go4cognition: Evaluation of a Newly Developed Multicomponent Intervention in Mild Cognitive Impairment

Abstract

Background:

Cognitive training and physical exercise show positive effects on cognitive decline in subjects with mild cognitive impairment (MCI). Multimodal interventions for MCI patients, combining physical and cognitive training in a social context seem to slow down cognitive decline.

Objective:

Based on a previous study, a new mobile gamification tool (go4cognition; https://www.ontaris.de/go4cognition) has been developed to train cognitive and physical functions simultaneously in a group setting. It involves tasks targeting various cognitive functions (short-term memory, working memory, executive functions). The computer-based setup allows for individual performance analysis. This study evaluated the effects of this tool.

Methods:

30 participants with MCI, as defined by the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) cut-off-score, aged between 66 and 89 years, trained for one hour two days a week for twelve weeks. Additionally, standard neuropsychological assessment of memory and attention was carried out before and after the intervention.

Results:

The go4cognition device is highly effective in improving various cognitive functions. A significant improvement in the CERAD total score resulting in re-classification of 70% of former MCI patients into non-MCI patients was found. Additionally, an improvement of verbal fluency, verbal memory, spatial memory, and attention was observed. Furthermore, the CERAD total score was significantly correlated with performance in the go4cognition tool.

Conclusions:

The results of the intervention support the idea of the effectiveness of a combined cognitive and motor intervention by incorporating neuropsychological paradigms in a group setting and suggest a close relation between combined cognitive and physical exercise and cognitive performance.

Keywords

Alzheimer’s disease CERAD total score cognitive training gamification mild cognitive impairment multimodal intervention physiological intervention simultaneous stimulation of cognitive and physical abilities social contact

INTRODUCTION

Cognitive decline of various extent accompanies aging [1]. Due to demographic changes, the incidence of dementia is expected to increase considerably in the future. This phenomenon will significantly affect the health care system worldwide, especially with respect to the socioeconomic as well as medical spending for older adults [2, 3]. Mild cognitive impairment (MCI) reflects an intermediate stage between normal cognitive aging and dementia [4], which increases the risk of dementia by 5–10% [5, 6]. MCI is associated with memory decline that exceeds normal age-related changes, although daily activities are not directly affected [7]. The prevalence of MCI increases from 6.7% in the 60–64 years age group to 25.2% among individuals aged 80–84 years [8]. Interventions to improve cognitive function are needed to slow the cognitive decline that leads to dementia and to improve the well-being of MCI patients and their caregivers [9].

Lifelong social and cognitively stimulating experiences as well as physical activity and a healthy diet appear to be associated with a lower risk of cognitive decline [9 –19]. Cognitive interventions like cognitive training (CT), demonstrated beneficial effects on global cognitive function, attention, memory, and psychomotor learning in individuals with MCI [20 –25].

CT involves repeated practice of specific cognitive functions such as working memory and short-term memory but also includes learning memorization strategies [20 , 27], and stimulates neuroprotective mechanisms based on synaptic plasticity [27, 28]. Therefore, a broad and specific training of cognitive functions is needed.

Additionally, epidemiological data suggest an association between moderate physical activity such as walking and a lower dementia risk [27, 29]. Physical activity appears to protect brain function and may lead to neurogenesis [9, 30]. Several authors found an association between cognitive and physical functioning in older adults with MCI [9 , 31].

Furthermore, findings from different studies yield evidence for the effect that physical exercise leads to slower cognitive decline [5 , 32–43] and increased brain volume in people with MCI [30]. By contrast, unimodal interventions that train only one specific function may be too simple compared to the complexity of cognitive impairment in MCI, but more than one cognitive function (multiple domains versus single domain) may be affected [27, 44].

Multidimensional interventions involving cognitive and aerobic exercise in older adults with MCI resulted in significant improvement in cognitive function as well as an increase in parahippocampal cerebral blood flow [27, 45] and decreases in precuneus/posterior cingulate cortex activity in the delta, theta, and beta bands [9, 46].

Several studies evaluated the effect of a multidimensional intervention. The studies differed with respect to the time devoted to physical and cognitive interventions. Dannhauser et al. (2014) asked their participants to complete in sum 30 h of CT in contrast to 18 h of physical training [47]. Results yield evidence for an improvement in physical fitness [47]. Cognitive functions improved over time as assessed by the digit span backward, the Trail Making Test A/B (TMT A/B) and the category fluency [47]. In contrast, Suzuki et al. (2013) investigated the effect of a training spanning over six months (in sum 18 h) and incorporating simultaneous physical, attention, and memory training as aerobic exercise [48]. Subjects were for instance asked to “to walk while inventing their own poem” [48].

Results provided evidence for better memory performance as well as higher scores in the Mini-Mental State Examination (MMSE) in patients with amnestic MCI (aMCI) [48]. Straubmeier et al. (2017) investigated the effect of a six-month (five-session per week) intervention phase, by applying the so-called MAKS (acronym: Motor, Activities of daily living, Cognitive, Social) therapy which lasts for approximately 2 h per day [49]. This approach combined sensorimotor activation followed by cognitive activation including tasks involving memory, language comprehension, and logical thinking [49]. Results yield evidence for a stabilization of cognitive and activities of daily living (ADL) abilities [49]. It has to be mentioned that this study was carried out in daycare centers which allowed for the high frequency of interventions (240 h) [49]. Han et al. (2017) evaluated the effect of a so-called Multimodal Cognitive Enhancement Therapy (MCET) covering different therapeutical approaches including cognitive training and physical therapy in participants diagnosed with MCI or mild dementia [50]. The intervention included three hours of training three times per week for eight weeks (72 h) [50]. Results provided evidence for improvements with respect to memory performance and quality of life [50]. Taken together, these studies illustrate the effect of multimodal training on cognitive and physical functions. As all studies varied with respect to duration and frequency of the intervention phase, we calculated the average time of training which varies between 18 and 240 h. Additionally, in most of the studies cognitive functions were trained in a traditional way like it is used in neuropsychological rehabilitation (e.g., Rehacom; https://hasomed.de/produkte/rehacom/).

A previous study by our group showed that two non-pharmacological multicomponent interventions combining physical and cognitive training either simultaneously or sequentially improved cognitive functioning and led to a lasting change in the classification of former MCI patients into non-MCI patients based on the CERAD total score cut-off [9]. Based on these findings, a new gamification training tool (go4cognition) was developed. It must be mentioned that the name for the whole funded project was go4cognition and that additionally the newly developed tool received the name of the project. An established program addressing cognitive enhancement in combination with physical exercise is, e.g., the SpeedCourt^®, which is typically used in rehabilitation clinics for athletes, not for subjects with cognitive decline, is not portable and performed alone. By contrast, go4cognition is based on a group training approach and involves different cognitive tasks focusing on functions such as short-term memory, working memory, long-term memory, and executive functions. This allows the training of different cognitive functions using only one computer-based device. It also renders it possible to vary and update the tasks and their demands easily. Digital devices such as tablets and batons allow for an individual analysis of performance within a group to illustrate changes in behavioral performance during training. The performance level can be adjusted automatically. The portable device consists of eight stations, which allows flexible use in different rooms of different sizes (see Fig. 3).

The aim of this study was to evaluate the effect of a twelve-week training (with two 1-h sessions per week) of the newly developed go4cognition device on subjects with MCI as defined by the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) [9, 51], a standard diagnostic neuropsychological tool. As the go4cognition tool targets everyday life cognitive functions, such a behavioral-based classification of MCI will be used. A recent meta-analysis yielded evidence for high diagnostic sensitivity and specificity of the CERAD (Area under summary receiver operating characteristic curve (sAUC) 0.847) [52]. We are aware of the fact, that no further clinical assessment, examination, blood tests or neuroimaging was performed to support this classification. However, Petersen et al. (2004) proposed criteria for the diagnosis of MCI [44]. These include subjective cognitive complaints, objective cognitive decline, the absence of dementia, and normal essential functional activities of daily living [44]. Based on this, suitable participants were included. Furthermore, Petersen et al. (2001) described neuropsychological test batteries that measure memory performance as a guideline for determining the risk of dementia and the degree of existing impairment, as they have proven to be effective, particularly in groups with an increased risk of dementia due to MCI [53]. Barth et al. (2005) showed a sensitive discrimination of the CERAD between mild and moderate Alzheimer’s disease (AD), MCI, major depression, and normal controls (NC), with individuals with MCI showing deficits particularly in verbal fluency and episodic memory compared to healthy controls [54].

Additionally, it has been shown by Chandler et al. (2005) and Paajanen et al. (2010) that the CERAD was able to differentiate between healthy controls, mild cognitive impairment, and AD [55, 56]. For reasons of simplicity, we are using the term MCI and non-MCI in the article which reflects the classification based on the CERAD cut-off score defined by Chandler et al. (2005) [55].

METHODS

Recruitment of participants

The present study was approved by the local Ethics Committee of the Psychological Faculty at the Ruhr University Bochum (No. 627) which complies with the current version of the Declaration of Helsinki of the World Medical Association. Participants were recruited via newspaper articles or the network of senior centers in Oberhausen (North Rhine-Westfalia) and surrounding cities. They gave their written informed consent prior to participation.

Study design

The prospective study design included screening measures, pre-intervention testing, the twelve-week intervention period, post-intervention assessments of cognitive and physiological status, and recording of physical activity using a pedometer up to six months after training. Participants were recruited in a two-stage process that included a screening phase in which potentially eligible individuals were selected from the general population and a second phase in which the eligibility for participation was clinically confirmed by determining the cognitive and physiological status. Baseline measurements took place one to four weeks before the intervention, and post-intervention testing was conducted within seven days after completion of the intervention. Figure 1 illustrates the study design.

Fig. 1

Illustration of the study design.

MCI assessment

MCI assessment was performed using the CERAD total score, which was determined using the demographic correction regression formula of Chandler et al. [55] (raw score –(–0.324 –age+0.897 –education –2.858-sex)). The required raw score includes the sum of the following test scores: Verbal Fluency, Boston Naming Test, Learn word list, Construction exercises, Word list recognition & Word list Discrimination. The demographically corrected CERAD total score showed high test-retest reliability (r = 0.95) and accurately distinguished independent samples of NC, MCI, and AD subjects (NC and MCI: area under curve (AUC).823, MCI and AD: AUC 0.882) [55]. This assessment was performed twice: before the intervention and immediately after the intervention. MCI was defined using a CERAD cut-off score of 68.5–85.1.

Assessment of physical parameters

Regular sporting activity was defined as an exclusion criterion. This was recorded using an adapted version of the Freiburg Physical Activity Questionnaire [57] during the screening phase. Furthermore, physical activity was recorded at several time points during the intervention (one month before the start, one week before the start, every four weeks during and up to six months after the intervention) using a pedometer for seven days each.

Furthermore, the following parameters were examined before and after training: The Timed Up and Go test (TUG) was used to assess general mobility, balance, and the risk of falling. Postural control in a static and dynamic situation was determined using the Tandem Stand (TS). Furthermore, the hand grip strength (HGS) of both hands was measured using the Jamar-Jackson hand grip dynamometer as an indicator of global strength abilities.

Assessment of cognitive functions

A further exclusion criterion was the presence of clinical signs of depression (Beck Depression Inventory-II (BDI II)>20) assessed by the BDI II (Cronbach’s α= 0.90) during the screening phase [58, 59]. Five interested older adults were excluded due to this criterion. Additionally, a test battery including standard neuropsychological tests has been used pre- and post-intervention. This battery included the following tests: The visuoconstructive and visuospatial memory capacity was evaluated using the Rey-Osterrieth Complex Figure (ROCF) [60]. The Verbal Learning and Memory Test (VLMT) was applied to assess verbal learning and memory capacity [61]. Verbal and visual short-term and working memory capacity was evaluated with the Digit-Span and Block-Design subtests of the Wechsler Memory Scale–Revised Edition (WMS-R) [62]. With the computerized German Test of Attention Performance (TAP 2.3.1) different forms of attention performance (Alertness, Go/NoGo, Divided Attention, and Flexibility) were investigated [63]. These tests assess the reaction times in milliseconds (ms) with shorter reaction times reflecting better performance. Beside reaction times, the number of omissions (less omission reflects better performance) and errors (less errors reflects better performance) was analyzed. The German version of a word fluency task (Regensburger Wortflüssigkeits-Test (RWT) was used to examine executive functions [64]. These assessments were performed twice: before and immediately after the intervention.

Sample, inclusion, and exclusion criteria

The current study included older individuals aged from 66 to 89 years with MCI as determined by a standard neuropsychological battery using the CERAD (cut-off: total score >85.1) [51, 65]. Exclusion criteria included dementia (CERAD total score <68.5), clinical signs of depression (BDI II > 20 [58, 59]), regular exercise (assessed using an adapted version of the Freiburg Physical Activity Questionnaire [57]), and severe neurological or motor problems that precluded or limited participation in the physical part of the intervention.

A total of 117 interested older adults was screened. Forty-seven older adults met the previously defined inclusion criteria. 14 participants refused to participate before the start of the training or during the first weeks of intervention due to personal problems with fulfilling the schedule of the project (health problems, other obligations, mobility problems). Additionally, three participants had to withdraw their participation due to health reasons. These 17 participants were therefore excluded from the project. Table 2 illustrates the cognitive status of the included participants before and after the intervention.

In total, n = 30 individuals (20 women and 10 men) aged 66 to 89 years participated in the training with an average education of twelve years.

Ninety percent of the participants reported being active in their daily lives (e.g., shopping, gardening), while 3.3% of the participants reported exercising irregularly to a small extent and 6.7% reported being rather inactive. In an adapted version of the Freiburg Physical Activity Questionnaire, 86.7% of the subjects reported being physically active for less than one hour per day (gardening, climbing stairs, swimming, etc.). 66.7% of the participants reported being cognitively active (Sudoku, crossword puzzles, theater, active participation in a choir), while 33.3% reported being inactive in this regard.

Due to health reasons, not all 30 participants were able to complete the survey following the intervention, so that less data could be expected for a few test procedures (at least 24 people). The CERAD total score was recorded for all 30 participants.

Table 1 illustrates the sample characteristics.

Table 1

Demographic data (mean, standard deviation, and range) and CERAD total score

	M	SD	Range
Age	80.41	5.83	66.00–89.00
Years of education	11.53	3.26	8–18
CERAD total score	79.90	4.34	69.46–84.89

CERAD, Consortium to Establish a Registry for Alzheimer’s Disease.

Fig. 2

Illustration of one station showing new cognitive tasks.

Fig. 3

Illustration of the structure of the intervention with the stations showing new cognitive tasks.

Intervention

The tasks included in the go4cognition tool have been developed by the researchers and have been implemented in the go4cognition tool by the company Ontaris (https://www.ontaris.de/). Technical solutions like the baton and the usage of tablets etc. have been developed by this company.

Table 2

Cognitive status as assessed by standard neuropsychological tests of all participants before and after intervention as well as results of the paired sample t-test (pre-intervention, post-intervention) for all included neuropsychological tests. A Bonferroni correction using a corrected alpha = 0.002 (0.05/24) was used in this analysis. Below-average performance is shown in italics. In addition to the Raw Value and Standard Deviation (SD), the Percentage Rank (and its standard deviation) are presented. Percentage Ranks below 16 reflect performance below one standard deviation (below average)

	Pre		Post
	Raw Value (mean, SD)	Percentage Rank (mean, SD)	Raw Value (mean, SD)	Percentage Rank (mean, SD)	T	p
CERAD total score	79.90 (4.34)		88.85 (8.11)		–8.42	<0.001
BDI	9.10 (5.25)		8.63 (7.18)		0.501	0.62
ROCF	13.32 (5.55)	17.22 (17.03)	13.82 (6.26)	20.52 (18.29)	–0.25	0.803
RWT (lexical)	11.79 (5.51)	44.34 (29.21)	16.81 (6.55)	59.26 (28.69)	–5.37	<0.001
RWT (categorical)	16.48 (5.16)	30.03 (16.28)	30.11 (8.89)	57.19 (24.48)	–7.99	<0.001
RWT (alternate categorical)	14.52 (3.85)	46.66 (25.67)	17.89 (3.69)	67.85 (18.92)	–4.24	<0.001
RWT (alternate lexical)	10.77 (4.26)	26.42 (20.87)	15.50 (5.40)	46.24 (26.46)	–4.96	<0.001
VLMT (learning)	30.65 (8.53)	12.72 (12.59)	33.42 (9.33)	17.43 (17.03)	–1.85	0.076
VLMT (interference)	2.33 (1.47)	7.92 (10.26)	3.11 (1.37)	13.91 (15.77)	–1.29	0.030
VLMT (loss after interference)	3.07 (2.17)	26.53 (24.16)	3.15 (1.81)	24.37 (19.47)	–.15	0.875
VLMT (direct recall)	4.58 (2.97)	10.22 (13.29)	5.58 (3.47)	15.28 (21.49)	–2.02	0.053
VLMT (delayed recall)	4.41 (2.82)	9.92 (11.73)	5.26 (3.34)	15.44 (16.85)	–1.98	0.058
VLMT (loss)	3.37 (1.71)	19.72 (21.72)	3.37 (1.86)	20.54 (19.53)	0.00	1.000
WMS (digit span)	5.93 (1.31)	30.20 (20.63)	6.41 (1.42)	42.30 (26.02)	–1.61	0.119
WMS (digit span –WM)	4.60 (1.04)	25.00 (14.94)	5.07 (1.44)	35.59 (25.54)	–1.17	0.252
WMS (block span)	5.00 (1.51)	8.3 (15.27)	6.63 (1.84)	30.26 (31.60)	–5.09	<0.001
WMS (block span –WM)	4.70 (1.49)	17.03 (16.29)	5.44 (1.95)	27.07 (26.67)	–2.03	0.052
TAP Alertness (RT, ms)	364.07 (117.63)	36.83 (33.49)	369.07 (103.03)	26.07 (24.06)	–0.34	0.732
TAP Divided Attention (number of omissions)	6.62 (5.23)	24.17 (24.11)	6.04 (4.65)	24.72 (25.95)	0.81	0.421
TAP Divided Attention (number of errors)	8.07 (15.52)	41.14 (38.71)	5.35 (5.72)	32.38 (34.27)	0.95	0.348
TAP Go/NoGo (RT, ms)	749.07 (182.62)	41.79 (35.57)	761.29 (224.55)	38.89 (36.74)	–0.30	0.766
TAP Go/NoGo (number of errors)	6.07 (5.71)	12.59 (16.76)	3.17 (4.72)	25.61 (19.98)	3.19	0.003
TAP Flexibility (RT, ms)	2238.45 (1156.36)	27.35 (30.68)	2319.28 (1703.91)	33.69 (33.53)	–0.44	0.657
TAP Flexibility (number of errors)	8.66 (6.88)	30.07 (30.32)	7.48 (6.36)	33.76 (30.46)	1.40	0.171

CERAD, Consortium to Establish a Registry for Alzheimer’s Disease; BDI, Beck Depression Inventory II; ROCF, Rey Osterrieth complex figure; RT, Reaction Time in ms; RWT, Regensburger Wortflüssigkeits-Test; TAP, Test of Attentional Performance; VLMT, Verbal Learning and Memory Test; WMS, Wechsler Memory Scale –Fourth Edition; WM, Working Memory.

The training took place in a group setting including seven to ten people, with only seven participants training at one time. Three participants always took a break to avoid overloading. Training took place twice a week in the mornings for one hour each. The break resulted in a training time of about 45 min per session for each participant. The setting consisted of eight stations arranged in a circle, which were equipped with a tablet on which various cognitive tasks were presented (remembering sequences of numbers forwards and backwards to assess short-term or working memory or sequences of images to assess visual memory, a variation of the subject-ordered task as invented by Petrides and Milner and forming words from presented syllables or letters to assess executive functions, attention, and short-term memory) [66]. Subjects received a baton with which they could identify themselves at the stations by means of a Radio Frequency Identification (RFID) chip. This device was also used to record the performance of each subject at each station allowing for the digital analysis of speed and performance. The order of the tasks was predefined in a way that the group could work independently. They were supervised by trained physiotherapists who could help if needed. All cognitive tasks required the subjects to visit the individual stations in the order predetermined by the corresponding task, which had to be remembered after a brief presentation. In this way, cognitive abilities and physical mobility were trained simultaneously. The participants covered an approximate distance of 800 to 1000 meters per session. Previous research showed the effectiveness of a combination of cognitive and physical stimulation in slowing the cognitive decline of older individuals with MCI and in improving their cognitive abilities to a reclassification from formerly MCI range to the non-MCI range [9]. The importance of social contact has been described in several studies [9, 29]. The collaboration involved in solving cognitive tasks together in addition to the already existing social contact with the other participants in the group reinforced this effect. The distance covered, the time required, and the correctly solved tasks were recorded by means of the system. The level of difficulty was automatically adjusted to the subject’s performance. With at least 80% correct responses in the previous task, the level of difficulty was increased, with 50% or less correct responses, the difficulty level was reduced by going back the previous level.

Data processing and statistical analysis (pre-intervention and post-intervention)

The Statistical Package for the Social Sciences software (SPSS, version 29.0; https://www-01.ibm.com/software/de/stats29/) was used to analyze the acquired data. To determine possible effects of the intervention on cognitive (neuropsychological tests) and physical parameters (TUG, TS, and hand strength) paired sample t-tests were used. These were found to be robust against violations of the normal distribution for large samples (from n = 30) [67].

Using a Pearson’s bivariate correlation analysis, a possible relationship between age or physical activity and a possible improvement in cognitive abilities was analyzed. A mixed analysis of variance (ANOVA) including the factor Group (gender) and Time (pre versus post) was calculated to examine a possible difference between the genders. In order to fulfill the requirements of an ANOVA (normal distribution of the data and sphericity), a Kolmogorov-Smirnov and a Mauchly test with a Greenhouse-Geisser or Huynd-Feldt correction were performed to adjust the degrees of freedom in the absence of sphericity. Deviating data were identified using boxplots.

A Bonferroni correction was applied to adjust the results for multiple comparisons.

MCI status analysis

After the intervention, based on the CERAD total score, participants were divided into two groups (still meeting the criteria of MCI and not meeting the criteria of MCI (non-MCI)) for further analysis of possible underlying modulatory processes of the cognitive profiles. A bivariate Pearson correlation analysis was calculated to determine a correlation between the improvement in general cognitive performance in the CERAD (pre-post) and performance in other cognitive functions. A mixed ANOVA was calculated to examine possible interaction effects between the factors group (MCI/non-MCI) and time (pre/post).

Furthermore, to look more closely at the improvement in general cognitive performance as reflected by the CERAD total score, the non-MCI group was divided into one that showed a higher baseline performance in the CERAD total score before the training (over 80 points) and one whose performance was lower before the intervention.

Comparison of the CERAD total score with the performance during training

In addition, the performance in the CERAD total score before and after the intervention was compared with the performance in the individual training tasks using a bivariate Pearson correlation analysis. The highest levels of the different training tasks were included in this correlation analysis.

RESULTS

Physical parameters

Results of the TUG and the TS tests showed an impairment of functional mobility with TUG scores below one point (equaling measured time under 10 s) for 53.3% of participants in the first examination but no impairment at the level of static posture control as measured by the TS test.

There was no improvement in the TUG with 10.81 s needed pre-intervention and 10.08 s needed after intervention (26.9% of participants showed an impairment of functional mobility) and hand strength from 22.41 kg pre- to 24.54 kg post-testing (TUG: t(25) = –0.600, p = 0.554; hand strength: t(29) = –0.194, p = 0.242). There was also no significant difference in TS scores before (10.00 s) and after intervention (9.92 s), t(21) = 1.000, p = 0.329.

Recording physical activity with a pedometer showed an increase in the average number of steps before the intervention in contrast to the time during the intervention by M = 636.1250 SD = 1595.02 (pre: M = 9829.50, SD = 3454.34; during intervention: M = 10082.67, SD = 2597.48) steps per day. After completion of the intervention, the average number of steps per day decreased by M = 463.54, SD = 1212.51 (post: M = 9952.63, SD = 2883.92). Overall, the number of steps taken per day increased slightly on average by M = 102.00, SD = 1514.02 steps per day compared to the number of steps taken daily. However, these changes did not reach significance (pre-post: t(18) = –0.286, p = 0.778; pre-during intervention: t(23) = –1.954, p = 0.063).

CERAD

The CERAD total score was assessed at two time points (pre-intervention and post-intervention) to determine the cognitive status. Results of a paired sample t-test yield evidence for a significant effect of the intervention with regard to the cognitive status t(29) = –8.43, p < 0.001, d = 1.54 (M_Diff = 8.96, 95% –CI[6.78, 11.13]). There was no significant difference between sexes F(1,28) = 0.3160, p = 0.692, η_p² = 0.006. Also, no significant correlation between the improvement in cognitive status and age (r = 0.306, p = 0.121) or physical activity (r = 0.105, p = 0.583) could be observed.

Neuropsychological tests

All results of the statistical analyses using a paired sample t-test for the standard neuropsychological tests are summarized in Table 2. To control for inflated type I error rate, we applied a Bonferroni correction using a corrected alpha = 0.002 (0.05/24).

Significant pre-post differences were found with respect to verbal fluency (lexical: t(25) = –5.38, p < 0.001, d = 1.06, categorical: t(25) = –7.00, p < 0.001, d = 1.59, alternate categorical: t(25) = –4.24, p < 0.001, d = 0.83 and alternate lexical: t(25) = –4.97, p < 0.001), d = 0.98, which was assessed using the RWT, as well as in relation to spatial short term memory as assessed by the block-tapping task (forward) t(26) = –5.10, p < 0.001, d = 0.98. Table 2 illustrates the cognitive status of the included participants before and after the intervention.

MCI versus non-MCI

The CERAD was administered at two time points: pre-intervention and post-intervention. According to the cut-off value (85.1), participants were divided into MCI (below 85.2) and non-MCI (above 85.1), provided that this cut-off value was exceeded or not reached post-training. The distribution of the participants with respect to this criterion is illustrated in Fig. 4. Seventy percent of all participants met the criteria for the non-MCI group after the intervention. The mean CERAD total score of the MCI group was 79.54 (SD = 4.5) and that of the non-MCI group was 92.83 (SD = 5.6).

Fig. 4

Distribution of participants based on the CERAD cut-off (81.5 separating MCI (M = 79.54, SD = 4.5) and non-MCI (M = 92.84, SD = 5.6)) for pre-intervention and post-intervention time point.

Comparison of change in CERAD total score and other neuropsychological tests

For a closer look at the improvement in cognitive performance, the improvement in the CERAD total score (difference pre-post) was correlated with the performance in standard neuropsychological tests (see Table 3). A significant correlation between the change in the CERAD total score (difference pre-post) and the ability to learn new unassociated information (measured by trial one –five of the VLMT) could be determined for the non-MCI group (r = 0.508, p = 0.032). The non-MCI group showed better baseline performance and improved constantly, while the MCI group’s performance remained rather unchanged. For the MCI group, there was no significant correlation between the change in performance on the CERAD total score and performance on the VLMT (r = –0.215, p = 0.578). The capacity of long-term memory retrieval performance was also assessed using the VLMT. A significant correlation between the results of the VLMT and the CERAD total score increase (difference pre-post) could be shown r = 0.607, p = 0.007 for the non-MCI-group but not for the MCI-group: r = –0.526, p = 0.145. Again, the non-MCI group showed better baseline performance. The performance of both groups improved steadily.

Table 3

Pearson correlation between the change in cognitive status (difference pre –post-intervention), assessed by CERAD total score, and performance in all included neuropsychological tests divided for MCI and non-MCI

	MCI Change of		Non-MCI Change of
	CERAD total score		CERAD total score
	r	p	r	p
BDI	–0.468	0.763	–0.403	0.097
ROCF	–0.312	0.495	0.309	0.213
RWT (lexical)	–0.393	0.295	0.293	0.238
RWT (categorical)	–0.474	0.197	0.312	0.208
RWT (alternate categorical)	0.435	0.241	0.003	0.991
RWT (alternate lexical)	–0.318	0.405	0.397	0.103
VLMT (learning)	–0.215	0.578	0.508	0.032
VLMT (interference)	0.116	0.766	0.069	0.787
VLMT (loss after interference)	0.290	0.449	0.027	0.916
VLMT (direct recall)	–0.590	0.094	0.363	0.138
VLMT (delayed recall)	–0.526	0.145	0.607	0.007
VLMT (loss)	0.140	0.719	–0.199	0.429
WMS (digit span)	0.146	0.708	–0.515	0.029
WMS (digit span –WM)	0.022	0.955	–0.005	0.986
WMS (block span)	0.077	0.845	–0.240	0.337
WMS (block span –WM)	–0.612	0.080	0.031	0.904
TAP Alertness (RT, ms)	–0.257	0.505	–0.123	0.594
TAP Divided attention (number of omissions)	–0.146	0.708	–0.041	0.864
TAP Divided attention (number of errors)	–0.215	0.579	–0.180	0.447
TAP Go/NoGo (RT, ms)	0.275	0.474	0.009	0.971
TAP Go/NoGo (number of errors)	–0.046	0.906	0.094	0.694
TAP Flexibility (RT, ms)	–0.131	0.737	0.044	0.853
TAP Flexibility (number of errors)	–0.505	0.166	0.127	0.595

CERAD, Consortium to Establish a Registry for Alzheimer’s Disease; BDI, Beck Depression Inventory II; p, significance level (two-sided); r, correlation coefficient (Pearson); ROCF, Rey Osterrieth complex figure; RT, Reaction Time in ms; RWT, Regensburger Wortflüssigkeits-Test; TAP, Test of Attentional Performance; VLMT, Verbal Learning and Memory Test; WMS, Wechsler Memory Scale –Fourth Edition; WM, Working Memory.

Verbal short-term memory performance was assessed using the digit span of the WMS-R. For the non-MCI group, the improvement (difference pre-post) within the general cognitive performance (CERAD total score) correlated negatively with short-term memory performance after training (r = –0.515, p = 0.029). However, for the MCI group that showed lower baseline performance in remembering a range of numbers and whose performance tended to decrease on average, compared to the performance of the non-MCI group, which increased, this correlation could not be observed (r = –0.146, p = 0.708).

In addition, there were interaction effects between the change (difference pre-post) in general cognitive performance (CERAD total score) and visual working memory performance (block span) between the factor Time and Group (MCI/non-MCI), F(1, 25) = 7.63, p = 0.011, partial η² = 0.23. This was also shown for divided attention, as measured by TAP, in relation to the number of omissions, F(1, 27) = 7.91, p = 0.009, partial η² = 0.227. There was a correlation between the change (difference pre-post) in the CERAD total score and the change in the block span (r = –0.436, p = 0.023). While the performance of the non-MCI group increased in terms of visual working memory performance, that of the MCI group decreased.

This picture also emerged regarding the number of omissions in the TAP’s divided attention task. While the number of omissions in the non-MCI group decreased, that of the MCI group increased.

Again, there was a correlation between the change in the number of omissions and the change (difference pre-post) in general cognitive performance in the CERAD total score (r = 0.393, p = 0.035).

Further analysis of MCI patients

A closer look at the improvement

To look more closely at the participants’ improvement, the non-MCI group was divided into two sub-cohorts: the first included those whose CERAD total score performance was already high (above 80 points) before the training, with those whose performance was lower (below 80 points) before the training. It was found that both non-MCI groups showed an average improvement of 11 points in the CERAD total score after training, while the performance of those who were in the MCI group after training improved less on average (2.9 points) (see Fig. 5).

Fig. 5

Average improvement in the CERAD total score of the two groups MCI versus non-MCI. The non-MCI group was further divided into a group with a higher baseline CERAD total score (above 80 points) and one with a lower baseline CERAD total score (below 80 points).

Comparison of CERAD total score before and after the intervention with training performance

The final highest go4cognition training results were additionally correlated with the pre- and post-CERAD total scores separately (see Table 4). Results show a high correlation between the post CERAD total score with the performance in the training module addressing short-term and working memory performance, Alphanumerics and Pictures (forward and backward). CERAD pre- and post-total scores were also significantly correlated with the training module World Tour (based on the approach used in the Subject Ordered Pointing Task (see Petrides and Milner [66]), which addresses executive functions. Results from the go4cognition Picture module were significantly correlated with the post-CERAD total score.

Table 4

Pearson correlation between cognitive status (pre & post-intervention), assessed by CERAD total score, and performance in the different training modules captured by level achieved

	CERAD total score		CERAD total score
	(pre intervention)		(post intervention)
	r	p	r	p
Numbers	0.057	0.764	0.342	0.064
Letters	–0.192	0.309	–0.007	0.971
Pictures	0.184	0.331	0.435	0.016
German Chancellor	0.306	0.106	0.125	0.517
Alphanumerics (forward and backward)	0.140	0.477	0.305	0.115
Numbers (forward and backward)	0.352	0.056	0.494	0.006
Letters (forward and backward)	0.235	0.220	0.255	0.183
German Chancellor (forward and backward)	–0.063	0.751	0.170	0.387
Pictures (forward and backward)	0.319	0.121	0.538	0.006
Word puzzle	0.177	0.351	–0.013	0.946
Syllable word puzzle	0.305	0.102	0.275	0.141
World tour	0.450	0.013	0.459	0.011

p, significance level (two-sided); r, correlation coefficient (Pearson).

DISCUSSION

Effects of go4cognition on the MCI classification

The present study aimed at investigating the effect of a newly developed gamification tool training cognitive and physical functions simultaneously in a group setting in subjects diagnosed with MCI according to the cut-off value defined by the CERAD. Previous multicomponent interventions indicated positive, lasting effects on cognition [9 , 68–73] as well as on their implementation in daily life [74 –77]. Unfortunately, the present study showed no significant improvement in functional mobility and hand strength, which would have a positive effect on daily life and activity. However, the intervention appears to have a positive effect on verbal fluency performance (RWT), verbal memory performance (VLMT), spatial short-term memory (block span), and response inhibition (TAP-Go/NoGo).

Components of the intervention

The large number of combined approaches makes it difficult to identify effective intervention components as well as a logical and efficient combination. A previous study by our group compared two multimodal interventions for older individuals with MCI. These used different foci to combine exercise with cognitive training and social contact and identified these three components as critical for sustained improvement in both physical and cognitive functioning. Following the intervention, a large proportion of the study population no longer met MCI criteria according to CERAD total score [9]. Unfortunately, the impact of social contact has not been evaluated in the current study. The development of the gamification tool examined here was based on these findings and therefore combines exactly these three components. Additionally, the go4cognition device includes tasks that address different cognitive functions like short-term memory, working memory and executive functions.

Comparison to previous interventions

The results of this study yield evidence for an improvement in the CERAD total score, leading to a classification of older people with MCI into non-MCI and MCI after the intervention. This is consistent with previous research on the effects of combined physical and cognitive interventions [9, 46] and support the relationship between cognitive and physical functions in subjects with MCI [9, 31]. Some proven effective multicomponent treatments are recommended to be administered daily for more than one year [5 , 78], which seems impossible to implement in clinical practice [9]. To evaluate the possibility of increasing effectiveness, the intervention presented here lasted twelve weeks (24 h of intervention in sum) and showed a higher proportion of participants who no longer met MCI criteria after the intervention compared to the previously studied interventions. In the present study, 70% of participants could be assigned to the non-MCI group after the intervention, compared with 59% in the previous study. Compared to the study by Suzuki et al. (2013) who also trained cognitive and physical activities simultaneously, the current study lasted only twelve weeks in contrast to six months [48]. However, the study time was slightly longer in the current study (24 h versus 18 h). It may be discussed controversially if this represents an advantage or not. In our opinion it is easier to implement twelve weeks of intervention into everyday life than 24 weeks. As this was the first study exploring the effect of go4cognition, the effect of a longer intervention will be explored in future studies.

Comparing the current intervention with the previous ones, significant group differences were found in terms of visual short-term memory performance. This might reflect the added value provided by the variety of tasks offered by the newly developed intervention program, in addition to the obvious avoidance of boredom, which entails a variety of tasks and thus the training of different cognitive functions.

Correlation of training modules with CERAD total score

Furthermore, the post-intervention CERAD total score correlated significantly with performance in the go4cogition modules addressing short-term and working memory functions suggesting a training-related effect with respect to the CERAD total score as well as to the neuropsychological performance. Interestingly, the pre- and post-intervention CERAD total score was significantly correlated with a training module addressing executive functions (World tour, based on the Subject Ordered Pointing Task), suggesting that executive functions, which were also addressed in the Alphanumeric and Picture modules may play a key role for improvements of the CERAD total score.

MCI versus non-MCI

Evidence of a marked ability to learn new non-associative verbal information and to retrieve long-term memory as assessed by the VLMT, as well as improvements in visual working memory (WMS –block span), verbal short-term memory (WMS –digit span) and divided attention (TAP) were revealed by post-hoc classification of neuropsychological performance into MCI and non-MCI groups based on the CERAD total score. It is not obvious whether the CERAD cut-off score for classifying MCI reflects sufficient ecological validity. However, the significant improvements in VLMT scores in terms of the ability to learn new, non-associated verbal information in non-MCI group, as well as the ability of long-term memory recall, reflect changes in one of the critical cognitive domains affected by dementia and MCI, and thus ecological validity [9].

Unfortunately, a follow-up survey was not feasible within the project period due to the COVID-19 situation. However, the results of a small subsample of nine participants also indicate a lasting effect on cognitive performance. Thus, 33.3% of the participants could still be assigned to the non-MCI group three months after intervention.

It would also have been interesting to examine cognitive performance after an intervention period of only six weeks in order to evaluate whether efficiency could have been increased with a shorter training period. However, this would not have been possible and would have increased the probability of possible practice effects. Furthermore, the comparison to the previously examined shorter interventions indicates a higher effectiveness of the longer training duration. However, a training duration of twelve weeks still represents a rather short training duration compared to the recommended year [74 , 78].

Limitation

One limitation of the present study is using the CERAD as the only diagnostic tool. In future studies, additional parameters like participants’ medical history, neuroimaging data using computer tomographic or magnetic resonance imaging results to control for tumors or stroke should be acquired. Additionally, blood tests checking for physical problems affecting cognitive functions, e.g., reduced vitamin B-12, should be run.

Practice effects

It needs to be discussed whether the effect described can better be explained by a practice effect, which in the sense of familiarity with the test procedure and the test situation cannot be ruled out [79]. To minimize possible practice effects, parallel versions of the tests were used where available (RWT, VLMT). Furthermore, the test methods used have high retest reliability (VLMT: r_tt = 0.68 –r_tt = 0.87; ROCF: r_tt = 0.76 –r_tt = 0.89; RWT: r_tt = 0.72–r_tt = 0.89), therefore a new survey should be possible after three to four months. Moreover, Chandler et al. (2005) were able to show a good one-month test-retest reliability (r = 0.95) over different samples (AD and NC) for the corrected version of the CERAD total score [55].

The time dependence of a possible exercise effect is not clear [9]. Sanderson et al. (2021), who investigated the accuracy of MCI diagnostics using a method to eliminate a possible practice effect using a test-naïve control group for early detection of MCI, describe a possible reduction in the practice effect due to retroactive interference [9, 79].

Duff et al. (2012) showed a practice effect in a sample of MCI patients for a time interval of one week [9, 80], which is a very short period. In this study, the post-tests took place minimum twelve weeks after the pre-tests. A possible practice effect may therefore have already been reduced. The possible progression of cognitive performance losses, which would have an effect in the opposite direction to a practice effect, must also be considered here.

Furthermore, no intervention was carried out in the two studies mentioned, which makes a comparison difficult [9].

Further analyses in the form of a reduction of possible practice effects by, for example, a test-naïve control group as suggested by Sanderson et al. (2021) unfortunately, were not feasible due to the COVID-19 pandemic [9, 79].

Since a clear distinction is not possible, both, a possible practice effect and an intervention effect should be considered, when analyzing the effectiveness of an intervention [9 , 81].

It could also be noted that the non-MCI group only consists of participants whose performance before the intervention was already very high and close to the cut-off, so that they exceeded this cut-off due to a practice effect. By contrast, our analysis of the non-MCI group indicates a high improvement in general cognitive performance within the CERAD total scores regardless of the level of initial performance. Since previous results also indicate long-term effects [9, 69], a follow-up survey would be of great interest. For example, Burschert et al. (2012) demonstrated a persistence of improvements in cognitive abilities of participants with aMCI after completion of multicomponent treatment for up to two years [69].

Group size

Overall group size could be discussed as a limiting factor. The pre-calculated sample size which was based on a power analysis could not be reached due to the COVID-19 pandemic and unforeseeable events, such as significant damage caused by a flood in one of the cooperating senior citizens’ facilities. However, in total, 117 subjects were assessed using the CERAD, but 70 did not reach the criteria for MCI as defined in this study or presented with depression. To overcome this limitation, future studies should be enrolled as multi-center studies.

A sham or placebo group could not be implemented but could have provided further insight into the underlying processes of the intervention investigated and would have enabled us to control for bias and confounding factors. Unfortunately, the implementation of such a control group was not feasible due to the reasons mentioned above.

Selection bias

In addition, a selection bias must be discussed, which cannot be excluded as participation was voluntary. Two thirds of all participants already participated in stimulating activities prior to this study. It might be speculated that only subjects might have participated in a study like this who have already experience with stimulating activities and are interested in preserving their cognitive level. However, the participants met the criteria of a CERAD cut-off-score which reflects a cognitive decline to a certain amount. Furthermore, most participants reported having many years of education and explained to be active with respect to their cognitive abilities and activities of daily living.

However, general cognitive functioning was in the MCI range, supported by borderline memory performance. The neuropsychological examination further revealed an average attentional performance and word fluency, suggesting that a representative sample has been investigated (see Table 2).

Conclusion

In summary, it was shown that the newly developed non-pharmacological multi-component intervention go4cognition, which combined physical and cognitive training in a group setting, efficiently improved the cognitive functions of older adults with MCI: The cognitive performance of a large proportion of the participants (70%) was no longer in the MCI range after the intervention. Our study provides evidence for the effectiveness of go4cognition in improving verbal and spatial memory performance, word fluency and response inhibition of a combined intervention program with a duration of only twelve weeks.

AUTHOR CONTRIBUTIONS

Vanessa Lissek (Data curation; Formal analysis; Investigation; Methodology; Visualization; Writing – original draft; Writing – review & editing); Boris Suchan (Conceptualization; Funding acquisition; Methodology; Project administration; Supervision; Validation; Visualization; Writing – original draft; Writing – review & editing); Stefan Orth (Conceptualization; Funding acquisition; Project administration; Software).

Footnotes

ACKNOWLEDGMENTS

This work was supported by the Leitmarkt Agentur.NRW, the European Union and the state government of North Rhine-Westfalia, Germany.

The authors would like to thank Prof. Dr. Patriza Thoma for very helpful comments on this manuscript.

FUNDING

This work was supported by the Leitmarkt Agentur.NRW, the European Union and the state government of North Rhine-Westfalia.

CONFLICT OF INTEREST

Stefan Orth is the founder and managing partner of Ontaris GmbH & Co. KG, which developed and technically implemented the go4cognition tool. He was involved in the analysis of the pedometer data.

Beyond that, the authors have no conflict of interest to report.

DATA AVAILABILITY

The data supporting the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

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