Validation of the structured interview section of the penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT GOASSESS)
Copyright © 2024 Elsevier B.V. All rights reserved..
Large-scale studies and burdened clinical settings require precise, efficient measures that assess multiple domains of psychopathology. Computerized adaptive tests (CATs) can reduce administration time without compromising data quality. We examined feasibility and validity of an adaptive psychopathology measure, GOASSESS, in a clinical community-based sample (N = 315; ages 18-35) comprising three groups: healthy controls, psychosis, mood/anxiety disorders. Assessment duration was compared between the Full and CAT GOASSESS. External validity was tested by comparing how the CAT and Full versions related to demographic variables, study group, and socioeconomic status. The relationships between scale scores and criteria were statistically compared within a mixed-model framework to account for dependency between relationships. Convergent validity was assessed by comparing scores of the CAT and the Full GOASSESS using Pearson correlations. The CAT GOASSESS reduced interview duration by more than 90 % across study groups and preserved relationships to external criteria and demographic variables as the Full GOASSESS. All CAT GOASSESS scales could replace those of the Full instrument. Overall, the CAT GOASSESS showed acceptable psychometric properties and demonstrated feasibility by markedly reducing assessment time compared to the Full GOASSESS. The adaptive version could be used in large-scale studies or clinical settings for intake screening.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:335 |
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| Enthalten in: |
Psychiatry research - 335(2024) vom: 09. Apr., Seite 115862 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Zoupou, Eirini [VerfasserIn] |
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| Links: |
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| Themen: |
Assessment instrument validation |
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| Anmerkungen: |
Date Completed 15.04.2024 Date Revised 25.04.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.psychres.2024.115862 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM370440196 |
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| 520 | |a Large-scale studies and burdened clinical settings require precise, efficient measures that assess multiple domains of psychopathology. Computerized adaptive tests (CATs) can reduce administration time without compromising data quality. We examined feasibility and validity of an adaptive psychopathology measure, GOASSESS, in a clinical community-based sample (N = 315; ages 18-35) comprising three groups: healthy controls, psychosis, mood/anxiety disorders. Assessment duration was compared between the Full and CAT GOASSESS. External validity was tested by comparing how the CAT and Full versions related to demographic variables, study group, and socioeconomic status. The relationships between scale scores and criteria were statistically compared within a mixed-model framework to account for dependency between relationships. Convergent validity was assessed by comparing scores of the CAT and the Full GOASSESS using Pearson correlations. The CAT GOASSESS reduced interview duration by more than 90 % across study groups and preserved relationships to external criteria and demographic variables as the Full GOASSESS. All CAT GOASSESS scales could replace those of the Full instrument. Overall, the CAT GOASSESS showed acceptable psychometric properties and demonstrated feasibility by markedly reducing assessment time compared to the Full GOASSESS. The adaptive version could be used in large-scale studies or clinical settings for intake screening | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Assessment instrument validation | |
| 650 | 4 | |a Clinical assessment | |
| 650 | 4 | |a Computerized psychiatric assessments | |
| 650 | 4 | |a Mood and cognition | |
| 650 | 4 | |a Neurocognition | |
| 650 | 4 | |a Psychiatric comorbidity | |
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| 650 | 4 | |a Psychosis | |
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| 700 | 1 | |a Kennedy, Kelly P |e verfasserin |4 aut | |
| 700 | 1 | |a Calkins, Monica E |e verfasserin |4 aut | |
| 700 | 1 | |a Gorgone, Alesandra |e verfasserin |4 aut | |
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| 700 | 1 | |a Ruparel, Kosha |e verfasserin |4 aut | |
| 700 | 1 | |a Daryoush, Tarlan |e verfasserin |4 aut | |
| 700 | 1 | |a Okoyeh, Paul |e verfasserin |4 aut | |
| 700 | 1 | |a Savino, Andrew |e verfasserin |4 aut | |
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| 700 | 1 | |a Gur, Raquel E |e verfasserin |4 aut | |
| 700 | 1 | |a Gur, Ruben C |e verfasserin |4 aut | |
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