One-year Cognitive Outcomes From A Multiple Realworld Skill Learning Intervention With Older Adults Part 1

Novel skill learning has been shown to have cognitive benefits in the short term (up toa few months). Two studies expanded on prior research by investigating whether learning multiplenovel real-world skills simultaneously (e.g. Spanish, drawing, music composition), for a minimum ofsix hours a week, would yield 1-year cognitive gains.

Cognition is an important aspect of human thinking, which is directly related to our learning, memory, judgment, and decision-making. The benefits of cognition are very significant. It can help us better understand and cope with the world and life and improve our thinking ability and adaptability. At the same time, cognition is also closely related to memory and has the effect of actively promoting memory.

Finally, cognitive abilities can also improve self-management and learning strategy formulation capabilities, thereby helping us better control our learning progress and methods. In learning, it is very important to develop appropriate learning strategies, because only through scientific methods and steps can it be easier to understand and master knowledge. Through cognitive exercise, we can understand our learning habits and methods, better develop personalized learning strategies, and successfully apply them to learning and memory.

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Following a 3-month multi-skill learning intervention, Study 1 (N=6, Mage=66years, SDage= 6.41) and Study 2 (N=27, Mage=69years, SDage=7.12) participants completed follow-up cognitiveassessments 3months, 6months, and one year after the intervention period. Cognitive assessmentstested executive function (working memory and cognitive control) and verbal episodic memory.

Linear mixed-effects models revealed improvements in multiple cognitive outcomes frombefore the intervention to the follow-up timepoints. Specifically, executive function increased from the pre-test to the 1-year follow-up for both studies (an effect driven mostly by cognitive control scores).

Our findings provide evidence that simultaneously learning real-world skills can lead tolong-term improvements in cognition during older adulthood. Future work with diverse samplescould investigate individual differences in gains. Overall, our findings promote the benefits of lifelonglearning, namely, to improve cognitive abilities in older adulthood.

Promising research over the past few decades has revealed thatfluid cognitive abilities (e.g. working memory, cognitive control, episodic memory) can increase in older adulthood (seeHertzog et al., 2008; Nyberg & Pudas, 2019). In addition to cognitive training, which uses targeted computer tasks or strategytraining for specific abilities (see Lampit et al., 2014 for areview), cognitive engagement interventions that use real-world skills such as photography (Noice & Noice, 2013; Parket al., 2014) have demonstrated cognitive gains in older adulthood. 

Cognitive training studies using computer tasks havedemonstrated increases in trained abilities immediately following the intervention (i.e. Jaeggi et al., 2014;  Kueider et al.,2012), although evidence of gains in non-trained abilitiesseems to be rare (see Simons et al., 2016). Only a handful ofcognitive engagement interventions, where older adults areactively working with new materials and instructors, exist (e.g.Bugos et al., 2007; Chan et al., 2016; Leanos et al., 2020; Parket al., 2014; Stine-Morrow et al., 2008). 

Among these studies,the results generally support cognitive gains in fluid abilitiesas measured via computer tasks (see Berggren et al.,2020), even though the engaged tasks were real-world skills,such as photography and piano playing.

Despite these encouraging findings, evidence of longer-term (at least one year) maintenance of, or improvementsin, cognitive gains is rare. Only a small subset of cognitive training studies have investigated long-term intervention effects(Nguyen et al., 2019). The ACTIVE study is a landmark project that has demonstrated very long-term effects of cognitivetraining through two-, five-, and ten-year follow-ups (Ball et al.,2002; Rebok et al., 2014; Willis et al., 2006). The ACTIVE studyplaced participants into one of three cognitive training groups(memory, reasoning, and speed of processing); training wasprovided in ten sessions over six weeks. 

Eleven monthsafter completing the intervention, randomly selected participants received booster training consisting of four sessions over three weeks. By the two-year follow-up, participantsdemonstrated overall maintenance of trained cognitivedomains (Ball et al., 2002). By the ten-year follow-up, improvements in trained tasks were sustained in the reasoning andspeed-of-processing groups, but not in the memory group(Rebok et al., 2014). 

Another cognitive training study (Chambonet al., 2014), which focused on episodic memory and attention,found that at the six-month follow-up, older adults maintainedtheir episodic memory via free recall from the post-test. However,maintenance of other trained abilities in this intervention(visual recognition, visuospatial recognition) was not observed.Chambon et al. (2014) posited that tasks with a high mentalload (such as those for episodic memory) may be more likelyto provide longer-term benefits.

With the small number of real-world skill learning intervention studies compared to cognitive training studies, there arevery few engagement interventions that have included follow-up periods. In one study, Bugos et al. (2007) found that threemonths after finishing personalized piano training, older adults continued to show increases in their working memory ability.Notably, the participants did not practice the exact memory tasksfrom the assessments in the skill learning intervention, and therefore these findings provide evidence for far transfer of cognitiveabilities from a complex real-world skill to a pared-down task foran assessment. 

Additionally, a small subset of Synapse participants (Park et al., 2014) was selected to participate in fMRI scansat the intervention pre-and post-testing and for a one-year follow-up scan. Scans at the one-year follow-up timepoint revealedthat the participants had maintained the improvements in thebrain regions that had improved immediately after the skill learning intervention (McDonough et al., 2015).

How might real-world skill learning promote long-term cognitivegains? A novel lifespan theory provides an approach for maximizing long-term cognitive gains in older adulthood, perhaps beyondwhat is currently known (Wu et al., 2017; Wu & Strickland-Hughes,2019). This theory posits that providing older adults with rich learning environments akin to learning environments from childhoodmay yield considerable immediate and long-term cognitive gains.
In contrast to practicing or training specific abilities using computertasks or cognitive strategies, the theory proposes six key ingredients that allow learning experiences to promote cognitive growth:open-minded input-driven learning (e.g. learning completely newskills), individualized scaffolding (tailored help from instructors),growth mindset (belief that one's abilities can improve with effort),forgiving environment (being allowed to make mistakes, no negative stereotypes about novel learning), serious commitment tolearning (e.g. spending several hours a week to learn difficult skills),and learning multiple skills simultaneously. 

Evidence for this theory thus far has largely been circumstantial. For example, learning experiences earlier in the lifespanin terms of education are one of the strongest predictors ofcognitive outcomes in late life (e.g. Park et al., 2014; Ritchie &Tucker-Drob, 2018; Vemuri et al., 2014; although see Nyberget al., 2021). Real-world skill-learning interventions with olderadults typically include learning only one skill at a time (Bugoset al., 2007; Chan et al., 2016; Park et al., 2014), but studies thatinclude some of the six factors have provided promising evidence to support the novel theory, although mostly in terms ofshort-term effects. If older adults are provided with aspects ofthe rich learning environment for skill learning afforded to children, would we observe cognitive gains over the long term?
Leanos et al. (2020) reported one of the first skill-learning interventions that included learning at least three new real-world skillssimultaneously. As one of the first tests of the novel theory,Leanos et al. (2020) taught new skills, such as Spanish, drawing,and music composition, to community-dwelling healthy olderadults (aged 55+) for several hours, multiple days a week, over three months. Immediately following the end of theintervention, participants exhibited significant improvements in cognitive abilities: older adult participants' post-test cognitivescores were similar to a cross-sectional sample of middle-agedadults' baseline cognitive scores (Mage=42.36, SDage=5.79).Although learning multiple skills concurrently promoted robustgains in cognitive abilities by post-test, it is unclear whether theseimprovements would be sustained over the long term (one yearlater). If engaging in intervention activities is important for maintaining intervention outcomes, the considerable time commitment needed to do so (Leanos et al. 2020 reported approximately15 hours per week) may not be sustainable.

The present study investigated whether learning multiple newreal-world skills simultaneously would lead to long-term (one year) gains in cognitive abilities. These include executive functions of cognitive control (one's ability to adapt behaviors tocontinuously changing environments or information; considered in this manuscript via inhibition and flexibility tasksexplained below), working memory, and verbal episodic memory. 

Specifically, we predicted that overall cognitive compositescores, as well as the sub-components of the cognitive batterymeasuring working memory and cognitive control, would significantly improve compared to pre-test assessments for Study1 and baseline assessments for Study 2, as described in Leanoset al. (2020). Regarding verbal episodic memory, we predictedthat both studies would demonstrate improvements in theimmediate list recall (RAVLT) measure for all three follow-upscompared to pre-test (Study 1) and baseline (Study 2) assessments. We predicted that Study 2 also would reveal improvements for the digit span task across the three follow-up time points compared to the baseline. 

Cognitive abilities in twostudies with older adults were assessed up to one year aftercompleting the intense multi-skill learning interventionreported by Leanos et al. (2020). The first study included a feasibility sample, and the second study included a larger sampleaimed to replicate the pattern of findings from the feasibilitysample. Long-term gains would indicate the potential for cognitive growth in older adulthood, perhaps in some ways likecognitive growth observed earlier in the lifespan within richlearning environments.

This study received ethical approval from the Institutional ReviewBoard at the University of California, Riverside (IRB protocolnumber HS-17-211). All participants provided written informedconsent before their participation at the first assessment time point. This consent process was conducted with a trained member of the research team and explained voluntary participation,confidentiality and privacy, risks and benefits, results communication, and general procedures of the study. Participants wereprovided with a copy of their signed consent form.

We conducted two separate studies with older adults:Intervention Study 1 included six participants (67% female, Mage= 66.33years, SDage=6.41, Mdnage=68.5, range=58–74yearsold at pre-test), and Intervention Study 2 included 27 participants (67% female, Mage=69.44years, SDage= 7.12, Mdnage=69,range=58–86years old at baseline) (see Figure 1 for recruitment and attrition). Table 1 details the demographic information from these two studies. Participants were recruitedfrom the community via an existing aging database of potentialparticipants, neighborhood online message boards, local community programs, and word of mouth. 

Inclusion criteria wereas follows: 55+ years of age, fluent in English, had a normal orcorrected-to-normal vision, and self-reported no diagnostichistory of a cognitive condition (e.g. mild cognitive impairment).All participants (Studies 1 and 2) were compensated $40 foreach assessment session and were able to retain all supplies(apart from iPads, which were university property) provided tothem from the classes, such as notebooks and writing utensils,sketchbooks, and art supplies.

Participants in Study 1 (feasibility sample) all learned the samethree skills (Spanish, iPad operation, and painting) over 15 weeks. Weekly training included 2-hour classes foreach skill and an additional 1-hour lecture/discussion sessionwhich covered topics such as motivation, growth mindset, barriers to learning, and successful aging. Attendance and hoursinvolved in intervention-related activities (i.e. classes and homework) were tracked for analysis purposes. Cognitive assessmentswere administered at pre-test (start of the intervention, week0), mid-point (week 7–8 of the intervention), post-test (aftercompletion of the intervention classes—week 15), and 3-month,6-month, and 1-year follow-ups.

The design and procedure for Study 2 were largely like Study1 with a few differences. Study 2 participants had 12 weeks ofclasses (due to increased absences in the last three weeks of theintervention for Study 1). Additionally, to maintain small classsizes (under 20 students), Study 2 participants were assignedto three out of five possible classes (Spanish, photography, iPad operation, drawing, and music composition; class size range:15–19 students, M=17.4) based on experience level (i.e.assigned to classes to which they were naïve). To minimize attrition, participants were allowed to enroll in more than the threeassigned classes if they were interested. Five participantsenrolled in four classes, and three participants enrolled in allfive classes. Classes were scheduled in the same 2-hour structure as Study 1 and included the 1-hour lecture/discussions onmotivation and successful aging. Participants therefore completed a minimum of six hours of classes a week plus the 1-hourdiscussion. 

Study 2 included the same cognitive assessmentperiods as Study 1: pre-test (start of intervention—week 0), midpoint (week 6), post-test (after completion of the intervention—week 12), and 3-month, 6-month, and 1-year follow-ups. In addition,to measure testing effects or changes in performance unrelatedto the intervention, a baseline assessment was administered6weeks before the pre-test assessment. The procedure andassessments for Study 1 were pre-registered on ClinicalTrials.gov (Protocol Record 1320181), and for Study 2 the procedureswere pre-registered on the Open Source Framework via aspredicted.org (https://osf.io/3ehtq).

The cognitive assessments consisted of tasks that measured executive function (cognitive control/inhibition and working memory) and verbal episodic memory. The executive function taskswere from a standard battery (NIH Examiner; Kramer et al., 2014),and included flanker and set-shifting (cognitive control/inhibition), and n-back and dot counting (working memory; Study 1completed 1-Back, Study 2 completed 1-Back and 2-Back). Thetasks were presented on a 19-inch computer monitor and administered via PsychoPy (version 7.1). Overall composite andsub-component scores were compiled from reaction times andaccuracy scores, apart from dot counting, which was a verbal task,and therefore only had accuracy scores. Overall composite andsub-component scores for working memory and cognitive control were standardized and computed using the R script providedby the EXAMINER development team (Kramer et al., 2014).

The verbal episodic memory tasks included the Rey AuditoryVerbal Learning Task (RAVLT; Schmidt, 1996), and the WAIS-III(Ryan & Lopez, 2001) Digit Span forward and backward tasks.Participants were prompted five times with the same RAVLTword lists, at a rate of one word per second. Participants weregiven 60 to recall as many words from the list as possible. Aftera distractor word list, there was an immediate sixth recall trial,in which participants were asked to recall as many words as theycould remember without hearing the list again. Trial responseswere scored for each correct word, excluding duplicates (i.e. aperfect score was 15 for a single trial). The six trial scores weresummed and then averaged for the overall RAVLT score.

For the Digit Span task, experimenters verbally presenteddigits at a rate of one number per second. Participants werethen asked to repeat the numbers back to the examiner in thecorrect order for the forward task, and in reverse sequence forthe backward task. Sequence levels were in trial pairs. Thelength of the number sequences increased by one number witheach successive trial pair until the participant incorrectlyrecalled two consecutive sequences of the same length. A perfect score for the forward version was 16, and 14 was a perfectscore for the backward version. Forward and backward scoreswere summed for a total score (out of a possible 30).

The full assessments lasted 1.5 to 2 hours, depending on participants' pacing (breaks, practice blocks, etc.).

Participants' hours of attendance (total class time in hours; experimenter recorded) and number of hours spent on homework(self-reported) during the intervention period were summed intoan 'hours of engagement' measure (similar to Park et al., 2014) tomeasure engagement in the intervention activities.

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