When Do those “Risk-Taking Adolescents” Take Risks? The Combined Effects of Risk Encouragement by Peers, Mild-to-Borderline Intellectual Disability and Sex

Eline Wagemaker; Hilde M. Huizenga; Tycho J. Dekkers; Annematt L. Collot d’Escury-Koenigs; Elske Salemink; Anika Bexkens

doi:10.1007/s10802-020-00617-8

When Do those “Risk-Taking Adolescents” Take Risks? The Combined Effects of Risk Encouragement by Peers, Mild-to-Borderline Intellectual Disability and Sex

Wagemaker, Eline; Huizenga, Hilde M.; Dekkers, Tycho J.; Collot d’Escury-Koenigs, Annematt L.; Salemink, Elske; Bexkens, Anika 2020-04-17 00:00:00 Adolescents with mild to borderline intellectual disability (MBID) show more daily life risk taking than typically developing adolescents. To obtain insight in when these “risk-taking adolescents” especially take risks, we investigated main and interaction effects of (a) MBID, (b) sex, and (c) type of peer influence on risk taking. The Balloon Analogue Risk Task (BART) was used as a proxy of real-life risk taking. 356 adolescents (12–19 years, 51.7% MBID, 63.4% boys) were randomly assigned to one of three BART peer-influence conditions: solo (no peers), positive risk encouragement (e.g., ‘You are cool if you continue’)or negative risk encouragement (e.g., ‘You are a softy if you do not continue’). The main finding was that boys with MBID took more risks than typically developing boys in the negative risk encouragement condition. Boys with MBID also took more risks in the negative risk encouragement condition compared to the solo condition, whereas typically developing boys did not. There were no such effects for girls. Surprisingly, boys with MBID took less risks in the solo condition than typically developing boys. We conclude that boys with MBID especially show high risk taking when peers belittle or threat with exclusion from the peer group. Prevention and intervention programs should specifically target boys with MBID to teach them to resist negative risk encour- agement by peers. . . . . Keywords Adolescence Risk taking Peer influence Intellectual disability Balloon Analogue Risk Task Risk-taking behavior (e.g., substance use, reckless driving, sex- ual risk taking) is the leading cause of death in adolescents (Dahl 2004; Institute of Medicine 2011) and results in high societal * Eline Wagemaker costs (Groot et al. 2007). The dual systems model or imbalance E.Wagemaker@uva.nl model provides the dominant explanation for high risk taking in adolescence by proposing an imbalance between the fast devel- oping social-emotional systems and the more gradual developing Department of Psychology, University of Amsterdam, Nieuwe Achtergracht 129b, 1018, WS Amsterdam, The Netherlands cognitive control systems in the adolescent brain (Steinberg 2010). However, not all adolescents show high risk taking, many Research Priority Area Yield, University of Amsterdam, Amsterdam, The Netherlands individual differences exist. In 2015, Bjork and Pardini published a paper centered on the question ‘Who are those “risk-taking Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands adolescents”?’. Based on their research and earlier findings, high Department of Forensic Youth Psychiatry and Behavioral Disorders, risk taking in adolescence has been related to sensation seeking, De Bascule, Academic Center of Child- and Adolescent Psychiatry, impulsivity, low cognitive control, and low educational levels Amsterdam, The Netherlands (Bjork and Pardini 2015; Harakeh et al. 2012;Jessor 1992). Mind at Work, Almere, The Netherlands These characteristics are often overly represented in adolescents Department of Clinical Psychology, Utrecht University, with mild to borderline intellectual disability (MBID; e.g., Utrecht, The Netherlands Bexkens et al., 2014). MBID is definedbyanIQbetween 50 Department of Psychology, Developmental and Educational and 85 and problems in social adaptability (De Beer 2016). The Psychology, Leiden University, Leiden, The Netherlands prevalence of MBID is about 10% (Simonoff et al. 2006). In GGZ Delfland, Delft, The Netherlands daily life, adolescents with MBID indeed show more risk taking 574 J Abnorm Child Psychol (2020) 48:573–587 than typically developing peers, and they are over-represented in virtual peers than in the version without the peers. On top of that, the criminal justice system (Holland et al. 2002; Kaal 2016;Van adolescents with MBID took more risks than typically develop- Duijvenbode and Van der Nagel 2019). However, it is unclear ing adolescents, but only in the condition with the virtual peers. whether all adolescents with MBID are risk takers and whether This study provides initial evidence that adolescents with MBID the risk-taking context matters. Therefore, the current study ex- may be more susceptible to peer influence than typically devel- amines the impact of sex and peer influences on risk taking in oping adolescents. From the perspective of the imbalance model, adolescents with and without MBID. increased susceptibility to peer influence in adolescents with Adolescence is known as a period of increased sensitivity to MBID could be explained by a larger imbalance between peer influence (Crone and Dahl 2012; Steinberg and Morris social-emotional and cognitive control systems. Although this 2001;Van Hoornetal. 2017). Indeed, the peer context is related claim has not been investigated at a neurobiological level, there to adolescent risk taking in daily life, as demonstrated by the is ample evidence that adolescents with MBID have inhibition doubled risk of fatal injuries during driving accompanied by deficits as compared to typically developing adolescents (see peers (Chen et al. 2000). Several experimental studies also Bexkens et al. 2014 for a meta-analysis; Schuiringa et al. demonstrate that the (perceived) presence of peers increases risk 2017), and inhibition is an important component of cognitive taking (De Boer and Harakeh 2017; Gardner and Steinberg control (Ridderinkhof et al. 2004). These inhibitory deficits 2005; Maclean et al. 2014;Van Hoornetal. 2017;Weigard may suggest a larger imbalance between the social-emotional et al. 2014). However, adolescents vary in their susceptibility and the cognitive control system in adolescents with MBID, to peer influence on risk taking. These individual differences which may increase their susceptibility to peer influence can be related to resistance skills, social acceptance by friends (Albertetal. 2013). Therefore, the first goal of this study is to or peer status (Allen et al. 2012; Prinstein et al. 2011;Urberg confirm that adolescents with MBID are more susceptible to peer et al. 2003). More knowledge about individual factors could influence than adolescents without MBID. help to identify specific contexts in which at-risk groups are likely to show risky behavior. With this knowledge, prevention or intervention programs could be fine-tuned. The current study Sex Differences in Susceptibility to Peer focuses on three potential factors that may affect susceptibility Influence to peer influence in a risk-taking context. First, low intellectual functioning (i.e., MBID) could increase the susceptibility to Previous research about sex differences in susceptibility to peer peer influence. Second, boys and girls could differ in their sus- influence showed mixed results. Several experimental and self- ceptibility to peer influence. Third, the type of risk encourage- report studies found that boys were more susceptible to peer ment by peers may differentially relate to risk taking. The liter- influence than girls (De Boer et al. 2017;Sumteretal. 2009; ature for each of these factors is reviewed below. Widman et al. 2016), and this pattern was similar for adoles- cents with MBID (Dekkers et al. 2017). However, other exper- imental studies demonstrated that girls are more susceptible to Susceptibility to Peer Influence in Adolescents peer influence than boys (Shepherd et al. 2011)ordid notfind with MBID any differences between boys and girls (Gardner and Steinberg 2005). Similarly, recent neurobiological studies propose a gen- Few studies have focused on susceptibility to peer influence in eral pubertal surge in testosterone in both boys and girls, which adolescents with MBID. Professionals working with this popu- increases the motivation to be admired by others, and may lation, however, often report questions on how to deal with risk therefore increase risk taking under peer influence in both boys taking related to increased susceptibility to peer influence. and girls (Braams et al. 2015; Crone and Dahl 2012). Based on Indeed, intellectual disability is characterized by lower risk- these studies, it remains unclear whether sex differences are awareness (Greenspan et al. 2011), and vignette studies suggest relevant in susceptibility to peer influence. Therefore, the sec- that adolescents with MBID especially struggle to make safe ond goal of this study is to explore sex differences in suscepti- decisions under peer influence (Khemka et al. 2009). Also, ado- bility to peer influence in adolescents with and without MBID. lescents with MBID report lower resistance to peer influence than typically developing adolescents (Dekkers et al. 2017). To our knowledge, there is only one experimental study that compared The Effect of the Type of Risk Encouragement the susceptibility to peer influence of adolescents with MBID by Peers and typically developing adolescents (Bexkens et al. 2018). In this study, boys with MBID and typically developing boys per- Peers can actively encourage risk taking in a variety of ways. In formed a risk-taking task either with or without three pictures of Bexkens et al. (2018), peers encouraged risk taking in a mixed same-sex virtual peers that gave risk encouraging feedback. Both way: some feedback had a positive tone (e.g., giving compli- groups demonstrated more risk taking in the version with the ments), whereas other feedback had a more negative tone (e.g., J Abnorm Child Psychol (2020) 48:573–587 575 belittling). Consequently, this study did not allow to test differ- encouragement by peers: positive vs. negative vs. none) ential effects of positive and negative risk encouragements on between-subjects design. To measure susceptibility to peer in- risk taking. Therefore, we tested whether these different encour- fluence, we use a risk-taking task with a virtual peer paradigm agements have differential effects by assigning adolescents to as this enables standardization of peer influence. It has been either a positive or a negative risk encouragement condition. In shown that this paradigm yields similar effect sizes as para- the positive condition peers give compliments or talk about digms with real peers (Chein et al. 2011; Festl et al. 2013; inclusion in the peer group, while in the negative condition Gardner and Steinberg 2005;O’Brien et al. 2011;Reynolds peers belittle or threat with exclusion from the peer group. et al. 2014; Weigard et al. 2014). We manipulated the type of Three lines of evidence suggest that negative risk encourage- risk encouragement during the task and propose the following ment by peers, especially in the form of threatening with social hypotheses. First, we hypothesize that all adolescents show exclusion, can increase risk taking in adolescents. First, because increased risk taking when exposed to peer influence compared forming peer relations is important in adolescence, the perception to solo risk-taking. As previous research provides limited re- of being socially rejected can lead to a process called reputation sults about whether positive or negative peer encouragement management (i.e., displaying risk taking to gain status or avoid has a stronger effect, we expect that the effect of peer condition rejection by peers; Blakemore 2018; Brechwald and Prinstein on risk taking is present for both positive and negative risk 2011;Chenetal. 2015). Second, perceived peer rejection causes encouragement by peers. Second, we hypothesize that adoles- stress in adolescents (Gunther Moor et al. 2014), which has a cents with MBID show more risk taking than typically devel- negative impact on inhibition (De Houwer and Tibboel 2010) oping adolescents, especially when exposed to peer influence. and may therefore foster risk taking (Bjork and Pardini 2015). Again, as previous research is insufficient to claim that positive This is also in line with the need-to-belong theory predicting that and negative peer encouragement have differential effects, we social exclusion leads to decreased self-regulation (Baumeister expect a similar effect of MBID on risk taking for positive and et al. 2005;DeWalletal. 2008;Stensengetal. 2015). Finally, negative peer encouragement. Third, we explore (a) the differ- longitudinal studies confirm that a negative interactional style ences between boys and girls as well as interactions between between adolescents (i.e., negative laughter and coercive state- sex, type of peer encouragement, and MBID and (b) the differ- ments) predicts adolescents’ school misconduct and risk taking ences between positive and negative peer encouragement. (Ellis et al. 2018). Fourth, we explore the validity of the risk-taking task by relat- Positive risk encouragements such as laughing or giving ing it to scores on a self-report questionnaire measuring real-life positive feedback in response to risk-taking behavior are highly susceptibility to peer influence (Cavalca et al. 2013). prevalent in deviant adolescents (Dishion et al. 1999). Arguably, positive risk encouragement by peers could increase risk taking through the same mechanisms as negative risk en- Methods couragement, although in a more indirect way. That is, adoles- cents who receive compliments from peers on risk taking may Participants get the impression that peers will not exclude them if they take risks. Thus, to avoid exclusion, these adolescents will show risk 382 adolescents between 12 and 19 years were recruited at taking in response to positive risk encouragement. secondary schools (M = 15.31, SD = 1.42, 63.4% boys). age To our knowledge, there is only one experimental study in Assignment to the MBID and the control group was based children (10 years) that compared the effects of social exclusion on school type. Adolescents from special vocational education versus inclusiononrisktaking (Nesdale andLambert 2008). schools were assigned to the MBID group. The current study This studyshowedthatchildrendemonstratedmorerisktaking took place in the Netherlands. Special education schools for after social exclusion than after social inclusion. As this study MBID and practical education schools in the Netherlands did not explicitly focus on what peers say to encourage risk have the following admittance criteria: (1) an IQ between 60 taking, the evidence on differential effects of peer encourage- and 85 tested no more than 2 years prior to admittance; and (2) ments is limited. Therefore, the third goal of this study is to learning delays of 50% or more in at least two of the following explore the effects of negative and positive risk encouragement areas: mathematics, reading accuracy and fluency, reading by adolescent peers on risk taking. comprehension, and spelling. Adolescents from Dutch We acknowledge that with the introduction of DSM-5 (American Psychiatric The Current Study Association 2013), the severity of the intellectual disability is no longer pri- marily defined by IQ, but by the severity of limitations in adaptive functioning. However, as the DSM-IV was in use when this study was conducted To disentangle the effects of MBID, sex, and risk encourage- (American Psychiatric Association 2000), the MBID assignment mainly fo- ment by peers on risk taking, we adopt a 2 (MBID: present vs. cused on IQ (borderline intellectual functioning: IQ between 70 and 85, or absent) by 2 (sex: boys vs. girls) by 3 (type of risk mild intellectual disability: IQ between 50 and 85). 576 J Abnorm Child Psychol (2020) 48:573–587 regular education secondary schools with different education- trial was then transferred to the counter above the wallet, al levels (i.e. lower and higher vocational education and pre- which was accompanied by the sound of a slot machine. university education) were assigned to the control group. To This money remained in possession of the participant and confirm that the MBID and the control group actually differed could be exchanged for raffle tickets at the end of the session in IQ score, we administered Raven’s Standard Progressive (Lejuez et al. 2003;Lejuez etal. 2002). Matrices (Raven’s SPM; Raven et al. 1988). Our adaptation based on Bexkens et al. (2018) differed Informed consent was obtained from both parents (or care- from the original procedure (Lejuez et al. 2002)inthat the takers) and adolescents. Schools sent passive consent letters to balloon could not explode on the first five pumps. The prob- parents two weeks prior to testing. Adolescents provided their ability of explosion on the sixth pump was 1/123, the proba- assent immediately before testing. It was explained to both par- bility of explosion on the seventh pump was 1/122, etc. This ents and adolescents that they could withdraw from participation probability distribution was used once to generate an explo- whenever they wanted and without consequences. The study sion point for every balloon. This array of explosion points was approved by the ethical review board of the University of wasthenusedfor allparticipants,sothere wasnointer- Amsterdam and complied with relevant laws and guidelines. participant variation in the probability of exploding. The mean point of explosion was 57.6 pumps. The number of adjusted pumps (i.e., the average number of pumps on non-explosion trials) was used as dependent variable. Materials The BART has a test-retest correlation of r =0.77 across days (White et al. 2008). Construct validity is supported by Balloon Analogue Risk Task (BART) An adaptation of the com- puterized BART (Lejuez et al. 2002, adapted from Bexkens significant relations to a range of daily life risk-taking behav- iors (Hunt et al. 2005; Lejuez et al. 2002; MacPherson et al. et al. 2018) was used to assess risk-taking. The task was pre- 2010;Mishra et al. 2010). The adjusted current version of the sented on a HP 550, 15.4-in. notebook. On each trial, partic- ipants were instructed that they could earn money by inflating BART was used successfully in adolescents with MBID be- fore (Bexkens et al. 2018). a balloon, whilst simultaneously running the risk of popping the balloon and losing the money. Participants inflated the Peer Influence Manipulation Three conditions were used: no balloon by clicking the pump (see Fig. 1). Each click inflated the balloon a little, which was depicted visually, and was peer influence (i.e., the solo condition), negative risk encour- agement by peers, and positive risk encouragement by peers. rewarded with one cent. A counter above the balloon kept track of the number of cents earned on a particular trial. These BART conditions were based on the solo and peer condition of Bexkens et al. (2018) but had one important dif- Participants risked the balloon to explode at each next click. When the balloon exploded, an explosion cartoon was pre- ference: we split the positive and negative risk encouragements sented on screen together with an explosion sound. All cents into two separate conditions. Participants were randomly assigned to one of the three BART conditions. In the solo con- earned on that trial were lost and the counter above the balloon was reset to zero. Participants were instructed that they could dition, there was no peer influence. In the negative and positive risk encouragement conditions, risk encouragement by peers decide to ‘sell’ the balloon at any point of their own preference by clicking on the picture of a wallet. Money earned on that was added visually and auditory. Three pictures of same-sex Fig. 1 Sample trial from one of the peer influence conditions (faces are blurred to ensure anonymity) J Abnorm Child Psychol (2020) 48:573–587 577 peers were displayed during each trial of the BART and audio described the group of people they belonged to (i.e., more files with risk encouraging statementswereplayedineachtrial vs. less peer resistant), and then they were asked to indicate (see Fig. 1). When an audio file played, a speech balloon ap- to what degree they feel they belong to this group (i.e., “Really peared next to one of the pictures indicating which peer was true” or “Sort of true”). Scores on each item were aggregated speaking. Participants were instructed that these peers already in a 4-point Likert-type scale score, in which the “Really true” completed the task and would give feedback based on the par- and “Sort of true” options of the less peer-resistant statement ticipants’ performance. In the positive risk encouragement con- were coded as 1 and 2 respectively, and the “Sort of true” and dition, the statements were positively formulated and/or “Really true” options of the more peer-resistant statement contained signs of inclusion (e.g., ‘Yes continue’ or ‘You belong were coded as 3 and 4 respectively. A sample item was: to us if you continue’). In the negative risk encouragement “Some children will not break the law just because their condition, the statements were negatively formulated and/or friends say that they would BUT other children would break contained signs of exclusion (e.g., ‘Continue softy’ or ‘If you the law if their friends said that they would break it”. The stop you are chicken’). A pilot study was performed on the maximum score is 40 and higher scores indicate higher resis- reliability of the risk-encouraging statements before execution tance to peer influence. The reliability of the RPI is high (α > of the study. 41 first year psychology students rated 243 state- 0.70; Steinberg and Monahan 2007) and criterion validity has ments on a 5-point positivity-negativity scale and on an been demonstrated (Monahan et al. 2009a, b; Steinberg and inclusion-exclusion scale. Both scales had high reliability (pos- Monahan 2007). itivity-negativity scale α = 0.96, inclusion-exclusion scale To make sure that participants understood the structure of the α =0.95). The 183 statements with most reliable scores were items of the RPI, the research assistants provided additional as- used in the BART. The statements were played in a random sistance. First, the research assistant read the instructions aloud. order and at semi-random moments during each trial (i.e., never Participants were then asked to read aloud the sample item on one of the first 10 pumps, always separated by more than 10 (“Some children like to do fun things with a lot of people BUT pumps, and the same maximum number of statements per bal- other children like to do fun things with just a few people”)andto loon). A supplement containing all the Dutch statements can be verbally indicate how they would answer the item. This proce- requested from the corresponding author. dure was repeated, if necessary, until participants understood the structure of the items and understood what was required from Exit Interview In a random subgroup of the MBID group, an them. Before completing the questionnaire, participants were exit interview was added in which participants were instructed to ask for clarification if needed. Participants then questioned about their general comprehension of the BART completed the questionnaire, while the experimenter stayed in and about the peer manipulation. The results suggested that another part of the room to answer questions when needed. participants sufficiently comprehended the BART-related re- The RPI data of the current sample were also published in an- ward, could distinct the positive and negative risk encourage- other paper that demonstrated that adolescents with MBID were ment, and in general did not trust the feedback of the peers. able to understand the RPI (Dekkers et al. 2017). Specific questions and results can be found in Appendix 1. Raven’s Standard Progressive Matrices (Raven’sSPM) Procedure Intelligence was estimated using Raven’s SPM (Raven et al. 1988), which is a figural test using 60 items delivered in 5 sets. Schools willing to participate sent out the passive consent letters Each item consists of a series of figures following a certain to parents. Then, research assistants visited the adolescents that logical pattern in which one figure is missing, as indicated by were permitted to participate during their classes. During this an empty square. The participant was asked which figure from visit, all adolescents received general information about the test 8 options should be put in the empty square. Within each set, procedure. All tests were performed individually at school on the items became progressively more difficult. The sets in turn laptops in a separate testing room. Adolescents provided their also became progressively more difficult. The maximum score assent immediately before testing. First, participants completed is 60, higher scores indicate higher cognitive abilities. Raven’s the BART. A standardized step-by-step instruction including SPM has high internal consistency and validity (Lynn and two example items was programmed into the task and was read Irwing 2004). aloud by the research assistant. After these instructions, partic- ipants were first asked whether they had any questions. Then, Resistance to Peer Influence Scale (RPI) We used the RPI participants were told that they could receive a ticket per 100 (Steinberg & Monahan, 2009) as a self-report measure of sus- cents gained to join a raffle and were asked to choose one of ceptibility to peer influence. The RPI consists of ten items four age-appropriate potential raffle prizes worth 75 euros (por- about the ability to resist peer influences. On each item, par- table DVD player, iPod shuffle, national entertainment gift ticipants were first asked to choose the option that best card, or a general gift voucher of 75 euros) by clicking the 578 J Abnorm Child Psychol (2020) 48:573–587 corresponding picture on the screen. After this, participants effects and two- and three-way interactions with a medium completed the BART, while the experimenter stayed in another effect size (f =0.25). part of the room to answer questions when needed. After For all follow-up tests, we used Bonferroni corrected post- finishing the BART, participants received the raffle tickets. In hoc tests in SPSS. By using this correction, p values in the each participating school, therewas onewinnerofthe raffle, SPSS output are multiplied by the number of tests performed which was also told to the participants. Participants took about (IBM Support 2016). SPSS also returns the mean difference 20 min to complete the task. All adolescents were able to per- between the groups of the simple comparison, which will be form on the task. Additional instruction was provided when reported as ΔM. To be consistent, we also applied the needed during the practice trials. Second, participants received Bonferroni correction when testing simple effects. For exam- instructions on the RPI. If necessary, an example question was ple, to follow-up the interaction between MBID and BART answered together with the research assistant. Then, partici- condition by testing the effect of MBID in each of the three pants filled in the RPI individually, which took about five mi- BART conditions, we multiplied the p value by three. We nutes. Third, the Raven’s SPM was administered. In the MBID performed the Bonferroni correction for each follow-up test group, a random subgroup filled in the exit interview. At the separately. All Bonferroni corrected p-values are denoted by B 2 end, participants received raffle tickets based on the BART p . We calculated η effect sizes for ANOVA’s and Cohen’s d score and a small chocolate bar. effect sizes for t-tests (small: d= 0.2, medium: d = 0.5, large: d =0.8; Cohen 1988). Data Analysis With regard to the first hypothesis, we expected a signifi- cant main effect of BART condition with the positive and MBID was used as a categorical predictor in the analyses negative risk encouragement conditions having a higher num- because MBID is a well-defined distinct diagnostic category ber of adjusted pumps than the solo condition. With regard to (American Psychiatric Association 2013;De Beer 2016). the second hypothesis, we expected a main effect of MBID Knowledge about individual or contextual moderators of risk with the MBID group having a higher number of adjusted taking in adolescents with MBID is highly important, as it can pumps than the control group in all BART conditions. Also, guide interventions and future research for this highly preva- we expected a MBID × BART condition interaction with the lent and seriously impaired group (Simonoff et al. 2006). The MBID group especially having a higher number of adjusted control group was coded as 0 and the MBID group as 1. Age pumps than the control group in the positive and negative risk was added as covariate, as adolescents in the MBID group encouragement conditions. Third, we explored (a) the main (M =15.68, SD = 1.72) were significantly older than adoles- effect of sex and interactions including sex and (b) potential cents in the control group (M =14.91, SD =0.85; t(27.18) = differences in risk taking between the positive and the nega- 5.46, p < 0.001). The assumption of homogenous regression tive risk encouragement condition, also in interaction with lines was met as age did not interact with MBID and all other MBID and sex. Fourth, to explore the validity of the experi- independent variables (main effect age: F(7,314) = 0.88, p = mental BART peer influence conditions as a measure of sus- 0.52; age × MBID: F(4,314) = 0.19, p = 0.94; age × sex: ceptibility to peer influence, we related these BARTscores to a F(6,314) = 0.50, p = 0.81; age × BART condition: real-life indicator of susceptibility to peer influence: the RPI F(12,314) = 0.78, p = 0.68). Moreover, age had no significant score. That is, in each of the BART peer influence conditions linear, quadratic or cubic effect on risk taking, both when all (i.e. positive or negative risk encouragement condition), we BARTconditions were analyzed combined, and separately (all calculated partial correlations between RPI score and adjusted p’s > 0.05). Outliers were detected with the Median Absolute pumps while controlling for age. We did this for the whole Deviation method (MAD; Leys et al. 2013) within the MBID sample and for the MBID and control group separately. To test and sex subgroups. whether the potential relationship between RPI score and ad- To investigate the effects of MBID (present vs. absent), sex justed pumps differed between the MBID and the control (boys vs. girls), and BART condition (solo vs. positive vs. group, we performed two follow-up ANCOVA’sin each of negative) on the number of adjusted pumps in the BART, we the BART peer influence conditions. We included the main performed a 2 × 2 × 3 factorial ANCOVA. In addition to the effects of RPI and MBID, the interaction between RPI and main effects, all interactions were included in the ANCOVA: MBID, and age as covariate. When the interaction term is MBID × sex, MBID × BART condition, sex × BART condi- significant, this proves that the relation between RPI and ad- tion, and MBID × sex × BART condition. Whenever appro- justed pumps differs between the MBID and the control priate, we calculated partial eta squared effect sizes (denoted group. Outliers on the RPI score were also detected with the by η 2) which can be interpreted as small (η =0.01),medi- MAD method within the MBID and sex subgroups. p p 2 2 um (η =0.06) or large (η =0.14; Cohen 1988). An a priori p p power analysis revealed that a minimum of 158 participants The effects of MBID and sex on RPI were not examined as these analyses was sufficient to achieve a power of 0.8 and detect main were already published elsewhere (Dekkers et al. 2017). J Abnorm Child Psychol (2020) 48:573–587 Results showed that the MBID group (M =28.42, SD = 9.03) indeed had a significantly lower Raven’s SPM score than the control Preliminary Analyses group (M = 49.25, SD = 5.27; t(298.11) = 26.79, p < 0.001, d= 2.82), indicating IQ differences in the expected direction. From the 382 recruited participants, 17 participants were ex- cluded for the following reasons: the BART was not finished ANCOVA on BART Number of Adjusted Pumps (4), some trials of the BART were missing (1), the number of adjusted pumps equalled zero because none of the balloons A factorial ANCOVA with age as covariate was performed on were sold (1), Raven’s SPM scores were missing (2), Raven’s BART number of adjusted pumps (see Table 1 for means and SPM score equalled 0 (3), or RPI scores were missing (6). 13 SD’sand Fig. 2). In line with our first expectation, the ANCOVA of the 17 excluded participants belonged to the MBID group. yielded a significant main effect of BART condition: F(2,343) = Of the remaining 365 participants, eight participants had an 4.98, p=0.007, η = 0.03. Post-hoc analyses showed that the outlying score on the BART and one had an outlying score on adjusted number of pumps was significantly higher in the nega- the RPI. These nine participants were equally distributed over tive risk encouragement condition as compared to the solo con- all three predictors (4 controls / 5 MBID, 5 boys / 4 girls, 1 dition (ΔM =3.87, p =0.01, d= 0.34). However, there was no solo / 4 positive / 4 negative risk encouragement condition) significant difference in the number of adjusted pumps between and were also excluded, leaving a total sample size of 356 the positive risk encouragement condition and the solo condition. participants. Age was not a significant covariate. From 144 of the 184 MBID participants school file infor- Contrary to our second expectation, there was no main mation about DSM-IV classifications was available. This re- effect of MBID: F(1,343) = 0.50, p =0.48, η = 0.001. vealed that 25% of the adolescents in the MBID group had a However, in line with our second expectation, the interaction clinical diagnosis: Attention Deficit Hyperactivity Disorder between MBID and BART condition was significant: (ADHD; 8), Oppositional Defiant Disorder (ODD; 8), F(2,343) = 5.71, p =0.004, η = 0.03. To follow-up this in- ADHD/ODD (2), parent-child relational problem (2), parent- teraction, we performed three post-hoc t-tests to compare the child relational problem + ADHD (2), parent-child relational MBID and the control group for each BART condition sepa- problem + ODD (1), behavior disorder not otherwise specified rately. As expected, the MBID group had a significantly (1), Autism Spectrum Disorder (1), Pervasive Developmental higher number of adjusted pumps in the negative risk encour- Disorder-Not Otherwise Specified (6), attachment disorder agement condition than the control group, t(112) = 2.73, p = (2), adjustment disorder (1), dyslexia + ADHD (1), and 0.02, d = 0.51. Unexpectedly, in the positive risk encourage- parent-child relational problem + Post-Traumatic Stress ment condition this was not the case, t(111.89) = 1.46, p = Disorder (1). Overall, the majority of this group had comorbid 0.147, d= 0.27. In the solo condition, the MBID group unex- externalizing disorders (ADHD, ODD), which have been re- pectedly had a significantly lower number of adjusted pumps lated to risk taking (Dekkers et al. 2016; Pollak et al. 2019). than the control group, t(123) = −3.17, p = 0.006, d =0.57. Chi-square tests confirmed that the MBID and the control We explored the main effects and interactions of sex. Of all group were not significantly different in boy/girl ratio (60.9% effects, only the three-way interaction between MBID, BART boys in MBID group / 66.3% boys in control group, p =0.29) condition and sex was significant, F(2,343) = 4.01, p =0.02, and in the distribution over the three BART conditions (p = η = 0.02. To understand the pattern of interaction, we per- 0.48). Moreover, the three BART conditions were similar in formed two post-hoc ANCOVA’s for boys and girls separate- boy/girl ratio (68% boys in solo condition, 60.7% boys in the ly. In the model for boys, the interaction between MBID and positive risk encouragement condition, and 61.4% boys in the BART condition remained significant, F(2,219) = 13.64, p < negative risk encouragement condition, p = 0.43), distribution 0.001, η = 0.11. The ANCOVA on girls showed no signif- of age (p =0.06), RPI (p= 0.07), and Raven’s SPM scores icant effects. To follow-up this interaction in boys, we first (p =0.25). With regard to Raven’s SPM scores, Levene’stest performed three post-hoc ANCOVA’s on the effect of MBID for equality of variances revealed that the variances were un- within each BART condition. These showed that in the nega- equal. However, this is not a problem with approximately tive risk encouragement condition, boys with MBID had a equal group sizes (Bathke 2004). The assumption of homog- significantly higher number of adjusted pumps than boys in B 2 enous regression lines was met for Raven’s SPM scores as age the control group, F(1,67) = 7.20, p =0.03, η =0.10 . There did not interact with MBID, F(4,343) = 1.54, p =0.19, η = was no such significant difference in the positive risk encour- 0.02. Therefore, age was included as a covariate. An agement condition. However, in the solo condition this pattern ANCOVA showed that MBID was a significant predictor of was reversed: boys with MBID had a significantly lower num- Raven’s SPM score (F(1,353) = 617.08, p <0.001, η =0.64) ber of adjusted pumps than boys from the control group, B 2 and that age was a significant covariate (F(1,353) = 6.42, p = F(1,82) = 15.98, p <0.001, η = 0.16. Second, we per- 0.01, η = 0.02). A post-hoc t-test allowing unequal variances formed six post-hoc ANCOVA’s on the effect of condition p 580 J Abnorm Child Psychol (2020) 48:573–587 Table 1 M and SD on the number Total sample MBID Control of adjusted pumps (i.e. Risk Taking) for the total sample, the N M SD N M SD N M SD MBID group, the control group, and for boys and girls separately Solo 125 31.42 11.13 70 28.73 10.25 55 34.86 11.34 in the solo, positive and negative risk encouragement condition Positive risk encouragement 117 31.36 9.12 57 32.62 9.60 60 30.17 8.55 Negative risk encouragement 114 35.29 11.53 57 38.16 12.23 57 32.43 10.09 Total sample boys MBID boys Control boys N M SD N M SD N M SD Solo 85 31.41 11.65 45 27.15 9.88 40 36.20 11.73 Positive risk encouragement 71 31.38 9.44 34 33.46 9.41 37 29.46 9.18 Negative risk encouragement 70 35.39 11.11 33 39.54 11.48 37 31.70 9.48 Total sample girls MBID girls Control girls N M SD N M SD N M SD Solo 40 31.46 10.06 25 31.57 10.48 15 31.27 9.68 Positive risk encouragement 46 31.34 8.71 23 31.38 9.96 23 31.31 7.48 Negative risk encouragement 44 35.14 12.29 24 36.27 13.21 20 33.77 11.28 N = Number of participants, M = Mean, SD = Standard Deviation, MBID = Mild to Borderline Intellectual Disability (solo vs. positive, solo vs. negative and positive vs. negative) in the number of adjusted pumps between the negative and in the MBID and control group separately. These showed that positive risk encouragement condition. within the group of boys with MBID the number of adjusted Explorative analyses within the 144 adolescents with pumps in the negative risk encouragement condition was MBID with school file information about DSM-IV classifica- higher than in the solo condition, F(1,124) = 22.92, p < tions showed no significant main effect of comorbid external- 0.001, η = 0.16. The remaining ANCOVA’s did not show izing disorders on risk taking: F(1,131) = 0.14, p = 0.71, significant condition effects. Third, we performed six post- η =0.001, no interaction with sex: F(1,131) = 0.03, p = hoc ANCOVA’s on the effect of sex (boys vs. girls) within 0.87, η = <0.001, no interaction with BART condition: the each of the BART conditions for the control and MBID F(2,131) = 1.64, p =0.20, η = 0.02, and no three-way inter- group separately. These analyses did not show any significant action: F(2,131) = 2.33, p = 0.10, η = 0.03. Additionally, results. when the main analysis was repeated without 36 MBID ado- The exploration of risk taking in the positive risk encour- lescents with a comorbid disorder, the pattern of results was agement condition compared to risk taking in the negative risk similar (N = 320, a significant main effect of BART condition: encouragement condition showed that in the whole sample the F(2,307) = 3.59, p =0.03, η = 0.02, no main effect of MBID: number of adjusted pumps was significantly higher in the F(1,307) = 0.22, p =0.64, η = 0.001, a significant MBID by negative risk encouragement condition than in the positive BART condition interaction: F(2,307) = 4.67, p =0.01, η = risk encouragement condition (ΔM =3.93, p = 0.01, d = 0.03, and a significant three-way interaction between MBID, 0.38). In all subgroups, there were no significant differences BART condition, and sex: F(2,307) = 4.31, p = 0.01, η = Fig. 2 Mean Number of Adjusted Pumps (i.e. Risk Taking) and 95% Confidence Intervals in the MBID and Control Group for Boys and Girls Separately in the Solo, Positive and Negative Risk Encouragement Condition. Note: All significant comparisons are denoted with brackets and stars: B B ** = p <0.01, ***= p < 0.001. J Abnorm Child Psychol (2020) 48:573–587 0.03). Moreover, a highly similar pattern of results was found was related to higher risk taking compared to solo risk taking, when continuous Raven’s SPM scores were used in the main but positive risk encouragement by peers (e.g., ‘Continuing is analysis instead of MBID as categorical variable (see cool’) was not. In contrast to our second hypothesis, adoles- Appendix 2). cents with MBID did not take more risks than typically devel- oping adolescents in general, but they did take more risk when peers negatively encouraged risk taking. Third, the explora- Correlation between RPI and BART tion of (a) sex differences showed that the abovementioned effects were mainly driven by boys with MBID. In the whole sample, the correlation between the RPI score Unexpectedly, boys with MBID took less risks without peer and the number of adjusted pumps in the negative risk encour- influence than typically developing boys. The exploratory agement condition was significantly negative (r = −0.22, p = comparison of (b) positive and negative risk encouragement 0.018, see Table 2). This small to medium relation suggests showed that negative risk encouragement by peers was related that the more resistant to peer influence adolescents claim to to more risk taking than positive risk encouragement. Fourth, be, the less risks they took in the BART when peers negatively we found that that adolescents who reported more resistance encouraged risk taking. The correlation between RPI score to peer influence took less risks when peers negatively encour- and the number of adjusted pumps in the positive risk encour- aged risk taking. agement condition was also negative, but not significant. The With respect to our first hypothesis on the effect of peer correlations within the MBID and control group separately influence on risk taking, negative risk encouragement by peers were not significant. The follow-up ANCOVA’s in the nega- was related to more risk taking than no peer influence. This is tive and positive risk encouragement condition separately in line with three lines of evidence showing that social exclu- showed no significant main effects of RPI (negative: F(1, B 2 sion and peers’ negative interactional styles are related to rep- 109) = 1.76, p =0.37, η = 0.02; positive: F(1,112) = 2.01, B 2 utation management, stress causing decreased inhibition, and p =0.32, η = 0.02) and MBID (negative: F(1, 109) = 1.75, B 2 B 2 risk taking (Bjork and Pardini 2015;Blakemore 2018; p =0.38, η = 0.02; positive: F(1,112) = 0.06, p >1, η = p p Brechwald and Prinstein 2011; De Houwer and Tibboel 0.001), no significant interaction between RPI and MBID B 2 2010; Ellis et al. 2018; Gunther Moor et al. 2014; Nesdale (negative: F(1, 109) = 0.90, p = 0.69, η = 0.01; positive: B 2 and Lambert 2008). Adolescents did not demonstrate more F(1,112) = 0.19, p >1, η = 0.002), and age was not a sig- risk taking when peers positively encouraged risk taking than nificant covariate (negative: F(1, 109) = 0.50, p =0.96, 2 B 2 without peer influence. Arguably, the potential social exclu- η = 0.01; positive: F(1,112) = 0.44, p >1, η = 0.004). p p sion impression is more pronounced in negative as compared This demonstrates that the relations between the RPI and the to positive risk encouragement (cf. Nesdale and Lambert BART were not significantly different for the MBID group 2008). The differential effects of negative and positive risk and the control group. All correlations are shown in Table 2. encouragement on risk taking therefore suggest that future studies on the effects of peer influence should focus on nega- tive risk encouragement. Potential working mechanisms can Discussion be investigated by using physiological indicators of stress dur- ing the peer influence manipulation, or by assessing the need- The current study investigated the effects of MBID, sex, and to-belong as a potential mediator. type of peer encouragement on risk taking in adolescents. To With respect to our second hypothesis on the effect of this end, boys and girls with MBID were compared to typi- MBID and peer influence on risk taking, we found that al- cally developing boys and girls on an experimental risk-taking though adolescents with MBID did not take more risks than task with no, positive or negative risk encouragement by typically developing adolescents in general, they did when peers. Partly in line with our first hypothesis, negative risk peers negatively encouraged risk taking. Moreover, the effect encouragement by peers (e.g., ‘If you quit, you are a softy’) of MBID on susceptibility to peer influence was robust as it Table 2 Partial Correlations (r) between RPI score and the Number of was not driven by comorbid disorders in general or moderated BART Adjusted Pumps separately for all BART conditions in the Total by comorbid externalizing disorders specifically. The latter Sample, the MBID group and the Control Group finding matches earlier findings in adolescents with MBID (Bexkens et al. 2018), but is not in line with the fact that Total sample MBID Control decreased cognitive control, as often found in adolescents Nr N r N r with MBID (Bexkens et al. 2014), is related to more risk taking in general (e.g., Bjork and Pardini 2015). However, Positive risk encouragement 117 −0.16 57 −0.10 60 −0.18 the results specify the general views that adolescents with Negative risk encouragement 114 −0.22* 57 −0.23 57 −0.06 MBID are highly susceptible to peer influence and have low *= p <0.05 risk-awareness in peer situations (Dekkers et al. 2017; 582 J Abnorm Child Psychol (2020) 48:573–587 Greenspan et al. 2011;Khemka et al. 2009), by showing that when peers negatively encouraged risk taking. Thus, a new this is only the case when peers negatively encourage risk hypothesis could be that boys with MBID only take more risks taking. As positive risk encouragement by peers was not re- than typically developing boys in peer contexts and not when lated to more risk taking in adolescents with MBID, we con- alone. This idea suits the earlier findings of Bexkens et al. clude that the abovementioned potential mechanisms of neg- (2018) in which boys with and without MBID took the same ative risk encouragement by peers may apply more to adoles- amount of risks without peers in the solo condition, and even cents with MBID than to typically developing adolescents. more our unexpected finding of less risk taking without peer Potentially, an additional decrease in inhibition on top of the influence in boys with MBID. Future research should further already decreased cognitive control in adolescents with MBID elucidate the relation between MBID and risk taking without (Bexkens et al. 2014), could have made them take even more peer influence in both experimental settings and daily life. risks than typically developing adolescents in the same con- With regard to the second part of the third question, on the text. Nevertheless, note that the current study was performed comparison of positive and negative peer encouragement, in a MBID sample recruited at special vocational schools. It is negative risk encouragement by peers led to more risk taking possible that positive risk encouragement by peers can in- than positive risk encouragement. This is in line with earlier crease risk taking in adolescents with MBID who show pro- research comparing these two types of risk encouragement nounced deviant behavior (Dishion et al. 1999; Vitaro et al. (Nesdale and Lambert 2008). 2000). Therefore, future research in criminal justice system Finally, with regard to our fourth question on the relation settings is recommended. between the RPI and the BART, we found that lower self- With regard to the first part of the third question on poten- reported RPI was related to higher risk taking in the BART tial sex differences, boys with MBID were susceptible to neg- negative risk encouragement condition. This is in line with ative risk encouragement by peers, whereas girls with MBID earlier research in which adolescents with low RPI took more were not. This finding is in line with some research on sex risks after social exclusion than adolescents with high RPI differences in susceptibility to peer influence in typically de- (Peake et al. 2013). In contrast, a study in typically developing veloping adolescents (De Boer et al. 2017;Sumter et al. 2009; adolescents was not able to detect a correlation between self- Widman et al. 2016) and with the only study in adolescents reported RPI and risk taking in a version of the BART with with MBID known so far (Dekkers et al. 2017). Moreover, the neutral peer statements (e.g., ‘Pump more’; Cavalca et al. finding builds on earlier research in which boys with MBID 2013). As the RPI provides an indication of real-life suscepti- were more susceptible to mixed positive and negative risk- bility to peer influence, this suggests that our addition of neg- encouraging statements than typically developing boys ative risk encouragement by peers may have increased the (Bexkens et al. 2018), by showing that their susceptibility is ecological validity of the BART. limited to negative risk encouragement by peers. Thus, the Several limitations of the current study may have influ- exact effect of peer influence on risk taking seems to depend enced the results. First, as we used a between-subjects design, on specific combinations of adolescent and task characteris- we cannot claim variations in risk taking within an adolescent tics. With regard to task characteristics, our risk-taking task under different types of peer influence. Future studies are en- included explicit peer influence of same-sex peers. Potentially, couraged to incorporate a within-subjects design in which girls with MBID are be more susceptible to implicit peer in- adolescents receive at least a solo condition and a risk encour- fluences such as indirect bullying (Svahn and Evaldsson agement condition. This paradigm could be used to derive 2011) or to opposite sex peer influence related to norm scores for the peer influence effect. Deviation from this prostitution-related crime (Kuosmanen and Starke 2015). norm can then be determined for each individual. With this Nevertheless, many more variations in peer influence situa- single-participant approach, those adolescents with MBID tions exist. Therefore, we recommend future research to be most likely to engage in risk-taking behavior as a consequence aware of the complex interplay between adolescent and task of peer influence could be identified. characteristics when designing peer influence paradigms. Second, an alternative explanation for the finding that pos- Unexpectedly, boys with MBID took less risks without itive risk encouragement by peers was not related to increased peer influence than typically developing boys. This is not in risk taking could be that adolescents did not believe this ma- line with studies demonstrating that adolescents with MBID nipulation. Some adolescents in the positive risk encourage- show higher daily life risk taking than typically developing ment condition indeed showed some signs of disbelief (e.g., adolescents (Holland et al. 2002;Kaal 2016; Van Duijvenbode ‘You are kidding me, right?’). However, the same type of peer and Van der Nagel 2019). A potential explanation could be manipulation with mixed positive and negative risk encourag- that the observed high risk taking in adolescents with MBID ing statements convincingly produced increased risk taking as often occurs in peer contexts (e.g., Steinberg and Morris compared to no peer influence in Bexkens et al. (2018). 2001). This is also in line with our result that boys with Combined with our findings, this may suggest that peers MBID took more risks than typically developing adolescents who provide only negative statements or mixed statements J Abnorm Child Psychol (2020) 48:573–587 may be more credible than peers who only provide positive compared to a control training (PEER-DM, Khemka et al. statements. Unfortunately, our exit-interview was too limited 2016). Based on our results, peer-guided interventions promot- to investigate belief of the peer manipulation (see Appendix ing prosocial or healthy behavior via peers (see Stanish and 1). Future studies are encouraged to implement a more com- Temple 2012 for an illustration) could focus on decreasing neg- plete exit-interview and to use more interactive ways of ma- ative peer encouragement on desired behavior in boys with nipulating peer influence such as an online chatroom to in- MBID. Our findings suggest that negative peer encouragement crease credibility (see e.g., Weigard et al. 2014). may harm the efficacy of the intervention, but this potential Third, the age range of adolescents between 12 and 19 years effect requires empirical testing. Relatedly, peers could be used was rather broad. Age differences may have affected the out- as promotors of positive behavior. For example, recent studies comes since previous work suggests a peak in susceptibility to show that positive peer feedback on prosocial behavior in- peer influence around age 14 (Berndt 1985; Steinberg and creases this behavior in typically developing adolescents and Monahan 2007;Sumteret al. 2009). However, we did not ob- adolescents with autism (Choukas-Bradley et al. 2015;Van serve any main effects of age or interactions with age on risk Hoorn et al. 2017). Potentially, peer feedback could also be taking. Given these null findings for age, and given the fact that used in interventions to decrease risk taking, particularly ado- age is strongly correlated with pubertal status (Braams et al. lescents who are highly susceptible to peer influence could 2015), it is also unlikely that pubertal status played a role in benefit from this approach. our findings. Moreover, pubertal development is not different in The current study demonstrated the power of peer influ- adolescents with and without intellectual disability (De Graaf ence on risk taking. To return to our question: ‘When do those and Maris 2014; Nazli and Chavan 2016). Nevertheless, puber- “risk-taking adolescents” take risks?’, we now provided first tal status remains a strong predictor of risk taking in adoles- evidence that boys with MBID are “risk-taking adolescents” cence, even above and beyond age (Collado et al. 2014). Future when peers belittle or threat with exclusion from the peer studies are encouraged to study developmental and pubertal group. Although our findings require replication, we stress trends in susceptibility to peer influence, especially in MBID, that more knowledge about specific peer contexts in which by for example incorporating longitudinal designs. at-risk groups show risk taking is essential to decrease future Fourth, we did not study whether adolescents with and risk taking in adolescents. without MBID engage in different types of risk encourage- Acknowledgements The authors thank the students for their valuable ment in daily life. As adolescents with MBID are often aggre- assistance in gathering the data: Sander van Ommeren, Denise Plette, gated in special education classrooms, more deviant peer net- Lisanne van Houtum, Sabine Feith, Tijs Arbouw, Maayke Dost, Nikkita works could be formed than in regular schools (Müller 2010). Oversteegen, Nina de Ruiter, Madelon de Waal, and Imke Wojakowski. Potentially, this affects the risk encouragements that adoles- The authors further thank the schools and participants for participating. cents with and without MBID provide. Future research should study how often and what types of risk encouragement ado- Compliance with Ethical Standards lescents provide. Conflict of Interest The authors declare that they have no potential con- Fifth, the reward component of the BART could have been flict of interest. too abstract for adolescents with MBID. A total of 10 of 59 adolescents with MBID who completed the exit interview Ethical Approval All procedures performed in studies involving human indicated that they did not understand that a raffle ticket was participants were in accordance with the ethical standards of the institu- received for each 100 points in the game. Future research tional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. could include a more concrete reward such as earning actual money for each cashed balloon. Informed Consent Written active informed consent was obtained from The findings of this study emphasize that awareness of the all individual participants included in the study and written passive con- complexity of susceptibility to peer influence in MBID is cru- sent was obtained from their parents or caretakers. cial for clinical practice. Prevention and intervention programs aimed at reducing risk taking should incorporate individual and contextual factors. The current study was the first to find that Appendix 1. Exit Interview in the MBID Group especially boys with MBID take more risks when peers belittle or threaten with exclusion. If future studies replicate these find- Comprehension of the BART-Related Reward ings, interventions could be targeted or adapted to this group and context. An illustration of a suitable intervention could be a 59 participants answered the exit question ‘Was it clear for decision-making curriculum with hypothetical situations in- you that you received a raffle ticket for each 100 points in volving negative risk encouragement by peers, which was prov- the game?’. 49 respondents answered ‘yes’ and 10 participants en to successfully increase self-protective decision-making and answered ‘no’, suggesting that the majority of the MBID risk perception in adolescents with intellectual disabilities group understood the reward system. 584 J Abnorm Child Psychol (2020) 48:573–587 permission directly from the copyright holder. To view a copy of this Distinction between Positive and Negative Risk licence, visit http://creativecommons.org/licenses/by/4.0/. Encouragement 34 participants in the positive or negative risk encouragement conditions answered the exit question ‘Did you like the peers?’. 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Publisher: Springer Journals
Copyright: Copyright © The Author(s) 2020
ISSN: 0091-0627
eISSN: 1573-2835
DOI: 10.1007/s10802-020-00617-8
Publisher site: See Article on Publisher Site

Abstract

Adolescents with mild to borderline intellectual disability (MBID) show more daily life risk taking than typically developing adolescents. To obtain insight in when these “risk-taking adolescents” especially take risks, we investigated main and interaction effects of (a) MBID, (b) sex, and (c) type of peer influence on risk taking. The Balloon Analogue Risk Task (BART) was used as a proxy of real-life risk taking. 356 adolescents (12–19 years, 51.7% MBID, 63.4% boys) were randomly assigned to one of three BART peer-influence conditions: solo (no peers), positive risk encouragement (e.g., ‘You are cool if you continue’)or negative risk encouragement (e.g., ‘You are a softy if you do not continue’). The main finding was that boys with MBID took more risks than typically developing boys in the negative risk encouragement condition. Boys with MBID also took more risks in the negative risk encouragement condition compared to the solo condition, whereas typically developing boys did not. There were no such effects for girls. Surprisingly, boys with MBID took less risks in the solo condition than typically developing boys. We conclude that boys with MBID especially show high risk taking when peers belittle or threat with exclusion from the peer group. Prevention and intervention programs should specifically target boys with MBID to teach them to resist negative risk encour- agement by peers. . . . . Keywords Adolescence Risk taking Peer influence Intellectual disability Balloon Analogue Risk Task Risk-taking behavior (e.g., substance use, reckless driving, sex- ual risk taking) is the leading cause of death in adolescents (Dahl 2004; Institute of Medicine 2011) and results in high societal * Eline Wagemaker costs (Groot et al. 2007). The dual systems model or imbalance E.Wagemaker@uva.nl model provides the dominant explanation for high risk taking in adolescence by proposing an imbalance between the fast devel- oping social-emotional systems and the more gradual developing Department of Psychology, University of Amsterdam, Nieuwe Achtergracht 129b, 1018, WS Amsterdam, The Netherlands cognitive control systems in the adolescent brain (Steinberg 2010). However, not all adolescents show high risk taking, many Research Priority Area Yield, University of Amsterdam, Amsterdam, The Netherlands individual differences exist. In 2015, Bjork and Pardini published a paper centered on the question ‘Who are those “risk-taking Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands adolescents”?’. Based on their research and earlier findings, high Department of Forensic Youth Psychiatry and Behavioral Disorders, risk taking in adolescence has been related to sensation seeking, De Bascule, Academic Center of Child- and Adolescent Psychiatry, impulsivity, low cognitive control, and low educational levels Amsterdam, The Netherlands (Bjork and Pardini 2015; Harakeh et al. 2012;Jessor 1992). Mind at Work, Almere, The Netherlands These characteristics are often overly represented in adolescents Department of Clinical Psychology, Utrecht University, with mild to borderline intellectual disability (MBID; e.g., Utrecht, The Netherlands Bexkens et al., 2014). MBID is definedbyanIQbetween 50 Department of Psychology, Developmental and Educational and 85 and problems in social adaptability (De Beer 2016). The Psychology, Leiden University, Leiden, The Netherlands prevalence of MBID is about 10% (Simonoff et al. 2006). In GGZ Delfland, Delft, The Netherlands daily life, adolescents with MBID indeed show more risk taking 574 J Abnorm Child Psychol (2020) 48:573–587 than typically developing peers, and they are over-represented in virtual peers than in the version without the peers. On top of that, the criminal justice system (Holland et al. 2002; Kaal 2016;Van adolescents with MBID took more risks than typically develop- Duijvenbode and Van der Nagel 2019). However, it is unclear ing adolescents, but only in the condition with the virtual peers. whether all adolescents with MBID are risk takers and whether This study provides initial evidence that adolescents with MBID the risk-taking context matters. Therefore, the current study ex- may be more susceptible to peer influence than typically devel- amines the impact of sex and peer influences on risk taking in oping adolescents. From the perspective of the imbalance model, adolescents with and without MBID. increased susceptibility to peer influence in adolescents with Adolescence is known as a period of increased sensitivity to MBID could be explained by a larger imbalance between peer influence (Crone and Dahl 2012; Steinberg and Morris social-emotional and cognitive control systems. Although this 2001;Van Hoornetal. 2017). Indeed, the peer context is related claim has not been investigated at a neurobiological level, there to adolescent risk taking in daily life, as demonstrated by the is ample evidence that adolescents with MBID have inhibition doubled risk of fatal injuries during driving accompanied by deficits as compared to typically developing adolescents (see peers (Chen et al. 2000). Several experimental studies also Bexkens et al. 2014 for a meta-analysis; Schuiringa et al. demonstrate that the (perceived) presence of peers increases risk 2017), and inhibition is an important component of cognitive taking (De Boer and Harakeh 2017; Gardner and Steinberg control (Ridderinkhof et al. 2004). These inhibitory deficits 2005; Maclean et al. 2014;Van Hoornetal. 2017;Weigard may suggest a larger imbalance between the social-emotional et al. 2014). However, adolescents vary in their susceptibility and the cognitive control system in adolescents with MBID, to peer influence on risk taking. These individual differences which may increase their susceptibility to peer influence can be related to resistance skills, social acceptance by friends (Albertetal. 2013). Therefore, the first goal of this study is to or peer status (Allen et al. 2012; Prinstein et al. 2011;Urberg confirm that adolescents with MBID are more susceptible to peer et al. 2003). More knowledge about individual factors could influence than adolescents without MBID. help to identify specific contexts in which at-risk groups are likely to show risky behavior. With this knowledge, prevention or intervention programs could be fine-tuned. The current study Sex Differences in Susceptibility to Peer focuses on three potential factors that may affect susceptibility Influence to peer influence in a risk-taking context. First, low intellectual functioning (i.e., MBID) could increase the susceptibility to Previous research about sex differences in susceptibility to peer peer influence. Second, boys and girls could differ in their sus- influence showed mixed results. Several experimental and self- ceptibility to peer influence. Third, the type of risk encourage- report studies found that boys were more susceptible to peer ment by peers may differentially relate to risk taking. The liter- influence than girls (De Boer et al. 2017;Sumteretal. 2009; ature for each of these factors is reviewed below. Widman et al. 2016), and this pattern was similar for adoles- cents with MBID (Dekkers et al. 2017). However, other exper- imental studies demonstrated that girls are more susceptible to Susceptibility to Peer Influence in Adolescents peer influence than boys (Shepherd et al. 2011)ordid notfind with MBID any differences between boys and girls (Gardner and Steinberg 2005). Similarly, recent neurobiological studies propose a gen- Few studies have focused on susceptibility to peer influence in eral pubertal surge in testosterone in both boys and girls, which adolescents with MBID. Professionals working with this popu- increases the motivation to be admired by others, and may lation, however, often report questions on how to deal with risk therefore increase risk taking under peer influence in both boys taking related to increased susceptibility to peer influence. and girls (Braams et al. 2015; Crone and Dahl 2012). Based on Indeed, intellectual disability is characterized by lower risk- these studies, it remains unclear whether sex differences are awareness (Greenspan et al. 2011), and vignette studies suggest relevant in susceptibility to peer influence. Therefore, the sec- that adolescents with MBID especially struggle to make safe ond goal of this study is to explore sex differences in suscepti- decisions under peer influence (Khemka et al. 2009). Also, ado- bility to peer influence in adolescents with and without MBID. lescents with MBID report lower resistance to peer influence than typically developing adolescents (Dekkers et al. 2017). To our knowledge, there is only one experimental study that compared The Effect of the Type of Risk Encouragement the susceptibility to peer influence of adolescents with MBID by Peers and typically developing adolescents (Bexkens et al. 2018). In this study, boys with MBID and typically developing boys per- Peers can actively encourage risk taking in a variety of ways. In formed a risk-taking task either with or without three pictures of Bexkens et al. (2018), peers encouraged risk taking in a mixed same-sex virtual peers that gave risk encouraging feedback. Both way: some feedback had a positive tone (e.g., giving compli- groups demonstrated more risk taking in the version with the ments), whereas other feedback had a more negative tone (e.g., J Abnorm Child Psychol (2020) 48:573–587 575 belittling). Consequently, this study did not allow to test differ- encouragement by peers: positive vs. negative vs. none) ential effects of positive and negative risk encouragements on between-subjects design. To measure susceptibility to peer in- risk taking. Therefore, we tested whether these different encour- fluence, we use a risk-taking task with a virtual peer paradigm agements have differential effects by assigning adolescents to as this enables standardization of peer influence. It has been either a positive or a negative risk encouragement condition. In shown that this paradigm yields similar effect sizes as para- the positive condition peers give compliments or talk about digms with real peers (Chein et al. 2011; Festl et al. 2013; inclusion in the peer group, while in the negative condition Gardner and Steinberg 2005;O’Brien et al. 2011;Reynolds peers belittle or threat with exclusion from the peer group. et al. 2014; Weigard et al. 2014). We manipulated the type of Three lines of evidence suggest that negative risk encourage- risk encouragement during the task and propose the following ment by peers, especially in the form of threatening with social hypotheses. First, we hypothesize that all adolescents show exclusion, can increase risk taking in adolescents. First, because increased risk taking when exposed to peer influence compared forming peer relations is important in adolescence, the perception to solo risk-taking. As previous research provides limited re- of being socially rejected can lead to a process called reputation sults about whether positive or negative peer encouragement management (i.e., displaying risk taking to gain status or avoid has a stronger effect, we expect that the effect of peer condition rejection by peers; Blakemore 2018; Brechwald and Prinstein on risk taking is present for both positive and negative risk 2011;Chenetal. 2015). Second, perceived peer rejection causes encouragement by peers. Second, we hypothesize that adoles- stress in adolescents (Gunther Moor et al. 2014), which has a cents with MBID show more risk taking than typically devel- negative impact on inhibition (De Houwer and Tibboel 2010) oping adolescents, especially when exposed to peer influence. and may therefore foster risk taking (Bjork and Pardini 2015). Again, as previous research is insufficient to claim that positive This is also in line with the need-to-belong theory predicting that and negative peer encouragement have differential effects, we social exclusion leads to decreased self-regulation (Baumeister expect a similar effect of MBID on risk taking for positive and et al. 2005;DeWalletal. 2008;Stensengetal. 2015). Finally, negative peer encouragement. Third, we explore (a) the differ- longitudinal studies confirm that a negative interactional style ences between boys and girls as well as interactions between between adolescents (i.e., negative laughter and coercive state- sex, type of peer encouragement, and MBID and (b) the differ- ments) predicts adolescents’ school misconduct and risk taking ences between positive and negative peer encouragement. (Ellis et al. 2018). Fourth, we explore the validity of the risk-taking task by relat- Positive risk encouragements such as laughing or giving ing it to scores on a self-report questionnaire measuring real-life positive feedback in response to risk-taking behavior are highly susceptibility to peer influence (Cavalca et al. 2013). prevalent in deviant adolescents (Dishion et al. 1999). Arguably, positive risk encouragement by peers could increase risk taking through the same mechanisms as negative risk en- Methods couragement, although in a more indirect way. That is, adoles- cents who receive compliments from peers on risk taking may Participants get the impression that peers will not exclude them if they take risks. Thus, to avoid exclusion, these adolescents will show risk 382 adolescents between 12 and 19 years were recruited at taking in response to positive risk encouragement. secondary schools (M = 15.31, SD = 1.42, 63.4% boys). age To our knowledge, there is only one experimental study in Assignment to the MBID and the control group was based children (10 years) that compared the effects of social exclusion on school type. Adolescents from special vocational education versus inclusiononrisktaking (Nesdale andLambert 2008). schools were assigned to the MBID group. The current study This studyshowedthatchildrendemonstratedmorerisktaking took place in the Netherlands. Special education schools for after social exclusion than after social inclusion. As this study MBID and practical education schools in the Netherlands did not explicitly focus on what peers say to encourage risk have the following admittance criteria: (1) an IQ between 60 taking, the evidence on differential effects of peer encourage- and 85 tested no more than 2 years prior to admittance; and (2) ments is limited. Therefore, the third goal of this study is to learning delays of 50% or more in at least two of the following explore the effects of negative and positive risk encouragement areas: mathematics, reading accuracy and fluency, reading by adolescent peers on risk taking. comprehension, and spelling. Adolescents from Dutch We acknowledge that with the introduction of DSM-5 (American Psychiatric The Current Study Association 2013), the severity of the intellectual disability is no longer pri- marily defined by IQ, but by the severity of limitations in adaptive functioning. However, as the DSM-IV was in use when this study was conducted To disentangle the effects of MBID, sex, and risk encourage- (American Psychiatric Association 2000), the MBID assignment mainly fo- ment by peers on risk taking, we adopt a 2 (MBID: present vs. cused on IQ (borderline intellectual functioning: IQ between 70 and 85, or absent) by 2 (sex: boys vs. girls) by 3 (type of risk mild intellectual disability: IQ between 50 and 85). 576 J Abnorm Child Psychol (2020) 48:573–587 regular education secondary schools with different education- trial was then transferred to the counter above the wallet, al levels (i.e. lower and higher vocational education and pre- which was accompanied by the sound of a slot machine. university education) were assigned to the control group. To This money remained in possession of the participant and confirm that the MBID and the control group actually differed could be exchanged for raffle tickets at the end of the session in IQ score, we administered Raven’s Standard Progressive (Lejuez et al. 2003;Lejuez etal. 2002). Matrices (Raven’s SPM; Raven et al. 1988). Our adaptation based on Bexkens et al. (2018) differed Informed consent was obtained from both parents (or care- from the original procedure (Lejuez et al. 2002)inthat the takers) and adolescents. Schools sent passive consent letters to balloon could not explode on the first five pumps. The prob- parents two weeks prior to testing. Adolescents provided their ability of explosion on the sixth pump was 1/123, the proba- assent immediately before testing. It was explained to both par- bility of explosion on the seventh pump was 1/122, etc. This ents and adolescents that they could withdraw from participation probability distribution was used once to generate an explo- whenever they wanted and without consequences. The study sion point for every balloon. This array of explosion points was approved by the ethical review board of the University of wasthenusedfor allparticipants,sothere wasnointer- Amsterdam and complied with relevant laws and guidelines. participant variation in the probability of exploding. The mean point of explosion was 57.6 pumps. The number of adjusted pumps (i.e., the average number of pumps on non-explosion trials) was used as dependent variable. Materials The BART has a test-retest correlation of r =0.77 across days (White et al. 2008). Construct validity is supported by Balloon Analogue Risk Task (BART) An adaptation of the com- puterized BART (Lejuez et al. 2002, adapted from Bexkens significant relations to a range of daily life risk-taking behav- iors (Hunt et al. 2005; Lejuez et al. 2002; MacPherson et al. et al. 2018) was used to assess risk-taking. The task was pre- 2010;Mishra et al. 2010). The adjusted current version of the sented on a HP 550, 15.4-in. notebook. On each trial, partic- ipants were instructed that they could earn money by inflating BART was used successfully in adolescents with MBID be- fore (Bexkens et al. 2018). a balloon, whilst simultaneously running the risk of popping the balloon and losing the money. Participants inflated the Peer Influence Manipulation Three conditions were used: no balloon by clicking the pump (see Fig. 1). Each click inflated the balloon a little, which was depicted visually, and was peer influence (i.e., the solo condition), negative risk encour- agement by peers, and positive risk encouragement by peers. rewarded with one cent. A counter above the balloon kept track of the number of cents earned on a particular trial. These BART conditions were based on the solo and peer condition of Bexkens et al. (2018) but had one important dif- Participants risked the balloon to explode at each next click. When the balloon exploded, an explosion cartoon was pre- ference: we split the positive and negative risk encouragements sented on screen together with an explosion sound. All cents into two separate conditions. Participants were randomly assigned to one of the three BART conditions. In the solo con- earned on that trial were lost and the counter above the balloon was reset to zero. Participants were instructed that they could dition, there was no peer influence. In the negative and positive risk encouragement conditions, risk encouragement by peers decide to ‘sell’ the balloon at any point of their own preference by clicking on the picture of a wallet. Money earned on that was added visually and auditory. Three pictures of same-sex Fig. 1 Sample trial from one of the peer influence conditions (faces are blurred to ensure anonymity) J Abnorm Child Psychol (2020) 48:573–587 577 peers were displayed during each trial of the BART and audio described the group of people they belonged to (i.e., more files with risk encouraging statementswereplayedineachtrial vs. less peer resistant), and then they were asked to indicate (see Fig. 1). When an audio file played, a speech balloon ap- to what degree they feel they belong to this group (i.e., “Really peared next to one of the pictures indicating which peer was true” or “Sort of true”). Scores on each item were aggregated speaking. Participants were instructed that these peers already in a 4-point Likert-type scale score, in which the “Really true” completed the task and would give feedback based on the par- and “Sort of true” options of the less peer-resistant statement ticipants’ performance. In the positive risk encouragement con- were coded as 1 and 2 respectively, and the “Sort of true” and dition, the statements were positively formulated and/or “Really true” options of the more peer-resistant statement contained signs of inclusion (e.g., ‘Yes continue’ or ‘You belong were coded as 3 and 4 respectively. A sample item was: to us if you continue’). In the negative risk encouragement “Some children will not break the law just because their condition, the statements were negatively formulated and/or friends say that they would BUT other children would break contained signs of exclusion (e.g., ‘Continue softy’ or ‘If you the law if their friends said that they would break it”. The stop you are chicken’). A pilot study was performed on the maximum score is 40 and higher scores indicate higher resis- reliability of the risk-encouraging statements before execution tance to peer influence. The reliability of the RPI is high (α > of the study. 41 first year psychology students rated 243 state- 0.70; Steinberg and Monahan 2007) and criterion validity has ments on a 5-point positivity-negativity scale and on an been demonstrated (Monahan et al. 2009a, b; Steinberg and inclusion-exclusion scale. Both scales had high reliability (pos- Monahan 2007). itivity-negativity scale α = 0.96, inclusion-exclusion scale To make sure that participants understood the structure of the α =0.95). The 183 statements with most reliable scores were items of the RPI, the research assistants provided additional as- used in the BART. The statements were played in a random sistance. First, the research assistant read the instructions aloud. order and at semi-random moments during each trial (i.e., never Participants were then asked to read aloud the sample item on one of the first 10 pumps, always separated by more than 10 (“Some children like to do fun things with a lot of people BUT pumps, and the same maximum number of statements per bal- other children like to do fun things with just a few people”)andto loon). A supplement containing all the Dutch statements can be verbally indicate how they would answer the item. This proce- requested from the corresponding author. dure was repeated, if necessary, until participants understood the structure of the items and understood what was required from Exit Interview In a random subgroup of the MBID group, an them. Before completing the questionnaire, participants were exit interview was added in which participants were instructed to ask for clarification if needed. Participants then questioned about their general comprehension of the BART completed the questionnaire, while the experimenter stayed in and about the peer manipulation. The results suggested that another part of the room to answer questions when needed. participants sufficiently comprehended the BART-related re- The RPI data of the current sample were also published in an- ward, could distinct the positive and negative risk encourage- other paper that demonstrated that adolescents with MBID were ment, and in general did not trust the feedback of the peers. able to understand the RPI (Dekkers et al. 2017). Specific questions and results can be found in Appendix 1. Raven’s Standard Progressive Matrices (Raven’sSPM) Procedure Intelligence was estimated using Raven’s SPM (Raven et al. 1988), which is a figural test using 60 items delivered in 5 sets. Schools willing to participate sent out the passive consent letters Each item consists of a series of figures following a certain to parents. Then, research assistants visited the adolescents that logical pattern in which one figure is missing, as indicated by were permitted to participate during their classes. During this an empty square. The participant was asked which figure from visit, all adolescents received general information about the test 8 options should be put in the empty square. Within each set, procedure. All tests were performed individually at school on the items became progressively more difficult. The sets in turn laptops in a separate testing room. Adolescents provided their also became progressively more difficult. The maximum score assent immediately before testing. First, participants completed is 60, higher scores indicate higher cognitive abilities. Raven’s the BART. A standardized step-by-step instruction including SPM has high internal consistency and validity (Lynn and two example items was programmed into the task and was read Irwing 2004). aloud by the research assistant. After these instructions, partic- ipants were first asked whether they had any questions. Then, Resistance to Peer Influence Scale (RPI) We used the RPI participants were told that they could receive a ticket per 100 (Steinberg & Monahan, 2009) as a self-report measure of sus- cents gained to join a raffle and were asked to choose one of ceptibility to peer influence. The RPI consists of ten items four age-appropriate potential raffle prizes worth 75 euros (por- about the ability to resist peer influences. On each item, par- table DVD player, iPod shuffle, national entertainment gift ticipants were first asked to choose the option that best card, or a general gift voucher of 75 euros) by clicking the 578 J Abnorm Child Psychol (2020) 48:573–587 corresponding picture on the screen. After this, participants effects and two- and three-way interactions with a medium completed the BART, while the experimenter stayed in another effect size (f =0.25). part of the room to answer questions when needed. After For all follow-up tests, we used Bonferroni corrected post- finishing the BART, participants received the raffle tickets. In hoc tests in SPSS. By using this correction, p values in the each participating school, therewas onewinnerofthe raffle, SPSS output are multiplied by the number of tests performed which was also told to the participants. Participants took about (IBM Support 2016). SPSS also returns the mean difference 20 min to complete the task. All adolescents were able to per- between the groups of the simple comparison, which will be form on the task. Additional instruction was provided when reported as ΔM. To be consistent, we also applied the needed during the practice trials. Second, participants received Bonferroni correction when testing simple effects. For exam- instructions on the RPI. If necessary, an example question was ple, to follow-up the interaction between MBID and BART answered together with the research assistant. Then, partici- condition by testing the effect of MBID in each of the three pants filled in the RPI individually, which took about five mi- BART conditions, we multiplied the p value by three. We nutes. Third, the Raven’s SPM was administered. In the MBID performed the Bonferroni correction for each follow-up test group, a random subgroup filled in the exit interview. At the separately. All Bonferroni corrected p-values are denoted by B 2 end, participants received raffle tickets based on the BART p . We calculated η effect sizes for ANOVA’s and Cohen’s d score and a small chocolate bar. effect sizes for t-tests (small: d= 0.2, medium: d = 0.5, large: d =0.8; Cohen 1988). Data Analysis With regard to the first hypothesis, we expected a signifi- cant main effect of BART condition with the positive and MBID was used as a categorical predictor in the analyses negative risk encouragement conditions having a higher num- because MBID is a well-defined distinct diagnostic category ber of adjusted pumps than the solo condition. With regard to (American Psychiatric Association 2013;De Beer 2016). the second hypothesis, we expected a main effect of MBID Knowledge about individual or contextual moderators of risk with the MBID group having a higher number of adjusted taking in adolescents with MBID is highly important, as it can pumps than the control group in all BART conditions. Also, guide interventions and future research for this highly preva- we expected a MBID × BART condition interaction with the lent and seriously impaired group (Simonoff et al. 2006). The MBID group especially having a higher number of adjusted control group was coded as 0 and the MBID group as 1. Age pumps than the control group in the positive and negative risk was added as covariate, as adolescents in the MBID group encouragement conditions. Third, we explored (a) the main (M =15.68, SD = 1.72) were significantly older than adoles- effect of sex and interactions including sex and (b) potential cents in the control group (M =14.91, SD =0.85; t(27.18) = differences in risk taking between the positive and the nega- 5.46, p < 0.001). The assumption of homogenous regression tive risk encouragement condition, also in interaction with lines was met as age did not interact with MBID and all other MBID and sex. Fourth, to explore the validity of the experi- independent variables (main effect age: F(7,314) = 0.88, p = mental BART peer influence conditions as a measure of sus- 0.52; age × MBID: F(4,314) = 0.19, p = 0.94; age × sex: ceptibility to peer influence, we related these BARTscores to a F(6,314) = 0.50, p = 0.81; age × BART condition: real-life indicator of susceptibility to peer influence: the RPI F(12,314) = 0.78, p = 0.68). Moreover, age had no significant score. That is, in each of the BART peer influence conditions linear, quadratic or cubic effect on risk taking, both when all (i.e. positive or negative risk encouragement condition), we BARTconditions were analyzed combined, and separately (all calculated partial correlations between RPI score and adjusted p’s > 0.05). Outliers were detected with the Median Absolute pumps while controlling for age. We did this for the whole Deviation method (MAD; Leys et al. 2013) within the MBID sample and for the MBID and control group separately. To test and sex subgroups. whether the potential relationship between RPI score and ad- To investigate the effects of MBID (present vs. absent), sex justed pumps differed between the MBID and the control (boys vs. girls), and BART condition (solo vs. positive vs. group, we performed two follow-up ANCOVA’sin each of negative) on the number of adjusted pumps in the BART, we the BART peer influence conditions. We included the main performed a 2 × 2 × 3 factorial ANCOVA. In addition to the effects of RPI and MBID, the interaction between RPI and main effects, all interactions were included in the ANCOVA: MBID, and age as covariate. When the interaction term is MBID × sex, MBID × BART condition, sex × BART condi- significant, this proves that the relation between RPI and ad- tion, and MBID × sex × BART condition. Whenever appro- justed pumps differs between the MBID and the control priate, we calculated partial eta squared effect sizes (denoted group. Outliers on the RPI score were also detected with the by η 2) which can be interpreted as small (η =0.01),medi- MAD method within the MBID and sex subgroups. p p 2 2 um (η =0.06) or large (η =0.14; Cohen 1988). An a priori p p power analysis revealed that a minimum of 158 participants The effects of MBID and sex on RPI were not examined as these analyses was sufficient to achieve a power of 0.8 and detect main were already published elsewhere (Dekkers et al. 2017). J Abnorm Child Psychol (2020) 48:573–587 Results showed that the MBID group (M =28.42, SD = 9.03) indeed had a significantly lower Raven’s SPM score than the control Preliminary Analyses group (M = 49.25, SD = 5.27; t(298.11) = 26.79, p < 0.001, d= 2.82), indicating IQ differences in the expected direction. From the 382 recruited participants, 17 participants were ex- cluded for the following reasons: the BART was not finished ANCOVA on BART Number of Adjusted Pumps (4), some trials of the BART were missing (1), the number of adjusted pumps equalled zero because none of the balloons A factorial ANCOVA with age as covariate was performed on were sold (1), Raven’s SPM scores were missing (2), Raven’s BART number of adjusted pumps (see Table 1 for means and SPM score equalled 0 (3), or RPI scores were missing (6). 13 SD’sand Fig. 2). In line with our first expectation, the ANCOVA of the 17 excluded participants belonged to the MBID group. yielded a significant main effect of BART condition: F(2,343) = Of the remaining 365 participants, eight participants had an 4.98, p=0.007, η = 0.03. Post-hoc analyses showed that the outlying score on the BART and one had an outlying score on adjusted number of pumps was significantly higher in the nega- the RPI. These nine participants were equally distributed over tive risk encouragement condition as compared to the solo con- all three predictors (4 controls / 5 MBID, 5 boys / 4 girls, 1 dition (ΔM =3.87, p =0.01, d= 0.34). However, there was no solo / 4 positive / 4 negative risk encouragement condition) significant difference in the number of adjusted pumps between and were also excluded, leaving a total sample size of 356 the positive risk encouragement condition and the solo condition. participants. Age was not a significant covariate. From 144 of the 184 MBID participants school file infor- Contrary to our second expectation, there was no main mation about DSM-IV classifications was available. This re- effect of MBID: F(1,343) = 0.50, p =0.48, η = 0.001. vealed that 25% of the adolescents in the MBID group had a However, in line with our second expectation, the interaction clinical diagnosis: Attention Deficit Hyperactivity Disorder between MBID and BART condition was significant: (ADHD; 8), Oppositional Defiant Disorder (ODD; 8), F(2,343) = 5.71, p =0.004, η = 0.03. To follow-up this in- ADHD/ODD (2), parent-child relational problem (2), parent- teraction, we performed three post-hoc t-tests to compare the child relational problem + ADHD (2), parent-child relational MBID and the control group for each BART condition sepa- problem + ODD (1), behavior disorder not otherwise specified rately. As expected, the MBID group had a significantly (1), Autism Spectrum Disorder (1), Pervasive Developmental higher number of adjusted pumps in the negative risk encour- Disorder-Not Otherwise Specified (6), attachment disorder agement condition than the control group, t(112) = 2.73, p = (2), adjustment disorder (1), dyslexia + ADHD (1), and 0.02, d = 0.51. Unexpectedly, in the positive risk encourage- parent-child relational problem + Post-Traumatic Stress ment condition this was not the case, t(111.89) = 1.46, p = Disorder (1). Overall, the majority of this group had comorbid 0.147, d= 0.27. In the solo condition, the MBID group unex- externalizing disorders (ADHD, ODD), which have been re- pectedly had a significantly lower number of adjusted pumps lated to risk taking (Dekkers et al. 2016; Pollak et al. 2019). than the control group, t(123) = −3.17, p = 0.006, d =0.57. Chi-square tests confirmed that the MBID and the control We explored the main effects and interactions of sex. Of all group were not significantly different in boy/girl ratio (60.9% effects, only the three-way interaction between MBID, BART boys in MBID group / 66.3% boys in control group, p =0.29) condition and sex was significant, F(2,343) = 4.01, p =0.02, and in the distribution over the three BART conditions (p = η = 0.02. To understand the pattern of interaction, we per- 0.48). Moreover, the three BART conditions were similar in formed two post-hoc ANCOVA’s for boys and girls separate- boy/girl ratio (68% boys in solo condition, 60.7% boys in the ly. In the model for boys, the interaction between MBID and positive risk encouragement condition, and 61.4% boys in the BART condition remained significant, F(2,219) = 13.64, p < negative risk encouragement condition, p = 0.43), distribution 0.001, η = 0.11. The ANCOVA on girls showed no signif- of age (p =0.06), RPI (p= 0.07), and Raven’s SPM scores icant effects. To follow-up this interaction in boys, we first (p =0.25). With regard to Raven’s SPM scores, Levene’stest performed three post-hoc ANCOVA’s on the effect of MBID for equality of variances revealed that the variances were un- within each BART condition. These showed that in the nega- equal. However, this is not a problem with approximately tive risk encouragement condition, boys with MBID had a equal group sizes (Bathke 2004). The assumption of homog- significantly higher number of adjusted pumps than boys in B 2 enous regression lines was met for Raven’s SPM scores as age the control group, F(1,67) = 7.20, p =0.03, η =0.10 . There did not interact with MBID, F(4,343) = 1.54, p =0.19, η = was no such significant difference in the positive risk encour- 0.02. Therefore, age was included as a covariate. An agement condition. However, in the solo condition this pattern ANCOVA showed that MBID was a significant predictor of was reversed: boys with MBID had a significantly lower num- Raven’s SPM score (F(1,353) = 617.08, p <0.001, η =0.64) ber of adjusted pumps than boys from the control group, B 2 and that age was a significant covariate (F(1,353) = 6.42, p = F(1,82) = 15.98, p <0.001, η = 0.16. Second, we per- 0.01, η = 0.02). A post-hoc t-test allowing unequal variances formed six post-hoc ANCOVA’s on the effect of condition p 580 J Abnorm Child Psychol (2020) 48:573–587 Table 1 M and SD on the number Total sample MBID Control of adjusted pumps (i.e. Risk Taking) for the total sample, the N M SD N M SD N M SD MBID group, the control group, and for boys and girls separately Solo 125 31.42 11.13 70 28.73 10.25 55 34.86 11.34 in the solo, positive and negative risk encouragement condition Positive risk encouragement 117 31.36 9.12 57 32.62 9.60 60 30.17 8.55 Negative risk encouragement 114 35.29 11.53 57 38.16 12.23 57 32.43 10.09 Total sample boys MBID boys Control boys N M SD N M SD N M SD Solo 85 31.41 11.65 45 27.15 9.88 40 36.20 11.73 Positive risk encouragement 71 31.38 9.44 34 33.46 9.41 37 29.46 9.18 Negative risk encouragement 70 35.39 11.11 33 39.54 11.48 37 31.70 9.48 Total sample girls MBID girls Control girls N M SD N M SD N M SD Solo 40 31.46 10.06 25 31.57 10.48 15 31.27 9.68 Positive risk encouragement 46 31.34 8.71 23 31.38 9.96 23 31.31 7.48 Negative risk encouragement 44 35.14 12.29 24 36.27 13.21 20 33.77 11.28 N = Number of participants, M = Mean, SD = Standard Deviation, MBID = Mild to Borderline Intellectual Disability (solo vs. positive, solo vs. negative and positive vs. negative) in the number of adjusted pumps between the negative and in the MBID and control group separately. These showed that positive risk encouragement condition. within the group of boys with MBID the number of adjusted Explorative analyses within the 144 adolescents with pumps in the negative risk encouragement condition was MBID with school file information about DSM-IV classifica- higher than in the solo condition, F(1,124) = 22.92, p < tions showed no significant main effect of comorbid external- 0.001, η = 0.16. The remaining ANCOVA’s did not show izing disorders on risk taking: F(1,131) = 0.14, p = 0.71, significant condition effects. Third, we performed six post- η =0.001, no interaction with sex: F(1,131) = 0.03, p = hoc ANCOVA’s on the effect of sex (boys vs. girls) within 0.87, η = <0.001, no interaction with BART condition: the each of the BART conditions for the control and MBID F(2,131) = 1.64, p =0.20, η = 0.02, and no three-way inter- group separately. These analyses did not show any significant action: F(2,131) = 2.33, p = 0.10, η = 0.03. Additionally, results. when the main analysis was repeated without 36 MBID ado- The exploration of risk taking in the positive risk encour- lescents with a comorbid disorder, the pattern of results was agement condition compared to risk taking in the negative risk similar (N = 320, a significant main effect of BART condition: encouragement condition showed that in the whole sample the F(2,307) = 3.59, p =0.03, η = 0.02, no main effect of MBID: number of adjusted pumps was significantly higher in the F(1,307) = 0.22, p =0.64, η = 0.001, a significant MBID by negative risk encouragement condition than in the positive BART condition interaction: F(2,307) = 4.67, p =0.01, η = risk encouragement condition (ΔM =3.93, p = 0.01, d = 0.03, and a significant three-way interaction between MBID, 0.38). In all subgroups, there were no significant differences BART condition, and sex: F(2,307) = 4.31, p = 0.01, η = Fig. 2 Mean Number of Adjusted Pumps (i.e. Risk Taking) and 95% Confidence Intervals in the MBID and Control Group for Boys and Girls Separately in the Solo, Positive and Negative Risk Encouragement Condition. Note: All significant comparisons are denoted with brackets and stars: B B ** = p <0.01, ***= p < 0.001. J Abnorm Child Psychol (2020) 48:573–587 0.03). Moreover, a highly similar pattern of results was found was related to higher risk taking compared to solo risk taking, when continuous Raven’s SPM scores were used in the main but positive risk encouragement by peers (e.g., ‘Continuing is analysis instead of MBID as categorical variable (see cool’) was not. In contrast to our second hypothesis, adoles- Appendix 2). cents with MBID did not take more risks than typically devel- oping adolescents in general, but they did take more risk when peers negatively encouraged risk taking. Third, the explora- Correlation between RPI and BART tion of (a) sex differences showed that the abovementioned effects were mainly driven by boys with MBID. In the whole sample, the correlation between the RPI score Unexpectedly, boys with MBID took less risks without peer and the number of adjusted pumps in the negative risk encour- influence than typically developing boys. The exploratory agement condition was significantly negative (r = −0.22, p = comparison of (b) positive and negative risk encouragement 0.018, see Table 2). This small to medium relation suggests showed that negative risk encouragement by peers was related that the more resistant to peer influence adolescents claim to to more risk taking than positive risk encouragement. Fourth, be, the less risks they took in the BART when peers negatively we found that that adolescents who reported more resistance encouraged risk taking. The correlation between RPI score to peer influence took less risks when peers negatively encour- and the number of adjusted pumps in the positive risk encour- aged risk taking. agement condition was also negative, but not significant. The With respect to our first hypothesis on the effect of peer correlations within the MBID and control group separately influence on risk taking, negative risk encouragement by peers were not significant. The follow-up ANCOVA’s in the nega- was related to more risk taking than no peer influence. This is tive and positive risk encouragement condition separately in line with three lines of evidence showing that social exclu- showed no significant main effects of RPI (negative: F(1, B 2 sion and peers’ negative interactional styles are related to rep- 109) = 1.76, p =0.37, η = 0.02; positive: F(1,112) = 2.01, B 2 utation management, stress causing decreased inhibition, and p =0.32, η = 0.02) and MBID (negative: F(1, 109) = 1.75, B 2 B 2 risk taking (Bjork and Pardini 2015;Blakemore 2018; p =0.38, η = 0.02; positive: F(1,112) = 0.06, p >1, η = p p Brechwald and Prinstein 2011; De Houwer and Tibboel 0.001), no significant interaction between RPI and MBID B 2 2010; Ellis et al. 2018; Gunther Moor et al. 2014; Nesdale (negative: F(1, 109) = 0.90, p = 0.69, η = 0.01; positive: B 2 and Lambert 2008). Adolescents did not demonstrate more F(1,112) = 0.19, p >1, η = 0.002), and age was not a sig- risk taking when peers positively encouraged risk taking than nificant covariate (negative: F(1, 109) = 0.50, p =0.96, 2 B 2 without peer influence. Arguably, the potential social exclu- η = 0.01; positive: F(1,112) = 0.44, p >1, η = 0.004). p p sion impression is more pronounced in negative as compared This demonstrates that the relations between the RPI and the to positive risk encouragement (cf. Nesdale and Lambert BART were not significantly different for the MBID group 2008). The differential effects of negative and positive risk and the control group. All correlations are shown in Table 2. encouragement on risk taking therefore suggest that future studies on the effects of peer influence should focus on nega- tive risk encouragement. Potential working mechanisms can Discussion be investigated by using physiological indicators of stress dur- ing the peer influence manipulation, or by assessing the need- The current study investigated the effects of MBID, sex, and to-belong as a potential mediator. type of peer encouragement on risk taking in adolescents. To With respect to our second hypothesis on the effect of this end, boys and girls with MBID were compared to typi- MBID and peer influence on risk taking, we found that al- cally developing boys and girls on an experimental risk-taking though adolescents with MBID did not take more risks than task with no, positive or negative risk encouragement by typically developing adolescents in general, they did when peers. Partly in line with our first hypothesis, negative risk peers negatively encouraged risk taking. Moreover, the effect encouragement by peers (e.g., ‘If you quit, you are a softy’) of MBID on susceptibility to peer influence was robust as it Table 2 Partial Correlations (r) between RPI score and the Number of was not driven by comorbid disorders in general or moderated BART Adjusted Pumps separately for all BART conditions in the Total by comorbid externalizing disorders specifically. The latter Sample, the MBID group and the Control Group finding matches earlier findings in adolescents with MBID (Bexkens et al. 2018), but is not in line with the fact that Total sample MBID Control decreased cognitive control, as often found in adolescents Nr N r N r with MBID (Bexkens et al. 2014), is related to more risk taking in general (e.g., Bjork and Pardini 2015). However, Positive risk encouragement 117 −0.16 57 −0.10 60 −0.18 the results specify the general views that adolescents with Negative risk encouragement 114 −0.22* 57 −0.23 57 −0.06 MBID are highly susceptible to peer influence and have low *= p <0.05 risk-awareness in peer situations (Dekkers et al. 2017; 582 J Abnorm Child Psychol (2020) 48:573–587 Greenspan et al. 2011;Khemka et al. 2009), by showing that when peers negatively encouraged risk taking. Thus, a new this is only the case when peers negatively encourage risk hypothesis could be that boys with MBID only take more risks taking. As positive risk encouragement by peers was not re- than typically developing boys in peer contexts and not when lated to more risk taking in adolescents with MBID, we con- alone. This idea suits the earlier findings of Bexkens et al. clude that the abovementioned potential mechanisms of neg- (2018) in which boys with and without MBID took the same ative risk encouragement by peers may apply more to adoles- amount of risks without peers in the solo condition, and even cents with MBID than to typically developing adolescents. more our unexpected finding of less risk taking without peer Potentially, an additional decrease in inhibition on top of the influence in boys with MBID. Future research should further already decreased cognitive control in adolescents with MBID elucidate the relation between MBID and risk taking without (Bexkens et al. 2014), could have made them take even more peer influence in both experimental settings and daily life. risks than typically developing adolescents in the same con- With regard to the second part of the third question, on the text. Nevertheless, note that the current study was performed comparison of positive and negative peer encouragement, in a MBID sample recruited at special vocational schools. It is negative risk encouragement by peers led to more risk taking possible that positive risk encouragement by peers can in- than positive risk encouragement. This is in line with earlier crease risk taking in adolescents with MBID who show pro- research comparing these two types of risk encouragement nounced deviant behavior (Dishion et al. 1999; Vitaro et al. (Nesdale and Lambert 2008). 2000). Therefore, future research in criminal justice system Finally, with regard to our fourth question on the relation settings is recommended. between the RPI and the BART, we found that lower self- With regard to the first part of the third question on poten- reported RPI was related to higher risk taking in the BART tial sex differences, boys with MBID were susceptible to neg- negative risk encouragement condition. This is in line with ative risk encouragement by peers, whereas girls with MBID earlier research in which adolescents with low RPI took more were not. This finding is in line with some research on sex risks after social exclusion than adolescents with high RPI differences in susceptibility to peer influence in typically de- (Peake et al. 2013). In contrast, a study in typically developing veloping adolescents (De Boer et al. 2017;Sumter et al. 2009; adolescents was not able to detect a correlation between self- Widman et al. 2016) and with the only study in adolescents reported RPI and risk taking in a version of the BART with with MBID known so far (Dekkers et al. 2017). Moreover, the neutral peer statements (e.g., ‘Pump more’; Cavalca et al. finding builds on earlier research in which boys with MBID 2013). As the RPI provides an indication of real-life suscepti- were more susceptible to mixed positive and negative risk- bility to peer influence, this suggests that our addition of neg- encouraging statements than typically developing boys ative risk encouragement by peers may have increased the (Bexkens et al. 2018), by showing that their susceptibility is ecological validity of the BART. limited to negative risk encouragement by peers. Thus, the Several limitations of the current study may have influ- exact effect of peer influence on risk taking seems to depend enced the results. First, as we used a between-subjects design, on specific combinations of adolescent and task characteris- we cannot claim variations in risk taking within an adolescent tics. With regard to task characteristics, our risk-taking task under different types of peer influence. Future studies are en- included explicit peer influence of same-sex peers. Potentially, couraged to incorporate a within-subjects design in which girls with MBID are be more susceptible to implicit peer in- adolescents receive at least a solo condition and a risk encour- fluences such as indirect bullying (Svahn and Evaldsson agement condition. This paradigm could be used to derive 2011) or to opposite sex peer influence related to norm scores for the peer influence effect. Deviation from this prostitution-related crime (Kuosmanen and Starke 2015). norm can then be determined for each individual. With this Nevertheless, many more variations in peer influence situa- single-participant approach, those adolescents with MBID tions exist. Therefore, we recommend future research to be most likely to engage in risk-taking behavior as a consequence aware of the complex interplay between adolescent and task of peer influence could be identified. characteristics when designing peer influence paradigms. Second, an alternative explanation for the finding that pos- Unexpectedly, boys with MBID took less risks without itive risk encouragement by peers was not related to increased peer influence than typically developing boys. This is not in risk taking could be that adolescents did not believe this ma- line with studies demonstrating that adolescents with MBID nipulation. Some adolescents in the positive risk encourage- show higher daily life risk taking than typically developing ment condition indeed showed some signs of disbelief (e.g., adolescents (Holland et al. 2002;Kaal 2016; Van Duijvenbode ‘You are kidding me, right?’). However, the same type of peer and Van der Nagel 2019). A potential explanation could be manipulation with mixed positive and negative risk encourag- that the observed high risk taking in adolescents with MBID ing statements convincingly produced increased risk taking as often occurs in peer contexts (e.g., Steinberg and Morris compared to no peer influence in Bexkens et al. (2018). 2001). This is also in line with our result that boys with Combined with our findings, this may suggest that peers MBID took more risks than typically developing adolescents who provide only negative statements or mixed statements J Abnorm Child Psychol (2020) 48:573–587 may be more credible than peers who only provide positive compared to a control training (PEER-DM, Khemka et al. statements. Unfortunately, our exit-interview was too limited 2016). Based on our results, peer-guided interventions promot- to investigate belief of the peer manipulation (see Appendix ing prosocial or healthy behavior via peers (see Stanish and 1). Future studies are encouraged to implement a more com- Temple 2012 for an illustration) could focus on decreasing neg- plete exit-interview and to use more interactive ways of ma- ative peer encouragement on desired behavior in boys with nipulating peer influence such as an online chatroom to in- MBID. Our findings suggest that negative peer encouragement crease credibility (see e.g., Weigard et al. 2014). may harm the efficacy of the intervention, but this potential Third, the age range of adolescents between 12 and 19 years effect requires empirical testing. Relatedly, peers could be used was rather broad. Age differences may have affected the out- as promotors of positive behavior. For example, recent studies comes since previous work suggests a peak in susceptibility to show that positive peer feedback on prosocial behavior in- peer influence around age 14 (Berndt 1985; Steinberg and creases this behavior in typically developing adolescents and Monahan 2007;Sumteret al. 2009). However, we did not ob- adolescents with autism (Choukas-Bradley et al. 2015;Van serve any main effects of age or interactions with age on risk Hoorn et al. 2017). Potentially, peer feedback could also be taking. Given these null findings for age, and given the fact that used in interventions to decrease risk taking, particularly ado- age is strongly correlated with pubertal status (Braams et al. lescents who are highly susceptible to peer influence could 2015), it is also unlikely that pubertal status played a role in benefit from this approach. our findings. Moreover, pubertal development is not different in The current study demonstrated the power of peer influ- adolescents with and without intellectual disability (De Graaf ence on risk taking. To return to our question: ‘When do those and Maris 2014; Nazli and Chavan 2016). Nevertheless, puber- “risk-taking adolescents” take risks?’, we now provided first tal status remains a strong predictor of risk taking in adoles- evidence that boys with MBID are “risk-taking adolescents” cence, even above and beyond age (Collado et al. 2014). Future when peers belittle or threat with exclusion from the peer studies are encouraged to study developmental and pubertal group. Although our findings require replication, we stress trends in susceptibility to peer influence, especially in MBID, that more knowledge about specific peer contexts in which by for example incorporating longitudinal designs. at-risk groups show risk taking is essential to decrease future Fourth, we did not study whether adolescents with and risk taking in adolescents. without MBID engage in different types of risk encourage- Acknowledgements The authors thank the students for their valuable ment in daily life. As adolescents with MBID are often aggre- assistance in gathering the data: Sander van Ommeren, Denise Plette, gated in special education classrooms, more deviant peer net- Lisanne van Houtum, Sabine Feith, Tijs Arbouw, Maayke Dost, Nikkita works could be formed than in regular schools (Müller 2010). Oversteegen, Nina de Ruiter, Madelon de Waal, and Imke Wojakowski. Potentially, this affects the risk encouragements that adoles- The authors further thank the schools and participants for participating. cents with and without MBID provide. Future research should study how often and what types of risk encouragement ado- Compliance with Ethical Standards lescents provide. Conflict of Interest The authors declare that they have no potential con- Fifth, the reward component of the BART could have been flict of interest. too abstract for adolescents with MBID. A total of 10 of 59 adolescents with MBID who completed the exit interview Ethical Approval All procedures performed in studies involving human indicated that they did not understand that a raffle ticket was participants were in accordance with the ethical standards of the institu- received for each 100 points in the game. Future research tional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. could include a more concrete reward such as earning actual money for each cashed balloon. Informed Consent Written active informed consent was obtained from The findings of this study emphasize that awareness of the all individual participants included in the study and written passive con- complexity of susceptibility to peer influence in MBID is cru- sent was obtained from their parents or caretakers. cial for clinical practice. Prevention and intervention programs aimed at reducing risk taking should incorporate individual and contextual factors. The current study was the first to find that Appendix 1. Exit Interview in the MBID Group especially boys with MBID take more risks when peers belittle or threaten with exclusion. If future studies replicate these find- Comprehension of the BART-Related Reward ings, interventions could be targeted or adapted to this group and context. An illustration of a suitable intervention could be a 59 participants answered the exit question ‘Was it clear for decision-making curriculum with hypothetical situations in- you that you received a raffle ticket for each 100 points in volving negative risk encouragement by peers, which was prov- the game?’. 49 respondents answered ‘yes’ and 10 participants en to successfully increase self-protective decision-making and answered ‘no’, suggesting that the majority of the MBID risk perception in adolescents with intellectual disabilities group understood the reward system. 584 J Abnorm Child Psychol (2020) 48:573–587 permission directly from the copyright holder. To view a copy of this Distinction between Positive and Negative Risk licence, visit http://creativecommons.org/licenses/by/4.0/. Encouragement 34 participants in the positive or negative risk encouragement conditions answered the exit question ‘Did you like the peers?’. 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Effects of anonymous peer observation on adolescents’ preference Publisher’sNote Springer Nature remains neutral with regard to juris- for immediate rewards. Developmental Science, 17(1), 71–78. dictional claims in published maps and institutional affiliations. https://doi.org/10.1111/desc.12099.

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When Do those “Risk-Taking Adolescents” Take Risks? The Combined Effects of Risk Encouragement by Peers, Mild-to-Borderline Intellectual Disability and Sex

When Do those “Risk-Taking Adolescents” Take Risks? The Combined Effects of Risk Encouragement by Peers, Mild-to-Borderline Intellectual Disability and Sex

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When Do those “Risk-Taking Adolescents” Take Risks? The Combined Effects of Risk Encouragement by Peers, Mild-to-Borderline Intellectual Disability and Sex

When Do those “Risk-Taking Adolescents” Take Risks? The Combined Effects of Risk Encouragement by Peers, Mild-to-Borderline Intellectual Disability and Sex

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