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Using Online Screening in the General Population to Detect Participants at Clinical High-Risk for Psychosis

INTRODUCTION: Identification of participants at clinical high-risk (CHR) for the development of psychosis is an important objective of current preventive efforts in mental health research. However, the utility of using web-based screening approaches to detect CHR participants at the population level...

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Autores principales: McDonald, Mhairi, Christoforidou, Eleni, Van Rijsbergen, Nicola, Gajwani, Ruchika, Gross, Joachim, Gumley, Andrew I, Lawrie, Stephen M, Schwannauer, Matthias, Schultze-Lutter, Frauke, Uhlhaas, Peter J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6483579/
https://www.ncbi.nlm.nih.gov/pubmed/29889271
http://dx.doi.org/10.1093/schbul/sby069
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author McDonald, Mhairi
Christoforidou, Eleni
Van Rijsbergen, Nicola
Gajwani, Ruchika
Gross, Joachim
Gumley, Andrew I
Lawrie, Stephen M
Schwannauer, Matthias
Schultze-Lutter, Frauke
Uhlhaas, Peter J
author_facet McDonald, Mhairi
Christoforidou, Eleni
Van Rijsbergen, Nicola
Gajwani, Ruchika
Gross, Joachim
Gumley, Andrew I
Lawrie, Stephen M
Schwannauer, Matthias
Schultze-Lutter, Frauke
Uhlhaas, Peter J
author_sort McDonald, Mhairi
collection PubMed
description INTRODUCTION: Identification of participants at clinical high-risk (CHR) for the development of psychosis is an important objective of current preventive efforts in mental health research. However, the utility of using web-based screening approaches to detect CHR participants at the population level has not been investigated. METHODS: We tested a web-based screening approach to identify CHR individuals. Potential participants were invited to a website via e-mail invitations, flyers, and invitation letters involving both the general population and mental health services. Two thousand two hundred seventy-nine participants completed the 16-item version of the prodromal questionnaire (PQ-16) and a 9-item questionnaire of perceptual and cognitive aberrations (PCA) for the assessment of basic symptoms (BS) online. 52.3% of participants met a priori cut-off criteria for the PQ and 73.6% for PCA items online. One thousand seven hundred eighty-seven participants were invited for a clinical interview and n = 356 interviews were conducted (response rate: 19.9%) using the Comprehensive Assessment of At-Risk Mental State (CAARMS) and the Schizophrenia Proneness Interview, Adult Version (SPI-A). n = 101 CHR participants and n = 8 first-episode psychosis (FEP) were detected. ROC curve analysis revealed good to moderate sensitivity and specificity for predicting CHR status based on online results for both UHR and BS criteria (sensitivity/specificity: PQ-16 = 82%/46%; PCA = 94%/12%). Selection of a subset of 10 items from both PQ-16 and PCA lead to an improved of specificity of 57% while only marginally affecting sensitivity (81%). CHR participants were characterized by similar levels of functioning and neurocognitive deficits as clinically identified CHR groups. CONCLUSION: These data provide evidence for the possibility to identify CHR participants through population-based web screening. This could be an important strategy for early intervention and diagnosis of psychotic disorders.
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spelling pubmed-64835792019-04-30 Using Online Screening in the General Population to Detect Participants at Clinical High-Risk for Psychosis McDonald, Mhairi Christoforidou, Eleni Van Rijsbergen, Nicola Gajwani, Ruchika Gross, Joachim Gumley, Andrew I Lawrie, Stephen M Schwannauer, Matthias Schultze-Lutter, Frauke Uhlhaas, Peter J Schizophr Bull Regular Articles INTRODUCTION: Identification of participants at clinical high-risk (CHR) for the development of psychosis is an important objective of current preventive efforts in mental health research. However, the utility of using web-based screening approaches to detect CHR participants at the population level has not been investigated. METHODS: We tested a web-based screening approach to identify CHR individuals. Potential participants were invited to a website via e-mail invitations, flyers, and invitation letters involving both the general population and mental health services. Two thousand two hundred seventy-nine participants completed the 16-item version of the prodromal questionnaire (PQ-16) and a 9-item questionnaire of perceptual and cognitive aberrations (PCA) for the assessment of basic symptoms (BS) online. 52.3% of participants met a priori cut-off criteria for the PQ and 73.6% for PCA items online. One thousand seven hundred eighty-seven participants were invited for a clinical interview and n = 356 interviews were conducted (response rate: 19.9%) using the Comprehensive Assessment of At-Risk Mental State (CAARMS) and the Schizophrenia Proneness Interview, Adult Version (SPI-A). n = 101 CHR participants and n = 8 first-episode psychosis (FEP) were detected. ROC curve analysis revealed good to moderate sensitivity and specificity for predicting CHR status based on online results for both UHR and BS criteria (sensitivity/specificity: PQ-16 = 82%/46%; PCA = 94%/12%). Selection of a subset of 10 items from both PQ-16 and PCA lead to an improved of specificity of 57% while only marginally affecting sensitivity (81%). CHR participants were characterized by similar levels of functioning and neurocognitive deficits as clinically identified CHR groups. CONCLUSION: These data provide evidence for the possibility to identify CHR participants through population-based web screening. This could be an important strategy for early intervention and diagnosis of psychotic disorders. Oxford University Press 2019-04 2018-06-08 /pmc/articles/PMC6483579/ /pubmed/29889271 http://dx.doi.org/10.1093/schbul/sby069 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Regular Articles
McDonald, Mhairi
Christoforidou, Eleni
Van Rijsbergen, Nicola
Gajwani, Ruchika
Gross, Joachim
Gumley, Andrew I
Lawrie, Stephen M
Schwannauer, Matthias
Schultze-Lutter, Frauke
Uhlhaas, Peter J
Using Online Screening in the General Population to Detect Participants at Clinical High-Risk for Psychosis
title Using Online Screening in the General Population to Detect Participants at Clinical High-Risk for Psychosis
title_full Using Online Screening in the General Population to Detect Participants at Clinical High-Risk for Psychosis
title_fullStr Using Online Screening in the General Population to Detect Participants at Clinical High-Risk for Psychosis
title_full_unstemmed Using Online Screening in the General Population to Detect Participants at Clinical High-Risk for Psychosis
title_short Using Online Screening in the General Population to Detect Participants at Clinical High-Risk for Psychosis
title_sort using online screening in the general population to detect participants at clinical high-risk for psychosis
topic Regular Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6483579/
https://www.ncbi.nlm.nih.gov/pubmed/29889271
http://dx.doi.org/10.1093/schbul/sby069
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