Everyday memory and metacognitive intervention: a randomized controlled trial.

Everyday Memory and Metacognitive Intervention: A Randomized Controlled Trial - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Search Log in Primary site navigation Search Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice Neuropsychol Dev Cogn B Aging Neuropsychol Cogn . Author manuscript; available in PMC: 2026 Jun 3. Published in final edited form as: Neuropsychol Dev Cogn B Aging Neuropsychol Cogn. 2025 Jun 3;32(5):786–807. doi: 10.1080/13825585.2025.2513413 Everyday Memory and Metacognitive Intervention: A Randomized Controlled Trial Christopher Hertzog 1 , MacKenzie L Hughes 2 , Emily L Giannotto 3 , Clara W Coblenz 4 , Ethan Flurry 5 , Taylor Curley 6 , Ann Pearman 7 Author information Article notes Copyright and License information 1 Georgia Institute of Technology, School of Psychology 2 NORC at the University of Chicago 3 Emory University, School of Medicine, Department of Neurology 4 Emory University, School of Medicine, Department of Psychiatry, clara. 5 Mississippi University for Women, Department of Psychology & Family Science 6 711th Human Performance Wing, Air Force Research Laboratory 7 MetroHeath Medical Center ✉ Corresponding Author : Christopher Hertzog, PhD, christopher.hertzog@psych.gatech.edu Issue date 2025 Sep. PMC Copyright notice PMCID: PMC12354156  NIHMSID: NIHMS2085727  PMID: 40459026 The publisher's version of this article is available at Neuropsychol Dev Cogn B Aging Neuropsychol Cogn Abstract This study evaluated whether the Everyday Memory and Metacognitive Intervention (EMMI) improved everyday memory functioning and subjective memory among older adults. The EMMI uses a metacognitive approach to link awareness of situational cognitive demands to the selection and use of strategies to bypass cognitive constraints and to successfully achieve everyday goals. The randomized controlled trial randomly assigned participants to the EMMI group or an active control group trained in mnemonic strategies for word list memorization. We used an event-based ecological momentary assessment smartphone application to assess self-reported everyday memory failures during everyday life. We also evaluated group differences in pretest to posttest change on objective and subjective measures of memory. An intent-to-treat analysis of the 78 persons randomly assigned to conditions revealed no difference in measures assessed prior to the intervention. The final sample consisted of 30 EMMI participants ( M age = 75.83, SD = 4.68) and 32 control group participants ( M age = 74.94, SD = 4.38). There were no differences between the groups on everyday memory failures and prospective memory. Both groups showed significant increases in aspects of subjective memory ability from pretest to posttest, with the EMMI group producing greater improvements in memory self-efficacy. The control group differentially improved in associative memory after memory-strategy training. Although EMMI did not show the predicted everyday memory improvements, it still has potential to improve people’s everyday functioning by way of improving subjective experiences. Post-pandemic enhancements to the intervention could lead to demonstrable everyday memory successes. Keywords: Cognitive aging, everyday functioning, memory training, intervention, metacognition Gerontologists have long argued that intervention approaches that enable older adults to age in place would have salutary effects on older adults’ life satisfaction and well-being ( Sheffield, Smith, & Becker, 2013 ; Vanleerberghe et al., 2017 ). Although physical disabilities are a major barrier to older adults maintaining independent living arrangements, age-related cognitive changes, including dementia, represent another important constraint on older adults’ ability to conduct complex activities of daily living needed to manage everyday life. Interventions that support everyday cognitive function have the potential to prolong independent living in older adults experiencing normative age-related cognitive decline and may also prolong the span of independent living in individuals with mild cognitive impairment. Dominant approaches to cognitive training in older adults have not focused on enhancing everyday cognitive function by directly targeting relevant behaviors for self-management in the everyday ecology. Instead, they have followed the tradition of training cognitive processes relevant to performing in standardized cognitive tasks (e.g., memory for new associations, inductive reasoning, or spatial visualization; see Green & Bavelier, 2015 ; Plemons et al., 1978 ; Rebok et al., 2014 ) or intensive practice in cognitively demanding tasks ( Schmiedek et al., 2010 ) – see the review by Karbach and Verhaeghen (2014) . Unfortunately, there appears to be relatively little generalization of either cognitive training or practice to everyday cognition, with only a few possible exceptions ( Edwards et al., 2018 ). An alternative approach is to directly target everyday cognition and cognitively demanding instrumental activities via technological support (e.g., Czaja et al., 2020 ; Seelye et al., 2013 ) and/or behavioral interventions (e.g., Hunter & Kearney, 2018 ). Although some behavioral interventions have been incorporated into multi-modal cognitive training protocols (e.g., Cohen-Mansfield et al., 2015 ; Troyer et al., 2008 ; West et al., 2008 ), they have not typically been the primary focus of compensatory intervention studies. These approaches seek to modify behaviors to help older adults adapt to possible cognitive decline and ameliorate any practical consequences. For instance, Chandler and colleagues developed a memory notebook training that encouraged people to use calendars and other external aids linked to the notebook to help their everyday remembering ( Chandler et al., 2017 ). Schmitter-Edgecombe and colleagues created a similar approach using technological support for remembering to perform everyday tasks ( Farias et al., 2018 ). Recently, Hertzog et al. (2021) argued that a more comprehensive program targeting specific everyday cognitive strategies (e.g., use of spaced retrieval to learn names of newly met persons or reinforce behavioral intentions) could address the undesirable impacts of age-related cognitive challenges. The leitmotif of the program was a metacognitive approach to link awareness of situational cognitive demands to selection and use of strategies to bypass cognitive constraints and successfully achieve everyday goals. People typically use long-standing behavioral routines to support goal pursuit in everyday life. The metacognitive approach involves incorporating newly learned strategies, such as spaced retrieval, into new or modified behavioral routines to enhance the management of successful goal pursuit. For instance, a major challenge in everyday life involves prospective memory – remembering to pursue intentions (e.g., shop for needed food items) at appropriate times. Forming specific and concrete implementation intentions has been shown to be a highly successful approach to support older adults’ prospective memory (e.g., Chasteen et al., 2001 ; Henry et al., 2020 ) but they can only do so if they also develop a new habit of mind to form and retrieve such intentions at the right time and in appropriate contexts. This approach uses homework and group discussion of successes and challenges in using the new techniques to provide peer-based encouragement for changing everyday approaches to cognitive challenges. The intervention approach also assumes, based on available literature (e.g., Ouellette & Wood, 1998 ), that changing well-established habits and routines is difficult and prone to regression back to baseline. Hence, the approach includes two phases: a training phase and a shaping phase, in which new behaviors are shaped and reinforced as they are added to daily routines. Training began with a belief-restructuring unit designed to counteract negative age stereotypes about cognitive fitness while emphasizing that positive change in cognitive self-regulation is practical and achievable, then proceeded to train specific everyday cognitive skills, including spaced retrieval and implementation intentions. The shaping phase was implemented via phone conversations with participants to review, and, as necessary, modify how they were actually using the trained procedures. We conducted the first test of this intervention approach, with encouraging results ( Pearman et al., 2020 ). The intervention was delivered in-person over a one-week period with three half-day sessions. Following the training, participants completed ten shaping telephone calls with the research team over the course of one month to monitor their progress, analyze potential causes of memory failures, reinforce memory successes, and shape habit formation change. During the same month, participants reported their everyday remembering successes and failures in a nightly diary. People receiving the intervention were compared to a no-contact control group that received the intervention after the posttest. We found that the intervention differentially boosted measures of subjective memory self-efficacy and personal control over memory, while also leading to fewer days with reported everyday memory failures and more reported memory successes. We also included a lab-contact task to assess everyday prospective memory; people receiving the intervention were more likely to contact the lab at scheduled times than the control group and made the contacts closer to the exact scheduled time. The Present Study Here, we report on results from the next test of the intervention protocol. We ran a randomized controlled trial (RCT) of the intervention where participants were randomly assigned to either the Everyday Memory and Metacognitive Intervention group (EMMI group) or a memory-strategy control group (control group), which served as an active control. This control group mimicked more traditional cognitive intervention procedures from the existing literature and provided an important baseline to test our hypotheses about the benefits of training self-regulatory approaches for everyday memory. Importantly, both groups received the same belief restructuring module designed to combat negative aging stereotypes about inevitable cognitive decline while also promoting the idea that effects of aging on cognition can be managed effectively. In particular, this unit focused on enhancing a sense of memory self-efficacy ( Bandura, 1989 ) and personal control over memory (Lachman et al., 1991; Lineweaver & Hertzog, 1998 ). Giving this unit to both groups ensured that any benefit of the everyday memory intervention could not merely be due to fostering positive beliefs about oneself and cognitive aging. Outcome measures included performance on standard memory tasks (the target of traditional memory-strategy training) and measures of everyday memory from daily diary reports and ecological momentary assessment (EMA) data in which memory failures were reported in real-time using study-provided smartphones as well as subjective memory measures. We hypothesized that the mnemonic training provided to the control group would benefit performance on episodic memory tasks, as established in the existing literature, but would not improve everyday memory. In contrast, we hypothesized that the EMMI group would not show improvement in traditional memory tasks but would improve in everyday memory performance as well as on subjective memory experience. As we were preparing to launch the intervention study in 2020, the COVID-19 pandemic hit with full force, imposing a delay in launching the study and requiring us to redesign the intervention to be delivered virtually rather than in-person to adhere to safety protocols. The revised procedures are described in detail in the Research Design and Methods section. Research Design and Methods Data Availability This study was pre-registered and additional details about the pre-registration can be found on ClinicialTrials.gov ( https://clinicaltrials.gov/study/NCT04088136 ). The data are available upon request to the authors. Participants Participants were recruited from the Atlanta metropolitan area between March 2021 and October 2021. Sources of recruitment included the Adult Cognition Laboratory participant database; the ClinicalTrials.gov recruitment website; postcard mailouts to purchased ZIP codes in the greater Atlanta area; flyers posted around the greater Atlanta area; social media advertising; and participant referrals. Inclusion criteria included adults aged 70 to 85 years old; free from neurocognitive disorder diagnosis; scores equal to or above 31 on the Telephone Interview for Cognitive Status (TICS; Brandt et al., 1988 ; Elliott et al., 2020 ); fair, good, or excellent self-rated health; owning a computer or tablet; capable of attending Zoom video-conferencing sessions; experience with using a smartphone; and not having major impairments in hearing or vision. Sample Size Determination and Power Analysis Target sample size was determined based on funding constraints and statistical power analysis. We determined, based on the available funds, that we could afford participant fees for about 35 persons per group. Given the remote protocol, the requirement for substantial contact hours, and the intensive requirements for EMA assessment of everyday memory, we planned for some attrition from the study and based statistical power analysis on an expected sample size of 30 persons per group. A priori power was calculated for one-tailed tests, given that all of our hypotheses were directional (e.g., better prospective memory performance in the EMMI group). For outcome measures assessed at posttest only, we estimated the design had a .80 statistical power to detect a standardized mean difference favoring the EMMI group of d = 0.64, α = .05, 1-tailed. For outcome measures assessed at both pretest and posttest, we evaluated power to detect a Group × Time interaction using a directional null hypothesis. We predicted that the everyday memory intervention would reduce memory complaints and increase memory self-efficacy and perceived control from pretest to posttest in the EMMI group alone, leading to the prediction of group (Control vs. EMMI) × time (pretest, posttest) interactions. Conversely, we predicted that memory-strategy training in the control group would improve memory test performance, predicting a group (Control vs. EMMI) × time (pretest, posttest) interaction in the opposite direction. Given the special case of a 2 × 2 design, the hypothesized interactions are direct analogs of 1 df planned comparisons for differential gain for the two groups, and hence are also amenable to a directional hypothesis test, halving the critical p -value used for the typically reported F-test for interaction. We estimated that the design had .80 power to detect these interactions, assuming sample sizes of 30 and a training benefit effect size (difference in d ) of 0.75, α = .05, 1-tailed. Given specified a priori hypotheses on selected critical outcome measures, no adjustments of critical p -values were made, especially because we did not wish to sacrifice statistical power for a conservative control over the Type I error rate. Study Enrollment The chief research technician was responsible for recruiting candidates, screening eligibility, and then randomly assigning individuals who passed screening to one of the two intervention arms in the CONSORT flow diagram. Prior to pre-assessment, this technician randomized group assignment based on a pre-programmed sequence of randomly generated numbers while seeking to fill the schedule of homogenous EMMI or control groups set up to span the study’s anticipated evaluation period. Given the nature of the intervention, it was not possible to blind the chief technician or the interventionist to group membership. The chief technician worked with participants to ensure compatibility of their personal computer equipment to the programs generated for remote cognitive assessment, made contacts to confirm appointments, and conducted all pretest assessments. She also worked with participants at the start of each assessment and intervention session to ensure they had access to and could successfully engage all of the testing programs. The CONSORT flow diagram captures the recruitment and enrollment progress towards our target sample sizes. After initial recruitment and eligibility screening, there were 78 persons enrolled in the study and assigned at random to either the EMMI or control groups. This assignment preceded pretest assessment. Measures Primary Outcome Measures Everyday Memory Blips. For 16 consecutive days, participants reported specific everyday memory blips (i.e., defined for participants as “memory errors in everyday life”) using a study-provided Android smartphone application designed for the study. Memory blips were reported in an event-based EMA survey as soon as possible after they occurred, and then again in an evening survey completed each night of the study. Both surveys were accessed by participants using the smartphone application. More detail about the smartphone application and the surveys is provided below. Event-Based EMA Smartphone Application. Participants were asked to self-report each time they experienced a memory blip during the 16-day study period by opening the smartphone application and recording a brief description of the event. After providing a brief audio recording of the memory failure, they were asked several questions about the event, such as how stressful they found the memory failure and why they thought the memory failure occurred. These audio recordings were later accessed by the participant while reporting the day’s memory-related experiences in the Evening Survey. Participants could listen to their audio recorded descriptions of each memory failure to provide themselves with contextual information about each of the day’s reported blips. Evening Survey. Participants completed an Evening Survey hosted on Qualtrics each night before going to bed during the aforementioned 16-day period of the event-based EMA survey. Evening Survey questions included ratings on the participants’ thoughts, feelings, and actions across the day, their current emotions, and questions about their memory-related experiences. Participants were asked to consult the day’s audio-recorded memory blips in the smartphone application while completing the Evening Survey. In addition to reporting additional information on all of the memory blips they had previously reported via EMA, participants were asked to report any additional memory blips they had not already reported for that day. After memory-event reporting, participants used a checklist to indicate any trained strategies they had used that day and any difficulties they had encountered in doing so. Participants began recording memory blips following the final “shaping call”, or check-in call by researchers, after which participants received no further memory training from research staff (see Procedure below). The frequency of everyday memory blips was computed by dividing the total number of unique memory blips participants reported by the number of days during the same timeframe. Prospective Memory: Laboratory Contact Task. On the second day of the memory training, participants were given a set of four pre-scheduled times to contact the laboratory by participants’ choice of either phone call, text, or email during the last two weeks of their enrollment in the study. Two of the contacts were scheduled during the second week of completing the memory surveys (week 6) and two contacts were scheduled during the same week as posttest (week 7). Contact times were typically scheduled between 9:00 AM and 6:00 PM ET. However, participants were allowed upon assignment to reschedule any of these times if they had a conflict. No reminder or mention of this task was given following the final day of the group training. Prospective memory was then operationalized as (1) the number of completed contacts and (2) the deviation of each contact from the scheduled contact time. For the number of completed contacts, a binary variable indicated whether the participant completed the contact within a 15-minute window of the scheduled contact time. The contacts were scored as incomplete if the contact was not made or if the contact occurred outside of the 15-minute window. Participants could obtain a score between 0 and 4 completed contacts. For time deviation, the median absolute deviation of each contact was scored in relation to the scheduled contact time. For example, if a participant contacted the laboratory 3 minutes after their scheduled contact time, the call was assigned a score of 3. The median absolute deviation across the four contacts represented the score for each participant. For this measure, completed contacts were not evaluated if they were completed 60 minutes before the scheduled contact time or 120 minutes after the scheduled contact time. Participants could obtain a score between 0 and 120 minutes. Associative Recall Accuracy. A verbal paired associates test ( Dunlosky et al., 2005 ; Hertzog et al., 2013 ) was administered at pretest and posttest. Participants were asked to memorize a list of 30 word pairs (e.g., dog – spoon). Each word pair was displayed on the screen one at a time for eight seconds. After all words had been studied, participants’ memory was tested by cueing with the left-hand word; participants were to respond by providing the right-hand word of the pair. Participants received a different list at each test, and which list people were given was counterbalanced across participants. Serial Free Recall Accuracy. Participants were administered a serial presentation of unrelated words for a free recall test at pretest and posttest. Twenty-four English words were presented one at a time for four seconds each. After studying the list of words, participants made arithmetic calculations by completing a serial 7’s task where they were asked whether the number on the screen was 7 less than the previous number (starting at 97 and ending after reaching 60). After completing the arithmetic calculations, participants were given five minutes to recall as many words as they could remember. As with associative recall, participants received a different list at each test, with order of list use counterbalanced across participants. Simulated Everyday Memory Task. Participants completed two computer-administered everyday memory tasks ( Czaja et al., 2020 ; Harvey et al., 2020 ) at posttest. The tasks simulated using an automated teller machine (ATM) and refilling a prescription medication. For the current study, proportion correct on the ATM Task and the Prescription Refill Task were used as the measures of everyday memory performance. Story Recall. Participants completed a story recall task ( Dixon et al., 1993 ) at posttest. Participants were given five minutes to read a 102-word story and then eight minutes to recall as much of the story as they could remember. Total number of propositions recalled using a gist scoring criterion was used as the outcome variable. Participants could obtain a score of 0 to 53 with higher scores reflecting better story recall. Secondary Outcome Measures Personal Beliefs About Memory Inventory. Subjective memory beliefs were measured using the Personal Beliefs About Memory Inventory (PBMI; Lineweaver & Hertzog, 1998 ) at pretest and posttest. Participants rated their own memory on visual analog rating scales. Higher scores reflect better subjective memory. The study focused specifically on participants’ ratings of memory self-efficacy and perceived control over memory. Memory Functioning Questionnaire. Participants completed the Memory Functioning Questionnaire (MFQ; Gilewski et al., 1990 ) at pretest and posttest. The MFQ is a self-report questionnaire that assesses how people remember information within the context of their daily lives. The current study used the frequency of forgetting subscale of the MFQ, where individuals are asked to make judgements about the frequency in which different domains of remembering (e.g., names, faces) present a problem to the participant on a scale from 1 ( always ) to 7 ( never ). Participants could obtain a score between 1 and 7 with higher scores reflecting fewer problems with remembering. Memory Compensation Questionnaire. Participants completed the Memory Compensation Questionnaire (MCQ; Dixon et al., 2001 ) at pretest and posttest. The MCQ is a 45-item self-report questionnaire that assesses the ways in which an individual may or may not use memory compensation strategies. Using a scale ranging from 1 ( never ) to 5 ( always ), participants were asked to respond to items related to how frequently they use different memory compensation strategies (e.g., using a shopping list when you go shopping). The current study focused specifically on the internal and external strategy subscales of the MCQ. Participants could obtain a score between 1 and 5 with higher scores reflecting greater use of memory aids. Associative Recall: Strategy Use. Immediately after participants completed the associative recall test, they received a retrospective strategy self-report module based on Dunlosky and Hertzog (2001) . The word-pairs were again shown in the same order as the participant had originally studied them. For each item, participants reported which, if any, of the following strategies they had used: interactive imagery, sentence formation, other (often idiosyncratic personal associations), rote repetition, or none (no strategy). Participants could report multiple strategies. For each item, responses of imagery, sentence, or other associative strategy were coded as effective strategy use; others were coded as ineffective. The dependent variable was the total number of items that an individual reported using at least one effective strategy. Procedure The study included eight components spread across the course of seven consecutive weeks: (1) intake interview ( Hertzog et al., 2019 ); (2) pretest data collection; (3) four half-day memory intervention sessions across a two-week period; (4) six shaping telephone calls across a three-week period; (5) a 16-day measurement period, which included daily assessment of everyday memory-related events; (6) the Prospective Memory Laboratory Contact Task; (7) posttest data collection; and (8) debrief. Both groups followed identical study procedures. The only difference in study procedures between the two groups is the specific memory training provided (in component 3). Ordering of the study components can be found in Table 1 . Each component is described in more detail below. Table 1. Sequence of Study Procedures Component Timeframe Details (1) Intake interview Week 1 • 1-hour virtual interview to collect information on the participant’s current use of memory strategies (2) Pretest data collection Week 2 • Two 90-minute testing sessions scheduled on separate days • Tests and surveys were hosted on Qualtrics (3) Memory intervention sessions Weeks 3 & 4 • Four, 3-hour virtual training sessions held on Zoom video-conferencing • Participants completed in-session activities, group discussion, and homework (4) Shaping calls Weeks 3, 4, & 5 • Shaping calls were held the day after the first three training sessions (Weeks 3 & 4) • Three additional shaping calls were held the week following the completion of the memory training sessions (Week 5) (5) Measurement period (daily assessment of everyday memory- related events) Weeks 5 & 6 • Daily assessment of everyday memory took place for 16 days following the completion of the memory training sessions • The first measurement week included shaping calls (Week 5) • The second measurement week did not include shaping calls (Week 6) (6) Prospective Memory Laboratory Contact Task Weeks 6 & 7 • Two contacts were scheduled during the final week of the measurement period (Week 6) • Two contacts were scheduled during the final week of the study (Week 7) (7) Posttest data collection Week 7 • Two, 90-minute testing sessions scheduled on separate days • The tests and surveys were hosted on Qualtrics, except for the Everyday Memory Simulation tasks which was hosted in a separate online portal (8) Debrief Week 7 • Participants were debriefed by telephone after completion of the posttest sessions Open in a new tab Participants first completed an intake interview. The interview was held by video-conferencing and was conducted by a trained member of the research team. The purpose of the intake interview was to understand the ways in which participants used their memory in daily life, including memory strategies the participants were already using before the intervention. Next, participants completed the pretest sessions, which included two, 90-minute online testing sessions hosted on Qualtrics. Once the intake interview and pretest sessions were complete, participants joined the memory training sessions. The memory training sessions were held virtually over video-conferencing software (i.e., Zoom) for a 3-hour period on four weekdays scheduled over a two-week period. Sessions were held in small groups with three to six participants per group. Each session included a PowerPoint presentation led by the first author along with group discussions among participants. Participants in both groups were also given in-session, group-specific activities and homework assignments to be completed before the next training session. Shaping calls began during the same week as the training sessions. A research team member called participants the day following each training session to check-in on the homework and address any questions about the training session or strategies. Participants were trained on how to complete the event-based EMA survey and Evening Survey using the smartphone application during the final hour of the virtual memory training. Following completion of the memory training, the 16-day measurement period began. Participants reported their memory blips each day in the event-based EMA survey as well as in the Evening Survey. Use of the smartphone application was monitored by the research team who provided feedback as needed to participants on best practices for using the application. During the first week of the measurement period, participants received three additional shaping calls from the research team. During each shaping call, the research team member spoke to the participant about their memory-related experiences and answered any questions the participant may have had about the trained memory strategies, using the smartphone application, or about the study more generally. In addition, EMMI participants were provided additional coaching on how to incorporate the trained memory strategies into their everyday lives. The EMMI participants were encouraged to set goals to use the trained strategies in upcoming everyday life situations (i.e., grocery shopping) that might benefit from using one of the strategies. Research team members provided EMMI participants guidance and troubleshooting advice when memory errors occurred. The Prospective Memory Contact Task began during the final week of the 16-day measurement period. Participants were asked to complete two calls that week (week 6). Additionally, two online posttest sessions were scheduled the week following the conclusion of the formal measurement period, and the final two prospective memory contacts were scheduled during that same week (week 7). Finally, each participant received a debriefing call as soon as they completed the final posttest session. Participants could be compensated up to $190 for participating in the study. Accommodations to the Pandemic Prior to the start of the study, the pandemic began and the study had to be altered to adhere to COVID-19 regulations. Previous iterations of this intervention, particularly the training sessions, had been conducted as in-person group experiences ( Pearman et al., 2020 ). To adjust for the pandemic, all study experiences were moved to being held virtually using phone calls and video conferencing (specifically, Zoom) platforms. Individuals were only recruited if they had routine access to and experience with a computer that afforded use of Zoom meetings and administration of online tests and questionnaires via Qualtrics. All training, including the orientation to the use of an Android Smartphone for reporting everyday memory experiences using EMA, was conducted remotely. Using this approach also required us to shorten the intervention. Whereas previous iterations focused on in-person feedback on the use of EMMI techniques during the time of the group training sessions, feedback in the current study was provided remotely with a one-on-one shaping call involving a staff person and the participant. Given the delays in implementing the conversion to remote assessment, we also eliminated a planned pretest-posttest assessment of the EMA application and instead relied on posttest-only EMA assessment following the intervention. We were also forced to reduce the length and scope of the second-phase shaping period given budget and time constraints created by the pandemic. Statistical Procedure All analyses were conducted in SAS 9.4 ( SAS Institute, Inc., 2023 ) using either PROC TTEST for posttest-only comparisons and PROC MIXED to analyze the 2 × 2 Group × Time factorial using linear mixed models ( Littell et al., 2006 ). These multilevel models address missing data points by using all available data. For all independent-samples t-tests comparing intervention groups at either pretest or posttest, we estimated Cohen’s d for intervention group differences at either pretest or posttest as d = ( M Control - M EMMI ) / SQRT( MS Error ), as is typically computed. For the multi-level analyses of repeated measures, we did not generate often-recommended pseudo-R 2 statistics for effect size (e.g., Snijders & Bosker, 2012 ), given the desire to reflect effect size directly in standardized mean differences in an experimental design. Instead, we generated estimates of d for both main effects and the interaction. To compute estimates of d , we used differences in fitted least squares marginal means for Group or Time main effects or the Group × Time interaction-weighted contrast in the numerator, and the denominator was SQRT( MS Subjects ), reported from a repeated-measures SAS PROC GLM on each variable. Note this is not the error term for the repeated measures effect of Time, but rather a benchmark of residual individual differences after fitting the mean effects. In the case of the interaction effects, the desired effect size for interaction can be considered a difference between d for group differences at pretest and the d for group differences at posttest. Results Seventy-eight adults aged 75.77 years old ( SD = 4.65, range 67–86) were initially targeted for study enrollment. See the CONSORT flow diagram for additional information about participant recruitment, assignment, and retention. We conducted an initial intent-to-treat (ITT) analysis on the 78 participants designated for random assignment to conditions as a check on effectiveness of randomization. However, given that group assignment was designated prior to actual enrollment in the protocol, including pretest administration, the number of possible participants for ITT analysis was limited to those who actually received pretesting (see below). There were no reliable group differences on the demographic variables of age, t (76) = 0.45, p = .66; gender (χ 2 [1, N = 67] = 0.12, p = .73); ethnicity (χ 2 [1, N = 67] = 3.05, p = .08); race (χ 2 [4, N = 67] = 1.43, p = .84), education, t (65) = 0.68, p = .50; and self-rated health, t (65) = 0.17, p = .79. The cognitive pre-screen, the TICS, also did not differ by group, t (76) = 1.17, p = .25. For pretest variables, no group differences were found for any variable, including Associative Recall, t (65) = 0.29, p = .77; Associative Recall Strategy Use, t (60) = 0.91; p = .36; Serial Free Recall, t (65) = 0.73, p = .47; PBMI Specific Memory Self-Efficacy, t (65) = 1.74, p = .09; PBMI Present Control, t (65) = 1.04, p = .30; MFQ Frequency of Forgetting, t (65) = 0.61, p = .54; MCQ Internal, t (65) = 0.75, p = .45; and MCQ External, t (65) = 0.50, p = .62. The two groups were comparable in targeted outcome variables prior to the administration of the intervention. Of the 78 participants, five persons in each arm either failed to return digitally-signed informed-consent forms or otherwise could not be scheduled for pretesting before dropping out of the study. Five EMMI participants also dropped out of the study after completing the pretest sessions (see CONSORT plot ). One control participant was excluded from the study due to noncompliance with the strategy training instructions. CONSORT Flow Diagram. Open in a new tab The final sample included 62 participants: 30 EMMI participants ( M age = 75.83, SD = 4.68, range = 67–84) and 32 control participants ( M age = 74.94 years, SD = 4.38, range = 70–84). Table 2 reports on demographic variables for these groups. There were no group differences in any of the participant demographics, including age ( t [60] = 0.78, p = .44), gender (χ 2 [1, N = 62] = 0.003, p = .96), ethnicity (χ 2 [1, N = 62] = 2.20, p = .14), race (χ 2 [3, N = 62] = 2.07, p = .56), years of education ( t [60] = −0.14, p = .89), or self-rated health ( t [60] = 0.11, p = .91). The groups also did not significantly differ on the TICS ( t [60] = −1.14, p = .26). Table 2. Sample Characteristics by Intervention Group: Final Sample EMMI ( n = 30) Control ( n = 32) Variable M ( SD ) or N (%) M ( SD ) or N (%) Cohen’s d Age 75.83 (4.68) 74.94 (4.38) 0.20 Gender Female 18 (60.00%) 19 (59.38%) NA Male 12 (40.00%) 13 (40.63%) Ethnicity Hispanic or Latin American 0 (0.00%) 0 (0.00%) NA Non-Hispanic 28 (93.33%) 32 (100.00%) Prefer Not to Answer 2 (6.67%) 0 (0.00%) Race African American 4 (13.33%) 5 (15.63%) NA American Indian or Alaska Native 0 (0.00%) 1 (3.13%) White 25 (83.33%) 26 (81.25%) Other Race 1 (3.33%) 0 (0.00%) Years of Education 16.82 (3.60) 16.94 (3.23) 0.04 Self-Rated Health 3.87 (0.78) 3.84 (0.85) 0.04 Telephone Interview for Cognitive Status 34.93 (2.23) 35.56 (2.12) 0.29 Open in a new tab Note. Cohen’s d = (M Control – M EMMI )/SD Pooled . No statistically significant group differences on participant demographics. We also evaluated group differences in pretest measures to assess the comparability of the groups prior to the intervention. Table 3 reports means and standard deviations on all primary and secondary pretest measures, along with effect size statistics. The sample means tended to favor the control group, with Cohen’s d generally in the nil-to-small range, and none of the group differences were statistically reliable. The largest difference, for PBMI Specific Memory Self-Efficacy, yielded a nonsignificant result, t (64) = 1.65, p = .104. The nonsignificant trend favoring control participants in TICS scores were mirrored in pretest data on most other variables. Table 3. Pretest and Posttest Means, Standard Deviations, and Cohen’s d Effect Size Statistics for Primary and Secondary Outcomes by Intervention Group Pretest Posttest EMMI Control EMMI Control Measure N M ( SD ) N M ( SD ) Cohen’s d N M ( SD ) N M ( SD ) Primary Outcome Measures Everyday Memory Blips – – – 30 0.55 (0.57) 32 0.62 (0.71) Laboratory Contact Task: Number of Completed Calls – – – 30 2.77 (1.10) 32 2.97 (1.09) Laboratory Contact Task: Median Absolute Deviation a – – – 29 4.45 (9.11) 31 4.19 (5.87) Associative Recall Accuracy 30 0.52 (0.20) 32 0.53 (0.22) 0.13 27 0.55 (0.25) 29 0.66 (0.19) Serial Free Recall Accuracy 29 0.27 (0.29) 32 0.31 (0.23) 0.22 29 0.37 (0.28) 32 0.44 (0.28) Simulated Everyday Memory Task: ATM Task – – – 25 0.97 (0.01) 28 0.96 (0.03) Simulated Everyday Memory Task: Prescription Refill Task – – – 24 0.96 (0.04) 27 0.96 (0.04) Story Recall – – – 30 30.77 (8.95) 31 29.74 (10.71) Secondary Outcome Measures Personal Beliefs About Memory Inventory: Specific Memory Self-Efficacy Scale 30 0.65 (0.13) 32 0.71 (0.14) 0.41 30 0.72 (0.12) 31 0.73 (0.14) Personal Beliefs About Memory Inventory: Memory Control Scale 30 0.79 (0.15) 31 0.80 (0.13) 0.27 30 0.90 (0.09) 31 0.89 (0.10) Memory Functioning Questionnaire: Frequency of Forgetting Subscale 30 4.95 (0.91) 32 5.09 (0.82) 0.19 30 5.04 (0.92) 32 4.97 (0.81) Memory Compensation Questionnaire: Internal Strategy Scale 30 1.92 (0.62) 32 2.01 (0.65) 0.17 30 2.31 (0.58) 32 2.26 (0.63) Memory Compensation Questionnaire: External Strategy Scale 30 3.34 (0.46) 32 3.28 (0.50) −0.04 30 3.38 (0.41) 32 3.30 (0.44) Associative Recall: Strategy Use 29 0.61 (0.21) 29 0.66 (0.22) 0.34 25 0.61 (0.22) 29 0.75 (0.17) Open in a new tab Note. a Task excludes participants who completed 0 out of 4 contacts. Cohen’s d = ( M Control – M EMMI )/ SD Pooled . Table 3 reports posttest means and standard deviations for all posttest-only outcome variables. Table 4 reports effect size statistics for all primary and secondary outcomes. Table 4. Cohen's d Effect Size Statistics for Posttest Only and Pretest-Posttest Primary and Secondary Outcomes Posttest Only Primary Outcome Measures Group Everyday Memory Blips 0.11 Laboratory Contact Task: Number of Completed Calls 0.18 Laboratory Contact Task: Median Absolute Deviation a 0.03 Simulated Everyday Memory Task: ATM Task 0.11 Simulated Everyday Memory Task: Prescription Refill Task 0.03 Story Recall 0.10 Pretest-Posttest Outcome Measures Group Time Group × Time Primary Outcome Measures Associative Recall Accuracy 0.21 0.29 0.29 Serial Free Recall Accuracy 0.17 0.34 0.09 Secondary Outcome Measures Personal Beliefs About Memory Inventory: Specific Memory Self-Efficacy Scale 0.18 0.24 0.23 Personal Beliefs About Memory Inventory: Memory Control Scale 0.03 0.65 0.21 Memory Functioning Questionnaire: Frequency of Forgetting Subscale 0.03 0.01 0.19 Memory Compensation Questionnaire: Internal Strategy Scale 0.02 0.39 0.17 Memory Compensation Questionnaire: External Strategy Scale 0.12 0.05 0.02 Associative Recall: Strategy Use 0.36 0.17 0.26 Open in a new tab Note. a Task excludes participants who completed 0 out of 4 contacts. Primary Outcomes Everyday Memory Blips The frequency of reported memory blips was evaluated using a mean daily frequency of reported memory blips following the final shaping call. Reported failures were slightly lower in the EMMI group, M = 0.55, SD = 0.57, than in the control group, M = 0.62, SD = 0.71, but these differences were not significant, t (60) = −0.43, p = .67. Prospective Memory Laboratory Contact Task: Number of Completed Contacts The number of successfully completed lab contacts (range 0–4) was evaluated for group differences. The EMMI group completed an average of 2.77 calls ( SD = 1.10) and the control group completed an average of 2.97 calls ( SD = 1.09), but these differences were not significant, t (60) = −0.72, p = .47. Prospective Memory Laboratory Contact Task: Median Absolute Deviation from Scheduled Contact Time For successfully completed lab contacts, a median absolute deviation score (in minutes) was computed for each participant to assess how close in time the completed contacts were to the scheduled times. The control group ( M = 4.19, SD = 5.87) was slightly more punctual than the EMMI group ( M = 4.45, SD = 9.11), but this difference was not significant, t (58) = 0.13, p = .90. Associative Recall Accuracy Associative recall scores from pretest to posttest were analyzed in a Group × Time mixed model, with repeated measures on the second factor. There was no overall group difference, F (1,60) = 1.28, p = .26, but there were robust increases in recall from pretest to posttest, F (1,60) = 6.80, p = .012, and a Group × Time interaction, F (1,60) = 2.83, one-tailed p = .049. The control group manifested a greater increase in recall accuracy than the EMMI group (see Figure 1 ). Indeed, as hypothesized, the increase in associative recall was reliable with a simple main effect test for the control group, F (1,60) = 9.53, p = .003, but not for the EMMI group, F (1,60) = 0.41, p = .522. Figure 1. Paired Associates Recall at Pretest and Posttest by Intervention Group. Open in a new tab EMMI = Everyday Memory and Metacognitive Intervention Group. Error bars are one standard error of the mean (SEM). Serial Free Recall Accuracy Free recall scores from pretest to posttest were analyzed in a Group × Time mixed model, with repeated measures on the second factor. Posttest recall data for one EMMI participant were lost due to computer failure. There was no overall group difference, F (1,59) = 0.92, p = .34, but there were robust increases in recall from pretest to posttest, F (1,59) = 8.41, p = .005, without a reliable Group × Time interaction, F < 1. Although both groups showed an increase in recall scores at posttest, the control group manifested a reliable increase according to a simple main effect test, F (1,59) = 5.72, one-tailed p = .010, whereas the EMMI group produced a smaller effect, F (1,59) = 2.98, p = .049. Simulated Everyday Memory Task: ATM Task The ATM Task was assessed only at the posttest. Due to software issues, nine individuals could not complete the task. The dependent variable was the proportion of correct executions of instructed actions. There were no group differences in proportion correct on the task, t (51) = 0.41, p = .69. EMMI participants ( M = 0.97, SD = 0.01) manifested nearly the same proportion correct as the control participants ( M = 0.96, SD = 0.03). Simulated Everyday Memory Task: Prescription Refill Task The Prescription Refill Task was also assessed only at posttest, with data missing for 11 participants due to software issues. The dependent measure was the proportion of correct refills. There were no group differences on this task, t (49) = −0.09, p = .93. EMMI participants ( M = 0.96, SD = 0.04) had nearly the same proportion correct as the control participants ( M = 0.96, SD = 0.04). Story Recall Story recall was only administered at posttest. Story recall data were missing from one control participant. The total number of propositions recalled by a gist scoring criterion did not differ between the two groups, M EMMI = 30.77 ( SD = 8.95) versus M Control = 29.74 ( SD = 10.71), t (59) = 0.40, p = .69. This result was expected because the trained memory strategies are of little use for comprehending and remembering prose (e.g., Cavallini et al., 2010 ). Secondary Outcomes Personal Beliefs about Memory Inventory: Specific Memory Self-Efficacy Scale PBMI Specific Memory Self-Efficacy scores from pretest to posttest were analyzed in a Group × Time mixed model, with repeated measures on the second factor. There was no overall group difference, F (1,60) = 1.02, p = .32, but there were increases in memory self-efficacy from pretest to posttest, F (1,60) = 18.50, p < .0001, and a Group × Time interaction, F (1,60) = 4.56, p = .037. The EMMI group manifested a greater increase in memory self-efficacy than the control group (see Figure 2 ). Figure 2. Personal Beliefs About Memory Inventory: Specific Memory Self-Efficacy at Pretest and Posttest by Intervention Group. Open in a new tab EMMI = Everyday Memory and Metacognitive Intervention Group. Error bars are one standard error of the mean (SEM). Personal Beliefs about Memory Inventory: Memory Control Scale PBMI Present Control scores from pretest to posttest were analyzed in a Group × Time mixed model, with repeated measures on the second factor. There was no overall group difference, F (1,60) = 0.02, p = .89, but there were increases in memory control from pretest to posttest in both groups, F (1,60) = 36.05, p < .0001. There was no significant Group × Time interaction, F (1,60) = 0.95, p = .33, indicating that the increases in perceived present memory control were comparable for both groups. Memory Functioning Questionnaire: Frequency of Forgetting Scale The MFQ Frequency of Forgetting scale was administered at both pretest and posttest. The repeated measures analysis yielded no significant effects, including Group, F (1,60) = 0.02, p = .88, Time, F (1,60) = 0.04, p = .84, and the Group × Time interaction, F (1,60) = 2.58, p = .11. Memory Compensation Questionnaire: Internal Strategy Scale MCQ Internal Strategy scores from pretest to posttest were analyzed in a Group × Time mixed model, with repeated measures on the second factor. There was no overall group difference, F (1,60) = 0.01, p = .93. However, there were robust increases in the use of reported internal mnemonics from pretest to posttest, F (1,60) = 34.45, p < .0001 with no Group × Time interaction, F (1,60) = 1.65, p = .20. That is, the increases in use of reported internal memory strategies were roughly similar for both groups. Memory Compensation Questionnaire: External Strategy Scale There were no significant effects for the MCQ External Strategy Scale, with Group, Time, and Group × Time sources all yielding F < 1. Associative Recall: Strategy Use Associative recall strategy use changes from pretest to posttest were analyzed in a Group × Time mixed model, with repeated measures on the second factor. There was a significant group difference, F (1,59) = 4.04, p = 0.049, with the control group reporting using more high-quality associative encoding strategies than the EMMI group at both pretest and posttest. There was no significant effect of time from pretest to posttest, F (1,59) = 2.33, p = .13, nor a significant Group × Time interaction, F (1,59) = 1.40, p = .24. Discussion and Implications The results from this study were disappointing with respect to the primary outcome measures we were targeting. There were no group differences in either (1) the critical everyday memory outcome measures of EMA-reported and Evening Survey-reported memory errors, or (2) successful laboratory contacts in the prospective memory task. Thus, we found no evidence supporting the effectiveness of EMMI for everyday memory performance. As predicted, we did find that memory strategy training resulted in a differential improvement in associative recall performance in the control group. This benefit was also accompanied by a greater reported use of effective associative encoding strategies. We also saw evidence of better serial free recall performance in the control group. The effects were not large, consistent with the relatively limited amount of mnemonic strategy training, but they supported the claim that our strategy training approach was effective. Notably, both groups showed improvements in perceived memory control and memory self-efficacy from pretest to posttest, suggesting that the belief restructuring module given to both groups was effective, and that the experienced effects of successful remembering did modify older adults’ negative beliefs about their memory abilities. Given that the improvement in perceived control was seen in both groups, we cannot rule out other reasons for those changes, such as reactive effects or demand characteristics. However, the EMMI group showed differential improvement in the PBMI Specific Memory Self-Efficacy scale, indicating that the everyday skills intervention promoted more positive memory self-efficacy beliefs. This outcome also mitigates to some degree against nonspecific other explanations for subjective memory change. In any case, the failure to detect everyday memory benefits in the EMMI group cannot be attributed to a failure to change negative beliefs about aging and memory. The improved memory self-efficacy in the EMMI group is consistent with findings by Chandler et al. (2017) regarding their memory-notebook intervention. They found evidence of improved subjective memory but little evidence that other aspects of their multimodal intervention had been effective in improving everyday memory. Clearly, the standard interpretation of this study’s RCT results is that the EMMI did not work as expected in improving everyday memory. We acknowledge that fact. However, it is still possible that the procedural modifications we made to address the social distancing requirements of the pandemic (and to reduce burden on participants and staff) – including removal of in-person classes and reductions in the magnitude and nature of the second-phase shaping exercises and homework – may have undercut the intervention and inhibited its application in participants’ everyday cognitive experiences. Converting to remote presentation may have reduced the benefits of direct social interaction among participants when discussing their use of intervention techniques during homework review; it certainly appeared informally that the remote group discussions were less lively than in our previous in-person intervention ( Pearman et al., 2020 ). There is some evidence that adding social interaction to memory interventions benefits older adults (e.g., Izhak et al., 2025 ). Going to fully remote administration also resulted in interested older adults lacking sufficient computer experience being unable to enroll in the study; it is possible that this restriction created a more select sample less in need of the EMMI behavioral intervention. Moreover, the pandemic altered patterns of daily living such that individuals’ need for and ability to use EMMI-trained strategies in the broader ecology may have been reduced. For instance, one of the homework tasks for the EMMI group was to go out and meet a new person and learn their name using spaced retrieval. We had to adjust this assignment to learning a different type of information (e.g., a fact from a newspaper or a person from television). Further, the shaping procedures we implemented for controls to equate on the contacts and behaviors required by the EMMI shaping procedure may have bolstered their generalization of mnemonics to everyday remembering. It remains possible, then, that a more intensive intervention protocol with revamped shaping procedures would have shown benefits similar to those seen by Pearman et al. (2020) . Finally, remote assessment of cognition is prone to participant behaviors to enhance performance such as the inappropriate use of external aids to record target words during study (see Atkins et al., 2022 ). Such behaviors would increase experimental error and work against finding significant group differences in memory test performance. Nevertheless, we must conclude that the intervention as implemented in this study did not result in improved everyday memory performance on our primary targeted measures targeting assessment of everyday memory in the natural ecology. We note four other aspects of the study relevant to possible redesign of the intervention. First, our outcome measures focused on reported memory failures rather than successes. In part, this focus occurred because pilot work suggested that individuals do not necessarily monitor or register everyday memory successes as successful events per se and hence find it difficult to report on them. Second, focusing on EMA methods to register use of trained strategies as they occur could have both revealed training benefits as well as helped move those strategies from ideas to habits. Additional measurement work would be needed to test this idea. Third, our assessment could have benefitted from more information about how people were implementing the EMMI strategies to enable a forensic analysis of everyday memory failures and whether the EMMI approach reduces their frequency. The use of intensive interview or think-aloud simulations might reveal suboptimal strategy implementations and how to redress them. Fourth, this paper does not consider individual differences in training benefits. Empirical studies have shown individual differences in cognitive-training benefits (e.g., McArdle & Prindle, 2008 ). Indeed, we view the present intervention as requiring relatively intact levels of self-regulatory skills (and perhaps, good functioning of prefrontal cortex known to be involved in both metacognition and strategic self-regulation; Chua et al., 2009 ). We are currently conducting some pilot analysis, constrained by small sample size, to identify which persons benefited the most from the intervention and to search, after the fact, for possible explanations for their behavior and its benefits. In sum, this study found little evidence that our everyday memory intervention reduced everyday memory errors but the outcomes support the use of this intervention’s approaches as a way of assessing and improving subjective memory. We continue to believe the EMMI approach can in principle be highly effective in improving everyday memory but recognize the need to make adjustments, including (1) bringing back important features of the pre-pandemic protocol and (2) improving measurement of memory successes in order to recognize this effectiveness. Acknowledgements: We thank Georgia Tech’s Institute of People and Technology for loaning this project Android burner phones that were provided to participants during EMA assessment. Scott Robertson programmed all EMA-related apps. We also gratefully acknowledge the technicians who made this work possible. Joshua Paredes assisted with programming Qualtrics apps for remote computer assessment. Jada Allen and Cassandra Spiegl qualitatively coded EMA data and story recalls. Alysha Naran assisted with support during intervention sessions. They also assisted in participant scheduling. Additional research support was provided by Ellen Murphy. Katie Thackston, Vikram Sahgal, Rohan Chandrashekhar, Jenna Harrington, Grace Ahn, Elena Cabrera, Jenny Kang, Arantza Echauz, Delaney Elder, Sara Ferez- Henry Yun, Olivia Herrmann, and Kenley Tyler. Funding: This work was supported by a grant from the National Institute on Aging [5R21AG059942-02 to C.H.] and in part by a Ruth L. Kirschstein National Research Service Award Institutional Research Training Grant from the National Institutes of Health (National Institute on Aging) Grant [5T32AG000175 to E.G. and T.C]. Footnotes Conflict of Interest : None reported. Contributor Information Christopher Hertzog, Georgia Institute of Technology, School of Psychology. MacKenzie L. Hughes, NORC at the University of Chicago. Emily L. Giannotto, Emory University, School of Medicine, Department of Neurology. Clara W. Coblenz, Emory University, School of Medicine, Department of Psychiatry, clara.. Ethan Flurry, Mississippi University for Women, Department of Psychology & Family Science. Taylor Curley, 711th Human Performance Wing, Air Force Research Laboratory. Ann Pearman, MetroHeath Medical Center. Data Availability: The data are available upon request to the authors. This study was pre-registered. Additional details about the pre-registration can be found on ClinicialTrials.gov ( https://clinicaltrials.gov/study/NCT04088136 ). References Atkins AS, Kraus MS, Welch M, Yuan Z, Stevens H, Welsh-Bohmer KA, & Keefe RSE (2022). 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