Studying Within-Person Changes in Work Motivation in the Short and Medium- Term: You Will Likely Need More Measurement Points than You Think!

En el estudio de la motivación laboral, el análisis intrapersona de datos provenientes de diseños longitudinales es hoy común en el área. Sin embargo, algunas características del diseño de investigación empleado pueden estar influyendo en la variabilidad intrapersona encontrada. En este trabajo analizamos cómo influye el número de medidas repetidas por participante en la varianza intrapersona de la motivación laboral. Mediante dos estudios (una revisión sistemática y un estudio empírico original) mostramos cómo el número de medidas repetidas influye significativamente en la varianza intrapersona encontrada, que llega a alcanzar valores máximos del 52%-54% sobre el total de la varianza. Para llegar a esos valores de varianza explicada en el caso de la motivación laboral se necesitarían un mínimo de 25-30 medidas repetidas para ser rigurosos en la medida de la varianza intraperson

The relative importance of phytoplankton aggregates and zooplankton fecal pellets to carbon export: insights from free-drifting sediment trap deployments in naturally iron-fertilised waters near the Kerguelen Plateau

The first KErguelen Ocean and Plateau compared Study (KEOPS1), conducted in the naturally iron-fertilised Kerguelen bloom, demonstrated that fecal material was the main pathway for exporting carbon to the deep ocean during summer (January–February 2005), suggesting a limited role of direct export via phytodetrital aggregates. The KEOPS2 project reinvestigated this issue during the spring bloom initiation (October–November 2011), when zooplankton communities may exert limited grazing pressure, and further explored the link between carbon flux, export efficiency and dominant sinking particles depending upon surface plankton community structure. Sinking particles were collected in polyacrylamide gel-filled and standard free-drifting sediment traps (PPS3/3), deployed at six stations between 100 and 400 m, to examine flux composition, particle origin and their size distributions. Results revealed an important contribution of phytodetrital aggregates (49 ± 10 and 45 ± 22% of the total number and volume of particles respectively, all stations and depths averaged). This high contribution dropped when converted to carbon content (30 ± 16% of total carbon, all stations and depths averaged), with cylindrical fecal pellets then representing the dominant fraction (56 ± 19%).At 100 and 200 m depth, iron- and biomass-enriched sites exhibited the highest carbon fluxes (maxima of 180 and 84 ± 27 mg C m-2 d-1, based on gel and PPS3/3 trap collection respectively), especially where large fecal pellets dominated over phytodetrital aggregates. Below these depths, carbon fluxes decreased (48 ± 21% decrease on average between 200 and 400 m), and mixed aggregates composed of phytodetritus and fecal matter dominated, suggesting an important role played by physical aggregation in deep carbon export.Export efficiencies determined from gels, PPS3/3 traps and 234Th disequilibria (200 m carbon flux/net primary productivity) were negatively correlated to net primary productivity with observed decreases from ~ 0.2 at low-iron sites to ~ 0.02 at high-iron sites. Varying phytoplankton communities and grazing pressure appear to explain this negative relationship. Our work emphasises the need to consider detailed plankton communities to accurately identify the controls on carbon export efficiency, which appear to include small spatio-temporal variations in ecosystem structure

The relative importance of phytoplankton aggregates and zooplankton fecal pellets to carbon export: insights from free-drifting sediment trap deployments in naturally iron-fertilised waters near the Kerguelen Plateau

The first KErguelen Ocean and Plateau compared Study (KEOPS1), conducted in the naturally iron-fertilised Kerguelen bloom, demonstrated that fecal material was the main pathway for exporting carbon to the deep ocean during summer (January–February 2005), suggesting a limited role of direct export via phytodetrital aggregates. The KEOPS2 project reinvestigated this issue during the spring bloom initiation (October–November 2011), when zooplankton communities may exert limited grazing pressure, and further explored the link between carbon flux, export efficiency and dominant sinking particles depending upon surface plankton community structure. Sinking particles were collected in polyacrylamide gel-filled and standard free-drifting sediment traps (PPS3/3), deployed at six stations between 100 and 400 m, to examine flux composition, particle origin and their size distributions. Results revealed an important contribution of phytodetrital aggregates (49+/-10 and 45+/-22% of the total number and volume of particles respectively, all stations and depths averaged). This high contribution dropped when converted to carbon content (30+/-16% of total carbon, all stations and depths averaged), with cylindrical fecal pellets then representing the dominant fraction (56+/-19 %). At 100 and 200m depth, iron- and biomass-enriched sites exhibited the highest carbon fluxes (maxima of 180 and 84+/- 27 mgCm-2 d-1, based on gel and PPS3/3 trap collection respectively), especially where large fecal pellets dominated over phytodetrital aggregates. Below these depths, carbon fluxes decreased (48+/-21%decrease on average between 200 and 400 m), and mixed aggregates composed of phytodetritus and fecal matter dominated, suggesting an important role played by physical aggregation in deep carbon export. Export efficiencies determined from gels, PPS3/3 traps and 234Th disequilibria (200m carbon flux/net primary productivity) were negatively correlated to net primary productivity with observed decreases from ~0.2 at low-iron sites to ~0.02 at high-iron sites. Varying phytoplankton communities and grazing pressure appear to explain this negative relationship. Our work emphasises the need to consider detailed plankton communities to accurately identify the controls on carbon export efficiency, which appear to include small spatio-temporal variations in ecosystem structure

Methodological criteria for the assessment of moderators in systematic reviews of randomised controlled trials : a consensus study

Background: Current methodological guidelines provide advice about the assessment of sub-group analysis within RCTs, but do not specify explicit criteria for assessment. Our objective was to provide researchers with a set of criteria that will facilitate the grading of evidence for moderators, in systematic reviews. Method: We developed a set of criteria from methodological manuscripts (n = 18) using snowballing technique, and electronic database searches. Criteria were reviewed by an international Delphi panel (n = 21), comprising authors who have published methodological papers in this area, and researchers who have been active in the study of sub-group analysis in RCTs. We used the Research ANd Development/University of California Los Angeles appropriateness method to assess consensus on the quantitative data. Free responses were coded for consensus and disagreement. In a subsequent round additional criteria were extracted from the Cochrane Reviewers’ Handbook, and the process was repeated. Results: The recommendations are that meta-analysts report both confirmatory and exploratory findings for subgroups analysis. Confirmatory findings must only come from studies in which a specific theory/evidence based apriori statement is made. Exploratory findings may be used to inform future/subsequent trials. However, for inclusion in the meta-analysis of moderators, the following additional criteria should be applied to each study: Baseline factors should be measured prior to randomisation, measurement of baseline factors should be of adequate reliability and validity, and a specific test of the interaction between baseline factors and interventions must be presented. Conclusions: There is consensus from a group of 21 international experts that methodological criteria to assess moderators within systematic reviews of RCTs is both timely and necessary. The consensus from the experts resulted in five criteria divided into two groups when synthesising evidence: confirmatory findings to support hypotheses about moderators and exploratory findings to inform future research. These recommendations are discussed in reference to previous recommendations for evaluating and reporting moderator studies

Imputation strategies for missing binary outcomes in cluster randomized trials

<p>Abstract</p> <p>Background</p> <p>Attrition, which leads to missing data, is a common problem in cluster randomized trials (CRTs), where groups of patients rather than individuals are randomized. Standard multiple imputation (MI) strategies may not be appropriate to impute missing data from CRTs since they assume independent data. In this paper, under the assumption of missing completely at random and covariate dependent missing, we compared six MI strategies which account for the intra-cluster correlation for missing binary outcomes in CRTs with the standard imputation strategies and complete case analysis approach using a simulation study.</p> <p>Method</p> <p>We considered three within-cluster and three across-cluster MI strategies for missing binary outcomes in CRTs. The three within-cluster MI strategies are logistic regression method, propensity score method, and Markov chain Monte Carlo (MCMC) method, which apply standard MI strategies within each cluster. The three across-cluster MI strategies are propensity score method, random-effects (RE) logistic regression approach, and logistic regression with cluster as a fixed effect. Based on the community hypertension assessment trial (CHAT) which has complete data, we designed a simulation study to investigate the performance of above MI strategies.</p> <p>Results</p> <p>The estimated treatment effect and its 95% confidence interval (CI) from generalized estimating equations (GEE) model based on the CHAT complete dataset are 1.14 (0.76 1.70). When 30% of binary outcome are missing completely at random, a simulation study shows that the estimated treatment effects and the corresponding 95% CIs from GEE model are 1.15 (0.76 1.75) if complete case analysis is used, 1.12 (0.72 1.73) if within-cluster MCMC method is used, 1.21 (0.80 1.81) if across-cluster RE logistic regression is used, and 1.16 (0.82 1.64) if standard logistic regression which does not account for clustering is used.</p> <p>Conclusion</p> <p>When the percentage of missing data is low or intra-cluster correlation coefficient is small, different approaches for handling missing binary outcome data generate quite similar results. When the percentage of missing data is large, standard MI strategies, which do not take into account the intra-cluster correlation, underestimate the variance of the treatment effect. Within-cluster and across-cluster MI strategies (except for random-effects logistic regression MI strategy), which take the intra-cluster correlation into account, seem to be more appropriate to handle the missing outcome from CRTs. Under the same imputation strategy and percentage of missingness, the estimates of the treatment effect from GEE and RE logistic regression models are similar.</p

What causes the inverse relationship between primary production and export efficiency in the Southern Ocean?

The ocean contributes to regulating atmospheric CO2 levels, partly via variability in the fraction of primary production (PP) which is exported out of the surface layer (i.e. the e-ratio). Southern Ocean studies have found that, contrary to global scale analyses, an inverse relationship exists between e-ratio and PP. This relationship remains unexplained, with potential hypotheses being i) large export of dissolved organic carbon (DOC) in high PP areas, ii) strong surface microbial recycling in high PP regions and/ or iii) grazing mediated export varies inversely with PP. We find that the export of DOC has a limited influence in setting the negative e-ratio/PP relationship. However, we observed that at sites with low PP and high e-ratios, zooplankton mediated export is large and surface microbial abundance low suggesting that both are important drivers of the magnitude of the e-ratio in the Southern Ocean

Resupply of mesopelagic dissolved iron controlled by particulate iron composition

The dissolved iron supply controls half of the oceans’ primary productivity. Resupply by the remineralization of sinking particles, and subsequent vertical mixing, largely sustains this productivity. However, our understanding of the drivers of dissolved iron resupply, and their influence on its vertical distribution across the oceans, is still limited due to sparse observations. There is a lack of empirical evidence as to what controls the subsurface iron remineralization due to difficulties in studying mesopelagic biogeochemistry. Here we present estimates of particulate transformations to dissolved iron, concurrent oxygen consumption and iron-binding ligand replenishment based on in situ mesopelagic experiments. Dissolved iron regeneration efficiencies (that is, replenishment over oxygen consumption) were 10- to 100-fold higher in low-dust subantarctic waters relative to higher-dust Mediterranean sites. Regeneration efficiencies are heavily influenced by particle composition. Their make-up dictates ligand release, controls scavenging, modulates ballasting and may lead to the differential remineralization of biogenic versus lithogenic iron. At high-dust sites, these processes together increase the iron remineralization length scale. Modelling reveals that in oceanic regions near deserts, enhanced lithogenic fluxes deepen the ferricline, which alter the vertical patterns of dissolved iron replenishment, and set its redistribution at the global scale. Such wide-ranging regeneration efficiencies drive different vertical patterns in dissolved iron replenishment across oceanic provinces