The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index; 6 of the 29 sources its claims cite were checked for support.
Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null
Open accessAbstract
A recent meta-analysis by Au et al. Psychonomic Bulletin & Review, 22, 366-377, (2015) reviewed the n-back training paradigm for working memory (WM) and evaluated whether (when aggregating across existing studies) there was evidence that gains obtained for training tasks transferred to gains in fluid intelligence (Gf). Their results revealed an overall effect size of g = 0.24 for the effect of n-back training on Gf. We reexamine the data through a Bayesian lens, to evaluate the relative strength of the evidence for the alternative versus null hypotheses, contingent on the type of control condition used. We find that studies using a noncontact (passive) control group strongly favor the alternative hypothesis that training leads to transfer but that studies using active-control groups show modest evidence in favor of the null. We discuss these findings in the context of placebo effects.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
Dougherty et al. reanalyze Au et al.’s (2015) n-back training meta-analysis using Bayesian methods and find that evidence for transfer to fluid intelligence depends heavily on control-group type. Passive-control studies strongly favor transfer, but active-control studies provide modest-to-strong evidence for the null, suggesting the apparent training effect may be a placebo or design artifact.
Key findings
- Across all 24 comparisons from 20 papers, the meta-analytic Bayes factor ignoring control type was 152:1 in favor of the alternative hypothesis, but this masked a large difference by control condition.
- Passive-control studies yielded a Bayes factor of 13,241:1 in favor of transfer, whereas active-control studies yielded a Bayes factor of 7.7:1 in favor of the null; with a two-sided test, these were 6,000:1 for the alternative and 11:1 for the null, respectively.
- Hierarchical Bayesian models showed passive-control studies consistently had positive effect sizes, while active-control studies had effects near zero; the only aggregate effect whose 95% HDI excluded zero was for non-USA passive-control studies, and active-control effects within the USA shrank to essentially zero.
- Among individual studies, 11 of 12 passive-control effect sizes were positive, but only 6 of 12 active-control effect sizes were positive; the majority of individual studies favored the null, including 6 of 12 passive-control studies.
Methods
- Bayesian reanalysis of effect sizes from Fig. 3 of Au et al. (2015), using 24 comparisons from 20 papers with healthy adults aged 18–50 and n-back as the only training task; 12 comparisons used passive controls and 12 used active controls.
- Effect sizes were transformed to t values using \(t = \sqrt{1/n_1 + 1/n_2} \times g\), then default Bayes factors were computed with the BayesFactor package in R (`ttestBF`, `meta.ttestBF`), using a one-sided interval and scale factor \(r = 1\), with sensitivity checks using two-sided tests and different priors.
- Follow-up hierarchical Bayesian models estimated effect sizes as a function of control type (passive vs. active) and, in additive models, country of origin (USA vs. non-USA), using four prior distributions on population effect size (vague, small, medium, large).
Limitations
- The paper states that conclusions do not necessarily generalize to other types of training or age groups, because Au et al. limited inclusion to n-back training and healthy adults aged 18–50.
- The paper states that, without experiments specifically designed to test the placebo explanation, it cannot definitively conclude that the active–passive discrepancy reflects a placebo effect; it also notes causal indeterminacy in comparing placebo controls with no-contact controls across studies.
- The paper notes that control type covaried with country of origin—most active-control studies were conducted within the USA, while most non-USA studies used passive controls—leaving open the possibility that cultural differences contribute, though the authors doubt this accounts for the 7-fold difference. Evident from the text: active-control studies were heterogeneous in the nature of their control tasks, and the reanalysis depends on the effect sizes and control-type categorization provided by Au et al.
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Claims the paper makes
25 Own interpretation · 11 Sources not found · 9 Own result · 4 No full text of the sources · 4 Own method · 2 Supported so far · 2 Not checked yet · 2 No basis given · 1 Supported · 1 Partly supported · 1 Not supported · accuracy not yet measured
At least one cited source doesn’t support this claim or points to a different paper, and none confirmed it — see the verdicts below.
In the paper
“Due to causal indeterminacy, one cannot simply compare different types of control conditions to infer the presence or absence of placebo effects.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
What the sources say
- Disputedcites Hróbjartsson, Kaptchuk, and Miller (2011) sourceExperimental — accuracy not yet measured
The Introduction says that assessing a placebo effect requires comparison with a suitable control group, and the Conclusion calls placebo-versus-no-treatment comparison the best available design for estimating placebo effects. The section on extrapolation uses ‘causal indeterminateness’ to describe difficulty isolating the factors responsible for an observed effect, not to rule out control-group comparisons. The paper cautions that such comparisons are crude and susceptible to bias, but does not deem them invalid for detecting placebo effects. (LLM, conf=0.83)
Checked by a reasoning model — may be wrong.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Studies that use active controls may also use other procedures that reduce expectancy or placebo effects.
- Disputed
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Chein and Morrison (2010) reported a significant effect of complex span training on executive control with a t(38) = 1.81, which was reported as significant (p = .039,one-sided).”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
What the sources say
- Partly supportedcites Chein and Morrison (2010) sourceExperimental — accuracy not yet measured
Table 1 (page unavailable in our copy) reports a significant between-group effect on cognitive control, measured with the Stroop test: t(40) = 1.81, p = .039. The Results state that the t tests were one-tailed. The claim gives the wrong degrees of freedom, t(38); that value appears in Table 1 for reading comprehension, not cognitive control. (LLM, conf=0.94)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Partly supported
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“assuming a one-sided prior on the effect size, the corresponding BF is only 1.78 (BF = 0.98 for the two-sided test) in favor of the alternative.This is basically uninformative with respect to both the alternative and the null hypothesis.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Furthermore, the estimated effect size for the active-control studies within the USA shrink to essentially zero.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Favors Null
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Strikingly, even when the prior distribution is set such that the effect of training is assumed to be large, there is still no evidence of that n-back training leads to improvements on Gf measures.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Meta Analysis Bayes Factor
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Second, when these effect sizes are evaluated in terms of the Bayes factor, the majority of the individual studies favor the null hypothesis, including 6 of the 12 passive-control studies.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Preliminaries
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Importantly, the three international studies using active controls fail to yield a reliable positive effect.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Meta Analysis Bayes Factor
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“model reveals that the only estimated effect sizes that are different from zero are those based on non-USA passive-control studies.”
- Also stated in: § Meta Analysis Bayes Factor · plain
“Furthermore, at the aggregate level the only effect size in which the HDI does not include zero are effects based on studies conducted outside the USA that use passive control designs.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Favors Null
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Meta Analysis Bayes Factor · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“in the absence of experiments specifically designed to test the placebo effect explanation, it is impossible to definitively state that the difference between active and passive control studies reflects a placebo effect.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- The authors state this as an assumption: Studies that use active controls may also use other procedures that reduce expectancy or placebo effects.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Choice of experimental design should not moderate the effectiveness of a manipulation, unless of course the design creates the effect through confounding variables.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Passive Active
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
- Probably not a substantial claim. 15
- It may state two separate claims as one. 23
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“Our analysis approach closely followed the methods used by Rouder and Morey (2011) and Rouder et al. (2013) in their meta-analyses of psi (i.e., extrasensory perception).”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Preliminaries
What the sources say
- Supportedcites Rouder and Morey (2011) source
The Abstract describes Rouder and Morey’s analysis as a meta-analytic Bayes factor applied across Bem’s ESP experiments. The section “The meta-analysis problem” sets out the method, so this paper is an appropriate citation for a method used in a psi meta-analysis. This verdict does not assess the separate Rouder et al. (2013) citation. (LLM, conf=0.92)
- Not checked — no full text of the sourcecites Rouder et al. (2013) source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“In true placebo-control trials, the causal mechanism of the treatment is presumably isolated by virtue of including the placebo control condition.However, the same is not true when comparing a placebo-control with a no-contact control.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
What the sources say
- Supportedcites Hróbjartsson et al., 2011 source
In “The problem of the extrapolation of study results” (page not provided), the paper says a normal placebo-controlled trial isolates the hypothesized causal factor distinguishing treatment from placebo. It contrasts this with a placebo-versus-no-treatment comparison, in which the causal factors responsible for improvement are not isolated. (LLM, conf=0.94)
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“The limitations of NHST methods are well documented and need not be rehashed here in their entirety”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
What the sources say
- Not checked — no full text of the sourcecites Raftery (1995) source
- Supportedcites Wagenmakers (2007) source
The Abstract says the article reviews three problems with p-value NHST and cites an ongoing debate about its pros and cons in the psychological literature. The Interim Conclusion also summarizes statistical and practical difficulties with NHST. Together, these passages support the claim that its limitations are well documented. (LLM, conf=0.94)
- Supportedcites Rouder and Morey (2011) source
In “The evidence from p-values and Bayes factor” (page not provided), the paper calls the inability of significance tests to accept the null a “well-known asymmetry.” It also describes Lindley’s paradox as a primary critique of inference by p-values in the statistical literature. These passages support the broad claim that NHST’s limitations are well documented. (LLM, conf=0.91)
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“While this model estimates that the median effect size amongst the active control studies is slightly above zero, this small positive effect is essentially eliminated when country of origin is added as a predictor in the model, as shown in Figs. 5 and 6.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Meta Analysis Bayes Factor
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“First, ignoring the type of control, the odds in favor of the alternative hypothesis is 152:1.This qualifies as Bdecisive^evidence according to Jeffreys' (1961) scheme.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Preliminaries
What the sources say
- Not matchedcites Jeffreys, 1961
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: NHST tends to overstate evidence for the alternative hypothesis and does not allow evaluating the relative probability that the null hypothesis is true.
- Not matched
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“First, 11 of the 12 effect sizes for the passive control studies are positive, whereas only 6 of the 12 effect sizes are positive for the activecontrol studies.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Preliminaries
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Note that when a two-sided test is used lieu of the one-sided test, we obtain a Bayes factor of 6,000:1 (in favor of the alternative) for the passive control studies and a Bayes factor of 11:1 (in favor of the null) for the active control studies.The later constitutes strong evidence for the null amongst studies using proper experimental controls.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Preliminaries
What the sources say
- Not matchedcites Jeffreys, 1961
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: NHST tends to overstate evidence for the alternative hypothesis and does not allow evaluating the relative probability that the null hypothesis is true.
- Not matched
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“choice of experimental design also covaried with whether the study was conducted within the USA or outside the USA.Most of the studies using active controls were conducted within the USA, whereas the majority of the studies conducted outside of the USA used passive controls.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Passive Active
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“We find that studies using a noncontact (passive) control group strongly favor the alternative hypothesis that training leads to transfer but that studies using active-control groups show modest evidence in favor of the null.”
- Also stated in: § Preliminaries · plain
“While the Bayes factor for the passive control studies is a whopping 13,241:1 in favor of the alternative, the Bayes factor for the active control studies is a more modest 7.7:1 in favor of the null.As stated above, this qualifies as substantial evidence for the null.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Abstract
What the sources say
- Not matchedcites Jeffreys, 1961
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- The authors state this as an assumption: A one-sided interval placing prior mass on effects greater than zero is reasonable under the hypothesis that training improves Gf.
- Rests on an assumption: NHST tends to overstate evidence for the alternative hypothesis and does not allow evaluating the relative probability that the null hypothesis is true.
- Also stated in: § Preliminaries · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the effect size for the training condition amongst active-control studies (d = 0.25) is actually numerically smaller than the effect size amongst the control participants in the passive control studies (d = 0.28).”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“They also evaluated several possible mediators, including whether the studies used an active control (N = 12) or a passive control (N = 12), which yielded effect sizes of 0.06 and 0.44, respectively.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Preliminaries
What the sources say
- Not matchedcites Au et al., 2015
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plainn = 12- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
- Not matched
In the paper
“Two important details of the selection criteria are that Au et al. limited their analyses to studies that used a form of the n-back task as the only training task and to studies that included healthy adults aged 18-50.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Preliminaries
What the sources say
- Not matchedcites Au et al., 2015
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
In the paper
“Their results revealed an overall effect size of g = 0.24 for the effect of n-back training on Gf.”
- Also stated in: § Preliminaries · plain
“The aggregate weighted effect size across these 24 comparisons was 0.24.”
- Also stated in: § Preliminaries · plain
“Au et al. (2015) presented effect sizes for 24 individual comparisons drawn from 20 papers.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Abstract
What the sources say
- Not matchedcites Au et al., 2015
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plainn = 24- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Also stated in: § Preliminaries · plain
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“the main point of disagreement in the literature pertains to whether training leads to improvements on nontrained tasks (far transfer), where the null hypothesis is a theoretically meaningful and plausible hypothesis.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The hierarchical Bayesian analyses were repeated using three different prior distributions on the population level effect size (see Table 2) to assess the sensitivity of the posterior distribution to different prior beliefs.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Favors Null
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“there is at least one study using Bayesian analyses that showed that transfer from other forms of training to non-trained tasks uniformly favored the null (see Sprenger et al., 2013).”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Passive Active
What the sources say
- Not checked — no full text of the sourcecites Sprenger et al., 2013 source
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Importantly, even large modifications to the prior distribution do not alter our conclusions in any substantive way, nor does using a two-sided null interval.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Preliminaries
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Given the prevalence of placebo effects, the discrepancy in findings between active and passive experimental designs cannot simply be described as a moderation effect; it has to be fully considered as a possible root cause of the effect.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“such transfer effects are neither surprising nor of much practical interest, and neither of these studies found evidence for far transfer.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“rather than relying on a p value to infer the presence or absence of an effect, the Bayesian approach allows one to quantify the strength of the evidence.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Without showing effects relative to a proper control condition, or otherwise controlling for possible placebo effects, it is difficult to move forward with interpreting results from the passive control studies, let alone justify claims of effective transfer.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Abstract
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
- Rests on an assumption: NHST tends to overstate evidence for the alternative hypothesis and does not allow evaluating the relative probability that the null hypothesis is true.
None of the sources cited for this claim have been checked yet.
In the paper
“Unfortunately, deviation from the double-blind procedure is the norm within the cognitive training literature: We know of only a small number of studies that attempted to use a double blind placebo-control procedure (Sprenger et al., 2013, Study 2;von Bastian & Eschen, 2015).”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Abstract
What the sources say
- Not checked — no full text of the sourcecites Sprenger et al., 2013 source
- Not matchedcites von Bastian & Eschen, 2015
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, the conclusions we draw below do not necessarily generalize to other types of training or age groups.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Preliminaries
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“if nback training has a true effect on Gf, then these effects should hold even for studies that use active controls.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the strength of the evidence can be evaluated in relation to any theoretically justified hypothesis, including the null hypothesis.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“it is clear that the data reflect two separate data-generating processes, neither of which can be attributed to n-back training.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Passive Active
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- The authors state this as an assumption: The effects observed in passive-control studies reflect something other than a training effect.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“we doubt cultural differences would account for the 7-fold increase in the training effect, especially since the non-USA studies were primarily conducted in Westernized cultures (e.g., Europe).”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Passive Active
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“If n-back training does indeed produce gains in fluid abilities, as claimed by Au et al., then this should hold both for studies that include passive-control groups and for studies that use active-control groups.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Abstract
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
- Rests on an assumption: NHST tends to overstate evidence for the alternative hypothesis and does not allow evaluating the relative probability that the null hypothesis is true.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although their analysis does indeed illustrate an effect of some sort, we propose that this effect is an experimental design artifact, and is consistent with a placebo effect interpretation.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Abstract
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- The authors state this as an assumption: The effects observed in passive-control studies reflect something other than a training effect.
In the paper
“Jeffrey's (1961) labeling scheme provides one set of guidelines for interpreting the magnitude of BFs.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
What the sources say
- Not matchedcites Jeffreys (1961)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
In the paper
“the meta-analysis presented here and in Au et al. (2015) on n-back training does not provide such evidence.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
What the sources say
- Not matchedcites Au et al. (2015)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the beauty of the BF is that it can be interpreted numerically as the strength of evidence for a particular model relative to an alternative.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“One of these areas of methodological deficiencies entails the continued use of passive controls and the other the use of inappropriate analysis techniques that entails correlating training gains with transfer gains (see Tidwell et al., 2014).”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
What the sources say
- Not checked — no full text of the sourcecites Tidwell et al., 2014 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The comparison of control groups while ignoring the training groups isn't particularly informative regarding effect of training, since the effects of training can only be assessed relative to the control.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This is particularly challenging for cognitive training studies because participants literally see and engage in the intervention, making it difficult to mask what condition participants believe they have been assigned to.”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The authors state this as an assumption.
The effects observed in passive-control studies reflect something other than a training effect.
“Because the passivecontrol studies show a substantial positive effect while the active control studies do not, it seems reasonable to assume that the effects observed in the passive-control studies reflects something other than a training effect.”
The authors state this as an assumption.
A one-sided interval placing prior mass on effects greater than zero is reasonable under the hypothesis that training improves Gf.
“The one-sided test is a reasonable assumption under the hypothesis that training should lead to improvements in Gf.”
The paper relies on this without support.
NHST tends to overstate evidence for the alternative hypothesis and does not allow evaluating the relative probability that the null hypothesis is true.
“two well-known limitations of the NHST framework are that it tends to overstate evidence for the alternative hypothesis and does not permit one to evaluate the relative probability that the null hypothesis is in fact true.”
The authors state this as an assumption.
Studies that use active controls may also use other procedures that reduce expectancy or placebo effects.
“it is reasonable to assume that studies that adopt active controls might also adopt other procedures that minimize expectancy or placebo effects.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“However, subsequent meta-analyses did not find any significant far transfer effects [5, 13, 17], especially when the effects of WM training were compared with an active control group, that is, a group practicing tasks with little WM demands.”
From Adaptive working memory training does not produce transfer effects in cognition and neuroimaging (2022) · cites this paper as [17]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Critically, meta-analyses that explicitly distinguish between the types of a control group typically report a lack of far, sometimes also near, transfer effects [5, 15, 17].”
From Adaptive working memory training does not produce transfer effects in cognition and neuroimaging (2022) · cites this paper as [17]
The cited source says what the claim attributes to it.
In the citing paper
“The effectiveness of training based on the n-back task in eliciting transfer to other different tasks thus remains unclear.”
From Nearest transfer effects of working memory training: A comparison of two programs focused on working memory updating (2019) · cites this paper as [20]
In the citing paper
“Interestingly, the lack of follow-up far-transfer effects also seems to reject the hypothesis that some time is needed in order for generalized results reported in most recent meta-analyses and systematic reviews in the broader field of WM training”
From The cognitive and academic benefits of Cogmed: A meta-analysis (2019) · cites this paper as Dougherty, Hamovits, & Tidwell, 2016
In the citing paper
“Dougherty et al. (2016) conducted a meta-analysis of working-memory training studies using a Bayesian approach and found that studies that using a passive control group were more likely to favor the alternative hypothesis that training was effective, while studies employing active control groups were more likely to support the null.”
From A simultaneous examination of two forms of working memory training: Evidence for near transfer only (2016) · cites this paper as Dougherty et al. (2016)
In the citing paper
“An active control group was included in the study, as recommended by the literature (e.g., [20, 23]) to control for other experiment-related variables, such as contact with the experimenter or assessment context.”
From Nearest transfer effects of working memory training: A comparison of two programs focused on working memory updating (2019) · cites this paper as [20]
In the citing paper
“the presence and type of control groups is an essential requirement to dissociate the effectiveness of training (Mohr et al., 2009; Dougherty et al., 2016; Melby-Lervåg et al., 2016).”
From Training on Working Memory and Inhibitory Control in Young Adults (2016) · cites this paper as Dougherty et al., 2016
In the citing paper
“Thus, passive control groups (PC) may allow researchers to keep track of simple practice effects, while active control (AC) groups may enable them to uncover the specificity of different cognitive training procedures by maintaining similar levels of motivation and reducing the possibility of placebo effects (Boot et al., 2013; Dougherty et al., 2016).”
From Training on Working Memory and Inhibitory Control in Young Adults (2016) · cites this paper as Dougherty et al., 2016
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Preliminaries
“t = sqrt(1/n1 + 1/n2) * g”
§ Reevaluating the effectiveness of n-back training on transfer through the Bayesian lens: Support for the null > Aggregate
“| Jaeggi et al. 2008.17d | 2.218 | 8 | 8 | 1.109 |”
Citations
Cites
R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
Kass, R. E., & Raftery, A. E. (1995) · Journal of the American Statistical Association · doi:10.1080/01621459.1995.10476572 · Cited by 12,558
Jeffreys, H., Moran, P. A. P., & Chatfield, C. (1922) · Nature · doi:10.1093/oso/9780198503682.001.0001 · Cited by 7,878
Jeffreys, H., Moran, P. A. P., & Chatfield, C. (1922) · Nature · doi:10.1038/109132a0 · Cited by 7,877
Bayesian model selection in social research
Raftery, A. E. (1995) · Sociological Methodology · doi:10.2307/271063 · Cited by 6,823
Bayesian t tests for accepting and rejecting the null hypothesis
Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D., & Iverson, G. (2009) · Psychonomic Bulletin & Review · doi:10.3758/pbr.16.2.225 · Cited by 3,688
Willcutt, E. G., Doyle, A. E., Nigg, J. T., Faraone, S. V., & Pennington, B. F. (2005) · Biological Psychiatry · doi:10.1016/j.biopsych.2005.02.006 · Cited by 3,568
Working Memory Capacity as Executive Attention
Engle, R. W. (2002) · Current Directions in Psychological Science · doi:10.1111/1467-8721.00160 · Cited by 2,507
A practical solution to the pervasive problems ofp values
Wagenmakers, E.-J. (2007) · Psychonomic Bulletin & Review · doi:10.3758/bf03194105 · Cited by 2,490
Improving fluid intelligence with training on working memory
Jaeggi, S. M., Buschkuehl, M., Jonides, J., & Perrig, W. J. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0801268105 · Cited by 2,187
Research works printed but not linked: 4
- Jaeggi, S. M., Buschkuehl, M., & Jonides, J. (2009). Working memory training and transfer. Arlington: Presented at the annual ONR Contractor’s meeting.
- Jeffreys, H. (1961). Theory of probability. New York: Oxford University Press.
- Katz, B., Jaeggi, S. M., Buschkuehl, M., Shah, P., & Jonides, J. (2015). Money can’t buy you fluid intelligence (but it might not hurt either): The effect of compensation on transfer following a working memory intervention. Manuscript under review.
- Schwarb, H. (2012). Optimized cognitive training: Investigating the limits of brain training on generalized cognitive function (Unpublished doctoral dissertation). Atlanta: Georgia Institute of Technology.
Cited by
Sorted by citations
Do “brain-training” programs work?
Simons, D. J., Boot, W. R., Charness, N., Gathercole, S. E., Chabris, C. F., Hambrick, D. Z., & Stine-Morrow, E. A. L. (2016) · Psychological Science in the Public Interest · doi:10.1177/1529100616661983 · Cited by 1,183
Melby-Lervåg, M., Redick, T. S., & Hulme, C. (2016) · Perspectives on Psychological Science · doi:10.1177/1745691616635612 · Cited by 983
“Because previous meta-analyses have found a large difference between studies using treated and untreated controls (Dougherty et al., 2016; Lilienfeld, Ritschel, Lynn, Cautin, & Latzman, 2014; Melby-Lervåg & Hulme, 2013), these two designs were analyzed separately.”
Working memory training revisited: A multi-level meta-analysis of n-back training studies
Soveri, A., Antfolk, J., Karlsson, L., Salo, B., & Laine, M. (2017) · Psychonomic Bulletin & Review · doi:10.3758/s13423-016-1217-0 · Cited by 371
Cognitive Training Does Not Enhance General Cognition
Sala, G., & Gobet, F. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.10.004 · Cited by 303
“However, a re-analysis of the original data shows that the training effects are close to zero in studies including active control groups [47].”
Placebo effects in cognitive training
Foroughi, C. K., Monfort, S. S., Paczynski, M., McKnight, P. E., & Greenwood, P. M. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1601243113 · Cited by 270
Metadata
- Authors
- Dougherty, M. R., Hamovitz, T., & Tidwell, J. W.
- Affiliations
- University of Maryland, College Park (US)
- Corresponding author
- Dougherty, Michael R.
- Venue
- Psychonomic Bulletin & Review
- Published
- 2015-06-17
- Volume
- 23
- Issue
- 1
- Pages
- 306-316
- ISSN
- 1069-9384 (ISSN-L)
- 1531-5320
- OpenAlex
- W808339630
- Semantic Scholar
- 2058f86b82fec07fce805d1e617f1088fb8d4bd5
- Cited by
- 112
- References
- 54
- Citations by year
- 2026: 2 · 2025: 1 · 2024: 4 · 2023: 4 · 2022: 7 · 2021: 11 · 2020: 12 · 2019: 17 · 2018: 22 · 2017: 16 · 2016: 13 · 2015: 3
- FWCI
- 16.87
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Psychonomic Bulletin & Review (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
- Social Sciences › Psychology › Developmental and Educational Psychology › Cognitive and developmental aspects of mathematical skills
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Functions and Memory
- Keywords
- working memory training, fluid intelligence, transfer of training, Bayesian hypothesis testing, null hypothesis, placebo effect, active control, effect size
- MeSH terms
- Bayes Theorem, Data Interpretation, Statistical, Humans, Intelligence, Memory, Short-Term, Transfer, Psychology, Meta-Analysis as Topic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-08, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-08 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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