Content uploaded by Michael E W Varnum
Author content
All content in this area was uploaded by Michael E W Varnum on May 05, 2023
Content may be subject to copyright.
Homo Temporus: Seasonal Cycles as a Fundamental Source of Variation in Human
Psychology
Ian Hohm1*, Alexandra S. Wormley 2*, Mark Schaller1, & Michael E. W. Varnum2
1 Department of Psychology, University of British Columbia
2 Department of Psychology, Arizona State University, Tempe, AZ
*I. Hohm and A. S. Wormley contributed equally and are listed alphabetically.
Address correspondence to: Ian Hohm (ihohm@psych.ubc.ca), Alexandra Wormley
(awormley@asu.edu), Mark Schaller (schaller@psych.ubc.ca), or Michael Varnum
(mvarnum@asu.edu)
Accepted for Publication, Perspectives on Psychological Science
Word Count: 10,143
Funding: Funding was provided by the National Science Foundation's Graduate Student
Fellowship Program (A. S. W.) and an Insight Grant from the Social Sciences and Humanities
Research Council of Canada (M. S.)
Author Contributions: M. E. W. Varnum, M. Schaller, I. Hohm, and A. S. Wormley
conceptualized this manuscript. I. Hohm, A. S. Wormley, M. Schaller, and M. E. W. Varnum
wrote the initial draft and contributed to manuscript revisions. M. E. W. Varnum and M. Schaller
supervised the project.
Abstract:
Many animal species exhibit seasonal changes in their physiology and behavior. Yet, despite
ample evidence that humans are also responsive to seasons, the impact of seasonal changes on
human psychology is underappreciated relative to other sources of variation (e.g., personality,
culture, development). This is unfortunate, because seasonal variation has potentially profound
conceptual, empirical, methodological, and practical implications. Here, we encourage a more
systematic and comprehensive collective effort to document and understand the many ways in
which seasons influence human psychology. We provide an illustrative summary of empirical
evidence showing that seasons impact a wide range of affective, cognitive, and behavioral
phenomena. We then articulate a conceptual framework that outlines a set of causal mechanisms
through which seasons can influence human psychology—mechanisms that reflect seasonal
changes not only in meteorological variables but in ecological and sociocultural variables too.
This framework may be useful for integrating many different seasonal effects that have already
been empirically documented, and for generating new hypotheses about additional seasonal
effects that have not yet received empirical attention. The article closes with a section that
provides practical suggestions to facilitate greater appreciation for, and systematic study of,
seasons as a fundamental source of variation in human psychology.
In autumn, sockeye salmon embark on an epic journey, swimming up to 600 miles from
the ocean to the rivers in which they were born to spawn and die (Crossin et al., 2004). At the
same time, Canada geese fly thousands of miles south seeking warmer weather, then return
North in the spring to breed (Wege & Raveling, 1983). In winter, the black bear enters a state of
hibernation, slowing its heart rate to less than 10 beats per minute, and remains in hibernation
until the spring (Hellgren, 1998). Further north, the arctic fox molts, trading its dark coat of
summer fur for a new white one that blends in with the snow and ice (Mills et al., 2018). Every
December, children in much of the world make a special effort to be on their best behavior in
advance of the arrival of a large, mythical, bearded man in a red suit who delivers gifts in the
middle of the night. At first glance, this last seasonal pattern appears to have little in common
with our first several examples. Yet, the last example illustrates a similar point as those before
it—that human behavior, like that of many other organisms, is profoundly influenced by seasons.
Indeed, as we discuss below, just as a behavioral description of Oncorhynchus nerka (the
sockeye salmon) would be incomplete without carefully documenting its seasonal migratory and
mating patterns, so too the scientific study of Homo sapiens would be incomplete without
systematic inquiry into seasonal variation in human psychology.
Some effects of seasons on psychological phenomena are well-known, of course—such
as Seasonal Affective Disorder, the clinical condition characterized by recurring depression in
winter months (American Psychiatric Association, 2013; Han et al., 2000; Magnusson & Boivin,
2003). But, as we describe below, Seasonal Affective Disorder is just the tip of the proverbial
iceberg. Seasons affect many other psychological phenomena too, including decision-making in
diverse behavioral domains such as aggression, prosocial behavior, eating behavior, and sexual
activity (Kenrick & MacFarlane, 1986; Lauritsen & White, 2014; Levin et al., 2002; Ma et al.,
2006; Markey & Markey, 2013; Sachs & Chu, 2000), aesthetic preferences for music and for
colors (Palmer & Schloss, 2010; Park et al., 2019), as well as attentional processes and executive
functioning (Meyer et al., 2016). But, despite these many findings, seasons remain an
underappreciated source of variation in psychological phenomena—especially when compared to
other systematic sources of variation. Entire subfields of psychology have coalesced around
other sources of variation, such as variation due to individual differences (personality
psychology), developmental processes (developmental psychology), situational context (social
psychology), and cultural background (cultural psychology). In contrast—despite the potentially
profound conceptual, empirical, methodological, and practical implications associated with
seasonal variation—the effects of seasonal cycles are easily overlooked.
Perhaps one reason that seasonal effects are under-appreciated is because—in contrast to
research on other sources of variation (e.g., personality, culture, etc.)—research on seasonal
effects are scattered across different literatures that focus on different kinds of outcome
variables. For example, research revealing seasonal effects on attentional processes and
executive functioning has proceeded largely independently of research revealing seasonal effects
on prosociality or sexual behavior. Consequently, these effects, and the specific explanations for
them, tend to be conceptually disconnected. This too contrasts with psychological research on
other sources of variation (e.g., personality, culture, etc.), which are characterized by well-
articulated meta-theoretical principles of inquiry and conceptual frameworks that integrate
findings across diverse research streams. These kinds of frameworks are useful (Muthukrishna &
Henrich, 2019). Not only can they help integrate existing findings, but they can also illuminate
new research directions, and serve as generative foundations for new hypotheses and new
empirical discoveries.
If indeed seasonal changes are an important source of human psychological variation,
then perhaps “seasonal psychology” merits the kind of scholarly investigation—in terms of both
empirical and conceptual inquiry—that has been accorded to personality psychology, cultural
psychology, developmental psychology, and other sources of variation. The goal of this article is
to encourage a more systematic and comprehensive collective enterprise to reckon with the many
ways in which seasons influence human psychology.
Overview
We begin by briefly highlighting the ubiquity of seasons, and the many ways that
seasonal variation manifests in people’s lives—including not only changes in meteorological
variables but also changes in ecological and sociocultural variables too. Next, we summarize
some of the many effects that seasons have on a wide variety of psychological phenomena,
including mood, aggression, sexual activity, diet and exercise, prosocial behavior, color
preferences, and cognitive performance. We then outline a general framework that identifies a
set of conceptually-distinct causal mechanisms through which seasonal changes—in
meteorological, ecological, and sociocultural variables—can influence human affect, cognition,
and behavior. We use this framework not only to explain previously-documented empirical
findings, but also to derive novel predictions for additional ways in which seasons may influence
psychological phenomena, and to identify potential moderating variables (e.g., geographical,
cultural, and individual differences) that may influence the magnitude of seasonal effects. In the
final substantive section, we draw attention to methodological considerations that follow from
this perspective on seasonal variation, and offer some practical suggestions for researchers—
which, we hope, might facilitate additional research on seasonal effects and enhance appreciation
for seasons as a fundamental source of variation in human psychology.
Seasons are Everywhere and More Than Merely Meteorological
Seasons are most commonly thought of as recurring annual meteorological conditions.
This includes changes in features such as sunlight, temperature, and precipitation. In temperate
regions, the annual cycle typically includes four seasons (spring, summer, autumn, and winter)
each with its own meteorological features; and in the tropics—where there is relatively little
annual variation in day-length or temperature but considerable variation in precipitation—the
year is typically comprised by a wet season and a dry season. There is additional variability
within these 4- and 2-season conceptualizations. In fact, the Köppen climate classification
system—the most widely used climate classification system—outlines thirty distinct seasonal
patterns of temperature and precipitation across the globe (Kottek et al., 2006).
Although season cycles are defined by changes in meteorological variables, seasonal
variability is characterized by much more than just changes in the weather. As we will discuss
more fully below, seasonal cycles are characterized also by other kinds of changes that can also
affect human experience and human behavior—such as changes in the ecologies that people
inhabit. Partially as a consequence of changes in meteorological conditions, seasonal cycles
produce changes in ecological variables (e.g., prevalence of pathogens, abundance of food and
other valued resources) that can have additional, conceptually-distinct effects on psychological
phenomena. Further, specific seasons are associated with specific kinds of cultural traditions,
rituals, and large-scale social phenomena (e.g., seasonal holidays and the normative expectations
associated with those holidays). Seasonal variation in these cultural variables represents an
additional avenue through which seasons can have psychological consequences that are
conceptually independent of, and complementary to, effects that are more directly attributable to
the weather. Thus, there are multiple reasons to expect seasons to affect a wide variety of human
psychological phenomena, and multiple routes through which these effects can occur.
Seasons Are Known to Affect a Wide Range of Psychological Phenomena
In this section, we provide a summary of several lines of empirical evidence documenting
the impact of seasons on affective, cognitive, and behavioral phenomena. This overview is by no
means exhaustive; it simply illustrates the wide range of ways in which seasonal changes
influence psychological phenomena.
Mood
Black bears can hibernate for up to seven and a half months without eating, drinking, or
defecating (Hellgren, 1998). This behavior is viewed as an energy-conserving adaption for when
food is scarce in winter. Supporting this theory, hibernation has been shown to increase the
survival probability of bears and other hibernating animals (Turbill et al., 2011). Researchers
have noted the similarity between hibernation and Seasonal Affective Disorder (SAD). Similar to
hibernation, the core symptoms of SAD resemble an energy-conserving strategy (Levitan, 2022):
increased eating and sleep, decreased motivation and productivity, and cognitive impairments in
learning, memory, and visual-spatial ability (Michalon et al., 1997; O’Brien et al., 1993).
Seasonal effects on mood are also apparent beyond clinical syndromes such as SAD.
Researchers have suggested that seasonal variation in mood is common among the general
population, and SAD represents an extreme form of this effect (Wehr & Rosenthal, 1989). In
fact, one Twitter text analysis of 509 million tweets written by 2.4 million individuals in 84
countries found that decreased day-length was associated with less positive affect in tweets
(Golder & Macy, 2011), and another analysis of 800 million tweets in the United Kingdom
found a peak in sadness in winter (Dzogang et al., 2017). Further, nearly 50% of non-depressed
people report experiencing some depressive symptoms in winter (Dam et al., 1998; Kasper et al.,
1989), and an analysis of surveys in the United States on subjective happiness from 1946 – 1977
found that happiness was highest in the spring (Smith, 1979).
Aggression
The summer of 1967 would come to be known as the “long, hot summer.” Riots broke
out around the United States, leaving dozens dead and hundreds more injured (Carlsmith &
Anderson, 1979). Was the unusually hot summer just the backdrop for the unrest, or did it play a
role in what transpired? Psychologists and others were quick to notice the correlation between
heat and collective violence. This led to the hypothesis that seasonal increases in ambient
temperature cause people to be more irritable, thus increasing the likelihood of aggressive
behavior (Anderson, 1989; Miles-Novelo & Anderson, 2022).
This hypothesis has been supported in many studies, including research on riots: As
temperatures rose in the summertime, so did the frequency of riots (Gamble & Hess, 2012).
Increased ambient temperature has been linked to many other forms of aggressive behavior too,
some that are relatively trivial (e.g., horn-honking at red lights; acts of ritualized hostility
perpetrated in the context of competitive sports; Craig et al., 2016; Krenzer & Splan, 2018;
Kenrick & MacFarlane, 1986), and some that are not. For example, crime data in Philadelphia
showed that, compared to days at median temperature, rates of violent crime were 9% higher on
the hottest days of the year (Schinasi & Hamra, 2017). More broadly within the Northern
Hemisphere, the summer season from June to August has been associated with higher rates of
violent crime (Lauritsen & White, 2014), higher rates of rule infractions in prisons (Haertzen et
al., 1993), and higher rates of domestic violence (Sachs & Chu, 2000).
Sexual Activity
Seasons have been linked to variations in the mating behaviors of many animals.
Consider the penguin. The emperor penguin (Aptenodytes forsteri) and the Galapagos penguin
(Spheniscus mendiculus) behave similarly in many ways, but they vary drastically in their mating
patterns. Emperor penguins live in the Antarctic where day-length—and, more pertinently,
seasonal supplies of nutrients—varies drastically between summer and winter. Consequently,
Emperor penguins breed exclusively in summer when there are plentiful resources to feed
newborn chicks. On the other hand, Galapagos penguins live near the equator where this is little
seasonal variation in day-length and nutritional resources; and they exhibit no particular annual
cycle in their mating behavior (Ancel et al., 2013).
Humans appear more similar to Emperor penguins than their cousins in the Galapagos:
Humans too exhibit seasonal variation in sexual activity—although the nature of the seasonal
cycle is more complex. For instance, in the United States, condom sales, the timing of first
intercourse, and Google searches for pornography and prostitution all exhibit a biannual cycle
with peaks around Christmas and during the early summer months (Levin et al., 2002; Markey &
Markey, 2013; Wellings et al., 1999). These seasonal effects are not small: The biannual cycle
accounted for 16% of the variance in pornography searches and 24% of the variance in
prostitution searches. Analogous biannual cycles are evident in the timing of STI diagnoses (e.g.,
herpes, syphilis, HIV) and in abortion rates, both of which peak in the months following
Christmas and in late summer (Herold et al., 1993; Schroeder et al., 2001).
There are also seasonal cycles in birth rates. In an analysis of 78 years of United States
monthly natality data, Martinez-Bakker et al. (2014) found that birth rates peaked in the
summertime in northern states and peaked in the autumn in southern states. Martinez-Bakker et
al. (2014) found that similar seasonal patterns replicated in other countries within the northern
hemisphere. These birthrate data suggest that, at least in the northern hemisphere, conception
occurs more often in autumn and winter.
Diet and Exercise
Seasonal cycles are also evident in people’s diet and exercise behaviors. Several studies
have found that caloric intake reaches its highest peak in autumn and winter (Aparicio-Ugarriza
et al., 2017; de Castro, 1991; Ma et al., 2006). Overall diet quality is lower in the winter than any
other season, and body weight reaches its peak in winter (Crane et al., 2019; Ma et al., 2006). In
addition, physical activity reaches its lowest average in winter and peaks in spring, ostensibly
contributing to the lowest maximal oxygen intake and muscle strength in winter (Ma et al., 2006;
Shephard & Aoyagi, 2009). These seasonal effects on diet and exercise may contribute to
seasonal variation in health-related outcomes such obesity and rates of cardiovascular events.
Seasonal changes in biological mechanisms have been implicated as potential causes for
these effects. For example, Okada (2018) found that satiety after eating increases with outdoor
temperatures, suggesting that warm summers contribute to feeling full after a meal. Okada
(2018) also found that low humidity increases feelings of hunger, suggesting that the relative
aridity that comes with cold weather also contributes to increased eating behavior.
Cultural factors can also play a role in causing seasonal variation in dieting and exercise
behavior. For example, an analysis of more than 600,000 tweets on Twitter show that dieting-
related tweets peaked in the spring (Griffiths et al., 2022). Further, in a sample of sexual minority
men, Griffiths et al. (2021) found that body dissatisfaction peaked in the summer (especially
among men with higher body-weight). This seasonal effect on body dissatisfaction was
explained by seasonal variation in perceived pressure from media, feelings that one’s body was
on public display, and appearance-related social comparisons—all of which also peaked in the
summer. Considered together, these results suggest that dieting concerns vary seasonally in
anticipation of the body-image concerns associated with summer “swim-suit season.”
Prosocial Behavior
Whereas many seasonal effects in psychological phenomena may be primarily caused by
seasonal variation in meteorological conditions or ecological circumstances, others appear to be
attributable to season-specific cultural rituals and practices. One example, which has been
empirically documented in several countries with Christian traditions, is a seasonal peak in
charitable giving around Christmas—an annual holiday that emphasizes prosocial norms. One
analysis found that, in the United States, 31% of annual charitable giving occurred in the month
of December (Network for Good, 2014). Another study analyzed over 50 million giving
decisions over nine years in Sweden and found a 14% increase in unsolicited charitable
donations in December (Ekström, 2018).
This “Christmas effect” on prosociality is not limited just to formal charitable donations;
it appears to manifest on informal forms of everyday prosocial behavior too. For example, an
analysis of two years of within-customer tipping data found that people tip waiters and
waitresses more generously during the Christmas holiday season (Greenberg, 2014).
Color Preferences
People’s aesthetic preferences also appear to be influenced by seasonal changes. One
illustrative line of research has focused on the colors that people like and dislike. According to
the ecological valence theory of human color preferences, such preferences vary as a function of
affectively-laden cognitive associations with objects in a person’s perceptual environment
(Palmer & Schloss, 2010). Those objects (and/or the associations with them) may differ during
different seasons, with the implication that affective responses to—and preferences for—colors
will also vary seasonally (Palmer & Schloss, 2010; Schloss & Heck, 2017). In line with this
expectation, Schloss and Heck (2017)—employing a within-participants longitudinal
methodology—found that people living in the northeastern United States responded more
favorably to yellow and greenish-yellow colors in the autumn (when those colors may be
associated with the splendor of autumn leaves) than in the winter (when they may be associated
with less pleasing perceptual stimuli, such as symptoms of sickness). Additional studies also
show that color preferences vary seasonally, in accordance with the predictions of the ecological
valence theory of color preferences (e.g., Schloss et al., 2017).
The principles apply not just to objects in the natural ecology, but also to colorful
artifacts in the cultural environment too. For example, in many countries political parties are
associated with specific colors; and, since many high-profile political events (e.g., elections)
occur cyclically and sometimes take place during specific seasons, this too can lead to seasonal
changes in color preferences. Indeed, in the United States preferences for the colors red and blue
(symbolically associated with the Republican and Democratic parties, respectively) appear to
change on election day in November—and do so in a way that aligns with people’s political
party preferences (Schloss & Palmer, 2014).
Cognitive Performance
Even the most fundamental features of cognitive functioning may be affected by changes
in seasons. The cognitive performance of Alzheimer's patients has be shown to vary seasonally,
with more severe symptomatology in winter and early spring (Lim et al., 2018). Additionally, as
noted previously, the symptoms of seasonal affective disorder are associated with deficits in
working memory, short term memory, and auditory attention (Merikanto et al., 2012).
Seasonal variation in cognitive performance is not limited to clinical populations. In fact,
there is evidence indicating that analogous kinds of seasonal effects may occur more broadly
within human populations. For instance, one study—conducted on a sample of healthy young
adults in Belgium—found that performance on a measure of sustained attention was highest in
the winter and lowest in the summer (Meyer et al., 2016). Additionally, results obtained from the
same sample showed that performance on a working memory task was highest in the autumn and
lowest in the spring.
Summary
As these examples illustrate, changes in seasons influence a wide range of human
psychological phenomena (and this variation manifests in ways that are sometimes intriguingly
analogous to seasonal patterns of behavior that have been documented in studies of non-human
animals; see Table 1). The emerging implication is that, perhaps much more than most people
are aware, the psychology of Homo sapiens is subject to seasonal variation.
Table 1. Examples of Seasonal Effects in Human Affect, Cognition, and Behavior (and Some
Analogous Examples in Other Animal Species).
Domain of
Phenomena
Seasonal Variation within
Human Populations
Seasonal Variation Within
Non-Human Populations
Mood
Winter: Decreased mood
(Magnusson & Boivin, 2003)
Rhesus macaques:
Winter: Decreased mood (Qin et
al., 2015)
Aggression
Summer: Increased violence
(Anderson, 2001)
Rhesus macaques:
Autumn (mating season):
Increased aggression among males
(Wilson & Boelkins, 1970)
Sexual
Activity
December and early summer:
Increased internet searches
indicating interest in sexual
activity (Markey & Markey, 2013)
Emperor penguins:
Summer (breeding season):
Increased sexual activity (Ancel et
al., 2013)
Diet and
Exercise
Winter: Increased food intake
(Ma et al., 2006)
Domesticated cats:
Autumn and Winter: Increased
food intake (Serisier et al., 2014)
Prosocial
Behavior
December – January: Increased
charitable giving (Ekström, 2018)
Prairie voles:
Winter: Increased huddling
behavior (Beery et al., 2008)
Color
Preferences
Autumn: Increased preference for
yellow (Schloss & Heck, 2017)
Squinting bush brown butterflies:
Dry season: Increased preference
for brown (van Bergen & Beldade,
2019)
Cognitive
Performance
Autumn: Increased working
memory performance (Meyer et
al., 2016)
African striped mice:
Winter: Increased spatial
navigation performance (Maille et
al., 2015)
Mechanisms Through Which Seasons Exert Their Many Effects
The preceding section demonstrates that seasons have consequences for a wide array of
psychological phenomena—and do so not only as a result of seasonal variation in meteorological
variables, but also due to seasonal variation in ecological and sociocultural variables too. In this
section, we elaborate on that latter point by providing an overview of mechanisms through
seasons can have consequences for affect, cognition, and behavior (these mechanisms are
summarized in Figure 1). As with the preceding summary of empirical findings, this overview is
intended to be illustrative rather than exhaustive: It highlights the variety of conceptually-distinct
mechanisms through which different kinds of seasonal variation—meteorological, ecological,
and cultural—can exert effects on different kinds of psychological phenomena. This multi-
mechanism framework may be useful as a means for (a) explaining the extraordinarily wide
range of psychological effects that seasons are known to have, (b) reconciling effects that, at first
glance, may appear inconsistent, and (c) generating new hypotheses about additional seasonal
effects that have not yet been documented in the empirical literature.
Figure 1. A framework summarizing multiple ways in which seasonal variation manifests in human experience, and multiple causal
mechanisms through which these seasonal cycles can influence psychological phenomena.
17
Mechanisms Affected by Meteorological Conditions
For people inhabiting temperate regions of Earth, seasonal changes are most noticeably
characterized by changes in hours of daylight, intensity of sunshine, and quantity of heat in the
air (all of which are relatively abundant in the summer and scarce in the winter). For people
inhabiting the tropics, seasons are experienced differently (e.g., a wet season and a dry season)
and are typically defined by differences in rainfall. Exactly how do these meteorological
variables produce their cognitive and behavioral consequences? Just as there are multiple
meteorological variables and multiple consequences, multiple mediating mechanisms must be
considered to fully account for the effects of the former on the latter.
Physiological Effects (not Mediated by Cognitive Processes)
Meteorological conditions can lead to changes in physiology. In temperate regions,
seasonal variation in day length (which typically is associated with variation in sunlight,
temperature, and precipitation) is associated with many changes in neurochemical processes
within the human body, including processes involving cortisol, μ-opioid reception, serotonin and
testosterone (Demir et al., 2016; Peterson & Harmon-Jones, 2009; Praschak-Rieder et al., 2008;
Smals et al., 1976; Sun et al., 2021; Velo et al., 2012). These effects represent multiple
neurochemical routes through which seasonal variation in the weather can produce variability in
psychological phenomena—and some of these routes can potentially affect a wide range of
phenomena.
For example, serotonin binding and serotonin turnover in the brain are influenced by the
presence of natural sunlight (e.g., Lambert et al., 2002; Praschak-Rieder et al., 2008).
Consequently, in temperate regions, there are effectively higher levels of serotonin in the brain in
the summer and lower levels in the winter. Not only does seasonal variation in serotonin help to
18
explain seasonal variation in mood (Praschak-Rieder et al., 2008), it might also help to account
for the finding that people are more helpful on sunny days (Cunningham, 1979; Guéguen &
Lamy, 2013); and, more generally, seasonal variation in serotonin could have downstream
effects on many additional cognitive and behavioral phenomena that are known to be affected by
mood—such as memory, risk-taking behavior, and susceptibility to persuasion (e.g., Chou et al.,
2007; Eich & Forgas, 2003; Petty & Briñol, 2015).
As with serotonin levels, testosterone levels too tend to be highest in summer months
(Smals et al., 1976); and, among men, seasonal increases in testosterone are associated with
increased sex drive and sexual behaviors (Demir et al., 2016). Given the wide range of
psychological phenomena affected by testosterone, this effect on sexual activity is just one of
many potential implications. For example, the experimental administration of testosterone has
been shown to increase men’s public displays of charitable giving, increase men’s preferences
for high-status consumer products, and increase women’s preference for masculine-looking male
faces (Nave et al., 2018; Welling et al., 2007; Wu et al., 2020). These and other psychological
phenomena associated with testosterone (e.g. emotion regulation; Kaldewaij et al., 2019) might
therefore be expected to vary seasonally—a potentially promising avenue for future research.
Effects Mediated by Subjective Experiences
The physiological effects summarized above likely operate outside of conscious
awareness, but meteorological variables also have additional consequences that people are aware
of and may experience as subjectively pleasant or disagreeable (e.g., when someone is chilled,
warm sunshine feels good; when someone is hot, it does not). These subjective experiences can
consequently affect the ways in which people appraise objects and events and respond to them.
19
One illustrative example is provided by research linking hot temperatures to aggressive
behaviors. According to Anderson (2001, p. 36), the process plays out as follows: “Heat-induced
discomfort makes people cranky. It increases hostile affect (e.g., feelings of anger), which in turn
primes aggressive thoughts, attitudes, preparatory behaviors (e.g., fist clenching), and behavioral
scripts (such as ‘retaliation’ scripts). A minor provocation can quickly escalate.” The potential
consequences of this process are not limited just to aggressive behavior. An analogous
explanation accounts for reduced prosocial behavior on uncomfortably hot days (Belkin &
Kouchaki, 2017). More generally, because uncomfortably hot temperatures “produce biases in
the interpretation of observed social interactions” (Anderson, 2001, p. 36), this subjective
experience also has the potential to affect a wide range of judgments about and responses to
other people (e.g., the harshness of moral judgments about others’ counter-normative actions).
The implication for seasonal variation is straightforward: In places where there is seasonal
variation in the prevalence of uncomfortably hot weather, there should also be seasonal variation
in people’s inclinations toward hostile cognition, harsh judgment, and antisocial behavior.
Effects Mediated by Cognitive Associations
Meteorological variables need not elicit specific affective states (e.g., crankiness) in order
to activate specific cognitions that, in turn, facilitate specific behavioral responses. The mere
perception of a particular meteorological condition might have similar consequences. The
underlying principles here are the same as those that inform the ecological valence theory of
color preferences (Palmer & Schloss, 2010). People readily learn to associate specific perceptual
objects with specific affect-laden concepts (such as the association between yellow and falling
leaves; Schloss & Heck, 2017); once such a cognitive association has been acquired, the mere
20
perception of that object makes the associated concept more accessible in working memory,
which can then influence attitudes, judgments, and behavioral decisions.
Just as colors can be associated with specific concepts, meteorological variables can also
acquire specific cognitive associations. In places where winters are unpleasantly cold, sunshine
may acquire positive associations; in places where summers are unpleasantly hot, sunshine may
acquire negative associations instead. More universally perhaps, humans may associate daylight
with safety and darkness with danger. As a consequence, when people are in the dark (rather than
in the light) they respond more fearfully to sudden noises (Grillon et al., 1997) and perceive
ethnic outgroups to be less trustworthy (Schaller et al., 2003). Durations of daylight and darkness
vary seasonally in temperate regions, with the consequence that people spend more time in the
dark during the winter. One implication is that, during winter months, people may be more prone
to perceive the potential for danger, with consequences for attitudes and appraisals (e.g.,
increased risk-aversion, greater distrust of strangers).
Mechanisms Affected by Seasonal Variation in Local Ecologies
Just as the weather changes with the season so to do the ecologies inhabited by humans.
Many plants produce foliage seasonally (e.g., in tropical climates, some species of trees are
leafless during the dry season and fully foliated during the rainy season), creating seasonal
variation in the lushness of the local landscape. Additionally, in many parts of the world there is
seasonal variation in the prevalence of infectious diseases such as influenza, cholera, and malaria
(Martinez, 2018). These and other seasonal changes in local ecologies have the potential to
influence human affect, cognition, and behavior—and to do so in ways that are conceptually
distinct from, and complementary to, the effects of meteorological variables.
21
Physiological Effects (not Mediated by Cognitive Processes)
Beyond the physiological effects of the weather (e.g., light, temperature), seasonal
variation in the local ecology can also influence human physiology. One illustrative—and
speculative—example of the mediating role of ecology follows from a joint consideration of
seasonal variation in the incidence of infectious diseases (Martinez, 2018), and research on
cytokine-induced sickness behavior (Dantzer & Kelley, 2007). Seasonal variation in the
prevalence of infectious diseases implies seasonal variation in the percentage of people within a
population who contract infections—and thus seasonal variation in the extent to which
populations exhibit sickness-related behaviors. These effects are not limited just to physical
symptoms of illnesses; they include psychological effects as well. When the immune system
detects the presence of an infection, it typically mounts an inflammatory response, mediated by
the release of pro-inflammatory cytokines. These cytokines do more than merely promote
inflammation. They also exert diverse effects on the peripheral and central nervous systems
(Hopkins & Rothwell, 1995; Rothwell & Hopkins, 1995), leading to a diverse range of cognitive
and behavioral outcomes—including reduced motor activity and social withdrawal—that have,
collectively, been called “sickness behavior” (Dantzer & Kelley, 2007; Hart & Hart, 2019). This
process may contribute to the pathogenesis of depression—as indicated, for instance, by
empirical evidence linking inflammation to negative mood states and major depressive disorder
(Miller & Raison, 2016).
In addition to these clinical implications, inflammation “may play an important
modulatory role in shaping emotions, motivation, cognition, and behavior” and, as a
consequence, “may be an important mediator of many psychological and behavioral outcomes
that are of interest to social and personality psychologists” (Gassen & Hill, 2019, p. 1). For
22
example, the experimental induction of a benign endotoxin—which stimulates an inflammatory
response without introducing a harmful infection—caused people to report greater desire to
spend time with supportive friends and family members (Inagaki et al., 2015). These and other
findings (for a review, see Gassen & Hill, 2019) indicate that immunological responses to
infection may have subtle and nuanced consequences for human cognition and behavior. The
further implication is that immunological mechanisms may provide one specific route through
which one specific kind of seasonal change in the local ecology—variation in the prevalence of
infectious diseases (Martinez, 2018)—might also have subtle and nuanced consequences for
human cognition and behavior.
Effects Mediated by Activation of Specific Motivational Systems
Another route through which seasonal changes in local ecologies can have consequences
is through the activation of specific motives and goals. Humans are equipped with motivational
systems that evolved to regulate behavioral responses to one’s environment (Schaller et al.,
2017; Tooby et al., 2008). These motivational systems are attuned to perceptual cues connoting
the presence of specific threats to be avoided or specific opportunities to be seized. These
appraisals, in turn, stimulate functionally-specific affective, cognitive, and behavioral responses.
For instance, the sound of a sudden roar connotes the presence of a predator and thus activates
motivational mechanisms that regulate self-protective responses (Neuberg et al., 2011); whereas
the sight of neonatal facial features connotes the presence of an infant and activates motivational
mechanisms that regulate parental care-giving responses (Schaller, 2018). To the extent that
there is seasonal variation in these and other motive-activating cues within the local ecology,
then there may be seasonal variation in activation of specific motivational systems—and thus
also seasonal variation in their characteristic emotional, cognitive, and behavioral responses.
23
To illustrate, consider again the fact of seasonal variation in the incidence of infectious
diseases (Martinez, 2018), and its implications for activation of the motivational system that
regulates proactive behavioral defenses against infection (the “behavioral immune system”;
Schaller & Park, 2011). This motivational system is more readily activated under circumstances
in which individuals perceive themselves to be more vulnerable to infection; and once activated,
it has consequences for a wide range of cognitive and behavioral phenomena (Ackerman et al.,
2018; Murray & Schaller, 2016; Schaller et al., 2022). For example, when people feel more
vulnerable to infection, they consequently are more distrustful of other people (Aarøe et al.,
2016), reluctant to pursue dating relationships (Sawada et al., 2018), troubled by crowds (Wang
& Ackerman, 2019), wary of used consumer products (Huang et al., 2017), xenophobic
(Faulkner et al., 2004), likely to conform to majority opinion (Murray & Schaller, 2012), likely
to judge moral transgressions harshly (Murray et al., 2019), and supportive of conservative
sociopolitical policies (Aarøe et al., 2020). Assuming that people generally perceive themselves
to be more vulnerable to infection when they actually are more vulnerable to infection, then
analogous seasonal effects might plausibly occur as a consequence of seasonal variation in the
incidence of infectious diseases in the local ecology.
Effects Mediated by Cognitive Associations
Seasonal variation might also be produced by a process in which specific ecological
features are cognitively associated with specific concepts and consequently facilitate cognitive
access to those concepts. In the preceding section we summarized how this process can lead to
seasonal variation in color preferences (the ecological valence theory of color preferences;
Palmer & Schloss, 2010), but the potential consequences are not limited just to color preferences.
There are implications for seasonal variation in many psychological phenomena.
24
To illustrate, consider the outcomes of perceived resource scarcity. Experiments that
manipulate perceptions of abundance and/or scarcity have shown that these perceptions can
affect a wide range of phenomena, including object attachment (Goldsmith et al., 2021),
categorization of racially ambiguous faces (Rodeheffer et al., 2012), inclinations toward
impulsiveness and risky decision-making (Griskevicius et al., 2013), and prosocial behavior
(Roux et al., 2015). In real life, the concepts of resource abundance and resource scarcity may be
associated with seasonally-variable ecological circumstances. In temperate regions, for instance,
the lush vegetation of summer may tacitly connote abundance whereas bleak wintertime
landscapes are more likely to be associated with scarcity. Consequently, when wintery—rather
than lush—landscapes are perceived, the concept of scarcity may be more readily accessible in
working memory, with implications for seasonal variability in the many cognitive or behavioral
phenomenon that are affected by perceptions of scarcity (e.g., object attachment, face
categorization, risky decision-making, prosocial behavior, etc.).
Effects Mediated by the Changes in the Social Ecology
The preceding paragraphs focused on seasonal variation in the natural ecology—the
pathogens, plants, and other non-human organisms that characterize a person’s local
environment. A person’s local ecology is defined also by the other people who occupy their local
environment. In other words, in addition to the natural ecology, the social ecology matters too
(Oishi & Graham, 2010; Sng et al., 2018; Stokols, 1992; Uskul & Oishi, 2020). Just as a person’s
natural ecology can vary seasonally, a person’s social ecology may vary seasonally too, simply
as a consequence of season-specific patterns of human travel and migration.
Consider, for example, the “Spring Break” phenomenon during which many beach
communities in the southern United States and Mexico are temporarily inhabited by throngs of
25
young adults in skimpy swimwear. This seasonal change in local social ecology may create a
salient social comparison context that temporarily arouses body-image anxieties, especially
among young women (Griffiths et al., 2021), which may produce season-specific changes in the
problematic sequelae associated with these anxieties (e.g., restrained eating, disrupted academic
performance; Fredrickson et al., 1998; Quinn et al., 2006).
Some social ecological variables—such as population density—may vary seasonally in
places that are popular destinations for seasonal travel. For instance, the Bahamas are most
densely populated during winter, Provençal villages are most densely populated during summer,
and Mecca is most densely populated during the Ḥajj. High population density has psychological
consequences, some that have been well-known for decades (e.g., the experience of crowding is
subjective unpleasant and stressful; Baum & Valins, 1979), and some that have only recently
been illuminated. For instance, experiments show that the mere perception of greater population
density can lead people to become more future-oriented, to prefer fewer lifetime relationship
partners, and to prefer having fewer children (Sng et al., 2017). Some seasonal travel choices
may be particularly popular among people with specific demographic characteristics.
Consequently, the age profile of a local population may vary seasonally (e.g., the wintertime
influx of retirees to many parts in Arizona) and even sex ratio may vary seasonally in some
places. These changes may also have subtle consequences for the thoughts and actions of the
people who inhabit these ecologies (Sng et al., 2018).
Mechanisms affected by Seasonal Variation in Cultural Events and Practices
Festivals and holidays (e.g., Tsagaan Sar, Diwali, Christmas) occur during specific times
of the year. This creates seasonal variability in ritualized behaviors (e.g., gift giving) and in the
perceptual stimuli to which people are incidentally exposed (e.g., Santa Claus). Schools are in
26
session during specific chunks of the year and not others, contributing to seasonal variability in
the amount of time that parents and children spend together. The frequencies of many other
cultural practices also vary seasonally (weddings, pool parties, hunting trips, etc.). These cultural
events and popular practices can have additional effects on human cognition and behavior that
are distinct from, and conceptually complementary to, the effects due to seasonal changes in the
weather or local ecology.
Effects Mediated by Activation of Specific Motivational Systems
Just as motivational systems can be activated by cues in the local ecology (as discussed
above), they can also be activated by specific kinds of cues associated with cultural events and
practices; and if there is seasonal variation in these social cues, it may lead to seasonal variation
in activation of specific motivational systems and in their characteristic emotional, cognitive, and
behavioral responses.
To illustrate, consider school holidays. Compared to those times of year during which
schools are in session, parents of school-aged children are likely to spend more time actively
inhabiting their role as parents during school holidays. This may lead to increased activation of
the motivational system that governs parental care-giving behavior and kin care generally
(Schaller, 2018). As a consequence, parents might plausibly show seasonal variation across a
wide range of affective, cognitive, and behavioral phenomena that have been shown to be
affected by this motivational system—including not only care-giving behavior but also
aggression, risk-aversion, intergroup prejudice, mate preferences, moral judgment, and
sociopolitical attitudes (Buckels et al., 2015; Eibach et al., 2009; Gilead & Liberman, 2014;
Hahn-Holbrook et al., 2011; Kerry et al., 2020).
27
Other seasonal effects might possibly be produced by seasonal changes in clothing norms
and their implications for activation of motivational mechanisms underlying mating behavior. In
temperate climates, people are more likely to wear scanty attire in the summer. Motivational
mechanisms underlying mating behavior respond to visual cues of this sort, with the implication
that mating motives may be more readily activated in the summer—perhaps especially among
people who are most sensitive to such cues (e.g., adolescents and young adults). The activation
of mating motives not only has implications for overt acts of mating behavior, but it can also
have a wide range of additional cognitive and behavioral consequences as well. For instance,
activation of mating motives in young men has been shown to increase their tendencies toward
conspicuous consumption and blatant benevolence (Griskevicius et al., 2007), creativity, non-
conformity, and risk-taking behavior (e.g., Griskevicius, Cialdini, et al., 2006; Griskevicius,
Goldstein, et al., 2006; Ronay & Hippel, 2010; Wilson & Daly, 1985), and biased judgments
about other people (e.g., Maner et al., 2005). For people who are already in a mating
relationship, the popular practice of shedding clothes in the summertime also increases exposure
to scantily-clad bodies of people that their own mates might find sexually attractive. This can
activate motivational mechanisms that regulate mate-retention behavior—which may manifest in
jealousy and mate-guarding behavior (Buss & Haselton, 2005), as well as in increased attention
to, and distrust of, individuals who might be especially attractive to one’s mate (Krems et al.,
2016; Maner et al., 2007). Thus, there might be seasonal variation in these phenomena too.
Effects Mediated by Cognitive Associations
We have already discussed a process through which seasonally-variable features of the
weather and local ecology can be cognitively associated with specific concepts, and thus
facilitate cognitive access to those concepts, with downstream consequences for judgment and
28
behavior. This process applies to seasonal variation in cultural practices too. For instance, in
North America, the Thanksgiving and Christmas holidays have become associated with the
concepts of benevolence and generosity (e.g., giving thanks, giving gifts). Consequently, the
mere awareness of the holiday has the potential to make those concepts—along with other
thoughts and beliefs associated with them—more cognitively accessible. This may have
consequences not only for overt acts of benevolence (e.g., giving money to charitable causes;
Ekström, 2018), but also for less obvious manifestations of a generous mindset (e.g., more
forgiving responses to others’ misdeeds). The implication for seasonal variation: Regardless of
meteorological conditions, whenever holidays of this sort are psychologically salient (due to
holiday-themed content in popular media, for instance) people may exhibit more giving—and
forgiving—thoughts and behaviors.
Effects Mediated by Seasonal Changes in Normative Behavioral Choices
For pragmatic reasons, people often make different behavioral choices during different
seasons. Those popular choices represent seasonal changes in normative behaviors, which may
have additional (often unintended) consequences for cognition and behavior, for reasons that are
conceptually distinct from the processes outlined in the preceding paragraphs.
For instance, seasonal variation in the harshness of meteorological conditions creates
seasonal variation in the amount of time that people spend outdoors and in nature. Exposure to
nature has psychological consequences—including benefits for attention and memory, and for
health and well-being (e.g., Berman et al., 2008, 2012; Hartig et al., 2014). The implication is
that, in places where people spend disproportionately more time in nature during some seasons
rather than others, one might also expect there to be some seasonal variation in attention,
memory, health, and well-being. Nature may even provide a kind of spiritual resource,
29
decreasing the subjective need to seek spiritual comfort through other means. In fact, some work
finds lower adherence to traditional religions in places where people have greater access to
nature (Ferguson & Tamburello, 2015). If there is merit to this analysis, one implication might be
that in places characterized by seasonal variation in access to nature, they may also be seasonal
variation in traditional forms of religious activity.
These are just a few speculative examples that illustrate a broader point: large numbers of
people make similar season-specific behavioral choices; and when they do, it may produce
additional seasonally-variable effects on human affect, cognition, and behavior.
Moderators of Seasonal Effects
As summarized in the preceding sections, seasonal cycles manifest in a multitude of ways
that can have effects on a wide range of psychological phenomena. But the magnitude of these
seasonal effects likely varies, depending on other variables that differ across contexts or across
individuals. In this section, we provide a brief overview of some variables that might be expected
to moderate the impact that seasons have on affect, cognition, and behavior.
Geographical Variables
Any seasonal effect attributable to variation in meteorological conditions is likely to be
greater in places that are subject to more extreme variations in those conditions. Residents of
both Kugluktuk, Nunavut (in northern Canada) and Paducah, Kentucky (in the continental
United States) experience seasonal variation in sunlight and ambient temperature; but due to a
substantial difference in latitude (67°N and 39°N, respectively) that variability is more extreme
in Kugluktuk than Kentucky. To the extent that these meteorological variables affect
psychological phenomena, the magnitude of those effects would be expected to be bigger in
Kugluktuk—and, more generally, in locations characterized by a higher latitude. This kind of
30
moderating effect has been observed in the experience of seasonal affective disorder, which is
more prevalent at higher latitudes (Kegel et al., 2009; Mersch et al., 1999).
Higher latitudes are characterized not just by more extreme seasonal variation in
meteorological variables, but also by more extreme variation in their ecological consequences
(e.g., greater scarcity of plant life in the wintertime, which may contribute to the subjective
appraisal of a harsher environment). It is because of these kinds of ecological covariates, and not
just meteorological covariates, that latitude predicts cross-national differences in human behavior
(e.g., Van de Vliert, 2020; Van de Vliert et al., 2023; Van de Vliert & Van Lange, 2019; Van
Lange et al., 2017). If indeed seasonal variation in local ecologies accounts for some seasonal
effects on psychological outcomes, and if indeed the extremity of that variation differs at
different latitudes, then the sizes of those effects would also be expected to differ at different
latitudes.
The magnitude of seasonal variation is affected by other geographical variables too, such
as proximity to ocean waters. Moscow and Copenhagen are at the same latitude (55°N); but,
compared to residents of coastal Copenhagen, residents of Moscow experience hotter summers
and colder, snowier winters—which implies greater variation in the perceived harshness of the
landscape. To the extent that those forms of seasonal variation have psychological consequences,
those effects may be bigger among Moscovites. The same principle applies to tropical seasons.
Quito and Guayaquil—the two largest cities in Ecuador—are both located close to the equator
but are geographically different in other ways (Guayaquil is coastal; Quito is in the highlands).
As a consequent, Guayaquil has both a drier dry season and wetter wet season. Any
psychological consequences of the dry/wet seasonal cycle are likely to be greater in Guayaquil.
31
The broader point is this: Geography matters. In addition to the many main effects that
geographical variables have on psychological phenomena (e.g., Götz et al., 2020; Rentfrow,
2020), these variables also have implications for the magnitude of seasonal variation in
meteorological and ecological conditions. As a consequence, geographical variables may
moderate the magnitude of seasonal effects on affect, cognition, and behavior.
Demographic Variables that Affect a Person’s Exposure to Seasonal Variation
Seasonal variation in meteorological and ecological variables can affect people only to
the extent that people are actually exposed to that variation. That exposure differs depending
upon a person’s demographic circumstances, such as whether they live in a rural or urban
environment, or whether they are rich or poor.
Compared to urban populations, people in rural areas are more likely to work in
industries (e.g., agriculture) that are directly affected by the meteorological and ecological
manifestations of the seasons, and they spend more time outdoors (Matz et al., 2015). As a
consequence, exposure to seasonal variation is likely to be greater in rural populations. Indeed,
there is evidence that inhabitants of rural areas are more susceptible to certain kinds of seasonal
effects. For example, a study in Finland found more severe behavioral symptoms of seasonal
affective disorder in rural areas (Sandman et al., 2016), and a study in Italy found that seasonal
variation in suicide rates was also more pronounced in rural populations (Micciolo et al., 1991).
Regardless of whether a person inhabits a rural or an urban environment, that person is
more likely to be exposed to seasonal variation (e.g., hot summers and cold winters) if they lack
resources that provide buffers against that variation (e.g., air-conditioned cars; well-insulated
homes). Access to those resources is a function of wealth. The implication is that some seasonal
32
effects on psychological phenomena—perhaps especially effects due directly to variation in
meteorological variables—may be larger among people who are impoverished.
Trait-like Individual Differences
People differ in their sensitivities to different kinds of seasonal variation and these trait-
like differences are therefore likely to moderate the effects of seasons on thoughts, feelings, and
actions. Research on seasonal affective disorder provides an illustrative example, showing that
people differ in their vulnerability to seasonal depression and its sequelae (Levitan, 2022).
Similarly, Bronson (2004) makes the case that individuals differ in sensitivity to day length, with
implications for individual differences in the magnitude of seasonal effects on sex hormones and
reproductive outcomes. Individual differences in sensitivity to heat, humidity, and other
meteorological variables might be expected to moderate seasonal effects on aggression and other
outcomes mediated by physical discomfort. People also differ in their sensitivity to variation in
social norms and expectations, and in their eagerness to comply with those expectations (e.g.,
(Gangestad & Snyder, 2000). These individual differences may moderate seasonal effects that
result from the specific norms and expectations—and associated cognitions—that accompany
seasonal cultural events (such as Ramadan or Diwali).
Other kinds of individual differences may matter too. Some of the hypotheses identified
earlier in this article are predicated on seasonal variation in exposure to specific kinds of stimuli
that trigger specific kinds of cognitive associations (e.g., the iconography of Christmas may
activate cognitions associated with gift-giving, with implications for benevolence more
generally). The strength of these associations can vary across individuals depending upon their
previous experiences and learning histories, implying individual differences in the size of the
hypothesized effects. Other hypotheses are predicated on seasonal variation in stimuli that
33
activate specific motivational systems (e.g., darkness activates a self-protective motive; the
presence of sick people activates a disease-avoidance motive). Individuals differ in the extent to
which these motivational systems are readily activated (Neel et al., 2016). For example, some
people feel more vulnerable to disease than others (Duncan et al., 2009); so, if seasonal variation
in sickness leads to seasonal variation in disease-avoidant cognitions and behavior, these effects
may be more evident among individuals who feel more vulnerable to infection. More generally,
individual differences in the strength of specific cognitive associations and specific motives may
moderate specific effects resulting from seasonal variation in specific kinds of perceptual stimuli.
Cultural Differences
Just as the psychological effects of seasons may be moderated by individual differences,
so too may they be moderated by analogous cultural differences. For example, cultures differ in
their level of industrialization and infrastructure (e.g., climate-controlled office buildings,
covered bus shelters) that reduces individuals’ exposure to the meteorological and ecological
manifestations of seasons. The implication is that some seasonal effects may be more
pronounced in less industrialized cultures. Population-level economic variables—which can
interact with climatological variables to predict behavioral outcomes (Van de Vliert, 2013; Van
de Vliert et al., 2023; Van de Vliert & Murray, 2018)—might also moderate some effects of
seasonal variation on psychological phenomena.
One might also expect cultural differences in the magnitude of effects that result from
seasonal variation in the activation of specific motivational systems, simply because cultures
differ in the motivational profiles of their resident populations (Pick et al., 2022a; 2022b).
Cultures also differ in the kinds of perceptual stimuli and normative expectations that accompany
seasonal cultural events. For example, although Christmas is celebrated in many countries, the
34
popular iconographies of Christmas (e.g., visual depictions of St. Nicholas, Father Christmas,
and/or Santa Claus) vary across those countries, as do Christmas rituals and expectations. If
indeed these kinds of cultural stimuli and normative expectations account for some seasonal
effects on psychological phenomena, then these effects too may be stronger in some cultures
than others.
Toward a Systematic Science of “Seasonal Psychology”
In the preceding sections we have attempted to highlight the many effects that seasonal
cycles have on psychological phenomena, and the variety of underlying causal mechanisms
through which these effects may occur. One implication (which we have illustrated by offering
speculative hypotheses that still remain to be tested) is that existing evidence of seasonal effects
may represent just a preliminary peek at the full extent to which seasonal cycles influence human
psychology. If so, then there are also practical implications for scientists who study human
psychology. For example, since unaccounted-for variability (i.e., “noise”) in empirical data
depresses statistical power, psychological scientists might be wise to carefully consider
inferential costs that might accrue from failures to anticipate, and analytically account for,
seasonal variation in the data that they collect. And, if indeed there are (as we suspect) many
psychological effects of seasons that still remain to be discovered, then it might also be useful for
more psychological scientists to engage in more systemic efforts to discover them.
It is with these implications in mind that, in this section, we briefly summarize a set of
practical suggestions. Some suggestions are directed toward researchers who, like us, are
intrigued by the potential for a systematic science of “seasonal psychology,” are inspired to
initiate new studies that might reveal new effects of seasons on psychological variables, and who
might benefit from guidance about resources and tools that might aid those endeavors.
35
Additionally, we offer several suggestions for data collection and reporting practices that all
researchers (regardless of personal interest in seasonal phenomena) can engage in, to help ensure
that the collective database of the psychological sciences is more systematically attentive to the
effects of seasons on human psychology.
Useful Resources, Tools, and Techniques
In order to document seasonal effects, it is necessary to conduct analyses on data
collected across multiple seasons. Further, to test the replicability and robustness of those effects,
it may be necessary to conduct analyses on data collected across multiple years. Until recently,
these inferential requirements posed a substantial deterrent to the systematic study of seasonal
psychology. But times have changed. Advances in online data collection methods now make it
relatively easy to collect psychological data from large samples over long periods of time; and
there are many readily-available sources of “big data” that can also be analyzed for seasonal
trends (Adjerid & Kelley, 2018; Rafaeli et al., 2019). For instance, researchers now have the
opportunity to access results of many large-scale data-collection projects (e.g., Project Implicit,
Gosling Potter Internet Personality Project, YourMorals.org, Moral Machine), for which data
have been collected from millions of participants over months, years, and sometimes even
decades. Researchers can also easily access social media and search engine data (e.g., Twitter,
Reddit, Google, etc.) that can be mined to test for temporal trends, and recent studies have
productively seized on this opportunity to document seasonal cycles in psychological phenomena
(e.g., Griffiths et al., 2022; Hamamura & Chan, 2020).
There are unique inferential challenges associated with analyses of temporal trends in
data, which may seem daunting to researchers who are new to the study of seasonal variation.
But these challenges need not pose an obstacle; statistical tools are available to make rigorous
36
analyses of seasonal cycles relatively easy to learn and execute (for a useful and not-too-daunting
introduction to some of these inferential challenges and analytic means of addressing them, see
Jebb et al., 2015). Multiple powerful methodologies can be used to test for seasonal patterns in
psychological data (e.g., harmonic regression, ARIMA modelling, prophet modelling), and
readily-accessible R coding packages (e.g., rHarmonics, forecast, prophet) are available to
researchers to wish to implement them.
Researchers who study seasonal variation often face decisions about appropriate units of
analysis. For example, should calendar day be treated as the unit of analysis, or should data be
aggregated at the level of week, or month, or some other temporal unit? These analytic decisions
can have non-trivial inferential implications (e.g., aggregating data into larger temporal units
typically improves measurement reliability but reduces degrees of freedom—both of which have
implications for statistical power). In many ways, these decisions about temporal units are
analogous to the decisions about geographical units (e.g., postal code, state, country) that must
be made by researchers who study regional or cultural variation in psychological phenomena.
Recent advances in geographical psychology address the importance of thoughtfully selecting
geographical units of analysis that are appropriate to particular hypotheses or research questions
(Ebert et al., 2022), and these analytic considerations may help guide the analytic decisions made
by seasonal researchers too. For this reason—and because seasonal effects may be moderated by
geographical variables (as discussed above)—researchers studying seasonal variation may obtain
useful methodological guidance not only from the existing literature on seasonal effects, but also
from the literatures in cultural and geographical psychology.
Even if a seasonal effect is observed in some psychological phenomenon, it can be
challenging to infer the mechanism(s) through which that effect occurs. We have outlined many
37
possible sources of seasonal variation, involving meteorological, ecological, and cultural
variables that often covary and are difficult to disentangle. To help with this thorny inferential
task it can be useful to systematically assess, and compare, effects within multiple geographical
locations. For example, if a seasonal effect observed in the Northern Hemisphere is caused by
cyclical changes in meteorological variables (e.g., daylength), the timing of that effect—
measured in terms of calendar dates—would be expected to reverse in the Southern Hemisphere.
Useful clues can also be provided by careful empirical attention to other geographical variables
of the sort discussed above—such as latitude, which has implications for the extremity of
seasonal changes in specific meteorological and ecological variables, and thus for the sizes of
effects of those variables. In contrast, if an effect results from cyclical changes in specific
cultural practices (e.g., holidays), one would not expect it to be moderated by latitude, but
instead by cultural differences in the presence or absence—or the specific timing—of those
practices. It can also be useful to systematically assess, and compare, seasonal effects across
multiple years. For example, if a seasonal effect is caused by cyclical changes in a particular
ecological variable (e.g., disease prevalence), relevant evidence might include a comparison of
effect sizes across years with naturally varying levels of that variable (e.g., years with especially
low vs. high levels of seasonal influenza). Additionally, because naturalistic studies of seasonal
effects are inevitably correlational, it can be inferentially useful to complement them with
laboratory experiments. Even though annual seasonal cycles cannot be realistically manipulated
within an experiment, it is possible to experimentally manipulate some specific variables that
vary seasonally (e.g., ambient temperature; temporary perceptual exposure to lush vs. harsh
landscapes) and the results of these experiments may bear indirectly on specific underlying
mechanisms.
38
Data Collection and Reporting Practices
We are struck by historical parallels between the study of seasonal variation and the study
of cultural variation. Just as seasonal effects are often overlooked as a fundamental source of
variation in psychology, there was a time when cultural differences were similarly
underappreciated and overlooked. The belated emergence of a truly systematic science of
cultural psychology required that large numbers of researchers were sensitive to the possibility of
cultural differences and designed empirical studies to obtain data from multiple cultures. The
collection of data from multiple cultures is now recognized as a methodological imperative
within psychology and the behavioral sciences more broadly (Apicella et al., 2020; Henrich et
al., 2010). Analogously, the emergence of a truly systematic science of seasonal psychology will
require that large numbers of researchers be sensitive to the possibility of seasonal effects and
design empirical studies to obtain data across multiple seasons. Indeed, this too might be viewed
as an imperative. At the very least, when analyzing data that were collected over spans of months
or more, researchers can test for seasonal effects. Even better, researchers can proactively design
studies so that data are collected across multiple seasons, test for seasonal differences—even if
only in an exploratory way—and make the results (and the data) publicly available. By
deliberately collecting data that might potentially document the presence or absence of seasonal
effects, researchers—even those whose primary interests lie elsewhere—contribute to the
systematic study of seasonal variation in psychology.
Finally, every psychological scientist who does any empirical study can contribute to the
systematic study of seasonal variation by doing one very simple thing: When reporting on the
study, report when the data were collected. It is already common practice to report where data
were collected, and there are good reasons to do so (e.g., this information has implications for the
39
generalizability of findings, interpretation of replication attempts, and can be used to test for
regional and/or cultural differences in subsequent meta-analyses). For analogous reasons, it
would also be good practice to report when those data were collected. Doing so provides
information that may have implications for the generalizability of findings (perhaps especially
when the phenomenon of interest is already known to be seasonally variable), aids in the
interpretation of subsequent replication studies (regardless of the outcomes of those studies) and
allows for subsequent meta-analyses to test for seasonal effects. These and other benefits are
essential to a systematic science of seasonal psychology. Additionally, given the potential for
specific geographic and demographic variables—such as latitude, population density, etc.—to
moderate effects of seasonal cycles, it would also be good practice to be as precise as possible
(e.g., Hanoi, Hokkaido, New Hampshire), rather than vague (Vietnam, Japan, USA), when
reporting where data were gathered. This too will help support rigorous and systematic inquiry.
Conclusion
Almost a century ago, in an article on “The Seasonal Factor in Human Culture,”
Thomson (1939) wrote that seasons had such a powerful effect on the behavior of nomadic
tribespeople that, when observed during different seasons, these people appeared to be different
people entirely:
“It will be apparent that an onlooker, seeing these people at different seasons of
the year, would find them engaged in occupations so diverse, and with weapons
and utensils differing so much in character, that if he were unaware of the
seasonal influence on food supply, and consequently upon occupation, he would
be led to conclude that they were different groups.”
40
If anything, Thomson’s observations probably underestimate the impact of seasons on Homo
sapiens. Seasons exert profound influences on contemporary populations of people all over the
world, and seasonal effects occur across an extraordinarily wide range of psychological
phenomena. In short, seasons appear to be a fundamental source of variability in how people
think, feel, and behave. For many years, variability due to place (i.e., geography, culture,
ecological conditions) was largely overlooked in the theorizing and methodology of mainstream
psychology, and the psychological literature is richer now that it is no longer the case. We are of
the view that the impact of time (Varnum & Grossmann, 2017)—and time of year in particular—
has similarly been underappreciated, and that our understanding of human psychology will be
improved if more widespread efforts are undertaken to undo this oversight. To the extent that
seasons create variability in psychological phenomena, then it behooves researchers to be
attentive to that variability and, ideally, to measure it, account for it, and understand it. Rather
than remaining an overlooked source of noise in the database of the psychological sciences,
seasonal variation can instead be systematically documented as a key source of signal—a
fundamental feature of human psychology.
41
References
Aarøe, L., Osmundsen, M., & Petersen, M. B. (2016). Distrust as a disease avoidance strategy:
Individual differences in disgust sensitivity regulate generalized social trust. Frontiers in
Psychology, 7, 1038. https://doi.org/10.3389/fpsyg.2016.01038
Aarøe, L., Petersen, M. B., & Arceneaux, K. (2020). The behavioral immune system shapes
partisian preferences in modern democracies: Disgust sensitivity predicts voting for
socially conservative parties. Political Psychology, 41(6), 1073–1091.
https://doi.org/10.1111/pops.12665
Ackerman, J. M., Hill, S. E., & Murray, D. R. (2018). The behavioral immune system: Current
concerns and future directions. Social and Personality Psychology Compass, 12(2).
https://doi.org/10.1111/spc3.12371
Adjerid, I., & Kelley, K. (2018). Big data in psychology: A framework for research
advancement. American Psychologist, 73(7), 899.
American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental
Disorders (5th ed.).
Ancel, A., Beaulieu, M., & Gilbert, C. (2013). The different breeding strategies of penguins: A
review. Comptes Rendus Biologies, 336(1), 1–12.
https://doi.org/10.1016/j.crvi.2013.02.002
Anderson, C. A. (1989). Temperature and aggression: Ubiquitous effects of heat on occurrence
of human violence. Psychological Bulletin, 106(1), 74–96. https://doi.org/10.1037/0033-
2909.106.1.74
Anderson, C. A. (2001). Heat and violence. Current Directions in Psychological Science, 10(1),
33–38. https://doi.org/10.1111/1467-8721.00109
42
Aparicio-Ugarriza, R., Rumi, C., Luzardo-Socorro, R., Mielgo-Ayuso, J., Palacios, G., Bibiloni,
M. del M., Julibert, A., Argelich, E., Tur, J. A., & González-Gross, M. (2017). Seasonal
variation and diet quality among Spanish people aged over 55 years. Journal of
Physiology and Biochemistry, 74, 179–188. https://doi.org/10.1007/s13105-017-0599-4
Apicella, C., Norenzayan, A., & Henrich, J. (2020). Beyond WEIRD: A review of the last decade
and a look ahead to the global laboratory of the future. Evolution and Human Behavior,
41(5), 319–329. https://doi.org/10.1016/j.evolhumbehav.2020.07.015
Baum, A., & Valins, S. (1979). Architectural mediation of residential density and control:
Crowding and the regulation of social contact. Advances in Experimental Social
Psychology, 12, 131-175. https://doi.org/10.1016/S0065-2601(08)60261-0
Beery, A. K., Loo, T. J., & Zucker, I. (2008). Day length and estradiol affect same-sex affiliative
behavior in the female meadow vole. Hormones and Behavior, 54(1), 153–159.
https://doi.org/10.1016/j.yhbeh.2008.02.007
Belkin, L. Y., & Kouchaki, M. (2017). Too hot to help! Exploring the impact of ambient
temperature on helping. European Journal of Social Psychology, 47(5), 525–538.
https://doi.org/10.1002/ejsp.2242
Berman, M. G., Jonides, J., & Kaplan, S. (2008). The cognitive benefits of interacting with
nature. Psychological Science, 19(12), 1207–1212. https://doi.org/10.1111/j.1467-
9280.2008.02225.x
Berman, M. G., Kross, E., Krpan, K. M., Askren, M. K., Burson, A., Deldin, P. J., Kaplan, S.,
Sherdell, L., Gotlib, I. H., & Jonides, J. (2012). Interacting with nature improves
cognition and affect for individuals with depression. Journal of Affective Disorders,
140(3), 300–305. https://doi.org/10.1016/j.jad.2012.03.012
43
Bronson, F. H. (2004). Are humans seasonally photoperiodic? Journal of Biological Rhythms,
19(3), 180–192. https://doi.org/10.1177/0748730404264658
Buss, D. M., & Haselton, M. (2005). The evolution of jealousy. Trends in Cognitive Sciences,
9(11), 506-507. https://doi.org/10.1016/j.tics.2005.09.006
Carlsmith, J. M., & Anderson, C. A. (1979). Ambient temperature and the occurrence of
collective violence: A new analysis. Journal of Personality and Social Psychology, 37(3),
337–344. https://doi.org/10.1037/0022-3514.37.3.337
Chou, K.-L., Lee, T., & Ho, A. H. (2007). Does mood state change risk taking tendency in older
adults? Psychology and Aging, 22(2), 310-318. https://doi.org/10.1037/0882-
7974.22.2.310
Craig, C., Overbeek, R. W., Condon, M. V., & Rinaldo, S. B. (2016). A relationship between
temperature and aggression in NFL football penalties. Journal of Sport and Health
Science, 5(2), 205–210. https://doi.org/10.1016/j.jshs.2015.01.001
Crane, T. E., Latif, Y. A., Wertheim, B. C., Kohler, L. N., Garcia, D. O., Rhee, J. J., Seguin, R.,
Kazlauskaite, R., Shikany, J. M., & Thomson, C. A. (2019). Does season of reported
dietary intake influence diet quality? Analysis from the Women’s Health Initiative.
American Journal of Epidemiology, 188(7), 1304–1310.
https://doi.org/10.1093/aje/kwz087
Crossin, G. T., Hinch, S. G., Farrell, A. P., Higgs, D. A., Lotto, A. G., Oakes, J. D., & Healey,
M. C. (2004). Energetics and morphology of sockeye salmon: Effects of upriver
migratory distance and elevation. Journal of Fish Biology, 65(3), 788–810.
https://doi.org/10.1111/j.0022-1112.2004.00486.x
44
Cunningham, M. R. (1979). Weather, mood, and helping behavior: Quasi experiments with the
sunshine samaritan. Journal of Personality and Social Psychology, 37(11), 1947–1956.
https://doi.org/10.1037/0022-3514.37.11.1947
Dam, H., Jakobsen, K., & Mellerup, E. (1998). Prevalence of winter depression in Denmark.
Acta Psychiatrica Scandinavica, 97(1), 1–4. https://doi.org/10.1111/j.1600-
0447.1998.tb09954.x
Dantzer, R., & Kelley, K. W. (2007). Twenty years of research on cytokine-induced sickness
behavior. Brain, Behavior, and Immunity, 21(2), 153–160.
https://doi.org/10.1016/j.bbi.2006.09.006
de Castro, J. M. (1991). Seasonal rhythms of human nutrient intake and meal pattern. Physiology
& Behavior, 50(1), 243–248. https://doi.org/10.1016/0031-9384(91)90527-U
Demir, A., Uslu, M., & Arslan, O. E. (2016). The effect of seasonal variation on sexual
behaviors in males and its correlation with hormone levels: A prospective clinical trial.
Central European Journal of Urology, 69(3), 285–289.
https://doi.org/10.5173/ceju.2016.793
Duncan, L. A., Schaller, M., & Park, J. H. (2009). Perceived vulnerability to disease:
Development and validation of a 15-item self-report instrument. Personality and
Individual Differences, 47(6), 541–546. https://doi.org/10.1016/j.paid.2009.05.001
Dzogang, F., Goulding, J., Lightman, S., & Cristianini, N. (2017). Seasonal variation in
collective mood via Twitter content and medical purchases. In N. Adams, A. Tucker, &
D. Weston (Eds.), Advances in Intelligent Data Analysis XVI (Vol. 10584, pp. 63–74).
Springer International Publishing. https://doi.org/10.1007/978-3-319-68765-0_6
45
Ebert, T., Götz, F. M., Mewes, L., & Rentfrow, P. J. (2022). Spatial analysis for psychologists:
How to use individual-level data for research at the geographically aggregated level.
Psychological Methods. Advance online publication. https://doi.org/10.1037/met0000493
Eibach, R. P., Libby, L. K., & Ehrlinger, J. (2009). Priming family values: How being a parent
affects moral evaluations of harmless but offensive acts. Journal of Experimental Social
Psychology, 45(5), 1160–1163. https://doi.org/10.1016/j.jesp.2009.06.017
Eich, E., & Forgas, J. P. (2003). Mood, cognition, and memory. In A. F. Healy & R. W. Proctor
(Eds.), Handbook of psychology: Vol 4: Experimental psychology (pp. 61-83). New
York: Wiley.
Eisenberger, N. I., Inagaki, T. K., Mashal, N. M., & Irwin, M. R. (2010). Inflammation and
social experience: An inflammatory challenge induces feelings of social disconnection in
addition to depressed mood. Brain, Behavior, and Immunity, 24(4), 558–563.
Ekström, M. (2018). Seasonal altruism: How Christmas shapes unsolicited charitable giving.
Journal of Economic Behavior & Organization, 153, 177–193.
https://doi.org/10.1016/j.jebo.2018.07.004
Faulkner, J., Schaller, M., Park, J. H., & Duncan, L. A. (2004). Evolved disease-avoidance
mechanisms and contemporary xenophobic attitudes. Group Processes & Intergroup
Relations, 7(4), 333–353. https://doi.org/10.1177/1368430204046142
Ferguson, T. W., & Tamburello, J. A. (2015). The natural environment as a spiritual resource: A
theory of regional variation in religious adherence. Sociology of Religion, 76(3), 295–
314. https://doi.org/10.1093/socrel/srv029
Fredrickson, B., Roberts, T.-A., Noll, S., Quinn, D., & Twenge, J. (1998). That swimsuit
becomes you: Sex differences in self-objectification, restrained eating, and math
46
performance. Journal of Personality and Social Psychology, 75, 1098–1098.
https://doi.org/10.1037/h0090332
Gamble, J. L., & Hess, J. J. (2012). Temperature and violent crime in Dallas, Texas:
Relationships and implications of climate change. Western Journal of Emergency
Medicine, 13(3), 239–246. https://doi.org/10.5811/westjem.2012.3.11746
Gangestad, S. W., & Snyder, M. (2000). Self-monitoring: Appraisal and reappraisal.
Psychological Bulletin, 126(4), 530–555. https://doi.org/10.1037/0033-2909.126.4.530
Gassen, J., & Hill, S. E. (2019). Why inflammation and the activities of the immune system
matter for social and personality psychology (and not only for those who study health).
Social and Personality Psychology Compass, 13(6), e12471.
https://doi.org/10.1111/spc3.12471
Gilead, M., & Liberman, N. (2014). We take care of our own: Caregiving salience increases out-
group bias in response to out-group threat. Psychological Science, 25(7), 1380–1387.
https://doi.org/10.1177/0956797614531439
Golder, S. A., & Macy, M. W. (2011). Diurnal and seasonal mood vary with work, sleep, and
daylength across diverse cultures. Science, 333(6051), 1878–1881.
https://doi.org/10.1126/science.1202775
Goldsmith, K., Roux, C., & Cannon, C. (2021). Understanding the relationship between resource
scarcity and object attachment. Current Opinion in Psychology, 39, 26–30.
Götz, F. M., Stieger, S., Gosling, S. D., Potter, J., & Rentfrow, P. J. (2020). Physical topography
is associated with human personality. Nature Human Behaviour, 4(11), 1135–1144.
47
Greenberg, A. E. (2014). On the complementarity of prosocial norms: The case of restaurant
tipping during the holidays. Journal of Economic Behavior & Organization, 97, 103–112.
https://doi.org/10.1016/j.jebo.2013.10.014
Griffiths, S., Austen, E., Krug, I., & Blake, K. (2021). Beach body ready? Shredding for
summer? A first look at “seasonal body image.” Body Image, 37, 269–281.
https://doi.org/10.1016/j.bodyim.2021.03.004
Griffiths, S., Cowley-Court, T., Austen, E., Russo-Batterham, D., & Blake, K. (2022). “Spring is
the best time to lose weight”: Evidence that dieting is seasonal and reaches peak intensity
during Spring. Body Image, 41, 406–416. https://doi.org/10.1016/j.bodyim.2022.04.011
Grillon, C., Pellowski, M., Merikangas, K. R., & Davis, M. (1997). Darkness facilitates the
acoustic startle reflex in humans. Biological Psychiatry, 42(6), 453–460.
https://doi.org/10.1016/S0006-3223(96)00466-0
Griskevicius, V., Ackerman, J. M., Cantú, S. M., Delton, A. W., Robertson, T. E., Simpson, J.
A., Thompson, M. E., & Tybur, J. M. (2013). When the economy falters, do people spend
or save? Responses to resource scarcity depend on childhood environments.
Psychological Science, 24(2), 197–205. https://doi.org/10.1177/0956797612451471
Griskevicius, V., Cialdini, R. B., & Kenrick, D. T. (2006). Peacocks, Picasso, and parental
investment: The effects of romantic motives on creativity. Journal of Personality and
Social Psychology, 91(1), 63–76. https://doi.org/10.1037/0022-3514.91.1.63
Griskevicius, V., Goldstein, N. J., Mortensen, C. R., Cialdini, R. B., & Kenrick, D. T. (2006).
Going along versus going alone: When fundamental motives facilitate strategic
(non)conformity. Journal of Personality and Social Psychology, 91(2), 281–294.
https://doi.org/10.1037/0022-3514.91.2.281
48
Griskevicius, V., Tybur, J. M., Sundie, J. M., Cialdini, R. B., Miller, G. F., & Kenrick, D. T.
(2007). Blatant benevolence and conspicuous consumption: When romantic motives elicit
strategic costly signals. Journal of Personality and Social Psychology, 93(1), 85–102.
https://doi.org/10.1037/0022-3514.93.1.85
Guéguen, N., & Lamy, L. (2013). Weather and helping: Additional evidence of the effect of the
sunshine Samaritan. The Journal of Social Psychology, 153(2), 123–126.
https://doi.org/10.1080/00224545.2012.720618
Haertzen, C., Covi, L., Buxton, K., & Richards, H. (1993). Seasonal changes in rule infractions
among prisoners: A preliminary test of the temperature-aggression hypothesis.
Psychological Reports, 72(1), 195–200. https://doi.org/10.2466/pr0.1993.72.1.195
Hahn-Holbrook, J., Holt-Lunstad, J., Holbrook, C., Coyne, S. M., & Lawson, E. T. (2011).
Maternal defense: Breast feeding increases aggression by reducing stress. Psychological
Science, 22(10), 1288–1295. https://doi.org/10.1177/0956797611420729
Hamamura, T., & Chan, C. S. (2020). Anxious? Just Google it: Social ecological factors of
internet search records on anxiety. Emotion, 20(8), 1475–1484.
https://doi.org/10.1037/emo0000663
Han, L., Wang, K., Du, Z., Cheng, Y., Simons, J. S., & Rosenthal, N. E. (2000). Seasonal
variations in mood and behavior among Chinese medical students. The American Journal
of Psychiatry, 157(1), 133–135. https://doi.org/10.1176/ajp.157.1.133
Hart, B. L., & Hart, L. A. (2019). Sickness behavior in animals: Implications for health and
wellness. In J. C. Choe (Ed.), Encyclopedia of Animal Behavior (2nd ed., Vol. 1, pp. 171-
175). Elsevier.
49
Hartig, T., Mitchell, R., de Vries, S., & Frumkin, H. (2014). Nature and health. Annual Review of
Public Health, 35, 207–228. https://doi.org/10.1146/annurev-publhealth-032013-182443
Hellgren, E. C. (1998). Physiology of hibernation in bears. Ursus, 10, 467–477.
https://www.jstor.org/stable/3873159
Henrich, J., Heine, S. J., & Norenzayan, A. (2010). The weirdest people in the world?
Behavioral and Brain Sciences, 33 (2-3), 61-83.
https://doi.org/10.1017/S0140525X0999152X
Herold, A. H., Woodard, L. J., Roetzheim, R. G., Pamies, R. J., Young, D. L., & Micceri, T.
(1993). Seasonality of Chlamydia trachomatis genital infections in university women.
Journal of American College Health: J of ACH, 42(3), 117–120.
https://doi.org/10.1080/07448481.1993.9940826
Hopkins, S. J., & Rothwell, N. J. (1995). Cytokines and the nervous system I: expression and
recognition. Trends in Neurosciences, 18(2), 83–88.
Huang, J. Y., Ackerman, J. M., & Sedlovskaya, A. (2017). (De)contaminating product
preferences: A multi-method investigation into pathogen threat’s influence on used
product preferences. Journal of Experimental Social Psychology, 70, 143–152.
https://doi.org/10.1016/j.jesp.2017.01.001
Inagaki, T. K., Muscatell, K. A., Irwin, M. R., Moieni, M., Dutcher, J. M., Jevtic, I., Breen, E.
C., & Eisenberger, N. I. (2015). The role of the ventral striatum in inflammatory-induced
approach toward support figures. Brain, Behavior, and Immunity, 44, 247–252.
https://doi.org/10.1016/j.bbi.2014.10.006
50
Jebb, A. T., Tay, L., Wang, W., & Huang, Q. (2015). Time series analysis for psychological
research: Examining and forecasting change. Frontiers in Psychology, 6, 727.
https://doi.org/10.3389/fpsyg.2015.00727
Kaldewaij, R., Koch, S. B., Zhang, W., Hashemi, M. M., Klumpers, F., & Roelofs, K. (2019).
High endogenous testosterone levels are associated with diminished neural emotional
control in aggressive police recruits. Psychological Science, 30(8), 1161–1173.
Kasper, S., Wehr, T. A., Bartko, J. J., Gaist, P. A., & Rosenthal, N. E. (1989). Epidemiological
findings of seasonal changes in mood and behavior. A telephone survey of Montgomery
County, Maryland. Archives of General Psychiatry, 46(9), 823–833.
https://doi.org/10.1001/archpsyc.1989.01810090065010
Kegel, M., Dam, H., Ali, F., & Bjerregaard, P. (2009). The prevalence of seasonal affective
disorder (SAD) in Greenland is related to latitude. Nordic Journal of Psychiatry, 63(4),
331–335. https://doi.org/10.1080/08039480902799040
Kenrick, D. T., & MacFarlane, S. W. (1986). Ambient temperature and horn honking: A field
study of the heat/aggression relationship. Environment and Behavior, 18(2), 179–191.
https://doi.org/10.1177/001391658618200
Kerry, N., & Murray, D. R. (2020). Politics and parental care: Experimental and mediational
tests of the causal link between parenting motivation and social conservatism. Social
Psychological and Personality Science, 11(2), 284–292.
https://doi.org/10.1177/1948550619853598
Kottek, M., Grieser, J., Beck, C., Rudolf, B., & Rubel, F. (2006). World Map of the Köppen-
Geiger climate classification updated. Meteorologische Zeitschrift, 259–263.
https://doi.org/10.1127/0941-2948/2006/0130
51
Krems, J. A., Neel, R., Neuberg, S. L., Puts, D. A., & Kenrick, D. T. (2016). Women selectively
guard their (desirable) mates from ovulating women. Journal of Personality and Social
Psychology, 110(4), 551–573. https://doi.org/10.1037/pspi0000044
Krenzer, W. L. D., & Splan, E. D. (2018). Evaluating the heat-aggression hypothesis: The role of
temporal and social factors in predicting baseball related aggression. Aggressive
Behavior, 44(1), 83–88. https://doi.org/10.1002/ab.21726
Lambert, G. W., Reid, C., Kaye, D. M., Jennings, G. L., & Esler, M. D. (2002). Effect of
sunlight and season on serotonin turnover in the brain. Lancet, 360(9348), 1840–1842.
https://doi.org/10.1016/s0140-6736(02)11737-5
Lauritsen, J. L., & White. (2014). Seasonal Patterns in Criminal Victimization Trends. US
Department of Justice, Office of Justice Programs, Bureau of Justice Statistics.
https://bjs.ojp.gov/content/pub/pdf/spcvt.pdf
Levin, M. L., Xu, X., & Bartkowski, J. P. (2002). Seasonality of sexual debut. Journal of
Marriage and Family, 64(4), 871–884. https://doi.org/10.1111/j.1741-3737.2002.00871.x
Levitan, R. D. (2022). The chronobiology and neurobiology of winter seasonal affective
disorder. Dialogues in Clinical Neuroscience, 9(3), 315–324.
https://doi.org/10.31887/DCNS.2007.9.3/rlevitan
Lim, A. S. P., Gaiteri, C., Yu, L., Sohail, S., Swardfager, W., Tasaki, S., Schneider, J. A., Paquet,
C., Stuss, D. T., Masellis, M., Black, S. E., Hugon, J., Buchman, A. S., Barnes, L. L.,
Bennett, D. A., & Jager, P. L. D. (2018). Seasonal plasticity of cognition and related
biological measures in adults with and without Alzheimer disease: Analysis of multiple
cohorts. PLOS Medicine, 15(9), e1002647. https://doi.org/10.1371/journal.pmed.1002647
52
Ma, Y., Olendzki, B. C., Li, W., Hafner, A. R., Chiriboga, D., Hebert, J. R., Campbell, M.,
Sarnie, M., & Ockene, I. S. (2006). Seasonal variation in food intake, physical activity,
and body weight in a predominantly overweight population. European Journal of
Clinical Nutrition, 60(4), 519–528. https://doi.org/10.1038/sj.ejcn.1602346
Magnusson, A., & Boivin, D. (2003). Seasonal Affective Disorder: An overview. Chronobiology
International, 20(2), 189–207. https://doi.org/10.1081/CBI-120019310
Maille, A., Pillay, N., & Schradin, C. (2015). Seasonal variation in attention and spatial
performance in a wild population of the African striped mouse (Rhabdomys pumilio).
Animal Cognition, 18(6), 1231–1242. https://doi.org/10.1007/s10071-015-0892-y
Maner, J. K., Gailliot, M. T., Rouby, D. A., & Miller, S. L. (2007). Can’t take my eyes off you:
Attentional adhesion to mates and rivals. Journal of Personality and Social Psychology,
93(3), 389–401. https://doi.org/10.1037/0022-3514.93.3.389
Maner, J. K., Kenrick, D. T., Becker, D. V., Robertson, T. E., Hofer, B., Neuberg, S. L., Delton,
A. W., Butner, J., & Schaller, M. (2005). Functional projection: How fundamental social
motives can bias interpersonal perception. Journal of Personality and Social Psychology,
88(1), 63–78. https://doi.org/10.1037/0022-3514.88.1.63
Markey, P. M., & Markey, C. N. (2013). Seasonal variation in internet keyword searches: A
proxy assessment of sex mating behaviors. Archives of Sexual Behavior, 42(4), 515–521.
https://doi.org/10.1007/s10508-012-9996-5
Martinez, M. E. (2018). The calendar of epidemics: Seasonal cycles of infectious diseases. PLoS
Pathogens, 14(11), e1007327. https://doi.org/10.1371/journal.ppat.1007327
Martinez-Bakker, M., Bakker, K. M., King, A. A., & Rohani, P. (2014). Human birth
seasonality: Latitudinal gradient and interplay with childhood disease dynamics.
53
Proceedings of the Royal Society B: Biological Sciences, 281(1783), 20132438.
https://doi.org/10.1098/rspb.2013.2438
Matz, C., Stieb, D., & Brion, O. (2015). Urban-rural differences in daily time-activity patterns,
occupational activity and housing characteristics. Environmental Health : A Global
Access Science Source, 14, 88. https://doi.org/10.1186/s12940-015-0075-y
Merikanto, I., Lahti, T., Castaneda, A. E., Tuulio-Henriksson, A., Aalto-Setälä, T., Suvisaari, J.,
& Partonen, T. (2012). Influence of seasonal variation in mood and behavior on cognitive
test performance among young adults. Nordic Journal of Psychiatry, 66(5), 303–310.
https://doi.org/10.3109/08039488.2011.633618
Mersch, P. P. A., Middendorp, H. M., Bouhuys, A. L., Beersma, D. G. M., & van den
Hoofdakker, R. H. (1999). Seasonal affective disorder and latitude: A review of the
literature. Journal of Affective Disorders, 53(1), 35–48. https://doi.org/10.1016/S0165-
0327(98)00097-4
Meyer, C., Muto, V., Jaspar, M., Kussé, C., Lambot, E., Chellappa, S. L., Degueldre, C., Balteau,
E., Luxen, A., Middleton, B., Archer, S. N., Collette, F., Dijk, D.-J., Phillips, C., Maquet,
P., & Vandewalle, G. (2016). Seasonality in human cognitive brain responses.
Proceedings of the National Academy of Sciences USA, 113(11), 3066–3071.
https://doi.org/10.1073/pnas.1518129113
Micciolo, R., Williams, P., Zimmermann-Tansella, Ch., & Tansella, M. (1991). Geographical
and urban—rural variation in the seasonality of suicide: Some further evidence. Journal
of Affective Disorders, 21(1), 39–43. https://doi.org/10.1016/0165-0327(91)90017-M
54
Michalon, M., Eskes, G. A., & Mate-Kole, C. C. (1997). Effects of light therapy on
neuropsychological function and mood in seasonal affective disorder. Journal of
Psychiatry and Neuroscience, 22(1), 19–28.
Miles-Novelo, A., & Anderson, C. A. (2022). Climate change and human behavior: Impacts of a
rapidly changing climate on human aggression and violence. Cambridge University
Press. https://doi.org/10.1017/9781108953078
Miller, A. H., & Raison, C. L. (2016). The role of inflammation in depression: From
evolutionary imperative to modern treatment target. Nature Reviews Immunology, 16(1),
22–34. https://doi.org/10.1038/nri.2015.5
Mills, L. S., Bragina, E. V., Kumar, A. V., Zimova, M., Lafferty, D. J. R., Feltner, J., Davis, B.
M., Hackländer, K., Alves, P. C., Good, J. M., Melo-Ferreira, J., Dietz, A., Abramov, A.
V., Lopatina, N., & Fay, K. (2018). Winter color polymorphisms identify global hot spots
for evolutionary rescue from climate change. Science, 359(6379), 1033–1036.
https://doi.org/10.1126/science.aan8097
Murray, D. R., Kerry, N., & Gervais, W. M. (2019). On disease and deontology: Multiple tests of
the influence of disease threat on moral vigilance. Social Psychological and Personality
Science, 10(1), 44–52. https://doi.org/10.1177/1948550617733518
Murray, D. R., & Schaller, M. (2012). Threat(s) and conformity deconstructed: Perceived threat
of infectious disease and its implications for conformist attitudes and behavior. European
Journal of Social Psychology, 42(2), 180–188. https://doi.org/10.1002/ejsp.863
Murray, D. R., & Schaller, M. (2016). The behavioral immune system: Implications for social
cognition, social interaction, and social influence. Advances in Experimental Social
Psychology, 53, 75-129. https://doi.org/10.1016/bs.aesp.2015.09.002
55
Muthukrishna, M., & Henrich, J. (2019). A problem in theory. Nature Human Behaviour, 3(3),
221–229. https://doi.org/10.1038/s41562-018-0522-1
Nave, G., Nadler, A., Dubois, D., Zava, D., Camerer, C., & Plassmann, H. (2018). Single-dose
testosterone administration increases men’s preference for status goods. Nature
Communications, 9(1), 2433. https://doi.org/10.1038/s41467-018-04923-0
Neel, R., Kenrick, D. T., White, A. E., & Neuberg, S. L. (2016). Individual differences in
fundamental social motives. Journal of Personality and Social Psychology, 110(6), 887–
907. http://dx.doi.org.ezproxy1.lib.asu.edu/10.1037/pspp0000068
Network for Good. (2014). Online Giving Statistics. Charity Navigator.
http://www.charitynavigator.org/index.cfm?bay=content.view&cpid=1360
Neuberg, S. L., Kenrick, D. T., & Schaller, M. (2011). Human threat management systems: Self-
protection and disease avoidance. Neuroscience & Biobehavioral Reviews, 35(4), 1042–
1051. https://doi.org/10.1016/j.neubiorev.2010.08.011
O’Brien, J. T., Sahakian, B. J., & Checkley, S. A. (1993). Cognitive impairments in patients with
seasonal affective disorder. The British Journal of Psychiatry, 163, 338–343.
https://doi.org/10.1192/bjp.163.3.338
Oishi, S., & Graham, J. (2010). Social ecology: Lost and found in psychological science.
Perspectives on Psychological Science, 5(4), 356–377.
https://doi.org/10.1177/1745691610374588
Okada, M. (2018). Influence of muscle mass and outdoor environmental factors on appetite and
satiety feeling in young Japanese women. International Journal of Environmental
Research and Public Health, 15(1), E167. https://doi.org/10.3390/ijerph15010167
56
Palmer, S. E., & Schloss, K. B. (2010). An ecological valence theory of human color preference.
Proceedings of the National Academy of Sciences USA, 107(19), 8877–8882.
https://doi.org/10.1073/pnas.0906172107
Park, M., Thom, J., Mennicken, S., Cramer, H., & Macy, M. (2019). Global music streaming
data reveal diurnal and seasonal patterns of affective preference. Nature Human
Behavior, 3, 230–236. https://doi.org/10.1038/s41562-018-0508-z
Peterson, C. K., & Harmon-Jones, E. (2009). Circadian and seasonal variability of resting frontal
EEG asymmetry. Biological Psychology, 80(3), 315–320.
https://doi.org/10.1016/j.biopsycho.2008.11.002
Pettijohn, T. F., Williams, G. M., & Carter, T. C. (2010). Music for the seasons: Seasonal music
preferences in college students. Current Psychology, 29(4), 328–345.
https://doi.org/10.1007/s12144-010-9092-8
Petty, R. E., & Briñol, P. (2015). Emotion and persuasion: Cognitive and meta-cognitive
processes impact attitudes, Cognition and Emotion, 29(1), 1-26.
https://doi.org/10.1080/02699931.2014.967183
Pick, C., Ko, A., Kenrick, D. T., Wiezel, A., Wormley, A. S., Awad, E., Al-Shawaf, L., Barry,
O., Bereby-Meyer, Y, Boonyasiriwat, W., Brandstätter, E., Ceylan-Batur, S., Choy, B. K.
C., Crispim, A. C., Cruz, J. E., David, D., David, O. A., Defelipe, R. P., Elmas, P.,
Espinosa, A., Fernandez, A. M., Fetvadjiev, V. H., Fetvadjieva, S., Fischer, R., …
Varnum, M. E. W. (2022a). Fundamental social motives measured across 42 cultures in
two waves. Scientific Data, 9, 499. https://doi.org/10.1038/s41597-022-01579-w
Pick, C. M., Ko, A., Wormley, A. S., Wiezel, A., Kenrick, D. T., Al-Shawaf, L., Barry, O.,
Bereby-Meyer, Y., Boonyasiriwat, W., Brandstätter, E., Crispim, A. C., Cruz, J. E.,
57
David, D., David, O. A., Defelipe, R. P., Elmas, P., Espinosa, A., Fernandez, A. M.,
Fetvadjiev, V. H., … Varnum, M. E. W. (2022b). Family still matters: Human social
motivation across 42 countries during a global pandemic. Evolution and Human
Behavior. https://doi.org/10.1016/j.evolhumbehav.2022.09.003
Praschak-Rieder, N., Willeit, M., Wilson, A. A., Houle, S., & Meyer, J. H. (2008). Seasonal
variation in human brain serotonin transporter binding. Archives of General Psychiatry,
65(9), 1072-1078. https://doi.org/10.1001/archpsyc.65.9.1072
Qin, D., Chu, X., Feng, X., Li, Z., Yang, S., Lü, L., Yang, Q., Pan, L., Yin, Y., Li, J., Xu, L.,
Chen, L., & Hu, X. (2015). The first observation of seasonal affective disorder symptoms
in Rhesus macaque. Behavioural Brain Research, 292, 463–469.
https://doi.org/10.1016/j.bbr.2015.07.005
Quinn, D. M., Kallen, R. W., Twenge, J. M., & Fredrickson, B. L. (2006). The disruptive effect
of self-objectification on performance. Psychology of Women Quarterly, 30(1), 59–64.
https://doi.org/10.1111/j.1471-6402.2006.00262.x
Rafaeli, A., Ashtar, S., & Altman, D. (2019). Digital traces: New data, resources, and tools for
psychological-science research. Current Directions in Psychological Science, 28(6), 560–
566. https://doi.org/10.1177/0963721419861410
Rentfrow, P. J. (2020). Geographical psychology. Current Opinion in Psychology, 32, 165–170.
https://doi.org/10.1016/j.copsyc.2019.09.009
Rodeheffer, C. D., Hill, S. E., & Lord, C. G. (2012). Does this recession make me look black?
The effect of resource scarcity on the categorization of biracial faces. Psychological
Science, 23(12), 1476–1478. https://doi.org/10.1177/0956797612450892
58
Ronay, R., & Hippel, W. von. (2010). The presence of an attractive woman elevates testosterone
and physical risk taking in young men. Social Psychological and Personality Science,
1(1), 57–64. https://doi.org/10.1177/1948550609352807
Rothwell, N. J., & Hopkins, S. J. (1995). Cytokines and the nervous system II: actions and
mechanisms of action. Trends in Neurosciences, 18(3), 130–136.
https://doi.org/10.1016/0166-2236(95)93890-A
Roux, C., Goldsmith, K., & Bonezzi, A. (2015). On the psychology of scarcity: When reminders
of resource scarcity promote selfish (and generous) behavior. Journal of Consumer
Research, 42(4), 615–631. https://doi.org/10.1093/jcr/ucv048
Sachs, C. J., & Chu, L. D. (2000). The association between professional football games and
domestic violence in Los Angeles County. Journal of Interpersonal Violence, 15(11),
1192–1201. https://doi.org/10.1177/088626000015011006
Sandman, N., Merikanto, I., Määttänen, H., Valli, K., Kronholm, E., Laatikainen, T., Partonen,
T., & Paunio, T. (2016). Winter is coming: Nightmares and sleep problems during
seasonal affective disorder. Journal of Sleep Research, 25(5), 612–619.
https://doi.org/10.1111/jsr.12416
Sawada, N., Auger, E., & Lydon, J. E. (2018). Activation of the behavioral immune system:
Putting the brakes on affiliation. Personality and Social Psychology Bulletin, 44(2), 224–
237. https://doi.org/10.1177/0146167217736046
Schaller, M. (2018). The parental care motivational system and why it matters (for everyone).
Current Directions in Psychological Science, 27(5), 295–301.
https://doi.org/10.1177/0963721418767873
59
Schaller, M., Kenrick, D. T., Neel, R., & Neuberg, S. L. (2017). Evolution and human
motivation: A fundamental motives framework. Social and Personality Psychology
Compass, 11(6), e12319. https://doi.org/10.1111/spc3.12319
Schaller, M., Murray, D. R., & Hofer, M. K. (2022). The behavioural immune system and
pandemic psychology: The evolved psychology of disease-avoidance and its implications
for attitudes, behaviour, and public health during epidemic outbreaks. European Review
of Social Psychology, 33(2), 360-396. https://doi.org/10.1080/10463283.2021.1988404
Schaller, M., & Park, J. H. (2011). The behavioral immune system (and why it matters). Current
Directions in Psychological Science, 20(2), 99–103.
https://doi.org/10.1177/0963721411402596
Schaller, M., Park, J. H., & Mueller, A. (2003). Fear of the dark: Interactive effects of beliefs
about danger and ambient darkness on ethnic stereotypes. Personality and Social
Psychology Bulletin, 29(5), 637–649. https://doi.org/10.1177/0146167203029005008
Schinasi, L. H., & Hamra, G. B. (2017). A time series analysis of associations between daily
temperature and crime events in Philadelphia, Pennsylvania. Journal of Urban Health,
94(6), 892–900. https://doi.org/10.1007/s11524-017-0181-y
Schloss, K. B., & Heck, I. A. (2017). Seasonal changes in color preferences are linked to
variations in environmental colors: A longitudinal study of fall. I-Perception, 8(6),
2041669517742177. https://doi.org/10.1177/2041669517742177
Schloss, K. B., Nelson, R., Parker, L., Heck, I. A., & Palmer, S. E. (2017). Seasonal variations in
color preference. Cognitive Science, 41(6), 1589–1612.
https://doi.org/10.1111/cogs.12429
60
Schloss, K. B., & Palmer, S. E. (2014). The politics of color: Preferences for Republican red
versus Democratic blue. Psychonomic Bulletin & Review, 21(6), 1481–1488.
https://doi.org/10.3758/s13423-014-0635-0
Schroeder, B., Tetlow, P., Sanfilippo, J. S., & Hertweck, S. P. (2001). Is there a seasonal
variation in gonorrhea and chlamydia in adolescents? Journal of Pediatric and
Adolescent Gynecology, 14(1), 25–27. https://doi.org/10.1016/s1083-3188(00)00079-6
Serisier, S., Feugier, A., Delmotte, S., Biourge, V., & German, A. J. (2014). Seasonal variation
in the voluntary food intake of domesticated cats (Felis catus). PLOS ONE, 9(4), e96071.
https://doi.org/10.1371/journal.pone.0096071
Shephard, R. J., & Aoyagi, Y. (2009). Seasonal variations in physical activity and implications
for human health. European Journal of Applied Physiology, 107(3), 251–271.
https://doi.org/10.1007/s00421-009-1127-1
Smals, A. G. H., Kloppenborg, P. W. C., & Benraad, Th. J. (1976). Circannual cycle in plasma
testosterone levels in man. The Journal of Clinical Endocrinology & Metabolism, 42(5),
979–982. https://doi.org/10.1210/jcem-42-5-979
Smith, T. W. (1979). Happiness: Time trends, seasonal variations, intersurvey differences, and
other mysteries. Social Psychology Quarterly, 42(1), 18–30.
https://doi.org/10.2307/3033870
Sng, O., Neuberg, S. L., Varnum, M. E. W., & Kenrick, D. T. (2017). The crowded life is a slow
life: Population density and life history strategy. Journal of Personality and Social
Psychology, 112(5), 736–754. https://doi.org/10.1037/pspi0000086
61
Sng, O., Neuberg, S. L., Varnum, M. E. W., & Kenrick, D. T. (2018). The behavioral ecology of
cultural psychological variation. Psychological Review, 125(5), 714–743.
https://doi.org/10.1037/rev0000104
Stokols, D. (1992). Establishing and maintaining healthy environments: Toward a social ecology
of health promotion. American Psychologist, 47(1), 6–22. https://doi.org/10.1037/0003-
066X.47.1.6
Sun, L., Tang, J., Liljenbäck, H., Honkaniemi, A., Virta, J., Isojärvi, J., Karjalainen, T.,
Kantonen, T., Nuutila, P., Hietala, J., Kaasinen, V., Kalliokoski, K., Hirvonen, J.,
Scheinin, H., Helin, S., Eerola, K., Savontaus, E., Yatkin, E., Rinne, J. O., Roivainen, A.,
& Nummenmaa, L. (2021). Seasonal variation in the brain μ-Opioid receptor availability.
Journal of Neuroscience, 41(6) 1265-1273. https://doi.org/10.1523/JNEUROSCI.2380-
20.2020
Tooby, J., Cosmides, L., Sell, A., Lieberman, D., & Sznycer, D. (2008). Internal regulatory
variables and the design of human motivation: A computational and evolutionary
approach. Handbook of Approach and Avoidance Motivation, 15, 251.
Turbill, C., Bieber, C., & Ruf, T. (2011). Hibernation is associated with increased survival and
the evolution of slow life histories among mammals. Proceedings of the Royal Society B,
278, 3355–3363. https://doi.org/10.1098/rspb.2011.0190
Uskul, A. K., & Oishi, S. (2020). What is socio-ecological psychology? Current Opinion in
Psychology, 32, 181–184. https://doi.org/10.1016/j.copsyc.2020.01.001
van Bergen, E. van, & Beldade, P. (2019). Seasonal plasticity in anti-predatory strategies:
Matching of color and color preference for effective crypsis. Evolution Letters, 3(3),
313–320. https://doi.org/10.1002/evl3.113
62
Van de Vliert, E. (2013). Climato-economic habitats support patterns of human needs, stresses,
and freedoms. Behavioral and Brain Sciences, 36(5), 465–480.
https://doi.org/10.1017/S0140525X12002828
Van de Vliert, E. (2020). The global ecology of differentiation between us and them. Nature
Human Behaviour, 4(3), 270–278. https://doi.org/10.1038/s41562-019-0783-3
Van de Vliert, E., Conway III, L. G., & Van Lange, P. A. (2023). Enriching psychology by
zooming out to general mindsets and practices in natural habitats. Perspectives on
Psychological Science. https://doi.org/10.1177/1745691622114165
Van de Vliert, E., Huang, X., & Parker, P. M. (2004). Do colder and hotter climates make richer
societies more, but poorer societies less, happy and altruistic? Journal of Environmental
Psychology, 24(1), 17–30. https://doi.org/10.1016/S0272-4944(03)00021-5
Van de Vliert, E., & Murray, D. R. (2018). Climate and creativity: Cold and heat trigger
invention and innovation in richer populations. Creativity Research Journal, 30(1), 17–
28. https://doi.org/10.1080/10400419.2018.1411571
Van de Vliert, E., & Van Lange, P. A. M. (2019). Latitudinal psychology: An ecological
perspective on creativity, aggression, happiness, and beyond. Perspectives on
Psychological Science, 14(5), 860–884. https://doi.org/10.1177/1745691619858067
Van Lange, P. A. M., Rinderu, M. I., & Bushman, B. J. (2017). Aggression and violence around
the world: A model of CLimate, Aggression, and Self-control in Humans (CLASH).
Behavioral and Brain Sciences, 40, e75. https://doi.org/10.1017/S0140525X16000406
Varnum, M. E. W., & Grossmann, I. (2017). Cultural change: The how and the why.
Perspectives on Psychological Science, 12(6), 956-972.
https://doi.org/10.1177/1745691617699971
63
Velo, J. R., Stewart, J. L., Hasler, B. P., Towers, D. N., & Allen, J. J. B. (2012). Should it matter
when we record? Time of year and time of day as factors influencing frontal EEG
asymmetry. Biological Psychology, 91(2), 283–291.
https://doi.org/10.1016/j.biopsycho.2012.06.010
Wang, I. M., & Ackerman, J. M. (2019). The infectiousness of crowds: Crowding experiences
are amplified by pathogen threats. Personality and Social Psychology Bulletin, 45(1),
120–132. https://doi.org/10.1177/0146167218780735
Wege, M. L., & Raveling, D. G. (1983). Factors influencing the timing, distance, and path of
migrations of Canada geese. The Wilson Bulletin, 95(2), 209–221.
Wehr, T. A., & Rosenthal, N. E. (1989). Seasonality and affective illness. The American Journal
of Psychiatry, 146(7), 829–839. https://doi.org/10.1176/ajp.146.7.829
Welling, L. L. M., Jones, B. C., DeBruine, L. M., Conway, C. A., Law Smith, M. J., Little, A. C.,
Feinberg, D. R., Sharp, M. A., & Al-Dujaili, E. A. S. (2007). Raised salivary testosterone
in women is associated with increased attraction to masculine faces. Hormones and
Behavior, 52(2), 156–161. https://doi.org/10.1016/j.yhbeh.2007.01.010
Wellings, K., Macdowall, W., Catchpole, M., & Goodrich, J. (1999). Seasonal variations in
sexual activity and their implications for sexual health promotion. Journal of the Royal
Society of Medicine, 92(2), 60–64. https://doi.org/10.1177/014107689909200204
Wilson, A. P., & Boelkins, R. C. (1970). Evidence for seasonal variation in aggressive behaviour
by Macaca mulatta. Animal Behaviour, 18, 719–724. https://doi.org/10.1016/0003-
3472(70)90017-5
64
Wilson, M., & Daly, M. (1985). Competitiveness, risk taking, and violence: The young male
syndrome. Ethology and Sociobiology, 6(1), 59–73. https://doi.org/10.1016/0162-
3095(85)90041-X
Wu, Y., Zhang, Y., Ou, J., Hu, Y., & Zilioli, S. (2020). Exogenous testosterone increases the
audience effect in healthy males: Evidence for the social status hypothesis. Proceedings
of the Royal Society B: Biological Sciences, 287(1931), 20200976.
https://doi.org/10.1098/rspb.2020.0976
