Bequests to health‐related charitable organisations: a structural model

Abstract

• Charitable organisations, which support research on serious diseases such as cancer, heart diseases or rheumatism, are to a considerable extent dependent on bequests. Because in the Netherlands, in the next decade, the number of deaths per year is expected to increase at a faster rate than the population growth, it is likely that in the future bequests, there will be an even larger source of income. This paper examines the psychological motives that determine the propensity to include a health-related charitable organisation in the will. Qualitative research by Schervish and Havens (2003) suggested that empathy for the suffering of others is the most important explanatory variable for leaving a bequest to charity. This result is examined and confirmed in a quantitative study by estimating a structural model that shows how other explanatory variables are mediated by empathy. Empathy is positively influenced by appeal of the charitable organisation, lack of family need, altruism and gratitude. Independent from empathy, generativity and personal experience with disease contribute to donations by bequests.

The timing of final charitable bequest decisions

“…For example, one experiment found that slight wording changes during the will‐making process doubled or tripled the share of testators including charity in their estate plans (Cabinet Office, ). Although previous research has explored the characteristics of planned bequest donors (Wiepking et al, ; Sargeant et al, ; Routley & Sargeant, ; Sikkel & Schoenmakers, ) and the predictors of charitable plan changes during life (James, ), none has focused specifically on the timing of the final charitable bequest decision.…”

Searching for Prosociality in Qualitative Data: Comparing Manual, Closed–Vocabulary, and Open–Vocabulary Methods

“…One coding method that meets both criteria is having human raters familiar with the design of the original studies read the personal strivings and guess how much people donated to charity. Not only can human raters understand language in context, but they can also accurately perceive how cooperative a target is from a brief face–to–face interaction, even when the target has a monetary incentive to convince others that he or she is cooperative (Sparks, Burleigh, & Barclay, 2016). It is plausible then that human raters could detect evidence of a desire to help needy others from participants’ strivings, even if some participants tried to present themselves as pursuing noble goals.…”

“…We also may have had more success predicting donations had we coded for different content. For instance, many researchers code textual data for generativity , which reflects a preoccupation with making a positive impact on the next generation (Emmons, 1999; Mansfield & McAdams, 1996) and is linked to charitable donations (Sikkel & Schoenmakers, 2012). Alternatively, we may have uncovered stronger predictors had we measured participants' attitudes towards their own strivings rather than coding their content.…”

Searching For Prosociality in Qualitative Data: Comparing Manual, Closed-Vocabulary, and Open-Vocabulary Methods

“…We also may have had more success predicting donations had we coded for different content. For instance, many researchers code textual data for generativity, which reflects a preoccupation with making a positive impact on the next generation (Emmons, 1999;Mansfield & McAdams, 1996) and is linked to charitable donations (Sikkel & Schoenmakers, 2012).…”