TY - JOUR
T1 - Using online screening in the general population to detect participants at clinical high-risk for psychosis
AU - McDonald, Mhairi
AU - Christoforidou, Eleni
AU - Van Rijsbergen, Nicola
AU - Gajwani, Ruchika
AU - Gross, Joachim
AU - Gumley, Andrew I.
AU - Lawrie, Stephen M.
AU - Schwannauer, Matthias
AU - Schultze-Lutter, Frauke
AU - Uhlhaas, Peter J.
N1 - © The Author(s) 2018. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.
PY - 2019/5/13
Y1 - 2019/5/13
N2 - 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.
AB - 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.
KW - Basic symptoms
KW - Clinical high-risk
KW - Early intervention
KW - Psychosis
KW - Web screening
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UR - http://www.mendeley.com/research/using-online-screening-general-population-detect-participants-clinical-highrisk-psychosis
U2 - 10.1093/schbul/sby069
DO - 10.1093/schbul/sby069
M3 - Article (journal)
C2 - 29889271
AN - SCOPUS:85072057749
SN - 0586-7614
VL - 45
SP - 600
EP - 609
JO - Schizophrenia Bulletin
JF - Schizophrenia Bulletin
IS - 3
ER -