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 ORIGINAL ARTICLE
Year : 2020  |  Volume : 68  |  Issue : 2  |  Page : 352--357

The Development and Validation of DSM 5-Based AIIMS-Modified INDT ADHD Tool for Diagnosis of ADHD: A Diagnostic Test Evaluation Study


1 Child Neurology Division, Department of Pediatrics, All India Institute of Medical Sciences, Delhi, India
2 The INCLEN Trust International, 2nd Floor, F-1/5, Okhla Industrial Area, Phase-I, New Delhi, India
3 Department of Biostatistics, All India Institute of Medical Sciences, Delhi, India
4 Department of Psychiatry, All India Institute of Medical Sciences, Delhi, India
5 Department of Pediatrics, All India Institute of Medical Sciences, Delhi, India

Correspondence Address:
Dr. Sheffali Gulati
Professor and Chief of Child Neurology Division, Department of Pediatrics, All India Institute of Medical Sciences, Delhi - 110 029
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0028-3886.280638

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Background: The current study was planned at a tertiary centre in northern India to develop and validate a Diagnostic and Statistical Manual-5 (DSM-5)-based diagnostic tool and design a severity score for attention deficit hyperactivity disorder (ADHD) in children aged 6–18 years. An existing DSM-IV-based tool, INDT (International Clinical Epidemiology Network [INCLEN] diagnostic tool) for ADHD has been modified and named All India Institute of Medical Sciences (AIIMS)-modified INDT ADHD tool. Method: The first phase was development of the tool and the second phase was validation of the same against the gold standard of diagnosis by the DSM-5. A severity score was developed for ADHD in concordance with the Conners rating scale. Results: The tool was validated in 66 children with a sensitivity and specificity of 100 per cent and 90 per cent, respectively. A cut-off score of 12 was decided for labelling severity of ADHD, which corresponded to 63 in the Conners rating scale. Conclusion: This diagnostic tool for ADHD based on DSM-5 has acceptable psychometric properties. The severity score will be useful for prognostication, monitoring treatment response, and designing intervention trials.






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