While the Berlin wisdom model considers wisdom-related knowledge—knowledge about facts and strategies, but also about variability and uncertainty—as the key component of wisdom, Monika Ardelt has argued that wisdom really is a personality characteristic (Ardelt, 2003; Ardelt, Pridgen, & Nutter-Pridgen, 2019). Based on the findings by Clayton and Birren described earlier and on theoretical considerations, she argues that wise individuals have a specific personality structure which combines three dimensions: a cognitive dimension that consists of the deep desire to understand life; a reflective dimension defined as a general willingness to take different perspectives and to reflect upon oneself and one's behavior; and an affective dimension characterized by compassionate love for others. Ardelt certainly agrees with Baltes and colleagues that wise people have a lot of knowledge about life, but she believes that the personality dimensions are what enables people both to acquire that knowledge and to apply it to real-life problems. While the Berlin model assumes that wisdom can be learned from observing other people such as wise mentors, Ardelt has argued that wisdom is not gained by reading books or observing other people's lives: she believes that wisdom comes from personal, internalized insights that develop as people experience and navigate difficult challenges in their own lives (Ardelt, 2004. 2005). Such challenges, according to Ardelt, can change a person and make him or her wiser. Thus, while Baltes and colleagues assume that wisdom is a body of knowledge that can exist outside individuals—for example, in books or proverbs (Baltes & Kunzmann, 2004)—, Ardelt says that wisdom is inextricably connected to an individual's personal life story.

#### <IP_ADDRESS> Other Definitions of Wisdom

The Berlin Wisdom Model and the Three-Dimensional Wisdom Model are probably the two most-studied conceptions of wisdom. They are also typical examples of two types of definitions in wisdom literature: some definitions focus on aspects of wisdom-related knowledge and wise thinking (e.g., Grossmann, 2017; Sternberg, 1998, 2019), while others emphasize non-cognitive, attitudinal aspects of wisdom such as self-transcendence or humor (Levenson, Jennings, Aldwin, & Shiraishi, 2005; Webster, 2007). Table 16.1 gives an overview of

psychological wisdom definitions that can be found in literature.

At first sight, the definitions shown in Table 16.1 may seem to be about different constructs. However, few of them are incompatible with one another. As mentioned earlier, wisdom is a complex, multifaceted construct that integrates facets of knowledge and thinking, personality, and motivation. One important aspect that most wisdom definitions have in common, although not all of them make it explicit, is an orientation at a greater good than just one's own benefit. The common-good orientation of wisdom is most visible in Robert J. Sternberg's balance theory of wisdom (Sternberg, 1998, 2019). Essentially, Sternberg says that wisdom is practical intelligence that is utilized to balance different interests in a difficult situation so as to maximize a common good, rather than the benefit of any particular party.

In sum, wisdom has been defined in many different ways, but the definitions share some common characteristics. Typical elements of wisdom definitions include:

#### 16.2 How Can Wisdom Be Measured?

One reason why psychologists consider it important to have precise definitions of wisdom is that such definitions are necessary for developing methods to measure wisdom. Only if we have valid measures of wisdom, can we study how wisdom manifests itself and how it develops (Glück, 2018; Glück et al., 2013). The Berlin Wisdom Model and the Three-Dimensional Wisdom Model are not just prototypes for different definitions of wisdom; they are also good examples of two traditions in the measurement

of wisdom: one focusing on wisdom-related knowledge and thinking (overview in Kunzmann, 2019)

and one focusing on wise personality characteristics (overview in Webster, 2019).

Table 16.1: Some definitions of wisdom (adapted from Glück, 2015).

# 16.2.1 The Berlin Wisdom Paradigm and Other Measures of Wise Thinking

To measure wisdom as expert knowledge, Baltes and colleagues developed the Berlin Wisdom Paradigm (BWP). Participants are presented with brief descriptions of difficult life problems, such as "A fifteen-year-old girl wants to move out of her family home immediately." or "Someone gets a phone call from a good friend. The friend says that he cannot go on anymore and has decided to commit suicide." (e.g., Glück & Baltes, 2006; Staudinger & Baltes, 1996). They are asked to think aloud about what one could consider and do in such a situation. Participants talk about the problem for as long as they want; their responses are recorded, and transcribed. The response transcripts are then evaluated by trained raters with respect to the five criteria shown in Table 16.2.

A total of ten independent raters—two for each of the five criteria—are trained to rate the response transcripts on seven-point scales that range from "very little similarity" to "very high similarity" to an ideally wise response. The average across the ten ratings is then used as a participant's wisdom score. The Berlin Wisdom Paradigm is a reliable method, i.e., the two raters per criterion usually show good agreement and the ten ratings are sufficiently interrelated to form a meaningful score (Glück et al., 2013). Validity studies have shown that people who score highly in the BWP have more life experience than other people and are more intelligent and creative, more open to new experiences, and more oriented toward personal growth and supporting others (Kunzmann & Baltes, 2003; Staudinger, Lopez, & Baltes, 1997). Thus, even though the BWP mea-

Table 16.2: The five criteria for wisdom used in the Berlin Wisdom Paradigm.

sures wisdom-related knowledge, this knowledge is associated with non-cognitive variables relevant to wisdom.

More recently, Igor Grossmann built upon the BWP to develop a method for measuring *wise reasoning* (Grossmann, Na, Varnum, Park, Kitayama, & Nisbett, 2010; Oakes, Brienza, Elnakouri, & Grossmann, 2019). Grossmann and colleagues define wise reasoning as "the use of certain types of pragmatic reasoning to navigate important challenges of social life" (Grossmann et al., 2010, p 7246). Wise reasoning is characterized by dialectical thinking and intellectual humility as manifested, for example, in taking different perspectives, recognizing the limitations of knowledge, making flexible predictions, and searching for compromise. To measure wisdom, Grossmann and colleagues developed vignettes that describe difficult real-life societal or interpersonal problems, such as political conflicts in foreign countries or letters written to a newspaper columnist. Participants are presented with these vignettes and asked to write or talk about how these situations may unfold and why. As in the BWP, trained raters evaluate the transcripts with respect to criteria for wise reasoning. People who show high levels of wise reasoning have been found to be agreeable, nondepressed, and satisfied with their lives (Grossmann, Na, Varnum, Kitayama, & Nisbett, 2013).

Another measure of wisdom-related knowledge focuses on personal or self-related wisdom. As Ursula M. Staudinger has argued (Mickler & Staudinger, 2008; Staudinger, 2019; Staudinger, Dörner, & Mickler, 2005), some people are quite wise when they are thinking about someone else's problems, but have great difficulty applying their wisdom when it comes to themselves and their own problems. According to Staudinger, "general wisdom" is wisdom about life in general as it concerns other people, whereas "personal wisdom" is wisdom about oneself and one's own life. Measures like the BWP assess people's general wisdom. To measure personal wisdom, Mickler and Staudinger (2008) developed the *Bremen wisdom paradigm* (BrWP). In the BrWP, participants are interviewed about themselves as a friend—their typical behaviors, strengths and weaknesses, how they deal with difficult situations in friendships, and the reasons they see for

their own behavior. Participants' responses are rated for criteria that are somewhat parallel to those of the BWP, but apply to wisdom about oneself: selfknowledge (knowledge about one's strengths and weaknesses, priorities, and life meaning), heuristics of growth and self-regulation (knowing how to deal with challenges and grow from them), interrelating the self (seeing oneself in the context of one's social relations and life situation), self-relativism (being self-reflective and self-critical, but also having a healthy amount of self-esteem), and tolerance of ambiguity (recognizing and managing uncertainty and uncontrollability). As in the BWP, two raters per criterion rate each transcript, and their average is used as the wisdom score. People with high scores in the BrWP are intelligent, open to new experiences, and mature (Mickler & Staudinger, 2008).

The Berlin wisdom paradigm, Grossmann's measure of wise reasoning, and the Bremen wisdom paradigm all measure wisdom as a competence: a way of thinking about life challenges that is based on knowledge, intelligence, and ways of thinking that reflect an awareness of variability, uncertainty, and the limitations of one's knowledge. In all three approaches, people produce open-ended responses, which are then rated with respect to certain criteria as to what makes a response wise. Researchers who define wisdom as a matter of personality or attitude take a different approach to measuring it.

# 16.2.2 The Three-dimensional Wisdom Scale and Other Measures of Non-Cognitive Aspects of Wisdom

To measure wisdom according to her threedimensional model of wisdom as a personality characteristic, Monika Ardelt used the typical way psychologists assess personality: self-report scales. The *Three-Dimensional Wisdom Scale* (3D-WS, Ardelt, 2003) consists of 39 statements that reflect one of Ardelt's three dimensions of wisdom. Participants indicate the extent to which they agree to each of these items on five-point scales. For example, "Sometimes I feel a real compassion for everyone" is an item for the affective dimension. Many items in

the 3D-WS are reverse-coded. For example, "Things often go wrong for me by no fault of my own" measures the reflective dimension, but wise persons are expected to disagree with this statement, as they would always be aware of their own role in things that go wrong. "Ignorance is bliss" is a reversecoded item for the cognitive dimension, as a wise person is assumed to always want to understand things in depth. People's responses to the items are summed up to form separate scores for the three dimensions, and these three scores are then averaged into a wisdom score. People who score high in the 3D-WS have been found to have a strong sense of mastery and purpose in life, to be forgiving of others, not very afraid of death, and generally happy (Ardelt, 2003, 2011).

Jeffrey Dean Webster (2003, 2007) developed the *Self-Assessed Wisdom Scale* (SAWS), which defines wisdom as the willingness and ability to learn from life experiences and to utilize one's insights about life "to facilitate the optimal development of self and others" (Webster, 2007, p.164). The SAWS consists of 40 items that measure five components of wisdom. Critical life experience (having experienced difficult life challenges, e.g., "I have had to make many important life decisions") is considered as a prerequisite to developing wisdom. Reminiscence and reflectiveness (e.g., "I often think about my personal past") enables people to reflect upon and learn from their experiences and use them to deal with new challenges. Three personal characteristics help people to reflect upon experiences and grow wiser from them: openness (to perspectives, ideas, and inner experiences, e.g., "I'm very curious about other religious and/or philosophical belief systems"), emotional regulation (being able to perceive and regulate complex feelings, e.g., "I can regulate my emotions when the situation calls for it"), and humor (recognizing ironies and being able to laugh about oneself, which helps reduce stress and bond with others, e.g., "I can chuckle at personal embarrassments"). People with high SAWS scores are also high in ego integrity, generativity, forgiveness, and well-being, and they consider personal growth and supporting others as important values in their life (Webster, 2003, 2007, 2010).

Michael R. Levenson and colleagues defined wisdom as self-transcendence (Levenson et al., 2005). Drawing on conceptions from Buddhism, philosophy, and identity development in old age, they argued that wise individuals have acquired in-depth knowledge about themselves, understood that external things like money, success, or fame are not really essential to who a person is, and integrated and accepted the different aspects of their selves. These insights lead them to be at peace with themselves and to become self-transcendent—to care less about themselves and more about others and to feel deeply united with humanity, nature, and the world at large. The Adult Self-Transcendence Inventory (ASTI; Levenson et al., 2005; see also Koller, Levenson, & Glück, 2017) is a 34-item scale that measures self-transcendence and its predecessors, selfknowledge, non-attachment, and integration, using items like "My peace of mind is not easily upset" and "I feel that my individual life is part of a greater whole." People scoring high in the ASTI are open to new experiences, extraverted, non-neurotic and mature, and they often have experience with meditation and related practices.

Finally, the Brief Wisdom Screening Scale (BWSS; Glück et al., 2013) is not based on any specific theory of wisdom. It was developed based on a statistical analysis of data from a study that involved the 3D-WS, SAWS, and ASTI. The researchers used factor analysis to identify a common core across those three wisdom measures and then identified those 21 items from the three scales that were statistically most closely related to this common factor. In other words, the 21 items of the BWSS are closely related to one another and to what is common across the three wisdom self-report scales described earlier.

Other self-report wisdom scales include the Foundational Value Scale (Jason, Reichler, King, Madsen, Camacho, & Marchese, 2001) and the Wisdom Development Scale (Brown & Greene, 2006; Greene & Brown, 2009).

# 16.2.3 How Can Wisdom Best Be Measured?

The two approaches to measuring wisdom—openended measures and self-report scales—both have

some advantages, but also disadvantages. Selfreport scales are easy to administer. Study participants check their responses to each item, and researchers just need to sum up or average the responses into a wisdom score. The problem with selfreport scales, however, is that people's responses reflect who they think they are, which may not necessarily be who they really are. As an example, consider the item "I am good at identifying subtle emotions within myself." Wise people, being highly self-reflective, probably know how difficult it can be to disentangle the complex and ambivalent feelings they have in challenging situations. Therefore, they would probably partially, but not fully agree to this item. On the other hand, not-so-wise people may not even notice the complexity of their more subtle feelings in such situations, and might therefore happily select "fully agree." The more general problem is that humility and self-questioning are part of the wise personality, but a self-questioning person might be unlikely to describe him- or herself in a very positive way in a self-report scale. Thus, those people who receive the highest scores may not be the wisest ones, but the ones that are most certain of being "wise." In addition, of course, it is quite easy to intentionally "fake" wisdom in a self-report scale. If you want to try this out, fill out the ten items from the Brief Wisdom Screening Scale in Table 16.3

Glück Wisdom

twice—once as you would describe yourself, and once as you think a very wise person would. Thus, self-report measures of wisdom should always be taken with a grain of salt because they are susceptible to both socially desirable responding and to self-deception.

Open-ended measures do not have this problem: unless you know the criteria by which your response gets evaluated, it is a lot more difficult to produce a wise response to a vignette from the Berlin Wisdom Paradigm than to score high in a self-report scale. However, one problem remains: it may still be easier to talk wisely about what should be done in a theoretical situation involving a suicidal friend or a difficult teenager than to actually act wisely in such a situation in real life. Real-life wisdom requires not just wise thinking but also emotional strength and balance, self-reflection, and compassion—qualities that the BWP does not measure and that cannot really be inferred from a person's verbal response to a theoretical problem. Some researchers have tried to measure wisdom in ways that are closer to real life for example, by presenting participants with videos of real people discussing a conflict (Thomas & Kunzmann, 2013) or by asking participants about actual difficult challenges from their own lives (Brienza, Kung, Santos, Bobocel, & Grossmann, 2018; Glück, Bluck, & Weststrate, in press). A practical disadvan-

Table 16.3: Ten items from the Brief Wisdom Screening Scale. Check how much you agree to each item (1 = disagree completely, 5 = agree completely), then add up the numbers to compute your "wisdom score."

tage of open-ended measures compared with selfreport scales is that they require far more effort from both participants and researchers—participants are interviewed individually, responses have to be transcribed, raters have to be trained and paid. For this reason, most studies of wisdom used self-report scales, but more and more researchers try to incorporate at least one open-ended measure to ensure that their results are consistent across methods (e.g., Webster, Weststrate, Ferrari, Munroe, & Pierce, 2018; Weststrate & Glück, 2017a).

In sum, it is still an open question as to how wisdom can best be measured. While aspects of wise thinking should be assessed using open-ended measures, self-report scales may be the only possibility we have to access certain non-cognitive aspects, such as a person's feelings. An optimal measure of wisdom may need to integrate both approaches.

# 16.3 Is Wisdom a Stable Personal Characteristic—Or Are We All Wise Sometimes?

Most people think of wisdom as a quality of a small number of very special people. However, recent research shows that wisdom varies quite considerably by situation (Grossmann, 2017). Most of us have probably done a few very wise things in our lives—and a few very unwise things as well. For example, Glück, Bluck, Baron, and McAdams (2005) interviewed people about situations where they thought they had done something wise. Almost all participants were able to name at least one situation—making a difficult life decision, dealing with an unexpected emergency, learning to deal with a long-term problem—that they had handled wisely. Why were they able to do the wise thing in those situations, even if they weren't particularly wise people in general?—How wisely we act in real life depends not just on our wisdom-related knowledge and personality but also on whether we are able to utilize our knowledge and the relevant facets of our personality in a particular situation. For example, experiments have shown that people give wiser responses when they are instructed to use certain thinking strategies. Staudinger and Baltes

(1996) found that people responded more wisely to the BWP problem about the suicidal friend after spending ten minutes in an imaginary conversation about the problem with a friend. Interestingly, people also scored higher if they *actually* discussed the problem with a friend—but only if they had a few minutes to think about the discussion before responding. Thus, considering someone else's perspective on a problem may help us to act more wisely in a given situation. Similarly, Kross and Grossmann (2012) showed that so-called "selfdistancing" interventions improved people's wise reasoning. For example, Americans reasoned more wisely about the possible outcomes of U.S. elections if they tried to think about the elections from an Icelander's perspective than if they considered how the election outcome would affect their own lives. Grossmann and Kross (2014) showed that people reasoned more wisely about a relationship problem if they imagined the problem happening to a friend than if they imagined it happening to themselves. In fact, people even reasoned more wisely if they thought about a problem in the third person ("he/she") than if they were thinking in the first person ("I/me")!

Together, these findings suggest that people are wiser when they are able to mentally distance themselves from a problem and try to take various different perspectives on it than if they immerse themselves in it, taking a self-centered perspective. How well people can do this in real life, outside psychological experiments, certainly depends on what kind of person they are, but it also depends on the situation. If we are very angry or scared, for example, it is a lot more difficult to take someone else's perspective or even to think clearly about the best way to proceed.

Together, these findings show that wisdom is not just a matter of wise persons but also of situations. When we are able to take a step back and look at the broader picture, take the perspective of others, and acknowledge and regulate our feelings before reacting to a challenge, our wisdom has a far better chance to manifest itself. This brings up the question of how we can create situational contexts that foster wisdom. Wouldn't it be good if we could identify ways to make political, economic, or medical decisions wiser? As discussed earlier, Sternberg's balance theory of wisdom (Sternberg, 1998, 2019) states that a wise solution to a complex problem balances all the different interests involved, so that a common good is achieved. To be able to do that, it is necessary to be aware of all relevant interests and perspectives. Surowiecki (2005) has shown that groups can act more wisely than individuals if their members represent different perspectives and different areas of knowledge about the problem, and if all these different voices are heard and respected. It would seem to be possible to change the conditions under which, for example, political decisions are made so that such a culture can develop. Groups can, however, also make very bad decisions, especially if their leaders are unwise, i.e., foolish, and the group is structured in a highly hierarchical way.

Sternberg (2005; see also Sternberg & Glück, 2019) identified five fallacies that cause people in leading positions to make foolish decisions: *unrealistic optimism* (thinking one is so smart that everything one undertakes will end well, even if it looks to others like a bad idea); *egocentrism* (considering one's own needs and desires as the only thing that's really important); *false omniscience* (believing one knows everything and doesn't need to listen to others), *false omnipotence* (grossly overestimating one's control over things and therefore setting far too high goals), and *false invulnerability* (believing that one will not get caught or will not be hurt by the outcomes of one's decisions). These fallacies are clearly the opposite of wisdom, which is characterized, as described earlier, by a clear awareness of the limitations of one's knowledge and power, a willingness to take different perspectives, and a strong concern for the well-being of others. Unfortunately, power structures in many large organizations, including governments and large companies, tend to reinforce these fallacies: few people will speak up against their leader if it is likely to cost them their jobs. One of the most important applications of wisdom psychology to real life may be to develop ways to introduce wisdom-fostering structures into organizations.

# 16.4 Where Does Wisdom Come From?

In a world that is faced with difficult challenges climate change, global inequality, mass migration, political polarization, failing educational systems, and so on—, it seems very important to identify ways to increase wisdom. Broadly, there are two approaches to studying this question. First, some research has looked at how wisdom develops naturally over the course of people's lives. Second, studies have investigated how wisdom can be fostered through interventions—for example, by including teaching for wisdom in school and university curricula.

#### 16.4.1 The Development of Wisdom

How does wisdom develop, and why is it such a relatively rare phenomenon? Is it true that wisdom comes with age? And if it isn't, why do some people still become wiser over the course of their lives?

#### <IP_ADDRESS> Wisdom and age

When people are asked to name the wisest person they know, they usually come up with an older person (Weststrate et al., 2019). It makes a lot of sense to assume that wisdom comes with age: after all, wisdom is based on life experience, and life experience obviously accumulates over time. Older people have "seen it all", and they are in a phase of life where it may be easier to look back and see what is really important in life when one is no longer struggling to build one's own life. At the same time, few people agree that wisdom generally comes with age (Glück & Bluck, 2011)—we all know some older people who are anything but wise. How do these two notions fit together? Most wisdom researchers believe that many very wise people are, indeed, in the second half of life, but there are few of those very wise people in total (Jeste, Ardelt, Blazer, Kraemer, Vaillant, & Meeks, 2010). Most older people are quite happy and well-adjusted, but few are very wise.

There are a number of studies that looked at the relationship between wisdom and age in the general population. Virtually all of this research is crosssectional—that is, people of different ages were compared with respect to their levels of wisdom. These studies have produced surprisingly inconsistent results (Glück, 2019)—in fact, their results seem to be highly dependent on which measure of wisdom was used. For the BWP, a strong increase in wisdom has been found between the ages of about 15 and 25 (Pasupathi, Staudinger, & Baltes, 2001), but after that, wisdom-related knowledge seems to neither increase or decrease with age (Staudinger, 1999), although there may be a small decline in very old age. Scores in the 3D-WS actually are a bit lower in older age groups, mostly because older people have lower scores in the cognitive dimension of wisdom (Ardelt, 2003; Glück et al., 2013). Many older adults tend to think in less complex ways than young and middle-aged people do.

Recent research has found that wisdom as measured by the 3D-WS is highest in middle and late middle adulthood (Ardelt, Pridgen, & Nutter-Pridgen, 2018). The same pattern has also been found for the SAWS (Webster, Westerhof, & Bohlmeijer, 2014), whereas no relationship with age has been found for the ASTI (Glück et al., 2013; Levenson et al., 2005). Together, these findings would suggest that wisdom peaks in late middle adulthood, that is, in people's 50s and early 60s. However, Grossmann et al. (2010) found a linear positive relationship of wise reasoning with age well into participants' nineties, and Brienza, Kung, Santos, Bobocel, and Grossmann (2018) actually found a U-shaped relationship—that is, the lowest scores in middle age—for the SWIS. In sum, wisdom increases, stays stable, increases then decreases, decreases then increases, or just decreases with age, depending on which measure of wisdom is considered.

The most likely explanation for these inconsistencies is that the different measures emphasize different aspects of wisdom. As mentioned earlier, wisdom is a complex construct that includes several different components (Glück, 2019). Some of these components decrease with age in the general population—for example, openness to experience or the ability and willingness to think in very complex ways. Measures that focus on these components tend to produce lower scores in old age. Other components actually increase with age—for example,

compassion and concern for others or a willingness to make compromises and accept one's limitations. Measures emphasizing these aspects tend to produce higher scores in old age. It is important to also keep in mind that findings from cross-sectional studies are affected by so-called cohort effects: the people we compare in such a study differ not only in age, but also in the experiences they have had over their lifetime. The middle-aged and late middle-aged people who show high wisdom scores in current research were born in the 1950s and 1960s, that is, they came of age in the 1960s and 1970s, a period of time in which wisdom-related qualities may have been valued more highly than was the case for older and, perhaps, also for younger generations. For all these reasons, we do not have really conclusive evidence on the general relationship between wisdom and age yet. To understand how wisdom develops, it may be more important to look at individual developmental pathways over people's life courses. Longitudinal studies, which follow the same people over extended periods of their lives, have the potential to show us not just how age cohorts differ in wisdom but how individual life experiences shape a person's wisdom over time. For now, we have relatively little such evidence, but we have some theories about the development of wisdom that shed light on important factors.

# 16.4.2 Theories of How Wisdom Develops

As described earlier, Paul Baltes and colleagues (Baltes & Smith, 1990; Baltes & Staudinger, 2000) argued that wisdom is expert knowledge about the fundamental pragmatics of human life. The fundamental pragmatics of life are the "big issues" of human existence such as how we should live with the knowledge that we are going to die, how we can balance intimacy and autonomy in our relationships, or the complex moral dilemmas of our modern times. "Expert knowledge" (see Chapter 13, "Expertise") refers to an extraordinary amount of knowledge about a subject domain that is acquired through long-term, intense, goal-oriented practice. Baltes and Smith (1990) discussed in detail how wisdom might develop. They distinguished three types of factors that facilitate the development of wisdom:

According to the Berlin group, people's pathways to wisdom are very different depending on their unique life stories and life experiences. The MORE Life Experience Model (Glück & Bluck, 2013) specifies the role of life experiences in more detail. Its main assumption is that life challenges – experiences that deeply change people's beliefs about themselves or the world—are the main catalysts of the development of wisdom. Such challenges are often negative, such as a serious illness or a difficult conflict, but they can also be positive. For example, many people say that having their first child completely changed their priorities and needs. According to the MORE Life Experience Model, such experiences may not only change people's worldviews but also show them how much worldviews are shaped by experiences in general. For example, someone might learn from having a divorce or a baby not just that it is important to be attentive to one's partner or that unconditional love is possible, but also how little we know about situations that we haven't experienced ourselves. In other words, that person might gain insights that refer to the BWP criteria of lifespan contextualism, value relativism, and recognition of uncertainty.

Thus, life challenges can foster wise insights but not everybody gains wisdom from them. Especially after a negative experience, many people are not very interested in analyzing what happened they just want to regain their happiness and emotional balance (Weststrate & Glück, 2017a). Only those people who are willing and able to become "experts on life" are likely to explore the meaning

of an experience even if it may be painful for them. The MORE Life Experience Model proposes that certain psychological resources enable people on their way to wisdom to dig deeper into the meaning of life challenges. The most important resources are the following.

*Openness* is a general interest in multiple perspectives. People on the way toward wisdom are interested in how other people's worldviews, goals, and values differ from their own. They have no difficulty with seeking out advice and learning from others, and they are not afraid of new experiences in their own lives.

*Empathic concern*. People developing wisdom are compassionate with others and deeply motivated to alleviate their suffering. People who care deeply about others will strive for achieving a common good rather than for optimizing their own gain in complex situations (Sternberg, 2005). However, wise empathy is not simply taking on others' pain as one's own; it also involves being able to distance oneself so as to help another person optimally.

*Emotional sensitivity and emotion regulation*. People developing wisdom do not only pay attention to the feelings of others. They are also sensitive to their own emotions, and they are skilled at dealing with negative and mixed feelings. They try not to suppress negative feelings but to understand them and learn from them, while at the same time appreciating the positive things in life (König & Glück, 2014). They have learned to manage their emotions as a situation requires, which may sometimes mean recognizing but not showing one's feelings.

*Reflectivity* refers to the idea that people on the way to wisdom are motivated to understand complex issues of human life in their full complexity. Highly reflective people are willing and able to question their own beliefs because learning more about life is more important to them than feeling good about themselves (Weststrate & Glück, 2017a).

*Managing uncertainty and uncontrollability*. Most people tend to overestimate how much control they have over the things that happen in their lives. They believe, for example, that if they eat well and work out, they are never going to fall ill, or that professional success is simply a matter of hard work. People on the way to wisdom have learned from

experience that much in life is uncontrollable—that even people with a healthy lifestyle can have a heart attack, and that good or bad luck plays an important role in people's careers. While they know that something unexpected may happen at any time, however, they are not anxious or overly cautious because they have also learned to trust their own ability to deal with whatever may happen.

According to the MORE Life Experience model, people who have high levels of these five resources will

In this sense, gaining wise insights may not always make people happy. In the short run, it may make people happier to not question their own views, ignore unpleasant or complicated feelings, empathize only with their friends and family, and overestimate their control over their life (Staudinger & Glück, 2011; Weststrate & Glück, 2017b). Wisdom may come at a cost, and the path toward it requires a willingness to face the darker sides of human life.

#### 16.4.3 Wisdom Interventions

As discussed earlier, the current state of our world suggests that we urgently need to find ways to foster wisdom—in individuals as well as in systems and institutions. Research, up to now, has focused on ways to increase individual wisdom. As described in section 3, several studies have shown that short-term interventions can help people access their wisdomrelated knowledge and mindset. These interventions

include imagining discussing a problem with someone else (Staudinger & Baltes, 1996) or imagining that the problem does not concern oneself but someone else (Grossmann & Kross, 2014; Kross & Grossmann, 2012). Another class of interventions consists, of course, of actually discussing a problem with someone else, which has been found to foster wisdom in an experimental setting (Staudinger & Baltes, 1996) as well as in retrospective accounts of real-life experiences (Igarashi, Levenson, & Aldwin, 2018). In this vein, a promising approach to fostering wisdom might lie in simply instructing people to ask for, and listen to, information and advice from others if they are facing a difficult problem. But what characterizes wise advice? It is an interesting and understudied question how wise people give advice to others.

As discussed earlier, in addition to increasing wisdom in individuals, it seems important that we look more into the way situational contexts can foster wisdom (Grossmann, 2017; Surowiecki, 2005). Why, for example, do interactions in online discussion boards often become uncivil and polarized, especially when they are about an ideological or political topic? Perhaps simple interventions, such as having users rate the wisdom of each statement instead of "liking" or "disliking" it, might create an incentive for more balanced and constructive conversations.

In addition to such situational short-term interventions, researchers have discussed how wisdom could be implemented as a goal in more long-term interventions, such as school curricula or psychotherapy. Sternberg (2001; Reznitskaya & Sternberg, 2004) suggested teaching for wisdom in schools, criticizing that today's curricula focus on academic intelligence at the expense of wisdom and ethics. He argued that exercises such as reflecting on and discussing one's own values, possible consequences of decisions, or ethically relevant topics in classes on history or social sciences can have a long-term effect on the development of wisdom. Michael Linden and colleagues, on the other hand, argue that psychotherapy can explicitly focus on elements of wisdom such as perspective-taking or emotion regulation (Linden, Baumann, Lieberei, Lorenz, & Rotter, 2011). In a broader sense, one could argue that many general goals of psychotherapy, such as increased selfGlück Wisdom

individually, we need to learn how to make decisions that are not just smart but wise—decisions that balance our own interests with those of others and

reflection, awareness and regulation of emotions, and empathy are also components of wisdom.

In a world that is facing enormous global challenges, the psychology of wisdom may have important contributions to make. Globally as well as

Summary

1. What is wisdom? There are a number of definitions of wisdom in psychological literature. Wisdom is a complex and multifaceted construct, and different definitions tend to emphasize different aspects of it. The most important components of wisdom are (a) broad and deep life experience and life knowledge, (b) an awareness of the variability and uncertainty of human life and a willingness to consider different perspectives, (c) self-reflection, self-knowledge, and self-acceptance, and (d) compassionate concern for others and a motivation to serve a greater good.

the world at large.

#### Review Questions

# Hot Topics: Wise Solutions for Complex Global Problems

Judith Glück (Photo: Barbara Maier)

What can we do to make today's world wiser? Our world is faced with enormous global challenges including climate change, global inequality, political polarization and rising populism, the negative effects of digitalization, and educational systems that seem to fail at teaching students how to navigate these challenges. What are wise ways to deal with these problems? While earlier wisdom research has focused on wisdom as a characteristic of persons, more recent research is beginning to understand how situations foster or hinder wisdom. To develop wise solutions to complex world problems, however, we need to learn more about the processes of making wise decisions. If, as Robert J. Sternberg (2019) argues, wisdom involves a balancing of different interests that optimizes a common good, how exactly does it achieve this goal? There is a large body of scientific research on judgment and decision-making, but most of these studies have focused on problems that have pre-defined

optimal solutions. New research is needed that identifies wise approaches to solving complex, ill-defined problems. Another open question is how we can create systems that invite or reward wise behavior, e.g., from politicians and policymakers. Recent political developments show that voters are not necessarily attracted by wise political candidates (Sternberg, 2019), so other mechanisms are required to ensure a certain level of wisdom in politics. All democratic countries have constitutional checks and balances that are supposed to protect them against undemocratic developments. However, the recent rise of populism in many Western democracies (Levitsky & Ziblatt, 2018) sheds doubt on the efficacy of these processes in a time of social media and ideological polarization. Wisdom research needs to investigate how political systems can contribute to wise politics, and how people can be made more aware of the importance of wisdom for the survival of our planet.

#### References

Levitsky, S., & Ziblatt, D. (2018). *How democracies die*. New York: Crown Publishing.

Sternberg, R. J. (2019). Why people often prefer wise guys to guys who are wise: An augmented balance theory of the production and reception of wisdom. In R. J. Sternberg & J. Glück (Eds.), *The Cambridge handbook of wisdom* (pp. 162–181). Cambridge: Cambridge University Press. doi:10.1017/9781108568272.009

#### Glück Wisdom

# References

*sonality and Social Psychology*, *115*(6), 1093–1126. doi:10.1037/pspp0000171

*Series B: Psychological Sciences*, *73*, 1350–1358. doi:10.1093/geronb/gby002

bitterment disorder with cognitive behaviour therapy based on wisdom psychology and hedonia strategies. *Psychotherapy and Psychosomatics*, *80*(4), 199–205. doi:10.1159/000321580

*tives* (pp. 191–219). New York: Cambridge University Press. doi:10.1017/CBO9780511610486.009

# Glossary

of them have in common is that they dedicated their lives to a cause that benefited many people and changed the world by peaceful means. 308

# Chapter 17

# Development of Human Thought

#### KATHLEEN M. GALOTTI

#### Carleton College

My then fourteen-year-old daughter wanted to upgrade her cellphone to an expensive smart phone model. She "mentioned" this topic several days a week, for several months. At first, she described all the advantages for her, personally: she'd be able to take more pictures, use Instagram and Snapchat more easily, and text more friends for free. Although numerous, none of these reasons were particularly compelling for me. Eventually, she created a several-slide powerpoint, describing costs and benefits that *did* matter to me—including being able to track where she was, the ability to create a local hotspot for the internet, and chores she promised to do if/when she got the model of phone she was angling for. So persuasive was she that I ended up getting two iPhones—one for each of us (thanks to a two-for-one special).

This ability to plan and marshall a convincing argument illustrates a textbook example of a developing cognitive ability. In earlier points of her development, my daughter could do little more than express her desires (often loudly) or offer one-sided and non-compelling arguments ("I really, really, *really* want it"). Her proclivity to adopt my point of view and use that to offer reasons and incentives that persuaded me to adopt her perspective is a gradually emerging ability, and one that will be the focus of this chapter.

First, we'll talk about different realms of thought, including problem-solving, reasoning, decision making, planning and goal setting. All of these terms

come under the broader term of thinking, and we will explore definitions and connections among these various instances of thought. We will then take a chronological look at how these different realms of thought develop. We will look at some precursors in infancy and the toddler years. We'll have much more to learn about the development of thought in the preschool years, when children become much more verbal. Examination of the elementary school years will show that children gather a lot of information to construct a knowledge base, even as they refine many of their thinking skills. Finally, we'll see dramatic improvements in many if not all realms of thinking when we examine adolescence and young adulthood.

# 17.1 Defining the Domain: Realms of Thought

Let's start by defining a few key terms that we'll be discussing in this chapter. Consider the term, *thinking*. It's a pretty broad term and used to cover a lot of different kinds of mental activities, including making inferences, filling in gaps, searching through mental spaces and lists, and deciding what to do when in doubt. I'll use it in this chapter as the overall label for mental activities that process information.

The terms problem solving, reasoning and decision making are often used interchangeably with the term *thinking*. Many psychologists see the first

three as special cases of the fourth. Specifically, when cognitive psychologists speak of problem solving, they refer to instances where a person is trying to see a solution to some sort of impediment (see Chapter 9, "Problem Solving"). When they speak of reasoning, they mean a specific kind of thinking done to draw inferences, such as you might do in solving certain puzzles or reading a mystery novel (see Chapter 7, "Deductive Reasoning", and Chapter 8, "Inductive Reasoning"). Reasoning often involves the use of certain principles of logic. The term, *decision making*, then, refers to the mental activities that take place when one chooses among alternatives (see Chapter 10, "Decision Making").

Goal setting as used here means a mental activity in which one sets specific intentions to achieve some specific objective or aim. This term is intertwined with planning, which indicates a projection into the future of a trajectory by which goals can be attained, including sourcing the materials and resources needed and taking the steps necessary to achieve an objective.

It is important to note here that thinking tasks we'll talk about make use of two other important cognitive realms: language, and the knowledge base. Language refers to the ways people comprehend and produce utterances (whether in speech or in writing; see Chapter 11, "The Nature of Language", and Chapter 12, "Language and Thought"). Being a proficient language user certainly helps when it comes to understanding and expressing one's arguments, decisions, or plans.

The knowledge base refers to the sum total of stored information that an individual possesses (see Chapter 4, "Concepts: Structure and Acquisition", and Chapter 5, "Knowledge Representation and Acquisition"). For example, I know hundreds of thousands of words; I have previously memorized multiplication tables up to 12 and can quickly retrieve from memory many multiplication facts; I remember names of teachers and classmates from my kindergarten year up through graduate school; I also know about parenting, dog training techniques, mystery stories, *Pokemon Go* and some television series (currently I'm binge-watching *Scandal*). When people think, they think *about* things, and the richer

their knowledge base, the richer their thinking about propositions derived from it.

With those introductory remarks in mind, let's turn to a chronological look at the development of thinking in infancy through adolescence.

# 17.2 Infancy and Toddlerhood

It might seem a little incongruous to have a section on thought in infancy. After all, one of the great cognitive developmental theorists, Jean Piaget, argued that infants were at a stage of development where, essentially, they did not have thought (Piaget, 1952). Piaget believed that individuals passed through a series of stages in their cognitive development, with each stage defined by a qualitatively different set of intellectual structures through which the individual processed information and understood the world. The first stage of cognitive development, which operates from birth to roughly 2 years, was named the *sensorimotor* stage by Piaget, because his belief was that infants and toddlers were limited in their cognition to sensory experiences and motor responses. Put another way, from birth through the first 18 to 24 months, infants and toddlers were said to lack a capacity for mental representation, the ability to construct internal depictions of information.

One of Piaget's most famous demonstrations of (the lack of) infant cognition is on the so-called "object permanence" task, depicted in Figure 17.1. A young (say, five- or six-month-old) infant is seated facing a desirable object or toy. Suddenly, some sort of screen is placed between the infant and the object. Typically, the infant fairly immediately appears to lose all interest, as if the object or toy has somehow ceased to exist!

Because he believed that infants lack that capacity, Piaget would conclude that infants really don't do very much, if any, "thinking." However, some recent work has challenged Piagetian interpretations of infant cognition, and reawakened the idea that infants do have some knowledge and some rudimen-

Figure 17.1: According to Piaget, until object permanence develops, babies fail to understand that objects still exist when no longer in view. Source: Galotti (2017, p.113).

tary mental activity that can be clearly labelled as "thinking."

One of the most prolific researchers posing this challenge to Piaget is psychologist Renée Baillargeon. Here, we will only cover a small fraction of her elaborate body of work. In one classic study (Baillargeon, 1986), she seated infants (6-8 months old) in front of a screen set up to the right of an inclined ramp. During the first phase of the study, infants saw the screen raised and lowered. Behind the screen was a track for a small toy car. After the screen was lowered, infants saw a small toy car go down the inclined ramp and to the right, behind the screen.

Next, infants were given the impossible/possible events task, in which they were tested with one of two events—the first, a "possible" event, occurred when the screen was raised. It revealed a box sitting behind the track. As in the first phase of the study, after the screen was lowered, the car rolled down the ramp and across the track behind the screen. The second, "impossible" event was very similar to the possible event, except that the box was actually placed *on* the track instead of behind it.

Now, according to Piaget, 6-month-old infants ought not to react any differently to the "possible" than to the "impossible" event. Lacking a sense of object permanence, they should be just as unsurprised to see a car roll in front of a box as "through" a box—after all, if infants have no expectations of objects continuing to exist when hidden behind a screen, then they would have forgotten all about the

existence of the occluded box anyway. But Baillargeon's results showed something clearly at odds with Piagetian predictions. Her 6.5- and 8-monthold participants, and even some 4-month-old female participants, looked longer at the "on-track" "impossible" event. Baillargeon interpreted this result to mean that the infants "(a) believe that the box continued to exist, in its same location, after the screen was lowered; (b) believed that the car continued to exist, and pursued its trajectory, when behind the screen; (c) realized that the car could not roll through the space occupied by the box; and hence (d) were surprised to see the car roll past the screen when the box lay in its path" (Baillargeon, 1999, p. 128).

In a related study, Baillargeon and DeVos (1991) presented infants 3.5 months old with an unusual stimulus display. Each infant saw one of two events first. These events presented either a short carrot or a tall carrot moving behind a large rectangular yellow screen, followed, a few seconds later, by the emergence of an identically appearing carrot appearing from the right-hand side of the screen. In other words, it looked as though the same carrot simply traveled behind the occluding screen. After a 1-second pause, the experimenter slid the carrot back behind the yellow occluding screen, paused for 2 seconds, and then slid the leftmost carrot out from behind the left edge of the screen. This cycle of carrots disappearing and reappearing continued until the infant reached a predetermined criterion of amount of time looking at the stimulus or looking away having previously attended to it.

Next came either a "possible" or "impossible" event. This event was the same as the corresponding habituation event, *except that* the occluding screen had a new color, blue, meant to draw infants' attention to the fact that the screen was new. It also had a new shape: a large rectangle with a smaller rectangle "cut out" from the top. The idea was that short carrots ought to fit completely behind the new screen all the way across, and thus the possible event ought not to have been perceived as all that surprising. However, a tall carrot would *not* have fit behind the new screen—its top ought to have been visible as it moved through the "cut out" portion of the screen if it were moving from one end to the other. Thus, the tall carrot moving behind the new screen ought to have been an impossible event.

Results showed that although infants looked for an equal amount of time at the two habituation events (i.e., tall vs. short carrots moving behind the rectangular yellow screen), they looked longer at the impossible than the possible test event. Baillargeon and DeVos (1991) took this result as evidence that their three-and-a-half-month-old infants "(a) realized that each carrot continued to exist after it slid behind the screen, (b) assumed that each carrot retained its height behind the screen, (c) believed that each carrot pursued its trajectory behind the screen, and therefore, (d) expected the tall carrot to be visible in the screen window [the opening in the blue test screen] and were surprised that it was not" (p. 1233).

These conclusions (and others from Baillargeon's additional studies not described here) strongly suggest that even fairly young infants possess a fair amount of knowledge about what objects are and how they behave. Baillargeon (2008) believes that infants begin with an innate principle of persistence, "which states that objects persist, as they are, in time and space" (p. 11). From this initial knowledge, infants gather perceptual information and use it to construct more complex and detailed representations of objects and, in so doing, learn more about how objects behave and what their properties are. So, if you believe Baillargeon's interpretations (and not everyone does; see Cohen & Cashon 2013 for a critique), young infants *do* have some knowledge about objects. What about knowledge about social beings?

In a recent review, Baillargeon, Scott, and Bian (2016) present evidence from many different studies from many different laboratories that young infants and toddlers can reason about agents' goals and states and can use this information to predict an agent's future actions. Here's just one example (from Woodward, 2009): an infant sees an adult seated at a table with two different toys (let's call them A and B) in front of her. She reaches for and grasps one of the toys (A). Infants watch repetitions of this action for some predetermined amount of time, becoming habituated to seeing this action. Next, they see the same adult in front of the same two toys, which have now traded positions. Infants as young as five months look longer when the adult reaches for the new toy (B) than they do when the adult reaches for (A). According to Baillargeon et al (2016) these infants: "(a) attributed to the agent a preference or liking for object A, as the agent always chose it over object B, and (b) expected the agent to continue acting on this preference. . ." (p. 162). This finding has been replicated in several laboratories.

Baillargeon along with other developmental psychologists such as Elizabeth Spelke and Susan Carey argue that infants are born with some amount of "core knowledge." The existence of these innate systems does not imply that infants can articulate all their principles. Indeed, infants aren't known for their articulation abilities in any domain. Instead, the implication here is that infants come into the world prepared to make certain assumptions, entertain certain hypotheses, or hold certain expectations of the way objects will or won't behave. Thus, they do have some knowledge, and thus, they can do some rudimentary reasoning about it.

### 17.3 The Preschool Period

It is in the preschool period that we see the first glimmers of what cognitive psychologists call "higher order cognitive processes"—processes that operate on mental representations. These glimmers are fleeting and fragile, but also unmistakable signs of growing maturity of thought.

One of my personal favorite demonstrations of preschooler reasoning competence comes from the work of Hawkins, Pea, Glick, and Scribner (1984). They demonstrated that, under certain circumstances at least, preschoolers aged 4 and 5 years could draw deductive inferences (see Chapter 7, "Deductive Reasoning"). They began by constructing various reasoning problems, examples of which are shown in Table 17.1. There were three types of problems. The first consisted of premises that were congruent with the child's world knowledge—for example, "Bears have big teeth. Animals with big teeth can't read books. Can bears read books?" Note that whether a child actually reasoned from the premises or from her world knowledge of the general illiteracy of bears, she would have arrived at the deductively correct conclusion, "No." Preschoolers were expected to do particularly well on these problems, even if their scores overstated their true reasoning ability.

A second type of problem included information that was incongruent with the child's world knowledge—for example, "Glasses bounce when they fall. Everything that bounces is made of rubber. Are glasses made of rubber?" Here, the real-world correct answer is directly at odds with the answer a reasoner would derive from strictly reasoning from the premises to answer the question. Preschoolers were expected to do particularly poorly on these problems, as it was expected they would answer the questions using their world knowledge rather than use abstract reasoning to derive a valid conclusion.

The most theoretically interesting type of problem was one using so-called "fantasy" premises—for example, "Every banga is purple. Purple animals always sneeze at people. Do bangas sneeze at people?" Notice that in these problems, there is no relevant world knowledge for the child to call upon. Hawkins et al. (1984) believed, then, that fantasy problems would be the ones most likely to reveal whether or not preschool children could, in fact, draw logical inferences.

The results were clear-cut. Children were presented with 8 problems of each kind. Overall, children gave correct responses to 7.5, 1.0, and 5.8 congruent, incongruent, and fantasy problems, respectively. A chance level of performance was 4, and thus children performed significantly better than chance on the fantasy (and congruent) problems. Thus, the authors concluded, preschool children, under limited circumstances, *can* reason deductively.

Moreover, the order in which the problems were administered was crucially important. Children who reasoned with fantasy premises first tended to perform better on all problems, even the congruent and incongruent ones, than did the children who received congruent problems first, incongruent problems first, or problems in a jumbled order. Hawkins et al. (1984) argued that presenting fantasy problems first sets a context for children to help cue them as to how to correctly solve the problem. When congruent or incongruent problems were presented first, children mistakenly recruited their real-world knowledge to answer the questions, instead of relying strictly on the premises.

Of course, being able to draw a deductive inference in certain circumstances does not prove that preschoolers are fully capable of deductive reasoning. Adults can reason better than preschoolers on just about every problem, but do especially well with incongruent content. Indeed, Markovits and Barrouillet (2004) argue that what happens with cognitive development is increasing control over complex forms of reasoning, and being able to divorce one's store of knowledge about the world from the information presented in the premises to a problem.

Another important development in children's thinking in the preschool period concerns the development of theory of mind. A person's theory of mind is the ability to reason about mental states (Apperly, 2012). Thus, theory of mind guides a person's beliefs and expectations about what another person is thinking, feeling, or expecting; it guides one's ability to predict accurately what another person's reaction will be to a specific set of circumstances (Flavell, Green, & Flavell, 1995). This ability develops rapidly between the ages of two and five.

One common task used to investigate preschool children's theory of mind is the so-called *false belief task* (Wimmer & Perner, 1983). For example, children might be told a story about a boy who puts a toy in a box and leaves the room. While he is away, his sister enters the room, takes the toy out of the box, plays with it, and puts it away in a different location. Children are then asked where the *boy* (who was not present in the room at the time the toy was

Model Affirmative Example Negative Example A is B Every banga is purple. Bears have big teeth. B is C Purple animals always sneeze at people. Animals with big teeth can't read books. A is C Do bangas sneeze at people? Can bears read books? A has B Pogs wear blue boots. Rabbits never bite. C is an A Tom is a pog. Cuddly is a rabbit. C has B Does Tom wear blue boots? Does Cudly bite? A does B when ... Glasses bounce when they fall. Merds laugh when they're happy. B is C Everything that bounces is made of rubber. Animals that laugh don't like mushrooms. A has C Are glasses made of rubber? Do merds like mushrooms?

Table 17.1: Types of problems used by Hawkins, Pea, Glick, and Scribner (1984). Source: Galotti (2017, p. 230), adapted from Hawkins, Pea, Glick, and Scribner (1984, p. 585).

moved) will think the toy is. In other words, can the children disentangle their own state of knowledge about the toy from the state of knowledge or belief of someone who lacks their information?

Another theory of mind task is the *unexpected contents task* (e. g., Gopnik & Astington, 1988), in which a child is handed a box of, say, crayons but opens it to discover that the box really contains small candies. The child is then asked to predict what another child, who has no previous experience with the crayon box, will think is inside. Typically, children younger than about 4 years answer that they knew all along that the box contained candies rather than crayons, even though they initially answered "crayons" when asked what was in the box. Further, young preschoolers respond that someone else coming into the room later will think that the crayon box contains candies rather than crayons.

Apperly (2012) makes the argument that although theory of mind is studied widely in preschoolers, it's a mistake to believe that only preschoolers struggle with this concept. Infants, as we've just seen, have some (if incomplete) knowledge about others' goals; adults show stable individual differences in their ability to predict others' motivations and intentions. Thus, theory of mind is not something that a child "finishes" developing at age 5. However, most researchers agree that there is rapid development in theory of mind during the preschool period, and it seems to correlate with developments in language, pretend play, symbolic understanding, and inhibitory control, the ability to maintain focus and resist the temptation to become distracted (Carlson, Moses & Claxton, 2004; Lillard & Kavanaugh, 2014; Wellman, Cross, & Watson, 2001).

# 17.4 Middle Childhood

One of the more noticeable aspects of cognitive development in middle childhood is the growth of the knowledge base (see Chapter 5, "Knowledge Representation and Acquisition" ). School-aged children in the United States learn an incredible amount of what adults would consider "basic" information vocabulary words; how to read; how to use different punctuation marks; addition, subtraction, multiplication, and division facts; historical and geographical facts; information about certain authors; and information about animals, planets, and machines, to take just a few examples from my children's elementary

school's curriculum. Add to that knowledge of domains that aren't formally taught in schools—how to play *Minecraft*, how to operate an iPhone, or characters from the *Magic Tree House* or *Harry Potter* book series are just a few examples.

With this tremendous acquisition of knowledge going on, children need to find efficient ways of storing and representing it. (As an analogy, think about files on your laptop. It didn't matter very much what you called them when you only had a small number, but when you get up into the thousands of files, how you organize them might well determine whether or not you are ever going to find a particular one again.) How children represent and organize their knowledge is certainly a matter of active debate and discussion in the field. Presumably, their knowledge bases underlie their ability to draw inferences from examples they see. Like so many other topics in this chapter, we'll only have space to cover a couple of examples.

Kalish, Kim, and Young (2012) reported on three studies of preschoolers and young school-aged children that we will focus on. The task presented children with a number of individual examples of a category, e.g., small plastic frogs or dinosaurs that were either yellow or blue. Typically, children would first see a *biconditional relation* between color and species. For example, they might be shown four yellow dinosaurs and four blue frogs, one at a time. What makes this relationship *biconditional* is that all yellow things are dinosaurs, and all dinosaurs are yellow.

In a second phase of the task, children were presented (again, one at a time) with examples some of which undermined the biconditional relationship. For example, children might see six yellow frogs and two yellow dinosaurs. So, after this information is presented, it is no longer true that all yellow things are dinosaurs, nor that all frogs are blue. However, there are *conditional* relationships that remain true even after this phase of the task. For example, the relationship, *If an item is a dinosaur, it is yellow* remains true, although it allows for the possibility of other yellow things, for example, frogs, existing.

Older (seven-year-old) children were able to see that some conditional relationships (*if dinosaur, then yellow*) were true after the second phase of the task even though the biconditional relationship (*all and only yellow things are dinosaurs*) were not. That is, they were able to revise their beliefs about what relationships held in light of new evidence. The ability to make this revision seemed, in contrast, to escape the five-year-olds.

These results echo ones reported earlier by Deanna Kuhn (1977) who presented children aged 6-14 with conditional reasoning problems all pertaining to the fictional land of Tundor. She began with a pretest disguised as a game where she would give them one piece of information about Tundor (e.g., "John is tall, and Bob is short") and then ask questions (e.g., "Is Bob tall?") to which the child could respond "yes", "no", or "maybe." The pretest gave examples of questions that could be answered definitively as well as ones that could not, based on the given information. Only children who correctly answered both pretest questions were allowed to continue.

Next, Kuhn (1977) gave children conditional reasoning problems. For example, "All of the people in Tundor are happy. Jean lives in Tundor. Is Jean happy?" (The correct, logically valid answer is *yes*, and this is considered a fairly easy inference to draw) or, "All people who live in Tundor own cats. Mike does not live in Tundor. Does he own a cat?" (Here, the correct answer is *maybe*; no logically necessary inference can be drawn; though even adults make mistakes on this type of problem). Kuhn found that even the first graders show some reasoning ability, particularly on easy problems. Children did less well on the more difficult problems (the ones adults make mistakes on), unsurprisingly. In similar studies, Janveau-Brennan and Markovits (1999) conclude that children are likely reasoning in ways fundamentally similar to the way adults reason, at least by the time they are in middle childhood, and when they are reasoning with concrete kinds of content rather than abstract propositions.

#### 17.5 Adolescence

Cognitive developmental psychologists have long noticed another major change in thinking that occurs right around puberty. Adolescents are much

more capable than younger children of thinking hypothetically, and about the future; and to be able to think abstractly versus only with concrete instances as they were in childhood (Byrnes, 2003; Galotti, 2017). A now-classic study by Daniel Osherson and Ellen Markman (1975) illustrates this last point very well.

Children, adolescents, and adults were shown small plastic poker chips in assorted solid colors, and were told that the experimenter would be saying some things about the chips and that they should indicate after each statement if it was true, if it was false, or if they "couldn't tell." Some of the statements were made about chips held visibly in the experimenter's open hand. Other, similar statements were made about chips hidden in the experimenter's closed hand. Among the statements used were logical tautologies (statements true by definition)—for example, "Either the chip in my hand is yellow, or it is not yellow"; logical contradictions (statements false by definition)—for example, "The chip in my hand is white, and it is not white"; and statements that were neither true nor false by definition but depended on the color of the chip (e.g., "The chip in my hand is not blue and it is green").

Younger children (those in grades 1, 2, 3 and even 6) had difficulty distinguishing between statements that were empirically true or false (i.e., true in fact) and those that were logically true or false (i.e., true by necessity or definition). They did not respond correctly to tautologies and contradictions, especially in the hidden condition. They tended to believe, for example, that a statement such as "Either the chip in my hand is red, or it is not red" cannot be assessed unless the chip is visible. Tenth graders and adults, in contrast, were much more likely to respond that even when the chip couldn't be seen, if the statement was a tautology or contradiction, the statement about it could be evaluated on the basis of the syntactic form of the sentence. Said another way, adolescents and adults are able to examine the *logical!form* of a statement, instead of insisting that none of the "hidden" statements could be evaluated.

Thinking about the future is also an important emerging capability in adolescence (Nurmi, 1991). Being able to project oneself into a future context requires an ability to think beyond the current set of

circumstances. For example, most sixteen-year-olds in the United States are high school students who live with parents or guardians. But as they prepare for adult life, they have to be able to imagine what it will be like to live independently, find and keep a job, decided on whether and what kind of further education they will seek, among other life-framing decisions.

This kind of thinking is crucial to what cognitive developmental theorists call identity development. This term refers to the development of a mature sense of who you are and what your goals, values, and principles are. Lifespan developmental psychologist Erik Erikson (1968) was the first to highlight the construction or discovery of identity as a major developmental task, typically first encountered during adolescence. Psychologist James Marcia (1966), however, is the one credited with operationalizing this idea and developing measures to study it.

Marcia (1966) saw identity development as proceeding through two or more phases, and these are depicted in Figure 17.2. Marcia asserted that identity status is defined jointly by two factors: whether or not the person had made a definite choice or commitment (e.g., to a career, to a value system, to a romantic partner) and whether or not the person had gone through some sort of "crisis", or period of active doubt and exploration, in making that choice.

A teen in the *identity diffused* status has not made any commitments and has not developed a relevant set of values or principles with which to guide his goal setting and decision making in a given realm (e.g., career, education, political philosophy, religious affiliation). He has not experienced a period of crisis or doubt but, rather, either is in the early phase of identity development or is simply drifting along, with no set plan for the future.

An adolescent in the *foreclosure* status, in contrast, is very committed to a plan and/or to a set of values and principles. Similar to her identity diffused colleagues, however, she has never experienced a crisis or period of doubt. Typically, this indicates that she has adopted someone else's goals and plans, most often those of a parent or another significant adult figure. Thus, adolescents in this status tend to have a very narrow vision for their future—and not much autonomy or power in mak-

Figure 17.2: Marcias Identity Statuses. Source: Galotti (2017, p. 399).

ing decisions. Students at my college who enter my office on their very first day of college, announcing they are "premed" or "prelaw" because both of their parents are doctors or lawyers and they've known since they were 5 what they'd be, tend to present rather textbook examples of foreclosure.

The *moratorium* identity status is often typified by college students who "want to keep all their options open." They are actively exploring different options, experimenting and trying on for size the possibility of different majors, different careers, and different religious or political affiliations. The moratorium student is usually struggling and not in what others would call a "stable" state—that is, this individual is likely to remain in this period for only a brief period—a year or two (Moshman, 2011). Moratorium is a period of delay, in which the individual knows that a commitment must soon be made but is not yet ready to make it. Individuals in this status usually either resolve this crisis in a positive way, moving into the identity achieved status, or, in less successful cases, retreat into identity diffusion.

Marcia (1966) held that only individuals who experienced moratorium could move into the *identity achieved* status. The individual here has made one or more personal commitments, after having struggled to find her or his own path toward that decision. This student has considered alternative options and weighed both the pros and the cons. This status is seen as marking a successful end to adolescent development, as a bridge has been built from one's childhood to one's future adulthood. Accompanying identity achievement are increases in self-acceptance.

Many theorists find Marcia's (1966) proposal a useful analogy for understanding one major realm of adolescent development (Moshman, 2011). Identity encompasses an adolescent's value system as well as her view of knowledge and herself as a learner and an agent in the world.

# 17.6 Conclusion

Our look at the development of thought has been brief and selective. I've tried to give you some flavor of the changes occurring during the first two decades of life when it comes to higher-order cognitive processes. We have seen a gradual increase in knowledge of the world—the inputs used in thinking and reasoning and decision making. Although infants are not without relevant knowledge of the world, certainly they have much less when compared with a child in third grade or an adolescent. We've also seen that thinking becomes more abstract, more

flexible, and sometimes even more hypothetical with increasing levels of cognitive development.

Many questions remain to be resolved. How many of the changes we've described are due to factors such as biological maturation, say, versus education, experience, and expertise? Are there periods of rapid change in thinking, or is the entire process an orderly and continuous one? How different are the trajectories of thinking for children who grow up in very different cultures? Are the developmental paths for thinking general-purpose and broad, or does thinking develop differently in different domains? Stay tuned to the field of cognitive development to find the answers to these important questions!

# Summary

#### Review Questions

#### Hot Topic

Kathleen Galotti (Photo: Tania Legvold)

My research program is centered around the question, how do ordinary people facing important decisions go about the process of choosing an option? I've studied adults choosing a first-grade program for their children; pregnant women choosing birthing options; college students choosing majors, courses, housing, and summer plans, to name just a few. Here, I'll focus on the studies of college students choosing a major (Galotti, 1999; Galotti, Ciner, Altenbaumer, Geerts, Rupp, & Woulfe, 2006; Galotti, Wiener & Tandler 2014).

Many of these studies were *longitudinal* in design—meaning that we asked the same people about their decision-making process at two or more different points in time, in order to study changes over time. At each point, we asked students to describe the *options* they were actively considering (e.g., Psychology, Computer Science, English) as well as the *criteria* they were

using to decide among options (e.g., How many requirements are there? Do I like the profs who teach the classes? Are there labs? Will it help get me into med school?). We also asked students to assess their emotional reactions to the decision-making process (e.g., How stressful was it? How comfortable with the process were they?).

Across studies, college students considered about 4-5 options and about 5-7 criteria. As the final decision drew near, students were likely to reduce the number of options under consideration (from about 4-5 to about 3-4), but not the number of criteria they were using. When we looked at whether or not the same options or criteria were being used at different points in time, the answer was that about half of the options and half of the criteria were different. Students generally reported that this decision was moderately stressful and difficult, and that it was guided by their overall values, with an emphasis on the future. Some work suggests, however, that the way students approach a specific decision is largely a function of what that decision is about. The implication here is that people approach different decisions has at least as much to do with the specifics of a particular decision as it does with the characteristics of the decision maker.

#### References

# References

*of Experimental Child Psychology, 8*7, 299–319. doi:10.1016/j.jecp.2004.01.002

#### Galotti Glossary

# Glossary

# Chapter 18

# Affect and Thought: The Relationship Between Feeling and Thinking

JOSEPH FORGAS

University of New South Wales

Since time immemorial, philosophers, writers, and artists have wondered about the intricate relationship between feeling and thinking, affect and cognition. Humans are certainly an emotional species. Our feelings seem to influence and color everything we think and do (Zajonc, 2000), in ways that we do not yet fully understand. Philosophers such as Blaise Pascal put it very succinctly: 'The heart has its reasons that reason does not understand'. Yet apart from some early exceptions (e.g., Rapaport, 1942/1961; Razran, 1940), focused empirical research on the links between affect and cognition has been slow to emerge. One possible reason is the widespread assumption in Western philosophy that affect is an inferior and more primitive faculty of human beings compared to rational thinking, an idea that can be traced all the way to Plato (Adolphs & Damasio, 2001; Hilgard, 1980; see also Chapter 2, "History of the Field of the Psychology of Human Thought"). Affective states indeed have some unique properties. They often have broad non-specific effects on thinking and behavior, can occur spontaneously and often subliminally, they are difficult to control, and they are linked to powerful and sometimes visible bodily reactions. Most importantly, affective states have an invasive quality, influencing our thoughts and behaviors (Dolan, 2002; James, 1890).

Yet, of the two major paradigms that dominated the brief history of our discipline (behavior-

ism and cognitivism), neither assigned great importance to the study of the functions of affective states, such as moods and emotions. Radical behaviorists considered all unobservable mental events (including affect) as irrelevant to scientific psychology. The emerging cognitive paradigm in the 1960s largely focused on the study of cold and rational mental processes, and initially also had little interest in the study of affect. Thus, understanding the delicate interplay between feeling and thinking still remains one of the greatest puzzles about human nature (Koestler, 1967/1990). It was only in the last few decades that researchers started to focus on how moods and emotions influence how people think and behave.

This chapter reviews what we now know about the multiple roles that affective states play in influencing both the *content* (what we think) and the *process* (how we think) of cognition. After a brief introduction looking at some early work and theories linking affect and cognition, the chapter is divided into two main sections. First, research on affective influences on the *content* of thinking is reviewed, focusing especially on how positive and negative affective states preferentially produce positive and negative thoughts, a pattern of thinking called affect congruence. The second section of the chapter surveys evidence for the *processing effects* of affect, documenting how affect influences the quality of our information processing strategies.

For the purposes of our discussion, affect is used as a generic term to encompass two distinct kinds of feeling states. Moods may be defined as "relatively low-intensity, diffuse, subconscious, and enduring affective states that have no salient antecedent cause and therefore little cognitive content" (Forgas, 2006, pp. 6–7). Distinct emotions in contrast are more intense, conscious, and short-lived affective experiences (e.g., fear, anger, or disgust). Moods tend to have relatively uniform and reliable cognitive consequences, and much of the research we deal with looks at the cognitive consequences of moods. Emotions such as anger, fear, or disgust tend to have more context and situation-dependent effects that are less uniform (e.g., Unkelbach, Forgas, & Denson, 2008).

# Early Evidence Linking Affect and Cognition

Although radical behaviorists showed little interest in affect, Watson's classic conditioning research with Little Albert is an early demonstration of affect congruence in judgments—when negative affect produces negative reactions (Watson & Rayner, 1920). These studies showed that reactions to an initially neutral stimulus, such as a furry rabbit, became more negative after participants experienced unexpected negative affect, elicited by a sudden loud noise. Watson—incorrectly, as it turns out—thought that most complex affective reactions are acquired in a similar way throughout life as a result of ever-more complex and subtle layers of stimulus associations. In a later study linking affect and thought, Razran (1940) found that people responded to sociopolitical messages more favorably when they were in a positive affective state (just received a free lunch!) rather than in a bad affective state (being exposed to aversive smells). Politicians seem to instinctively know this, using positive affect manipulations (upbeat music, free food and drinks, etc.) to improve the likely acceptance of their messages.

In a subsequent psychoanalytically oriented study, Feshbach and Singer (1957) induced negative affect using electric shocks and then instructed subjects

to suppress their fear. Fear produced more negative evaluations of another person just encountered, and ironically, this effect became even greater when judges were actively trying to *suppress* their fear. This paradox pattern was interpreted as consistent with the psychodynamic mechanism of suppression and projection, suggesting that "suppression of fear facilitates the tendency to project fear onto another social object" (Feshbach & Singer, 1957, p.286).

Subsequently, Byrne and Clore (1970) returned to a classical-conditioning approach to explore how affective states can color thinking and judgments. They placed participants into pleasant or unpleasant environments (the unconditioned stimuli) to elicit good or bad moods (the unconditioned response), and then assessed their evaluations of a person they just met (the conditioned stimulus; Gouaux, 1971; Griffitt, 1970). As expected, manipulated positive affect reliably produced more favorable judgments than did negative affect. These early studies, although based on very different theoretical models (psychoanalysis, behaviorism, etc.), produced convergent evidence demonstrating an affect congruent bias in thinking.

# 18.1 Affect Congruence: Affective Influences on the Content of Thinking

In the studies described above, positive affect produced more positive thoughts and negative affect produced more negative thoughts. Interest in this pattern of affect congruence re-emerged in the last few decades. Investigators now wanted to understand the information-processing mechanisms that can explain how affect can come to infuse the *content and valence* (positivity or negativity) of cognition. Three convergent theories accounting for affect congruence have been proposed: (1) associative network theories emphasizing underlying memory processes (Bower, 1981; 1991), (2) affectas-information theory relying on inferential processes (Clore & Storbeck, 2006; Schwarz & Clore, 1983), and (3) an integrative Affect Infusion Model (AIM; Forgas, 1995, 2006), a theory that seeks to explain how different thinking strategies can increase or decrease the extent of affect infusion.

# 18.1.1 A Memory Effect? The Associative Network Explanation

The first cognitive model to explain affect congruence suggested that affective states influence cognition because affect is linked to memory within a shared associative network of memory representations (Bower, 1981). When an affective state is experienced, for whatever reason, that affect may automatically prime or activate units of knowledge or memories previously associated with the same affective state. Such affectively primed constructs are then more likely to be primed or activated, and used in subsequent constructive cognitive tasks. For example, Bower (1981) found that happy or sad people were more likely to remember details from their childhood and also remembered more events that occurred in the past few weeks that happened to match their current affective state. Similar affect congruence was also demonstrated in how people interpreted their own and others' observed social behaviors. When happy or sad participants viewed the same videotape of an encounter, judges in a positive affective state saw significantly more skilled, positive behaviors both in themselves and in other people, while those in a negative mood interpreted the same observed behaviors more negatively (Forgas, Bower, & Krantz, 1984).

Further research showed that affect congruence is subject to some limiting conditions (see Blaney, 1986; Bower & Mayer, 1989). Affect-congruence seems most robust (a) when the affective state is clear, strong, and meaningful, (b) the cognitive task is self-referential, and (c) when more open, elaborate, and constructive thinking is used (Blaney, 1986; Bower, 1991; Bower & Mayer, 1989). In general, quick, easy, familiar and regularly performed tasks are less likely to show affect congruence. In contrast, cognitive tasks that call for more constructive, openended thinking (such as judgments, associations, inferences, impression formation, and planning behaviors) are most likely to show an affect-congruent

pattern (e.g., Bower, 1991; Fiedler, 2002; Forgas, 1995; Mayer, Gaschke, Braverman, & Evans, 1992). This occurs because more open, elaborate processing increases the opportunities for affectively primed memories and associations to be retrieved and incorporated into a newly constructed response (Forgas, 1995; 2006).

# 18.1.2 Affect as a Heuristic? The Affect-As-Information Theory

Following Bower's (1981) work, an alternative theory sought to explain affect congruence by proposing that instead of computing a judgment on the basis of recalled features of a target, individuals may "ask themselves: 'how do I feel about it?' [and] in doing so, they may mistake feelings due to a preexisting state as a reaction to the target" (Schwarz, 1990, p. 529; see also Schwarz & Clore, 1983; Clore & Storbeck, 2006). In other words, rather than properly constructing a response, the pre-existing affective state is used as a heuristic shortcut indicating their reaction to a target. For example, affect incidentally induced by good or bad weather was found to influence evaluative judgments on a variety of unexpected and unfamiliar questions in a telephone interview (Schwarz & Clore, 1983). In a similar situation, we also found affect congruence in survey responses of almost 1000 subjects who completed a questionnaire after they had just seen funny or sad films at the cinema (Forgas, 1995).

The affect-as-information model is closely based on related research showing that people often rely on various shortcuts in their judgments. The model is also related to earlier conditioning models that predicted a blind, unconscious connection between affect and coincidental responses (Byrne & Clore, 1970). This kind of affective influence is far less likely to explain affective influences on more complex cognitive tasks, involving memory and associations where more elaborate computation is required. Affect as a simple, direct source of evaluation seems most likely when "the task is of little personal relevance, when little other information is available, when problems are too complex to be solved systematically, and when time or attentional resources are limited" (Fiedler, 2001, p. 175), as in the casual survey situations studied by Schwarz and Clore (1983), and also in the study showing affective influences on responses to a street interview after seeing happy or sad movies by Forgas (1995). In most realistic situations when people need to think constructively about new, unfamiliar and complex problems, moodcongruent associations in memory offer a more plausible explanation for affect congruence than simply using affect as a heuristic cue.

# 18.1.3 Putting it all Together: The Affect Infusion Model (AIM)

The research reviewed so far suggests that the occurrence of affect congruence in thinking (more positive thoughts in positive mood, more negative thoughts in negative mood) very much depends on *how* a particular cognitive task is processed. The Affect Infusion Model (AIM; Forgas, 1995; 2006) relies on this principle to explain the presence or absence of affect congruence in different situations. The AIM identifies four alternative processing strategies that vary in terms of (a) their *openness* (how much new information needs to be accessed), and (b) the degree of *effort* used in processing a cognitive task. The first, *direct-access* strategy involves the simple and direct retrieval of a pre-existing response, likely to be used when a task is familiar and of low relevance, producing no affect infusion (for example, if somebody asked your opinion about a familiar target, like President Trump, and you already have a well-defined and stored judgment, simply reproducing this judgment requires no constructive thinking and will not be influenced by how you are feeling at the time). (2) *Motivated processing* occurs when thinking is dominated by a specific motivational objective requiring highly targeted and selective information search and processing strategies that inhibit open, constructive thinking (e.g., when trying hard to make a good impression at a job interview, this objective will dominate your responses, and your affective state will not have much of an affect congruent influence) (Clark & Isen, 1982; Sedikides, 1994).

(3) The third, *heuristic processing strategy* (using whatever easy shortcuts are available) involves low-effort processing used when time, involvement

and processing resources are limited (e.g., in the telephone and street survey situations studied by Schwarz & Clore, 1983, and in Forgas, 1995). Heuristic processing only results in affect congruence when affect can be used as a convenient shortcut to infer a reaction (Schwarz & Clore, 1983; see also Clore & Storbeck, 2006). (4) Only the fourth processing style, *substantive processing*, involves constructive and effortful thinking. This kind of thinking should be used when the task is new and relevant and there are adequate processing resources available (for example, trying to form a judgment about a new person you are likely to see a lot of in the future). Substantive processing should produce affect congruence because it increases the likelihood of incorporating affectively primed thoughts and memories in constructing a response (Forgas, 1994; 1999). In summary, the AIM explains how four different processing strategies may promote or inhibit affect congruence in thinking and judgments (Fiedler, 2001; Forgas, 1995). One interesting and counter-intuitive prediction of this model is that sometimes, more extensive and elaborate thinking may actually increase affective distortions in judgments by increasing the likelihood that affectively primed information will be used (Forgas, 1992; Sedikides, 1995). Such a paradoxical pattern has now been found in a range of studies, as we will see below.

# 18.1.4 Affect Congruence in Memory

Affect plays a key role in memory. The events we remember are almost always marked out for special attention by their affective quality (Dolan, 2002). And by definition, only the things we actually remember—the available contents of memory can be used for thinking. Considerable research now shows that affect indeed does have a significant influence on what we remember. People are consistently better at remembering memories that are either consistent with their current affective state (affect congruence), or have been experienced in a similar, matching rather than dissimilar affective state (affect-state dependent memory).

Several studies found that people are better at retrieving both early and recent autobiographical memories that match their current mood (Bower, 1981; Miranda & Kihlstrom, 2005). Depressed people also selectively remember negative experiences and negative information (Direnfeld & Roberts, 2006). This pattern is also confirmed with implicit tests of memory when happy or sad subjects are asked to complete a few letters to make a word that first comes to mind (e.g., *can*- may be completed into words like *cancer* or *candy*; Ruiz-Caballero & Gonzalez, 1994). It turns out that happy people reliably come up with more positive, and sad people with more negative words in such a task. We found that happy or sad participants also selectively remembered more positive and negative details respectively about the good or bad characteristics of people they had read about (Forgas & Bower, 1987). This pattern was also confirmed in a study by Eich, Macaulay, and Ryan (1994), who asked happy or sad students to remember 16 specific episodes from their past. There was a clear affect congruent pattern in what they recalled.

These affect-congruent memory effects occur because an affective state can selectively activate affect-congruent information (Bower, 1981). People will actually spend longer reading and encoding affect-congruent material into a richer pre-activated network of affect-congruent memory associations. Not surprisingly, they are also better in remembering such information later on (see Bower, 1991). Affect may also direct selective attention to affectcongruent information when it is first encountered. For example, affect influences participants' attentional filter, focusing attention on faces that showed affect-congruent rather than incongruent expressions (Becker & Leinenger, 2011). Positive affect can also produce a marked attentional bias toward positive, rewarding words (Tamir & Robinson, 2007), and greater attention to positive images (Wadlinger & Isaacowitz, 2006). In contrast, depressed people pay selectively greater attention to negative information (Koster, De Raedt, Goeleven, Franck, & Crombez, 2005), negative facial expressions (Gilboa-Schechtman, Erhard-Weiss, & Jecemien, 2002), and negative behaviors (Forgas et al., 1984).

Such an affect-congruent bias has its dangers, because through selective attention to negative events, negative affect may easily spiral into a state of endur-

ing depression. Fortunately, with non-clinical subjects, this spiral is rare as sad people automatically escape the vicious circle of negativity by automatically switching to an *affect-incongruent* processing strategy after a while. For example, after initially retrieving negative memories, non-depressed participants in a negative mood spontaneously shifted to retrieving positive memories as if to lift their mood (Josephson, Singer, & Salovey, 1996).

# 18.1.5 Affect-state Dependence in Memory

Affective states also impact on memory by selectively facilitating the retrieval of information that has been learnt in a *matching* rather than a *non-matching* affective state. Such affect-state dependent memory is a special case of state dependence. We all remember information better when the same state is reinstated in which the event was first encountered. For example, a list of words learnt when you were feeling happy is more likely to be remembered when you feel happy again rather than sad at the time of retrieval (Bower, 1981). In extreme cases of state dependency, serious memory deficits can also occur in patients with alcoholic blackout, chronic depression, dissociative identity and other psychiatric disorders (Goodwin, 1974; Reus, Weingartner, & Post, 1979). Bipolar patients with intense affective fluctuations also show a marked pattern of affectstate dependence in remembering (Eich, Macaulay, & Lam, 1997).

Affect-state dependence is a rather subtle effect (Bower & Mayer, 1989; Kihlstrom, 1989), and is most likely to be found when the task requires open and constructive processing. Accordingly, affectstate dependence is more likely in constructive free recall tasks rather than in recognition tasks (Eich, 1995; Bower & Mayer, 1989), and more robust when the recalled events are self-relevant and the encoding and retrieval affect are distinctive, well matched and salient (Eich, 1995; Eich & Macauley, 2000; Ucros, 1989). There are also important individual differences between people in their susceptibility to affect congruence and state-dependent memory (Bower, 1991; Smith & Petty, 1995).

# 18.1.6 Affect Infusion in Associations and Judgments

The increased availability of affect-related information in memory should also have a marked influence on the kinds of associations and inferences people make, and subsequently, of how complex or ambiguous social information is interpreted. Bower (1981) found that after receiving a mood induction, people generated more mood-congruent ideas when daydreaming or free associating to ambiguous TAT pictures. Happy people also generated more positive than negative associations to words such as *life* (e.g., *love* and *freedom* vs. *struggle* and *death*) than did sad subjects. The selective priming and greater availability of affect-congruent ideas in memory can ultimately also influence complex social judgments, as judges also tend to rely on their most available, affect-consistent thoughts when making an interpretation of complex and ambiguous stimuli. For example, after an affect induction, judges made significantly more affect-congruent judgments when evaluating faces (Forgas, 2013; Gilboa-Schechtman et al., 2002), and they also form more affect-consistent impressions about others as well as themselves (Forgas et al., 1984; Forgas & Bower, 1987; Sedikides, 1995).

Paradoxically, affective influences on judgments tend to be greater when the targets require more constructive and elaborate processing because they are more complex and atypical (e.g., Forgas, 1992; 1995). Several studies found that the more people needed to think in order to compute a difficult and complex judgment, the greater the likelihood that their affectively primed ideas influenced the outcome. In one experiment, participants were asked to form impressions about characters who had either typical and predictable features (eg. typical medical students), or were atypical and complex (eg. a medical student who is also a hippy; Forgas, 1992). Affect had a significantly greater impact when judges had to form impressions of such complex, atypical characters (Figure 18.1).

These judgmental effects can be quite robust, even influencing judgments about very well-known people, such as a person's real-life partners. Forgas (1994) in one experiment showed that temporary affective state significantly influenced judgments about one's partner as well as real, recurring relationship conflicts. Ironically, affective influences were stronger when judgments about more complex, difficult relationship situations required longer and more constructive processing. In other words, the more one needs to think about a judgmental task,

Figure 18.1: Affect-congruence in judgments is magnified when the target is complex and unusual and so requires more constructive and extensive processing (after Forgas, 1992).

the more likely that one's prevailing affective state will come to bias the outcome. Some personality characteristics, such as high trait anxiety, may interfere with these effects, as highly anxious people are often less likely to process information in an open, constructive manner.

### 18.1.7 Affect and Self-Perception

Can fluctuating affective state also bias how we think about ourselves? It turns out that the answer is 'yes' (Sedikides, 1995). For example, students in a positive affective state are more likely to claim credit for their success in a recent exam, but are less likely to blame themselves for failure (in Forgas, 1995). These findings were replicated in a study by Detweiler-Bedell and Detweiler-Bedell (2006), who concluded that consistent with the AIM, "constructive processing accompanying most self-judgments is critical in producing mood-congruent perceptions of personal success" (p. 196). Sedikides (1995) further found that central, well-established ideas about ourselves tend to be processed more automatically and less constructively and thus are less likely to be influenced by how we happen to feel at the time. In contrast, judgments about more "peripheral" and vague self-conceptions require more substantive processing and are more influenced by a person's affective state. Long-term, enduring individual differences in self-esteem also play a role, as high selfesteem people are less influenced by their temporary affective state when judging themselves (Smith & Petty, 1995). Low self-esteem judges in turn have a less clearly defined and less stable self-concept and are more influenced by their fluctuating affective states (Brown & Mankowski, 1993).

These results are consistent with the Affect Infusion Model described previously (Forgas, 1995), and show that affectively primed thoughts and associations are more likely to influence associations and judgments when more extensive, open and constructive processing is required. Other work suggests that affect congruence in self-judgments may eventually be spontaneously corrected as people shift to a more targeted, motivated thinking style, reversing the initial affect-congruent pattern (Sedikides, 1994).

# 18.1.8 Affect Congruence in Social Behaviors

As we have seen, affective states often influence what people think. Because planning strategic social behaviors necessarily requires some degree of constructive, open information processing in calculating what to do (Heider, 1958), affect should ultimately also influence how people actually behave in social situations. Positive affective states, by activating more positive evaluations and inferences, should elicit more optimistic, positive, confident, and cooperative behaviors. In contrast, negative mood may produce more avoidant, defensive, and unfriendly behaviors. In one experiment, positive and negative affective states were induced in people (by showing them happy and sad films) before they engaged in a complex, strategic negotiation task (Forgas, 1998a). Those in a positive affective state employed more trusting, optimistic, and cooperative and less competitive negotiating strategies, and actually achieved better outcomes. Those in a negative mood were more pessimistic, competitive and ultimately, less successful in their negotiating moves (Figure 18.2).

Other kinds of social behaviors, for example, the way people chose their words when formulating a request, are also significantly influenced by how the person feels at the time (Forgas, 1999). Individuals in a negative affective state tend to make more pessimistic implicit inferences about the likely success of their requests, and so they use more polite, elaborate and cautious request forms. Positive affect has the opposite effect: it increases optimism and results in more confident and less elaborate and polite request formulations

Affect also has an impact on how people *respond* to an unexpected real-life request. In a realistic field study, students in a library were induced in a positive or negative affective state by finding folders on their desks containing affect inducing pictures and text (Forgas, 1998b). Soon afterwards they received an unexpected polite or impolite request from a passing student (actually, a confederate) asking for some stationery needed to complete an essay. There was a marked affect-congruent pattern. Negative mood resulted in more critical, negative evaluations of the request and requester, and reduced compliance, but positive mood yielded a more positive evaluation and greater willingness to help. These effects were even stronger when the request was more unexpected and impolite and so required more substantive processing.

Affect infusion can be particularly important when performing complex strategic social behaviors such as *self-disclosure* that plays a critical role in the development and maintenance of intimate relationships. By facilitating access to affect-congruent memories and associations, people in a positive affective state disclose more positive, intimate, varied, and abstract information about themselves (Forgas, 2011). Negative affect has exactly the opposite effect, resulting in less open and positive selfdisclosure. Studies such as these provide convergent evidence that temporary fluctuations in affective state can result in marked changes not only in thinking (memory, associations and judgments), but also in actual social behaviors. In other words, our affective states play an important informational function in thinking and responding to the social world. These effects are most marked when an open, constructive processing style is adopted (Forgas, 1995; 2006) that increases the scope for affectively primed information to become activated and used (Bower, 1981).

# 18.2 Affective Influences on Thinking Strategies

The evidence surveyed so far clearly shows that affect has a marked *informational* influence on the valence and *content* of our thinking, resulting in affect-congruent effects on memory, attention, associations, judgments and social behaviors. Affect also has a second effect on cognition, influencing *how* people think, that is, the *process of cognition*. This section will look at evidence for the informationprocessing consequences of affect. Early studies suggested that people in a positive affective state tend to think in a more superficial and less effortful way. Those feeling good made up their minds more quickly, used less information, tended to avoid more effortful and systematic thinking, yet, ironically, also appeared more confident about their decisions. Negative affect, in contrast, seemed to produce a more effortful, systematic, analytic and vigilant processing style (Clark & Isen, 1982; Isen, 1984; Schwarz, 1990). Positive affect can also produce distinct processing advantages as happy people tend to adopt a more creative, open, and inclusive thinking style, use broader cognitive categories, show greater mental flexibility, and perform better on secondary tasks (Bless & Fiedler, 2006; Fiedler, 2001; Frederickson, 2009).

Figure 18.2: Affect-congruent influences on negotiating strategies: positive affect promotes cooperation and making deals, negative affect promotes competition (After Forgas, 1998a).

# 18.2.1 Linking Affect to Processing Style

How can we explain such affectively induced processing differences? Early theories emphasized *motivational* factors. According to the *mood maintenance/mood repair* hypothesis, positive affect may motivate people to maintain this pleasant state by avoiding effortful activity such as elaborate thinking. In contrast, negative affect is aversive, and should motivate people to shift to a more vigilant, effortful information processing style as a useful strategy to improve their affect (Clark & Isen, 1982; Isen, 1984). A somewhat similar *cognitive tuning* account (Schwarz, 1990) proposed that affective states have a fundamental signaling/tuning function, automatically informing us about the level of vigilance and processing effort required in a given situation. Thus affective states have important adaptive and motivational functions, consistent with a functionalist/evolutionary view of affect (Dolan, 2002). However, this view has been challenged by some experiments demonstrating that positive mood does not always reduce processing effort, as performance on simultaneously presented secondary tasks is not necessarily impaired (e.g., Fiedler, 2001).

An integrative theory by Bless and Fiedler's (2006) suggests that the fundamental, evolutionary significance of affect is not simply to regulate processing *effort*, but rather to trigger equally effortful but qualitatively different *processing styles*. The model identifies two complementary adaptive functions, *assimilation* and *accommodation*, triggered by positive and negative affect, respectively (cf. Piaget, 1954). Assimilation means using existing internal knowledge to understand the world, whereas accommodation requires greater attention to new, external information to modify internal representations (Bless & Fiedler, 2006; p. 66; Piaget, 1954; see also Chapter 10, "Decision Making", on dual process theories in psychology). Positive affect signals safety and familiarity, so that existing knowledge can be relied upon. In contrast, negative affect functions as a mild alert signal, triggering more careful and accommodative processing. This processing dichotomy bears more than a passing resemblance to Kahneman's (2011) distinction between System 1

and System 2 thinking. In important ways, it appears that positive affect promotes faster, simpler, and more heuristic and creative thinking, while negative affect produces a slower, more systematic and more analytic thinking style.

Several experiments show that positive affect indeed promotes more assimilative and abstract language representations, the use of fewer and broader cognitive categories, and greater focus on the global rather than the local features of a target (Forgas, 2006; Frederickson, 2009; Gasper & Clore, 2002; Isen, 1984; Koch, Forgas, & Matovic, 2013). Further, positive affect increases, and negative affect decreases people's tendency to rely on their preexisting internal knowledge in cognitive tasks, and improves memory for self-generated information (Fiedler, Nickel, Asbeck, & Pagel, 2003). Thus, *both* positive and negative affect can confer processing advantages, albeit in response to different situations. In contrast to the dominant hedonic emphasis on the benefits of positive affect in our culture, an important implication of this model is that positive affect is not always advantageous, and negative affect can often produce distinct processing advantages, as the experiments to be reviewed next will show.

# 18.2.2 Can Negative Affect Improve Cognitive Performance?

As negative affect promotes more accommodative, externally focused processing, this should improve memory as well. In one field experiment, happy or sad shoppers (on sunny or rainy days, respectively) saw a variety of unusual small objects displayed in a local shop (Forgas, Goldenberg, & Unkelbach, 2009). Their affective state (induced by good or bad weather on that day) had a significant effect on memory. Those in a negative mood (on rainy days) had significantly better memory for the details of what they saw in the shop than did happy people (on sunny days; Figure 18.3). Laboratory experiments confirmed this pattern, as memory for the details of essays read was also significantly better in a negative compared to a positive affective state (Forgas, 2013).

Negative affect can also improve recall and reduce errors in eyewitness memory (Forgas, Vargas,

& Laham, 2005). In one experiment using a real-life incident, students witnessed a staged aggressive encounter during a lecture (Forgas et al., 2005, Exp. 2). A week later, while induced into a positive or negative affective state, witnesses received questions about the incident that included false, misleading information. Happy affect increased the tendency to assimilate these false details into memory, but negative affect eliminated this source of error in eye-witness reports. Conceptually similar results were reported by Clore and Storbeck (2006), who also found that individuals in a negative mood were significantly less likely to show false memory effects than those in positive moods, consistent with negative affect promoting more attentive and accommodative thinking. Paradoxically, even though happy affect *reduced* eye-witness accuracy, it *increased* eye-witness confidence, suggesting that witnesses had no real internal awareness of the processing consequences of their affective states.

# 18.2.3 Affective Influences on Judgmental Accuracy

Many common judgmental errors occur in everyday life because people are imperfect and often inattentive information processors (Kahneman, 2011). For

example, the *fundamental attribution error* (FAE) or *correspondence bias* refers to the pervasive tendency by people to attribute intentionality and internal causation to an actor and underestimate external, situational constraints (Gilbert & Malone, 1995). This happens because people focus on the most salient information, the actor, and ignore peripheral cues. As negative mood promotes more attentive, detailoriented processing, it should reduce the incidence of this common judgmental bias. This was confirmed in one experiment (in Forgas, 2013) where happy or sad subjects were asked to judge the attitudes of the writer of an essay that was either freely chosen, or was assigned to them. Happy persons were more likely and sad people were less likely to commit the fundamental attribution error by incorrectly attributing internal causation based on a coerced essay. Memory data confirmed that those in a negative affective state also remembered more details, consistent with accommodative processing.

Many judgmental inaccuracies are due to humans' excessive reliance on using judgmental shortcuts or heuristics (Kahneman, 2011). It seems that positive affect may increase, and negative affect reduce such judgmental biases when forming impressions. One relevant example is primacy effects, when early information about a person dominates our subsequent

Figure 18.3: Mean number of target items seen in a shop correctly remembered as a function of affective state (happy vs. sad) induced by good or bad weather (after Forgas, Goldenberg & Unkelbach, 2009).

impressions. In one experiment, participants formed impressions about a character (Jim) described in two paragraphs in either an introvert–extrovert or an extrovert–introvert sequence (Forgas, 2011). Subsequent impression-formation judgments showed that positive affect significantly increased reliance on heuristic primacy cues (relying on whatever information came first; Figure 18.4). In contrast, negative mood, by recruiting a more accommodative, System 2 processing style, almost eliminated the usual primacy effect. We should note, however, that negative affect can only improve judgmental accuracy when relevant stimulus information is actually available. Ambady and Gray (2002) found that in the absence of diagnostic details, "sadness impairs [judgmental] accuracy precisely by promoting a more deliberative information processing style" (p. 947).

# 18.2.4 Affective Influences on Stereotyping

Positive affect, by promoting assimilative thinking and the use of pre-existing knowledge in judgments, may also promote stereotyping. For example, Bodenhausen, Kramer, and Süsser (1994) found that happy participants relied more on ethnic stereotypes

when evaluating a student accused of misconduct, whereas negative mood reduced this tendency. Generally speaking, negative affect tends to promote greater attention to specific, individuating information when forming impressions of other people (Forgas, 2013). Similar effects were demonstrated in an experiment where happy or sad subjects had to form impressions about the quality of a brief philosophical essay allegedly written by a middle-aged male academic (stereotypical author) or by a young, alternative-looking female writer (atypical author). Once again, results showed that positive affect increased the judges' tendency to be influenced by irrelevant stereotypical information about the age and gender of the author. In contrast, negative affect eliminated this judgmental bias (in Forgas, 2013).

Relying on stereotyped expectations can ultimately also impact on behaviors. We tested this prediction using the 'shooters bias' paradigm assessing subliminal aggressive tendencies, where happy or sad people had to make rapid on-line decisions about whether to shoot at rapidly presented videotaped targets who did or did not appear to be holding a weapon (Correll et al., 2007). US subjects often display a strong implicit bias on this task and shoot more at Black rather than White targets (Correll et al., 2007). In our study we manipulated the im-

Figure 18.4: Primacy effects on impressions formation are increased by positive affect, and eliminated by negative affect: Judges perceive the target person as more extroverted when the extroverted description comes first, and this primacy effect is strongest in a positive rather than negative mood (vertical axis = extraversion judgments; differences between the columns indicate the size of the primacy effect; after Forgas, 2011).

ages so that some targets appeared to be Muslims, wearing a turban, while in the control condition the same person was shown without a turban.. In this case, we found a strong "turban effect", that is, Muslim targets elicited more aggression. Yet the most intriguing finding was that positive affect further *increased* this selective response tendency to shoot at muslim targets, while negative affect reduced it (Unkelbach, Forgas, & Denson, 2008). Thus, affective influences on stereotyped thinking may extend to influencing actual aggressive behaviors as well.

# 18.2.5 Affective Influences on Gullibility

Much of our knowledge about the world is based on second-hand information we receive from others that is often ambiguous and not easily verified (eg. hearsay, gossip, urban myths, fake news, conspiracy theories, trivia claims, etc.). Gullibility (accepting invalid information as true) can be just as problematic as rejecting valid information (excessive skepticism). Affective states also seem to play a role in how such decisions are made (Forgas, 2008; 2013, in press). For example, one study asked happy or sad participants to judge the probable truth of a number of urban legends and rumours (Forgas, 2018). Positive mood promoted greater gullibility for novel and unfamiliar claims, whereas negative mood promoted skepticism, consistent with a more externally focused, attentive, and accommodative thinking style. In another experiment, participants' recognition memory was tested two weeks after they were informed about the truth or falsity of various claims taken from a trivia game. Sad participants were better able to correctly distinguish between the true and false claims they had seen previously. In contrast, happy participants tended simply to rate previously seen and thus familiar statements as likely to be true (in essence, a familiarity/fluency effect). This pattern suggests that happy affect promoted reliance on the simple "what is familiar is true" heuristic, whereas negative mood conferred a clear cognitive advantage improving judges' ability to accurately remember the truth value of the statements.

# 18.2.6 Mood Effects on Bullshit Receptivity: Perceiving Meaning Where There is None

Perhaps the most striking form of gullibility occurs when people see meaning in meaningless, randomly generated information. Such absurd gullibility has been repeatedly demonstrated even in ideologically biased academic journals dealing with postmodernist theory, radical feminism and 'grievance studies'. Several such academic journals accepted for publication a number of articles composed of intentionally meaningless jargon and politically correct verbiage (Sokal & Bricmont, 1998). Pennycook et al. (2015) confirmed a similar effect, showing that people often perceive vacuous, pseudo-profound "bullshit" text as meaningful.

 One experiment asked participants in a positive or negative mood (after viewing cheerful or sad videotapes) to rate the meaningfulness of two kinds of verbal 'bullshit' text, including vacuous New Age pronouncements (e.g. "Good health imparts reality to subtle creativity"), and meaningless scientificsounding psychological jargon phrases (e.g. "subjective instrumental sublimations"; Forgas, Matovic, & Slater, 2018). People in a positive mood were more gullible and saw more 'meaning' in these nonsense statements than did those in the neutral and negative mood groups (see Figure 18.5). Positive mood judges were not only more gullible, but also were faster to produce a judgment, and also had worse recall and recognition memory than did those in the neutral and negative mood conditions, consistent with the prediction that positive mood produced a less attentive information processing style.

 Participants in public places received a mood induction (reminiscing about positive or negative life episodes) and then judged the meaningfulness of four modern abstract expressionist paintings. Positive mood again increased the perceived meaningfulness of these abstract images compared to negative mood.

 Accepting or rejecting such messages is critically important for effective social interaction. For example, people in a negative affective state were significantly less likely than those in a positive state to believe that various facial expressions were authentic (in Forgas, 2013).Taking this line of reasoning one step further, can affective states also influence people's ability to detect deception? In one study, happy or sad participants watched videotaped interrogations of suspects accused of theft who were either guilty or not guilty (Forgas & East, 2008). As predicted, those in a positive mood were more gullible, as they accepted more denials as true. In contrast, negative affect resulted in more guilty judgments, and also improved the participants' ability to correctly identify targets who were deceptive. So negative affect not only increased overall skepticism, but improved people's ability to accurately detect deception.

Detecting ambiguity in *verbal messages* is an equally important task. In one study (Matovic,

Koch, & Forgas, 2014) participants received a mood induction (watched happy or sad films), and were next asked to detect confusing, ambiguous sentences whose meaning was unclear. Results showed that negative mood promoted the more accurate detection of verbal ambiguity, consistent with the adoption of a more accommodative processing style. This was also confirmed by more extensive processing, and the more accurate recall when in a negative mood (Figure 18.6).

### 18.2.8 Affective Influences on Behavior

Our behavioral strategies may also benefit when negative affect triggers a more thorough processing style. To take one example, negative affect may optimize the way people process, produce, and respond to persuasive messages. In a number of studies, participants in a negative affective state were more sensitive to message quality, and were more persuaded by strong rather than weak arguments. In contrast, those in a positive affective state were not influenced by message quality, and were equally persuaded by strong and weak arguments (e.g., Sinclair, Mark, & Clore, 1994). Affective states may also influence the *production* and quality of persuasive messages. Those experiencing induced negative af-

Figure 18.6: The effects of positive and negative mood on (a) the ability to correctly identify ambiguous sentences (left panel), (b) the time taken to process the task (middle panel), and (c) the ability to remember the target sentences (right panel; after Matovic et al., 2014).