Assessment of temporal instability in the applied ecology and conservation evidence base

Outcomes of meta-analyses are increasingly used to inform evidence-based decision making in various research fields. However, a number of recent studies have reported rapid temporal changes in magnitude and significance of the reported effects which could make policy-relevant recommendations from meta-analyses to quickly go out of date. We assessed the extent and patterns of temporal trends in magnitude and statistical significance of the cumulative effects in meta-analyses in applied ecology and conservation published between 2004 and 2018. Of the 121 meta-analyses analysed, 93% showed a temporal trend in cumulative effect magnitude or significance with 27% of the datasets exhibiting temporal trends in both. The most common trend was the early study effect when at least one of the first 5 years effect size estimates exhibited more than 50% magnitude difference to the subsequent estimate. The observed temporal trends persisted in majority of datasets once moderators were accounted for. Only 5 datasets showed significant changes in sample size over time which could potentially explain the observed temporal change in the cumulative effects. Year of publication of meta-analysis had no significant effect on presence of temporal trends in cumulative effects. Our results show that temporal changes in magnitude and statistical significance in applied ecology are widespread and represent a serious potential threat to use of meta-analyses for decision-making in conservation and environmental management. We recommend use of cumulative meta-analyses and call for more studies exploring the causes of the temporal effects.

Is there selective retroactive memory enhancement in humans?: a meta-analysis

Memory is an adaptive and flexible system that preferentially stores motivationally relevant information. However, in some cases information that is initially irrelevant can become relevant at a later time. The question arises whether and to what extent the memory system can retroactively boost memories of the initially irrelevant information. Experimental studies in animals and humans have provided evidence for such retroactive memory boosting. Additionally, these studies suggest that retroactive memory enhancement (RME) can be selective to the semantic meaning of the material. Nonetheless, recent experimental work could not replicate these findings, posing the question whether the selective RME effect is reliable. To synthesize the available evidence, we conducted meta-analyses of 14 experiments. Although the classical meta-analytic procedure suggested a small selective RME effect, Cohen's dz = 0.16, when accounting for small-study bias using robust Bayesian meta-analysis the null hypothesis was supported, Cohen's dz = 0.02, BF01 = 3.03. Furthermore strong evidence was found for a bias due to small-study effects, BF10 = 11.39. Together, this calls the reliability of a selective RME effect into question.

The Meta-Plot

Abstract. The meta-plot is a descriptive visual tool for meta-analysis that provides information on the primary studies in the meta-analysis and the results of the meta-analysis. More precisely, the meta-plot portrays (1) the precision and statistical power of the primary studies in the meta-analysis, (2) the estimate and confidence interval of a random-effects meta-analysis, (3) the results of a cumulative random-effects meta-analysis yielding a robustness check of the meta-analytic effect size with respect to primary studies’ precision, and (4) evidence of publication bias. After explaining the underlying logic and theory, the meta-plot is applied to two cherry-picked meta-analyses that appear to be biased and to 10 randomly selected meta-analyses from the psychological literature. We recommend accompanying any meta-analysis of common effect size measures with the meta-plot.

Journal N-Pact Factors From 2011 to 2019: Evaluating the Quality of Social/Personality Journals With Respect to Sample Size and Statistical Power

Scholars and institutions commonly use impact factors to evaluate the quality of empirical research. However, a number of findings published in journals with high impact factors have failed to replicate, suggesting that impact alone may not be an accurate indicator of quality. Fraley and Vazire proposed an alternative index, the N-pact factor, which indexes the median sample size of published studies, providing a narrow but relevant indicator of research quality. In the present research, we expand on the original report by examining the N-pact factor of social/personality-psychology journals between 2011 and 2019, incorporating additional journals and accounting for study design (i.e., between persons, repeated measures, and mixed). There was substantial variation in the sample sizes used in studies published in different journals. Journals that emphasized personality processes and individual differences had larger N-pact factors than journals that emphasized social-psychological processes. Moreover, N-pact factors were largely independent of traditional markers of impact. Although the majority of journals in 2011 published studies that were not well powered to detect an effect of ρ = .20, this situation had improved considerably by 2019. In 2019, eight of the nine journals we sampled published studies that were, on average, powered at 80% or higher to detect such an effect. After decades of unheeded warnings from methodologists about the dangers of small-sample designs, the field of social/personality psychology has begun to use larger samples. We hope the N-pact factor will be supplemented by other indices that can be used as alternatives to improve further the evaluation of research.

A Systematic Review and Meta-Analysis on Post-Abortion Contraceptive Utilization and Associated Factors in Ethiopia

Background

Post-abortion contraceptive utilization is the initiation and use of family planning methods at the time of management of abortion or before fertility returns. A significant discrepancy was reported regarding the prevalence and its associated factors of post-abortion contraceptive utilization in Ethiopia. So, this systematic review and meta-analysis aimed to estimate the pooled prevalence of post-abortion contraceptive utilization and its associated factors in Ethiopia.

Methods

Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guideline was used. The databases such as PubMed, Google Scholar, Science Direct, Cochrane library, Scopus, CINAHL, Web of Science, and additional searches by using direct Google search, libraries, and preprint were searched. Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument (JBI-MAStARI) was used for critical appraisal.

Results

A total of 17 studies with 13,075 individuals were included. Of these, 14 studies with 5,719 individuals were used to estimate the prevalence. The pooled prevalence of post-abortion contraceptive utilization in Ethiopia was 63.64% (95% CI: 57.75–69.53). The subgroup analysis reported the highest prevalence of post-abortion contraceptive utilization in a study conducted in Addis Ababa (77.40%), a study published in 2015–2021 (66.15%), and among studies with a sample size >400 (66.84%). The pooled odds ratio (OR) of post-abortion contraceptive utilization for the mothers who had post-abortion family planning counseling was 4.15 (95% CI = 1.30, 13.2), and history of family planning utilization was 4.28 (95% CI = 2.66, 6.89).

Conclusions

The pooled prevalence of utilization of post-abortion contraceptives in this meta-analysis remains low. Post-abortion family planning counseling and the history of the utilization of modern family planning methods were significantly associated with the practice of post-abortion contraceptives. The Ministry of Health should encourage post-abortion family planning utilization, making more efforts on post-abortion contraceptive counseling. Health facilities should work hard to strengthen the family planning counseling service, especially focusing on those who had no previous family planning utilization.

Prevalence of exclusive breastfeeding practice and its association with maternal employment in Ethiopia: a systematic review and meta-analysis

Background

Exclusive breastfeeding is defined as the practice of providing only breast milk for an infant for the first 6 months of life without the addition of any other food or water, except for vitamins, mineral supplements, and medicines. Findings are inconsistent regarding the prevalence of exclusive breastfeeding in Ethiopia. Full-time maternal employment is an important factor contributing to the low rates of practice of exclusive breastfeeding. Empowering women to exclusively breastfeed, by enacting 6 months’ mandatory paid maternity leave can increase the rate of exclusive breastfeeding in the first 6 months of life up to 50%. The purpose of this review was to estimate the pooled prevalence of exclusive breastfeeding and its association with full-time maternal employment in the first 6 months of life for infants in the context of Ethiopia.

Methods

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was used in this systematic review and meta-analysis. All observational studies reporting the prevalence of exclusive breastfeeding and its association with maternal employment in Ethiopia were considered. The search was conducted from 6 November 2020 to 31 December 2020 and all papers published in the English language from 1 January 2015 to 31 December 2020 were included in this review.

Results

Forty-five studies were included in the final analysis after reviewing 751 studies in this meta-analysis yielding the pooled prevalence of EBF 60.42% (95% CI 55.81, 65.02) at 6 months in Ethiopia. Those full-time employed mothers in the first 6 months were 57% less likely to practice exclusive breastfeeding in comparison to mothers not in paid employment in Ethiopia (OR 0.43; 95% CI 0.31, 0.61).

Conclusions

Full-time maternal employment was negatively associated with the practice of exclusive breastfeeding in comparison to unemployed mothers. The prevalence of exclusive breastfeeding in Ethiopia is low in comparison to the global recommendation. The Ethiopian government should implement policies that empower women. The governmental and non-governmental organizations should create a conducive environment for mothers to practice exclusive breastfeeding in the workplace.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13006-021-00432-x.

Replicability, Robustness, and Reproducibility in Psychological Science

Replication-an important, uncommon, and misunderstood practice-is gaining appreciation in psychology. Achieving replicability is important for making research progress. If findings are not replicable, then prediction and theory development are stifled. If findings are replicable, then interrogation of their meaning and validity can advance knowledge. Assessing replicability can be productive for generating and testing hypotheses by actively confronting current understandings to identify weaknesses and spur innovation. For psychology, the 2010s might be characterized as a decade of active confrontation. Systematic and multi-site replication projects assessed current understandings and observed surprising failures to replicate many published findings. Replication efforts highlighted sociocultural challenges such as disincentives to conduct replications and a tendency to frame replication as a personal attack rather than a healthy scientific practice, and they raised awareness that replication contributes to self-correction. Nevertheless, innovation in doing and understanding replication and its cousins, reproducibility and robustness, has positioned psychology to improve research practices and accelerate progress. Expected final online publication date for the Annual Review of Psychology, Volume 73 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

A meta-review of transparency and reproducibility-related reporting practices in published meta-analyses on clinical psychological interventions (2000-2020)

Meta-analysis is a powerful and important tool to synthesize the literature about a research topic. Like other kinds of research, meta-analyses must be reproducible to be compliant with the principles of the scientific method. Furthermore, reproducible meta-analyses can be easily updated with new data and reanalysed applying new and more refined analysis techniques. We attempted to empirically assess the prevalence of transparency and reproducibility-related reporting practices in published meta-analyses from clinical psychology by examining a random sample of 100 meta-analyses. Our purpose was to identify the key points that could be improved, with the aim of providing some recommendations for carrying out reproducible meta-analyses. We conducted a meta-review of meta-analyses of psychological interventions published between 2000 and 2020. We searched PubMed, PsycInfo and Web of Science databases. A structured coding form to assess transparency indicators was created based on previous studies and existing meta-analysis guidelines. We found major issues concerning: completely reproducible search procedures report, specification of the exact method to compute effect sizes, choice of weighting factors and estimators, lack of availability of the raw statistics used to compute the effect size and of interoperability of available data, and practically total absence of analysis script code sharing. Based on our findings, we conclude with recommendations intended to improve the transparency, openness, and reproducibility-related reporting practices of meta-analyses in clinical psychology and related areas.

Is personality associated with dementia risk? A meta-analytic investigation

This study provides a quantitative synthesis of the prospective associations between personality traits (neuroticism, extraversion, openness, agreeableness, conscientiousness) and the risk of incident Alzheimer's disease and related dementias. We conducted five separate meta-analyses with 8-12 samples (N = 30,036 to 33,054) that were identified through a systematic literature search following the MOOSE guidelines. Higher neuroticism (HR = 1.24, 95% CI [1.17, 1.31]) and lower conscientiousness (HR = 0.77, 95% CI [0.73, 0.81]) were associated with increased dementia risk, even after accounting for covariates such as depressive symptoms. Lower extraversion (HR = 0.92, 95% CI [0.86, 0.97]), openness (HR = 0.91, 95% CI [0.86, 0.96]), and agreeableness (HR = 0.90, 95% CI [0.83, 0.98]) were also associated with increased risk, but these associations were less robust and not significant in fully adjusted models. No evidence of publication bias was found. The strength of associations was unrelated to publication year (i.e., no evidence of winner's curse). Meta-regressions indicated consistent effects for neuroticism, openness, and conscientiousness across methods to assess dementia, dementia type, follow-up length, sample age, minority, country, and personality measures. The association of extraversion and agreeableness varied by country. Our findings indicate robust associations of neuroticism and conscientiousness with dementia risk.

Does contingent biofeedback improve cardiac interoception? A preregistered replication of Meyerholz, Irzinger, Withöft, Gerlach, and Pohl (2019) using the heartbeat discrimination task in a randomised control trial

Meyerholz, Irzinger, Withöft, Gerlach, and Pohl (2019) reported on a comparably large effect (d = 1.21) of a contingent biofeedback procedure on cardiac accuracy as assessed by the heartbeat tracking task. However, this task has recently been criticized as a measure of interoceptive accuracy. We aimed to replicate this finding by using the well-validated heartbeat discrimination task and to compare the biofeedback with a deep breathing and a control condition (viewing a film clip). The trial was preregistered at open science framework (https://osf.io/9fxn6). Overall, 93 participants were randomized to one of the three conditions and the heartbeat discrimination task was presented prior and after the 20-minutes training sessions. The study had a power of .86 to detect a medium-sized effect in the biofeedback group and a power of .96 to detect a medium-sized interaction of intervention group and time. A general tendency for improvement in heartbeat detection accuracy was found across intervention groups (d = 0.19, p = .08); however, groups did not differ significantly. In particular, there was no significant interaction of intervention group and time (f = .00, p = .98) and no reliable effect for the biofeedback group (d = 0.15, p = .42). One limitation is that a different, but well-validated task was used to quantify interoceptive accuracy. This study suggests that biofeedback might not improve interoceptive accuracy in the cardiac domain, but effects seem to depend on the specific task applied.

Limited evidence for the effect of red color on cognitive performance: A meta-analysis

Red color supposedly affects cognitive functioning in achievement situations and impairs test performance. Although this has been shown for different cognitive domains in different populations and cultural contexts, recent studies including close replications failed to corroborate this effect. Reported here is a random-effects meta-analysis of 67 effect sizes (38 samples) that compared test performance after viewing red or a control color. For anagram tests and knowledge tests no significant difference between color conditions was found (Cohen's d of -0.06 and -0.04); for reasoning tests the pooled effect of d = -0.34, 95% CI [-0.61, -0.06] indicated significantly lower scores in the red condition. The cumulative meta-analysis revealed substantially larger effects in initial studies as compared to subsequent research. After correcting for publication bias no evidential value for an effect of red color on intellectual performance was available. The review casts doubt on the existence of a robust color-priming effect in achievement situations.

Effect Sizes, Power, and Biases in Intelligence Research: A Meta-Meta-Analysis

In this meta-study, we analyzed 2442 effect sizes from 131 meta-analyses in intelligence research, published from 1984 to 2014, to estimate the average effect size, median power, and evidence for bias. We found that the average effect size in intelligence research was a Pearson's correlation of 0.26, and the median sample size was 60. Furthermore, across primary studies, we found a median power of 11.9% to detect a small effect, 54.5% to detect a medium effect, and 93.9% to detect a large effect. We documented differences in average effect size and median estimated power between different types of intelligence studies (correlational studies, studies of group differences, experiments, toxicology, and behavior genetics). On average, across all meta-analyses (but not in every meta-analysis), we found evidence for small-study effects, potentially indicating publication bias and overestimated effects. We found no differences in small-study effects between different study types. We also found no convincing evidence for the decline effect, US effect, or citation bias across meta-analyses. We concluded that intelligence research does show signs of low power and publication bias, but that these problems seem less severe than in many other scientific fields.

Recommendations in pre-registrations and internal review board proposals promote formal power analyses but do not increase sample size

In this preregistered study, we investigated whether the statistical power of a study is higher when researchers are asked to make a formal power analysis before collecting data. We compared the sample size descriptions from two sources: (i) a sample of pre-registrations created according to the guidelines for the Center for Open Science Preregistration Challenge (PCRs) and a sample of institutional review board (IRB) proposals from Tilburg School of Behavior and Social Sciences, which both include a recommendation to do a formal power analysis, and (ii) a sample of pre-registrations created according to the guidelines for Open Science Framework Standard Pre-Data Collection Registrations (SPRs) in which no guidance on sample size planning is given. We found that PCRs and IRBs (72%) more often included sample size decisions based on power analyses than the SPRs (45%). However, this did not result in larger planned sample sizes. The determined sample size of the PCRs and IRB proposals (Md = 90.50) was not higher than the determined sample size of the SPRs (Md = 126.00; W = 3389.5, p = 0.936). Typically, power analyses in the registrations were conducted with G*power, assuming a medium effect size, α = .05 and a power of .80. Only 20% of the power analyses contained enough information to fully reproduce the results and only 62% of these power analyses pertained to the main hypothesis test in the pre-registration. Therefore, we see ample room for improvements in the quality of the registrations and we offer several recommendations to do so.

Are Social Media Ruining Our Lives? A Review of Meta-Analytic Evidence

A growing number of studies have examined the psychological corollaries of using social networking sites (SNSs) such as Facebook, Instagram, or Twitter (often called social media). The interdisciplinary research area and conflicting evidence from primary studies complicate the assessment of current scholarly knowledge in this field of high public attention. We review meta-analytic evidence on three hotly debated topics regarding the effects of SNSs: well-being, academic achievement, and narcissism. Meta-analyses from different laboratories draw a rather equivocal picture. They show small associations in the r = .10 range between the intensity of SNS use and loneliness, self-esteem, life satisfaction, or self-reported depression, and somewhat stronger links to a thin body ideal and higher social capital. There is no indication for potential devastating effects of social media on school achievement; social media use and school grades are unrelated for adolescents. The meta-analyses revealed small to moderate associations between narcissism and SNS use. In sum, meta-analytic evidence is not in support of dramatic claims relating social media use to mischief.

Intuitive Honesty Versus Dishonesty: Meta-Analytic Evidence

Is self-serving lying intuitive? Or does honesty come naturally? Many experiments have manipulated reliance on intuition in behavioral-dishonesty tasks, with mixed results. We present two meta-analyses (with evidential value) testing whether an intuitive mind-set affects the proportion of liars (k = 73; n = 12,711) and the magnitude of lying (k = 50; n = 6,473). The results indicate that when dishonesty harms abstract others, promoting intuition causes more people to lie, log odds ratio = 0.38, p = .0004, and people to lie more, Hedges's g = 0.26, p < .0001. However, when dishonesty inflicts harm on concrete others, promoting intuition has no significant effect on dishonesty (p > .63). We propose one potential explanation: The intuitive appeal of prosociality may cancel out the intuitive selfish appeal of dishonesty, suggesting that the social consequences of lying could be a promising key to the riddle of intuition's role in honesty. We discuss limitations such as the relatively unbalanced distribution of studies using concrete versus abstract victims and the overall large interstudy heterogeneity.

Practical tools and strategies for researchers to increase replicability

A growing body of evidence indicates that the effects reported in many scientific fields may be overestimated or even false. This problem has gained a lot of attention in the field of psychology, where researchers have even started to speak of a 'replication crisis'. Fortunately, a number of measures to rectify this problem have already been proposed and implemented, some inspired by practices in other scientific fields. In this review, I briefly examine this issue in the field of psychology and suggest some practical tools and strategies that researchers can implement to increase replicability and the overall quality of their scientific research. WHAT THIS PAPER ADDS: Researchers can implement many practical tools and strategies to improve replicability of their findings. Strategies include improving statistical inference, pre-registration, multisite collaboration, and sharing data. Different scientific fields could benefit from looking at each other's best practices.

Publication bias examined in meta-analyses from psychology and medicine: A meta-meta-analysis

Publication bias is a substantial problem for the credibility of research in general and of meta-analyses in particular, as it yields overestimated effects and may suggest the existence of non-existing effects. Although there is consensus that publication bias exists, how strongly it affects different scientific literatures is currently less well-known. We examined evidence of publication bias in a large-scale data set of primary studies that were included in 83 meta-analyses published in Psychological Bulletin (representing meta-analyses from psychology) and 499 systematic reviews from the Cochrane Database of Systematic Reviews (CDSR; representing meta-analyses from medicine). Publication bias was assessed on all homogeneous subsets (3.8% of all subsets of meta-analyses published in Psychological Bulletin) of primary studies included in meta-analyses, because publication bias methods do not have good statistical properties if the true effect size is heterogeneous. Publication bias tests did not reveal evidence for bias in the homogeneous subsets. Overestimation was minimal but statistically significant, providing evidence of publication bias that appeared to be similar in both fields. However, a Monte-Carlo simulation study revealed that the creation of homogeneous subsets resulted in challenging conditions for publication bias methods since the number of effect sizes in a subset was rather small (median number of effect sizes equaled 6). Our findings are in line with, in its most extreme case, publication bias ranging from no bias until only 5% statistically nonsignificant effect sizes being published. These and other findings, in combination with the small percentages of statistically significant primary effect sizes (28.9% and 18.9% for subsets published in Psychological Bulletin and CDSR), led to the conclusion that evidence for publication bias in the studied homogeneous subsets is weak, but suggestive of mild publication bias in both psychology and medicine.

Examining reproducibility in psychology: A hybrid method for combining a statistically significant original study and a replication

The unrealistically high rate of positive results within psychology has increased the attention to replication research. However, researchers who conduct a replication and want to statistically combine the results of their replication with a statistically significant original study encounter problems when using traditional meta-analysis techniques. The original study's effect size is most probably overestimated because it is statistically significant, and this bias is not taken into consideration in traditional meta-analysis. We have developed a hybrid method that does take the statistical significance of an original study into account and enables (a) accurate effect size estimation, (b) estimation of a confidence interval, and (c) testing of the null hypothesis of no effect. We analytically approximate the performance of the hybrid method and describe its statistical properties. By applying the hybrid method to data from the Reproducibility Project: Psychology (Open Science Collaboration, 2015), we demonstrate that the conclusions based on the hybrid method are often in line with those of the replication, suggesting that many published psychological studies have smaller effect sizes than those reported in the original study, and that some effects may even be absent. We offer hands-on guidelines for how to statistically combine an original study and replication, and have developed a Web-based application ( https://rvanaert.shinyapps.io/hybrid ) for applying the hybrid method.

Who Should Do Replication Labor?

Scientists, for the most part, want to get it right. However, the social structures that govern their work undermine that aim, and this leads to nonreplicable findings in many fields. Because the social structure of science is a decentralized system, it is difficult to intervene. In this article, I discuss how we might do so, focusing on self-corrective-labor schemes (i.e., ways of distributing replication efforts within the scientific community). First, I argue that we need to implement a scheme that makes replication work outcome independent, systematic, and sustainable. Second, I use these three criteria to evaluate extant proposals, which place the responsibility for replication on original researchers, consumers of their research, students, or many labs. Third, on the basis of a philosophical analysis of the reward system of science and the benefits of the division of cognitive labor, I propose a scheme that satisfies the criteria better: the professional scheme. This scheme has two main components. First, the scientific community is organized into two groups: discovery researchers, who produce new findings, and confirmation researchers, whose primary function is to do confirmation work (i.e., replication, reproduction, meta-analysis). Second, a distinct reward system is established for confirmation researchers so that their career advancement is separated from whether they obtain positive experimental results.

Replication and Reproducibility in Cross-Cultural Psychology

Replication is the scientific gold standard that enables the confirmation of research findings. Concerns related to publication bias, flexibility in data analysis, and high-profile cases of academic misconduct have led to recent calls for more replication and systematic accumulation of scientific knowledge in psychological science. This renewed emphasis on replication may pose specific challenges to cross-cultural research due to inherent practical difficulties in emulating an original study in other cultural groups. The purpose of the present article is to discuss how the core concepts of this replication debate apply to cross-cultural psychology. Distinct to replications in cross-cultural research are examinations of bias and equivalence in manipulations and procedures, and that targeted research populations may differ in meaningful ways. We identify issues in current psychological research (analytic flexibility, low power) and possible solutions (preregistration, power analysis), and discuss ways to implement best practices in cross-cultural replication attempts.

Empirical assessment of published effect sizes and power in the recent cognitive neuroscience and psychology literature

We have empirically assessed the distribution of published effect sizes and estimated power by analyzing 26,841 statistical records from 3,801 cognitive neuroscience and psychology papers published recently. The reported median effect size was D = 0.93 (interquartile range: 0.64-1.46) for nominally statistically significant results and D = 0.24 (0.11-0.42) for nonsignificant results. Median power to detect small, medium, and large effects was 0.12, 0.44, and 0.73, reflecting no improvement through the past half-century. This is so because sample sizes have remained small. Assuming similar true effect sizes in both disciplines, power was lower in cognitive neuroscience than in psychology. Journal impact factors negatively correlated with power. Assuming a realistic range of prior probabilities for null hypotheses, false report probability is likely to exceed 50% for the whole literature. In light of our findings, the recently reported low replication success in psychology is realistic, and worse performance may be expected for cognitive neuroscience.

Leukocyte telomere length and hippocampus volume: a meta-analysis

Leukocyte telomere length has been shown to correlate to hippocampus volume, but effect estimates differ in magnitude and are not uniformly positive. This study aimed primarily to investigate the relationship between leukocyte telomere length and hippocampus gray matter volume by meta-analysis and secondarily to investigate possible effect moderators. Five studies were included with a total of 2107 participants, of which 1960 were contributed by one single influential study. A random-effects meta-analysis estimated the effect to r = 0.12 [95% CI -0.13, 0.37] in the presence of heterogeneity and a subjectively estimated moderate to high risk of bias. There was no evidence that apolipoprotein E (APOE) genotype was an effect moderator, nor that the ratio of leukocyte telomerase activity to telomere length was a better predictor than leukocyte telomere length for hippocampus volume. This meta-analysis, while not proving a positive relationship, also is not able to disprove the earlier finding of a positive correlation in the one large study included in analyses. We propose that a relationship between leukocyte telomere length and hippocamus volume may be mediated by transmigrating monocytes which differentiate into microglia in the brain parenchyma.