The influence of romantic partners on male risk-taking

Abstract

Studies show that young men’s tendency to take risks may be exacerbated or attenuated in different social contexts. Despite widespread evidence that social context influences young men’s risk-taking, few studies have examined the impact of romantic partners on risky decision-making. The present study examined risk-taking among young men in relationships with women (n = 134, ages 18–24) randomly assigned to be tested alone (n = 47), in the presence of their romantic partner (n = 44), or in the presence of an attractive female stranger (n = 43). The presence of a romantic partner diminished young men’s tendency to take risks. Findings demonstrate that a dampening effect on risk-taking is attributable to the romantic partner’s presence and not merely due to knowledge of being in a relationship.

Keywords

Late adolescence opposite-sex peers peer influence risk-taking romantic relationships romantic partners social influence young adulthood young men

Adolescents (including individuals in their early twenties) are more likely than children and somewhat older adults to engage in risk-taking both in the real world (Institute of Medicine and National Research Council, 2011) and in the lab (Duell et al., 2018; Shulman et al., 2016). One hallmark characteristic of adolescent risk-taking is that a disproportionate amount of it occurs when individuals are with their peers (Steinberg, 2008). For instance, young drivers are much more likely to speed and drive recklessly when accompanied by the same-age passengers than when driving alone (Ouimet et al., 2010; Simons-Morton et al., 2005). Experimental work also demonstrates that, compared to when they are alone, adolescents take more risks in the presence of other same-sex peers (Albert et al., 2013; Chein et al., 2011; Silva et al., 2015, 2016; Smith et al., 2014). Moreover, studies suggest the effect of same-sex peers on risk-taking behavior may be greater in young men compared to women (Gardner & Steinberg, 2005).

While the influence of same-sex peers on adolescent risk-taking has been widely studied, fewer investigations have focused on the influence of opposite-sex peers and romantic partners. This is a significant gap in our knowledge since young people become increasingly more involved in a wide array of romantic experiences by late adolescence and early adulthood. Some research suggests that, compared to single men, romantically involved men are less prone to risk-taking when they are in the presence of an attractive female stranger (Baker & Maner, 2008, 2009; Frankenhuis & Karremans, 2012; Ronay & van Hippel, 2010). While these findings suggest that the influence of opposite-sex peers on young men’s risk-taking propensity may differ as a function of their relationship status, it does not rule out the possibility that men who take fewer risks are simply more likely to be in stable romantic relationships.

Nonetheless, the potential protective effect of being in a romantic relationship has been implicated in correlational studies that compare risk-taking behavior between single and romantically involved youth (Amato & Kane, 2011; Barr & Simon, 2015; Fleming et al., 2010; Monahan et al., 2014; Staff et al., 2010). For example, one study followed recent high school graduates for 2 years (from ages 18 to 20) to examine the association between shifts in relationship status and changes in substance use (Fleming et al., 2010). After controlling for individual differences in baseline levels of substance use, as well as employment, school enrollment, and parenthood, the researchers found that romantically involved youth engaged in less heavy drinking and marijuana use than single individuals over the 2-year study period. Similarly, Gudonis-Miller et al. (2012) found that high school students who became romantically involved or whose existing relationship became more serious during a 6-year period (from ages 17 to 23) were less likely to use drugs at age 23, after controlling for marijuana use at age 17. Together, these findings suggest that being in a romantic partnership in late adolescence or early adulthood may dampen risk-taking.

By controlling for baseline differences in risk behavior, correlational studies showing that romantically involved young men have lower rates of risk-taking than their unattached peers partly rule out the possibility that more risk-averse males are simply more likely to establish and maintain longer-term relationships. However, studies that link romantic attachment to males’ lower rates of risk-taking in the real world cannot distinguish between accounts that attribute this association to diminished opportunities for risky behavior that often accompany commitment to an intimate partnership (e.g., less time available to socialize in all male peer groups; Warr, 1998) or to psychological changes that develop over time and deter risk-taking when individuals establish stable, high-quality romantic partnerships (Giordano et al., 2002). More generally, we do not know whether young men’s inclination toward risk-taking is diminished by the actual presence of a partner or merely by the knowledge that they are in a secure relationship.

The present study

In this study, we employed a similar behavioral paradigm as that used in prior peer effect studies (e.g., Silva et al., 2015) to compare risk-taking propensity among romantically involved young men randomly assigned to be tested in one of three conditions: alone, in the presence of their girlfriend, or in the presence of an attractive female stranger. Experiments that expose young men to attractive female strangers create a unique and ecologically valid context for understanding the ways in which males respond to potentially tempting interpersonal stimuli (Frankenhuis & Karremans, 2012; Lydon & Karrevans, 2015; Maner et al., 2008). Generally, the presence of attractive female strangers diminishes risk-taking in romantically involved young men, at least when compared to single men (Frankenhuis & Karremans, 2012), presumably by shifting the individual’s goal toward maintaining his existing relationship and securing long-term reproductive success (Lydon, 2010; Lydon & Karremans, 2015). To the extent that the presence of an attractive female stranger cues young men to think about their current romantic relationship and partner, and to behave in ways that are consistent with wanting to maintain that bond (especially in situations where their significant other is absent but nearby), we assessed whether the mere presence of an attractive female stranger dampens young men’s risk-taking, or whether the actual presence of a romantic partner has an effect on young men’s risk-taking relative to when they are alone. We hypothesized that young men would take fewer risks in the presence of their romantic partner compared to when they are alone or in the presence of an attractive female stranger. Thus, we predicted that the actual presence of a romantic partner would have a protective effect on males’ risk-taking behavior. This prediction was guided by the Theory of Cognitive Transformation which posits that when individuals enter secure romantic partnerships (particularly marriage), there are affective and cognitive transformations that develop or become more refined—such as the ability to self-regulate—that may lower individuals’ propensity for risk-taking and facilitate the longevity of the partnership (Giordano et al., 2002). In particular, Giordano and colleagues (2007) argue that, as a romantic relationship develops, individuals improve their ability to manage emotions in socially acceptable ways. Furthermore, they suggest that part of what facilitates improvements in emotion regulation is the diminution of positive or rewarding emotions (e.g., thrill, excitement) associated with risk-taking itself (Giordano et al., 2007). Giordano and colleagues (2002, 2007) posit that improved self-regulation and a diminished reward response to risk behaviors enable a sort of “emotional mellowing” that makes individuals less likely to engage in risky activities (Giordano et al., 2007, p. 1611).

Based on this perspective, which has received some empirical support in studies of married adults (e.g., Forrest & Hay, 2011), we reasoned that young men would engage in less risk-taking in the presence of a romantic partner. According to the Giordano and colleagues (2002, 2007), this partner effect may occur because partner presence (relative to absence) may provoke better self-regulation and greater orientation toward future (as opposed to immediate) rewards among individuals who are presumably motivated to establish or sustain their long-term romantic attachment. The present study was not designed to formally test the role of self-regulation and future orientation as mediators of the hypothesized link between partner presence and risk-taking. Nonetheless, the present study explored the effect of romantic partners on several of the processes—namely inhibitory control, future orientation, and learning from consequences—implicated in Theory of Cognitive Transformation (Giordano et al., 2002, 2007) and theories of adolescent and young adult risk-taking behavior (Shulman et al., 2016). We provide the results of our exploratory analyses of these processes in Online Supplemental Material to this manuscript. In our view, this is a necessary first step in exploring potential mechanisms through which the presence of a romantic partner may tamper risk-taking in young men.

Method

Participants and procedures

Young cross-sex couples were recruited from local colleges in a large northeastern U.S. city. The study was publicized through printed advertisements designed to recruit young couples between 18 and 24 years old to participate in a decision-making study. Interested individuals who contacted our research office were screened to ensure they met the age criteria and were able to come to the lab with their romantic partner for a 75-min visit.

In the lab, couples were tested in one of the three experimental conditions: (1) Alone, where the couple was separated and each partner in the pair was tested alone; (2) Female Stranger (Confederate) Presence, in which the male partner was tested in the presence of an attractive female stranger and the romantic partner was tested alone; and (3) Romantic Partner Presence, in which the male partner was tested in the presence of his romantic partner. In Conditions 2 and 3, the young man was selected as the target subject to complete the study tasks while the partner or female stranger observed. All experimenters in the study were female.

We determined that a sample size of 50 subjects in each condition (for a total sample size of 150 subjects) provided adequate power (0.80) to detect a significant (p < .05) moderate effect (d = .30, η² = .06). The estimated sample size of 50 subjects per condition is inflated and assumes a 20% drop out rate. Study compensation for each target participant and each partner was a US$15 Amazon gift card. In addition to this baseline compensation, all participants were informed they could win a US$10 bonus on the gift card depending on how they performed on the study tasks. When the target subject was tested in the presence of another person (girlfriend or female stranger, Conditions 2 or 3), the observer’s bonus was also said to be contingent on the performance of the target participant. This compensation strategy was used to increase motivation and engagement in the tasks. In reality, however, both the target participant and observer (girlfriend or female stranger) received both the baseline and bonus compensation (i.e., each received a US$25 gift card). The experimenters claimed to be naïve about what constituted “good performance,” and the system only informed them whether or not a participant reached the “performance threshold” at the end of the all behavioral tasks.

The experimental procedure was as follows. Upon arrival at the laboratory, each couple was assigned to one of the three experimental conditions. Condition assignment was counterbalanced, such that we assigned one participant couple to Condition 1, the next participant couple to Condition 2, and so forth until the target sample for each condition was met. A 24-year-old attractive female was recruited to serve as the study confederate in Condition 2. Confederate attractiveness was established by having 32 independent male undergraduates view 3 photographs of the female confederate and rate how attractive they found her on a scale from 1 (very unattractive) to 9 (very attractive). The mean attractiveness rating was 7.28 (SD = 0.81).

Members of couples assigned to Conditions 1 (alone) and 2 (confederate) were separated, and each partner in the pair was escorted to a different testing room. In order to introduce the confederate in Condition 2, a second experimenter approached the testing room to say that a female participant had just arrived without a partner—that she and her boyfriend were scheduled to participate but because they recently broke up, she wanted to know whether she could still participate in the study. The experimenters exchanged this information in the front of the male participant and briefly pretended to ponder how to accommodate the extra participant. The male participant was subsequently asked if he would be comfortable participating with another female. No participants declined to participate with the “extra participant.” The confederate was thereafter escorted to the testing room and introduced as a study participant. This procedure was repeated consistently for all participants in the confederate condition. In addition, other than affirming that she was single without providing details of her breakup (if the male participant asked), the confederate was instructed to interact naturally with the participant during the experiment. While males assigned to Condition 2 were tested in the presence of the study confederate, their girlfriends were simultaneously tested alone.

Each participant in Conditions 2 and 3 was asked to write their name on a piece of paper for the experimenter to “randomly” select which of the two participants would complete the study tasks while the other person observed. In actuality, the experimenter always selected the male participant to complete the study tasks while the female (confederate or romantic partner) observed. This manipulation enabled us to focus on examining only males’ behavior across different social contexts, while giving the impression that the female participant had equal chances of being selected to complete the behavioral tasks.

Because we were concerned that participants might discuss the study with fellow students who might be interested in participating, we waited before debriefing participants until all data had been collected and enrollment was permanently halted. The study team kept a running journal of observations (including notable comments from the confederate or participants) about the study and subject-confederate interactions and concerns that may be relevant to fidelity of the study manipulation. After the study was completed, a written letter was sent to debrief all study participants about the study’s experimental manipulation and findings. The university’s Institutional Review Board approved all study procedures.

Measures

To assess risk-taking propensity, we used the Stoplight game (Steinberg et al., 2008), which is a computerized driving task in which subjects control the progress of a vehicle along a straight track, from the driver’s point of view. Prior research has found that performance on the Stoplight task is positively associated with self-reported risk-taking outside the laboratory (Duell et al., 2016; Kim-Spoon et al., 2016), as well as self-reported risk preference, impulsivity, and sensation-seeking (Duell et al., 2016), factors that are generally predictive of risk behaviors in real life.

At the beginning of the Stoplight task, a timer appears on the screen, and subjects are instructed to reach the end of the track as quickly as possible, and informed that a traffic signal will turn yellow as the car approaches each of the 32 intersections along the track (see screenshot of instructions in Online Supplemental Materials). Before the vehicle enters an intersection, the subject must decide whether to stop the car (by using the space bar) and wait for the light to turn green (STOP decision) or go through the intersection and chance a possible crash (GO decision). Subjects are informed that if they decide to brake, the car will stop safely, but that they will lose time (3 s) waiting for the green light. They are also told that if they decide to go through the intersection, the car may cross the intersection successfully and they will save time (3 s), or the car may crash into a crossing vehicle (a crash event is accompanied by squealing tires and a loud crash, as well as the image of a shattered windshield), and that they will lose even more time (6 s) than if they had decided to brake. Thus, subjects must decide whether to drive through the intersection in order to save time but chance a collision with another vehicle that will cause them to lose time, or to stop and wait, and willingly lose a smaller amount of time. Risky decisions offered the potential payoff of experiencing no delay, but also the potentially costly consequence of a crash, which added significantly to the delay. A risk-taking index for each subject was computed as the proportion of GO decisions (i.e., proportion of intersections in which the brakes were not applied, regardless of whether the subject crashed or ran the intersection successfully).

Overall, the Stoplight task is configured to have a probabilistic crash rate slightly below 50%. There are intersections in which the latency between the yellow and red lights is long enough for participants to stop, and some of these intersections are configured such that running a red light results in a crash. There are also intersections in which the latency between the yellow light and crossing vehicle is so short that almost all participants crash, and others in which the latency between the yellow light and crossing vehicle is long enough that participants can run the red light without crashing. Both the timing of the traffic signals and the probability of a crash in the associated intersections in the Stoplight task are varied and unpredictable by the subjects.

Upon collection of behavioral task(s), all subjects (target participants and their romantic partners) privately completed a series of self-report measures that assessed relationship characteristics (e.g., duration, overall relationship satisfaction, feelings of commitment), and several aspects of personality that have been shown to be correlated with risk-taking in peer contexts (sensation seeking, impulsivity, and risk preference).

Data analysis

The first step in the analysis was to conduct a series of one-way analysis of variance to test whether there were individual differences in self-reported measures (e.g., age, race, relationship characteristics, and personality traits) across experimental conditions (alone vs. confederate vs. romantic partner). If the groups differed on any of the self-reported measures, then variable was included as a covariate in subsequent behavioral analyses. To assess the effect of social context on risk-taking, we conducted an analysis of covariance specifying social context (alone vs. confederate vs. romantic partner) as the between-subjects variable, controlling for any covariates identified in the first step of the analysis.

Results

Recruitment and sample

Approximately 190 couples were screened—24 of them were ineligible to participate in the study (because they did not meet the age criteria or were unable to come to lab together). Of the 166 eligible couples, 140 participated in the study (the remaining 26 couples either did not show up to their appointment or did not enroll due to a scheduling conflict). Of the 140 couples tested, 6 couples were excluded from the analysis because they disclosed after completing the testing that they were not in fact romantically involved, despite having said so to the screener (and on their self-report questionnaire). The analytic sample for the present analyses is based on data from 134 romantically involved males (47 were tested alone, 43 were tested in the presence of an attractive female confederate, and 44 were tested in the presence of their romantic partner). Overall, 64% (n = 86) of male participants were Caucasian, approximately 13% (n = 18) were Black/African American, 14% (n = 19) were Asian/Pacific Islander, and 8% (n = 8) were Hispanic. The mean sample age was 20.2 (SD = 1.65). Participant age differed significantly across conditions, F(2, 131) = 3.92, p = .02. On average, target participants tested in the presence of their girlfriend (M = 19.84, SD = 1.58) were approximately a year younger than participants tested in the presence of the confederate (M = 20.79, SD = 1.67), and this was a statistically significant difference (p = .01). With respect to age, participants tested alone (M = 20.15, SD = 1.59) were not significantly different than those tested in the other conditions. Given these findings, subsequent analyses were run with (and without) age as a covariate. There were no other differences in demographics or self-report measures between individuals in each social context. One subject (in the confederate condition) had missing data on the Stoplight task.

Impact of social context on risk-taking

Social context had a significant effect on participants’ risk-taking behavior, F(2, 129) = 5.62, p = .005, η² = .08 (Figure 1). Post hoc comparisons indicated that participants in the presence of their girlfriend took significantly fewer risks compared to participants completing the task alone (B = −.09, SE = 0.03, 95% confidence interval (CI) [−.15, −.04], t(132) = −3.17, p = .002, d = .62), and those who were in the presence of the confederate (B = −.08, SE = 0.03, 95% CI [−.14, −.002], t(132) = −2.55, p = .01, d = .54). There were no significant differences in risk-taking between participants in the confederate and alone conditions (B = −.01, SE = 0.03, 95% CI [−.07, .04], t(132) = −0.47, p = .64). The main effect of context on risk-taking did not change when age was not included as a covariate, F(2, 130) = 4.96, p = .008, η² = .07.

Figure 1.
Risk-taking behavior across social context. Note. Error bars represent +1 SE. SE = standard error.

Discussion

As predicted, young men took fewer risks when they were with their girlfriend than when they were alone or in the presence of an attractive female stranger. This is the first study to experimentally test how the actual presence of romantic partners influences risk-taking propensity in young men in relationships with women. The results are consistent with previous, non-experimental research suggesting a protective effect of romantic partnerships against risk behaviors, such as substance use or criminal behavior. In this study, we demonstrate that a dampening effect on risk-taking is specifically attributable to the romantic partner’s presence and not merely due to differences between men who are romantically involved with women and men who are single.

The process through which the presence of romantic partners tempers young men’s risk-taking propensity remains unclear. Exploratory analyses (see Online Supplemental Material) did not yield notable insights regarding the effect of romantic partners on the psychological processes (e.g., inhibitory control) implicated by cognitive transformations theory (Giordano et al., 2002) and theories of adolescent risk-taking (Shulman et al., 2016). In particular, we did not find that the presence of a romantic partner affects self-regulation in a way that is consistent with existing theories of adolescent/young adult risk-taking or risk-taking in the context of romantic relationships. However, we can speculate about other plausible mechanisms. It is possible that being risk averse in the presence of a romantic partner signals safety, dependability, or security. It is also possible that the presence of romantic partners has a calming effect on young men, such that they become less concerned about task performance or about competing against an ambiguous “performance threshold” to receive a monetary bonus. Indeed, an alternative explanation for the observed pattern of results is that it was in the absence of the romantic partners that young men felt enticed and motivated to reach the “performance threshold” and demonstrate (to the romantic partner, once reunited at the end of the experiment) that they were able to achieve the maximum possible gain (after all, the romantic partners of men tested alone or with the study confederate were completing the Stoplight task on their own; thus, whether or not they each received the bonus was likely a point of discussion when the couple reunited after the experiment). Future research is needed to examine the mechanisms via which adolescent males adjust their propensity toward risk in ways that are aligned with their motivational goals in specific social contexts.

The present study has some limitations. Because we recruited couples to come to the lab together, there may have been a selection bias toward couples who were relatively more comfortable and familiar with each other than couples with an individual who may have been interested in the study but who was hesitant to ask their partner to participate. A second limitation is that the results from the present study are based on older adolescents and young adults, between 18 and 24 years old. It is possible that different patterns of behavior would be observed among younger or older individuals. Lastly, although performance on the Stoplight task is correlated with risk-taking behavior in the real world (Duell et al., 2016; Kim-Spoon et al., 2016), the task is not a measure of risky driving per se but serves as a means of assessing risk-taking propensity in an experimentally controlled context.

Despite these limitations, the current study has several strengths. In particular, since all participants in the present study were in relationships, the study design rules out the possibility that young men who take fewer risks are simply more likely to have stable relationships. Moreover, the current study contributes to the growing body of experimental work demonstrating that young men’s inclination to engage in risk-taking is amplified or attenuated in different social contexts (e.g., with same-sex peers [Silva et al., 2015], parents [Telzer et al., 2015], or other adults [Silva et al., 2016]). Notably, the present findings mirror the effect of parent presence on adolescent risk-taking (Telzer et al., 2015). Though deserving of further experimental investigation, the findings also suggest the intriguing possibility that the presence of a romantic partner may serve as an important check on young men’s general tendency to behave more recklessly when around other male peers.

Supplemental material

Supplemental Material, Final_Edits_Supplemental_Material_Other_Behavioral_Findings - The influence of romantic partners on male risk-taking

Supplemental Material, Final_Edits_Supplemental_Material_Other_Behavioral_Findings for The influence of romantic partners on male risk-taking by Karol Silva, Jason Chein and Laurence Steinberg in Journal of Social and Personal Relationships

Footnotes

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Karol Silva

Open research statement

As part of IARR’s encouragement of open research practices, the author(s) have provided the following information: This research was not pre-registered. The data and materials used in the research are available upon reasonable request. The data and materials can be obtained by emailing: karol.alejandra@gmail.com.

Supplemental material

Supplemental material for this article is available online.

References

Albert

Chein

Steinberg

(2013). Peer influences on adolescent decision-making. Current Directions in Psychological Science, 22, 80–86.

Amato

P. R.

Kane

J. B.

(2011). Life-course pathways and the psychosocial adjustment of young adult women. J Marriage and Family, 73, 279–295.

Baker

M. J.

Maner

J. K.

(2008). Risk-taking as a situationally sensitive male mating strategy. Evolution and Human Behavior, 29, 391–395.

Baker

M. J.

Maner

J. K.

(2009). Male risk-taking as a context-sensitive signaling device. J Experimental Social Psychology, 45, 1136–1139.

Barr

A. B.

Simons

R. L.

(2015). Different dimensions, different mechanisms? Distinguishing relationship status and quality effects on desistance. J Family Psychology, 29, 360–370.

Chein

Albert

O’Brien

Uckert

Steinberg

(2011). Peers increase adolescent risk taking by enhancing activity in the brain’s reward circuitry. Developmental Science, 14, F1–F10.

Duell

Steinberg

Chein

Al-Hassan

S. M

Bacchini

Lei

Chaudhary

Di Giunta

Dodge

K. A.

Fanti

K. A.

Lansford

J. E.

Malone

P. S.

Oburu

Pastorelli

Skinner

A. T.

Sorbring

Tapanya

Uribe Tirado

L. M.

Alampay

L. P

. (2016). Interaction of reward seeking and self-regulation in the prediction of risk-taking: A cross-national test of the dual systems model. Developmental Psychology, 52, 1593–1605.

Duell

Steinberg

Icenogle

Chein

Chaudhary

Di Giunta

Dodge

K. A.

Fanti

K. A.

Lansford

J. E.

Oburu

Pastorelli

Skinner

A. T.

Sorbring

Tapanya

Uribe Tirado

L. M.

Alampay

L. P.

Al-Hassan

S. M.

Takash

H. M. S.

Bacchini

Chang

. (2018). Age patterns in risk taking across the world. J Youth and Adolescence, 47, 1052–1072.

Fleming

C. B.

White

H. R.

Catalano

R. F.

(2010). Romantic relationships and substance use in early adulthood: An examination of the influences of relationship type, partner substance use, and relationship quality. J Health and Social Behavior, 51, 153–167.

10.

Forrest

Hay

(2011). Life-course transitions, self-control and desistance from crime. Criminology and Criminal Justice, 11, 487–513.

11.

Frankenhuis

W. E.

Karrenmans

J. C.

(2012). Uncommitted men match their risk taking to female preferences, while committed men do the opposite. J Experimental Social Psychology, 48, 428–431.

12.

Gardner

Steinberg

(2005). Peer influence on risk taking, risk preference, and risky decision making in adolescence and adulthood: An experimental study. Developmental Psychology, 41, 625–635.

13.

Giordano

P. C.

Cernkovich

S. A.

Rudolph

J. L.

(2002). Gender, crime, and desistance: Toward a theory of cognitive transformation. American J Sociology, 107, 990–1064.

14.

Giordano

P. C.

Schroeder

R. D.

Cernkovich

S. A.

(2007). Emotions and crime over the life course: A neo-Meadian perspective on criminal continuity and change. American Journal of Sociology, 112, 1603–1661.

15.

Gudonis-Miller

L. C.

Lewis

Tong

Aalsma

M. C.

(2012). Adolescent romantic couples influence on substance use in young adulthood. J Adolescence, 35, 638–647.

16.

Institute of Medicine & National Research Council. (2011). The science of adolescent risk-taking: Workshop summary. National Academies Press.

17.

Kim-Spoon

Kahn

Deater-Deckard

C. P.

Steinberg

King-Casas

. (2016). Risky decision making in a laboratory driving task is associated with health risk behaviors during late adolescence but not adulthood. International J Behavioral Development, 40, 58–63.

18.

Lydon

J. E.

(2010). How to forego forbidden fruit: The regulation of attractive alternatives as a commitment mechanism. Soc Pers Psychol Compass, 4, 635–644.

19.

Lydon

J. E.

Karremans

J. C.

(2015). Relationship regulation in the face of eye candy: A motivated cognition framework for understanding responses to attractive alternatives. Current Opinion in Psychology, 1, 76–80.

20.

Maner

J. K.

Rouby

D. A.

Gonzaga

G. C.

(2008). Automatic inattention to attractive alternatives: The evolved psychology of relationship maintenance. Evolution and Human Behavior, 29, 343–349.

21.

Monahan

K. C.

Dmitrieva

Cauffman

(2014). Bad romance: Sex differences in longitudinal associations between romantic relationships and deviant behavior. J Research on Adolescence, 24, 12–26.

22.

Ouimet

M. C.

Simons-Morton

B. G.

Zador

P. L.

Lerner

N. D.

Freedman

Duncan

G. D.

Wang

(2010). Using the U.S. National Household Travel Survey to estimate the impact of passenger characteristics on young drivers’ relative risk of fatal crash involvement. Accident Analysis and Prevention, 42, 689–694.

23.

Ronay

von Hippel

(2010). The presence of an attractive woman elevates testosterone and physical risk taking in young men. Social Psychological and Personality Science, 1, 57–64.

24.

Shulman

E. P.

Smith

A. R.

Silva

Icenogle

Duell

Chein

Steinberg

(2016). The dual systems model: Review, reappraisal, and reaffirmation. Developmental Cognitive Neuroscience, 17, 103–117.

25.

Silva

Chein

Steinberg

(2016). Adolescent in peer groups make more prudent decisions when a slightly older adult is present. Psychological Science, 27, 322–330.

26.

Silva

Shulman

E. P.

Chein

Steinberg

(2015). Peers increase adolescents’ exploratory behavior and sensitivity to positive and negative feedback. J Research on Adolescence, 26, 696–705.

27.

Simons-Morton

Lerner

Singer

(2005). The observed effect of teenage passenger on the risky driving behavior of teenage drivers. Accident Analysis and Prevention, 37, 973–982.

28.

Smith

A. R.

Chein

Steinberg

(2014). Peers increase adolescent risk taking even when the probabilities of negative outcomes are known. Developmental Psychology, 50, 1564–1568.

29.

Staff

Schulenberg

J. E.

Maslowsky

Bachman

J. G.

O’Malley

P. M.

Maggs

J. L.

Johnston

L. D.

(2010). Substance use changes and social role transitions: Proximal developmental effects on ongoing trajectories from late adolescence through early adulthood. Development and Psychopathology, 22, 917–932.

30.

Steinberg

(2008). A social neuroscience perspective on adolescent risk-taking. Developmental Review, 28, 78–106.

31.

Telzer

E. H.

Ichien

N. T.

(2015). Mothers know best: Redirecting adolescent reward sensitivity toward safe behavior during risk taking. Social Cognitive and Affective Neuroscience, 10, 1383–1391.

32.

Warr

(1998). Life course transitions and desistance from crime. Criminology, 36, 183–216.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.47 MB