Examining mental health in adults with intellectual disability: The benefits of multilevel modelling

ABSTRACT

Background: Adults with intellectual disabilities (ID) commonly live in specialised residential settings. Data collected from these adults are often nested. The aim of this study is to examine the impact of this data structure.

Method: Referent caregivers completed the Reiss Screen for Maladaptive Behaviour for each of the 571 adults with ID who participated in the study. Single-level and two-level multilevel modelling was compared in the context of confirmatory factor analysis and group difference analysis.

Results: For both types of analysis, the two-level solution showed a better fit. Furthermore, all group differences highlighted using the one-level model disappeared, i.e., became non-significant, in the two-level solution.

Conclusions: It is important to control for nested data when analysing mental health in adults with ID. Otherwise, the risk of underestimating the standard errors and obtaining biased results in significance tests appears greater, as was the case in the present study.

KEYWORDS:

• Intellectual disability
• nested data
• multilevel modelling
• mental health

Acknowledgements

We are most grateful for this support and that of all the adults and their caregivers who agreed to take part in this study.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was in part supported by the Swiss National Science Foundation (Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung) (grant number 100014-120657/1, Prof. Koviljka Barisnikov, Principle Investigator).