td>.006</td><td>.03</td></tr><tr><td>Switch_cost</td><td>0.13 (0.15) [0.10−0.16]</td><td>0.23 (0.21) [0.19−0.26]</td><td>0.22 (0.18) [0.18−0.25]</td><td>9.52</td><td><.001</td><td>.06</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>M</emph> = mean value; SD = standard deviation; CI = 95% confidence interval, based on bootstrapping (5000 samples); EBPM = event-based prospective memory task; TBPM = time-based prospective memory task; OT = ongoing task; WM-2Back = working memory measure based on 2-back task of EBPM task; RM = running memory task; short/long = short/long presentation time; GNG = go/no-go task; FA = false alarms. Df for numerator of F statistic is 2, for the denominator between 317 (for the GNG-Hits-FA measure) and 323.</p> <hd id="AN0139548399-22">Association between task variables</hd> <p>Table 2 displays the association, expressed as eta or zero-order correlations, among the various outcome measures. As also suggested by the results of the ANOVAs in Table 1, age was strongly associated with all outcome measures except for those of the Stroop, flanker, and switching tasks. Moreover, most of the correlations among the various PM, RM, WM, and GNG task measures were significant, whereas those involving the Stroop, flanker, and switching tasks only showed a few significant but relatively weak correlations. Notably, the score on the WM measure (2-back task performance) was significantly more strongly associated with the RM-long (<emph>r</emph>=.56) than RM-short (<emph>r</emph> =.39) score, as revealed by a comparison using Fisher r-to-z transformation (<emph>z</emph> = 2.79, <emph>p</emph> =.005). This suggests a stronger involvement of active WM updating in the RM-long than RM-short task version. The unique predictive value of the different cognitive measures for performance on each of the three types of PM task was examined further using the analyses reported below.</p> <p>Table 2. Associations among the outcome measures.</p> <p> <ephtml> <table><thead><tr><td /><td>1</td><td>2</td><td>3</td><td>4</td><td>5</td><td>6</td><td>7</td><td>8</td><td>9</td><td>10</td><td>11</td><td>12</td><td>13</td><td>14</td></tr></thead><tbody><tr><td>1. Age Group</td><td>×</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>2. EBPM/focal</td><td>.<bold>50</bold></td><td>×</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>3. EBPM/focal-OT</td><td>.<bold>64</bold></td><td>.<bold>29</bold></td><td>×</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>4. EBPM/non-focal</td><td>.<bold>30</bold></td><td>.<bold>35</bold></td><td>.<italic>16</italic></td><td>×</td><td /><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>5. EBPM/non-focal-OT</td><td>.<bold>52</bold></td><td>.<bold>21</bold></td><td>.<bold>66</bold></td><td>.05</td><td>×</td><td /><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>6. TBPM</td><td>.<bold>56</bold></td><td>.<bold>29</bold></td><td>.<bold>42</bold></td><td>.13</td><td>.<bold>39</bold></td><td>×</td><td /><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>7. TBPM-OT</td><td>.<bold>67</bold></td><td>.<bold>36</bold></td><td>.<bold>56</bold></td><td>.<italic>17</italic></td><td>.<bold>49</bold></td><td>.<bold>48</bold></td><td>×</td><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>8. WM-2Back</td><td>.<bold>65</bold></td><td>.<bold>41</bold></td><td>.<bold>73</bold></td><td>.<bold>31</bold></td><td>.<bold>60</bold></td><td>.<bold>41</bold></td><td>.<bold>55</bold></td><td>×</td><td /><td /><td /><td /><td /><td /></tr><tr><td>9. RM-short</td><td>.<bold>55</bold></td><td>.<bold>27</bold></td><td>.<bold>37</bold></td><td>.<bold>20</bold></td><td>.<bold>27</bold></td><td>.<bold>28</bold></td><td>.<bold>46</bold></td><td>.<bold>39</bold></td><td>×</td><td /><td /><td /><td /><td /></tr><tr><td>10. RM-long</td><td>.<bold>60</bold></td><td>.<bold>34</bold></td><td>.<bold>44</bold></td><td>.<bold>23</bold></td><td>.<bold>39</bold></td><td>.<bold>40</bold></td><td>.<bold>49</bold></td><td>.<bold>56</bold></td><td>.<bold>63</bold></td><td>×</td><td /><td /><td /><td /></tr><tr><td>11. GNG-Hits-FA</td><td>.<bold>66</bold></td><td>.<bold>37</bold></td><td>.<bold>45</bold></td><td>.<bold>24</bold></td><td>.<bold>40</bold></td><td>.<bold>40</bold></td><td>.<bold>61</bold></td><td>.<bold>52</bold></td><td>.<bold>47</bold></td><td>.<bold>51</bold></td><td>×</td><td /><td /><td /></tr><tr><td>12. GNG-GoRT</td><td>.<bold>66</bold></td><td><bold>−.31</bold></td><td><bold>−.40</bold></td><td><bold>−</bold>.<italic>19</italic></td><td><bold>−.35</bold></td><td><bold>−.35</bold></td><td><bold>−.54</bold></td><td><bold>−.46</bold></td><td><bold>−.40</bold></td><td><bold>−.45</bold></td><td><bold>−.52</bold></td><td>×</td><td /><td /></tr><tr><td>13. Stroop</td><td>.16</td><td>.12</td><td>.11</td><td>.10</td><td>.06</td><td>.02</td><td>.10</td><td>.<italic>15</italic></td><td>.06</td><td>.14</td><td>.14</td><td>−.06</td><td>×</td><td /></tr><tr><td>14. Flanker</td><td>.17</td><td><bold>−</bold>.<italic>18</italic></td><td>−.06</td><td>−.09</td><td>−.05</td><td><italic>−</italic>.14</td><td>−.12</td><td>−.08</td><td><italic>−</italic>.11</td><td><bold>−.20</bold></td><td>−.12</td><td>.05</td><td>.07</td><td>×</td></tr><tr><td>15. Switch_cost</td><td>.24</td><td>.05</td><td>.13</td><td>.04</td><td>.11</td><td>.14</td><td>.<bold>21</bold></td><td>.11</td><td>.<bold>28</bold></td><td>.<bold>21</bold></td><td>.<bold>22</bold></td><td><italic>−.17</italic></td><td>.05</td><td>−.09</td></tr></tbody></table> </ephtml> </p> <p>2 The values for Age Group (column 1) represent eta; other values represent Pearson correlations. For Column 1, values in bold represent a strong effect (eta ≥ 0.30). For the other columns, values in bold and italics represent, respectively, <emph>p</emph> <.001 (indicating significance when adopting α = 0.001 to control for Type 1 error inflation) and <emph>p</emph> <.01. Correlations are based on 311 > <emph>N</emph> < 327.</p> <hd id="AN0139548399-23">Regression and mediation analyses: age-group level</hd> <p>Tables 3–5 display the results of the age-group-based regression and mediation analyses, with focal EBPM, non-focal EBPM, and TBPM task performance as criterion, respectively.</p> <p>Table 3. Hierarchical regression analysis and CIs for indirect effect in mediation analysis with focal EBPM task performance as criterion.</p> <p> <ephtml> <table><thead><tr><td>Predictor</td><td>Beta</td><td>ΔF (df)</td><td>F (df)</td><td>ΔR<sup>2</sup></td><td>R<sup>2</sup></td><td>CI relative indirect effect</td></tr></thead><tbody><tr><td><bold>Step 1</bold></td><td /><td /><td>59.98*** (2,320)</td><td /><td>.27</td><td /></tr><tr><td> Children</td><td>−.40***</td><td /><td /><td /><td /><td /></tr><tr><td> Adolescents</td><td>−.31***</td><td /><td /><td /><td /><td /></tr><tr><td><bold>Step 2</bold></td><td /><td>0.13 (2,318)</td><td>29.89*** (4,318)</td><td>.00</td><td>.27</td><td /></tr><tr><td> Children</td><td>−.38***</td><td /><td /><td /><td /><td /></tr><tr><td> Adolescents</td><td>−.31***</td><td /><td /><td /><td /><td /></tr><tr><td> GoRT</td><td>.00</td><td /><td /><td /><td /><td /></tr><tr><td> EBPM-OT</td><td>.00</td><td /><td /><td /><td /><td /></tr><tr><td><bold>Step 3</bold></td><td /><td>2.14* (6,312)</td><td>13.50*** (10,312)</td><td>.04</td><td>.30</td><td /></tr><tr><td> Children</td><td>−.26***</td><td /><td /><td /><td /><td /></tr><tr><td> Adolescents</td><td>−.27***</td><td /><td /><td /><td /><td /></tr><tr><td> GoRT</td><td>.00</td><td /><td /><td /><td /><td>D1:[−.08,.03] D2:[−.03,.01]</td></tr><tr><td> EBPM-OT</td><td>−.03</td><td /><td /><td /><td /><td>D1:[−.05,.07] D2:[−.03,.05]</td></tr><tr><td> RM-short</td><td>.00</td><td /><td /><td /><td /><td>D1:[−.05,.05] D2:[−.01,.01]</td></tr><tr><td> RM-long</td><td>.19</td><td /><td /><td /><td /><td>D1:[−.10,.01] D2:[−.03,.00]</td></tr><tr><td> GNG-Hits-FA</td><td>.23</td><td /><td /><td /><td /><td><bold>D1:[−.11, −.02]</bold><bold>D2:[−.03, −.01]</bold></td></tr><tr><td> Stroop</td><td>.14</td><td /><td /><td /><td /><td>D1:[−.03,.01] D2:[−.01,.00]</td></tr><tr><td> Flanker</td><td>−.49*</td><td /><td /><td /><td /><td><bold>D1:[−.03, −.003]</bold> D2:[−.02,.002]</td></tr><tr><td> witch cost</td><td>−.08</td><td /><td /><td /><td /><td>D1:[−.01,.03] D2:[−.01,.00]</td></tr></tbody></table> </ephtml> </p> <p>3 Beta = unstandardized regression coefficients; CI = 95% bias-corrected confidence interval based on bootstrapping (5000 samples); relative indirect effect = effect of D1 and D2 on the criterion via the corresponding cognitive measure (indicated in the first column) in a mediation model including all cognitive measures as mediators; D1 = contrast between children and adults; D2 = contrast between adolescents and adults; EBPM = event-based prospective memory task; OT = ongoing task; GoRT = RT on Go trials of the go/no-go task; RM = running memory task; short/long = short/long presentation time; GNG = go/no-go task; FA = false alarms. *<emph>p</emph> <.05, **<emph>p</emph> <.01, ***<emph>p</emph> <.001. CIs in bold are significant (not containing zero). Note that the beta's in Step 1 reflect the total effects and the beta for Children and Adolescents in Step 3 the direct effects in the mediation model.</p> <p>Table 4. Hierarchical regression analysis and CIs for indirect effect in mediation analysis with non-focal EBPM task performance as criterion.</p> <p> <ephtml> <table><thead><tr><td>Predictor</td><td>Beta</td><td>ΔF (df)</td><td>F (df)</td><td>ΔR<sup>2</sup></td><td>R<sup>2</sup></td><td>CI relative indirect effect</td></tr></thead><tbody><tr><td><bold>Step 1</bold></td><td /><td /><td>16.27*** (2,322)</td><td /><td>.09</td><td /></tr><tr><td>Children</td><td>−.23***</td><td /><td /><td /><td /><td /></tr><tr><td>Adolescents</td><td>−.21***</td><td /><td /><td /><td /><td /></tr><tr><td><bold>Step 2</bold></td><td /><td>3.07* (2,320)</td><td>9.77*** (4,320)</td><td>.02</td><td>.11</td><td /></tr><tr><td>Children</td><td>−.26***</td><td /><td /><td /><td /><td /></tr><tr><td>Adolescents</td><td>−.24***</td><td /><td /><td /><td /><td /></tr><tr><td>GoRT</td><td>.00</td><td /><td /><td /><td /><td /></tr><tr><td>EBPM-OT</td><td>−.23*</td><td /><td /><td /><td /><td /></tr><tr><td><bold>Step 3</bold></td><td /><td>1.88 (6,314)</td><td>5.10*** (10,314)</td><td>.03</td><td>.14</td><td /></tr><tr><td>Children</td><td>−.11</td><td /><td /><td /><td /><td /></tr><tr><td>Adolescents</td><td>−.20***</td><td /><td /><td /><td /><td /></tr><tr><td>GoRT</td><td>.00</td><td /><td /><td /><td /><td>D1:[−.12,.03] D2:[−.04,.01]</td></tr><tr><td>EBPM-OT</td><td>−.24*</td><td /><td /><td /><td /><td><bold>D1:[.02,.12]</bold><bold>D2:[.01,.08]</bold></td></tr><tr><td>RM-short</td><td>.18</td><td /><td /><td /><td /><td>D1:[−.10,.03] D2:[−.02,.00]</td></tr><tr><td>RM-long</td><td>.09</td><td /><td /><td /><td /><td>D1:[−.10,.06] D2:[−.03,.02]</td></tr><tr><td>GNG-Hits-FA</td><td>.25</td><td /><td /><td /><td /><td>D1:[−.15,.01] D2:[−.05,.00]</td></tr><tr><td>Stroop</td><td>.20</td><td /><td /><td /><td /><td>D1:[−.03,.00] D2:[−.02,.00]</td></tr><tr><td>Flanker</td><td>−.34</td><td /><td /><td /><td /><td>D1:[−.03,.00] D2:[−.02,.00]</td></tr><tr><td>Switch cost</td><td>−.06</td><td /><td /><td /><td /><td>D1:[−.01,.03] D2:[−.01,.00]</td></tr></tbody></table> </ephtml> </p> <p>4 See note to Table 3 for details.</p> <p>Table 5. Hierarchical regression analysis and CIs for indirect effect in mediation analysis with TBPM task performance as criterion.</p> <p> <ephtml> <table><thead><tr><td>Predictor</td><td>Beta</td><td>ΔF (df)</td><td>F (df)</td><td>ΔR<sup>2</sup></td><td>R<sup>2</sup></td><td>CI relative indirect effect</td></tr></thead><tbody><tr><td><bold>Step 1</bold></td><td /><td /><td>75.85*** (2,321)</td><td /><td>.32</td><td /></tr><tr><td>Children</td><td>−.48***</td><td /><td /><td /><td /><td /></tr><tr><td>Adolescents</td><td>−.37***</td><td /><td /><td /><td /><td /></tr><tr><td><bold>Step 2</bold></td><td /><td>7.46**(2,319)</td><td>43.18*** (4,319)</td><td>.03</td><td>.35</td><td /></tr><tr><td>Children</td><td>−.34***</td><td /><td /><td /><td /><td /></tr><tr><td>Adolescents</td><td>−.30***</td><td /><td /><td /><td /><td /></tr><tr><td>GoRT</td><td>.00</td><td /><td /><td /><td /><td /></tr><tr><td>EBPM-OT</td><td>.55***</td><td /><td /><td /><td /><td /></tr><tr><td><bold>Step 3</bold></td><td /><td>1.81 (6,313)</td><td>18.62*** (10,313)</td><td>.02</td><td>.37</td><td /></tr><tr><td>Children</td><td>−.26***</td><td /><td /><td /><td /><td /></tr><tr><td>Adolescents</td><td>−.28***</td><td /><td /><td /><td /><td /></tr><tr><td>GoRT</td><td>.00</td><td /><td /><td /><td /><td>D1:[−.06,.07] D2:[−.02,.02]</td></tr><tr><td>EBPM-OT</td><td>.48**</td><td /><td /><td /><td /><td><bold>D1:[−.18, −.07]</bold><bold>D2:[−.09, −.03]</bold></td></tr><tr><td>RM-short</td><td>−.16</td><td /><td /><td /><td /><td>D1:[−.01,.09] D2:[.00,.02]</td></tr><tr><td>RM-long</td><td>.36*</td><td /><td /><td /><td /><td><bold>D1:[−.14, −.03]</bold><bold>D2:[−.04, −.01]</bold></td></tr><tr><td>GNG-Hits-FA</td><td>.19</td><td /><td /><td /><td /><td><bold>D1:[−.09, −.01]</bold><bold>D2:[−.03, −.002]</bold></td></tr><tr><td>Stroop</td><td>−.16</td><td /><td /><td /><td /><td>D1:[.00,.02] D2:[.00,.01]</td></tr><tr><td>Flanker</td><td>−.20</td><td /><td /><td /><td /><td>D1:[−.02,.01] D2:[−.01,.00]</td></tr><tr><td>Switch cost</td><td>.08</td><td /><td /><td /><td /><td>D1:[−.03,.01] D2:[.00,.01]</td></tr></tbody></table> </ephtml> </p> <p>5 See note to Table 3 for details.</p> <hd id="AN0139548399-24">Focal EBPM task</hd> <p>Age groups accounted for 27% of the variance in focal EBPM task performance in Step 1. Inclusion of the GNG-goRTs and OT performance during the criterion task did not result in a significant increase in explained variance and age groups continued to be the only significant predictors. The non-significance of the OT task performance suggests that there was no trade-off between OT and target-task (PM) performance. Including the EF measures in Step 3 significantly enhanced the explained variance and age groups and flanker-task performance were significant unique predictors in the final model. The mediation analysis revealed that the age-group-related variance in focal EBPM task performance was partially mediated (the direct effect of the age-group variables on the criterion remained significant) by performance on the GNG and flanker tasks, with the qualification that the mediation by flanker task performance specifically held for the children/adults contrast variable.</p> <hd id="AN0139548399-25">Non-focal EBPM task</hd> <p>Age groups significantly predicted non-focal EBPM task performance in Step 1. Adding response speed and OT performance in Step 2 significantly increased the explained variance, with age groups and OT performance being significant predictors. Including the EF measures in Step 3 did not result in any major changes, except that the effect of "children" (contrast between children and adults) was no longer significant. The significant negative association with OT performance suggests a trade-off between performance on the OT and the PM task. The mediation analysis suggested a full mediation of the association between the children-adults contrast variable and non-focal EBPM task performance by OT performance (given the non-significance of the direct effect), and a partial mediation of the association between the adolescents-adults contrast variable and PM task performance by OT performance.</p> <hd id="AN0139548399-26">TBPM task</hd> <p>For TBPM task performance, age groups continued to be significant predictors when introducing the other measures in Steps 2 and 3. Introducing OT performance in Step 2 significantly increased the explained variance and the predictive value of OT performance remained significant in Step 3. Although the change in explained variance from Step 2 to Step 3 was not significant, in the final model performance on the RM-long task was a significant unique predictor, next to the age groups and OT performance. OT performance was positively related to TBPM task performance, suggesting the absence of a trade-off in performance on the two tasks, but shared cognitive processes. The mediation analysis revealed that performance on the OT, RM-long, and GNG tasks partially mediated the association between the age groups and TBPM task performance.</p> <hd id="AN0139548399-27">Regression analyses: within-age-group level</hd> <p></p> <hd id="AN0139548399-28">Focal EBPM task</hd> <p>For the child group, the hierarchical regression analysis did not reveal any significant models and predictors of focal EBPM performance in any of the steps (final model in Step 3: <emph>R</emph><sups>2</sups> =.10, <emph>F</emph>(<reflink idref="bib9" id="ref57">9</reflink>, 94) = 1.13, <emph>p</emph> =.34, and max. <emph>β</emph> =.18, <emph>p</emph> =.20). For the adolescent groups too, none of the models were significant (model in Step 3: <emph>R</emph><sups>2</sups> =.10, <emph>F</emph>(<reflink idref="bib9" id="ref58">9</reflink>, 96) = 1.16, <emph>p</emph> =.33), although performance on the switching task appeared as sole significant predictor (<emph>β</emph> =.-.23, <emph>p</emph> =.02). None of the models reached significance using the data from the adult sample (model in Step 3: <emph>R</emph><sups>2</sups> =.13, <emph>F</emph>(<reflink idref="bib9" id="ref59">9</reflink>, 95) = 1.58, <emph>p</emph> =.13), although in this group performance on the RM-long task was a significant predictor (<emph>β</emph> =.29, <emph>p</emph> =.02).</p> <hd id="AN0139548399-29">Non-focal EBPM task</hd> <p>For the group of children, none of the models predicting non-focal EBPM performance reached significance (final model, Step 3: <emph>R</emph><sups>2</sups> =.09, <emph>F</emph>(<reflink idref="bib9" id="ref60">9</reflink>, 96) = 1.04, <emph>p</emph> =.42), although OT performance was a significant predictor in Step 2 (<emph>β</emph> = −.21, <emph>p</emph> =.04). A similar pattern was found for the adult sample (Step 3 model: <emph>R</emph><sups>2</sups> =.15, <emph>F</emph>(<reflink idref="bib9" id="ref61">9</reflink>, 91) = 1.83, <emph>p</emph> =.07, and <emph>β</emph> = −.21, <emph>p</emph> =.03, for OT performance). The analysis for the adolescent groups failed to reveal any significant models and predictors (Step 3 model: <emph>R</emph><sups>2</sups> =.10, <emph>F</emph>(<reflink idref="bib9" id="ref62">9</reflink>, 99) = 1.20, <emph>p</emph> =.31, and max. <emph>β</emph> =.16, <emph>p</emph> =.12).</p> <hd id="AN0139548399-30">TBPM task</hd> <p>Using the data from the children, regression analysis revealed a significant final model (Step 3: <emph>R</emph><sups>2</sups> =.18, <emph>F</emph>(<reflink idref="bib9" id="ref63">9</reflink>, 96) = 2.39, <emph>p</emph> =.02), although none of the predictors in isolation had a significant predictive value (max. <emph>β</emph> =.19, <emph>p</emph> =.10). OT performance was a significant predictor in Step 2 (<emph>β</emph> =.21, <emph>p</emph> =.03), although the corresponding full model was not significant (<emph>R</emph><sups>2</sups> =.06, <emph>F</emph>(<reflink idref="bib3" id="ref64">3</reflink>, 102) = 2.24, <emph>p</emph> =.09). For the adolescent group, both the Step 2 and Step 3 models were significant (respectively, <emph>R</emph><sups>2</sups> =.13, <emph>F</emph>(<reflink idref="bib3" id="ref65">3</reflink>, 104) = 5.16, <emph>p</emph> =.002, and <emph>R</emph><sups>2</sups> =.22, <emph>F</emph>(<reflink idref="bib9" id="ref66">9</reflink>, 98) = 3.02, <emph>p</emph> =.003). In both these steps, OT performance was a significant predictor (<emph>β</emph>s >.28, <emph>p</emph>s <.005); in Step 3, RM-long task performance was an additional significant predictor (<emph>β</emph> =.22, <emph>p</emph> =.04). Finally, a partly similar pattern of results was found for the adult group, with both the Step 2 and 3 models being significant (respectively, <emph>R</emph><sups>2</sups> =.13, <emph>F</emph>(<reflink idref="bib3" id="ref67">3</reflink>, 99) = 5.11, <emph>p</emph> =.002, and <emph>R</emph><sups>2</sups> =.19, <emph>F</emph>(<reflink idref="bib9" id="ref68">9</reflink>, 93) = 2.36, <emph>p</emph> =.02), and with OT performance being a significant predictor in each of these models (<emph>β</emph>s >.30, <emph>p</emph>s =.002). However, for this group, none of the other measures was a significant predictor in the final model.</p> <hd id="AN0139548399-31">Discussion</hd> <p></p> <hd id="AN0139548399-32">Summary of findings</hd> <p>Three age groups, children (7−9 years), adolescents (12−14 years), and young adults (17−23 years), performed a focal and non-focal EBPM task, a TBPM task, and tasks assessing a number of cognitive functions, including WM, inhibition, and switching. For all measures, performance significantly differed between age groups. For most measures, the children performed worse than the adolescents, who performed worse than the adults. Exceptions were the Stroop and switching tasks, on which the children showed <emph>less</emph> interference and <emph>weaker</emph> switch costs than the adolescents and/or adults. Regression and mediation analyses suggested that the differences between age groups in focal EBPM task performance were partly due to age group differences in interference control, as measured by a flanker task, and by response inhibition capacity, as measured by a go/no-go task. The age-group-related non-focal EBPM task performance differences were primarily mediated by age-group-related differences in ongoing task performance. Finally, age group differences in TBPM task performance could be partly ascribed to performance differences in the OT, and tasks used to measure WM updating and response inhibition. Separate regression analyses within each age group only revealed evidence for variations in WM updating to significantly predict the adolescent's TBPM performance. For the child and adult samples, none of the cognitive measures in isolation (besides OT performance) could be identified as a significant predictor of TBPM performance, although the measures combined did. For the focal and non-focal EBPM tasks, none of the models were significant, although switching and WM-updating ability appeared as significant isolated predictors for, respectively, the adolescent and adult sample in the focal task.</p> <hd id="AN0139548399-33">Age group differences in task performance</hd> <p>The increase in task performance on the EBPM, TBPM, OT, RM, 2-back, GNG, and flanker tasks with increasing age suggests a developmental trajectory across the three age groups of the processes underlying performance on these tasks, specifically, PM, WM capacity and updating, response inhibition, and interference control. This finding is in line with the prolonged developmental trajectory of these functions reported in previous studies (see references in corresponding section in the introduction). Moreover, the age group related increase in general response speed, as measured by the Go-RT measure, is also in accordance with previous studies (Kail, [<reflink idref="bib17" id="ref69">17</reflink>]). Somewhat unexpected were the smaller interference effect shown by the children compared to the adults on the Stroop task, and the smaller switch cost for the children compared to both the adolescence and adults. Concerning the Stroop task, a complicating issue is that task performance is also affected by level of reading automaticity (Leon-Carrion, García-Orza, & Pérez-Santamar, [<reflink idref="bib25" id="ref70">25</reflink>]), and it may be that the younger participants experienced less interference due to a lower reading automaticity (to our knowledge there are no previous studies examining this issue for Chinese populations and the use of Chinese characters). With respect to the switch cost, it must be noted that Davidson, Amso, Anderson, and Diamond ([<reflink idref="bib10" id="ref71">10</reflink>]) also found switch cost in terms of RTs to <emph>increase</emph> from age 4 until adulthood and that this pattern was partly due to a speed-accuracy trade-off. Although in the present study an analysis of switch cost in terms of accuracy did not reveal a significant group effect, there was an inverted U-shaped pattern, with the adolescents showing a larger switch cost than the children and adults. This pattern resembles that found by Davidson et al. ([<reflink idref="bib10" id="ref72">10</reflink>]), although the maximum switch cost using an accuracy measure in this study was present at an earlier age than in the present study.</p> <p>A further notable finding was the profound lower accuracy for the focal compared to non-focal task in each of the age groups (see Table 1). This is an unexpected finding on account of the assumption that a PM cue that is in the same focus of attention as the stimulus of the OT is more salient and easy to detect than a PM cue that is less overlapping with the OT stimulus. Accordingly, the non-focal task should be cognitively more demanding than the focal task (McDaniel & Einstein, [<reflink idref="bib32" id="ref73">32</reflink>]). However, as noted and further supported by the research by Zuber et al. ([<reflink idref="bib49" id="ref74">49</reflink>]), PM cue detection is but one of the processes involved in successful PM performance, in addition to intention retrieval and execution, and focal EBPM task performance may require more EFs than previously assumed. The research by Zuber et al. and our own findings, at least in terms of explaining our age-group focal PM performance differences, suggest especially inhibitory processes to be one of those EFs, and that these processes are more importantly involved in the currently used focal than non-focal PM task. Presumably, in the focal task participants are more immersed in the OT than in the non-focal task, because of a lesser necessity to actively monitor <emph>peripheral</emph> PM cues. This greater immersion might require stronger inhibitory processes to realize the PM task than in the non-focal task.</p> <hd id="AN0139548399-34">Mediators of age group differences in focal EBPM task performance</hd> <p>Of all cognitive measures, only variations in GNG (response inhibition) and flanker (interference control) task performance were relevant for explaining part of the age-group-related differences in focal EBPM task performance. A mediating role of inhibition, specifically response inhibition, was also reported by Mahy et al. ([<reflink idref="bib29" id="ref75">29</reflink>]) when comparing 4- to 5-year-old children, and by Zuber et al. ([<reflink idref="bib49" id="ref76">49</reflink>]) examining participants aged from 20 to 68 years. Moreover, in some conditions of the PM task they used, Ward et al. ([<reflink idref="bib42" id="ref77">42</reflink>]) found a significant mediating role of interference control when examining groups of children, adolescents, and adults. However, one difference is that the latter study used the Stroop task, rather than the flanker task as measure of interference control, and we found no significant results for the Stroop task. This difference might be linked to the hypothesized strong involvement of reading automaticity differences in the Stroop task performance in our study. The involvement of both types of inhibition in mediating performance in our focal PM task is in accordance with the suggestion that detection of a PM-cue letter and subsequent correct responding to this cue require suppression of attention and responding to the OT letter according to the OT task requirement. The absence of a mediating role of WM, either primarily maintenance as tapped by the RM-short task, or WM updating as assessed by the RM-long task, is not in accordance with the results of Zuber et al. ([<reflink idref="bib49" id="ref78">49</reflink>]), who did find an association between WM updating and focal PM performance. However, as noted by the authors, this association might not be surprising, being due to the fact that both the OT and WM measures were based on the same updating task. Accordingly, if a participant has a strong WM-updating capacity, he/she automatically is also good at performing the OT and more resources are available for performing the PM task. In fact, incorporating 2-back performance during the first block of the EBPM in our regression model also reveals a significant mediating effect (data not shown).</p> <hd id="AN0139548399-35">Mediators of age group differences in non-focal EBPM task performance</hd> <p>For the non-focal EBPM task, only OT task performance played a significant mediating role. The absence of a clear involvement of any of the other cognitive measures supports the notion that this task was relatively less cognitive demanding than the focal EBPM task. However, this result is not in line with the results reported by Schnitzspahn et al. ([<reflink idref="bib37" id="ref79">37</reflink>]) and Zuber et al. ([<reflink idref="bib49" id="ref80">49</reflink>]). Schnitzspahn et al. compared young and older adults and found both inhibition, defined by a composite score based on response inhibition and interference control tasks, and switching ability to fully mediate the age-related PM performance differences. Zuber et al. ([<reflink idref="bib49" id="ref81">49</reflink>]) only found switching to predict variations in PM task performance that were observed in a sample of adults ranging from 20 to 68-years of age. Unlike Schnitzspahn et al. and Zuber et al., we did not find switching ability to be a significant mediator. However, Schnitzspahn et al. used the so-termed <emph>unspecific</emph> switch cost (difference in RT between mixed- and single-task blocks) as outcome measure, which is more similar to the mixing cost than the traditional switch cost as used in the present study. This is a factor complicating a comparison between studies given that mixing and switch costs reflect different processes (Kiesel et al., [<reflink idref="bib19" id="ref82">19</reflink>]). As in our study, Zuber et al. used a measure based on the RT difference between switch and non-switch trials of the mixed-trial blocks but did not provide any direct information on the association between age and switch cost. One possible reason for the different results regarding the association between switch cost and non-focal EBPM task performance might be due to the different age ranges examined, but clearly, more research is necessary to validate this.</p> <hd id="AN0139548399-36">Mediators of age group differences in TBPM task performance</hd> <p>Performance differences between the age groups in TBPM task performance were significantly mediated by differences in OT performance, WM updating (RM-long), and response inhibition. The involvement of two of the three components of EF supports the relatively strong cognitive demands associated with this type of PM task (relative to EBPM tasks). The direct association between OT and TBPM performance was positive, indicating that it was not due to a trade-off between the OT and PM aspects of the task. Instead, being good at performing the OT could have implicated more available cognitive resources to spend on the PM task. The mediating role of WM updating is in line with previous studies using a valid WM-updating measure and covering an age range of 5−29 years (Kerns, [<reflink idref="bib18" id="ref83">18</reflink>]; Kretschmer et al., [<reflink idref="bib23" id="ref84">23</reflink>]; Mäntylä et al., [<reflink idref="bib30" id="ref85">30</reflink>]; Voigt et al., [<reflink idref="bib41" id="ref86">41</reflink>]).</p> <p>Like in our study, in two of these studies (Kerns, [<reflink idref="bib18" id="ref87">18</reflink>]; Mäntylä et al., [<reflink idref="bib30" id="ref88">30</reflink>]) inhibition too was related to TBPM performance differences, next to WM updating, albeit with interference control in one study (Kerns, [<reflink idref="bib18" id="ref89">18</reflink>]) and a combined response inhibition/interference control measure in the other. Of the other two studies, one did not have a measure of inhibition (Voigt et al., [<reflink idref="bib41" id="ref90">41</reflink>]), and one study failed to find an association with response inhibition, as measured by a go/no-go task (Kretschmer et al., [<reflink idref="bib23" id="ref91">23</reflink>]). The results of the latter study are not in line with the present results but may be related to the use of younger age groups (5 to 6 vs. 7 to 8-year-olds in Kretchmer et al.'s study). These younger children might have a different EF skill structure compared to that of our older participants, although studies relevant to this issue reveal contradictory results (see Zelazo, Blair, & Willoughby, [<reflink idref="bib44" id="ref92">44</reflink>], for an overview). Finally, Gonneaud et al. ([<reflink idref="bib15" id="ref93">15</reflink>]) also found response inhibition to have a significant mediating role (they did not have a standard measure of WM updating), although inhibition was measured using a relatively process impure, random letter generation, task.</p> <p>Switching ability, together with performance on a planning task, were found to partially mediate age-related (age range: 7−12 years) TBPM performance differences in a study by Mackinlay et al. ([<reflink idref="bib26" id="ref94">26</reflink>]). However, this study only included the backward digit span test as measure of WM-updating capacity, a test which perhaps may not be as sensitive for uncovering age-related WM-updating differences as the RM-long task, and this study did not include an inhibition measure. Task switching is held to heavily build on response inhibition and WM-updating abilities (e.g., Diamond, [<reflink idref="bib11" id="ref95">11</reflink>]). In order to successfully realize a task switch, one has to suppress responding to the previously relevant response rules and to update WM with the rules of the now relevant task. The proposed link between switching, inhibition, and WM updating allows for the possibility that, if a (valid) measure of WM updating and inhibition had been included in the model, Mackinlay et al. would also have found a strong mediating role by WM updating and inhibition, at the expense of the contribution of switching (sharing variance with the other two EFs).</p> <p>In terms of our own study, of all types of PM task, we expected TBPM task performance to be most strongly dependent on switching capacity. The fact that we did not find such role may be related to the proposed shared variance of switching cost with inhibition and WM (e.g., see also Table 1) and/or the influence of age group related, nonlinear differences in response accuracy on the switching measure that complicated the interpretation of the switch cost RT measure. However, the present null results for switching ability are in line with the overall literature finding little proof of a separate mediating role of this ability in explaining age-related difference in TBPM task performance.</p> <hd id="AN0139548399-37">Predictors of within-age-group PM task performance differences</hd> <p>Unlike the between-age-group-based analyses, the within-age-group analyses revealed little evidence of the involvement of specific EFs for any of the three types of PM task. The only exception concerned the TBPM task, which was hypothesized to be the most cognitively demanding, in the adolescent group. Here, WM updating (RM-long) explained a significant portion of the variance in TBPM performance, in combination with the full model being significant. For the child and adult samples, only the combination of all cognitive functions could explain a significant portion of TBPM performance. The latter might reflect a different task approach in these samples relative to the adolescents. Alternatively, the (range in) capacity of each of the different EFs in these samples was either outside or fully within the EF demands of the PM task. Specifically, the WM-updating capacity of the best scoring children could have been still below the WM capacity requirements of the TBPM task, whereas the WM capacity for the worst scoring adults was still sufficient to meet the WM-updating demands of that task. Following this line of reasoning, adolescence is a period in which there <emph>is</emph> a relatively large variation in EFs, with some adolescents already having reached a much more mature EF level than other adolescents. This variation is responsible for the emergence of significant predictive associations between some aspects of EF and PM performance. Regardless of these speculations, in general, the differences in results from the between- and within-age-group analyses underscore the fact that the outcome of studies examining relatively broad or narrow age ranges may yield very different results when it comes to identifying EF correlates of PM performance. Such age-range differences, or differences in the relative frequency of specific ages in studies examining relatively broad age ranges, may be an important factor in explaining the rather mixed results of studies attempting to identify the specific EF(s) underlying age differences in PM performance.</p> <hd id="AN0139548399-38">Study limitations</hd> <p>One limitation of our study was that, except for interference control, we included only one task to measure the different EF components. This enhances task-specific aspects rather than the main intended (latent) construct to affect the results. However, it must be noted that we took great care to use tasks that are relatively well-accepted as process pure. The assumption of a relative process pureness is supported by the fact that our results of the between-age-group analyses are largely in agreement with other studies that did use multiple tasks to cover the EFs. However, the present results require replication using a study with a more extensive EF test battery, in order to be able to create more reliable latent EF constructs. For example, note that even for the two common tasks we used to assess interference control, the flanker and Stroop tasks, the correlation between performance scores was negligible, a finding that is quite common (Rouder, Kumar, & Haaf, [<reflink idref="bib36" id="ref96">36</reflink>]). Another limitation is the exclusive use of university students in the sample of young adults, which limits the generalizability of the present results to other populations. Another limitation is the use of a cross-sectional rather than a longitudinal design. Moreover, the results are based on laboratory PM tasks that require further validation using real-life PM tasks.</p> <hd id="AN0139548399-39">Conclusions</hd> <p>The results of the present study, examining the age groups of 7 to 9-year-old children, 12 to 14-year-old adolescents, and 17 to 23-year-old adults, confirmed the results of previous research concerning the mediating role of inhibitory processes in explaining age-group-related differences in focal EBPM task performance, and of WM updating and response inhibition in TBPM task performance. No significant contribution of a specific executive function was found to mediate performance in a non-focal EBPM task. Analyses at a within-age-group level revealed specifically WM updating to explain a significant portion of TBPM task performance in the group of adolescents. The joint results speak to the generalizability of results of some previous PM studies when analyses were performed at a between-age but not within-age group level. The differences in outcome dependent on the specific age ranges involved in the analysis might be important for explaining mixed results of previous studies regarding the precise components of executive functioning underlying performance on EBPM and TBPM tasks and that, in turn, might explain age-related performance differences on these tasks.</p> <hd id="AN0139548399-40">Disclosure statement</hd> <p>No potential conflict of interest was reported by the authors.</p> <ref id="AN0139548399-41"> <title> References </title> <blist> <bibl id="bib1" idref="ref29" type="bt">1</bibl> <bibtext> Azzopardi, B., Juhel, J., & Auffray, C. (2015). Aging and performance on laboratory and naturalistic prospective memory tasks: The mediating role of executive flexibility and retrospective memory. Intelligence, 52, 24 – 35. doi: 10.1016/j.intell.2015.06.007</bibtext> </blist> <blist> <bibl id="bib2" idref="ref10" type="bt">2</bibl> <bibtext> Ballhausen, N., Schnitzspahn, K. M., Horn, S. 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  Data: Age Differences in Prospective Memory: A Further Evaluation of the Executive Framework
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Cognition+and+Development%22"><i>Journal of Cognition and Development</i></searchLink>. 2019 20(5):680-701.
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  Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
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  Data: <searchLink fieldCode="DE" term="%22Age+Differences%22">Age Differences</searchLink><br /><searchLink fieldCode="DE" term="%22Memory%22">Memory</searchLink><br /><searchLink fieldCode="DE" term="%22Executive+Function%22">Executive Function</searchLink><br /><searchLink fieldCode="DE" term="%22Age+Groups%22">Age Groups</searchLink><br /><searchLink fieldCode="DE" term="%22Children%22">Children</searchLink><br /><searchLink fieldCode="DE" term="%22Adolescents%22">Adolescents</searchLink><br /><searchLink fieldCode="DE" term="%22Adults%22">Adults</searchLink><br /><searchLink fieldCode="DE" term="%22Task+Analysis%22">Task Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Interference+%28Learning%29%22">Interference (Learning)</searchLink><br /><searchLink fieldCode="DE" term="%22Responses%22">Responses</searchLink><br /><searchLink fieldCode="DE" term="%22Inhibition%22">Inhibition</searchLink><br /><searchLink fieldCode="DE" term="%22Predictor+Variables%22">Predictor Variables</searchLink><br /><searchLink fieldCode="DE" term="%22Performance%22">Performance</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Color%22">Color</searchLink><br /><searchLink fieldCode="DE" term="%22Reaction+Time%22">Reaction Time</searchLink><br /><searchLink fieldCode="DE" term="%22Visual+Stimuli%22">Visual Stimuli</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink>
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  Data: 10.1080/15248372.2019.1648268
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  Data: According to the executive framework of prospective memory (PM), age-related differences in PM performance are mediated by age-related differences in executive functioning (EF). The present study further explored this framework by examining which specific components of EF are associated with PM differences between and within three age groups. A group of children (7-9 years; N = 108), adolescents (12-14 years; N = 112), and adults (17-23 years; N = 106) performed focal- and non-focal event-based PM (EBPM) tasks, a time-based PM (TBPM) task, and tasks measuring EF components. Differences between age groups in focal EBPM, non-focal EBPM, and TBPM performance were mediated by, respectively, differences in interference control and response inhibition, performance on the ongoing task, and differences in working memory and response inhibition. However, within-age group analyses only revealed WM updating as significant predictor of TBPM performance in the adolescent group. These results support and further qualify the executive framework of PM. The differences in outcome dependent on the examined age range might be important for explaining mixed results of previous studies regarding the precise EF components underlying age-related PM task performance differences.
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        Value: 10.1080/15248372.2019.1648268
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      – Text: English
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        PageCount: 22
        StartPage: 680
    Subjects:
      – SubjectFull: Age Differences
        Type: general
      – SubjectFull: Memory
        Type: general
      – SubjectFull: Executive Function
        Type: general
      – SubjectFull: Age Groups
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      – SubjectFull: Children
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      – SubjectFull: Adolescents
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      – SubjectFull: Adults
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      – SubjectFull: Task Analysis
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      – SubjectFull: Interference (Learning)
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      – SubjectFull: Responses
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      – SubjectFull: Inhibition
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      – SubjectFull: Predictor Variables
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      – SubjectFull: Performance
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      – SubjectFull: Foreign Countries
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      – SubjectFull: Color
        Type: general
      – SubjectFull: Reaction Time
        Type: general
      – SubjectFull: Visual Stimuli
        Type: general
      – SubjectFull: China
        Type: general
      – SubjectFull: Stroop Color Word Test
        Type: general
    Titles:
      – TitleFull: Age Differences in Prospective Memory: A Further Evaluation of the Executive Framework
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Zhao, Xin
      – PersonEntity:
          Name:
            NameFull: Fu, Junjun
      – PersonEntity:
          Name:
            NameFull: Ma, Xiaofeng
      – PersonEntity:
          Name:
            NameFull: Maes, Joseph H. R.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2019
          Identifiers:
            – Type: issn-print
              Value: 1524-8372
          Numbering:
            – Type: volume
              Value: 20
            – Type: issue
              Value: 5
          Titles:
            – TitleFull: Journal of Cognition and Development
              Type: main
ResultId 1