Journal article
Integration of symptom ratings from multiple informants in ADHD diagnosis: a psychometric model with clinical utility
Psychological assessment, Vol.27(3), pp.1060-1071
09/2015
DOI: 10.1037/pas0000088
PMCID: PMC4549180
PMID: 25730162
Abstract
The Diagnostic and Statistical Manual of Mental Disorder-Fifth Edition explicitly requires that attention-deficit/hyperactivity disorder (ADHD) symptoms should be apparent across settings, taking into account reports from multiple informants. Yet, it provides no guidelines how information from different raters should be combined in ADHD diagnosis. We examined the validity of different approaches using structural equation modeling (SEM) for multiple-informant data. Participants were 725 children, 6 to 17 years old, and their primary caregivers and teachers, recruited from the community and completing a thorough research-based diagnostic assessment, including a clinician-administered diagnostic interview, parent and teacher standardized rating scales, and cognitive testing. A best-estimate ADHD diagnosis was generated by a diagnostic team. An SEM model demonstrated convergent validity among raters. We found relatively weak symptom-specific agreement among raters, suggesting that a general average scoring algorithm is preferable to symptom-specific scoring algorithms such as the "or" and "and" algorithms. Finally, to illustrate the validity of this approach, we show that averaging makes it possible to reduce the number of items from 18 items to 8 items without a significant decrease in validity. In conclusion, information from multiple raters increases the validity of ADHD diagnosis, and averaging appears to be the optimal way to integrate information from multiple raters.
Details
- Title: Subtitle
- Integration of symptom ratings from multiple informants in ADHD diagnosis: a psychometric model with clinical utility
- Creators
- Michelle M Martel - Psychology DepartmentUlrich Schimmack - Psychology Department, University of TorontoMolly Nikolas - Psychology Department, University of IowaJoel T Nigg - Psychiatry Department, Oregon Health and Sciences University
- Resource Type
- Journal article
- Publication Details
- Psychological assessment, Vol.27(3), pp.1060-1071
- DOI
- 10.1037/pas0000088
- PMID
- 25730162
- PMCID
- PMC4549180
- NLM abbreviation
- Psychol Assess
- ISSN
- 1040-3590
- eISSN
- 1939-134X
- Publisher
- United States
- Grant note
- R37 MH059105 / NIMH NIH HHS R01 MH070004 / NIMH NIH HHS R01-MH070004-01A2 / NIMH NIH HHS K12 DA 035150 / NIDA NIH HHS R01 MH099064 / NIMH NIH HHS K12 DA035150 / NIDA NIH HHS
- Language
- English
- Date published
- 09/2015
- Academic Unit
- Psychological and Brain Sciences; Injury Prevention Research Center
- Record Identifier
- 9984002581402771
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