Measuring co-authorship and networking-adjusted scientific impact

Appraisal of the scientific impact of researchers, teams and institutions with productivity and citation metrics has major repercussions. Funding and promotion of individuals and survival of teams and institutions depend on publications and citations. In this competitive environment, the number of authors per paper is increasing and apparently some co-authors don't satisfy authorship criteria. Listing of individual contributions is still sporadic and also open to manipulation. Metrics are needed to measure the networking intensity for a single scientist or group of scientists accounting for patterns of co-authorship. Here, I define I1 for a single scientist as the number of authors who appear in at least I1 papers of the specific scientist. For a group of scientists or institution, In is defined as the number of authors who appear in at least In papers that bear the affiliation of the group or institution. I1 depends on the number of papers authored Np. The power exponent R of the relationship between I1 and Np categorizes scientists as solitary (R>2.5), nuclear (R=2.25-2.5), networked (R=2-2.25), extensively networked (R=1.75-2) or collaborators (R<1.75). R may be used to adjust for co-authorship networking the citation impact of a scientist. In similarly provides a simple measure of the effective networking size to adjust the citation impact of groups or institutions. Empirical data are provided for single scientists and institutions for the proposed metrics. Cautious adoption of adjustments for co-authorship and networking in scientific appraisals may offer incentives for more accountable co-authorship behaviour in published articles.Comment: 25 pages, 5 figure

The influence of the team in conducting a systematic review

There is an increasing body of research documenting flaws in many published systematic reviews' methodological and reporting conduct. When good systematic review practice is questioned, attention is rarely turned to the composition of the team that conducted the systematic review. This commentary highlights a number of relevant articles indicating how the composition of the review team could jeopardise the integrity of the systematic review study and its conclusions. Key biases require closer attention such as sponsorship bias and researcher allegiance, but there may also be less obvious affiliations in teams conducting secondary evidence-syntheses. The importance of transparency and disclosure are now firmly on the agenda for clinical trials and primary research, but the meta-biases that systematic reviews may be at risk from now require further scrutiny

Impact of inhaled corticosteroids on growth in children with asthma: systematic review and meta-analysis

Background: Long-term inhaled corticosteroids (ICS) may reduce growth velocity and final height of children with asthma. We aimed to evaluate the association between ICS use of >12 months and growth. Methods: We initially searched MEDLINE and EMBASE in July 2013, followed by a PubMed search updated to December 2014. We selected RCTs and controlled observational studies of ICS use in patients with asthma. We conducted random effects meta-analysis of mean differences in growth velocity (cm/year) or final height (cm) between groups. Heterogeneity was assessed using the I2 statistic. Results: We found 23 relevant studies (twenty RCTs and three observational studies) after screening 1882 hits. Meta-analysis of 16 RCTs showed that ICS use significantly reduced growth velocity at one year follow-up (mean difference -0.48 cm/year (95% CI -0.66 to -0.29)). There was evidence of a dose-response effect in three RCTs. Final adult height showed a mean reduction of -1.20 cm (95% CI -1.90 cm to -0.50 cm) with budesonide versus placebo in a high quality RCT. Meta-analysis of two lower quality observational studies revealed uncertainty in the association between ICS use and final adult height, pooled mean difference -0.85 cm (95% CI -3.35 to 1.65). Conclusion: Use of ICS for >12 months in children with asthma has a limited impact on annual growth velocity. In ICS users, there is a slight reduction of about a centimeter in final adult height, which when interpreted in the context of average adult height in England (175 cm for men and 161 cm for women), represents a 0.7% reduction compared to non-ICS users

Chromosome 1p13 genetic variants antagonize the risk of myocardial infarction associated with high ApoB serum levels

PMCID: PMC3480949This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

What’s in a surname? Physique, aptitude, and sports type comparisons between Tailors and Smiths

Combined heredity of surnames and physique, coupled with past marriage patterns and trade-specific physical aptitude and selection factors, may have led to differential assortment of bodily characteristics among present-day men with specific trade-reflecting surnames (Tailor vs. Smith). Two studies reported here were partially consistent with this genetic-social hypothesis, first proposed by Bäumler (1980). Study 1 (N = 224) indicated significantly higher self-rated physical aptitude for prototypically strength-related activities (professions, sports, hobbies) in a random sample of Smiths. The counterpart effect (higher aptitude for dexterity-related activities among Tailors) was directionally correct, but not significant, and Tailor-Smith differences in basic physique variables were not significant. Study 2 examined two large datasets (Austria/Germany combined, and UK: N = 7001 and 20532) of men’s national high-score lists for track-and-field events requiring different physiques. In both datasets, proportions of Smiths significantly increased from light-stature over medium-stature to heavy-stature sports categories. The predicted counterpart effect (decreasing prevalences of Tailors along these categories) was not supported. Related prior findings, implicit egotism as an alternative interpretation of the evidence, and directions for further inquiry are discussed in conclusion

Menstrual cycle phase does not predict political conservatism

Recent authors have reported a relationship between women's fertility status, as indexed by menstrual cycle phase, and conservatism in moral, social and political values. We conducted a survey to test for the existence of a relationship between menstrual cycle day and conservatism. 2213 women reporting regular menstrual cycles provided data about their political views. Of these women, 2208 provided information about their cycle date, 1260 provided additional evidence of reliability in self-reported cycle date, and of these, 750 also indicated an absence of hormonal disruptors such as recent hormonal contraception use, breastfeeding or pregnancy. Cycle day was used to estimate day-specific fertility rate (probability of conception); political conservatism was measured via direct self-report and via responses to the "Moral Foundations” questionnaire. We also recorded relationship status, which has been reported to interact with menstrual cycle phase in determining political preferences. We found no evidence of a relationship between estimated cyclical fertility changes and conservatism, and no evidence of an interaction between relationship status and cyclical fertility in determining political attitudes. Our findings were robust to multiple inclusion/exclusion criteria and to different methods of estimating fertility and measuring conservatism. In summary, the relationship between cycle-linked reproductive parameters and conservatism may be weaker or less reliable than previously thought

Comparison of two independent systematic reviews of trials of recombinant human bone morphogenetic protein-2 (rhBMP-2) : The Yale Open Data Access Medtronic Project

Background: It is uncertain whether the replication of systematic reviews, particularly those with the same objectives and resources, would employ similar methods and/or arrive at identical findings. We compared the results and conclusions of two concurrent systematic reviews undertaken by two independent research teams provided with the same objectives, resources, and individual participant-level data. Methods: Two centers in the USA and UK were each provided with participant-level data on 17 multi-site clinical trials of recombinant human bone morphogenetic protein-2 (rhBMP-2). The teams were blinded to each other's methods and findings until after publication. We conducted a retrospective structured comparison of the results of the two systematic reviews. The main outcome measures included (1) trial inclusion criteria; (2) statistical methods; (3) summary efficacy and risk estimates; and (4) conclusions. Results: The two research teams' meta-analyses inclusion criteria were broadly similar but differed slightly in trial inclusion and research methodology. They obtained similar results in summary estimates of most clinical outcomes and adverse events. Center A incorporated all trials into summary estimates of efficacy and harms, while Center B concentrated on analyses stratified by surgical approach. Center A found a statistically significant, but small, benefit whereas Center B reported no advantage. In the analysis of harms, neither showed an increased cancer risk at 48 months, although Center B reported a significant increase at 24 months. Conclusions reflected these differences in summary estimates of benefit balanced with small but potentially important risk of harm. Conclusions: Two independent groups given the same research objectives, data, resources, funding, and time produced broad general agreement but differed in several areas. These differences, the importance of which is debatable, indicate the value of the availability of data to allow for more than a single approach and a single interpretation of the data. Systematic review registration: PROSPERO CRD42012002040and CRD42012001907

Does publication bias inflate the apparent efficacy of psychological treatment for major depressive disorder? A systematic review and meta-analysis of US national institutes of health-funded trials

Background The efficacy of antidepressant medication has been shown empirically to be overestimated due to publication bias, but this has only been inferred statistically with regard to psychological treatment for depression. We assessed directly the extent of study publication bias in trials examining the efficacy of psychological treatment for depression. Methods and Findings We identified US National Institutes of Health grants awarded to fund randomized clinical trials comparing psychological treatment to control conditions or other treatments in patients diagnosed with major depressive disorder for the period 1972–2008, and we determined whether those grants led to publications. For studies that were not published, data were requested from investigators and included in the meta-analyses. Thirteen (23.6%) of the 55 funded grants that began trials did not result in publications, and two others never started. Among comparisons to control conditions, adding unpublished studies (Hedges’ g = 0.20; CI95% -0.11~0.51; k = 6) to published studies (g = 0.52; 0.37~0.68; k = 20) reduced the psychotherapy effect size point estimate (g = 0.39; 0.08~0.70) by 25%. Moreover, these findings may overestimate the "true" effect of psychological treatment for depression as outcome reporting bias could not be examined quantitatively. Conclusion The efficacy of psychological interventions for depression has been overestimated in the published literature, just as it has been for pharmacotherapy. Both are efficacious but not to the extent that the published literature would suggest. Funding agencies and journals should archive both original protocols and raw data from treatment trials to allow the detection and correction of outcome reporting bias. Clinicians, guidelines developers, and decision makers should be aware that the published literature overestimates the effects of the predominant treatments for depression

Extent of non-publication in cohorts of studies approved by research ethics committees or included in trial registries

BACKGROUND: The synthesis of published research in systematic reviews is essential when providing evidence to inform clinical and health policy decision-making. However, the validity of systematic reviews is threatened if journal publications represent a biased selection of all studies that have been conducted (dissemination bias). To investigate the extent of dissemination bias we conducted a systematic review that determined the proportion of studies published as peer-reviewed journal articles and investigated factors associated with full publication in cohorts of studies (i) approved by research ethics committees (RECs) or (ii) included in trial registries. METHODS AND FINDINGS: Four bibliographic databases were searched for methodological research projects (MRPs) without limitations for publication year, language or study location. The searches were supplemented by handsearching the references of included MRPs. We estimated the proportion of studies published using prediction intervals (PI) and a random effects meta-analysis. Pooled odds ratios (OR) were used to express associations between study characteristics and journal publication. Seventeen MRPs (23 publications) evaluated cohorts of studies approved by RECs; the proportion of published studies had a PI between 22% and 72% and the weighted pooled proportion when combining estimates would be 46.2% (95% CI 40.2%-52.4%, I2 = 94.4%). Twenty-two MRPs (22 publications) evaluated cohorts of studies included in trial registries; the PI of the proportion published ranged from 13% to 90% and the weighted pooled proportion would be 54.2% (95% CI 42.0%-65.9%, I2 = 98.9%). REC-approved studies with statistically significant results (compared with those without statistically significant results) were more likely to be published (pooled OR 2.8; 95% CI 2.2-3.5). Phase-III trials were also more likely to be published than phase II trials (pooled OR 2.0; 95% CI 1.6-2.5). The probability of publication within two years after study completion ranged from 7% to 30%. CONCLUSIONS: A substantial part of the studies approved by RECs or included in trial registries remains unpublished. Due to the large heterogeneity a prediction of the publication probability for a future study is very uncertain. Non-publication of research is not a random process, e.g., it is associated with the direction of study findings. Our findings suggest that the dissemination of research findings is biased

Quantifying Selective Reporting and the Proteus Phenomenon for Multiple Datasets with Similar Bias

Meta-analyses play an important role in synthesizing evidence from diverse studies and datasets that address similar questions. A major obstacle for meta-analyses arises from biases in reporting. In particular, it is speculated that findings which do not achieve formal statistical significance are less likely reported than statistically significant findings. Moreover, the patterns of bias can be complex and may also depend on the timing of the research results and their relationship with previously published work. In this paper, we present an approach that is specifically designed to analyze large-scale datasets on published results. Such datasets are currently emerging in diverse research fields, particularly in molecular medicine. We use our approach to investigate a dataset on Alzheimer's disease (AD) that covers 1167 results from case-control studies on 102 genetic markers. We observe that initial studies on a genetic marker tend to be substantially more biased than subsequent replications. The chances for initial, statistically non-significant results to be published are estimated to be about 44% (95% CI, 32% to 63%) relative to statistically significant results, while statistically non-significant replications have almost the same chance to be published as statistically significant replications (84%; 95% CI, 66% to 107%). Early replications tend to be biased against initial findings, an observation previously termed Proteus phenomenon: The chances for non-significant studies going in the same direction as the initial result are estimated to be lower than the chances for non-significant studies opposing the initial result (73%; 95% CI, 55% to 96%). Such dynamic patters in bias are difficult to capture by conventional methods, where typically simple publication bias is assumed to operate. Our approach captures and corrects for complex dynamic patterns of bias, and thereby helps generating conclusions from published results that are more robust against the presence of different coexisting types of selective reporting