PAINTER, Jon, PURANDARE, Kiran, MCCABE, Joanne, ROY, Ashok and SHANKAR, Rohit (2025). Investigating the component structure of the Health of the Nation Outcomes Scales for people with Learning Disabilities (HoNOS-LD). International Journal of Social Psychiatry. [Article]
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34808:828906
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Painter-InvestigatingTheComponentStructure(AM).pdf - Accepted Version
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Painter-InvestigatingTheComponentStructure(AM).pdf - Accepted Version
Available under License Creative Commons Attribution.
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Abstract
Background:
Outcome measurement is increasingly recognised as a vital element of high-quality service provision, but practice remains variable in the field of intellectual disabilities. The Health of the National Outcome Scales for people with Learning Disabilities (HoNOS-LD) is a widely used Clinician Reported Outcome Measure in the UK and beyond. Over its 20-year lifespan, its psychometric properties have been frequently investigated. Multiple dimensionality reduction analyses have been published, each proposing a different latent structure.Aim:
To analyse a set of HoNOS-LD ratings to test its internal consistency, to identify the optimal number of latent variables, and to propose the items that group together in each domain.Methods:
A Principal Component Analysis of 169 HoNOS-LD ratings was performed to produce an initial model. The component loadings for each HoNOS-LD item were then examined, allowing the model to be adjusted to ensure the optimal balance of statistical robustness and clinical face-validity.Results:
HoNOS-LD’s internal consistency (18 items) was ‘acceptable’ (Cronbach’s alpha = 0.797). On excluding three items that had no bivariate correlations with the other 15 items internal consistency rose to ‘good’ (Cronbach’s alpha = 0.828). The final, four-component solution, using the 15 items possessed good internal reliability.Conclusion:
HONOS-LD statistical properties compared favourably to the other published latent structures and adheres to the tool’s rating guidance. The four-component solution offers an acceptable balance of statistical robustness and clinical face validity. It provides advantages over other models in terms of internal consistency and/or viability for use at a national level in the UK.More Information
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