Enhancing the Precision of the Revised Life Orientation Test (LOT-R) across Germany, Ghana, India, and New Zealand Using Rasch Methodology

Abstract Accurately measuring life orientation (or continuum from optimism to pessimism) is essential for research focused on enhancing health and well-being. The psychometric statistics of the Revised Life Orientation Test (LOT-R) has been examined using Classical Test Theory (CTT). This method has been criticized for relying on the imprecise ordinal scores. We have employed the advance Rasch methodology to examine the psychometric statistics of the Revised Life LOT-R within a community sample from Ghana, Germany, India, and New Zealand. Utilizing the Partial Credit Rasch model, we analyzed responses from a randomly selected sample of 1,000 individuals ( n = 250 from each country) out of the total sample of 1,822 recruited from these countries. Our initial analysis of the LOT-R revealed significant misfit to the unidimensional Rasch model ( χ 2 (24) = 93.38, p < 0.001). The best fit was achieved through the advanced modification process of testlet creation, as evidenced by no significant deviations from the model expectations ( χ 2 (27) = 10.85, p < 0.99). The optimal three testlet model demonstrated strict unidimensionality, good reliability (Person Separation Index = 0.73), monotonous pattern of item thresholds, and adequate sample targeting ( M = 0.20; SD = 0.72). The LOT-R demonstrated internal structural validity, as well as convergent and external validity reflected by expected correlations with measures of compassion towards others, self-compassion, positive affect, distress and negative affect. The LOT-R further showed invariance across sociodemographic factors, and the optimal parameters guided the creation of an algorithm for transforming ordinal to interval data, enhancing precision of the instrument. Our study supports the LOT-R's reliability and validity, improving its precision for investigating dispositional optimism. The study provides an ordinal-to-interval conversion table presented in the paper that can be used to enhance measurement accuracy.