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Never mind the length, feel the quality: the impact of long-term epidemiological data sets on theory, application and policy.

ABSTRACT: Infectious diseases have been a prime testing ground for ecological theory. However, the ecological perspective is increasingly recognized as essential in epidemiology. Long-term, spatially resolved reliable data on disease incidence and the ability to test them using mechanistic models have been critical in this cross-fertilization. Here, we review some of the key intellectual developments in epidemiology facilitated by long-term data. We identify research frontiers at the interface of ecology and epidemiology and their associated data needs.

SUBMITTER: Rohani P

PROVIDER: S-EPMC2949056 | biostudies-other | 2010 Oct

REPOSITORIES: biostudies-other

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Never mind the length, feel the quality: the impact of long-term epidemiological data sets on theory, application and policy.

Rohani Pejman P King Aaron A AA

Trends in ecology & evolution 20101001 10

Infectious diseases have been a prime testing ground for ecological theory. However, the ecological perspective is increasingly recognized as essential in epidemiology. Long-term, spatially resolved reliable data on disease incidence and the ability to test them using mechanistic models have been critical in this cross-fertilization. Here, we review some of the key intellectual developments in epidemiology facilitated by long-term data. We identify research frontiers at the interface of ecology ...[more]

PMID: 20800928

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Project description:BACKGROUND: Sharing of epidemiological and clinical data sets among researchers is poor at best, in detriment of science and community at large. The purpose of this paper is therefore to (1) describe a novel Web application designed to share information on study data sets focusing on epidemiological clinical research in a collaborative environment and (2) create a policy model placing this collaborative environment into the current scientific social context. METHODOLOGY: The Database of Databases application was developed based on feedback from epidemiologists and clinical researchers requiring a Web-based platform that would allow for sharing of information about epidemiological and clinical study data sets in a collaborative environment. This platform should ensure that researchers can modify the information. A Model-based predictions of number of publications and funding resulting from combinations of different policy implementation strategies (for metadata and data sharing) were generated using System Dynamics modeling. PRINCIPAL FINDINGS: The application allows researchers to easily upload information about clinical study data sets, which is searchable and modifiable by other users in a wiki environment. All modifications are filtered by the database principal investigator in order to maintain quality control. The application has been extensively tested and currently contains 130 clinical study data sets from the United States, Australia, China and Singapore. Model results indicated that any policy implementation would be better than the current strategy, that metadata sharing is better than data-sharing, and that combined policies achieve the best results in terms of publications. CONCLUSIONS: Based on our empirical observations and resulting model, the social network environment surrounding the application can assist epidemiologists and clinical researchers contribute and search for metadata in a collaborative environment, thus potentially facilitating collaboration efforts among research communities distributed around the globe.

Project description:Background: Several meta-analyses highlight pronounced problems in general Theory of Mind (ToM), the ability to infer other persons' mental states, in patients with psychosis in comparison to non-clinical controls. In addition, first studies suggest associations between Hyper-ToM, an exaggerated inference of mental states to others, and delusions. Research on different ToM subtypes (Cognitive ToM, Affective ToM, and Hyper-ToM) and symptom clusters of psychosis (positive, negative, and disorganized symptoms) have gathered conflicting findings. Thus, the present study examined group differences between patients with psychosis and non-clinical controls concerning Cognitive ToM/Affective ToM and Hyper-ToM. Further, the association between ToM subtypes and symptom clusters (positive, negative, and disorganized symptoms) were examined. Methods: Patients with psychotic disorders (n = 64, 1/3 with present delusions indicated by a minimum score of four in the PANSS P1 item) and non-clinical controls (n = 21) were examined with assessments of Cognitive ToM and Affective ToM abilities and Hyper-ToM errors using the Frith-Happé animations. Psychopathology was assessed using the Positive and Negative Syndrome Scale. Results: Patients with psychosis presented more pronounced problems in Cognitive and Affective ToM in comparison to non-clinical controls, whereas there were no group differences with regard to Hyper-ToM errors. Furthermore, deficits in Cognitive ToM were associated with general delusions, whereas problems in Affective ToM were associated with negative and disorganized symptoms. In addition, there was no association between Hyper-ToM errors and any symptoms when controlling for years of education. Conclusions: Our findings suggest that deficits in ToM subtypes might not be directly related to delusions and positive symptoms and are in line with more recently developed cognitive models of delusions. In addition, our results support the well-established finding of associations between ToM alterations and negative or disorganized symptoms. Our results shed light on the role of different dimensions of ToM in specific symptoms of psychosis.

Dataset Information

Never mind the length, feel the quality: the impact of long-term epidemiological data sets on theory, application and policy.

Publications

Never mind the length, feel the quality: the impact of long-term epidemiological data sets on theory, application and policy.

Similar Datasets

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