High-Ecological Cognitive Intervention to Improve Cognitive Skills and Cognitive–Functional Performance for Older Adults With Mild Cognitive Impairment

Abstract

Importance: Evidence of the effectiveness of cognitive activity and preparatory tasks in improving the cognitive skills and functional performance of people with cognitive decline is limited.

Objective: To examine the efficacy of a high-ecological cognitive intervention.

Design: Quasi-experimental, pretest–posttest design with nonequivalent control.

Setting: Community.

Participants: Older adults with mild cognitive impairment from two senior centers.

Intervention: Twelve 90-min weekly group sessions of a high-ecological cognitive intervention using simulated everyday cognitive tasks (experimental group) and of nutrition education (active control group).

Outcomes and Measures: Cognitive skills were measured with the Color Trails Test (CTT), the Contextual Memory Test (CMT; Immediate Recall [CMT–Im] and Delayed Recall [CMT–De] tasks), and the Wechsler Adult Intelligence Scale–Fourth Edition Digit Span subtest (Digits Forward and Digits Backward). Cognitive–functional performance was measured with the Rivermead Behavioural Memory Test–Third Edition (RBMT–3; Immediate Recall [RBMT–3–Im] and Delayed Recall [RBMT–3–De] tasks) and the Cognitive Failures Questionnaire (CFQ).

Results: Thirty-seven participants (M age = 70.84 yr; 70.3% women) met the inclusion criteria for analysis (20 participants in the intervention group, 17 participants in the control group). Multivariate linear regression showed that the intervention group improved significantly more than the control group on the CTT, CMT–Im, and RBMT–3–Im but not on the CMT–De, RBMT–3–De, and CFQ.

Conclusions and Relevance: Twelve 90-min weekly group sessions of a high-ecological cognitive intervention improved attention, executive function, immediate memory, and objective cognitive–functional performance with immediate-memory task demands.

What This Article Adds: Carefully designed and structured simulated everyday cognitive tasks can be used as a cognitive training agent to improve both cognitive skills and objective cognitive–functional performance. The effectiveness of group-based cognitive interventions depends on the skills of occupational therapy practitioners in activity analysis and grading.

Carefully designed and structured simulated everyday cognitive tasks can be used as a training agent to improve both cognitive skills and objective cognitive–functional performance for older adults with mild cognitive impairment.

According to the World Alzheimer Report 2018 (Alzheimer’s Disease International, 2018), 50 million people worldwide are living with dementia, and the number is expected to triple to 152 million by 2050. Mild cognitive impairment (MCI) is often considered a prodromal phase of dementia (i.e., an intermediate state between normal altered cognitive states of older adults and the pathological cognitive declines associated with dementia). People with MCI have a 50% risk of progressing to dementia within 5 yr, whereas the rest remain stable or return to normal over time (Gauthier 2006).

The number of studies focused on developing and evaluating interventions to maintain or improve the cognitive skills (e.g., memory and attention) of people with MCI has risen during the last decade (e.g., Chandler et al., 2016; Gates et al., 2011; Hampstead et al., 2014). Studies (e.g., Simon et al., 2012) have shown that after training, people with MCI are able to retain learning abilities because of cognitive plasticity, which can be associated with less cognitive decline. Other studies (e.g., Mowszowski et al., 2010) have reported that appropriate cognitive training has the potential to alter the brain neuromechanism of people with MCI, thus possibly delaying the progression to dementia.

People with MCI often have subtle difficulties with complex instrumental activities of daily living (IADLs), such as financial management, shopping, meal preparation, and travel (Albert et al., 2011; Wen et al., 2016). However, a meta-analysis (Chandler et al., 2016) of 14 cognitive interventions among people with MCI showed that cognitive skills were the primary outcomes for most studies. Few studies have examined the everyday effects of cognitive intervention. Despite the challenges people with MCI encounter performing their IADLs, everyday cognitive tasks as therapy agents are seldom used in cognitive interventions.

Research so far suggests that the positive transfer of cognitive training to nonpracticed tasks (e.g., tasks in real-life situations) is nonexistent or very small (Reijnders et al., 2013). One reason for poor transfer might be that most interventional cognitive exercises consist of decontextualized computerized or paper-and-pencil tasks that are not similar to activities of daily living (ADLs). Chen et al. (2018) proposed high-ecological cognitive training to improve the transfer of cognitive gains to ADLs for healthy older adults; this type of training involves a high degree of similarity between cognitive exercises and real-life ADLs. However, it is still unknown whether this training is effective for people with MCI.

According to the Occupational Therapy Practice Framework: Domain and Process (4th ed.; American Occupational Therapy Association, 2020), high-ecological training is consistent with the principle of therapeutic use of occupation, activity, and preparatory tasks. Although occupational therapy practitioners frequently use realistic or simulated everyday tasks, components of occupations, and preparatory tasks and activities in clinical settings, empirical evidence is limited regarding the effectiveness of cognitive activity and preparatory tasks in improving the cognitive skills and functional performance of people with MCI or dementia. We hypothesized that when simulated everyday cognitive tasks were used as an intervention medium in cognitive training, both cognitive skills and cognitive–functional performance would improve.

Method

In this quasi-experimental study with a nonequivalent control and a pretest–posttest design, participants were recruited from two senior centers in Taiwan. Inclusion criteria were being older than age 65 yr and meeting Petersen’s (2011) MCI criteria: subjective cognitive complaint by the clients or their caregivers, objective cognitive deficits with scores ≤1.5 standard deviation of the population norms in at least one of the cognitive skill tests, and no difficulties in basic ADLs. Exclusion criteria were (1) confirmed dementia, stroke, Parkinson’s disease, traumatic brain injury, major depression, or substance abuse by self-report; (2) severe visual or hearing impairments that interfered with following instructions in group activities or completing evaluations; (3) normal cognition (Mini-Mental State Examination [MMSE; Folstein et al., 1975] score = 29 or 30) or potential dementia (MMSE score ≤21 or ≤16, depending on years of education; Hsieh, 2003; Stephan et al., 2013); and (4) attendance at fewer than 10 of the total 12 sessions.

This study was approved by Chang Gung Memorial Hospital’s Ethics Committee for Medical Research (102-2717B) and is registered at ClinicalTrials.gov (Identifier: NCT03612167). Informed consent was obtained from all participants.

Group Assignments and Interventions

The participants chose either the cognition (intervention) or nutrition (control) group on the basis of their preferences and schedules. Both interventions were given in one 90-min group session per week for 12 wk. The cognitive intervention consisted primarily of modified everyday cognitive tasks, which were adjusted for individual participants and for the group by the group, which were adjusted for individual participants and for the group by Author Po-Yen Chen to provide an error-reduction learning environment. Each session consisted of (1) a 5-min warm-up physical activity, (2) 40 to 45 min of two or three contextually relevant cognitive tasks, and (3) 20 to 25 min of group discussion to identify occupations that require similar cognitive skills and ways to apply the learned strategies.

Cognitive tasks addressed elements such as complex attention, visual scanning, auditory attention, visual–motor memory, visual memory, auditory memory, prospective memory, executive functioning, and problem solving (for details on the intervention protocols, see Supplemental Appendix A, available online with this article at https://research.aota.org/ajot). The control group’s nutritional program was led by a dietitian and focused on caloric intake control, food safety, and a balanced diet. These classes included lectures and hands-on activities such as growing vegetables or cooking.

Instruments and Data Collection

Participants were assessed within 1 wk before the start of the 12-wk intervention (pretest) and were reassessed within 1 wk after completion (posttest). Occupational therapy students with training in test administration assisted in the assessments.

Primary Outcomes: Cognitive Skills

Color Trails Test.

The Color Trails Test–Part 1 (CTT–1) and the Color Trails Test–Part 2 (CTT–2) were used to assess attention and executive function (D’Elia et al., 1996). Participants were asked to connect 25 numbered circles as quickly as possible, and the length of time to complete was recorded.

Contextual Memory Test.

The Visual-Memory subtest of the Contextual Memory Test (CMT; Toglia, 1990) was used to assess visual memory. A worksheet of 20 line-drawn items about morning routine or a restaurant scene was presented for 90 s. Participants were asked to recall them immediately and again 15 to 20 min later. The number of items remembered correctly was scored (0–20). Alternative versions were used for pretest and posttest.

Wechsler Adult Intelligence Scale–Fourth Edition Digit Span subtest (Digits Forward and Digits Backward).

The Wechsler Adult Intelligence Scale–Fourth Edition Digit Span subtest (Chen & Chen, 2015) was used to measure short-term memory (Digits Forward [DF]) and working memory (Digits Backward [DB]). Participants listened to a sequence of digits and were asked to recall the sequence correctly (DF) or in reverse order (DB). Total scores ranged from 2 to 9 for DF and from 2 to 8 for DB.

Secondary Outcomes: Cognitive–Functional Performance

Rivermead Behavioural Memory Test–Third Edition.

The Rivermead Behavioural Memory Test–Third Edition (RBMT–3; Wilson et al., 2008) was used to assess everyday memory problems. Participants performed standardized simulated IADL tasks, such as recalling a route and a message, finding hidden objects, recognizing faces and recalling names, repeating questions when an alarm sounded, and retelling stories. Only 11 of the 13 subtests were used (those that did not overlap with other tests in this study). Higher raw scores on the immediate and delayed recall tasks indicated better objective everyday memory performance (Yassuda et al., 2010). Alternative versions were used for pretest and posttest.

Cognitive Failures Questionnaire.

The Cognitive Failures Questionnaire (CFQ; Broadbent et al., 1982) was used to rate (0–4) the frequency of 25 subjective everyday cognitive problems. Total scores ranged from 0 to 100; higher scores indicated worse subjective everyday cognitive performance.

Data Analysis

We analyzed baseline characteristics using descriptive statistics. Both parametric and nonparametric inferential statistics were used depending on data normality. A two-way, mixed-design analysis of variance (ANOVA) was used to check the overall significance between and within groups. If significant interaction effects were found, Fisher’s least significant difference test was used for post hoc comparisons. Effect size (Cohen’s d) was also used. We applied multivariate linear regression to confirm the intervention effect of the cognitive training, using the change in scores for each cognitive skill and performance as outcome variables while controlling variables with significant intergroup difference at baseline. Significance was set at p < .05. We performed all analyses using IBM SPSS Statistics (Version 20).

Results

Eighty-one participants were recruited. Sixty-three met the inclusion criteria for the intervention (n = 36) and control (n = 27) groups. Sixteen participants in the intervention group and 10 in the control group attended fewer than 10 sessions and were excluded, leading to a total of 37 participants (intervention group, n = 20; control group, n = 17). The mean age of the participants was 70.84 yr (SD = 6.86), and 70.3% were women. No significant intergroup differences existed in age, gender, attendance, overall cognitive function, cognitive–functional performance, or the baseline performance on each outcome measure (except DF and the CMT–Delayed Recall task [CMT–De]; Table 1).

Table 1.

Baseline Participant Characteristics

Characteristic	Total (N = 37)	Intervention Group (n = 20)	Control Group (n = 17)	p
Age, yr	70.84 ± 6.86	71.60 ± 7.49	69.94 ± 6.15	.511
Gender, n (%)				.447
Male	11 (29.7)	7 (35.0)	4 (23.5)
Female	26 (70.3)	13 (65.0)	13 (76.5)
Education, yr	10.62 ± 3.85	10.95 ± 4.08	10.24 ± 3.63	.603
No. of training sessions	10.41 ± 0.88	10.35 ± 0.88	10.47 ± 0.87	.990
MMSE score	26.11 ± 1.33	25.95 ± 1.39	26.29 ± 1.26	.464
Assessment scores
CTT–1, s	59.32 ± 20.78	59.55 ± 26.49	59.06 ± 11.76	.573
CTT–2, s	152.81 ± 32.90	152.10 ± 39.48	153.65 ± 24.13	.867
DF	6.41 ± 1.12	6.75 ± 1.16	6.00 ± 0.94	.030*
DB	4.00 ± 0.75	3.95 ± 0.89	4.06 ± 0.56	.902
CMT–Im	12.03 ± 2.25	12.15 ± 2.76	11.88 ± 1.54	.678
CMT–De	11.11 ± 2.87	11.80 ± 3.29	10.29 ± 2.08	.041*
CMT–total	23.14 ± 4.91	23.95 ± 5.94	22.18 ± 3.24	.199
RBMT–3–Im	27.53 ± 5.26	27.43 ± 5.94	27.65 ± 4.51	.771
RBMT–3–De	40.64 ± 7.37	40.98 ± 8.73	40.24 ± 5.61	.915
CFQ	16.95 ± 8.47	19.40 ± 10.10	14.06 ± 4.89	.095

Note. Unless otherwise noted, values indicate M ± SD. CFQ = Cognitive Failures Questionnaire; CMT–De = Contextual Memory Test–Delayed Recall task; CMT–Im = Contextual Memory Test–Immediate Recall task; CMT–total = Contextual Memory Test–total score; CTT–1 = Color Trails Test–Part 1; CTT–2 = Color Trails Test–Part 2; DB = Digits Backward; DF = Digits Forward; MMSE = Mini-Mental State Examination; RBMT–3–De = Rivermead Behavioural Memory Test–Third Edition–Delayed Recall task; RBMT–3–Im = Rivermead Behavioural Memory Test–Third Edition–Immediate Recall task.

p < .05.

The ANOVA results indicated a between-groups effect on DF and CFQ as well as a within-group (time) effect on the RBMT–3–Immediate Recall task (RBMT–3–Im). However, between- and within-group interactions were found for CTT–1, CTT–2, CMT–Immediate Recall task (CMT–Im), and CMT–total score (CMT–total; see Supplemental Appendix B). Further post hoc analyses were performed and are presented next.

In the intervention group, most cognitive skills significantly improved after intervention (Table 2). The pretest and posttest mean scores on the CTT–1, CTT–2, CMT–Im, and CMT–total were significantly higher (all ps < .05); the effect size was medium to large. For objective cognitive–functional performance, the RBMT–3–Im mean score was significantly higher (p < .05); the effect size was medium. In addition, the RBMT–3–Delayed Recall task (RBMT–3–De) mean score was descriptively higher with a small effect size. The control group showed no significant difference after intervention, except for an improved RBMT–3–De mean score with a small effect size (see Table 2).

Table 2.

Intragroup Comparisons of Pretest and Posttest Scores

Index	Intervention Group					Control Group
Index	Pretest	Posttest	Change	p	Cohen’s d a	Pretest	Posttest	Change	p	Cohen’s d a
Cognitive Skills
CTT–1	59.55 ± 26.49	54.65 ± 23.93	−4.90 ± 6.90	.002*	0.71	59.06 ± 11.76	59.65 ± 11.98	0.59 ± 2.06	.238	0.29
CTT–2	152.10 ± 39.48	140.95 ± 36.06	−11.15 ± 8.93	<.001*	1.25	153.65 ± 24.13	153.94 ± 25.56	0.29 ± 6.04	.686	0.05
DF	6.75 ± 1.16	7.00 ± 1.34	0.25 ± 0.55	.059	0.45	6.00 ± 0.94	6.00 ± 0.94	0.00 ± 0.79	1.000	0.00
DB	3.95 ± 0.89	4.15 ± 1.04	0.20 ± 0.62	.157	0.32	4.06 ± 0.56	4.12 ± 0.60	0.06 ± 0.75	.739	0.08
CMT–Im	12.15 ± 2.76	13.20 ± 2.88	1.05 ± 0.76	<.001*	1.38	11.88 ± 1.54	11.71 ± 1.61	−0.18 ± 1.01	.507	0.17
CMT–De	11.80 ± 3.29	12.00 ± 3.31	0.20 ± 1.40	.666	0.14	10.29 ± 2.08	10.47 ± 1.91	0.18 ± 0.81	.366	0.22
CMT–total	23.95 ± 5.94	25.20 ± 5.95	1.25 ± 1.77	.005*	0.70	22.18 ± 3.24	22.18 ± 3.30	0.00 ± 1.37	.684	0.00
Cognitive–Functional Performance
RBMT–3–Im	27.43 ± 5.94	28.63 ± 6.18	1.20 ± 1.89	.019*	0.64	27.65 ± 4.51	27.71 ± 3.70	0.06 ± 1.73	.221	0.03
RBMT–3–De	40.98 ± 8.73	41.53 ± 9.18	0.55 ± 2.67	.405	0.21	40.24 ± 5.61	41.35 ± 4.69	1.12 ± 2.44	.082	0.46
CFQ	19.40 ± 10.10	17.65 ± 8.62	−1.75 ± 9.90	.456	0.18	14.06 ± 4.89	14.24 ± 4.07	0.18 ± 4.49	.981	0.04

Note. Values indicate M ± SD. CFQ = Cognitive Failures Questionnaire; CMT–De = Contextual Memory Test–Delayed Recall task; CMT–Im = Contextual Memory Test–Immediate Recall task; CMT–total = Contextual Memory Test–total score; CTT–1 = Color Trails Test–Part 1; CTT–2 = Color Trails Test–Part 2; DB = Digits Backward; DF = Digits Forward; RBMT–3–De = Rivermead Behavioural Memory Test–Third Edition–Delayed Recall task; RBMT–3–Im = Rivermead Behavioural Memory Test–Third Edition–Immediate Recall task.

Effect size levels: ≥0.2 = low; ≥0.5 = medium; ≥0.8 = high.

p < .05.

The between-groups pretest–posttest differences were significant in CTT–1, CTT–2, CMT–Im, CMT–total, and RBMT–3–Im mean scores (all ps < .05; Table 3). After adjusting for DF and CMT–De scores at baseline, the between-groups pretest–posttest differences in mean scores on these assessments remained significant (all ps < .05; Table 4).

Table 3.

Between-Groups Comparisons of Pretest–Posttest Differences in Scores

Index	Intervention Group (n = 20)	Control Group (n = 17)	Difference: Intervention − Control	p	Cohen’s d a
Cognitive Skills
CTT–1	−4.90 ± 6.90	0.59 ± 2.06	−5.49	.003*	1.04
CTT–2	−11.15 ± 8.93	0.29 ± 6.04	−11.44	<.001*	1.48
DF	0.25 ± 0.55	0.00 ± 0.79	0.25	.310	0.37
DB	0.20 ± 0.62	0.06 ± 0.75	0.14	.820	0.21
CMT–Im	1.05 ± 0.76	−0.18 ± 1.01	1.23	<.001*	1.39
CMT–De	0.20 ± 1.40	0.18 ± 0.81	0.02	.794	0.02
CMT–total	1.25 ± 1.77	0.00 ± 1.37	1.25	.015*	0.78
Cognitive–Functional Performance
RBMT–3–Im	1.20 ± 1.89	0.06 ± 1.73	1.14	.023*	0.63
RBMT–3–De	0.55 ± 2.67	1.12 ± 2.44	−0.57	.295	0.22
CFQ	−1.75 ± 9.90	0.18 ± 4.49	−1.93	.408	0.24

Effect size levels: ≥0.2 = low; ≥0.5 = medium; ≥0.8 = high.

p < .05.

Table 4.

Multivariate Regression Model of Group Variable to Outcome Measurements (Pretest and Posttest Differences) by controlling DF (Pretest) and CMT–De (Pretest)

Outcome Measure	Parameter
Outcome Measure	Group	DF (Pretest)	CMT–De (Pretest)
CTT–1 difference
B [95% CI]	−5.81 [−9.66, −1.97]	−0.19 [−2.27, 1.89]	0.31 [−0.48, 1.10]
p	.004*	.854	.430
CTT–2 difference
B [95% CI]	−13.38 [−18.59, −8.16]	0.62 [−2.20, 3.45]	0.98 [−0.10, 2.05]
p	<.001*	.658	.074
DF difference
B [95% CI]	0.32 [−0.15, 0.78]	—	−0.04 [−0.13, 0.04]
p	.177		.287
DB difference
B [95% CI]	0.12 [−0.38, 0.61]	0.10 [−0.17, 0.37]	−0.03 [−0.14, 0.07]
p	.633	.456	.507
CMT–Im difference
B [95% CI]	1.12 [0.48, 1.76]	0.11 [−0.24, 0.45]	0.02 [−0.11, 0.15]
p	.001*	.541	.784
CMT–De difference
B [95% CI]	0.21 [−0.61, 1.03]	−0.25 [−0.62, 0.12]
p	.603	.178
CMT–Total difference
B [95% CI]	1.36 [0.19, 2.54]	−0.04 [−0.68, 0.59]	−0.05 [−0.29, 0.19]
p	.024*	.893	.659
RBMT–3–Im difference
B [95% CI]	1.42 [0.12, 2.72]	−0.44 [−1.14, 0.27]	0.03 [−0.24, 0.30]
p	.034*	.217	.809
RBMT–3–De difference
B [95% CI]	−0.88 [−2.74, 0.98]	0.53 [−0.48, 1.53]	−0.06 [−0.44, 0.33]
p	.342	.292	.765
CFQ difference
B [95% CI]	−2.92 [−8.66, 2.82]	0.93 [−2.18, 4.04]	0.19 [−0.99, 1.38]
p	.309	.546	.742

Note. The coding of the group variable was intervention group = 1 and control group = 0. — = not applicable; CFQ = Cognitive Failures Questionnaire; CI = confidence interval; CMT–De = Contextual Memory Test–Delayed Recall task; CMT–Im = Contextual Memory Test–Immediate Recall task; CMT–total = Contextual Memory Test–total score; CTT–1 = Color Trails Test–Part 1; CTT–2 = Color Trails Test–Part 2; DB = Digits Backward; DF = Digits Forward; RBMT–3–De = Rivermead Behavioural Memory Test–Third Edition–Delayed Recall task; RBMT–3–Im = Rivermead Behavioural Memory Test–Third Edition–Immediate Recall task.

p < .05.

Discussion

Our findings show that high-ecological cognitive training for people with MCI is efficacious for improving attention, executive functioning, immediate memory, and objective cognitive–functional performance with immediate-memory task demands; however, this benefit did not appear among the control group participants who attended nutritional classes. We conclude that carefully designed and structured simulated everyday cognitive tasks can be used as a cognitive training agent to improve both cognitive skills and objective cognitive–functional performance.

Our findings suggest that cognitive challenges are the key to achieving progress and are crucial to cognitive training (Smallfield & Heckenlaible, 2017). Occupational therapists working with the cognitive group carefully designed the tasks to demand a high level of cognitive engagement at the just-right level of challenge in an error-reduction environment. By contrast, the cognitive demands in the nutritional program (active control group) were not tailored to meet individualized cognitive challenges and cognitive deficits frequently seen in people with MCI. Moreover, this group showed no significant cognitive improvement. Thus, we postulate that ensuring the best fit between cognitive demands and the abilities of the participants is essential to the effectiveness of simulated everyday cognitive tasks as a therapy medium. This hypothesis highlights the unique skill set of occupational therapy practitioners in activity and task analysis, task grading, and retraining of ADLs (Smallfield & Heckenlaible, 2017). More studies are needed to examine this hypothesis.

Our findings provide empirical evidence to support and expand the use of cognitive activity and preparatory tasks as part of an occupational therapy cognitive intervention. Among the cognitive skills targeted in our intervention, processing speed (assessed by CTT–2) and immediate memory (assessed by CMT–IM) showed significant pretest–posttest improvement, whereas other cognitive skills, especially delayed memory, did not. Several studies have similarly shown that the processing speed of people with mild cognitive issues can significantly improve after intervention (e.g., Ngandu et al., 2015). Improvements in immediate memory can be ascribed to applying learned memory strategies to encode the information more efficiently. However, a training period longer than 12 wk may be needed to internalize the memory strategies necessary to improve delayed memory.

We found limited benefits for participants’ subjective cognitive difficulties in either group. However, the intervention group members were positive in the final week’s reflection regarding how the group had helped them become more aware of the cognitive demands inherent in daily tasks. It is possible that 12 wk of training was too short for the integration of cognitive strategies into daily routines; moreover, the group setting did not allow the participants to identify personally relevant goals and to devise strategies to address the cognitive difficulties they experienced in their daily lives (Bahar-Fuchs et al., 2013). In addition, the CFQ is a screening tool and thus may not be sensitive to changes. In future studies, researchers should examine the effectiveness of a longer and more tailored intervention for improving subjective perception of cognitive functioning; they could also use a more sensitive assessment.

Limitations

This study has limitations. First, the participants were recruited from two community senior health centers. Given the reality of community cognitive programs, we were unable to conduct a randomized trial. Second, the participants self-selected the program that they joined. Those who missed more than two sessions were excluded, resulting in a 40% attrition. It is therefore possible that the findings are limited to those who are highly motivated and that an increased level of motivation also contributed to the improvement in cognition among the intervention group. Treatment benefits could be different for people with lower attendance or motivation. Third, the participants did not have confirmed MCI diagnoses by medical doctors. Instead, we used MMSE scores and Petersen’s (2011) criteria for both objective and subjective cognitive decline as inclusion criteria. Last, but not least, this study used a nutritional noncognitive intervention as the active control. Thus, we were unable to compare the high-ecological cognitive intervention to other types of cognitive intervention.

Implications for Occupational Therapy Practice

With more occupational therapy practitioners becoming involved in dementia prevention, this study supports the efficacy of cognitive group interventions that rely on practitioners’ skills (activity analysis and grading) to improve cognitive skills and cognitive–functional performance for older adults with MCI. The results of this study have the following implications for occupational therapy practice:

Cognitive skills and objective cognitive–functional performance of people with MCI can improve after cognitive training.

Repetitive practice of simulated everyday cognitive tasks can improve cognitive skills.

Repetitive practice of contextually relevant cognitive tasks has limited effects on subjective cognitive–functional performance.

Conclusion

Our study confirms the efficacy of high-ecological cognitive training to improve cognitive skills (attention, executive function, and memory) and objective cognitive–functional performance (but not subjective cognitive–functional performance). It supports the use of simulated everyday cognitive tasks as an efficacious therapeutic medium. With the population aging, the role of occupational therapy practitioners in preventing or delaying cognitive decline is expected to grow. Occupational therapy practitioners are uniquely poised to use their professional skills in activity analysis to readily link simulated everyday cognitive tasks to everyday occupations to help maximize improvement in functional performance.

Supplemental Materials

Supplemental Material

Supplementary material for High-Ecological Cognitive Intervention to Improve Cognitive Skills and Cognitive–Functional Performance for Older Adults With Mild Cognitive Impairment

Supplementary material, sj-docx-1-aot-10.5014_ajot.2021.041996.docx for High-Ecological Cognitive Intervention to Improve Cognitive Skills and Cognitive–Functional Performance for Older Adults With Mild Cognitive Impairment by Ling-Hui Chang, Po-Yen Chen, Jye Wang, Bin-Huei Shih, Yu-Hsuan Tseng and Hui-Fen Mao in The American Journal of Occupational Therapy

Supplemental Material

Supplementary material for High-Ecological Cognitive Intervention to Improve Cognitive Skills and Cognitive–Functional Performance for Older Adults With Mild Cognitive Impairment

Supplementary material, sj-docx-2-aot-10.5014_ajot.2021.041996.docx for High-Ecological Cognitive Intervention to Improve Cognitive Skills and Cognitive–Functional Performance for Older Adults With Mild Cognitive Impairment by Ling-Hui Chang, Po-Yen Chen, Jye Wang, Bin-Huei Shih, Yu-Hsuan Tseng and Hui-Fen Mao in The American Journal of Occupational Therapy

Footnotes

Acknowledgments

We thank the participants and the staff at the Foundation of Tainan YMCA who participated in this project.

References

Albert

M. S.

DeKosky

S. T.

Dickson

Dubois

Feldman

H. H.

Fox

N. C.

, . . . Phelps

C. H.

(2011). The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the National Institute on Aging–Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s and Dementia , 7 , 270–279. https://doi.org/10.1016/j.jalz.2011.03.008

Alzheimer’s Disease International. (2018). World Alzheimer Report 2018. https://www.alzint.org/resource/world-alzheimer-report-2018/

American Occupational Therapy Association. (2020). Occupational therapy practice framework: Domain and process (4th ed.)

American Journal of Occupational Therapy , 74(Suppl. 2), 7412410010. https://doi.org/10.5014/ajot.2020.74S2001

Bahar-Fuchs

Clare

, & Woods

(2013). Cognitive training and cognitive rehabilitation for mild to moderate Alzheimer’s disease and vascular dementia. Cochrane Database of Systematic Reviews. https://doi.org/10.1002/14651858.CD003260

Broadbent

D. E.

Cooper

P. F.

FitzGerald

, & Parkes

K. R.

(1982). The Cognitive Failures Questionnaire (CFQ) and its correlates. British Journal of Clinical Psychology , 21 , 1–16. https://doi.org/10.1111/j.2044-8260.1982.tb01421.x

Chandler

M. J.

Parks

A. C.

Marsiske

Rotblatt

L. J.

, & Smith

G. E.

(2016). Everyday impact of cognitive interventions in mild cognitive impairment: A systematic review and meta-analysis. Neuropsychology Review , 26 , 225–251. https://doi.org/10.1007/s11065-016-9330-4

Chen

Wei

Deng

, & Sun

(2018). The effects of cognitive training on cognitive abilities and everyday function: A 10-week randomized controlled trial. International Journal of Aging and Human Development , 86 , 69–81. https://doi.org/10.1177/0091415017697725

Chen

H.-Y.

, & Chen

R.-H.

(2015). Wechsler Adult Intelligence Scale–Fourth Edition (Chinese version). Chinese Behavioral Science Corporation.

D’Elia

L. F.

Satz

Uchiyama

, & White

(1996). Color Trails Test. Psychological Assessment Resources.

10.

Folstein

M. F.

Folstein

S. E.

, & McHugh

P. R.

(1975). “Mini-Mental State”: A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research , 12 , 189–198. https://doi.org/10.1016/0022-3956(75)90026-6

11.

Gates

N. J.

Sachdev

P. S.

Fiatarone Singh

M. A.

, & Valenzuela

(2011). Cognitive and memory training in adults at risk of dementia: A systematic review. BMC Geriatrics , 11 , 55. https://doi.org/10.1186/1471-2318-11-55

12.

Gauthier

Reisberg

Zaudig

Petersen

R. C.

Ritchie

Broich

, . . . Winblad

(2006). Mild cognitive impairment. Lancet , 367 , 1262–1270. https://doi.org/10.1016/S0140-6736(06)68542-5

13.

Hampstead

B. M.

Gillis

M. M.

, & Stringer

A. Y.

(2014). Cognitive rehabilitation of memory for mild cognitive impairment: A methodological review and model for future research. Journal of the International Neuropsychological Society , 20 , 135–151. https://doi.org/10.1017/S1355617713001306

14.

Hsieh

C. J.

(2003). Application and measurement of cognitive function in the elderly [in Chinese]. Journal of Health Science , 5 , 387–395.

15.

Mowszowski

Batchelor

, & Naismith

S. L.

(2010). Early intervention for cognitive decline: Can cognitive training be used as a selective prevention technique? International Psychogeriatrics , 22 , 537–548. https://doi.org/10.1017/S1041610209991748

16.

Ngandu

Lehtisalo

Solomon

Levälahti

Ahtiluoto

Antikainen

, . . . Kivipelto

(2015). A 2 year multidomain intervention of diet, exercise, cognitive training, and vascular risk monitoring versus control to prevent cognitive decline in at-risk elderly people (FINGER): A randomised controlled trial. Lancet , 385 , 2255–2263. https://doi.org/10.1016/S0140-6736(15)60461-5

17.

Petersen

R. C.

(2011). Clinical practice: Mild cognitive impairment. New England Journal of Medicine , 364 , 2227–2234. https://doi.org/10.1056/NEJMcp0910237

18.

Reijnders

van Heugten

, & van Boxtel

(2013). Cognitive interventions in healthy older adults and people with mild cognitive impairment: A systematic review. Ageing Research Reviews , 12 , 263–275. https://doi.org/10.1016/j.arr.2012.07.003

19.

Simon

S. S.

Yokomizo

J. E.

, & Bottino

C. M.

(2012). Cognitive intervention in amnestic mild cognitive impairment: A systematic review. Neuroscience and Biobehavioral Reviews , 36 , 1163–1178. https://doi.org/10.1016/j.neubiorev.2012.01.007

20.

Smallfield

, & Heckenlaible

(2017). Effectiveness of occupational therapy interventions to enhance occupational performance for adults with Alzheimer’s disease and related major neurocognitive disorders: A systematic review. American Journal of Occupational Therapy , 71 , 7105180010. https://doi.org/10.5014/ajot.2017.024752

21.

Stephan

B. C. M.

Minett

Pagett

Siervo

Brayne

, & McKeith

I. G.

(2013). Diagnosing mild cognitive impairment (MCI) in clinical trials: A systematic review. BMJ Open , 3 , e001909. https://doi.org/10.1136/bmjopen-2012-001909

22.

Toglia

J. P.

(1990). Contextual Memory Test. Therapy Skill Builders.

23.

Wen

M.-H.

Mao

H.-F.

Chang

L.-H.

, & Chiu

M.-J.

(2016). A qualitative study of the instrumental activities of daily living for mild cognitive impairment and caregivers [Poster presentation abstract]. American Journal of Occupational Therapy , 70 , 701150057. https://doi.org/10.5014/ajot.2016.70S1-PO5087

24.

Wilson

Greenfield

Clare

Baddeley

Cockburn

Watson

, & Nannery

(2008). Rivermead Behavioural Memory Test–Third Edition. Pearson Assessment.

25.

Yassuda

M. S.

Flaks

M. K.

Viola

L. F.

Pereira

F. S.

Memória

C. M.

Nunes

P. V.

, & Forlenza

O. V.

(2010). Psychometric characteristics of the Rivermead Behavioural Memory Test (RBMT) as an early detection instrument for dementia and mild cognitive impairment in Brazil. International Psychogeriatrics , 22 , 1003–1011. https://doi.org/10.1017/S1041610210001055

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