Efficacy of smartphone application–based multi-domain cognitive training in non-demented older adults

doi:10.21203/rs.3.rs-2974058/v1

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Efficacy of smartphone application–based multi-domain cognitive training in non-demented older adults

https://doi.org/10.21203/rs.3.rs-2974058/v1

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Background. As the elderly population and the prevalence of dementia increase, the importance of cognitive training for dementia prevention is being emphasized. To increase accessibility to cognitive training programs among elderly individuals, the InBrain Trainer (IBT), a smartphone application–based cognitive training including 12 cognitive tasks covering language, calculation, memory, attention, visuospatial function, and frontal/executive function was developed. The purpose of this study was to examine the effectiveness of the IBT by investigating cognitive improvement and prefrontal cortex activation in non-demented older adults using functional near-infrared spectroscopy (fNIRS).

Methods. The IBT, an android-based cognitive training software program, was downloaded to the participant’s smartphone or tablet computer and administered at home. Non-demented older adults (51 intervention participants, 50 control participants) were enrolled in this study. The IBT consisted of 12 tasks derived from two tasks each for six cognitive domains. Each task has 4 difficulty levels, and 48 blocks (12 tasks × 4 levels) were used to frame the amount of cognitive tasks for ≥1.5 hours per day, 5 days per week, for 16 weeks. The intervention group received gradually increasing difficulty tasks as homework through a mobile phone application for 16 weeks. To verify the effectiveness of the IBT as the outcome measure, the InBrain Cognitive Screening Test (CST), fNIRS, and various scales were compared between the intervention and control groups at two time points (baseline and after 16 weeks of cognitive training).

Results. Among 101 participants, 85 non-demented older adults (84.1%) completed the study protocol and were included in the final analysis, including 41 (80.3%) in the cognitive intervention group and 44 (88.0%) in the control group. The group-by-time interaction effect was significant only in the language domain score of the InBrain CST. When the language domain subtest scores were analyzed, significant interaction effects were presented in the phonemic generative naming test but not in the semantic generative naming test or the Difficult Naming Test. In the hemodynamic response of the prefrontal cortex measured by all channels of fNIRS, the group-by-time interaction effect was significant only in the dorsolateral prefrontal cortex during the Stroop incongruent task. There were no group-by-time interaction effects in the second outcome measures of various scales.

Conclusion. Our study is meaningful in that cognitive training software implemented as an application on personal devices such as smartphones and tablet computers led not only to cognitive enhancement, but also increased prefrontal lobe activation. Therefore, cognitive training applications including the IBT are expected to provide effective cognitive intervention without time or space constraints both in a clinical setting and at home.

Computerized cognitive training

Smartphone application multi-domain cognitive training

Neuroimaging

Prefrontal lobe l activation

Older adults

The prevalence of dementia patients is expected to decrease due to education expansion, lifestyle improvement, and dementia treatment development. However, due to an increase in life expectancy and the aging of the world’s population, the number of patients with dementia continues to increase. According to the 2019 World Health Organization (WHO) guideline for risk reduction of cognitive decline and dementia [1], there are about 50 million dementia patients worldwide, and the dementia population is expected to increase to 82 million in 2030 and to 152 million in 2050. Korea is one of the countries with the fastest growing elderly population, and the proportion of elderly individuals aged ≥ 65 years accounts for 15.8% of the total population of Korea. The estimated number of dementia patients among the elderly population ≥ 65 years of age is about 830,000, with a prevalence of 10.2%, and the number of dementia patients is expected to continue to increase and exceed 3 million by 2050 in Korea. As a result, the total annual national dementia management cost is expected to continue to increase from the current 17.3 trillion won to 56.9 trillion won, and the social burden is expected to increase by day [2].

For prevention of dementia, the global policy is an active approach to maintaining and promoting cognitive health rather than a passive approach for management of dementia patients. The WHO guidelines recommend 12 methods for dementia prevention: physical activity, tobacco cessation, nutritional intervention, intervention for alcohol use disorders, social activity, cognitive interventions, management of weight, hypertension, diabetes mellitus, dyslipidemia, depression, and hearing loss [1]. In particular, the interest in cognitive intervention for older adults at high risk for dementia has been significantly increasing. Cognitive intervention is divided into cognitive training, cognitive rehabilitation, and cognitive stimulation according to subject and content [3, 4], and many studies have shown that cognitive training, which focuses on elderly individuals with normal cognition or mild cognitive impairment dementia, is effective for improving cognitive function [5–8]. Cognitive training methods have diversified and range from paper and pencil training methods to computerized cognitive training programs for digital devices such as robots, virtual reality, web-based, and mobile applications. Such programs have led to significant improvements in the cognitive abilities of elderly individuals [9–15].

Computerized cognitive training programs using digital devices have the advantage of being used according to the individual's cognitive level, providing immediate feedback, and storing training records, but they also have limitations in that their use rate may be low due to poor accessibility. However, a cognitive training program based on a smartphone application can be an innovative way to overcome this limitation because an individual’s personal smartphone device is being used for the cognitive training. We recently developed an application-based cognitive training program, the InBrain Trainer (IBT), which includes 12 training tasks for language, calculation, memory, attention, visuospatial functions, and frontal/executive functions. In our recent study, the IBT was implemented among community-dwelling elderly individuals for one year, and its effect on cognitive function was verified [16].

As an outcome measure of a cognitive intervention study, improvement in cognitive function can be directly investigated; however, some recent studies have relied on brain imaging techniques to assess such effects of cognitive training [17–19]. Measuring cortical thickness and brain volumetry, as well as conducting brain functional magnetic resonance imaging (fMRI), are useful for examining the effects of digital device-based cognitive training but have limitations in terms of cost and time. Functional near-infrared spectroscopy (fNIRS), which estimates cortical hemodynamic activity occurring in response to neural activity, may be an encouraging method for examining the effects of cognitive training because it can portably investigate the degree of activation in the prefrontal cortex, even though it has the disadvantage of not covering the whole brain.

The purposes of this study are 1) to confirm whether a 16-week cognitive training program with a mobile application (the IBT) is effective in improving cognitive function in non-demented older adults and 2) to investigate whether this cognitive training program can activate the prefrontal cortex, which is particularly vulnerable in older adults, using fNIRS.

2.1 Study design

The present study was a single-center, randomized, single-masked, and parallel-group study designed to investigate the effects of smartphone application–based cognitive training in non-demented older adults. All participants were recruited from the Department of Neurology, Samsung Medical Center, from July to October 2019. Eligible participants were randomly assigned to an intervention group and a control group. Randomization was stratified according to age (three age categories, 60–69, 70–79, and ≥80 years) and sex in a 1:1 ratio.

There were six small groups within the intervention group according to training starting point, and a cognitive training program was conducted from October 2019 to March 2020 with the IBT smartphone cognitive training application for 16 weeks per group. The control group was also provided IBT tasks for 16 weeks with the same contents as the intervention group after the post-test.

To investigate the effects of our cognitive training, the primary and secondary outcome measures (see section 2.5, Outcome measures for details) were conducted at baseline and 16 weeks later. All participants filled out a consent form to participate in the study before conducting the baseline test, and the study protocol was approved by the Institutional Review Board (IRB) of Samsung Medical Center (IRB no. 2019-06-083-006).

2.2 InBrain Trainer

The IBT is an Android-based cognitive training software program that is implemented as an application on a smartphone or tablet computer. The cognitive training tasks of the IBT have four difficulty levels. (elementary, beginner, intermediate, and advanced) so that it can be provided to all older adults ranging from non-demented individuals to those with mild dementia. Two tasks were developed for each cognitive domain, and a total of 12 cognitive training tasks from the six cognitive domains of attention, language, calculation, visuospatial function, memory, and frontal/executive function were included in the IBT. The details of the IBT cognitive training tasks are presented in Table 1.

2.3 Participants

All participants were non-demented older adults recruited from the Department of Neurology, Samsung Medical Center. The following inclusion criteria were applied: 1) age ≥ 60 years; (2) literate with ≥6 years of education; (3) Korean version of Mini-mental State Examination (K-MMSE) score ≥ 24 points; (4) preserved activities of daily living (ADL), as defined by Seoul Instrumental ADL score < 8 points; and (5) Android smartphone user (IBT is an android-based application).

Meanwhile, participants with the following conditions were excluded from the study: 1) major cardiovascular events, such as stroke or myocardial infarction, in the past three months; 2) severe or unstable medical disease that could interfere with successful study completion; 3) severe hearing difficulty or visual disturbance; 4) limitations in communication; 5) previous dementia diagnosis; and 6) finished another cognitive training session within six months of study enrollment.

2.4 Procedure

After installing the IBT application on their devices, participants in the intervention group had a one-week try-and-adaptation period and were trained on how to use and operate the IBT application. The intervention group performed cognitive training homework assigned to IBT through a mobile phone app for an average of 1 hour and 30 minutes per day, once a day, 5 days a week, for 16 weeks. They had to complete their homework before midnight every day. .The IBT consisted of 12 tasks derived from two tasks each for six cognitive domains. Each task has 4 difficulty levels (elementary, beginner, intermediate, advanced), and 48 blocks (12 tasks × 4 level) were used to create cognitive tasks for 16 weeks. From 1 to 4 weeks, it is a time to adapt to 12 tasks with elementary and beginner difficulty tasks, and from 5 to 12 weeks, it is a stage to learn and apply cognitive strategies with intermediate and advanced difficulty levels. In the 13th to 16th weeks, it is a step to use high-level learning strategies by increasing the level of difficulty to advanced.

The cognitive training tasks consisted of two sets (A and set B), each of which contained six tasks, one from each cognitive domain. The intervention group performed elementary- and beginner-level tasks for the first four weeks and were required to complete 6–10 assigned tasks per day. Then, during weeks 5–8, the beginner- and intermediate-level tasks were completed (10–13 tasks per day), while intermediate- and advanced-level tasks were performed during weeks 9–12 (13–16 tasks per day) and advanced-level tasks were completed during weeks 13–16 (17–20 tasks per day). From the first week to week 12, cognitive tasks in sets A and B were assigned alternatively for two weeks; during the last four weeks (weeks 13–16⁾, all cognitive tasks in both sets were performed (see Table 2 for details).

To facilitate adherence to this cognitive training, the daily task-completion rate was monitored every day, and requests were made through text messages and phone calls to participants who did not complete the assigned tasks. Furthermore, the participants of the intervention group shared their experiences with this cognitive training and learned some cognitive strategies from neuropsychologists by participating in offline sessions once a month. Participants were required to complete ≥80% of the assigned IBT tasks each day, and those who could not meet this requirement for >20% of total training periods (16 of 80 days total) were excluded from the final study analysis.

The control group was not given any cognitive training task for 16 weeks, and the primary and secondary outcome measures were administered at baseline and after 16 weeks.

2.5 Outcome measures

InBrain Cognitive Screening Test

Cognition was assessed by the InBrain Cognitive Screening Test (CST). The primary outcome measure was the total score of the InBrain CST, and the secondary outcome measures covered five cognitive domains of InBrain CST, which were attention, language, visuospatial function, memory, and frontal/executive functions. The InBrain CST is a tablet-based computerized cognitive screening test consisting of seven neuropsychological subtests—namely, the Visual Span Test (VST) forward and backward tasks for attention, the Difficult Naming Test (DNT) and semantic (fruits) and phonemic (Korean alphabet digeut) word fluency test for language, the Block Design Test for visuospatial function, time orientation and the Word Place Association Test (WPAT) for memory, and the Korean Trail-making Test—Elderly Version (K-TMT-E) for frontal/executive function [20].

Functional Near-Infrared Spectroscopy

The activity of the frontal lobe was measured with fNIRS. The hemodynamic response of the prefrontal cortex was recorded during the cognitive tasks using a portable, wireless continuous-wave near-infrared spectroscopy system (FNIRS; OBELAB, Inc., Seoul, Korea) [21, 22]. The device was composed of 24 sources (laser diodes) emitting two wavelengths (780 and 850 nm) and 32 photo-detectors where a source and a detector in each pair were 3 cm from each other, forming 48 channels with a sampling rate of 8.138 Hz [23]. The raw signals were first filtered by a band-pass filter (0.005–0.1 Hz) to minimize potential environmental artifacts and physiological noise due to body movement. After the optical density of each wavelength was derived, the relative concentration changes of oxy and deoxy hemoglobin were calculated via the modified Beer–Lambert law [24]. Channels with poor signal quality (coefficient of variation < 7.5%; low-frequency values < .3 where the correlation between oxy-Hb and deoxy Hb was < -.9 [25]) were rejected before being submitted for further analysis. The concentration values were block-averaged using values 5 s prior to each block as a baseline. Subsequent analyses were mainly conducted on oxy-Hb concentration changes. Participants performed three cognitive tasks—namely, the Digit-Span Task (DST), Stroop Task (STROOP), and Social Event Memory Task (SEMT). Each task consisted of two blocks of 2-min interleaved with a pair of 30-second resting periods prior. For statistical tests, block-averaged oxy-Hb changes from each channel were averaged to form eight regions of interest (ROIs) to yield more stable signals from each participant and to reduce the number of comparisons in subsequent tests.

Secondary Outcome Measures

The secondary outcome measures included various scales as follows: the K-MMSE [26], the Korean Everyday Cognition (K-ECog) [27, 28], the Bayer ADL (B-ADL) [29, 30], the Subjective Memory Complaints Questionnaire (SMCQ) [31, 32], the Korean version of the Geriatric Depression Scale (GDepS) [33, 34], the Korean version of the WHO’s Quality of Life Scale (Abbreviated Version) (WHOQOL-BREF) [35, 36], the Self-efficacy Scale (SES) [37], and the Attention Questionnaire Scale (AQS) [38].

Statistical Analysis

To analyze differences in demographic characteristics and S-IADL scores between the intervention and control groups, the chi-square test and independent t test were used. The primary and secondary outcome measures of the InBrain CST and various scales were analyzed using two-way repeated-measures analysis of variance to evaluate differences between the two groups (the intervention and control groups) at two time points (baseline and after 16 weeks of cognitive training). In the fNIRS analysis, we included the results of 72 participants after excluding missing data due to unintentional technical problems: the intervention group (n = 32) and the control group (n = 32). The resulting eight ROIs were the right and left dorsolateral prefrontal cortices (DLPFCs), right and left frontopolar cortices (FPCs), right and left orbitofrontal cortices (OFCs), and right and left ventrolateral prefrontal cortices (VLPFCs). Because most of the channels (channels with a 40%–50% rejection rate) in the bilateral VLPFCs were rejected during preprocessing, the formal statistical tests were performed on regions other than the bilateral VLPFC regions. The mean signals from the left and the right hemispheres and overall prefrontal cortex were also examined as additional analysis scope. The criterion for statistical signiﬁcance was set at P < .05. All statistical analyses were performed using R statistical software (R Foundation for Statistical Computing, Vienna, Austria) [39].

3.1 Participants in the final analysis

A total of 101 older adults without dementia was randomly assigned, including 51 to the intervention group and 50 to the control group. Of the 51 intervention participants, seven (13.7%) were excluded because their rate of cognitive training completion was <80% and three participants (5.8%) were removed from the final statistical analysis because they did not perform the InBrain CST after the 16-week training program. In the control group, six participants (12.0%) discontinued due to disease, withdrawal of consent, or loss of follow-up. Therefore, a total of 85 participants (84.1%) was included in the final analysis, including 41 participants (80.3%) in the intervention group and 44 participants (88.0%) in the control group. The average rate of smartphone application task-completion of the 41 intervention participants reached 94.8%. The flow diagram for study participants is presented in Figure 1. There were no significant differences between the intervention and control groups in age, sex, years of education, or baseline scores of K-MMSE and S-IADL (Table 3).

3.2 Intervention effects on cognitive performance

The group-by-time interaction effect was significant in the language domain scores of the InBrain CST, suggesting that the intervention group showed a larger increase than the control group at 16 weeks (P = .019). There was no significant interaction effect in total score (P = .297) or the attention (P = .694), visuospatial function (P = .081), memory (P = .331), or executive (P = .906) domain scores of the InBrain CST.

To conduct further analysis of the language domain scores where the group-by-time interaction effect was significant, the language domain subtest scores were further analyzed. Significant interaction effects were observed in the phonemic generative naming test (P < .001), not in the semantic generative naming (P = .677) or the Difficult Naming Test (P = .295). The intervention group showed a larger increase than the control group only in the phonemic generative naming test at 16 weeks. These results of InBrain CST are presented in Table 4.

3.3 Intervention effects on frontal lobe activation

In the hemodynamic response of the prefrontal cortex measured by all channels of fNIRS, the group-by-time interaction effect was marginally significant only in the STROOP incongruent task (P < .055). In the ROI analysis, the significant interaction effect was confirmed only in the DLFPCs, and there was no significant effect in the VLPFCs, OFCs, or FPCs. Furthermore, there was no significant interaction effect in the hemodynamic response of the prefrontal cortex while performing the DST, SEMT, and STROOP congruent tasks. These results are presented in Table 5 and Figure 2.

3.4 intervention effects on other scales

When the second outcome measures of various scales were investigated, the group-by-time interaction effects were not significant in the K-MMSE, K-ECog, B-ADL, SMCQ, GDepS, WHOQOL-BREF, SES, or AQS. These results are presented in Table 6.

This study was performed to confirm the intervention effect of the IBT, an Android-based cognitive training software, on cognitive function and activation of the prefrontal cortex among non-demented older adults. As a result of our study, the group-by-time interaction effect was significant only in the language domain of the InBrain CST—specifically in the phonemic generative naming test but not in the semantic generative naming or the Difficult Naming Test. Furthermore, in the hemodynamic response of the prefrontal cortex as measured by fNIRS, the group-by-time interaction effect was significant only in the dorsolateral prefrontal cortex during the STROOP incongruent task. Unexpectedly, there were no group-by-time interaction effects in the various scales for ADLS (i.e., K-ECog, B-ADL), depressive mood (i.e., GDepS), self-efficacy (i.e., SES), quality of life (i.e., WHOQOL-BREF), or subjective cognitive problems (i.e., SMCQ, AQS).

In terms of cognitive outcomes, the intervention group showed a significant improvement after 16 weeks of cognitive training only in the phonemic generative naming test among the subtests of the language domain. During cognitive training studies, improvements in language function, especially the generative naming ability, have been reported in previous studies [40–42]. In the above paper, language function was mainly evaluated by the semantic & phonemic verbal fluency task and the Boston naming test, and the summary effect size observed after cognitive training was moderate and significant. The treatment group showed significantly improved phonemic verbal fluency compared to the control group, which suggested that cognitive training might facilitate left prefrontal function. In addition, it immediate memory, delayed memory, and language improved when cognitive training was performed for ≥6 months with a computerized brain exercise program, such as Brain Fitness (Dakim Inc., Santa Monica, CA, USA), in older adults [9, 43]. The Application-based Cognitive Training at Home (ACTH) intervention study also deployed the IBT cognitive training program among non-demented older adults in the community. After one year of cognitive training 20–30 min in duration every day, the ACTH intervention group showed significant improvement in the total, memory, and language domain scores of the InBrain CST compared to the control group [16]. The reason why there were more cognitive domain effects in ACTH compared to in our study is that the intervention period of the ACTH was one year, which is longer than the four months of our study intervention.

Unexpectedly, there was no significant difference between the intervention and control groups in the scales for ADLS, depressive mood, self-efficacy, quality of life, and subjective cognitive complaints. Although it is difficult to identify significant improvements in psycho-behavioral factors after only four months of an intervention program, our result differed from those of previous studies showing that cognitive training usually could increase elderly participants’ confidence and life satisfaction [44, 45]. Our results seem to have arisen as a result of the psycho-social atmosphere during the study period, as psychological disturbances and anxiety levels among elderly populations increased with the start of the coronavirus disease 2019 pandemic.

The hemodynamic response of the prefrontal cortex as measured by fNIRS demonstrates the prefrontal cortical activation involved in cognitive tasks. These brain activations could provide valuable information about the mechanisms by which cognitive interventions improve cognitive function because functional brain changes are usually expected to appear in brain areas related to cognitive skills that are being trained and improved. In our study, the group-by-time interaction effect was only significant in the dorsolateral prefrontal cortex during the STROOP incongruent task, which meant that the intervention group had greater prefrontal activation than the control group during the task. The performance of the STROOP incongruent task involves the inhibitory control process that facilitates the suppression of automatic cognitive activity by new and non-automatic cognitive activity in cognitively conflicted conditions [46]. The inhibitory control ability is one of the major functions of the prefrontal cortex, and our results suggested that the IBT training was effective in strengthening prefrontal function. Furthermore, our fNIRS result was in line with the intervention group performing better on the phonemic generative naming test of the InBrain CST, which is known to measure left prefrontal function.

Although not many studies have reported cognitive training–induced changes in the frontal lobe, some have shown increased activation after cognitive training. Balardin et al. [47] examined differences in fMRI activation and deactivation patterns during episodic verbal memory encoding between individuals with Mild Cognitive Impairment (MCI) and healthy controls. Participants were scanned before and after a single session of strategic semantic training during the encoding of word lists. After training, both MCI and healthy controls exhibited increased activation in frontoparietal network regions, including the left dorsolateral and ventrolateral prefrontal cortices. And patients with MCI only had increased activation of the ventromedial prefrontal cortex and the right superior frontal gyrus related to semantic strategy implementation. Belleville et al. [48] used fMRI to determine the effects of memory training on brain activation in older adults with MCI were trained on memory encoding and retrieval strategies for six weeks, 120 min each day. During the fMRI scan, participants were instructed to memorize a list of words (encoding) and to recognize previously learned words among new word lists. After training, brain activation increased in the frontal, temporal, and parietal areas, especially in the right inferior parietal lobe, in MCI patients. These results suggest that cognitive interventions induce changes in brain regions/networks that mediate processes (e.g., lateral frontoparietal cortex) and result in significant neuronal changes that can be measured by brain imaging and indicate that the brains of MCI patients remain highly plastic. In another study, Moon et al. [49] evaluated the impact of a multi-domain lifestyle intervention, the SUPERBRAIN, on regional homogeneity (ReHo) in resting-state brain fMRI data, confirming that the ReHo values in the left medial orbitofrontal gyrus and right superior parietal lobule were increased in the facility-based intervention group compared to the control group.

Our study has a few limitations. First, when we measured the hemodynamic response of the prefrontal area using fNIRS, the performances of tasks carried out simultaneously, such as STROOP, SEMT and DST, were not recorded. Therefore, activation of DLPFCs in the intervention group was interpreted in the context of other cognitive outcomes. Second, we could not control the indirect psychological influences of the coronavirus disease 2019 pandemic on our participants during the study period, so various scales for depressive mood, self-efficacy, quality of life, and subjective cognitive complaints might reveal changes unrelated to the study intervention in psychological characteristics after cognitive training.

Nevertheless, our study is meaningful in that cognitive training software implemented as an application on personal devices, such as smartphones and tablet computers, led not only to cognitive enhancement, but also increased prefrontal lobe activation. When elderly individuals participate in cognitive training using digital devices, they recognized them as mentally challenging, which increases brain connections and has a positive effect on cognitive function [9]. Therefore, cognitive training applications like the IBT can be expected to enable the delivery of effective cognitive intervention without time or space constraints in both a clinical setting and at home.

Ethical Approval

This study was approved by the Institutional Review Board (IRB) of Samsung Medical Center (IRB no. 2019-06-083-006), which is responsible for protecting the rights, safety, and welfare of research subjects.

The researchers explained the contents of the study in detail, and obtained consent to participate and consent for publication from all participants.

Competing interests

The authors declare that they have no competing interests.

Author Contributions

Conceived and designed the experiments: Jinju Cho, Duk L. Na, Hyemin Jang, Juhee Chin; Performed the experiments: Jinju Cho, Eunhye Cho, Dayoung An, DaEun Kim; Data curation and formal analysis: Jinju Cho, Eunhye Cho, Dayoung An, DaEun Kim, Ingyu Choi, Jihyun Cha, JongKwan Choi, Juhee Chin; Investigation: Jinju Cho, Eunhye Cho, Dayoung An, Juhee Chin; Writing - original draft: Jinju Cho, Eunhye Cho, Dayoung An, Ingyu Choi, Jihyun Cha; Writing - review & editing: Jinju Cho, Duk L. Na, Hyemin Jang, Juhee Chin.

Funding

This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health Welfare, Republic of Korea (grant number : HR21C0885)

Availability of data and materials

The data cannot be made publicly available due to ethical restrictions. Participants agreed to provide their data only for the researchers at the Samsung Medical Center and Computational Neuroimage Analysis Laboratory of the OBELAB. However, all data is available upon request by contacting the following people. Requests for data and materials will be received by JinJuCho ([email protected])

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Table 1. Detailed explanation of the InBrain Trainer application

Cognitive domain	Task title	Description	Activation area
Attention	Miracle of concentration	Count the number of cards equal to the target number and simultaneously find the number of stimulus shapes in them. Stimuli come in a variety of shapes, patterns, and colors.	Temporal lobe
Attention	Mental imagery of Korean letters	This is a training program to infer four character idioms and to count the number of strokes (horizontal, vertical, diagonal, and circular) in the idioms in the mind using a mental blackboard.	Temporal lobe
Language	Word generation from initial consonants	Participants are required to create as many words as possible with two Korean syllables. The task consists of 144 initial combinations.	Left frontal and temporal lobes
Language	Word-completion task	This task is a modified form of a category fluency task. Participants are required to create as many words as possible suitable for given topic using 1–2 initial consonants of the words as hints. The task consists of 157 topic categories.	Left frontal and temporal lobes
Calculation	Calculation after cracking the code	The task is a modified form of a digit–symbol test. It is an exercise of mental arithmetic using numbers replaced by symbols.	Frontal lobe Left parietal lobe
Calculation	Mental arithmetic calculation	As a basic calculation training program, the exercise consists of four difficulty levels depending on the number of terms and digits and the type of operation involved.	Left parietal lobe
Visuospatial function	Block design	This is a training program to stack blocks in the same format as they are presented in three-dimensional space and to analyzes the shape from various views (top, side, front).	Right parietal lobe
Visuospatial function	Masterpiece jigsaw puzzle	Memorize the characteristics of famous paintings and the name of the artist within the time limit. Complete the puzzle pieces and guess the artist's name.	Right parietal lobe Temporal lobe
Memory	Matching personal information	Remember various personal information, such as people’s faces and names, favorite food, and favorite exercise.	Temporal lobe
Memory	Find the same card	Memorize the position of the card of the same picture for a limited time and find the position of the same picture when all the cards are turned over.	Temporal lobe
Frontal/executive functions	Coin combination exercise	Match the number of coins according to the given conditions (total number of coins and amount of money) with 2–4 types of coins.	Frontal lobe, Left parietal lobe
Frontal/executive functions	Weight inference	Infer the weight of the figure so that both scales have the same weight.	Frontal lobe

Table 2. Weekly/monthly cognitive task difficulty configuration

Duration	Level	Cognitive task set	Number of training tasks
1–4 weeks	Elementary and beginner	1–2 weeks: Set A 3–4 weeks: Set B	6–10 tasks
5–8 weeks	Beginner and intermediate	5–6 weeks: Set A 7–8 weeks: Set B	10–13 tasks
9–12 weeks	Intermediate and advanced	9 weeks: Set A 10 weeks: Set B 11 weeks: Set A 12 weeks: Set B	13–16 tasks
13–16 weeks	Advanced	All sets	17–20 tasks

Set A: Word generation from initial consonants, mental imagery of Korean letters, matching personal information, block design, mental arithmetic calculation, and coin combination exercise. Set B: Word-completion task, miracle of concentration, find the same card, masterpiece jigsaw puzzle, calculation after cracking the code, and weight inference.

Table 3. Demographic characteristics of study participants
	Control group (n = 44)	Intervention group (n = 41)	P value
Age, years	70.75 ± 5.77	71.24 ± 6.02	.700
Sex (M/F)	16/28	13/28	.412
Education, years	13.66 ± 3.13	13.71 ± 2.69	.940
K-MMSE, points	28.73 ± 1.66	28.90 ± 1.24	.586
S-IADL, points	1.48 ± 1.61	1.27 ± 1.29	.512

Abbreviations: K-MMSE, Korean version of the Mini-mental State Examination; S-IADL, Seoul Instrumental Activities of Daily Living.

Table 4. Cognitive outcomes of the InBrain Cognitive Screening Test

	Control group		Intervention group		P value
	Pre	Post	Pre	Post	Group	Time	Group × Time
Total score	59.85 ± 10.59	62.19 ± 10.06	61.67 ± 8.60	65.26 ± 10.11	.239	<.001	.297
Attention domain	8.27 ± 2.86	9.01 ± 2.36	8.68 ± 2.75	9.20 ± 2.38	.537	.035	.694
Language domain	14.22 ± 3.33	14.68 ± 3.10	14.74 ± 2.94	16.42 ± 3.43	.084	<.001	.019
Semantic fluency	11.14 ± 2.54	11.84 ± 2.85	11.71 ± 2.99	12.15 ± 2.90	.405	.073	.677
Phonemic fluency	9.71 ± 3.92	8.93 ± 4.25	9.90 ± 3.35	12.95 ± 4.28	.006	.010	<.001
Difficult Naming Test	10.63 ± 3.41	11.55 ± 2.97	11.00 ± 2.80	11.55 ± 2.97	.780	<.001	.295
Visuospatial domain	7.48 ± 2.97	7.78 ± 2.88	7.52 ± 2.53	8.51 ± 2.29	.487	.002	.081
Memory domain	20.70 ± 2.48	21.89 ± 2.66	21.13 ± 2.54	21.97 ± 2.81	.633	<.001	.331
Executive domain	9.19 ± 2.59	8.83 ± 2.77	9.59 ± 2.33	9.17 ± 2.81	.465	.149	.906

Table 5. fNIRS outcomes at pre- and post-intervention

	Control group		Intervention group		P value
	Pre	Post	Pre	Post	Group	Time	Group × Time
Digit Span Test
All channels	1.846658e-07 ± 4.882003e-07	1.903157e-07 ± 4.290512e-07	1.510052e-07 ± 4.161755e-07	1.250210e-07 ± 3.267736e-07	.549	.890	.794
Social Event Memory Test
All channels	−6.586666e-08 ± 3.716392e-07	1.275785e-08 ± 4.439713e-07	−7.317931e-08 ± 3.625239e-07	−3.437121e-08 ± 3.875491e-07	.826	.441	.964
STROOP congruent condition (word reading)
All channels	7.768051e-08 ± 3.984447e-07	1.553383e-07 ± 4.194475e-07	-8.719264e-08 ± 3.580719e-07	2.479234e-08 ± 3.466661e-07	.072	.047	.712
STROOP incongruent condition (color reading)
All channels	6.992907e-08 ± 4.098553e-07	1.060982e-07 ± 4.187726e-07	-6.910251e-08 ± 2.204959e-07	1.473907e-07 ± 2.498305e-07	.518	.013	.055
DLPFC	1.213210e-07 ± 3.255966e-07	6.989556e-08 ± 2.873651e-07	4.822417e-08 ± 2.462377e-07	2.726988e-07 ± 2.866960e-07	.345	.015	<.001
VLPFC	8.631301e-08 ± 5.828658e-07	1.114187e-07 ± 7.184406e-07	−8.782027e-08 ± 5.394030e-07	−1.067858e-07 ± 3.776621e-07	.226	.982	.879
OFC	1.720621e-07 ± 4.532048e-07	2.275832e-07 ± 5.654294e-07	-6.651365e-08 ± 3.488044e-07	9.054198e-08 ± 3.128447e-07	.012	.140	.371
FPC	1.977483e-07 ± 3.155458e-07	2.442845e-07 ± 5.654706e-07	−3.928061e-08 ± 3.826143e-07	1.548513e-07 ± 2.708319e-07	.029	.055	.274

Abbreviations: fNIRS, functional near-infrared spectroscopy; DLFPC, dorsolateral prefrontal cortex; VLPFC, ventrolateral prefrontal cortex; OFC, orbitofrontal cortex; FPC, frontal polar cortex.

Table 6. Secondary outcomes at pre- and post-intervention

	Control group		Intervention group		P value
	Pre	Post	Pre	Post	Group	Time	Group × Time
K-ECog	1.65 ± 0.50	1.73 ± 0.58	1.68 ± 0.60	1.75 ± 0.57	.797	.047	.916
B-ADL	1.98 ± 0.97	1.92 ± 0.90	2.09 ± 1.00	1.93 ± 1.05	.752	.192	.567
SMCQ	4.43 ± 2.68	3.82 ± 2.78	5.10 ± 3.68	4.51 ± 3.27	.292	.006	.946
GdepS	9.09 ± 7.05	8.68 ± 6.11	8.76 ± 6.08	8.88 ± 5.80	.957	.742	.568
WHOQOL-BREF	71.43 ± 11.81	70.36 ± 11.01	72.35 ± 10.12	72.44 ± 9.21	.491	.501	.450
SES	29.41 ± 4.59	28.93 ± 5.72	30.66 ± 3.90	30.57 ± 4.68	.086	.643	.752
AQS	22.62 ± 4.80	21.73 ± 4.92	23.02 ± 4.84	22.32 ± 5.16	.611	.073	.829

Abbreviations: K-ECog, Korean Everyday Cognition; B-ADL, Bayer Activities of Daily Living; SMCQ, Subjective Memory Complaints Questionnaire; GDepS, Korean version of the Geriatric Depression Scale; WHOQOL-BREF, Korean version of the World Health Organization’s Quality of Life Scale (Abbreviated Version); SES, Self-efficacy Scale; AQS, Attention Questionnaire Scale.

No competing interests reported.

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Efficacy of smartphone application–based multi-domain cognitive training in non-demented older adults

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