A Large-Scale, Cross-Sectional Investigation Into the Efficacy of Brain Training

Abstract

Brain training is a large and expanding industry, and yet there is a recurrent and ongoing debate concerning its scientific basis or evidence for efficacy. Much of evidence for the efficacy of brain training within this debate is from small-scale studies that do not assess the type of "brain training," the specificity of transfer effects, or the length of training required to achieve a generalized effect. To explore these factors, we analyze cross-sectional data from two large Internet-cohort studies (total N = 60,222) to determine whether cognition differs at the population level for individuals who report that they brain train on different devices, and across different timeframes, with programs in common use circa 2010-2013. Examining scores for an assessment of working-memory, reasoning and verbal abilities shows no cognitive advantages for individuals who brain train. This contrasts unfavorably with significant advantages for individuals who regularly undertake other cognitive pursuits such as computer, board and card games. However, finer grained analyses reveal a more complex relationship between brain training and cognitive performance. Specifically, individuals who have just begun to brain train start from a low cognitive baseline compared to individuals who have never engaged in brain training, whereas those who have trained for a year or more have higher working-memory and verbal scores compared to those who have just started, thus suggesting an efficacy for brain training over an extended period of time. The advantages in global function, working memory, and verbal memory after several months of training are plausible and of clinically relevant scale. However, this relationship is not evident for reasoning performance or self-report measures of everyday function (e.g., employment status and problems with attention). These results accord with the view that although brain training programs can produce benefits, these might extend to tasks that are operationally similar to the training regime. Furthermore, the duration of training regime required for effective enhancement of cognitive performance is longer than that applied in most previous studies.

Keywords: brain training; commercial brain training; cross sectional study; efficacy of brain training; memory.

FIGURE 1

Principle components analysis. Similar varimax rotated 3-component models were evident in Study 1 and 2. One component (WM) explained substantial variance in tasks that require information to be maintained actively in working memory. Another component (Reasoning) explained variance in tasks that required either information to be transformed according to rules (e.g., Rotations and Spatial Planning) or rules to be identified (e.g., Deductive Reasoning). The final component (Verbal) explained variance in tasks that have language or number stimuli.

FIGURE 2

Relationship of brain training and computer gaming with cognitive score in Study 1. Left – In Study 1 there was little difference in cognitive scores for individuals who report regular brain training vs. the rest of cohort. Right – Participants who played Video Games showed small-medium scaled advantages in cognitive scores. These scaled with frequency of gaming and were evident for the Global, WM and Reasoning scores, but not for Verbal score.

FIGURE 3

Relationship between religiosity and belief in brain training in Study 2. The majority of participants were of the opinion that brain training “works.” However, those who held strong religious beliefs also were more likely to believe in brain training.

FIGURE 4

Relationship of brain training and other cognitive pursuits with cognitive scores in Study 2. Left – Cognitive scores for participants who brain train at different frequencies in cohort 2. All measures are relative to those who do not brain train. Participants who engaged in daily brain training showed a small but significant disadvantage in their Global and Verbal scores. Right – Scores broken down according to other cognitive pursuits. All values relative to participants who do not participate in the relevant cognitive pursuit. Small-medium scaled advantages in cognitive scores were evident. These often scaled with frequency. The relationships also varied according to the type of cognitive pursuit. E.g., participants who played card games regularly showed advantages for WM score only whereas those who played Video Games showed advantages for WM and Reasoning but not Verbal scores. Puzzles were associated with higher scores for all three cognitive variables.

FIGURE 5

Cognitive scores in Study 2 for people who report brain training at different frequencies and over different durations. Participants who had just started brain training showed significantly scaled disadvantages in Global and Verbal score relative to participants who reported no brain training. These lower scores were most pronounced for participants who reported brain training on a daily basis. There was an increase in cognitive scores with duration of training such that those who trained weekly for a year or more had Global scores 0.32 SDs higher than the non-training population. Smaller scaled trends in the same direction were evident for the WM and Reasoning variables.

FIGURE 6

Relationship between time spent brain training and employment in Study 2. Approximately 70% of the study cohort reported being in full time employment. There was no significantly scaled relationship between employment status and the reported duration of brain training.