Family still matters: Human social motivation across 42 countries during a global pandemic.

The COVID-19 pandemic caused drastic social changes for many people, including separation from friends and coworkers, enforced close contact with family, and reductions in mobility. Here we assess the extent to which people's evolutionarily-relevant basic motivations and goals-fundamental social motives such as Affiliation and Kin Care-might have been affected. To address this question, we gathered data on fundamental social motives in 42 countries (N = 15,915) across two waves, including 19 countries (N = 10,907) for which data were gathered both before and during the pandemic (pre-pandemic wave: 32 countries, N = 8998; 3302 male, 5585 female; M age  = 24.43, SD = 7.91; mid-pandemic wave: 29 countries, N = 6917; 2249 male, 4218 female; M age  = 28.59, SD = 11.31). Samples include data collected online (e.g., Prolific, MTurk), at universities, and via community sampling. We found that Disease Avoidance motivation was substantially higher during the pandemic, and that most of the other fundamental social motives showed small, yet significant, differences across waves. Most sensibly, concern with caring for one's children was higher during the pandemic, and concerns with Mate Seeking and Status were lower. Earlier findings showing the prioritization of family motives over mating motives (and even over Disease Avoidance motives) were replicated during the pandemic. Finally, well-being remained positively associated with family-related motives and negatively associated with mating motives during the pandemic, as in the pre-pandemic samples. Our results provide further evidence for the robust primacy of family-related motivations even during this unique disruption of social life.

Fundamental social motives measured across forty-two cultures in two waves.

How does psychology vary across human societies? The fundamental social motives framework adopts an evolutionary approach to capture the broad range of human social goals within a taxonomy of ancestrally recurring threats and opportunities. These motives-self-protection, disease avoidance, affiliation, status, mate acquisition, mate retention, and kin care-are high in fitness relevance and everyday salience, yet understudied cross-culturally. Here, we gathered data on these motives in 42 countries (N = 15,915) in two cross-sectional waves, including 19 countries (N = 10,907) for which data were gathered in both waves. Wave 1 was collected from mid-2016 through late 2019 (32 countries, N = 8,998; 3,302 male, 5,585 female; Mage = 24.43, SD = 7.91). Wave 2 was collected from April through November 2020, during the COVID-19 pandemic (29 countries, N = 6,917; 2,249 male, 4,218 female; Mage = 28.59, SD = 11.31). These data can be used to assess differences and similarities in people's fundamental social motives both across and within cultures, at different time points, and in relation to other commonly studied cultural indicators and outcomes.

Family Matters: Rethinking the Psychology of Human Social Motivation.

What motives do people prioritize in their social lives? Historically, social psychologists, especially those adopting an evolutionary perspective, have devoted a great deal of research attention to sexual attraction and romantic-partner choice (mate seeking). Research on long-term familial bonds (mate retention and kin care) has been less thoroughly connected to relevant comparative and evolutionary work on other species, and in the case of kin care, these bonds have been less well researched. Examining varied sources of data from 27 societies around the world, we found that people generally view familial motives as primary in importance and mate-seeking motives as relatively low in importance. Compared with other groups, college students, single people, and men place relatively higher emphasis on mate seeking, but even those samples rated kin-care motives as more important. Furthermore, motives linked to long-term familial bonds are positively associated with psychological well-being, but mate-seeking motives are associated with anxiety and depression. We address theoretical and empirical reasons why there has been extensive research on mate seeking and why people prioritize goals related to long-term familial bonds over mating goals. Reallocating relatively greater research effort toward long-term familial relationships would likely yield many interesting new findings relevant to everyday people's highest social priorities.

Attention in risky choice.

Previous research on the processes involved in risky decisions has rarely linked process data to choice directly. We used a simple measure based on the relative amount of attentional deployment to different components (gains/losses and their probabilities) of a risky gamble during the choice process, and we related this measure to the actual choice. In an experiment we recorded the decisions, decision times, and eye movements of 80 participants who made decisions on 11 choice problems. We used the number of eye fixations and fixation transitions to trace the deployment of attention during the choice process and obtained the following main results. First, different components of a gamble attracted different amounts of attention depending on participants' actual choice. This was reflected in both the number of fixations and the fixation transitions. Second, the last-fixated gamble but not the last-fixated reason predicted participants' choices. Third, a comparison of data obtained with eye tracking and data obtained with verbal protocols from a previous study showed a large degree of convergence regarding the process of risky choice. Together these findings tend to support dimensional decision strategies such as the priority heuristic.

Testing process predictions of models of risky choice: a quantitative model comparison approach.

This article presents a quantitative model comparison contrasting the process predictions of two prominent views on risky choice. One view assumes a trade-off between probabilities and outcomes (or non-linear functions thereof) and the separate evaluation of risky options (expectation models). Another view assumes that risky choice is based on comparative evaluation, limited search, aspiration levels, and the forgoing of trade-offs (heuristic models). We derived quantitative process predictions for a generic expectation model and for a specific heuristic model, namely the priority heuristic (Brandstätter et al., 2006), and tested them in two experiments. The focus was on two key features of the cognitive process: acquisition frequencies (i.e., how frequently individual reasons are looked up) and direction of search (i.e., gamble-wise vs. reason-wise). In Experiment 1, the priority heuristic predicted direction of search better than the expectation model (although neither model predicted the acquisition process perfectly); acquisition frequencies, however, were inconsistent with both models. Additional analyses revealed that these frequencies were primarily a function of what Rubinstein (1988) called "similarity." In Experiment 2, the quantitative model comparison approach showed that people seemed to rely more on the priority heuristic in difficult problems, but to make more trade-offs in easy problems. This finding suggests that risky choice may be based on a mental toolbox of strategies.

Identifying decision strategies: a process- and outcome-based classification method.

This article presents a classification method that makes possible the detection of important decision strategies that people use in nonrisky multiattribute decision tasks. The classification method incorporates a multimethod approach that combines elements of both structural modeling and process tracing. We begin with a discussion of nine common characteristics of decision strategies and then classify 13 decision strategies on the basis of these characteristics. Next, we demonstrate that six of the characteristics can be used to develop one outcome-based and three process-based metrics. In addition, we present an algorithm that shows how to use the metrics. We demonstrate that using our metrics in conjunction with a measure for direction of search allows identification of most of the 13 decision strategies. Finally, we outline the potential of our research for the design of decision support systems such as online shops.

Risky choice with heuristics: reply to Birnbaum (2008), Johnson, Schulte-Mecklenbeck, and Willemsen (2008), and Rieger and Wang (2008).

E. Brandstätter, G. Gigerenzer, and R. Hertwig (2006) showed that the priority heuristic matches or outperforms modifications of expected utility theory in predicting choice in 4 diverse problem sets. M. H. Birnbaum (2008) argued that sets exist in which the opposite is true. The authors agree--but stress that all choice strategies have regions of good and bad performance. The accuracy of various strategies systematically depends on choice difficulty, which the authors consider a triggering variable underlying strategy selection. Agreeing with E. J. Johnson, M. Schulte-Mecklenbeck, and M. C. Willemsen (2008) that process (not "as-if") models need to be formulated, the authors show how quantitative predictions can be derived and test them. Finally, they demonstrate that many of Birnbaum's and M. O. Rieger and M. Wang's (2008) case studies championing their preferred models involved biased tests in which the priority heuristic predicted data, whereas the parameterized models were fitted to the same data. The authors propose an adaptive toolbox approach of risky choice, according to which people first seek a no-conflict solution before resorting to conflict-resolving strategies such as the priority heuristic.

Knowledge-based choice.

This study tested the distinction between knowledge-based choices and gambling decisions. Gambling decisions contain stated probabilities, and success depends on chance only. In knowledge-based decisions, in contrast, the probabilities are usually unknown and the outcomes of a choice depend on a person's ability or knowledge. Three different theoretical accounts were used to predict knowledge-based choices: prospect theory, the competence hypothesis, and probability-focused reasoning. Students (64 women, 93 men, M=22.4 yr.) chose between a knowledge bet and a sure gain of equal expected value. Analysis showed people prefer a knowledge bet over the sure gain, if the probability of winning is high-in contrast to prospect theory, which predicts the opposite. Both the competence hypothesis and probability focused reasoning can explain these differences, but prospect theory does not. It appears knowledge-based choices and gambling decisions capture different facets of decision-making.

The priority heuristic: making choices without trade-offs.

Bernoulli's framework of expected utility serves as a model for various psychological processes, including motivation, moral sense, attitudes, and decision making. To account for evidence at variance with expected utility, the authors generalize the framework of fast and frugal heuristics from inferences to preferences. The priority heuristic predicts (a) the Allais paradox, (b) risk aversion for gains if probabilities are high, (c) risk seeking for gains if probabilities are low (e.g., lottery tickets), (d) risk aversion for losses if probabilities are low (e.g., buying insurance), (e) risk seeking for losses if probabilities are high, (f) the certainty effect, (g) the possibility effect, and (h) intransitivities. The authors test how accurately the heuristic predicts people's choices, compared with previously proposed heuristics and 3 modifications of expected utility theory: security-potential/aspiration theory, transfer-of-attention-exchange model, and cumulative prospect theory.