Which of the following is the best example of someone with an altruistic personality?

Online Altruistic Behavior and Its Influencing Factors

Altruistic behavior is a form of prosocial behavior, which is voluntary and has the ultimate goal of increasing another’s welfare (Batson & Shaw, 1991). With the popularity and rapid development of the Internet, altruistic behavior has been extended to the Internet environment, therefore researchers began to focus their attention on altruistic behavior in cyberspace (Amichai-Hamburger, 2008; Wright & Li, 2011). Online altruistic behavior is a kind of voluntary behavior which is manifested in the Internet, and in favor of other people and society but without expecting anything in return (Zheng, 2010). Organizing altruistic and voluntary activities to help people in need in cyberspace is a typical example of prosocial Internet behavior (Ma, Li, & Pow, 2011).

Amichai-Hamburger (2008) stated that the characteristics of the Internet are more conducive to the occurrence of altruistic behavior than those of offline. For example, anonymity made it easier for people to ask for help on the Internet, and immediacy made the altruistic behavior more effective (Zheng & Gu, 2013). This may be due to the disinhibition effect that makes people feel less inhibited by others’ opinions or potential behaviors and social conventions, and the Internet might remove some possible barriers to help-seeking/giving. Unfortunately for so many published articles concerning Internet use among adolescents and college students, the author emphasized too much on its negative effects, such as problematic Internet use (Chen, Li, Bao, Yan, & Zhou, 2015), rather than its potential positive consequence such as online altruistic behavior. Take computer games as an example, the literature has stressed the association between game playing and aggression (Anderson & Dill, 2000), but there is some research that also revealed that those who spent more time playing computer games display more prosocial behavior (Mengel, 2014). Every coin has two sides, we should not neglect positive Internet use behavior.

In the mainland China, online altruistic behavior has got some scholars’ attention. Zheng, Zhu, and Gu (2011) developed the Internet Altruistic Behavior Scale for Chinese college students. The scale consisted of 30 items, which had four factors such as online support, online guidance, online sharing, and online reminding. This scale showed satisfying reliabilities and validities, and has been used in most of the online altruistic behavior studies in mainland China (e.g., Liu, Chen, et al., 2015; Zhao et al., 2012; Zheng, 2013; Zheng & Gu, 2012).

Previous work that examined the influencing factors of online altruistic behavior has focused on personality, Internet communication motivation, online interpersonal trust, online social support, and self-esteem among other related concepts. Zheng and Gu (2013) found that extraversion, conscientiousness, openness, and self-esteem were positively associated with Internet altruistic behavior, whereas neuroticism was negatively associated with Internet altruistic behavior. Moreover, the association between the big five characteristics, such as openness, conscientiousness, neuroticism, and Internet altruistic behavior was mediated by self-esteem. In addition, Zheng (2012) found that higher levels of optimism were positively related to online social support and Internet altruistic behavior. Besides, online social support plays a partially intermediary role in the effect of optimism on Internet altruistic behavior. Zhao and Zhang (2013) examined the effects of Internet communication motivation and online interpersonal trust on college students’ Internet altruistic behavior. The results revealed that Internet communication motivation and online interpersonal trust were positively related to Internet altruistic behavior, the effect of Internet communication motivation on Internet altruistic behavior was partially mediated by online interpersonal trust. Zhao et al. (2012) explored the mediating effects of online social support in the relationship between trait empathy and Internet altruistic behavior. The results indicated that college students’ online social support played a full mediation effect on trait empathy and Internet altruistic behavior. Liu, Chen, et al. (2015) examined the impact of Internet use and Internet altruistic behavior, and found that Internet use, including online social interaction, Internet information behavior, and online game behavior, was positively correlated with Internet altruistic behavior—and the positive association between Internet use and online altruistic behavior was mediated by Internet use self-efficacy.

In summary, given some characteristics of the Internet (e.g., anonymity, immediacy), people can easily offer assistance to others online. In the Chinese culture context, an Internet Altruistic Behavior Scale was developed and frequently used in the studies in mainland China. In terms of the influencing factors of online altruistic behavior, the existing literature in China has revealed some important factors, including personality, Internet communication motivation, online interpersonal trust, online social support, and self-esteem.

However, online altruistic behavior research is still in its early stages. Current research on online altruistic behavior is currently only a simple analysis based on its conception, features, and influencing factors, and lacks of in-depth and systematic research (Zheng & Gu, 2012). More specifically, the present studies on online altruistic behavior should be interpreted in light of certain limitations. First, many of the previous studies were cross-sectional, and it is important to realize that cross-sectional design cannot support causal inferences. Future studies should adopt longitudinal or experimental designs to obtain more robust measures of the online altruistic behavior and its influencing factors. Second, most studies only focused on the helper in online altruistic behavior, and a very important future direction is to consider the recipients and help giver in cyberspace simultaneously. In other words, we did not take other disclosure targets (e.g., parents) into consideration. Future research is needed to examine whether the current findings generalize to other disclosure targets. Last, individual differences are also important to consider in regard to online altruistic behavior. Some potential moderator factors, such as gender and different types of online altruistic behavior, are especially informative for our understanding of positive Internet use behavior.

Origin of a Killing Trait

As a species, we are certainly complex. We have pointed out that we sometimes demonstrate altruistic behavior, going out of our way to help others, and at other times, we seem to have very little respect for life. As members of what we may refer to as “normal” society, we routinely kill living things, often without ill feelings, and those who kill nonhuman animals often attempt to distinguish between which organisms have the right to live and those which do not. Humans who commit genocide even make this distinction between different groups of people (Andreopoulos, 1994).

Killing appears to be well engrained in our species, and it is found in most other predaceous animal species as well. It is a trait that actually assists all species in their survival and reproduction. Kill or be killed, express yourself in ways that tell your foe that you are not to be dealt with or hide to avoid killing. At times, however, we (psychopaths and “normal” people alike) kill for pleasure.

At the other end of the behavioral scale, there are people who abhor killing of any sort. Many individuals in our population even refrain from eating meat because of what they feel are atrocities committed to domestic animals from which the meat is taken (Andreopoulos, 1994). Yet, as a species, we most often feel no guilt for killing another animal: we kill agricultural animals; we fish certain species even to the brink of extinction; we hunt wild species as a sport, killing multitudes of feral individuals simply for our pleasure or by taking land for building upon or growing crops to feed our masses; and we sometimes kill one another, and often without feelings of empathy for the people we kill or their distraught families. But where does this killing trait originate? It is worth looking into this phenomenon to understand more about who we are and why we do these things.

In Becoming Evil, How Ordinary People Commit Genocide and Mass Killing, J. Waller (2007) discusses not only why humans commit genocide but the type of person who carries it out. While genocide and other forms of mass killing are complicated, prejudicial affairs, Waller’s conclusion was that the people who commit atrocities against humanity are people just like us.

Although this may be a bitter pill to swallow for most of us, we may take solace in knowing that killing is not always the nature of most individuals who take part in genocide. The idea, brought out in the last chapter and in the earlier statement , is generally initiated by dominant psychopaths and followed by group action.1

For a moment, let us entertain the thought that certain types of killing are accepted in human society (although some individuals within the society may feel otherwise). Other forms of killing may be determined to be expressions of amoral, selfish, or psychopathic behavior.

Reciprocity

Initially, it appears more difficult to understand why individuals that are not directly related to others would exhibit altruistic behavior. However, social organisms may perform certain behaviors to help another individual while expecting something in return at some later time. Such an act has been referred to as reciprocal altruism in the past but more recently as reciprocity. Reciprocity, for instance, occurs between organisms that are not closely related. One animal helping an unrelated one in a fight or offering food to another who is not kin may be adaptive if the individual that is aided returns the favor in the future. This phenomenon was originally offered by Robert Trivers (1971), but the concept is found in such children’s stories as the lion and mouse mutualism in Aesop’s Fables.

The phenomenon of reciprocity in nature typically functions to ensure a reliable supply of essential resources, especially for animals living in a habitat where food quantity or quality fluctuates unpredictably. As an example, some vampire bats occasionally fail to feed on prey while others manage to consume a surplus of blood. Bats that eat well may regurgitate part of their blood meal to save a conspecific from starvation. Since these animals live in close-knit groups over many years, an individual can count on other group members to reciprocate the favor on nights when it goes hungry.

In natural populations of animals other than humans, it is difficult to determine whether an act is truly altruistic, a function of reciprocity, or otherwise. In humans, it may be less difficult since we understand the neurological processes of humans best. The concept of altruism in humans, for instance, is supported in situations such as the Sandy Hook Elementary School Shooting, in which teachers hid students in closets and bathrooms, and even threw themselves in the line of fire. Some paid with their lives. These are altruistic acts that are not associated with relatedness or reciprocity. They were on-the-spur-of-the-moment decisions to help students who had been entrusted to the care of teachers, showing that behavior displayed by individuals do not always have a selfish origin or benefit the altruist. The same could be said for soldiers who throw themselves in harm’s way to protect other members of their group.

2 Genetic Relatedness and Altruism

Much cooperation is mutualistic in that all of the interacting individuals gain from the behavior. However, many forms of cooperation involve altruistic behavior, whereby one individual provides benefits to another at a cost to itself. The presence of such behavior appears paradoxical to evolutionary theory because reduced fitness cannot evolve. Hamilton (1964) proposed a resolution to this paradox: that genes for altruism can increase in frequency and be maintained because they may also be present in the recipient of the benefits. Thus, by helping genetic relatives, an individual can maximize its ‘inclusive fitness,’ the sum of its own reproduction (descendant kin), plus its reproduction via its positive effects on collateral kin devalued by its genetic relatedness to them. Altruistic behavior can be selected for under such ‘kin selection’ if rb−c>0, where r is the relatedness of actor to recipient (the probability that a focal gene in the actor is present in the recipient), b is benefit to the recipient, and c is cost to the actor. Inclusive fitness theory predicts that genetic relatedness should be high among individuals in social systems with altruism. In accordance with this prediction, substantial levels of genetic relatednesses have been found between interacting individuals in the overwhelming majority of cooperatively-breeding and eusocial species thus far studied (Choe and Crespi 1997). By contrast, the few communal species for which such data are available exhibit colonies comprised of non-relatives or distantly-related individuals. All told, inclusive fitness theory has gained tremendous empirical support and is one of the cornerstones of social evolution theory.

Altruism can also evolve if it is reciprocal, such that the altruistic act of one individual to another is later reciprocated (Trivers 1971) (Table 1). By this mechanism, individuals need not be relatives, but there must be some means whereby cheating is thwarted lest the system break down. Such means may include recognition of individuals or the building of ‘reputations’ and as such reciprocal altruism may be limited to species with highly-developed cognitive abilities, such as primates.

Table 1. The three mechanisms leading to social cooperation

Altruism

Altruism, or the provision of benefit for others at the cost of one's own, is a prominent trait characteristic of our species. Altruistic behavior challenges evolutionary theory, in that natural selection favors prosocial traits over selfish ones. It poses not only an evolutionary but an economic paradox, seeming to contradict the principle of profit maximization. By all accounts, Homo sapiens shows extraordinarily altruistic tendencies. Numerous explanations have been proposed, including kin selection, reciprocal altruism, indirect reciprocity, and altruistic punishment (Sigmund and Hauert, 2002; Fehr and Rockenbach, 2004).

An important experimental approach in understanding human altruistic behavior and its biologic underpinnings has been the adoption of behavioral economics paradigms. Knafo et al. (2008a) used a molecular genetic approach combined with a classic behavioral economic paradigm, the dictator game. Participants “dictate” how much of a fixed sum of money they receive they will give to a passive recipient. The length of the arginine vasopressin 1a receptor promoter (AVPR1a) RS3 microsatellite predicted fund allocations. The length of the RS3 microsatellite was associated with greater giving behavior. Meyer-Lindenberg et al. (2009) also found that long AVPR1a alleles predicted greater amygdala activation during functional imaging employing an emotional face-matching paradigm.

Social Approval

The motivation to obtain social approval (or avoid social disapproval) explains a variety of social behaviors in humans, including conformity behavior, prosocial or altruistic behavior, and so on. Past social neuroscience studies using fMRI have consistently revealed that the perception of social approval or a good reputation in the eyes of other people robustly activates the striatum and vmPFC (Davey, Allen, Harrison, Dwyer, & Yucel, 2010; Izuma, Saito, & Sadato, 2008; Jones et al., 2011; Korn, Prehn, Park, Walter, & Heekeren, 2012). For example, in two fMRI studies (Izuma et al., 2008; Korn et al., 2012), participants were led to believe that other people had evaluated them, and the evaluations were shown to each participant while he or she was inside an fMRI scanner. Not surprisingly, participants typically reported positive emotional feelings when they saw positive evaluations (e.g., ‘trustworthy’) from others. fMRI data revealed that the striatum and ACC were strongly activated when the participants were shown positive social evaluations. Furthermore, Izuma et al. (2008) showed that the striatum areas activated by positive social evaluations largely overlapped with the areas activated by monetary rewards (Izuma et al., 2008).

In addition to inducing positive emotional responses, reward affects learning and motivation (Berridge & Robinson, 2003). Neuroimaging studies show that learning based on social approval or evaluation and motivation to obtain social approval (or decision-making based on the value of social approval) also involve the brain's reward system. Just as we learn which restaurants are good or bad from the direct experience of eating at them, we learn whom we like or dislike based on positive or negative encounters: we tend to like people who are more likely to give us positive social feedback (i.e., ‘reinforcers’). In an fMRI study (Jones et al., 2011), participants saw a picture of each of three different individuals with or without positive social feedback. The probability of receiving positive social reinforcement from the three peers was experimentally manipulated so that one peer always gave positive feedback (100%) and the other two peers did so 66% or 33% of the time, respectively. After the fMRI sessions, participants rated the peer who always gave positive social feedback as the most likable and the peer who rarely gave positive social feedback the least likable, indicating that they learned about these three peers and formed differential attitudes based on social feedback. Interestingly, the fMRI results showed that activities in the striatum, ACC, and anterior insula significantly correlated with social prediction error (the difference between what they expected and what they actually received). Prediction error signals also occurred in these areas in a learning task based on other tangible rewards (O'Doherty, 2004), so the findings from the Jones et al. (2011) study suggest that learning based on social reward has a common neural basis with learning based on other tangible rewards.

In addition, when an individual passively obtains social reward (Izuma et al., 2008; Korn et al., 2012) and when he or she actively makes a decision based on its reward value, the values of social approval and money are both processed in the same striatal and midbrain areas. It is well known in psychology and economics that the presence of observers (or reduced anonymity) increases a person's tendency to act prosocially, because the social reward of the observers’ approval works as additional incentive. In an fMRI study (Izuma, Saito, & Sadato, 2010), participants were asked to make real donation decisions inside an fMRI scanner. In half of the fMRI sessions, two other people observed the participant’s donation decisions through a video camera. The ventral striatum and midbrain of the participants showed particularly strong activity when they decided to keep the money for themselves (i.e., not donate) in the absence of observers and when they decided to donate in the presence of observers—when high social reward (positive impression or approval from observers) was expected. These results suggest that the striatum and midbrain integrate the reward values of social approval and other tangible rewards (e.g., money) when making prosocial decisions. Thus, findings from fMRI studies converge to show that the abstract social reward of approval or a good reputation has the same neural bases as other tangible rewards.

Reconciling Evolution and Altruism

Over the course of the twentieth century, biologists identified two important mechanisms that alleviate the conflict between evolution and altruism. Both mechanisms work by showing how apparently altruistic behavior can be recharacterized as individually advantageous from an evolutionary perspective. As biologists William Hamilton and Robert Trivers explained in their respective work, aid to kin and assistance to nonrelatives can – under certain circumstances – enhance individual fitness.

Kin selection explains how altruism can evolve among genetically related individuals. One intuitive way to think of kin selection is by extending the logic involved in parental care. At first glance, one might think that the struggle for existence would favor a narrow focus on one’s own survival. However, from an evolutionary perspective, survival is only one part of the equation. Because the evolutionary process is intergenerational, long-term evolutionary success requires the production of offspring who, too, survive and reproduce. Investing in the survival of one’s offspring is therefore consistent with the basic strategy of promoting one’s own reproductive fitness, since fitness is measured by the number of descendants one leaves in subsequent generations. But if it is fitness enhancing to assist one’s own offspring, might it not be fitness enhancing to assist other close relatives, who share a similar genetic makeup, particularly if such individuals are of reproductive (or pre-reproductive) age?

The answer is yes, albeit with some limitations. As the genetic relationship between the helper and the helped attenuates, it becomes less advantageous to invest in helping. For example, it would be more fitness enhancing for an individual to lay down her life for a son than for a cousin. In 1964, biologist William Hamilton formalized an account of the conditions under which it is fitness enhancing to assist a relative. He showed that one would expect “altruistic” behavior (where one assists another at a cost to oneself) to evolve when the costs of such behavior are less than the benefits to the recipient, discounted according to the recipient’s genetic relatedness to the donor. As the relationship becomes more distant, the ratio of cost to benefit must decrease if helping is to be evolutionarily favored. Formally, altruistic behavior can be selected when C < B ∗ R, where C is the fitness cost to the donor, B is the fitness benefit to the recipient, and R is the coefficient of relatedness.

Thus, in the case of one’s full sibling, where the coefficient of relatedness is 0.5 (siblings share, on average, 50% of one another’s genes), it is evolutionarily advantageous to endure a cost C if by doing so one can confer a fitness benefit greater than 2C on the recipient. The general prediction of Hamilton’s theory of kin selection is that helping behavior can be evolutionarily favored, but such behavior should be targeted toward close relatives.

Not all examples of altruistic behavior occur between close relatives, however. This led biologist Robert Trivers to suggest another mechanism by which altruism could evolve: reciprocal altruism. Trivers’s theory of reciprocal altruism suggests that under certain circumstances, conditional helping behavior can be evolutionarily stable. The circumstances that favor such behavior can be identified using iterated game theoretic models. In a one-shot prisoner’s dilemma, noncooperators will always earn higher payoffs (i.e., have greater fitness) than cooperators. But if the game is repeated, then an individual who cooperated and was bilked in the first round can retaliate against the defector. It turns out that in a game with many rounds in a population containing a variety of strategies (some defectors, some cooperators, some conditional cooperators, etc.), the strategy ‘tit-for-tat’ – where an individual begins by cooperating, but then responds by doing whatever the opponent does – can be highly successful, and can beat out the strategy ‘always defect.’ The intuitive explanation for this is that reciprocal altruists enjoy the benefits of cooperation when paired with cooperators or other reciprocal altruists, while they avoid being seriously taken advantage of by defectors by refusing to cooperate in subsequent rounds. Defectors, on the other hand, never get taken advantage of, but they also fail to enjoy any of the benefits of cooperation.

Theoretical models of kin selection and reciprocal altruism go a significant distance to dissolving the tension that Huxley identified between evolution and ethics. There are limitations, however. For one, the models are behavioral and not psychological models. They offer no explicit insight as to how moral motivation evolved, although to show that altruistic behavior – a type of behavior often associated with moral behavior – is compatible with evolution certainly makes it more plausible that ethics as we know it could be the product of natural selection. Kin selection and reciprocal altruism both support the idea that natural selection and altruism need not be diametrically opposed.

Nevertheless, a number of scientists and philosophers believe that kin selection and reciprocal altruism alone are insufficient to account for the moral behavior and moral psychology of human beings. According to these scholars, one of the most fundamental limitations of kin selection and reciprocal altruism is that they cannot provide a full explanation of human ultrasociality, which involves cooperation in large, unrelated groups to which individuals have significant loyalties and for which individuals are often willing to make serious sacrifices.

Darwin, interestingly, noted this feature of human social life well over a century ago (although he did not label it ultrasociality), and in The Descent of Man, he proposed a mechanism to explain it. Darwin emphasized the importance of certain emotions – such as courage, sympathy, and loyalty – as a foundation for social life and moral behavior. These emotions, suggested Darwin, evolved by the very same evolutionary mechanism that is at work in so many other contexts: natural selection. However, the evolutionary struggle that generates emotions such as courage is not a struggle between individuals, but rather the result of competition between different human groups. Darwin argued that those groups that possess a greater prevalence of cooperative, loyal, and courageous individuals will prevail over those groups full of selfish individuals, because lack of social concern inevitably leads to internal strife.

The mechanism of selection Darwin outlined in relation to the moral emotions is group selection. For many decades, group selection was disfavored by biologists for a variety of reasons, including the fact that it was not clear exactly how this mechanism could work in nature. In particular, the conditions required for group selection were thought rarely to be obtained. Recently, however, group selection has experienced a renaissance as biologists and philosophers have disentangled conceptual problems and adduced plausible mechanisms and empirical examples of this process. In relation to human moral capacities, group selection has the potential to account for aspects of human psychology and behavior – specifically those involved in human ultrasociality – that kin selection and reciprocal altruism seem insufficient to explain.

In the view of this author, a full explanation of the origins of human morality will appeal to natural selection at multiple levels as well as to processes of cultural evolution through which ethical norms are elaborated. Recent research suggests that cultural and biological evolution interact both to stabilize ethical behavior and to facilitate change in ethical norms over time in response to changing social and environmental conditions. Because scientists are still exploring the frontiers of multilevel selection theory, cultural evolutionary theory, and the interactions between cultural and evolutionary processes, few evolutionary ethical theories have fully integrated these ideas.

Assumption of Universal Decline

Negative stereotypes about the elderly are ubiquitous with respect to many domains of behavior and perceived attributes (Hess, 2006), even though some exceptions are found in attributed wisdom and altruistic behavior (cf. Pasupathi & Löckenhoff, 2002). Perhaps one of the most serious assumptions made by many psychologists is that of universal cognitive decline. While it is true that the proportion of individuals who show cognitive decline increases with each decade after the 60s are reached, it is equally true that many individuals do not show such decline until close to their demise, and that some fortunate few, in fact, show selective ability gains from midlife into old age. Figure 1.1 shows data from the Seattle Longitudinal Study to document this point (Schaie, 2013).

The data showing that there is no universal decline with increasing age of behavioral effectiveness however should not be interpreted as the absence of biological deficits with increasing age. In fact, disease-free aging is an infrequent experience for only a lucky few (cf. Solomon, 1999). Indeed, effective health behaviors are significantly associated with optimal aging (Aldwin, Spiro, & Park, 2006).

Other-regarding preferences

One way in which behavioral economists have tried to build psychologically plausible economic models is to model people as having “other-regarding preferences.” Some research has examined the nature and origin of altruistic behavior (e.g., [Andreoni, 1990; 1995]), while other research focuses on the taste for fairness [Guth et al., 1982; Kahneman et al., 1986]. There is extensive research on “social utility,” which shows that people care about relative outcomes, and specifically have a strong distaste for situations in which their outcome falls below that of the people to whom they compare themselves [Loewenstein et al., 1989; Fehr and Schmidt, 1999; Bolton and Ockenfels, 2000], and research on reciprocal altruism which addresses the common tendency to reciprocate both kind and unkind behavior directed toward the self [Rabin, 1993]. Because most of these models work by allowing agents to derive utility from the pleasure (or pain) of others, the fairness of the overall distribution of goods, and so on, they are strictly speaking consistent with neoclassical economics (which, as we know from section 2.2 above, makes no assumption about the arguments of the utility function). In this sense, then, there is not necessarily anything characteristically behavioral about models of other-regarding preferences.

New research in the area of other-regarding preferences is beginning to support a new perspective, according to which people are inherently selfish but have a desire to appear to others (and even to themselves) to be fair and generous [Dana et al., 2007; Benabou and Tirole, 2006]. This perspective can help to explain a wide range of phenomena, including, perhaps most importantly, the ability of small rewards to undermine generous behaviour [Gneezy and Rustichini, 2000]. These models are obviously consistent with the traditional neoclassical approach.

A Missing Link Between Empathy and Prosocial Motivation

One could be tempted to suggest that empathy, prosocial motivation, and behavior are correlated; if not even that they represent the same phenomena. However, there are many forms of “prosocial or altruistic” behaviors that need not co-occur with genuine prosocial motivation. For instance, subjects may “act” prosocially because they have learned (and maybe internalized) certain (pro)social norms and suffer when they—or others—deviate from them [56], because they aim to avoid the guilt of not helping [57], or, relatedly, because they want to preserve a positive image, both with regard to themselves [58], and with regard to real [59] or imagined [60] others. They may also act altruistically to elicit positive reciprocity from others [61] or avoid various forms of punishment that they might incur by acting selfishly [62]. These examples clearly show that genuine prosocial motivation is only one of the many routes to prosocial behavior.

Moreover, even when we do empathize with others, this alone may not be sufficient to induce prosocial motivation and behavior. In fact, it has been argued [17,63–65] that empathy can play out in at least two different ways: on one hand, the ability to empathize with others in pain could motivate subjects to help them, in order to relieve them of their pain. On the other, empathizers could be also motivated to relieve others of their sufferings just because, by doing so, they relieve themselves of their vicariously felt pain [66], thus reducing their own “negative arousal” [17,67]. Interestingly, this understanding interprets empathy-based prosociality as stemming from an egoistic motivation rather than just an altruistic one.

Notably, however, a number of experiments by Batson and colleagues (see Ref. [17] for a review) have been able to dissociate between these two motives. For instance, in one study [68] participants observed others receiving small (but uncomfortable) electric shocks and were subsequently offered the possibility of helping the victims by receiving shocks in their place. The authors then manipulated how “easy it was to escape” the “stressful” situation without helping. Specifically, in an “easy escape” condition, subjects were informed that (regardless of whether they decided to help or not) they would cease to observe the targets receiving shocks, whereas in the “difficult escape” condition, they knew they would have continued to observe the others suffering. The authors then manipulated the level of empathy by informing subjects that their confederates were similar or dissimilar to them. Notably, the authors found that, across both empathy conditions, subjects offered to help the confederates when escape was difficult. However, subjects in the low-empathy condition ceased to help their confederates when escape opportunities were easy, whereas subjects in the high-empathy condition helped similarly in both cases. On the basis of this and similar studies [17,63–65], the literature has emphasized an important difference between two possible consequences of empathy. Namely, if empathy leads only to (empathic) distress, then the final goal of one's motivation will become only to help themselves—and helping others may be (at best) instrumental to this. Conversely, if empathy leads to compassion (or empathic concern), then subjects will have the ultimate goal of helping others, and any relief to themselves that they may incur in the process of doing so is accidental. In synthesis, compassion could “fill the gap” between empathy and prosocial behavior.