- Original authors / creators
- Julia S. Nakamura; Dorota Węziak-Białowolska; Robert D. Woodberry; Laura D. Kubzansky; Koichiro Shiba; R. Noah Padgett; Byron R. Johnson; Tyler J. VanderWeele
- Original publication
- Scientific Reports · Nature Publishing Group · 2025-04-30
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- CC BY 4.0
© The Author(s) 2025
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- Evidence limits
- Adjacent research, not a directly sampled family-office study. Applicability to a family office requires separate assessment. Our study has several limitations. First, item translation between languages may lead to different interpretations of our charitable giving and helping items. Charitable giving and helping are broad constructs, and participant interpretations may vary depending on cultural norms, personal experiences, and societal expectations (i.e., what constitutes ‘helping’ a stranger or ‘charity’ may differ across national contexts). Words may have different connotations in different languages (despite dedicated efforts to minimize this possibility). Because the meaning and practice of ‘charitable giving’ and ‘helping’ may vary across cultural and institutional contexts, future research should explore qualitative approaches (e.g., to understand how people interpret ‘helping’ a stranger), additional survey items (e.g., donating to religious organizations versus secular nonprofits versus other types of organizations), or other methodologies to capture further nuance in our understanding of these behaviors. Further, prosocial behaviors can take many forms, and charitable giving and helping are only two forms of prosocial engagement. In another manuscript using parallel methods, we have evaluated demographic variation in volunteering73. Future work may benefit from evaluating other forms of prosociality (e.g., empathy) which were not assessed in the GFS. Second, these are descriptive analyses and should not be interpreted causally (e.g., while employment may increase one’s likelihood of helping strangers, it is also possible that helping increases one’s likelihood of employment). The demographic descriptive statistics simply inform us of the proportion of people who helped in each demographic category. Third, these descriptive statistics capture patterns at a certain point in time – rates of charitable giving and helping in countries and across demographic groups may change over time and our findings may be influenced by seasonal effects (e.g., increased charitable giving during certain months of the year). For instance, the timing of surveys may influence charitable giving “in the past month” (e.g., Muslims often give the Zakat during Eid-al Fitr each year, and in the US, people give more in December, around the Christmas holidays, and before the tax year ends). We believe the GFS item asks about prosocial behaviors in the past month to maintain comparability across surveys and minimize concerns about recall bias over longer periods of time. Fourth, our assessment of charitable giving and helping was binary, and thus does not capture important nuance in prosocial engagement (e.g., what kind of helping behaviors occur, the amounts and targets of charitable giving, the type of organization money was given to [e.g., religious versus secular], etc.). Future studies may benefit from evaluating such nuances. For all the reasons above, we must be careful about interpreting specific rankings; confidence intervals moreover sometimes overlap. Our study also has several strengths, including comparison of a large number of demographic variables across many countries, consistency in operationalization of variables, and nationally representative samples40. Indeed, while there are already several other important multi-country international datasets, such as the Gallup World Poll and World Values Survey, the GFS has the advantage of a much wider breadth of well-being constructs, and also a longitudinal panel data structure starting in Wave 2, all of which will become more evident in future waves41.
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