This study proposed a nuanced approach to the association between job insecurity and financial stress by examining whether financial well‐being mediates the established association. In addition, we examined whether the association between the job insecurity and financial stress, through financial well‐being, is moderated by income. For this study, we conducted a path analysis using 1,145 survey respondents. Results revealed a significant relationship between the job insecurity and financial stress and a partial mediation effect of financial well‐being. Moreover, the indirect effect of job insecurity on financial stress through financial well‐being was moderated by income. Although people who have higher financial well‐being were more likely to have lower financial stress, this relationship varied by income such that it was stronger for higher income groups than for lower income groups. Our findings provide insights into the way job insecurity and financial well‐being influence financial stress. This study will help the researchers and practitioners develop more effective and adaptive intervention programmes and resources for individuals and families. Implications for practice and directions for future research are discussed.

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This research derived information functions and proposed new scalar information indices to examine the quality of multidimensional forced choice (MFC) items based on the RANK model. We also explored how GGUM-RANK information, latent trait recovery, and reliability varied across three MFC formats: pairs (two response alternatives), triplets (three alternatives), and tetrads (four alternatives). As expected, tetrad and triplet measures provided substantially more information than pairs, and MFC items composed of statements with high discrimination parameters were most informative. The methods and findings of this study will help practitioners to construct better MFC items, make informed projections about reliability with different MFC formats, and facilitate the development of MFC triplet-and tetrad-based computerized adaptive tests.

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Historically, multidimensional forced choice (MFC) measures have been criticized because conventional scoring methods can lead to ipsativity problems that render scores unsuitable for interindividual comparisons. However, with the recent advent of item response theory (IRT) scoring methods that yield normative information, MFC measures are surging in popularity and becoming important components in high-stake evaluation settings. This article aims to add to burgeoning methodological advances in MFC measurement by focusing on statement and person parameter recovery for the GGUM-RANK (generalized graded unfolding-RANK) IRT model. Markov chain Monte Carlo (MCMC) algorithm was developed for estimating GGUM-RANK statement and person parameters directly from MFC rank responses. In simulation studies, it was examined that how the psychometric properties of statements composing MFC items, test length, and sample size influenced statement and person parameter estimation; and it was explored for the benefits of measurement using MFC triplets relative to pairs. To demonstrate this methodology, an empirical validity study was then conducted using an MFC triplet personality measure. The results and implications of these studies for future research and practice are discussed.