» Articles » PMID: 39026526

Psychometric Properties of the Self-report Version of the Strengths and Weaknesses of ADHD Symptoms and Normal Behavior Scale in a Sample of Hungarian Adolescents and Young Adults

Overview
Specialty Psychiatry
Date 2024 Jul 19
PMID 39026526
Authors
Affiliations
Soon will be listed here.
Abstract

The Strengths and Weaknesses of ADHD Symptoms and Normal Behaviour Scale (SWAN) measures the full spectrum of attention and activity symptoms, not just the negative end of the distribution. Previous studies revealed strong psychometric properties of the parent and teacher report versions; however, there is little research on the new self-report form of the SWAN. Therefore, our research aimed to explore the psychometric characteristics of the SWAN self-report. A non-clinical sample of young women ( = 664, mean age: 20.01 years, : 3.08 years) completed the SWAN self-report, the Strengths and Difficulties Questionnaire (SDQ) and the Mental Health Continuum Short Form (MHC-SF). We tested several models using confirmatory factor analyses to assess the factorial validity of the SWAN self-report. Distributional characteristics, convergent, and predictive validity were assessed. A bifactor model with a general factor and a specific inattention factor (bifactor-1) provided the best fit in our data (CFI = 0.977, TLI/NFI = 0.972, RMSEA = 0.053 [90% CI: 0.047 - 0.059], SRMR = 0.061, ω = 0.90). The reliability of the general ADHD factor was good (ω = 0.87), and the specific inattention factor was acceptable (ω = 0.73). The distribution of the SWAN self-report scores did not differ from the normal distribution. A strong correlation between the SWAN and the SDQ Hyperactivity subscale was found. The analyses revealed good predictive validity. Our results suggest that the SWAN self-report is a valuable tool for assessing symptoms of ADHD in adolescents and young adults.

References
1.
Arildskov T, Virring A, Lambek R, Carlsen A, Sonuga-Barke E, Ostergaard S . The factor structure of attention-deficit/hyperactivity disorder in schoolchildren. Res Dev Disabil. 2022; 125:104220. DOI: 10.1016/j.ridd.2022.104220. View

2.
Coghill D, Sonuga-Barke E . Annual research review: categories versus dimensions in the classification and conceptualisation of child and adolescent mental disorders--implications of recent empirical study. J Child Psychol Psychiatry. 2012; 53(5):469-89. DOI: 10.1111/j.1469-7610.2011.02511.x. View

3.
Bonvicini C, Faraone S, Scassellati C . Attention-deficit hyperactivity disorder in adults: A systematic review and meta-analysis of genetic, pharmacogenetic and biochemical studies. Mol Psychiatry. 2016; 21(7):872-84. PMC: 5414093. DOI: 10.1038/mp.2016.74. View

4.
Goodman R . Psychometric properties of the strengths and difficulties questionnaire. J Am Acad Child Adolesc Psychiatry. 2001; 40(11):1337-45. DOI: 10.1097/00004583-200111000-00015. View

5.
Nikolas M, Burt S . Genetic and environmental influences on ADHD symptom dimensions of inattention and hyperactivity: a meta-analysis. J Abnorm Psychol. 2010; 119(1):1-17. DOI: 10.1037/a0018010. View