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"One Health" or Three? Publication Silos Among the One Health Disciplines.

ABSTRACT: The One Health initiative is a global effort fostering interdisciplinary collaborations to address challenges in human, animal, and environmental health. While One Health has received considerable press, its benefits remain unclear because its effects have not been quantitatively described. We systematically surveyed the published literature and used social network analysis to measure interdisciplinarity in One Health studies constructing dynamic pathogen transmission models. The number of publications fulfilling our search criteria increased by 14.6% per year, which is faster than growth rates for life sciences as a whole and for most biology subdisciplines. Surveyed publications clustered into three communities: one used by ecologists, one used by veterinarians, and a third diverse-authorship community used by population biologists, mathematicians, epidemiologists, and experts in human health. Overlap between these communities increased through time in terms of author number, diversity of co-author affiliations, and diversity of citations. However, communities continue to differ in the systems studied, questions asked, and methods employed. While the infectious disease research community has made significant progress toward integrating its participating disciplines, some segregation--especially along the veterinary/ecological research interface--remains.

SUBMITTER: Manlove KR

PROVIDER: S-EPMC4839662 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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"One Health" or Three? Publication Silos Among the One Health Disciplines.

Manlove Kezia R KR Walker Josephine G JG Craft Meggan E ME Huyvaert Kathryn P KP Joseph Maxwell B MB Miller Ryan S RS Nol Pauline P Patyk Kelly A KA O'Brien Daniel D Walsh Daniel P DP Cross Paul C PC

PLoS biology 20160421 4

The One Health initiative is a global effort fostering interdisciplinary collaborations to address challenges in human, animal, and environmental health. While One Health has received considerable press, its benefits remain unclear because its effects have not been quantitatively described. We systematically surveyed the published literature and used social network analysis to measure interdisciplinarity in One Health studies constructing dynamic pathogen transmission models. The number of publi ...[more]

PMID: 27100532

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Project description:Selective publication and reporting in individual papers compromise the scientific record, but are meta-analyses as compromised as their constituent studies? We systematically sampled 63 meta-analyses (each comprising at least 40 studies) in PLoS One, top medical journals, top psychology journals, and Metalab, an online, open-data database of developmental psychology meta-analyses. We empirically estimated publication bias in each, including only the peer-reviewed studies. Across all meta-analyses, we estimated that "statistically significant" results in the expected direction were only 1.17 times more likely to be published than "nonsignificant" results or those in the unexpected direction (95% CI: [0.93, 1.47]), with a confidence interval substantially overlapping the null. Comparable estimates were 0.83 for meta-analyses in PLoS One, 1.02 for top medical journals, 1.54 for top psychology journals, and 4.70 for Metalab. The severity of publication bias did differ across individual meta-analyses; in a small minority (10%; 95% CI: [2%, 21%]), publication bias appeared to favor "significant" results in the expected direction by more than threefold. We estimated that for 89% of meta-analyses, the amount of publication bias that would be required to attenuate the point estimate to the null exceeded the amount of publication bias estimated to be actually present in the vast majority of meta-analyses from the relevant scientific discipline (exceeding the 95th percentile of publication bias). Study-level measures ("statistical significance" with a point estimate in the expected direction and point estimate size) did not indicate more publication bias in higher-tier versus lower-tier journals, nor in the earliest studies published on a topic versus later studies. Overall, we conclude that the mere act of performing a meta-analysis with a large number of studies (at least 40) and that includes non-headline results may largely mitigate publication bias in meta-analyses, suggesting optimism about the validity of meta-analytic results.

Project description:ContextOver the past three decades, industry sponsored research expanded in the United States. Financial incentives can lead to potential conflicts of interest (COI) resulting in underreporting of negative study results.ObjectiveWe hypothesized that over the three decades, there would be an increase in: a) reporting of conflict of interest and source of funding; b) percentage of randomized control trials c) number of patients per study and d) industry funding.Data sources and study selectionOriginal articles published in three calendar years (1988, 1998, and 2008) in The Lancet, New England Journal of Medicine and Journal of American Medical Association were collected.Data extractionStudies were reviewed and investigational design categorized as prospective and retrospective clinical trials. Prospective trials were categorized into randomized or non-randomized and single-center or multi-center trials. Retrospective trials were categorized as registries, meta-analyses and other studies, mostly comprising of case reports or series. Study outcomes were categorized as positive or negative depending on whether the pre-specified hypothesis was met. Financial disclosures were researched for financial relationships and profit status, and accordingly categorized as government, non-profit or industry sponsored. Studies were assessed for reporting COI.Results1,671 original articles were included in this analysis. Total number of published studies decreased by 17% from 1988 to 2008. Over 20 year period, the proportion of prospective randomized trials increased from 22 to 46% (p < 0.0001); whereas the proportion of prospective non-randomized trials decreased from 59% to 27% (p < 0.001). There was an increase in the percentage of prospective randomized multi-center trials from 11% to 41% (p < 0.001). Conversely, there was a reduction in non-randomized single-center trials from 47% to 10% (p < 0.001). Proportion of government funded studies remained constant, whereas industry funded studies more than doubled (17% to 40%; p < 0.0001). The number of studies with negative results more than doubled (10% to 22%; p<0.0001). While lack of funding disclosure decreased from 35% to 7%, COI reporting increased from 2% to 84% (p < 0.0001).ConclusionImproved reporting of COI, clarity in financial sponsorship, increased publication of negative results in the setting of larger and better designed clinical trials represents a positive step forward in the scientific publications, despite the higher percentage of industry funded studies.

Project description:BACKGROUND:While the application of learning analytics in tertiary education has received increasing attention in recent years, a much smaller number have explored its use in health care-related educational studies. OBJECTIVE:This systematic review aims to examine the use of e-learning analytics data in health care studies with regards to how the analytics is reported and if there is a relationship between e-learning analytics and learning outcomes. METHODS:We performed comprehensive searches of papers from 4 electronic databases (MEDLINE, EBSCOhost, Web of Science, and ERIC) to identify relevant papers. Qualitative studies were excluded from this review. Papers were screened by 2 independent reviewers. We selected qualified studies for further investigation. RESULTS:A total of 537 papers were screened, and 19 papers were identified. With regards to analytics undertaken, 11 studies reported the number of connections and time spent on e-learning. Learning outcome measures were defined by summative final assessment marks or grades. In addition, significant statistical results of the relationships between e-learning usage and learning outcomes were reported in 12 of the identified papers. In general, students who engaged more in e-learning resources would get better academic attainments. However, 2 papers reported otherwise with better performing students consuming less e-learning videos. A total of 14 papers utilized satisfaction questionnaires for students, and all were positive in their attitude toward e-learning. Furthermore, 6 of 19 papers reported descriptive statistics only, with no statistical analysis. CONCLUSIONS:The nature of e-learning activities reported in this review was varied and not detailed well. In addition, there appeared to be inadequate reporting of learning analytics data observed in over half of the selected papers with regards to definitions and lack of detailed information of what the analytic was recording. Although learning analytics data capture is popular, a lack of detail is apparent with regards to the capturing of meaningful and comparable data. In particular, most analytics record access to a management system or particular e-learning materials, which may not necessarily detail meaningful learning time or interaction. Hence, learning analytics data should be designed to record the time spent on learning and focus on key learning activities. Finally, recommendations are made for future studies.

Dataset Information

"One Health" or Three? Publication Silos Among the One Health Disciplines.

Publications

"One Health" or Three? Publication Silos Among the One Health Disciplines.

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