Are Risk-Preferences Dynamic? Within-Subject Variation in Risk-Taking as a Function of Background Music

Halko, Marja‐Liisa; Kaustia, Markku

doi:10.2139/ssrn.1997520

Cited by 4 publications

(13 citation statements)

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“…Regarding participants, almost all of the included studies involved healthy people and just one of them investigated schizophrenia patients (Moritz et al, 2009). Most of the studies involved students (Brooks & Schweitzer, 2011; Day et al, 2009; Fischer & Greitemeyer, 2006; Greitemeyer, 2009a, 2009b; Skulmowski et al, 2014; Strick et al, 2015), while one of them investigated adolescents and teenagers (Halko & Kaustia, 2012) and just one of them included children (Kirschner & Tomasello, 2010). In general, the number of participants was quite small, with five studies having less than 40 participants (Chung et al, 2016; Day et al, 2009; Greitemeyer, 2009b, Study 1; Halko & Kaustia, 2012; Halko et al, 2015), and seven studies with 40 to 60 participants (Greitemeyer, 2009b, Study 2, 3 and 4; Greitemeyer, 2011, Study 5; Moritz et al, 2009; Schulreich et al, 2014).…”

Section: Resultsmentioning

confidence: 99%

“…Most of the studies involved students (Brooks & Schweitzer, 2011; Day et al, 2009; Fischer & Greitemeyer, 2006; Greitemeyer, 2009a, 2009b; Skulmowski et al, 2014; Strick et al, 2015), while one of them investigated adolescents and teenagers (Halko & Kaustia, 2012) and just one of them included children (Kirschner & Tomasello, 2010). In general, the number of participants was quite small, with five studies having less than 40 participants (Chung et al, 2016; Day et al, 2009; Greitemeyer, 2009b, Study 1; Halko & Kaustia, 2012; Halko et al, 2015), and seven studies with 40 to 60 participants (Greitemeyer, 2009b, Study 2, 3 and 4; Greitemeyer, 2011, Study 5; Moritz et al, 2009; Schulreich et al, 2014). Five studies included 60 to 100 people (Greitemeyer, 2009a; Kirschner & Tomasello, 2010; Kniffin et al, 2016, Study 1; 1 Skulmowski et al, 2014; Strick et al, 2015, Study 1), while four of them involved more than 100 participants (Brooks & Schweitzer, 2011; Fischer & Greitemeyer, 2006, Study 1 and 3; Kniffin et al, 2016, Study 2).…”

Section: Resultsmentioning

confidence: 99%

“…In particular, some of them used between-subjects designs (Brooks & Schweitzer, 2011, Study 1; Chung et al, 2016; Fischer & Greitemeyer, 2006, Study 1 and 3; Kirschner & Tomasello, 2010; Kniffin et al, 2016, Study 1 and 2; Strick et al, 2015, Study 1). Four studies used within-subjects designs (Day et al, 2009; Halko & Kaustia, 2012; Halko et al, 2015; Schulreich et al, 2014), while two studies combined both between and within-subject factors (Moritz et al, 2009; Skulmowski et al, 2014).…”

Section: Resultsmentioning

confidence: 99%

“…In terms of the type of music, we highlight that the vast majority of the studies used standardized songs for all the participants, pre-selected by experts or experimenters. Only the research of Halko and colleagues used liked and disliked music, previously selected by participants (Halko & Kaustia, 2012; Halko et al, 2015).…”

Section: Resultsmentioning

confidence: 99%

“…Strick et al (2015) also investigated the positive and negative affective response, which can be related to the mood or valence dimension of Russell’s (1980) model. The studies of Halko and colleagues, despite not being interested in specific emotions, assumed that mood has a mediator effect between music and risk-taking (Halko & Kaustia, 2012; Halko et al, 2015).…”

Section: Resultsmentioning

confidence: 99%

See 4 more Smart Citations

Music-induced emotion effects on decision-making

Palazzi

Fritzen

Gauer

2018

Psychology of Music

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This qualitative systematic review aimed to examine music-induced emotion effects on decision-making. Empirical articles published from 2006 to 2016 were searched for in PubMed and PsycInfo. Through the main search, 634 records were identified and 15 articles were included and analyzed according to the following categories: aims of the study, participants, study design, type of music, type of emotion, decision-making tasks, and study results. The included studies aimed to investigate the effects of music on prosociality and aggression, risk-taking, and other decision-making processes. All studies used experimental designs and most of them used pre-selected music and stimulation through music listening. Different decision-making tasks were used, such as a gambling task, helping behavior tasks, and even assessment of aggressive behavior through adding hot chili sauce to food. Results showed that music is a powerful and engaging stimulus that influences decision-making processes and risk-taking, promotes prosociality, and affects customers’ behavioral choices. Different underlying processes in the interaction between music, mood, and decision-making are discussed. This review contributes to promoting research on the use of background music as an arousal and mood inducer in different contexts, as well as music-based interventions to foster prosociality and decrease aggressive behaviors.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 3 more Smart Citations

Music-induced emotion effects on decision-making

Palazzi

Fritzen

Gauer

2018

Psychology of Music

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Hedonic context modulates risky choices and reward responses in amygdala and dorsal striatum.

Halko¹,

Mäkelä²,

Nummenmaa³

et al. 2015

Journal of Neuroscience, Psychology, and Economics

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The hedonic context of the environment can alter an individual's emotional states and consequently their risk taking. Here we reveal the brain mechanisms underlying music-induced unstable risk preferences using functional MRI (fMRI). Subjects listened to self-selected liked or disliked music while they decided to accept or reject risky gambles. Behaviorally loss aversion was lower during liked music than during disliked or no music. At the neural level, reduced loss aversion was associated with a specific pattern of value coding in amygdala and dorsal striatum: during disliked music gambles with high expected reward induced higher activation than gambles with low expected reward, whereas during liked music this activation pattern was reversed. Furthermore, individual differences in loss aversion influenced value coding in such a way that for the most loss-averse subjects, bilateral activation of anterior insula, dorsolateral prefrontal cortex, and posterior parietal cortex increased as the expected value of the gamble increased, whereas for the least loss-averse subjects increase in potential reward was associated with decreasing activation in those areas. We propose music-modulated value coding in amygdala and striatum as a neural mechanism supporting emotiondependent adjustments to risk-taking which in turn facilitate behavior depending on how dangerous versus safe the environment is experienced to be.

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Contextual Factors Affecting Risky Decision Making: The Influence of Music on Task Performance and Perceived Distraction

et al. 2022

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Previous research has investigated factors that contribute to the development of different risk-taking behaviors, such as can occur on lab-based behavioral risky decision making tasks. On several of the most common tasks, participants must develop an adequate understanding of the relative risks and benefits associated with each decision in order to learn to decide advantageously. However, contextual factors can affect the decision making process and one’s ability to weigh the risks and benefits of a decision. The present study investigates the extent to which music may be an additional contextual factor that can disrupt decision making and other executive functions. Across four studies we examine whether having music playing passively in the background or having participants actively listen to music affects performance on measures of risky decision making, working memory, processing speed, and problem solving. Participants reported greater distraction for rock music than classical music in the passive listening studies but did not report any differences in distraction across conditions in the active listening studies. Despite this self-reported increased level of distraction, few significant differences were found in task performance across groups and across studies. The Angling Risk Task (ART) was sensitive to differences in risk by condition, with music leading to greater risk-taking in a passive listening study, but less risk-taking in an active listening study, compared to no music. The extent to which music serves as a contextual factor disrupting performance on measures of risky decision making and other executive functions may depend in part on whether individuals are actively versus passively listening to the music.

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Are Risk-Preferences Dynamic? Within-Subject Variation in Risk-Taking as a Function of Background Music

Cited by 4 publications

References 55 publications

Music-induced emotion effects on decision-making

Music-induced emotion effects on decision-making

Hedonic context modulates risky choices and reward responses in amygdala and dorsal striatum.

Contextual Factors Affecting Risky Decision Making: The Influence of Music on Task Performance and Perceived Distraction

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