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, 74 (5), 520-527

The World Health Organization Adult Attention-Deficit/Hyperactivity Disorder Self-Report Screening Scale for DSM-5

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The World Health Organization Adult Attention-Deficit/Hyperactivity Disorder Self-Report Screening Scale for DSM-5

Berk Ustun et al. JAMA Psychiatry.

Erratum in

  • Error in Results.
    JAMA Psychiatry. 2017 Dec 1;74(12):1279. doi: 10.1001/jamapsychiatry.2017.3375. JAMA Psychiatry. 2017. PMID: 29071343 No abstract available.
  • Error in Table 1 Note and Results.
    JAMA Psychiatry. 2019 Oct 2;76(11):1213. doi: 10.1001/jamapsychiatry.2019.3111. Online ahead of print. JAMA Psychiatry. 2019. PMID: 31577334 Free PMC article. No abstract available.

Abstract

Importance: Recognition that adult attention-deficit/hyperactivity disorder (ADHD) is common, seriously impairing, and usually undiagnosed has led to the development of adult ADHD screening scales for use in community, workplace, and primary care settings. However, these scales are all calibrated to DSM-IV criteria, which are narrower than the recently developed DSM-5 criteria.

Objectives: To update for DSM-5 criteria and improve the operating characteristics of the widely used World Health Organization Adult ADHD Self-Report Scale (ASRS) for screening.

Design, setting, and participants: Probability subsamples of participants in 2 general population surveys (2001-2003 household survey [n = 119] and 2004-2005 managed care subscriber survey [n = 218]) who completed the full 29-question self-report ASRS, with both subsamples over-sampling ASRS-screened positives, were blindly administered a semistructured research diagnostic interview for DSM-5 adult ADHD. In 2016, the Risk-Calibrated Supersparse Linear Integer Model, a novel machine-learning algorithm designed to create screening scales with optimal integer weights and limited numbers of screening questions, was applied to the pooled data to create a DSM-5 version of the ASRS screening scale. The accuracy of the new scale was then confirmed in an independent 2011-2012 clinical sample of patients seeking evaluation at the New York University Langone Medical Center Adult ADHD Program (NYU Langone) and 2015-2016 primary care controls (n = 300). Data analysis was conducted from April 4, 2016, to September 22, 2016.

Main outcomes and measures: The sensitivity, specificity, area under the curve (AUC), and positive predictive value (PPV) of the revised ASRS.

Results: Of the total 637 participants, 44 (37.0%) household survey respondents, 51 (23.4%) managed care respondents, and 173 (57.7%) NYU Langone respondents met DSM-5 criteria for adult ADHD in the semistructured diagnostic interview. Of the respondents who met DSM-5 criteria for adult ADHD, 123 were male (45.9%); mean (SD) age was 33.1 (11.4) years. A 6-question screening scale was found to be optimal in distinguishing cases from noncases in the first 2 samples. Operating characteristics were excellent at the diagnostic threshold in the weighted (to the 8.2% DSM-5/Adult ADHD Clinical Diagnostic Scale population prevalence) data (sensitivity, 91.4%; specificity, 96.0%; AUC, 0.94; PPV, 67.3%). Operating characteristics were similar despite a much higher prevalence (57.7%) when the scale was applied to the NYU Langone clinical sample (sensitivity, 91.9%; specificity, 74.0%; AUC, 0.83; PPV, 82.8%).

Conclusions and relevance: The new ADHD screening scale is short, easily scored, detects the vast majority of general population cases at a threshold that also has high specificity and PPV, and could be used as a screening tool in specialty treatment settings.

Conflict of interest statement

Conflict of Interest Disclosures: Dr Adler has received grant and research support from Sunovion Pharmaceuticals, Purdue Pharmaceuticals, Enzymotec, Shire Pharmaceuticals, and Lundbeck; served as a consultant for Enzymotec, Alcobra Pharmaceuticals, Rhodes Pharmaceuticals, Shire Pharmaceuticals, National Football League, and Major League Baseball; and has received royalty payments (as inventor) from New York University for license of adult attention-deficit/hyperactivity disorder (ADHD) scales and training materials since 2004. With his institution, Dr Faraone has US patent US20130217707 A1 for the use of sodium-hydrogen exchange inhibitors in the treatment of ADHD and has received income, potential income, travel expenses, and/or research support from Rhodes Pharmaceuticals, Arbor Pharmaceuticals, Pfizer, Ironshore, Shire, Akili Interactive Labs, CogCubed, Alcobra, VAYA Pharma, NeuroLifeSciences, and NACE. Dr Spencer receives research support from or is a consultant for Alcobra Pharma, Avekshan, Heptares Therapeutics, Impax Laboratories, Ironshore, Lundbeck, Shire Pharmaceuticals, Sunovion Pharmaceuticals, VAYA Pharma, the US Food and Drug Administration, and the US Department of Defense; serves on an advisory board for Alcobra Pharmaceuticals; receives research support from Royalties and Licensing fees on copyrighted ADHD scales through Massachusetts General Hospital (MGH) Corporate Sponsored Research and Licensing; and has a US Patent Application pending (provisional number 61/233,686), through MGH corporate licensing on a method to prevent stimulant abuse; consultant fees are paid to the MGH Clinical Trials Network and not directly to Dr Spencer. Dr Kessler has received support for his epidemiologic studies from Sanofi; was a consultant for Johnson & Johnson Wellness and Prevention, Shire Pharmaceuticals, and Takeda Pharmaceuticals; served on an advisory board for the Johnson & Johnson Services Inc Lake Nona Life Project; and is a co-owner of DataStat, Inc, a market research firm that carries out healthcare research. No other conflicts were reported.

Figures

Figure 1.
Figure 1.. Ten-fold Cross-Validated (10-CV) Area Under the Curve (AUC) vs the Number of Questions in the Screening Scale
Pooled National Comorbidity Survey Replication and managed care samples (n = 337). The reported range represents the highest and lowest values of mean AUC across the 10 separate folds for 8 questions.
Figure 2.
Figure 2.. Ten-fold Cross-Validated (10-CV) Mean Calibration Accuracy vs the Number of Questions in the Screening Scale
Pooled National Comorbidity Survey Replication and managed care samples (n = 337). The reported range represents the highest and lowest values of mean calibration accuracy across the 10 separate folds for 8 questions.

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