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Enhancing Psychosis-Spectrum Nosology Through an International Data Sharing Initiative

Overview of attention for article published in Schizophrenia Bulletin, May 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
2 news outlets
blogs
1 blog
twitter
12 X users

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73 Mendeley
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Article details
Title
Enhancing Psychosis-Spectrum Nosology Through an International Data Sharing Initiative
Published in
Schizophrenia Bulletin, May 2018
DOI 10.1093/schbul/sby059
Pubmed ID
Authors
Abstract

The latent structure of schizotypy and psychosis-spectrum symptoms remains poorly understood. Furthermore, molecular genetic substrates are poorly defined, largely due to the substantial resources required to collect rich phenotypic data across diverse populations. Sample sizes of phenotypic studies are often insufficient for advanced structural equation modeling approaches. In the last 50 years, efforts in both psychiatry and psychological science have moved toward (1) a dimensional model of psychopathology (eg, the current Hierarchical Taxonomy of Psychopathology [HiTOP] initiative), (2) an integration of methods and measures across traits and units of analysis (eg, the RDoC initiative), and (3) powerful, impactful study designs maximizing sample size to detect subtle genomic variation relating to complex traits (the Psychiatric Genomics Consortium [PGC]). These movements are important to the future study of the psychosis spectrum, and to resolving heterogeneity with respect to instrument and population. The International Consortium of Schizotypy Research is composed of over 40 laboratories in 12 countries, and to date, members have compiled a body of schizotypy- and psychosis-related phenotype data from more than 30000 individuals. It has become apparent that compiling data into a protected, relational database and crowdsourcing analytic and data science expertise will result in significant enhancement of current research on the structure and biological substrates of the psychosis spectrum. The authors present a data-sharing infrastructure similar to that of the PGC, and a resource-sharing infrastructure similar to that of HiTOP. This report details the rationale and benefits of the phenotypic data collective and presents an open invitation for participation.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 73 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 9 12%
Professor 8 11%
Researcher 7 10%
Other 5 7%
Student > Doctoral Student 5 7%
Other 18 25%
Unknown 21 29%
Readers by discipline
Readers by discipline Count As %
Psychology 21 29%
Medicine and Dentistry 6 8%
Neuroscience 3 4%
Biochemistry, Genetics and Molecular Biology 2 3%
Nursing and Health Professions 2 3%
Other 12 16%
Unknown 27 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 32. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 June 2026.
All research outputs
#1,585,972
of 34,518,147 outputs
Outputs from Schizophrenia Bulletin
#306
of 3,809 outputs
Outputs of similar age
#25,745
of 373,735 outputs
Outputs of similar age from Schizophrenia Bulletin
#7
of 144 outputs
Altmetric has tracked 34,518,147 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,809 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.0. This one has done particularly well, scoring higher than 91% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 373,735 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 144 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.