Original Paper Received: September 8, 2010 Accepted: December 31, 2010 Published online: February 10, 2011
Neuroepidemiology 2011;36:91–99 DOI: 10.1159/000323950
Computer-Based, Personalized Cognitive Training versus Classical Computer Games: A Randomized Double-Blind Prospective Trial of Cognitive Stimulation Chava Peretz a Amos D. Korczyn b Evelyn Shatil e, f Vered Aharonson d Smadar Birnboim g Nir Giladi c
a
Department of Epidemiology, Sackler Faculty of Medicine, and b Sieratzki Chair of Neurology and Department of Neurology, Tel-Aviv Sourasky Medical Center, Sackler Faculty of Medicine, Tel-Aviv University, and d NexSig Ltd., and Afeka, Tel-Aviv Academic College of Engineering, Tel-Aviv, e Department of Psychology and Center for Psychobiological Research, Max Stern Academic College, Emek Yezreel, f CogniFit Ltd., Yoqneam, and g Ono Academic College, Kiryat Ono, Israel c
Key Words Brain plasticity ⴢ Cognitive enhancement ⴢ Cognitive training ⴢ Older adults
Abstract Background: Many studies have suggested that cognitive training can result in cognitive gains in healthy older adults. We investigated whether personalized computerized cognitive training provides greater benefits than those obtained by playing conventional computer games. Methods: This was a randomized double-blind interventional study. Selfreferred healthy older adults (n = 155, 68 8 7 years old) were assigned to either a personalized, computerized cognitive training or to a computer games group. Cognitive performance was assessed at baseline and after 3 months by a neuropsychological assessment battery. Differences in cognitive performance scores between and within groups were evaluated using mixed effects models in 2 approaches: adherence only (AO; n = 121) and intention to treat (ITT; n = 155). Results: Both groups improved in cognitive performance. The improvement in the personalized cognitive training group was significant (p ! 0.03, AO and ITT approaches) in all 8 cognitive domains. However, in the computer games group it was significant (p ! 0.05) in only 4 (AO) or 6 domains (ITT). In the AO
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analysis, personalized cognitive training was significantly more effective than playing games in improving visuospatial working memory (p = 0.0001), visuospatial learning (p = 0.0012) and focused attention (p = 0.0019). Conclusions: Personalized, computerized cognitive training appears to be more effective than computer games in improving cognitive performance in healthy older adults. Further studies are needed to evaluate the ecological validity of these findings. Copyright © 2011 S. Karger AG, Basel
Introduction
People’s performance on cognitive tasks declines steadily with age [1]. This decline negatively impacts their quality of life, promotes the loss of autonomy and affects everyday activities such as driving, taking medication and grocery shopping [2, 3]. Thus, there has been a great deal of research into possible ways to preserve or enhance cognitive function in an older population. Many studies have provided evidence that cognitive training interventions can result in cognitive gains in healthy older adults [4–10] and that these gains can be maintained for several years [4, 5]. Some studies have shown that improvements do not easily transfer to new Prof. Nir Giladi, MD Department of Neurology, Tel-Aviv Sourasky Medical Center 6 Weizmann Street Tel-Aviv 64239 (Israel) Tel. +972 3 697 4790, Fax +972 3 697 4153, E-Mail nirg @ tasmc.health.gov.il
tasks or that they transfer only to tasks with the same processing requirements as the trained tasks [4–6], with the effect sizes for a cognitive stimulation intervention being quite small [11]. However, other studies have shown that cognitive improvements can transfer to new tasks, including those with different processing requirements than the trained task [7–10, 12]. Most cognitive training interventions are administered in group [4, 5] or individual [7, 12] settings. They may target the training of multiple cognitive domains [12, 13] or a single cognitive domain such as memory [7], attentional control [8], linguistic verbal-auditory processing [9] or working memory [14]. Cognitive training programs vary in the minimum number of training sessions, in the frequency of the required training and in the length of the training sessions. Cognitive training interventions may be administered by a therapist using oral instruction and practice [4] or via computerized technology [9, 12, 13]. With regard to computerized interventions, it is unclear which types of cognitive training programs are the most effective in improving cognitive skills [15]. It appears that training approaches that are designed to accommodate each individual’s neuropsychological strengths and weaknesses, as well as those that offer instant item-specific feedback [8, 16] and dynamically adapt the training program accordingly, are especially effective, particularly in populations with particular cognitive enhancement needs, such as the elderly [17]. For a review of the cognitive training interventions in a healthy older population, see Papp et al. [11]. The present study aimed to investigate the beneficial effects of a multidomain, personalized, computer-based cognitive training and to compare them to those obtained by playing conventional computer games. Methods Population The study was conducted at the Department of Neurology outpatient facilities at the Tel-Aviv Sourasky Medical Center. Healthy adult volunteers aged 50 years or over who attended a self-referral program assessing risk factors for stroke, falls or dementia were invited to participate in the study. Inclusion criteria were willingness to take part in the study and to follow the researchers’ instructions, the ability to understand the meaning of a consent form, and the ability to train on a personal computer at home. Exclusion criteria were a Mini Mental State Examination [18] score ! 25 or a diagnosis of dementia according to the DSM-IV criteria [19], Parkinson’s disease, major depression or any psychiatric disorder requiring treatment, active malignant disease, uncontrolled hypertension, diabetes mellitus, renal or liver disease, or a history of clinical stroke or significant head trauma associ-
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ated with loss of consciousness. Permission for the study was granted by the Institutional Review Board of the Tel-Aviv Sourasky Medical Center, and all patients signed an informed consent prior to their baseline assessment. Procedures This was a randomized, double-blind interventional study. Participants were randomly assigned (using a random number generator) to the cognitive training group or to the computer games group, with investigators and participants being blind to group assignment. Participants received a CD containing either the cognitive training program or the computer games program. To preserve blindness, all CDs were labeled and packaged identically, and all graphics, fonts, opening screens, baseline evaluations and posttraining evaluations were identical on both CDs. Personnel were kept unaware of the participants’ group assignment, which was encrypted in the code number labels on the CDs. The personalized cognitive training program selected for this study was the CogniFit Personal Coach쏐. The program’s training regimen is based on the results of a baseline cognitive evaluation called the Neuropsychological Examination – CogniFit Personal Coach쏐 (N-CPC) [20]. The evaluation is composed of 15 tasks that measure 17 cognitive abilities. Scores on these 17 cognitive abilities are computed based on normative data previously recorded from a large, healthy population (n = 861). These abilities are then ranked (best, medium or poorest) and subsequently trained by means of 21 different training tasks (Appendix 1). Although subjects train on all tasks, the time spent on each task is determined by individual performance. The N-CPC has been validated in younger adults against several major standard neuropsychological tests, including the full Cambridge Neuropsychological Test Automated Battery, Raven’s Standard Progressive Matrices, the Wisconsin Card Sorting Test, the Continuous Performance Test and the Stroop test [20]. The reliability and validity of the N-CPC have been demonstrated in a study of older adults (aged 50 years and over), with an internal consistency of 0.70 (Cronbach’s ␣) and a test-retest reliability of 0.80 (intraclass correlation coefficient) [20]. Twelve classic computer games that significantly engage cognitive processing were selected to create the computer games program. This program shared several features with the personalized cognitive training program, including the baseline cognitive evaluation, a total of 24 sessions comprising 3 different tasks, and a similar graphic design (Appendix 2). However, it did not have the adaptive training features of the personalized cognitive training program. Each individual session of both the computer games and the cognitive training took 20–30 min to complete. Subjects completed approximately 3 sessions per week throughout a 3-month period. This regimen was considered most likely to encourage compliance as it was deemed relatively undemanding in the amount of time required, while at the same time it was sufficiently intensive to provide a training effect, as indicated by previous studies using this program [12–14]. Cognitive performance was assessed at baseline and at the completion of training using the NexAde쏐 cognitive test battery. This reliable battery overcomes heterogeneity due to age, gender, education and computer experience, and it has previously been used with older adults [21–23]. The 6 tasks in the battery bear little resemblance to the 21 training tasks in the personalized cognitive training program or to the 12 traditional computer games.
Peretz /Korczyn /Shatil /Aharonson / Birnboim /Giladi
Subjects rated their satisfaction with their daily cognitive functioning using a visual analog scale at baseline and again following the completion of training. The Geriatric Depression Scale (Short Form) [24] was administered at baseline. Analytical Methods We used mixed effects models (with both fixed and random effects) for repeated measures to evaluate the differences between the two groups’ cognitive scores at baseline and afterintervention, as well as the training effect in each group. We established a separate model for each cognitive domain score and for the overall score. In the mixed effects model, the dependent variable was the cognitive outcome measure and the independent (fixed) variables were time (before or after training), group and the interaction time * group. The subject was the random variable in the model. General linear models were also used to evaluate the postintervention difference between the two groups, adjusting for baseline scores. The dependent variable was the posttraining cognitive outcome measure and the independent variables were group, baseline scores and the interaction groupⴢbaseline scores. The SPSS 14.0 and SAS 9.2 (Proc Mixed) computer software packages were used for statistical analyses. The data were analyzed in 2 approaches: adherers only (AO; participants who did not deviate from the protocol and provided a complete set of data) and intention to treat (ITT).
Results
Study Population A total of 155 individuals were enrolled in the study. Participants were randomly assigned to either the cognitive training group (n = 84) or the computer games group (n = 71; fig. 1). (The unequal number of subjects at baseline in the two groups was found after completion of the experiment, when blindness was broken, and is a random occurrence.) A total of 34 (22%) participants (18 in the cognitive training group and 16 in the computer games group) did not complete the training; the majority of those (n = 29) never began the home training. In these cases, no specific reason was given aside from ‘personal reasons,’ which, to our understanding, meant an unwillingness to adhere to the protocol after becoming familiarized with it during the baseline assessment. Thus, the AO analysis included a total of 121 participants, 66 in the cognitive training group and 55 in the computer games group. The baseline characteristics (age, gender, education level, Mini Mental State Examination score) of the two groups were similar (table 1). There was no significant difference in the baseline characteristics of the noncompliant and adherent subjects, although a higher proportion of men were noncompliant in the cognitive training group. No significant gender influences were found in any of the analyses. Computerized Cognitive Training versus Classical Computer Games
Enrolled n = 155
Personalized cognitive training group n = 84 (ITT analysis)
Computer games training group n = 71 (ITT analysis)
Completed the study n = 66 (AO analysis)
Completed the study n = 55 (AO analysis)
Fig. 1. Study participants.
Training Effects The training effect refers to the difference between baseline scores and posttraining scores (within-group differences), and the interaction training * group effect refers to the difference between the training effects in the two groups (between-group differences; tables 2, 3). Using the AO approach to investigate within-group differences, we found that personalized cognitive training significantly (p ! 0.05) improved both the overall cognitive score and each of the 8 cognitive domains. In the computer games group, the training effect was significant for the overall cognitive score but for only 4 of the 8 cognitive domains (focused attention, sustained attention, memory recognition and mental flexibility; table 3). Regarding the between-group differences (interaction) we found a borderline significance (p = 0.0817) in the overall cognitive score. There was a highly significant (p ! 0.0019) improvement in the cognitive training group as compared to the computer games group in 3 domains: visual-spatial working memory, visual-spatial learning and focused attention. The interaction effect was not significant in the 5 remaining domains, although the trend was in the same direction (table 3). Similar findings were obtained using the ITT approach (table 3). Further analyses revealed that the lower the baseline cognitive performance score, the greater the effect of cognitive training as compared with computer games training (fig. 2, overall score) for focused attention (p = 0.0039), Neuroepidemiology 2011;36:91–99
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Table 1. Baseline characteristics of the study population
ITT analysis (n = 155)
Age, years Women, % GDS score Education, years MMSE score
AO analysis (n = 121)
personalized cognitive training group (n = 84)
computer games group (n = 71)
personalized cognitive training group (n = 66)
computer games group (n = 55)
68.488.3 67 2.8282.61 14.682.8 29.081.2
67.187.2 56 2.8082.76 15.183.6 28.981.3
68.687.7 72* 2.5282.48 14.582.8 29.181.2
66.987.3 54* 2.7682.72 15.083.5 28.981.2
Values shown are means 8 SD. GDS = Geriatric Depression Scale; MMSE = Mini Mental State Examination. * p < 0.05: significant difference between the personalized cognitive training group and computer games group.
Table 2. Differences in cognitive scores between the cognitive training group and the computer games group
Cognitive domains
Difference in baseline scores personalized cognitive training compared to games
p
Score change in personalized cognitive training group, posttraining compared to baseline
Score change in the conventional games group, posttraining compared to baseline
ITT population (n = 155) Focused attention Sustained attention Memory recognition Memory recall Visuospatial learning Visuospatial working memory Executive functions Mental flexibility Overall score
1.2181.53 0.4081.44 –0.4981.14 –1.7581.45 –5.6882.25 –6.4482.71 –2.1982.02 –2.1481.98 –2.1481.41
0.43 0.78 0.67 0.23 0.01 0.02 0.28 0.28 0.13
4.3180.92 2.8881.14 3.1780.86 4.1481.01 6.5281.49 6.8981.85 5.1481.39 4.7381.37 4.6580.89
3.3781.02 4.0981.26 3.0480.95 2.6481.13 1.9281.65 1.5982.06 3.1881.54 3.2881.53 2.8680.99
AO population (n = 121) Focused attention Sustained attention Memory recognition Memory recall Visuospatial learning Visuospatial working memory Executive functions Mental flexibility Overall score
0.4281.55 0.4581.66 –0.7981.27 –1.7581.56 –4.0982.27 –4.7982.73 –1.3182.36 –1.2082.31 –1.6381.51
0.79 0.79 0.53 0.27 0.07 0.08 0.58 0.61 0.28
4.7680.97 2.7381.25 3.0680.92 3.6581.05 5.4681.46 5.4481.81 5.0381.53 4.5981.52 4.3480.93
2.9881.07 3.6281.37 2.4781.01 2.0981.15 1.5081.60 0.9381.98 3.2581.68 3.3481.67 2.5281.02
Values shown are means 8 SD.
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Table 3. Scores at baseline and at posttraining assessment on the cognitive test battery
Cognitive domains
Personalized cognitive training group (n = 66) baseline
after training
p1
ITT population (n = 155) Focused attention Sustained attention Memory recognition Memory recall Visuospatial learning Visuospatial working memory Executive functions Mental flexibility Overall score
92.2688.55 90.91810.45 91.7588.05 89.68810.72 81.73818.83 80.35823.28 87.49815.77 87.54815.66 87.72810.62
96.7985.11 93.9586.05 95.1484.79 94.0686.79 89.4389.92 88.60812.13 92.9688.43 92.6188.46 92.9786.04
AO population (n = 121) Focused attention Sustained attention Memory recognition Memory recall Visuospatial learning Visuospatial working memory Executive functions Mental flexibility Overall score
92.5588.79 91.54811.03 92.1588.15 90.37810.38 83.73816.10 82.88820.49 88.03816.55 88.14816.51 88.6689.85
97.3184.39 94.1685.64 95.2184.67 94.0286.97 89.24810.19 88.32812.57 93.0688.52 92.7288.51 93.0186.00
Conventional games group (n = 55)
p2
baseline
after training
p1
