New ReQoL paper - An item response theory analysis of an item pool for the recovering quality of life (ReQoL) measure

Dr Anju Devianee Keetharuth

An item response theory analysis of an item pool for the recovering quality of life (ReQoL) measure

ReQoL-10 and ReQoL-20 have been developed for use as outcome measures with individuals aged 16 and over, experiencing mental health difficulties. 

Purpose

ReQoL-10 and ReQoL-20 have been developed for use as outcome measures with individuals aged 16 and over, experiencing mental health difficulties. This paper reports modelling results from the item response theory (IRT) analyses that were used for item reduction.

Methods

From several stages of preparatory work including focus groups and a previous psychometric survey, a pool of items was developed. After confirming that the ReQoL item pool was sufficiently unidimensional for scoring, IRT model parameters were estimated using Samejima’s Graded Response Model (GRM). All 39 mental health items were evaluated with respect to item fit and differential item function regarding age, gender, ethnicity, and diagnosis. Scales were evaluated regarding overall measurement precision and known-groups validity (by care setting type and self-rating of overall mental health).

Results

The study recruited 4266 participants with a wide range of mental health diagnoses from multiple settings. The IRT parameters demonstrated excellent coverage of the latent construct with the centres of item information functions ranging from − 0.98 to 0.21 and with discrimination slope parameters from 1.4 to 3.6. We identified only two poorly fitting items and no evidence of differential item functioning of concern. Scales showed excellent measurement precision and known-groups validity.

Conclusion

The results from the IRT analyses confirm the robust structure properties and internal construct validity of the ReQoL instruments. The strong psychometric evidence generated guided item selection for the final versions of the ReQoL measures.  The results were also used in developing a health state classification for the ReQoL-Utility Index (ReQoL-UI) so that the ReQoL measures can be used to generate quality adjusted life years to reflect benefits of mental health interventions in cost effectiveness analyses

For the full article, please visit here.

To visit the ReQoL website, please click here.

New HEDS Discussion Paper - Mapping the Health of Nation Outcomes Scale (HoNOS) onto the Recovering Quality of Life Utility Index (ReQoL-UI)

Anju Keetharuth and Donna Rowen

                                          Abstract

Dr Anju Devianee Keetharuth

Aim: The aim of this project is to develop and assess a mapping function to predict ReQoL-UI (a patient-reported mental health-specific preference-based measure) scores from HoNOS scores (clinician-reported measure, Health of Nation Outcomes Score).

Methods: Participants were recruited from 14 secondary mental health services in England, UK, and their clinician completed HoNoS. Mapping models were estimated using Ordinary Least Squares (OLS) on individual level and mean level data and different model specifications were explored. Model performance was assessed using mean absolute error (MAE), root mean square error (RMSE), percentage of observations with absolute errors greater than 0.1, and plots of the observed and predicted ReQoL-UI utilities and errors.

Results: Matched ReQoL-UI and HoNOS scores were collected for 649 participants. The sample comprised 56% inpatients, with overall mean ReQoL-UI utility of 0.683 and range from 1 to -0.195. Correlations between ReQoL-UI (items and utility) and HoNOS scores were moderate (0.2<r<0.4) or small (<0.2). The best model was OLS estimated using mean level data, with lowest MAE (0.046) and RMSE (0.056).

Discussion: There is little conceptual overlap between ReQoL-UI and HoNOS. They measure different concepts and, arguably, service users and clinicians, who complete the measures respectively, have different perspectives. Under these circumstances, caution is recommended when applying these estimates.        

Download the Discussion Paper here.     

Dr Donna Rowen