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Sensitivity, specificity, and predictive power of the “Brief Risk-resilience Index for SCreening,” a brief pan-diagnostic web screen for emotional health

Few standardized tools are available for time-efficient screening of emotional health status across diagnostic categories, especially in primary care. We evaluated the 45-question Brief Risk-resilience Index for SCreening (BRISC) and the 15-question mini-BRISC in identifying poor emotional health an...

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Autores principales: Williams, Leanne M, Cooper, Nicholas J, Wisniewski, Stephen R, Gatt, Justine M, Koslow, Stephen H, Kulkarni, Jayashri, DeVarney, Savannah, Gordon, Evian, John Rush, Augustus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Blackwell Publishing Inc 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3489810/
https://www.ncbi.nlm.nih.gov/pubmed/23139903
http://dx.doi.org/10.1002/brb3.76
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author Williams, Leanne M
Cooper, Nicholas J
Wisniewski, Stephen R
Gatt, Justine M
Koslow, Stephen H
Kulkarni, Jayashri
DeVarney, Savannah
Gordon, Evian
John Rush, Augustus
author_facet Williams, Leanne M
Cooper, Nicholas J
Wisniewski, Stephen R
Gatt, Justine M
Koslow, Stephen H
Kulkarni, Jayashri
DeVarney, Savannah
Gordon, Evian
John Rush, Augustus
author_sort Williams, Leanne M
collection PubMed
description Few standardized tools are available for time-efficient screening of emotional health status across diagnostic categories, especially in primary care. We evaluated the 45-question Brief Risk-resilience Index for SCreening (BRISC) and the 15-question mini-BRISC in identifying poor emotional health and coping capacity across a range of diagnostic groups – compared with a detailed clinical assessment – in a large sample of adult outpatients. Participants 18–60 years of age (n = 1079) recruited from 12 medical research and clinical sites completed the computerized assessments. Three index scores were derived from the full BRISC and the mini-BRISC: one for risk (negativity–positivity bias) and two for coping (resilience and social capacity). Summed answers were converted to standardized z-scores. BRISC scores were compared with detailed health assessment and diagnostic interview (for current psychiatric, psychological, and neurological conditions) by clinicians at each site according to diagnostic criteria. Clinicians were blinded to BRISC scores. Clinical assessment stratified participants as having “clinical” (n = 435) or “healthy” (n = 644) diagnostic status. Receiver operating characteristic analyses showed that a z-score threshold of −1.57 on the full BRISC index of emotional health provided an optimal classification of “clinical” versus “healthy” status (sensitivity: 81.2%, specificity: 92.7%, positive predictive power: 80.2%, and negative predictive power: 93.1%). Comparable findings were revealed for the mini-BRISC. Negativity–positivity bias index scores contributed the most to prediction. The negativity–positivity index of emotional health was most sensitive to classifying major depressive disorder (100%), posttraumatic stress disorder (95.8%), and panic disorder (88.7%). The BRISC and mini-BRISC both offer a brief, clinically useful screen to identify individuals at risk of disorders characterized by poor emotion regulation, from those with good emotional health and coping.
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spelling pubmed-34898102012-11-08 Sensitivity, specificity, and predictive power of the “Brief Risk-resilience Index for SCreening,” a brief pan-diagnostic web screen for emotional health Williams, Leanne M Cooper, Nicholas J Wisniewski, Stephen R Gatt, Justine M Koslow, Stephen H Kulkarni, Jayashri DeVarney, Savannah Gordon, Evian John Rush, Augustus Brain Behav Original Research Few standardized tools are available for time-efficient screening of emotional health status across diagnostic categories, especially in primary care. We evaluated the 45-question Brief Risk-resilience Index for SCreening (BRISC) and the 15-question mini-BRISC in identifying poor emotional health and coping capacity across a range of diagnostic groups – compared with a detailed clinical assessment – in a large sample of adult outpatients. Participants 18–60 years of age (n = 1079) recruited from 12 medical research and clinical sites completed the computerized assessments. Three index scores were derived from the full BRISC and the mini-BRISC: one for risk (negativity–positivity bias) and two for coping (resilience and social capacity). Summed answers were converted to standardized z-scores. BRISC scores were compared with detailed health assessment and diagnostic interview (for current psychiatric, psychological, and neurological conditions) by clinicians at each site according to diagnostic criteria. Clinicians were blinded to BRISC scores. Clinical assessment stratified participants as having “clinical” (n = 435) or “healthy” (n = 644) diagnostic status. Receiver operating characteristic analyses showed that a z-score threshold of −1.57 on the full BRISC index of emotional health provided an optimal classification of “clinical” versus “healthy” status (sensitivity: 81.2%, specificity: 92.7%, positive predictive power: 80.2%, and negative predictive power: 93.1%). Comparable findings were revealed for the mini-BRISC. Negativity–positivity bias index scores contributed the most to prediction. The negativity–positivity index of emotional health was most sensitive to classifying major depressive disorder (100%), posttraumatic stress disorder (95.8%), and panic disorder (88.7%). The BRISC and mini-BRISC both offer a brief, clinically useful screen to identify individuals at risk of disorders characterized by poor emotion regulation, from those with good emotional health and coping. Blackwell Publishing Inc 2012-09 2012-07-26 /pmc/articles/PMC3489810/ /pubmed/23139903 http://dx.doi.org/10.1002/brb3.76 Text en Copyright © 2012 Wiley Periodicals, Inc. http://creativecommons.org/licenses/by/2.5/ Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation.
spellingShingle Original Research
Williams, Leanne M
Cooper, Nicholas J
Wisniewski, Stephen R
Gatt, Justine M
Koslow, Stephen H
Kulkarni, Jayashri
DeVarney, Savannah
Gordon, Evian
John Rush, Augustus
Sensitivity, specificity, and predictive power of the “Brief Risk-resilience Index for SCreening,” a brief pan-diagnostic web screen for emotional health
title Sensitivity, specificity, and predictive power of the “Brief Risk-resilience Index for SCreening,” a brief pan-diagnostic web screen for emotional health
title_full Sensitivity, specificity, and predictive power of the “Brief Risk-resilience Index for SCreening,” a brief pan-diagnostic web screen for emotional health
title_fullStr Sensitivity, specificity, and predictive power of the “Brief Risk-resilience Index for SCreening,” a brief pan-diagnostic web screen for emotional health
title_full_unstemmed Sensitivity, specificity, and predictive power of the “Brief Risk-resilience Index for SCreening,” a brief pan-diagnostic web screen for emotional health
title_short Sensitivity, specificity, and predictive power of the “Brief Risk-resilience Index for SCreening,” a brief pan-diagnostic web screen for emotional health
title_sort sensitivity, specificity, and predictive power of the “brief risk-resilience index for screening,” a brief pan-diagnostic web screen for emotional health
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3489810/
https://www.ncbi.nlm.nih.gov/pubmed/23139903
http://dx.doi.org/10.1002/brb3.76
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