Abstract
Artistic behavior as aesthetically enhancing activities is conceptualized as a functionally autonomous activity within the evolved human behavioral repertoire. Accordingly, it should be intrinsically motivated, and it might also be expected to be temporally stable and domain specific. Preferential freely-pursued activities reflect intrinsic motivation and offer a valuable measure of artistic motivation. We used a large decades-long real-life public Brazilian data set from university applications to test these ideas. We analysed data on extra-class activities from 674.699 late-adolescents applying for university courses between 1987 and 2004, mostly between 17 and 19 years of age; approximately half men and half women. We found that 27% of individuals reported that Artistic/cultural activities were the leisure-time activity they participated in most frequently, and 32% reported they spent the longest period of free-time doing Artistic-activities (theater/cinema, music, dance, art-craft/plastic arts). Interestingly, from this whole sample, only less than 3% actually applied for artistic careers, which suggests that the prevalence of prioritizing artistic activities is higher than commonly assumed and includes not only professional artists, but also many hobbyists, amateurs and dedicated fans. Further, artistic careers applicants prioritize art almost three times more than the total of applicants, suggesting its specificity. After controlling for inconsistency of answer options during the period, prioritizing both Artistic/cultural and Artistic-activities remained temporally stable, as predicted. Despite limitations, overall results supported the hypotheses that artistic behavior is more intrinsically motivated, domain specific, and temporally stable. This plausibly demonstrates that artistic propensity has at least partly an evolved nature.
Introduction
Motivation of behavior has experienced a revival of interest from an evolutionary perspective (Cosmides & Tooby, 2013). The classical ‘pyramid of needs’ was updated through a life-history evolutionary approach (Kenrick, Griskevicius, Neuberg, & Schaller, 2010), offering implications for Economy, Politics, and Health (Schaller, Kenrick, Neel, & Neuberg, 2017). Even motivation for sports has recently been approached in evolutionary terms (Deaner, Balish, & Lombardo, 2016). Indeed, in order to be converted into behavioral action, the output of cognitive mechanisms requires motivational processes (Anselme, 2016; Berridge, 2012). The evolved species-typical psychological mechanisms that process specific information relevant to ancestral adaptive problems motivate behaviors that solve those problems (Starratt & Shackelford, 2010). The functional/adaptive significance of a given set of behaviors depends on the underlying capabilities as well as on the forces that motivate a species to perform and sustain them in appropriate contexts (Bispham, 2009). The motivation system helps animals to behave and evaluate the fitness consequences of their actions, and such motivation system must evolve along with the related behaviors (Batali & Grundy, 1996). In this sense, motivation and cognition co-evolve with one another (Ermer, Cosmides, & Tooby, 2008). Thus, the existence of specific feelings, desires, pleasures, or intrinsic motivation for a given activity possibly signal ancestral biological advantages and indicate its evolved nature (Huron, 2005; Thornhill, 2003).
Evolutionary approaches to motivation can help in explaining psychological faculties that lack definitive empirical support of [and general consensus about] its possible evolved nature. Artistic tendencies are a good candidate (cf. Varella, 2021). Over the last 30 years, a developing body of theoretical literature approached artistic precursors, capacities and behaviors as an integral part of human nature (Davies, 2012; Dissanayake, 1988, 1992; Dutton, 2009; Eibl-Eibesfeldt, 1989; Høgh-Olesen, 2018; Martindale, Locher, Petrov, & Berleant, 2007; Menninghaus, 2019; Richards, 2019; Sütterlin, Schiefenhövel, Lehmann, Forster, & Apfelauer, 2014; Varella, Souza, & Ferreira, 2011; Varella, Valentova, & Fernández, 2017). Much work remains to be done regarding the conceptual refinement of artistic capacities, including work on its definitions, multifaceted components, multiple functions, and distinction between proximate and distal factors (Fitch, 2015; Honing & Ploeger, 2012; Menninghaus, 2019; Merker, Morley, & Zuidema, 2015; Seghers, 2016; Varella, Souza, & Ferreira, 2012, 2017). Moreover, to avoid ‘just-so stories’, pitfalls and anecdotal evidence (Honing & Ploeger, 2012; Varella et al., 2011, 2013, 2017), more empirical research is needed, particularly addressing many artistic modalities simultaneously (Brown, 2018) to probe whether they share the same evolutionary influences (cf. Varella, 2021; Varella, Štěrbová, Bártová, Fisher, & Valentova, 2022). Hence, an evolutionary approach to artistic motivation is a promising way to uncover its possible particular features and indicate valuable evolutionary insights (Merker et al., 2015; Varella, 2021).
Artistic activities can be broadly defined as multimodal and extraordinary aesthetically enhancing activities, including behaviors, its products, and its appreciations (Varella, 2018; Varella et al., 2011, 2017). The term “artisticality” (Varella et al., 2017) encompasses the propensities to develop psychological faculties that underlie a whole array of multimodal and extraordinary aesthetically enhancing activities, including behaviors, its products, and appreciations across cultures, historical periods, and species (Varella, 2018; Varella et al., 2017). Artisticality covers propensities for developing capacities in five interrelated sub-domains, mostly focused on aesthetically enhancing of images and objects (Visual/plastic arts), stories and narratives (Literary/scenic arts), melodic and rhythmic sounds (Musical arts), body movements (Circus arts), and tastes and smells (Olfactory arts) (Varella, 2018; Varella et al., 2017).
The three main psychological components of artisticality are capacities for (re)creative (re)production, aesthetic appreciation, and artistic motivations (Bispham, 2009; Merker et al., 2015; Varella et al., 2011, 2017; Watanabe, 2013). Capacities for production and appreciation relate to the abilities, biases and ways of cognitive processing during executive and perceptive artistic actions, respectively (Varella et al., 2011). Recently, Varella (2021) proposed that artistic motivations are what compels and reinforce individuals to engage and maintain engagement in artistic activities, both production and appreciation. Artistic motivation drives and rewards individuals to use their artistic capacities to actively or passively engage in aesthetically-oriented activities with some level of commitment. Active and passive artistic engagement activate a different balance of executive and perceptive capacities, and offer slightly different personal outcomes in terms of subjective well-being, health and therapy (cf. Brown, 2018; Kaptein, Hughes, Murray, & Smyth, 2018; Węziak-Białowolska, Białowolski, & Sacco, 2019; Wheatley & Bickerton, 2017). However, despite possible distinct influences of situational and individual factors in each mode of artistic engagement, it is suggested that likely the same basic motivational system underlies both forms of artistic engagement. For instance, Sacks (2008) describes a case in which a surgeon who was a fan of rock music, who previously had just a few piano lessons as a boy, got struck by a lightning and a few months later felt a sudden craving for listening to piano music. After buying and listening to many classical recordings, the person felt the desire to play the piano, and much later to compose piano music. This suggests that the same motivational factors might activate both the appreciative artistic capacities leading the passive artistic engagement and later the productive capacities leading to active engagement.
The evolutionary functions of artistic motivation might be to initiate, gratify and sustain aesthetically enhancing activities in (preparation to) contexts and phases of life in which artistic capacities might have produced ancestral fitness pay-offs, such as in forms of kin/group cohesion, general improvements of cognition, and promotion of mate selection and competition (De Tiège, Verpooten, & Braeckman, 2021; Dissanayake, 2008; Menninghaus, 2019; Varella, Ferreira, Cosentino, Ottoni, & Bussab, 2010, 2017, 2022). So far, the sexual selection hypothesis for the evolution of artisticality is the one that has received most empirical support (for reviews see, Fink, Bläsing, Ravignani, & Shackelford, 2021; Karamihalev, 2013; Ravignani, 2018; Varella et al., 2022). Nevertheless, because the different proposed functions for artisticality are not mutually exclusive (Menninghaus, 2019), much effort should be put to test different propositions simultaneously (cf. Varella, 2021; Varella et al., 2022). Furthermore, to test for specific adaptive values of artisticality is not the same as to reunite the converging interdisciplinary evidence pointing to the evolved status of artisticality (Honing & Ploeger, 2012; Huron, 2001; Seghers, 2016; Varella, 2018; Varella et al., 2010). That is, it is possible to empirically test whether artistic motivations and/or capacities (and their consequent behavioral patterns) exhibit the typical features of evolved adaptations without testing any specific adaptive function. Following Varella (2021), this study focuses on the possible evolved psychological structure of artistic motivation, analyzing its source, specificity, and temporal stability.
Evolutionary minded researchers have independently hypothesized about the main design feature of artistic motivation: its mainly internal source (Varella, 2021). Morris (1962) concludes that the motivation for picture-making, which is shared between apes and humans, has an element of self-rewarding activation. Csikszentmihalyi (1996) describes creativity as an autotelic activity that is enjoyable in itself. Dutton (2009) considers direct artistic pleasure as one of the main features of human artistic propensity, and he stresses the evolutionary relevance of pleasure for its own sake that humans get from artistic appreciation and production. Watanabe (2013) concludes that self-reinforcement of the art-like behavior and the reinforcing power of the product for the artist and for conspecifics are mostly unique to humans. Høgh-Olesen (2018) referred to the universal need to embellish human body and surroundings and the desire to fill time and space with song, music, dance, and stories as the aesthetic impulse. He argues that it is a primary impulse and an inherent part of human nature. Thus, similarly to curiosity and play (cf. Moraes, Valentova, & Varella, 2022), artistic behavior is hypothesized to be an inherently-rewarding activity motivated rather intrinsically through an evolved motivational system (Varella, 2021).
This does not exclude the possibility that some external factors, such as social belonging, social prestige or mate attraction, could also be important, and possibly even evolved, extrinsic motivation activating artistic tendencies (cf. De Block & Dewitte, 2007; Varella et al., 2017; Winegard, Winegard, & Geary, 2018). In a review of effects of external rewards on creativity, Eisenberger and Shanock (2003) concluded that only rewards for novel performance increase intrinsic motivation and creativity, whereas rewards for conventional performance decrease intrinsic motivation and creativity.
There is empirical evidence stemming from research using different methodologies in support of the rather intrinsic nature of artistic motivation. Some brain damaged patients present intrinsically spontaneous, compulsive and highly sustained artistic production, sometimes even as de novo artists (Abraham, 2019; Midorikawa & Kawamura, 2015; Sacks, 2008; Zaidel, 2014). Further, intrinsic motivation leads to more creative and better aesthetic value than when artistic behavior is extrinsically motivated (Amabile, 1982; Amabile & Gitomer, 1984; Amabile, Hennessey, & Grossman, 1986). Surveys showed that aesthetic and artistic activities are among popular choices of the free-time activities and hobbies individuals spontaneously pursue (Chalip, Thomas, & Voyle, 1996; Chamorro-Premuzic & Furnham, 2004; Chong, 2010; Furnham & Chamorro-Premuzic, 2004; McManus & Furnham, 2006; Walker & Scott-Melnyk, 2001). Studies show that among the primary and intrinsic reasons for artistic engagement is personal interest in the artistic material itself, desire to express themselves artistically (McCarthy & Jinnett, 2001), recreation and aesthetics (Swanson, Davis, & Zhao, 2008), and self-expression and aesthetic experience (Chong, 2010). Varella (2021) showed that intrinsic factors (e.g., personal taste/aptitude/fulfillment reasons) are more frequently reported by individuals applying for artistic careers (i.e., Music, Dance, Scenic Arts, Visual Arts, and Literary Studies) compared to other non-artistic careers. Moreover, extrinsic motives (e.g., the influence of media/teacher/family, salary, social contribution/prestige) were less mentioned as reasons for artistic career-choice compared to those applying for other non-artistic careers (Varella, 2021). Hence, it is possible that artistic motivation is more intrinsically than extrinsically sourced.
Varella (2021) suggested that domain specificity is the second design feature of artistic motivation, given its possible evolved nature. Modularity, domain specificity or functional autonomy/specialization have been considered a hallmark of mental adaptation because different information-processing problems usually require different procedures for their successful solution (Andrews, Gangestad, & Matthews, 2002; Barrett, 2008; Cosmides & Tooby, 1994; Tooby & Cosmides, 2015). Thus, specialization has been naturally selected because it pays-off in terms of solving problems faster and more efficiently (Cosmides & Tooby, 1994; Tooby & Cosmides, 2015). Watanabe (2013) stresses functional autonomy of art-like behavior among animals, particularly in humans. Varella (2021) demonstrated that the motivational pattern of high intrinsic and low extrinsic motives is specific to individuals applying to artistic careers compared to those applying to other careers. Moreover, the cases of de novo artists following brain damage (e.g., Abraham, 2019) and artistic leisure activities (e.g., McManus & Furnham, 2006) indicate some level of specificity in motivation. Similarly, studies on musicality indicate some level of cognitive specialization (Merker et al., 2015; Norman-Haignere, Kanwisher, & McDermott, 2015; Peretz, 2006; Peretz & Coltheart, 2003). Moreover, various taxonomies and classificatory schemes consider artistic/aesthetic as a specific and legitimate domain within the field of vocation interests (Guilford, Christensen, Bond, & Sutton, 1954; Holland, 1997; Kuder, 1948; Moloney, Bouchard, Sigal, 1991; Su, Tay, Liao, Zhang, & Rounds, 2019) and of leisure practices (Dumazedier, 1988; Mingo & Montecolle, 2014; Scott & Willits, 1998). There is even specificity regarding engagement with beauty, in which ‘artistic’ beauty is distinct from the ‘natural’ and ‘moral’ beauty (Diessner, Solom, Frost, Parsons, & Davidson, 2008). Thus, it is plausible that artistic motivations would present domain specificity.
Temporal stability is suggested as the third design feature of artistic motivation (Varella, 2021). Evolutionary Psychology focuses on the universal basic psychological components of human nature that were mostly solidified during the Pleistocene period and that continue to be expressed nowadays (Hagen, 2015; Starratt & Shackelford, 2010). Indeed, the stability of some superordinate psychological tendencies is substantially influenced by shared genetic factors (Figueredo, de Baca, & Black, 2014). Varella (2021) found that the artistic-specific high intrinsic motivational pattern is temporally stable throughout the last three decades. Furthermore, the earliest artistic manifestations are prehistorically very old:, 35 thousands of years ago (i.e., ka: kiloanni) for bone flutes (Conard, Malina, & Münzel, 2009) and for a ‘venus’ figurine (Conard, 2009), 40–45 ka for cave paintings and hand stencils (Aubert et al., 2014, 2019; Bednarik, 2014; Brumm et al., 2021; Pike et al., 2012), 73–77 ka for a engraving and an abstract drawing (Henshilwood et al., 2002, 2018), between 70 and 120 ka for the painted collar beads (d’Errico et al., 2009), and 164 ka for the use of red ochre (Marean et al., 2007). Moreover, some ancient artistic manifestations were also performed by extinct hominid species, such Neanderthals (Rodríguez-Vidal et al., 2014; Zilhão et al., 2010), Denisovans (Li et al., 2019; Pitulko, Pavlova, Nikolskiy, & Ivanova, 2012), and Homo erectus, particularly as ancient as 430–540 ka (Joordens et al., 2014), indicating even deeper roots for the onset of artistic propensities. Thus, it is plausible that artistic motivation would be long consolidated and temporally stable.
The current study
Intrinsic motivation is frequently assessed behaviorally in terms of freely pursued activities. Free-time is understood as time for oneself, for relaxation, for family and friends, to have fun, and time outside of obligatory work and school (Mingo & Montecolle, 2014). Although external influences, such as family and friends, definitely influence which free-activity to do, it does not exclude intrinsic factors given that there is an element of self-similarity among relatives and friends. Thus, free-time activities, together with leisure and recreation activities can be seen as mostly influenced by internal preferences, tendencies, hobbies, choice and desires rather than activities externally influenced, such as work, schooling and other duties (cf. Howe & Rancourt, 1990; Veal, 1992). Hence, leisure activities are generally pleasurable, being an end in itself and valuable for its own sake, and more intrinsically motivated, though not only (Cushman & Laidler, 1990). Given the limited amounts of time for leisure activities, individuals need to prioritize and directly choose those that they find most satisfactory.
Aesthetics and artistic activities are among the free time activities and hobbies individuals spontaneously pursue. Walker and Scott-Melnyk (2001) surveyed by telephone 2,406 individuals and found high rates (84%) of participation in broadly defined (popular) music, theater, dance, and visual arts activities. Kleiber, Larson, and Csikszentmihalyi (1986) analysed 4,489 self-reports of 75 adolescents on various dimensions of experience during their daily lives: arts and hobbies occupied 1.5% of the day. Chalip et al. (1996) sampled 700 individuals and found that on spare time 7% usually do sewing/knitting, 4.6% crafts, and 4.4% music. Chamorro-Premuzic and Furnham (2004) sampled 102 participants and found that 22% currently paint, 25% play a musical instrument. Furnham and Chamorro-Premuzic (2004) sample of 74 participants indicated that 20% currently painted. McManus and Furnham (2006) sampled almost 1,200 individuals and found that 92% listen to popular music between once a week and every day, 33.5% go dancing, 21.6% play a musical instrument, 23.2% draw or paint, 11.4% go to museums or art galleries, 40% read a novel, 13.3% read poetry, 4.2% act in a theater. Finally, Mosing et al. (2015) studied 10,975 twin individuals and found that roughly 28% play or have played a musical instrument (including singing), and 18% of the musically active reported having participated in special musical education also outside of school. In general, there is an average of 25% engagement, and passive engagement is more frequent than active engagement, because specific skills is often needed for artistic production.
However, the existing literature has many shortcomings that hinder wide-ranging conclusions about the psychological structure of artistic motivation, in terms of its source, specificity and stability. Firstly, most of the aforementioned studies base their conclusions on relatively small samples. Secondly, most studies focus on one or a few English speaking countries which also can hamper its generalization. Thirdly, studies mostly approach a limited range of artistic activities which restricts the conclusions in terms of the scope of artistic psychology. Furthermore, studies are normally cross-sectional, thus they are unable to access possible longitudinal, generational and temporal trends.
In order to fill this gap, this study complemented Varella (2021) and investigated the pursuit of artistic activities during leisure-time using a decades-long unobtrusive real-life big data from late adolescences applying to enter a São Paulo state public university in Brazil. The socio-demographic questionnaire that the students are requested to answer (e.g., for the year 2019 is http://www.comvest.unicamp.br/estatisticas/2019/quest/quest1.php) when registering for the entrance exams had normally two multiple answer questions about extra-class activities. Using the pursuit of extra-class activities during leisure-time reported by individuals choosing a career from a large decades-long real-life public Brazilian database from university applications, we tested whether artistic motivation is rather intrinsic sourced, domain specific, temporally stable, as expected for an evolved trait (cf. Varella, 2021).
Method
We accessed public data available online from the ‘statistics’ section in the website ‘www.comvest.unicamp.br’ of the Permanent Commission for the University Entrance (Comissão Permanente para os Vestibulares, COMVEST). COMVEST is a Brazilian autonomous institution that runs the entrance examinations to the University of Campinas (UNICAMP). Until 2004, the applicants could undertake the examination in up to 19 different Brazilian cities, the majority from São Paulo State. We obtained access to data from all the cities, thus adding a geographic diversity into our sample. The data were from all individuals applying for the entrance exams, not only those who were approved. Between 1987 and 2004 the socio-demographic questionnaire from the entrance exams included two multiple answer questions about extra-class activities answered by 674.699 individuals, mostly late-adolescents (70.50% between 17 and 19 years; 50.75% men and 49.25% women).
The first question asked applicants about (1) which extra-class activity they most frequently practiced (focus on frequency). The options of the most frequently participated extra-class activities included ‘Artistic/cultural’, ‘Religious’, ‘Political-partisan’, ‘Esoteric’, ‘Sports’, ‘Blank’, ‘Other’, and ‘None’. Participants could choose only one answer. The fact that the options were mutually exclusive, participants faced a trade-off and indicated their priority, not only frequency of engagement. The question remained the same throughout the time period and the option ‘Esoteric’ was added in 1999. Table 1 presents the average percentage of choice per answer item for all individuals throughout the period.
Average percentage of choice per answer item for all individuals between 1987 and 2004
| Answer Item | Average percentage of choice |
| ‘Artistic/cultural’ | 26.50% |
| ‘Religious’ | 8.44% |
| ‘Political-partisan’ | 2.01% |
| ‘Esoteric’ | 0.21% |
| ‘Sports’ | 38.57% |
| ‘Other’ | 11.67% |
| ‘None’ | 11.20% |
| ‘Blank’ | 1.40% |
The subsequent question asked applicants about (2) which activity occupied most of their free-time (focus on duration, time investment). The multiple answers options offered the following extra-class activities: ‘TV’, ‘Theater/Cinema’, ‘Music’, ‘Dance’, ‘Art-craft’, ‘Plastic-arts’, ‘Bar/disco’, ‘Reading’, ‘Sports’, ‘Internet’, ‘Blank’ and ‘None of those’. Participants were allowed to choose only one answer. The question phrasing remained the same throughout the time period and the options ‘Dance’, ‘Art-craft’, ‘Plastic-arts’ were removed in 1999, and the options ‘Bar/disco’, ‘Sports’, ‘Internet’ were added in 1999. See Table 2, for the average choice per item for all individuals in the period.
presents the average percentage of choice per item for all individuals between 1987 and 2004
| Answer Item | Average percentage of choice |
| ‘TV’ | 18.15% |
| ‘Theater/Cinema’ | 5.49% |
| ‘Music’ | 23.69% |
| ‘Dance’ | 2.01% |
| ‘Art-craft’ | 0.47% |
| ‘Plastic-arts’ | 0.39% |
| ‘Bar/disco’ | 1.18% |
| ‘Reading’ | 29.73% |
| ‘Sports’ | 4.36% |
| ‘Internet’ | 2.82% |
| ‘None of those’ | 10.45% |
| ‘Blank’ | 1.23% |
Differently from the first question which offered ‘Artistic’ always together with ‘Cultural’, this second question discriminated some artistic modalities, and could be later grouped into a more homogenous way by adding the percentage of answers for ‘Theater/Cinema’, ‘Music’, ‘Dance’, ‘Art-craft’, ‘Plastic-arts’ into an Artistic-activities category. Although COMVEST has an official reading list assigning literary books, there is also much non-fiction reading about other curricular topics and extracurricular topics such as newspapers and magazines involved, thus to avoid inflating the artistic categorization we treated ‘Reading’ as a non-artistic activity. The option ‘TV’ was also treated as non-art, because despite many possible artistic programs, such as music clips, soap-operas, films and cartoons, TV offers many non-artistic programs, such as news, interviews, etc. The same treatment was given to ‘bar/disco’: although some people go out to dance, many more go out rather to drink/eat, flirt and socialize. Thus, the first question contained a wider range of artistic and cultural activities, including non-artistic cultural activities such as non-fiction reading, journalism, second language learning, other voluntary service and educational activities, while the second question used a more restricted definition.
First, we manually tabulated the percentages and total number of answers in each option, including the options ‘blank’, ‘other’ ‘none’, for each year and career. The use of percentages normalizes the variation in the actual amount of applicant in each year and career. Second, the data were transferred into SPSS 20 (IBM Corp., Armonk, NY) for group comparisons and correlation analyses.
We collected data from all available artistic careers between 1987 and 2004 in UNICAMP (viz. Music, Dance, Drama, Artistic Education/Visual Arts), for comparisons with some non-humanities careers (Chemistry, Dentistry, Physical Education), some humanities non-artistic careers (History, Philosophy, Pedagogy, Social Sciences), and also with ‘All careers’ (up to a total of 57 in 2004). The courses of careers chosen are full-time courses, and the different career modalities of music were collapsed into an overall Music career.
Data analysis strategy and hypotheses testing
To test if the artistic motivation is intrinsically biased, we examined the prioritization of artistic activities during extra-class leisure-time as a proxy for intrinsic motivation. The overall descriptive percentage prevalence of prioritizing artistic extra-class activities during leisure time offers a measure of the relative intrinsic appeal of artistic leisure activities in the population in contrast to other non-artistic extra-class activities. If artistic activities were mostly extrinsically motivated very few individuals would prioritize arts in their leisure time. To test this hypothesis, we analyzed the entire sample regardless of the career-choice.
The comparison of the engagement with artistic extra-class activities between individuals applying for artistic or non-artistic careers indicates its specificity. If artistic motivation were not domain specific, there would be no major difference in prioritization of artistic extra-class activities between those applying for artistic careers and those not applying for artistic careers. The career choice is influenced by many factors, including individual cognitive style (Varella, Ferreira, Pereira, Bussab, & Valentova, 2016) and particularly artistic career-choice is specific by relatively higher intrinsic than extrinsic motives (Varella, 2021). To test this hypothesis, we performed a multivariate General Linear Model (GLM) with Bonferroni post-hoc comparison for main effects and Partial Eta-squared (ηp2) as effect size estimators during the entire available time period.
Finally, we tested the temporal stability of the prioritization of artistic extra-class leisure activities by analyzing whether there were any temporal trends in the overall artistic leisure engagement. Following Varella et al. (2016) and Varella (2021), the correlation between the series of years throughout the available period and the percentage of prioritization artistic extra-class activities indicates its temporal stability or instability. If the tendency to prioritize artistic leisure activities was temporally instable there would be positive or negative significant correlations between the time period and the percentage of artistic prioritization. To test for the time stability, the time period entered as covariate in the GLM, and subsequent Pearson correlation was performed to specifically test the temporal stability hypothesis.
Analyzes and results
We found that among ‘All careers’, 26.50% of individuals mostly participated in Artistic/cultural activities, and 32.06% spent the longest period of free-time in Artistic-activities (theater/cinema, music, dance, art-craft/plastic-arts). These figures are around ten times higher than the 2.77% of artistic careers applicants between 1987 and 2004.
We performed a multivariate General Linear Model (GLM), where dependent variables were the percentage of individuals indicating Artistic/cultural activities as their most frequent extra-class activity, percentage of individuals indicating Artistic-activities as the most leisure-time consuming activity, and percentage of individuals indicating priority to Non-Artistic extra-class activities. Further, groups of careers entered as independent factors (total of careers in the period, non-artistic careers, non-humanities careers, humanities non-artistic careers, and artistic careers), and the year (17 years’ period: 18 consecutive application periods) as a covariate. The model showed that the individuals applying for the combined artistic studies reported prioritizing significantly more Artistic/cultural activities (F = 2,130.035, df = 4, p < 0.001, ηp2= 0.990), Artistic-activities (F = 139.407, df = 4, p < 0.001, ηp2= 0.863), and less Non-Artistic activities (F = 136.747, df = 4, p < 0.001, ηp2= 0.867) as extra-class activities than all other groups (F = 36.967, df = 3,000, p < 0.001, ηp2= 0.575). See Fig. 1.
Averaged percentages of individuals prioritizing Artistic/Cultural, Artistic-Activities and Non-artistic Activities as extra-class activities by cluster of careers (1987–2004)
The cluster ‘All careers’ includes 57 different careers; ‘Non-artistic’ includes Chemistry, Dentistry, Physical Education, History, Philosophy, Pedagogy, and Social Sciences; ‘Non-humanities’ includes Chemistry, Dentistry, and Physical Education; ‘Humanities Non-artistic’ includes History, Philosophy, Pedagogy, and Social Sciences; ‘Artistic’ includes Music, Dance, Scenic Arts, and Artistic Education/Visual Arts. Error bars are 95% Confidence Interval.
Citation: Culture and Evolution 19, 1; 10.1556/2055.2022.00012
The Bonferroni post-hoc showed differences between Artistic careers and all other career groups in Artistic/cultural activities (all p's < 0.001), in Artistic-activities (all p's < 0.001), and in Non-Artistic activities (all p's < 0.001). The percentage of individuals prioritizing arts among applicants for artistic careers (Artistic/cultural, 76.06%; Artistic-activities, 72,48%) is respectively 2.87 and 2.26 times higher than the prioritizing of arts among applicants for all careers (26.50% and 32.06%). Moreover, regarding Artistic/cultural activities all career groups differed from every other group (all p's < 0.001). The highest percentage of individuals prioritizing Artistic/cultural activities was found among the applicants for Artistic careers, followed by Humanities Non-artistic, then by Non-artistic, by all careers and finally followed by Non-humanities. There was no other group difference in Artistic-activities nor in Non-Artistic activities (lowest P=0.540).
The multivariate GLM model has indicated an effect of the year on Artistic/cultural activities (F = 18.115, df = 1, p < 0.001, ηp2= 0.177), Artistic-activities (F = 74.694, df = 1, p < 0.001, ηp2= 0.471) and Non-artistic activities (F = 46.067, df = 1, p < 0.001, ηp2= 0.354) throughout the 18 consecutive application periods. However, the observed effect was actually an artifact of the official addition of the option ‘Esoteric’ in 1999 into the first question, and the removal of options ‘Dance’, ‘Art-craft’, and ‘Plastic-arts’, and addition of options ‘Bar/disco’, ‘Sports’, ‘Internet’ in 1999 into the second question, which increased the options for non-artistic activities in the later period. Thus, in order to account for these distortions, we selected from the 18 consecutive application periods only the 12 years before 1999 when the answer options remained unchanged. The Pearson correlation confirmed that the years between 1987 and 1999 were not associated with percentages of individuals prioritizing Artistic/cultural activities (r = 0.015, n = 60, p = 0.912), Artistic-activities (r =0.022, n = 60, p = 0.870), or Non-artistic activities (r = −0.101, n = 60, p = 0.445), indicating no possible long-term linear temporal trends, thus it likely exhibits some temporal stability within a little over a decade timeframe.
Discussion
This study tested evolutionarily oriented propositions about the psychological structure of artistic motivation using unobtrusive data from a large decades-long real-life public Brazilian database about university entrance applications. Following Varella (2021), artistic motivation is predicted to be rather intrinsically sourced, domain specific, and temporally stable The author focused on preferential extra-class activities among 674,699 late-adolescents between 1987 and 2004 from 57 different study careers and 19 different Brazilian cities. This study comprised the artistic areas of theater/cinema, music, dance, art-craft, plastic-art as artistic activities in strict sense, and as artistic/cultural in broad sense. General results from both strict and broad sense artistic activities corroborated Varella (2021) showing a specific, stable and rather intrinsically motivated prioritizing of artistic activities consistent with its possible evolved nature as partly predicted by Dutton (2009), Høgh-Olesen (2018), and Morris (1962).
The hypothesis that artistic motivation is rather intrinsic received some support from the finding that during the free-time 26.50% of all individuals mostly participated in Artistic/cultural activities, and 32.06% spent the longest period of free-time in Artistic-activities (theater/cinema, music, dance, art-craft/plastic-arts) instead of other activities such as religious or sportive activities, watching TV, reading or surfing the internet. This indicates that between a quarter and a third of the sample in fact prioritize artistic activities during the self-pursued leisure time. If artistic activities were mostly motivated by extrinsic factors very few individuals would prioritize arts in their leisure time. Arguably, there are also extrinsic factors involved. However, arts are not the only way to get pleasure, family approval, social interaction, friends, mates, fame, or money. For instance, adult play (cf. Moraes, Varella, Silva & Valetova, 2021) and sports (cf. Varella et al., 2022) are other routes towards mating success. Still, some physical activities (competitive sports) are more intrinsically motivated than others (such as exercises) (Hsu, Cardoso, Varella, Pires, & Valentova, 2022; Hsu & Valentova, 2020). Success in arts is costly, requiring talent, practice, dedication, and courage to display to others. Hence, an individual performing arts mostly for extrinsic reasons would quickly recognize that the same reward can be easily and rapidly achieved through other means, such as talking or socializing. Thus, in general, extra-class activities do reflect more intrinsic rather than extrinsic motivation, in particularly when accessing leisure activities performed most frequently and for longer periods, as accessed in this study.
Furthermore, the percentages of prioritizing arts during free-time reported here could be considered conservative and underestimated, because individuals could also engage at least passively with artistic content through reading, watching TV, at the internet or at the bar/disco, which were not included into the same factor of the more purely artistic options. The results that between a quarter and a third of the sample prioritize artistic leisure-time activities corroborate previous surveys from other countries showing that aesthetics and artistic activities are spontaneously pursued by individuals during leisure-time at comparable rates, such as between 10 and 40% (Chalip et al., 1996; Chamorro-Premuzic & Furnham, 2004; Chong, 2010; Furnham & Chamorro-Premuzic, 2004; McManus & Furnham, 2006; Mosing et al., 2015; Walker & Scott-Melnyk, 2001). In general, previous results suggest that passive engagements such as listening to popular music are more popular (92%) than actively playing an instrument (21.6%.) (McManus & Furnham, 2006). This fact might explain why music was a much more popular option than any other artistic activity.
The general findings are also aligned with further evidence supporting rather intrinsic nature of artistic motivation stemming from research in different methodologies. Individuals applying at university for any artistic careers exhibited significantly higher intrinsic and lower extrinsic motivations than other groups of careers, including all applicants together (Varella, 2021). Some brain damaged patients present spontaneous, compulsive and highly sustained artistic production (Abraham, 2019; Midorikawa & Kawamura, 2015; Zaidel, 2014). Some experiments show that intrinsic motivation leads to better aesthetic value (Amabile, 1982; Amabile & Gitomer, 1984; Amabile et al., 1986). Finally, studies show that personal interest in the artistic material itself and the desire to express themselves artistically are among the reasons given to engage in artistic activities (McCarthy & Jinnett, 2001). Recreation and aesthetics (Swanson et al., 2008), and self-expression and aesthetic experience (Chong, 2010) are among the primary and intrinsic reasons individuals report when engaging in artistic activities.
The hypothesis that artistic motivation is domain specific is supported by the findings that the intrinsically based motivational profile reflected from extra-class activities of individuals applying for artistic careers is uniquely increased and distinct from other non-artistic careers, humanities, non-humanities, and also total of careers. The artistic careers applicants prioritize art as extra-class activities almost 3 times more than the total of applicants. These findings corroborate the previous discovery that the relative proportion between intrinsic and extrinsic reasons to apply for artistic careers is around 4 to 4.5 times higher than for the total of applicants and the high intrinsic and low extrinsic motivational pattern exhibited by those applying for artistic careers is unique and distinct from the motivational patterns of those applying for other careers (Varella, 2021). These results also align with several classificatory taxonomies within the fields of vocation interests and leisure practices that consider artistic/aesthetic as a specific and legitimate domain. For instance, the classic hexagonal RIASEC model of vocation interests (Holland, 1997) presents the ‘Artistic’ dimension (interest in creative expression, including writing and the visual and performing arts) as distinct from ‘realistic’, ‘investigative’, ‘social’ and ‘conventional’ vocational interests. The recent SETPOINT model of vocational interests (Su et al., 2019) also features ‘Creative Expression’ as a distinct domain from ‘health science’, ‘technology’, ‘people’, ‘organization’, ‘influence’, ‘nature’, and ‘things’ types of interests. Similarly, Dumazedier (1988) identified ‘Entertainment and Arts’ (theatre, concerts, art exhibits, visiting museums and monuments, cinema, music, etc.) as one of the five categories of leisure activities, including ‘physical recreation’, ‘practical leisure’, ‘intellectual leisure’ and ‘social leisure’. Scott and Willits (1998) described ‘Creative’ as one of the four categories of leisure activities, the others being ‘socializing’, ‘intellectual’, and ‘sports’. Mingo and Montecolle (2014) include ‘Artistic and/or recreational’ activities (e.g., taking photos, making movies, home videos; drawing, sculpting, painting; writing diaries, poems, short stories; using the computer in a creative way; playing an instrument; composing music, singing, dancing, reciting) as a class of leisure activities independent from, ‘reading’, ‘technology related’, ‘practical’, ‘outdoor’, ‘relational’, ‘passive’, ‘games and hobbies’, ‘personal care and shopping’, and ‘sports and physical activities’. Moreover, even regarding the engagement with beauty, Diessner et al. (2008) distinguished ‘Artistic’ from the ‘natural’ and ‘moral’ beauty. All this strengthens the case for the domain specificity of artistic motivation.
The third hypothesis that the profile of artistic motivation is temporally stable also received support from both analyzed questions. We found that neither the artistic/cultural (broad sense) nor artistic-activities (strict sense) extra-class artistic activities correlated with the year throughout the period of years when the answer options remained unchanged (12 years). If the motivation to prioritize artistic activities during leisure-time were more extrinsically sourced, it would be possible to detect any long-term linear trend following social changes throughout the 12 years' period. This relatively short historical stability is aligned with the temporal stability over the periods of 8 and 33 years found for intrinsic motives to apply for an artistic career (Varella, 2021). These findings also relate to previous studies showing life-time individual stability of interests. Artistic expression remains sustained in some brain damaged patients (Abraham, 2019), vocation interests seem to be stable (Lubinski, Benbow, & Ryan, 1995; Waller, Lykken, & Tellegen, 1995), and particularly interests in hands-on physical activities and self-expressive/artistic activities tend to be more stable than scientific, social, enterprising, and clerical interests (Low, Yoon, Roberts & Rounds, 2005). Finally, leisure interests (Waller et al., 1995), and engagement with artistic beauty (Diessner et al., 2008) are stable throughout periods of individuals' life. Thus, at least within the little over a decade time-frame, the motivation for prioritizing artistic leisure activities seems to remained at stable levels.
The present investigation advances the recent state of art. On a huge sample size through a little over a decade as temporal span, it shows that around 30% of young educated Brazilian population prioritizes artistic activities over other free-time activities. This figure is around ten times higher than the 2.77% of individuals who actually applied for artistic careers between 1987 and 2004. These 30% of individuals are a combination of future art professionals, dedicated amateurs and hobbyists, and big fans of appreciating artistic activities, all of who are highly oriented towards artistic/aesthetically creative activities, active and passive engagements (see, Brooks, 2002). Those highly prioritizing arts are positioned on the top of the participation pyramid (cf. Literat, 2012), above all others that consider those activities their second best, or third and fourth most preferred activities. This indicates that the individual prevalence of pronounced/gifted artisticality goes well beyond only those famous and rare successful artists or those holding a professional degree, which in turn expand the prevalence of individuals highly artistic oriented in the population. In fact, 51% of American students self-consider to be an artistic person, and 64% self-consider a creative person (Furnham & Chamorro-Premuzic, 2004; Chamorro-Premuzic & Furnham, 2004). It is important to recognize that the modern western conception of the artist as a unique and highly gifted individual expressing individuality and an independent personality is a historically specific one. It dates from the rise of the merchant classes in France and Italy, during the rise of humanist ideas in philosophy since the sixteenth century (Wolff, 1981). Before that, the artistic profession was not differentiated from craftsmanship and the social organization of artistic production was based in guild workshops, following communal lines with much cooperation with pupils and assistants (Wolff, 1981). It was more in line with tribal practices where artistic activities are an integral feature of daily life and rituals collectively engaging talented individuals as well as the entire community (Dissanayake, 1988, 1992, Eibl-Eibesfeldt, 1989).
This investigation, however, has some limitations. The COMVEST system rounds the percentage data up to only one decimal place, so we might expect a 0.1 error rate in the given percentages. The system does not show frequency results when there are less than 5 candidates in a given career of a given year. This means that in some years some cases of musical instrument modality, such as clarinet or trombone, could not be added to the other modalities to create the overall Music career. Further, the system excluded the questions on extra-class activities after 2004, which leaves a gap in how this engagement is manifested throughout more recent time. The COMVEST system also changed the way questions were framed or the number of answer options, however, the changes were minor and performed only once throughout the period, so that analyses could contour inconsistencies. The data is only available per year, city, and choice of career, not by sex of participants, so we could not compare males and females (cf. (Varella et al., 2022, 2010; Luoto & Varella, 2021). Although the data is impressive and out of the North America-Europe axis, the samples do not represent an overall Brazilian or world population given its circumscribed location and its age limited mostly to late-adolescents applying for diurnal, but not nocturnal careers. Moreover, within Brazilian context our results are limited by the fact that, during the years available, the access to such a prestigious university was mostly restricted to individuals form more affluent classes who also had enough resources to pay for extra-class activities. Although standardized, the context in which participants filled the questions cannot be verified in order to assert reliability, however it is highly improbable that the same external factor influenced in the same direction the majority of individuals, in most of the cities and application years across decades, so the influences of the context might have cancel each other out in difference places and years. Future studies should try to account for and expand beyond these limitations in order to replicate and further explore the psychological structure and features of human artistic motivation in real-life scenarios.
Conclusion
Despite limitations, the confluence of results from both questions about prioritization of artistic leisure activities corroborate the hypotheses that artistic motivation might be rather intrinsic, domain specific, and historically stable. This conclusion offers complementary empirical corroboration to Varella (2021) and support the notion that artistic motivation might be an evolved aspect of human nature (Morris, 1962; Dutton, 2009; Høgh-Olesen, 2018).
Acknowledgements
Financial support from (PNPD 33002010037P0 – MEC/CAPES). I thank the Dep. of Experimental Psychology for trusting this project. I thank Prof. Eduardo Ottoni for offering valuable suggestions, advices and comments. I also thank Prof. Jerry Hogan and Prof. Prof. Jaroslava V. Valentova for valuable proofreading and comments.
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