We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
A Machine Learning Approach to Assess Differential Item Functioning of the KINDL Quality of Life Questionnaire Across Children with and Without ADHD.
- Authors
Jafari, Peyman; Mehrabani-Zeinabad, Kamran; Javadi, Sara; Ghanizadeh, Ahmad; Bagheri, Zahra
- Abstract
This study aimed to investigate differential item functioning (DIF) of the child and parent reports of the KINDL measure across children with and without Attention-deficit/hyperactivity disorder (ADHD). The sample included 122 children with ADHD and 1086 healthy peers, alongside 127 and 1061 of their parents, respectively. The generalized partial credit model with lasso penalization, as a machine learning method, was used to assess DIF of the KINDL across the two groups. The findings showed that three out of 24 items of the child reports and seven out of 24 items of the parent reports of the KINDL exhibited DIF between children with and without ADHD. Accordingly, Iranian children with and without ADHD along with their parents perceive almost all items in the KINDL similarly. Hence, the observed difference in quality of life scores between children with and without ADHD is a real difference and not a reflection of measurement bias.
- Subjects
MACHINE learning; QUALITY of life; ATTENTION-deficit hyperactivity disorder; IRANIANS; QUESTIONNAIRES
- Publication
Child Psychiatry & Human Development, 2022, Vol 53, Issue 5, p980
- ISSN
0009-398X
- Publication type
Article
- DOI
10.1007/s10578-021-01179-6