Cognitive function improvement courses -
All participants who completed the study were compensated with a 6-month membership to Lumosity. Based on the ongoing study completion rate, recruitment ended when it was estimated that the number of participants enrolled in the study would be sufficient to obtain 5, fully evaluable participants.
In total, 11, individuals consented to take part in the study and completed a baseline pre-test assessment battery. The first participant was randomized on April 27, , and the final participant completed the post-test on April 28, Participants were assigned a treatment condition using a random number generator with equal probabilities of assignment to cognitive training and crosswords control conditions.
Random assignment occurred after the pre-test. An additional participants were excluded because a computer error delayed their randomization into a treatment condition by more than 24 hours, allowing these participants to continue with the Lumosity program in the free user state.
Of the remaining 9, participants randomized into a treatment condition, 5, The training platform was designed to direct each participant, upon logging in each day, to either cognitive training or crossword puzzles based on his or her group assignment. However, in some cases participants in the crossword control group were able to access cognitive training.
As a result, control participants were removed from the primary analysis because they accessed the cognitive training program during the study period Fig 1. See Table 1 for demographic characteristics of the fully evaluable cohorts in both conditions. Age, gender, and educational attainment were evenly distributed across the groups.
All participants were instructed to log into the website and do one session per day of their activity cognitive training for the treatment group or crossword puzzles for the control group , 5 days a week for 10 weeks. Daily email participation reminders were sent to all participants during the study period.
The Lumosity cognitive training program was used as the treatment condition in this study. Treatment participants in this study received the same training experience that Lumosity subscribers received over the same period of time.
Daily training sessions included five cognitive training tasks. On any given day, the five tasks for that particular session were chosen by an algorithm that attempted to optimize a balance of training activities such that tasks were presented in clusters across days without repeating individual tasks on a given day.
One five-task session typically took approximately 15 minutes to complete. Outside of this session, participants could opt to do additional training with any of the 49 available tasks in an a la carte fashion.
The cognitive training tasks each target a particular core cognitive ability and are grouped into five categories by target domain: speed of processing, attention, memory, flexibility, and problem solving. Many of these tasks are described in detail elsewhere in the literature [ 25 — 27 , 29 , 30 , 35 — 37 ], and a description of all tasks is included as Supporting Information S1 Appendix.
Participants randomized into the active control group received a daily session timed at a minimum of 15 minutes. They were instructed to complete as many crossword puzzles as possible in the allotted time. If a participant completed a puzzle within the minute time period, the crossword application would provide a new puzzle.
At the end of the minute period, participants were able to continue to work on the current puzzle for as long as they chose but were not given additional puzzles that day. The crossword puzzles were produced by professional crossword constructors and presented in a web-based crosswords platform.
Constructors were asked to create crosswords that were of medium difficulty, approximately equivalent to a Thursday New York Times crossword puzzle note: the New York Times puzzles increase in difficulty throughout the week, culminating with the most difficult puzzle on Saturday.
Participants filled out the puzzles by typing the answers in the appropriate boxes. Feedback about correct and incorrect responses was given immediately following submission of a completed crossword.
The puzzles were placed in a website frame that replicated the look and feel of the cognitive training website in order match as closely as possible the experience across the two conditions.
See the Supporting Information S1 File for additional details on how engagement time was estimated. Secondary analyses based on total time are included in S1 File. Outcomes were assessed using a battery of seven neuropsychological tests, as well as a participant-reported outcomes survey.
The primary outcome measure used in this study was change in aggregate cognitive performance, as measured by the Grand Index described further below of the neuropsychological assessment battery, from before to after the week study period.
Secondary outcome measures included change in performance on each of the subtests in the neuropsychological battery and changes in responses to the survey. The assessments and survey were administered online in a pre-test one day prior to beginning the treatment or control condition.
Participants were directed to take the post-test 70 days later, one day following the end of the treatment or control. Seven neuropsychological assessments were used in this study. These assessments required participants to recall a sequence of randomized spatial locations in either forward or reverse order.
This task was designed to measure divided visual attention and required participants to recall the locations of briefly presented target letters while ignoring distractors.
See the Supporting Information S2 Appendix for more detailed information about the design of these assessments. Importantly, none of the tasks used in the outcome assessment battery were presented during training.
Rather, outcome assessments were implemented as measures of transfer to underlying cognitive abilities. Our assessment scaling procedure follows standard rank-based normalization approaches used in well-established IQ tests [ 42 , 43 ]. Normalization tables were created based on the pre-test data from participants who completed both the pre- and post-tests, including control participants who completed some amount of cognitive training during the study period.
Norms were generated in 5-year age bins and tables were created within each age bin for each assessment. These normalization tables were created by taking the empirically observed percentile rank for each raw score and finding the value corresponding to that percentile from a normal distribution with a mean of and standard deviation of 15 i.
This sum was then transformed using the same percentile rank normalization procedure described above. Participants also completed a survey including nine questions related to specific cognitive failures [ 44 ] and successes as well as emotional status.
Participants took the survey immediately after completing the neuropsychological test battery, once before beginning the study period pre-test and once upon completion of the study post-test.
Because this question did not apply equally to the treatment and control groups, and was not included in the original protocol, it was removed from the analysis. For completeness, responses to this question are included along with the rest of the study data in the attached S1 Dataset.
The survey items are presented in the Results section. Our primary hypothesis was that the treatment program would lead to greater improvements in aggregate cognitive performance compared to the active control, as measured by the neuropsychological assessment battery.
If this hypothesis were correct, we would expect to see larger improvements from pre-test to post-test on the Grand Index of the assessment battery for the treatment group relative to the control group. Such differences in change scores were observed. The mean increase on the Grand Index score post-pre in the treatment group was 5.
Error bars represent confidence intervals bootstrapped over , iterations. Mean change scores and error bars are based on unadjusted summary statistics.
P value is based on results from the ANCOVA analysis described in Table 2. The difference in composite Grand Index change scores between the two groups treatment vs. control was evaluated with an ANCOVA model measuring the effect of group, controlling for the pre-test score.
Pre-test score was included as a covariate to control for regression to the mean effects as well as any effects of baseline performance. These results indicate that the cognitive training treatment condition was more effective than the crosswords control for improving cognitive performance on the assessment battery on an aggregate basis.
To ensure that the exclusion of control participants who did some cognitive training with the treatment program see Participants section in Methods could not explain these results, we performed an additional set of ANCOVA analyses S1 File.
The pattern of results and conclusions remained consistent across all comparisons see S1 File , indicating that these exclusions could not explain the main result that cognitive training led to larger gains in cognitive performance compared to crosswords.
In the primary analysis conducted here, no outliers were removed. All completed assessments were included in the analysis. In order to ensure that outliers did not play an important role in the findings, we completed a secondary outlier analysis see S1 File. In this analysis, any raw scores that were outside the range of three standard deviations above or below the mean were removed prior to further statistical analysis.
The conclusions remained the same across all subtests included in the battery. The Grand Index change score analysis was recalculated for participants with no outliers.
Based on this analysis, outlier effects could not account for the results of this study. Based on the significant main effect on our primary outcome measure, we performed secondary analyses consisting of additional ANCOVA models for each assessment.
The models revealed that the cognitive training treatment group improved significantly more than the crossword puzzles control group on five of the seven assessments. There was no statistically significant difference between the groups for the Two-Target Search task. Fig 3 provides an illustration of the unadjusted change scores for each assessment for both groups.
ANCOVA model p values and effect sizes along with unadjusted pre-test means and change scores for each assessment are shown in Table 2. P values are based on results from the ANCOVA analyses listed in Table 2. If the cognitive training treatment was more effective than playing crossword puzzles for improving cognitive abilities, we may observe a larger effect of active days of study engagement for the treatment condition compared to the control condition.
In order to test for a group difference in the effect of active days, we constructed a general linear model predicting Grand Index change score from pre-test score, treatment group, active days, and the group-by-active-days interaction.
Lines represent estimates from the general linear model including effects of group, active day, and the group-by-active-days interaction. The estimated total time participants engaged with their respective conditions provides an additional measure of compliance. These results indicate that participants in both conditions on average complied with the instructions to engage for at least 15 minutes per day, 5 days per week for 10 weeks See S1 File for matched sample analyses demonstrating that the observed group differences in overall cognitive performance improvement are not explained by differences in the distributions of total engagement time.
Of the 4, participants included in the analyses above, 4, In order to calculate change scores on the survey, participant responses were first numerically coded on a scale from 0 to 4, with the scale always ranging from 0 as the most negative response to 4 as the most positive response.
Responses to questions 1, 2, 3, 7, 8, and 9 were reverse coded to maintain consistency of response coding across all questions i. An average of the scores was taken for both pre- and post-tests as an overall measure of self-reported real-world cognitive performance and emotional status.
The differences between pre- and post-test overall scores and scores on each question were analyzed. The hypothesis that participants in the treatment group would show greater self-reported improvements in cognition and emotional status relative to control participants was tested via an ANCOVA model measuring the effect of group treatment vs.
control on the change in average survey score, controlling for average pre-test score. These results indicate that, overall, the cognitive training treatment was more effective than the crosswords control for improving self-reported real-world cognition and emotional status. For all nine questions, both groups tended to report improvements following study participation, compared to the pre-test.
The changes were significant for both groups on all questions except for question 4 memory for a new name. Results for each question are presented in Table 3. The three largest group differences were on questions 1, 3 and 6, all of which were related to concentration. The findings of this study are consistent with the extant literature on cognitive training that shows that progressively challenging, targeted cognitive training can be an effective tool for improving core cognitive abilities including speed of processing [ 13 ], working memory [ 46 ], and fluid reasoning [ 10 ].
The results presented here extend previous findings by demonstrating that a cognitive training program targeting a variety of cognitive capacities with different exercises can be more effective than crossword puzzles at improving a broad range of cognitive abilities.
In addition, improvement on the overall measure of cognitive function used as the primary outcome measure in this study—the Grand Index for the assessment battery—was more than twice as large in the cognitive training group as it was in the crossword puzzles control group.
Thus, for improving a variety of core cognitive abilities, the treatment used in this trial was more effective than crossword puzzles. Another approach to appreciating the magnitude of these results is to contextualize them in the distribution of scores on the outcome measures.
We observe that participants in the training group improve by 2. Given that the scores are scaled on a mean ± 15 sd scale, we can evaluate how far an average participant would move within the population distribution for their age based on moving a given number of points.
In this case, 2. This is a potentially meaningful move within the distribution. A significant group-by-active-days interaction was observed in this study, such that an additional active day engaging with the cognitive training intervention was related to larger gains on the cognitive battery composite score compared to an additional active day engaging with crossword puzzles Fig 4.
This suggests that additional training could lead to larger gains. While it is unlikely that the linear relation holds indefinitely i. In addition to the enhanced performance observed in the cognitive training group on the neuropsychological measures of cognitive function, participants in this group also self-reported experiencing benefits that were significantly greater than those reported by participants in the active control.
These participant-reported improvements were particularly strong on questions related to the ability to concentrate. These results suggest that participants in the treatment group experienced benefits from the training in their everyday lives. Crossword puzzles were chosen as the active control because they are commonly believed to be a cognitively stimulating activity that is good for brain health [ 31 , 32 ].
This is important because it has been suggested that belief in the efficacy of a training intervention could affect effort and performance on testing outcomes [ 47 ].
While not as large as the gains seen in the treatment group, participants in the crosswords control group also showed improvements in cognitive performance.
Without a no-contact control group in this study, it is not possible to conclusively determine whether these improvements in the active control condition were due to practice effects, placebo effects, real treatment effects, or some combination of these.
Further study will be needed to better understand the benefits of crossword puzzles for maintenance and enhancement of cognition. It is worth noting that participants in the crosswords group improved slightly more than the cognitive training group on a measure of grammatical reasoning.
There are several reasons why the treatment program might have outperformed crossword puzzles in enhancing cognitive function. First, the cognitive training program is specifically targeted to core cognitive functions. This distinguishes the treatment from crossword puzzles, which are not designed with the goal of cognitive enhancement.
Another central feature of the cognitive training program studied here is that it is progressively challenging —that is, many of the tasks explicitly increase in difficulty as the individual improves, while others encourage the individual to perform at threshold by rewarding increasingly faster and more accurate performance see S1 Appendix.
This follows a long-established tenet in the psychological literature, that learning conditions are optimized when the task is challenging, but not prohibitively difficult [ 48 , 49 ]. Task variety and novelty are also potentially important.
In the case of crossword puzzles, participants are primarily involved in vocabulary retrieval, challenging a more limited set of neural pathways. In the cognitive training program studied here, participants are challenged to engage with a variety of cognitive tasks that challenge different neural processing systems and do so in different ways.
This variety limits the opportunity to solve the tasks with a single task-specific strategy, thus encouraging the learning of new strategies and the development of new neural connections. We noted that there have been several studies that have reported not finding benefits from cognitive training.
The only other similarly powered study that did not find positive results is a study that recruited 11, participants through a BBC television show and collected data online [ 17 ]. The authors concluded that brain training had no measureable benefits.
Several key aspects of that study differ from the one presented here. First, neither of the two treatment conditions they used had been studied empirically prior to that experiment.
As we demonstrate in this study, not all cognitively stimulating activities are equally effective for enhancing cognition, and it is possible that other programs not examined in their study are more effective.
Also, the average amount of training exposure in the BBC study was less than half of that in this study. This is an important distinction as results of this study indicate that amount of training is related to the magnitude of gains in cognitive performance Fig 4.
Our results represent statistically significant improvements in cognitive processes through training. This study included a sufficiently large number of participants and enough training to reliably detect these effects.
As has been noted previously [ 50 ], most cognitive training studies that have shown null results have not been powered in such a way that either a positive or a null outcome would be informative, and often include quite short training periods.
Murphy, D. Age-related similarities and differences in the components of semantic fluency: Analyzing the originality and organization of retrieval from long-term memory.
Eich, T. Age-based differences in task switching are moderated by executive control demands. Functional brain and age-related changes associated with congruency in task switching.
Neuropsychologia 91 , — Jimura, K. Age-related shifts in brain activity dynamics during task switching. Cortex 20 , — Matthews, K. The consequences of self-reported vision change in later-life: Evidence from the English Longitudinal Study of Ageing.
Public Health , 7—14 Malavita, M. The effect of aging and attention on visual crowding and surround suppression of perceived contrast threshold. Nyberg, L. Forecasting memory function in aging: Pattern-completion ability and hippocampal activity relate to visuospatial functioning over 25 years.
Aging 94 , — Cognitive training and selective attention in the aging brain: An electrophysiological study. Mishra, J. Neural plasticity underlying visual perceptual learning in aging. Brain Res. Rhodes, R. Working memory plasticity and aging. Aging 32 , 51—59 van der Lee, S. Lancet Neurol. Dementia prevention, intervention, and care.
Lancet , — Zheng, F. Progression of cognitive decline before and after incident stroke. Neurology 93 , e20—e28 Stefanidis, K.
The effect of non-stroke cardiovascular disease states on risk for cognitive decline and dementia: A systematic and meta-analytic review. Li, C. Risk score prediction model for dementia in patients with type 2 diabetes. Zhang, X. Chronic obstructive pulmonary disease as a risk factor for cognitive dysfunction: A meta-analysis of current studies.
Ardila, A. Spontaneous language production and aging: Sex and educational effects. Anguera, J. Video game training enhances cognitive control in older adults.
Nature , 97— Golino, M. Effects of cognitive training on cognitive performance of healthy older adults. Li, B. Computerized cognitive training for Chinese mild cognitive impairment patients: A neuropsychological and fMRI study.
Neuroimage Clin. Jin, Y. Effects of digital device ownership on cognitive decline in a middle-aged and elderly population: Longitudinal observational study. Internet Res. Automated functional upper limb evaluation of patients with Friedreich ataxia using serious games rehabilitation exercises.
van der Kolk, N. Geddes, M. Remote cognitive and behavioral assessment: Report of the Alzheimer Society of Canada Task Force on dementia care best practices for COVID Vatansever, D.
Covid and promising solutions to combat symptoms of stress, anxiety and depression. Savulich, G. Cognitive training using a novel Memory Game on an iPad in patients with amnestic mild cognitive impairment aMCI. Wolinsky, F. Does visual speed of processing training improve health-related quality of life in assisted and independent living communities?
Aging 4 , Koo, B. Mobile technology for cognitive assessment of older adults: A scoping review. Aging 3 , Wainer, H. Speed vs reaction time as a measure of cognitive performance.
Kochan, N. Is intraindividual reaction time variability an independent cognitive predictor of mortality in old age? Findings from the Sydney Memory and Ageing Study.
PLoS ONE 12 , e Amieva, H. Is low psychomotor speed a marker of brain vulnerability in late life? Digit symbol substitution test in the prediction of Alzheimer, Parkinson, stroke, disability, and depression.
Albers, C. When power analyses based on pilot data are biased: Inaccurate effect size estimators and follow-up bias. R Core Team. R: A Language and Environment for Statistical Computing Download references.
Bruno Bonnechère was funded by the Fondation Wiener-Anspach ; Dr. Barbara J Sahakian receives funding from the Wallitt Foundation and Eton College and research is conducted within the NIHR MedTech and in vitro diagnostic Co-operative MIC and the NIHR Cambridge Biomedical Research Centre BRC Mental Health and Neurodegeneration Themes.
REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University, Hasselt, Belgium. Department of Psychiatry and Behavioural and Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0SZ, UK. Laboratory of Applied Biology and Neurophysiology, ULB Neuroscience Institute UNI , Université Libre de Bruxelles ULB , Brussels, Belgium.
You can also search for this author in PubMed Google Scholar. The study was conceived by B. performed the analysis. and B. did the data interpretation and contributed to the writing. Correspondence to Bruno Bonnechère.
Bonnechère, Dr. Langley and Prof. Klass have nothing to disclose. Sahakian consults for Cambridge Cognition, Greenfield BioVentures and Cassava Sciences. She receives funds from Cambridge Enterprise for Technology Transfer of Wizard and Decoder to Brainbow and Peak.
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Reprints and permissions. Brain training using cognitive apps can improve cognitive performance and processing speed in older adults. Sci Rep 11 , Download citation. Received : 09 November Accepted : 18 May Published : 10 June Anyone you share the following link with will be able to read this content:.
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Skip to main content Thank you for visiting nature. nature scientific reports articles article. Download PDF. Subjects Dementia Geriatrics. Abstract Managing age-related decrease of cognitive function is an important public health challenge, especially in the context of the global aging of the population.
Introduction According to the World Health Organization WHO , the world population aged over 60 years will have doubled in number by , with an estimated total of 2 billion people 1. Results Time needed to perform all sessions Since no particular guidelines are given in the app regarding the frequency of the training sessions, we first analyzed the number of days needed to reach the sessions for each CMG.
CMG scores First, we analyzed the results of the first session of training to evaluate the influence of age on initial CMG scores. Table 1 Number of subjects in each age group n and mean SD or median [IQR] scores for the different CMG according to the age of the participants for the first session of training.
Full size table. Table 2 Results of the mixed models, β SE representing the change of score of the CMG per session training. Figure 1. Full size image. Table 3 Median [IQR] processing speed expressed as reaction time in ms for the different CMG according to the age of the participants for the first session of training.
Figure 2. Discussion This study aimed to determine the efficacy of a cognitive training performed using CMG in real-life use on cognitive performance in older adults. Table 5 Instructions, cognitive abilities trained, scoring system of the CMG, and how processing speed is measured in each of the CMG included in this study.
Methods Study design and participants We carried out a retrospective observational study in which we obtained anonymized CMG results of healthy participants. Procedures In this study, we used a set of seven individual short CMG provided by Peak brain training www.
Figure 3. Data availability The data that support the findings of this study are available from the corresponding author upon reasonable request. References WHO. Ageing and Health WHO, Google Scholar World Health Organization.
Google Scholar Cimler, R. Article CAS PubMed PubMed Central Google Scholar Cleveland, M. Article PubMed Google Scholar Lamar, M. Article PubMed PubMed Central Google Scholar Livingston, G.
Article Google Scholar Dyer, S. Article PubMed Google Scholar Abraha, I. Article PubMed PubMed Central Google Scholar Nouchi, R. Article ADS CAS PubMed PubMed Central Google Scholar Gates, N.
Article PubMed PubMed Central Google Scholar Shah, T. Article PubMed Google Scholar Bonnechère, B. Article PubMed PubMed Central Google Scholar Gates, N. PubMed Google Scholar Edwards, J. Article Google Scholar Bonnechère, B. Article PubMed PubMed Central Google Scholar Bonnechère, B.
Article PubMed Google Scholar Bettio, L. Article PubMed Google Scholar Norris, J. Article PubMed PubMed Central Google Scholar Johari, K. Article PubMed PubMed Central Google Scholar Martin, R.
Article PubMed Google Scholar Cappelletti, M. Article PubMed Google Scholar Vogel, A. Article PubMed Google Scholar Rizeq, J. Exercising the brain to improve memory, focus, or daily functionality is a top priority for many older adults. But people of all ages can benefit from incorporating a few simple brain exercises into their daily life.
The brain is involved in everything we do, and, like any other part of the body, it needs to be cared for too.
Research has shown that there are many ways you can hone your mental sharpness and help your brain stay healthy, no matter what age you are. Doing certain brain exercises to help boost your memory , concentration, and focus can make daily tasks quicker and easier to do, and keep your brain sharp as you get older.
Research has shown that doing jigsaw puzzles recruits multiple cognitive abilities and is a protective factor for visuospatial cognitive aging. In other words, when putting together a jigsaw puzzle, you have to look at different pieces and figure out where they fit within the larger picture.
This can be a great way to challenge and exercise your brain. Researchers who conducted a study in on mentally stimulating activities for adults, say a quick card game can lead to greater brain volume in several regions of the brain.
The same study also found that a game of cards could improve memory and thinking skills. A rich vocabulary has a way of making you sound smart. But did you know you can also turn a quick vocab lesson into a stimulating brain game? Research shows that many more regions of the brain are involved in vocabulary tasks, particularly in areas that are important for visual and auditory processing.
To test this theory, try this cognitive-boosting activity:. In other words, bust a move on the dance floor and your brain will thank you. A research report suggests that using all your senses may help strengthen your brain.
To give your senses and your brain a workout, try doing activities that simultaneously engage all five of your senses. Learning a new skill is not only fun and interesting, but it may also help strengthen the connections in your brain.
Research from also shows that learning a new skill can help improve memory function in older adults. You now have one more good reason to learn that new skill. After you learn a new skill, you need to practice it. Teaching it to someone else requires you to explain the concept and correct any mistakes you make.
For example, learn to swing a golf club, then teach the steps to a friend. Do you want an easy way to increase your creative brain power?
The answer may lie in turning on some music. According to a study , listening to happy tunes helps generate more innovative solutions compared to being in silence.
Which means, cranking up some feel-good music can help boost your creative thinking and brain power. And if you want to learn how to play music , now is a great time to start because your brain is capable of learning new skills at any point in your life.
Instead, be willing to try new ways to do the same things. Choose a different route to get to work each week or try a different mode of transport, like biking or using public transport instead of driving. Your brain can benefit from this simple change, and you might be surprised by how easy it is to change your thinking.
Daily meditation can calm your body, slow your breathing, and reduce stress and anxiety. A review of research has overwhelmingly proven the many cognitive benefits of being able to speak more than one language. According to numerous studies, bilingualism can contribute to better memory, improved visual-spatial skills, and higher levels of creativity.
Being fluent in more than one language may also help you switch more easily between different tasks, and delay the onset of age-related mental decline. According to researchers, you can boost your memory and improve other mental functions by becoming a student of a new language at any time in your life.
Cognitive function improvement courses exercises may help boost Leafy greens for pesto maintain Cognitive function improvement courses function. Memory cohrses, learning new skills, crosswords, and even cojrses games may help. Although the brain gets plenty of exercise every day, certain activities may help boost brain function and connectivity. This in turn may help protect the brain from age-related degeneration. The brain is always active, even during sleep. Cognitive function improvement courses March 12, Reviewed by Gary Drevitch. The Healthy metabolism habits York Times recently published an article about improcement "brain fitness" functiob, "Do Brain Workouts Work? Without Cognitive function improvement courses variety imprvoement other daily habits, these "brain-training" games cannot stave off mental decline or dramatically improve cognitive function. Most of these brain-training games will have some benefits, but it's impossible to optimize brain connectivity and maximize neurogenesis growth of new neurons sitting in a chair while playing a video game on a two-dimensional screen. In order to give your brain a full workout, you need to engage both hemispheres of the cerebrum, and of the cerebellum.
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