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One (Financial Well-Being) Model Fits All? Testing the Multidimensional Subjective Financial Well-Being Scale Across Nine Countries.

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Title: One (Financial Well-Being) Model Fits All? Testing the Multidimensional Subjective Financial Well-Being Scale Across Nine Countries.
Authors: Sorgente, Angela (AUTHOR), Atay, Bünyamin (AUTHOR), Aubrey, Marc (AUTHOR), Bhatia, Shikha (AUTHOR), Crespo, Carla (AUTHOR), Fonseca, Gabriela (AUTHOR), Güneri, Oya Yerin (AUTHOR), Lep, Žan (AUTHOR), Lessard, David (AUTHOR), Negru-Subtirica, Oana (AUTHOR), Portugal, Alda (AUTHOR), Ranta, Mette (AUTHOR), Relvas, Ana Paula (AUTHOR), Singh, Nidhi (AUTHOR), Sirsch, Ulrike (AUTHOR), Zupančič, Maja (AUTHOR), Lanz, Margherita (AUTHOR)
Source: Journal of Happiness Studies. Feb2024, Vol. 25 Issue 1/2, p1-26. 26p.
Abstract: A multidimensional model of emerging adults’ subjective financial well-being was proposed (Sorgente and Lanz, Int Journal of Behavioral Development, 43(5), 466–478 2019). The authors also developed a 5-factor scale (the Multidimensional Subjective Financial Well-being Scale, MSFWBS) intending to measure this construct in the European context. To date, data using this instrument have been collected in nine countries: Austria, Canada, Finland, India, Italy, Portugal, Romania, Slovenia, and Turkey. In the current study, data from these countries were analysed to test the validity of this model internationally. In particular, using an international sample of 4,475 emerging adults, we collected the following kinds of validity evidence for the MSFWBS: score structure, reliability, generalizability, convergent, and criterion-related evidence. Findings suggest that the MSFWBS (1) yields valid and reliable scores, and (2) works well in individualistic and economically developed countries, producing comparable scores. Implications for researchers and practitioners are discussed. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Happiness Studies is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Happiness+Studies%22">Journal of Happiness Studies</searchLink>. Feb2024, Vol. 25 Issue 1/2, p1-26. 26p.
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  Data: A multidimensional model of emerging adults’ subjective financial well-being was proposed (Sorgente and Lanz, Int Journal of Behavioral Development, 43(5), 466–478 2019). The authors also developed a 5-factor scale (the Multidimensional Subjective Financial Well-being Scale, MSFWBS) intending to measure this construct in the European context. To date, data using this instrument have been collected in nine countries: Austria, Canada, Finland, India, Italy, Portugal, Romania, Slovenia, and Turkey. In the current study, data from these countries were analysed to test the validity of this model internationally. In particular, using an international sample of 4,475 emerging adults, we collected the following kinds of validity evidence for the MSFWBS: score structure, reliability, generalizability, convergent, and criterion-related evidence. Findings suggest that the MSFWBS (1) yields valid and reliable scores, and (2) works well in individualistic and economically developed countries, producing comparable scores. Implications for researchers and practitioners are discussed. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Happiness Studies is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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