Does red light induce people to be riskier? Exploring the colored light effect on the Balloon Analogue Risk Task (BART)

https://doi.org/10.1016/j.jenvp.2018.07.001Get rights and content

Highlights

  • Red light does not promote riskier decisions compared to that of blue light.

  • Men behaved riskier than women whether in red light or blue light condition.

  • There were no significant effects of colored light on subjective sleepiness or mood.

  • No significant differences in subjective appraisals of different colored lights appeared.

Abstract

Risk-taking is behavior influenced by various factors. However, whether red light induces riskier decisions than other lights do is still inconclusive. In this study, a 2 × 2 mixed design (N = 59) was applied to investigate the effects of colored light (red light vs. blue light) on the Balloon Analogue Risk Task (BART), sleepiness, and mood between sexes. The results showed that (1) neither a significant effect of colored light nor a significant interaction effect was revealed. However, males made riskier decisions than females did. (2) There were no significant effects of colored light on subjective sleepiness or mood. (3) There were no significant differences in individual appraisals of different colored lights. These results suggest that red light does not promote riskier decisions compared to that of blue light.

Introduction

Risk-taking is pervasive and inevitable in our daily life. It is not the expression of a single personality trait but a behavior influenced by the characteristics of the situation (e.g., decision domain and ambient environment), the decision maker (e.g., age and gender), and interactions between the case and decision-maker (Figner & Weber, 2011; Ferrey & Mishra, 2014). People exhibit substantial individual differences in risk-taking propensity. Up to now, some factors have also been consistently associated with risk-taking. On average, men tend to engage in greater risk-taking than women do (Deuter et al., 2017; Kelly, Gert, Freek, Abraham, & Thomas, 2013; Martin, Neighbors, & Griffith, 2013; Wong, Zane, Saw, & Chan, 2013), and younger people tend to engage in greater risk-taking than older people (West, Tiernan, Kieffaber, Bailey, & Anderson, 2014). However, there are still some other factors that produce inconsistent results in there associated with risk-taking, such as ambient light.

Color plays a pervasive role in people's lives. People are continuously exposed to various colors that affect their perception and behaviors (Mehta, Demmers, van Dolen, & Weinberg, 2017). Red has long been identified as a unique, distinctive color. It is the color of blood, ripe fruit, and many aposematic signals. Therefore, red is always associated with signs (e.g., alarms and sirens), symbols (e.g., hearts and crosses), and sayings (e.g., “in the red” and “roll out the red carpet”) (Elliot & Maier, 2014). At first, studies about red color and risk-taking appeared in the field of color psychology. Most of the researchers thought that red makes people risk-averse. The underlying mechanism may be that red color increases avoidance motivations in achievement situations (Elliot & Maier, 2014) and thus leads to decreases in risk-taking (Gnambs, Appel, & Oeberst, 2015). For example, Gnambs, Appel, & Oeberst (2015) showed worse performance on the BART in the red condition. Similarly, red seems to implicitly increase the salience of financial losses compared to economic gains (Kliger & Gilad, 2012) and thus to shift an individual's attention to potential losses (Pravossoudovitch, Cury, Young, & Elliot, 2014). However, in the field of color light psychology, it seems that another contrary but rational theory appeared. That is, people took more risks in red ambient light, as red light increases an individual's arousal. One possible explanation may be that time seems to pass more slowly under red light, and red light rises excitement and creates the false impression that they are not wasting much time in the casino. Thus, it induces individuals to make quick decisions (Singh, 2006). Brevers et al. reported that a casino environment (casino-related sound, red light and playing against another participant) might decrease the time used for reflecting and thinking before acting after losses (Brevers et al., 2015). Similarly, Stark, Saunders, and Wookey (1982) provided one empirical contribution assessing the effects of colored light on gambling behavior and found that gambling under red light led to more risks being taken compared with blue light. Additionally, Yoto et al. found that red was stronger, more exciting, and more arousing than blue (Yoto, Katsuura, Iwanaga, & Shimomura, 2007). Though many previous studies have yielded the results that red light leads to more risk-taking, an empirical research combined the effects of both music tempo (fast and slow) and light (red and white) on gambling behavior and reported that no significant main effects were found for risk-taking for either of the two variables, but there was a significant interaction. That is, fast-tempo music under red light resulted in faster gambling (Spenwyn, Barrett, & Griffiths, 2009). Therefore, it was still unclear whether people take more risks in red light compared with other ambient light.

We thought that there are two possible reasons for the inconsistent results. First, they may differ due to some potential confounding variables. Different individuals may take risks differently in the same situation. It has been found that evening-type individuals have higher risk-taking than morning-type individuals (Ponzi, Wilson, & Maestripieri, 2014; Tonetti, Martoni, & Natale, 2016; Wang & Chartrand, 2015), people with low self-control showed a stronger risk preference than people with high self-control (Freeman & Muraven, 2010; Yan, 2014), a self-reported impulsivity measure was highly related to a risk-taking behavioral test (Reddy et al., 2014), and personality traits have also been postulated to play an essential role in predicting risk-taking (Fyhri & Backer-Grondahl, 2012; Nicholson, Soane, Fenton-O'Creevy, & Willman, 2005; Wang, Xu, Zhang, & Chen, 2016). Another possible reason may be that both the light settings and the risk-taking task were different, thus making it difficult to compare the results directly. For the light environment, Stark et al. (1982) used red and blue fluorescent light, Spenwyn et al., (2009) used two 60 W bulbs and two 60 W red blubs placed either side of the computer, and Brevers et al. (2015) used a 15 W red light and a 15 W white light set in the room's main lighting. As for the dependent measures, Stark et al. (1982) used a card game, Spenwyn et al. (2009) used participants' gambling behavior, and Brevers et al. (2015) used the Iowa Gambling Task. From the above methods, we can see that, in fact, there were very few studies that explored the influence of red light on risk-taking, and even worse, no study used ambient colored light, which is the most common light setting in our daily life. Based on these two issues, in the current research, all four potential confounding variables were controlled when examining whether people take more risks under red light compared with blue light. Additionally, the light setting was ambient colored lights, which are introduced in detail in methods below. Also, we used the BART as the measure of individual risk-taking in the current study. The BART is a very common and useful tool in the assessment of risk-taking (Lejuez et al., 2002) and has been associated with numerous forms of real-world risk-taking. Recent studies found that the BART not only has been associated with some disorders (e.g., conduct disorder and substance use disorder) but also has been related to many real-world risky behaviors (e.g., cigarette, alcohol and drug use, gambling, aggression, and sexual risk-taking) in adolescents (Buelow & Blaine, 2015; Fernie, Cole, Goudie, & Field, 2010; Krmpotich et al., 2015; Lejuez, Aklin, Zvolensky, & Pedulla, 2003; Panwar et al., 2014). Therefore, using the BART to measure individual risk-taking has the potential to provide evidence and suggestions for both the healthy population and in the clinical context.

Many previous studies demonstrated that males took more risks than females did in the same situation (Byrnes, Miller, & Schafer, 1999; Deuter et al., 2017; Kelly et al., 2013; Martin et al., 2013; Wong et al., 2013). In the field of color psychology, few studies reported gender differences for the effect of red color on risk-taking. The results of these studies were mostly consistent. That is, men seemed to be affected by the red color more than females. For example, Ioan et al. investigated the distractor effect of red during a computerized Stroop task and found that the result was more pronounced in men than in women when red color names were used (Ioan et al., 2007). Gnambs et al. demonstrated that men's performance dropped in the red condition, while female's performance remained unaffected (Gnambs, Appel, & Batinic, 2010). Shibasaki and Masataka (2014) investigated the effect of the color red on time perception and reported that men, but not women, overestimated the duration of the red screen. Similarly, a gender-dependent color effect has been published by other researchers (Gnambs, Appel, & Kasper, 2015; Hill & Barton, 2005). One potential underlying mechanism may be the evolutionary advantage theory. According to previous studies (Hill & Barton, 2005; Ioan et al., 2007), the association of red with dominance and avoidance had weaker importance for survival and reproduction for women while had stronger significance for men. Hence, men tended to be more sensitive to red and seemed to be more vulnerable towards the detrimental effects of the red color than women. Therefore, we expected that there would be a significant interaction effect by which men would be affected by red color much more than women.

Overall, both colored light and risk-taking are everywhere in our daily life, yet rigorous scientific research about the effect of colored light on risk-taking is sparse. The results of previous studies have not been clear enough to determine whether people behave riskier under red light compared with other ambient light. Thus, we employed the BART to assess individual risky choices under different ambient light (red light vs. blue light) conditions and included the Chinese Big Five Personality Inventory, the Morningness-Eveningness Questionnaire, the Self-Control Scale, the Barratt Impulsiveness Scale-11, and age as covariate variables. In previous relevant studies, red seemed to decrease risk-taking in the field of color psychology while increase risk-taking in the field of color light psychology. As our experiment was implemented in red ambient light, we hypothesized that people would behave more riskily under the red light condition than the blue light condition. Moreover, we expected that there would be a significant interaction effect between colored light and gender. Furthermore, many previous studies have found that light could affect an individual's alertness (Cajochen, 2007; Figueiro, Sahin, Wood, & Plitnick, 2016) and mood (LeGates, Fernandez, & Hattar, 2014; Plitnick, Figueiro, Wood, & Rea, 2010). Therefore, to explore whether there is a potential mediating process (i.e., whether red light effects subjective sleepiness and mood which in turn affects risk-taking), subjective sleepiness and mood and the participant's evaluation of the lighting conditions were measured.

Section snippets

Design

This study employed a 2-within (colored light: red light vs. blue light) x 2-between (sex: male vs. female) mixed-model design. Participants came to the laboratory at the same time on two separate days (with at least three days between the two sessions). During each session, participants completed the BART. The order of light manipulation sessions was counterbalanced across participants. After the final measurement session, participants completed questionnaires on personality traits,

Results

The experimental design assured random assignment to the color conditions. Controlling for these variables had little effect on the results. Therefore, all the results shown below were analyzed before the adjustment for the covariates (i.e., without control variables). And we also reported the results of the full ANCOVAs (i.e., with control variables) in the supplemental material. The correlations among the various covariates are shown in Table 1, and the means and standard deviations for all

Discussion

So far, there have been few studies investigating the effects of colored light on individuals’ risky decisions. The current study explored the effect of colored light (red light vs. blue light) on BART performance. To our knowledge, this study was the first study to systematically examine whether exposure to red light induces riskier decisions under controlled lab conditions. Based on previous studies, we hypothesized that males took more risks than females, and red light exposure would induce

Conclusion

Risky decisions are a pervasive and inevitable part of life, and they are affected by a large number of variables, including ambient light. Although light is permanently present in our daily life, rigorous scientific research regarding the psychological influences of light has been sparse. Given this issue, exploring the factors that influence risky decisions is particularly important and has real-world implications. In summary, the current study reported that red light exposure does not induce

Acknowledgements

This work has been funded by the National Key Research and Development Program of China (No. 2016YFB0401202); National Natural Science Foundation of China (Grant No. U1501244, 51561135014), Guangdong Innovative Research Team Program (No. 2013C102); Program for Chang Jiang Scholars and Innovative Research Teams in Universities (No. IRT_17R40); the Innovation Project of Graduate School of South China Normal University (No. 2017WKXM007); Guangdong Provincial Key Laboratory of Optical Information

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