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      The Relationship Between the Menstrual Cycle, Oral Contraceptives, and Executive Function – Inhibition, Updating, and Shifting : A Systematic Review and Meta-Analysis

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          Abstract

          Abstract: Previous research suggests a link between oral contraceptives and cognitive functioning in women, yet the results are contradictory and limited by methodological inconsistencies. This is the first meta-analysis of studies comparing naturally cycling women with women taking oral contraceptives on measures testing three executive functions: inhibition, updating, and shifting. We conducted a systematic literature search. Sixteen articles were included which were either cross-sectional or experimental and compared executive functions between women taking oral contraceptives ( n = 588) or cycling naturally ( n = 594). The average sample size was n = 32.33 for oral contraceptives users and n = 31.34 for naturally cycling women with ranges going from 8 to 144 participants per study. The age range of participants in all the studies taken together was between 18 for the youngest participant and 50 years old for the oldest participant with a mean age of M = 21.97, SD = 2.28. The studies presented a mixture of androgenic and anti-androgenic oral contraceptives which were rarely analyzed as separate groups. We ran a multivariate meta-analysis model to estimate the effect size of 66 comparisons in executive functioning between the groups taking oral contraceptives and the groups of naturally cycling women. Overall, the effect size of differences in executive functioning between groups was not significant: d = 0.044, SE = 0.0713, 95% CI [−0.0959, 0.1839], z = 0.62; p = 0.54. The analysis of the cycle phases and types of executive functions as moderators was not significant, however, the studies assessed as having a lower quality increased the overall effect. Our analysis indicates no difference between oral contraceptive users and naturally cycling women on core executive functions but the high amount of heterogeneity might reflect a high level of methodological diversity. Implications for research design and methodology are discussed.

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          Bias in meta-analysis detected by a simple, graphical test

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            Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement

            Systematic reviews should build on a protocol that describes the rationale, hypothesis, and planned methods of the review; few reviews report whether a protocol exists. Detailed, well-described protocols can facilitate the understanding and appraisal of the review methods, as well as the detection of modifications to methods and selective reporting in completed reviews. We describe the development of a reporting guideline, the Preferred Reporting Items for Systematic reviews and Meta-Analyses for Protocols 2015 (PRISMA-P 2015). PRISMA-P consists of a 17-item checklist intended to facilitate the preparation and reporting of a robust protocol for the systematic review. Funders and those commissioning reviews might consider mandating the use of the checklist to facilitate the submission of relevant protocol information in funding applications. Similarly, peer reviewers and editors can use the guidance to gauge the completeness and transparency of a systematic review protocol submitted for publication in a journal or other medium.
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              Quantifying heterogeneity in a meta-analysis.

              The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.
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                Author and article information

                Contributors
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                Journal
                European Psychologist
                European Psychologist
                Hogrefe Publishing Group
                1016-9040
                1878-531X
                December 22 2023
                Affiliations
                [1 ]Psychology Institute, SWPS University, Warsaw, Poland
                [2 ]Psychology Institute, SWPS University, Katowice, Poland
                Article
                10.1027/1016-9040/a000514
                2a2ba3df-9ce8-4b02-aadc-a01bc3b1bcc3
                © 2023

                https://creativecommons.org/licenses/by/4.0

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