Grandparental investment: Past, present, and future

What motivates grandparents to their altruism? We review answers from evolutionary theory, sociology, and economics. Sometimes in direct conflict with each other, these accounts of grandparental investment exist side-by-side, with little or no theoretical integration. They all account for some of the data, and none account for all of it. We call for a more comprehensive theoretical framework of grandparental investment that addresses its proximate and ultimate causes, and its variability due to lineage, values, norms, institutions (e.g., inheritance laws), and social welfare regimes. This framework needs to take into account that the demographic shift to low fecundity and mortality in economically developed countries has profoundly altered basic parameters of grandparental investment. We then turn to the possible impact of grandparental acts of altruism, and examine whether benefits of grandparental care in industrialized societies may manifest in terms of less tangible dimensions, such as the grandchildren's cognitive and verbal ability, mental health, and well-being. Although grandparents in industrialized societies continue to invest substantial amounts of time and money in their grandchildren, we find a paucity of studies investigating the influence that this investment has on grandchildren in low-risk family contexts. Under circumstances of duress - for example, teenage pregnancy or maternal depression - there is converging evidence that grandparents can provide support that helps to safeguard their children and grandchildren against adverse risks. We conclude by discussing the role that grandparents could play in what has been referred to as Europe's demographic suicid

Toward an integrative framework of grandparental investment

This response outlines more reasons why we need the integrative framework of grandparental investments and intergenerational transfers that we advocated in the target article. We discusses obstacles - from misconceptions to poor measures - that stand in the way of such a framework and of a better understanding of the effects of grandparenting in the developed world. We highlight new research directions that have emerged from the commentaries, and we end by discussing some of the things in our target article about which we may have been wron

Predictors of grandparental investment decisions in contemporary Europe: Biological relatedness and beyond

Across human cultures, grandparents make a valued contribution to the health of their families and communities. Moreover, evidence is gathering that grandparents have a positive impact on the development of grandchildren in contemporary industrialized societies. A broad range of factors that influence the likelihood grandparents will invest in their grandchildren has been explored by disciplines as diverse as sociology, economics, psychology and evolutionary biology. To progress toward an encompassing framework, this study will include biological relatedness between grandparents and grandchildren, a factor central to some discipline\u27s theoretical frameworks (e.g., evolutionary biology), next to a wide range of other factors in an analysis of grandparental investment in contemporary Europe. This study draws on data collected in the Survey of Health, Ageing and Retirement in Europe from 11 European countries that included 22,967 grandparent-child dyads. Grandparents reported biological relatedness, and grandparental investment was measured as the frequency of informal childcare. Biological and non-biological grandparents differed significantly in a variety of individual, familial and area-level characteristics. Furthermore, many other economic, sociological, and psychological factors also influenced grandparental investment. When they were controlled, biological grandparents, relative to non-biological grandparents, were more likely to invest heavily, looking after their grandchildren almost daily or weekly. Paradoxically, however, they were also more likely to invest nothing at all. We discuss the methodological and theoretical implications of these findings across disciplines

Phylogenetic signal and the utility of 12S and 16S mtDNA in frog phylogeny

Genes selected for a phylogenetic study need to contain conserved information that reflects the phylogenetic history at the specific taxonomic level of interest. Mitochondrial ribosomal genes have been used for a wide range of phylogenetic questions in general and in anuran systematics in particular. We checked the plausibility of phylogenetic reconstructions in anurans that were built from commonly used 12S and 16S rRNA gene sequences. For up to 27 species arranged in taxon sets of graded inclusiveness, we inferred phylogenetic hypotheses based on different apriori decisions, i.e. choice of alignment method and alignment parameters, including/excluding variable sites, choice of reconstruction algorithm and models of evolution. Alignment methods and parameters, as well as taxon sampling all had notable effects on the results leading to a large number of conflicting topologies. Very few nodes were supported in all of the analyses. Data sets in which fast evolving and ambiguously aligned sites had been excluded performed worse than the complete data sets. There was moderate support for the monophyly of the Discoglossidae, Pelobatoidea, Pelobatidae and Pipidae. The clade Neobatrachia was robustly supported and the intrageneric relationships within Bombina and Discoglossus were well resolved indicating the usefulness of the genes for relatively recent phylogenetic events. Although 12S and 16S rRNA genes seem to carry some phylogenetic signal of deep (Mesozoic) splitting events the signal was not strong enough to resolve consistently the inter-relationships of major clades within the Anura under varied methods and parameter settings

Age differences in risky choice: A meta-analysis

Does risk taking change as a function of age? We conducted a systematic literature search and found 29 comparisons between younger and older adults on behavioral tasks thought to measure risk taking (N= 4,093). The reports relied on various tasks differing in several respects, such as the amount of learning required or the choice framing (gains vs. losses). The results suggest that age-related differences vary considerably as a function of task characteristics, in particular the learning requirements of the task. In decisions from experience, age-related differences in risk taking were a function of decreased learning performance: older adults were more risk seeking compared to younger adults when learning led to risk-avoidant behavior, but were more risk averse when learning led to risk-seeking behavior. In decisions from description, younger adults and older adults showed similar risk-taking behavior for the majority of the tasks, and there were no clear age-related differences as a function of gain/loss framing. We discuss limitations and strengths of past research and provide suggestions for future work on age-related differences in risk taking