Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 600-609 |
| Number of pages | 10 |
| Journal | Schizophrenia Bulletin |
| Volume | 45 |
| Issue number | 3 |
| Early online date | 8 Jun 2018 |
| DOIs | |
| Publication status | Published - 13 May 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Basic symptoms
- Clinical high-risk
- Early intervention
- Psychosis
- Web screening
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