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Reproducibility is a defining feature of science, but the extent to which it characterizes current research is unknown. We conducted replications of 100 experimental and correlational studies published in three psychology journals using high-powered designs and original materials when available. Replication effects were half the magnitude of original effects, representing a substantial decline. Ninety-seven percent of original studies had statistically significant results. Thirty-six percent of replications had statistically significant results; 47% of original effect sizes were in the 95% confidence interval of the replication effect size; 39% of effects were subjectively rated to have replicated the original result; and if no bias in original results is assumed, combining original and replication results left 68% with statistically significant effects. Correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams.
The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia
(2019)
The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.
The relationships between sedentary lifestyle, sitting behaviour, and low back pain (LBP) remain controversial. In this study, we investigated the relationship between back pain and occupational sitting habits in 64 call-centre employees. A textile pressure mat was used to evaluate and parameterise sitting behaviour over a total of 400 h, while pain questionnaires evaluated acute and chronic LBP. Seventy-five percent of the participants reported some level of either chronic or acute back pain. Individuals with chronic LBP demonstrated a possible trend (t-test not significant) towards more static sitting behaviour compared to their pain-free counterparts. Furthermore, a greater association was found between sitting behaviour and chronic LBP than for acute pain/disability, which is plausibly due to a greater awareness of pain-free sitting positions in individuals with chronic pain compared to those affected by acute pain.
Nowadays, working in an office environment is ubiquitous. At the same time, progressively more people suffer from occupational musculoskeletal disorders. Therefore, the aim of this pilot study was to analyse the influence of back pain on sitting behaviour in the office environment. A textile pressure mat (64-sensor-matrix) placed on the seat pan was used to identify the adopted sitting positions of 20 office workers by means of random forest classification. Additionally, two standardised questionnaires (Korff, BPI) were used to assess short and long-term back pain in order to divide the subjects into two groups (with and without back pain). Independent t-test indicated that subjects who registered back pain within the last 24 h showed a clear trend towards a more static sitting behaviour. Therefore, the developed sensor system has successfully been introduced to characterise and compare sitting behaviour of subjects with and without back pain. (C) 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licensesiby-nc-nd/4.0/).
The use of high-frequency sensors on profiling buoys to investigate physical, chemical, and biological processes in lakes is
increasing rapidly. Profiling buoys with automated winches and sensors that collect high-frequency chlorophyll fluorescence
(ChlF) profiles in 11 lakes in the Global Lake Ecological Observatory Network (GLEON) allowed the study of the vertical
and temporal distribution of ChlF, including the formation of subsurface chlorophyll maxima (SSCM). The effectiveness of 3
methods for sampling phytoplankton distributions in lakes, including (1) manual profiles, (2) single-depth buoys, and (3)
profiling buoys were assessed. High-frequency ChlF surface data and profiles were compared to predictions from the
Plankton Ecology Group (PEG) model. The depth-integrated ChlF dynamics measured by the profiling buoy data revealed a
greater complexity that neither conventional sampling nor the generalized PEG model captured. Conventional sampling
techniques would have missed SSCM in 7 of 11 study lakes. Although surface-only ChlF data underestimated average water
column ChlF, at times by nearly 2-fold in 4 of the lakes, overall there was a remarkable similarity between surface and mean
water column data. Contrary to the PEG model’s proposed negligible role for physical control of phytoplankton during the
growing season, thermal structure and light availability were closely associated with ChlF seasonal depth distribution. Thus,
an extension of the PEG model is proposed, with a new conceptual framework that explicitly includes physical metrics to
better predict SSCM formation in lakes and highlight when profiling buoys are especially informative.