Measuring positive health using the My Positive Health (MPH) and Individual Recovery Outcomes Counter (I.ROC) dialogue tools: A panel study on measurement properties in a representative general Dutch population

V.P. van Druten*, M.J. Metz, J.J.P. Mathijssen, D. van de Mheen, M. van Vliet, B. Rudd, E. de Vries, L.M.W. Nahar-van Venrooij

*Corresponding author for this work

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Abstract

We aimed to investigate whether the dialogue tools My Positive Health (MPH) and Individual Recovery Outcomes Counter (I.ROC) tools were useful for quantitively measuring the positive health construct for monitoring and scientific purposes as well. An observational cross-sectional study was conducted in a representative general Dutch population (the LISS panel) to investigate factor structures and internal consistency from the 42-items MPH and 12-items I.ROC. After randomly splitting the dataset, principal component analysis (PCA) and confirmatory factor analysis (CFA) were applied. Pearson and Spearman correlation coefficient between both tools’ total scores were calculated. 2,457 participants completed the questionnaires. A six-factor structure was extracted for MPH (PH42) and a two-factor structure for I.ROC (I.ROC12). Explained variances were 68.1% and 56.1%, respectively. CFA resulted in good fit indices. Cronbach’s alphas were between 0.74 to 0.97 (PH42) and 0.73 to 0.87 (I.ROC12). Pearson correlation between the total scores was 0.8 and Spearman correlation was 0.77. Both PH42 and I.ROC12 are useful to quantitatively measure positive health aspects which can be summarised in sum scores. The dimensions found in this study and the corresponding item division differed from the dimensions of the original dialogue tools. Further research is recommended focussing on item reduction for PH42, factor structure of I.ROC, assessment of construct validity (in a general population) and response scales in more depth.
Original languageEnglish
Number of pages22
JournalApplied Research in Quality of Life
DOIs
Publication statusPublished - 2024

Keywords

  • positive health
  • recovery
  • patient-centred outcomes research
  • patient reported outcome measures
  • measurement properties
  • factor analysis

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