Graduate School of Psychology
RESEARCH MASTER’S PSYCHOLOGY INTERNSHIP REPORT
Behavioral Adaptations To Changing Strategies In Predator-Prey Interactions Alessandro Santoro
Student ID: 10865136 Supervisor: Carsten De Dreu Daily Supervisor: Michael Giffin
Abstract
The current research is a replication of a study by De Dreu (2015, unpublished), and investigated the relationship between basal cortisol levels and decision making in the predator-prey game, a game which represents a situation in which two parties have asymmetric control over a situation. The structure of the game allows to look at the relationship between cortisol and correspondent behavior in these two different roles: the predator, who invests for greed in order to steal money from the prey, and the prey, who invests for fear, to defend from the predator’s attacks. Furthermore, we investigated the effect of changing opponent’s strategies (soft/tough) on the decisions made in the two roles. Due to time constraints, the report only analyzed behavioral data, while the hormonal data was stored and will be analyzed in the future. The results of the behavioral data confirmed those observed in the original study by De Dreu (2015, unpublished): compared with predators, preys invested more overall, more often, were more impulsive, and adapted more to changes in their opponents’ strategies. The results will be then discussed, together with the limitations of the present study and suggestions for future research.
Introduction
Competitive and cooperative behavior has been the focus of extensive research in psychology. This is indeed a subject of great importance, since in most of our lives we face situations that intertwine our decisions with the lives of other people. It is rare that a decision we take has no repercussion on the world around us, especially in the globalized society where we live, where the bigger problems we are now facing, such as global warming or pollution, can only be tackled through collective action (as it happens in politics or in top-level management teams). For this reason, it is a priority to understand the way people approach these kind of decisions, defined as social dilemmas, in order to reach optimal levels in the decision making process. To do this, researchers in this field often employ games that portray a variety of social dilemmas (for a review, see Stallen & Sanfey, 2013). These games are powerful experimental tools because they represent only certain essential features of a social situation. This way researchers can examine particular characteristics of an interaction while controlling for other factors that would otherwise affect the
outcome.
Collective decisions are rarely balanced in terms of individual control over the situation. This imbalance of power is of particular interest if we consider that most competitive situations in real life are indeed asymmetric: it is rare to see an interaction where the two (or more) parties have an equal influence on the final outcome. An example for this could be the case in which the opposition party in a parliament is trying to pass a motion, but the coalition party opposes it. In the subsequent vote, there will be an
imbalance in the roles: while the coalition will need a strict majority to pass this motion, for the opposition even a tie is enough not to pass it.
The aim of the current study is thus to investigate patterns of competitive behavior in asymmetric interactions, and to do so, it will use a newly developed game, the predator-prey game (De Dreu, Scholte, van Winden, & Ridderinkhof, 2014). The two roles in this game model create an asymmetry of power that drives individuals to act for different motives: one invests in “predation” to get the prey’s endowment (hence a greed-driven investment), while the other invest in "prey-defense” to defend from the predator’s attacks (hence a fear-driven investment). The predator-prey game will be thoroughly described in the Materials section.
Although specific patterns of competitive behavior have been observed in different social
dilemmas, research on asymmetric games has generated mixed findings. There is contrasting evidence on whether, in a competitive situation, the advantaged party will be more competitive (Bornstein, Kugler, & Zamir, 2005), or the disadvantaged party will be the one that competes more (Halevy, Chou, Cohen, & Bornstein, 2010). Furthermore, little is known about this type of predator-prey interactions, and the aim of
the present study is therefore to use the predator-prey game to explore this type of situations, and specifically their behavioral and hormonal underpinnings.
Behavioral dynamics
In a recent study, De Dreu and his colleagues (2014) used neuroimaging to observe cortical activation in the predator-prey game. Their results showed that prey behavior was indeed faster, fear-driven, and modulated by the amygdala, which is widely associated with fear and processing of threatening stimuli (see Marek, Strobel, Bredy, & Sah, 2013; Duvarci & Pare, 2014); on the other hand, predators behavior was slower, more controlled, and modulated by the superior frontal gyrus (SFG). They also observed that the prey invests more compared to the predator, and this is in line with the idea that while the predator can afford unsuccessful predation, preys have to successfully defend themselves each time from the attacks of the predator. This line of thought leads to a new hypothesis for the current study: preys, compared to predators, will be more attentive and sensitive to changes in the pattern of attacks of the predator. Preys will tend to adapt more, so that they will respond more to changes in the investment strategies of predators, as opposed to predators, who will not be as much affected by differences in the patterns of investments of the preys.
Hormonal components
For decades, cortisol has been the subject of extensive investigation. Early research pointed out the relation between cortisol and stress in the animal kingdom (e.g. Barton & Peter, 1982; Schreck & Lorz, 1978), which then led to use cortisol as an biomarker of stress in a variety of human studies (e.g. Klein, Karaskov, Stevens, Yamada, & Koren, 2004). This link between cortisol and stress, together with the folk belief that stress clouds decision making, influenced research for many years, which mainly focused on the negative aspects of cortisol. For instance, high cortisol responses subsequent to a stressor have been associated with decreased attention (Bohnen, Houx, Nicolson, & Jolles, 1990) and (age-specific)
deactivation of brain areas (Keulers, Stiers, Nicolson, & Jolles, 2015). These findings have led to the belief that high cortisol levels have a variety of negative effects. However, the research in this field has often produced mixed findings according to the different interpretations that the experimenters gave to the results, and also often has failed to separate the specific effects of stress and the ones of cortisol. Indeed, there is an increasing body of evidence pointing out the positive potentials of cortisol. For instance, higher cortisol levels are naturally found in dominant wild chimps (Muller & Wrangham, 2004) and elevated cortisol levels correlate with more accurate decision making in a variety of settings (see Van den Bos, Harteveld, & Stoop, 2009; Chumbley et al., 2014; Van Honk, Schutter, Hermans, & Putman, 2003).
A recent study by De Dreu (2015, unpublished) offers additional support for the view that higher cortisol levels are linked with improved, rather than disrupted, decision making. In this study, individuals with higher basal cortisol levels made more controlled and rational investments while surviving more often in the predator-prey game. The current study will thus investigate whether cortisol, besides being an indicator of stress, can also positively correlate with better decision making, as it causes an elevated alertness that can be an important advantage. Finally, there is evidence suggesting that naturally occurring elevated cortisol can improve learning in the animal kingdom (Mateo, 2008); although this finding is far from being conclusive, we also decided to investigate the possibility of cortisol as an adaptive mechanism in humans. Accordingly, we aim to investigate whether adapting one’s own strategy in response to a changing opponent’s strategy is correlated with basal cortisol levels.
Overview of the current study
This study will thus be a replication of the study by De Dreu (2015, unpublished), using the predator-prey game to address the problem of contrasting findings in the past. We aim to replicate the results observed in the original study, which together with the literature discussed lead to a set of specific hypotheses:
1) Preys will invest more (1a), and more often (1b), than predators; 2) Preys’ investments decisions will be faster than those of predators;
3) Preys will be more responsive to changes in predator strategies than predators will be to changes in prey strategies.
4) High basal cortisol will correlate with more accurate responses, with individuals with high basal cortisol levels making less investments over a threshold representative of rational thinking;
furthermore, this will be stronger in preys than predators, as in the original study by De Dreu (2015, unpublished);
5) People with higher basal cortisol levels will be better in adjusting their investments in response to shifts in their opponents’ strategies.1
Methods Design
The study had a 2 (role: predator/prey) x 2 (order: opponent strategy changes from tough to soft / from soft to though) x 2 (opponent strategy: soft/tough) design, with the first two factors between-participants and the last factor within-between-participants. The first independent variable was the role the
1 Due to time constrains given by the nature of the project, it was not possible to analyze on time the hormonal data
collected. Furthermore, the questionnaires data has been stored but will not be used in the analyses as it is beyond the scope of this report. The rest of this report will therefore focus on the behavioral measures used in the study.
participant played, which could either be predator or prey. The second independent variable was the order condition, indicating the order of the opponent’s patterns of investments, which could either be low-high or high-low. In the low-high condition, participants invested against an opponent which played the first half randomly drawing from a pool of low investments, and the second half randomly drawing from a pool of high investments; in the high-low condition this order was reversed, with the computer drawing from the high investments pool first and the low investments pool second. The participants were assigned randomly to the each condition before the beginning of the experiment.
The dependent variables were of two types, hormonal and behavioral. The hormonal (cortisol and testosterone) levels were measured through saliva samples twice, at the beginning and at the end of the investment task. The behavioral measures were the participant’s investments and reaction times; these outcomes were automatically recorded by the software used. Furthermore, frequency and force of
aggression were computed and analyzed in the same way as in the study by De Dreu and colleagues (2014). Participants
51 male participants (M = 23.24 years) were recruited in Amsterdam for a study on economic decision making through an online recruiting system and social networks. They were offered a monetary reward of 10€ for participating, with the chance to win up to 10€ more according to their decisions. The inclusion criteria were the following: only men, up to 35 years old, non-smokers, not on medications for mental disorders (antidepressants, anti-anxiety, or other such medications). These inclusion criteria were necessary because hormonal levels are the most stable in this sample (see Kirchbaum & Hellhammer 1994; Kirschbaum, Kudielka, Gaab, Schommer, & Hellhammer, 1999). For the same reason, participants were also asked not to drink alcohol for the 24 hours prior the study, and for the 2 hours prior the study, avoid to: eat food, drink coffee (or any other beverage except water), brush their teeth, and smoke cigarettes. The experiment was approved by the Psychology Ethics Committee of the University of Amsterdam, and participants provided written informed consent prior to the start of the experiment.
Materials
The materials included in the study include the predator-prey game and several questionnaires, which will be described in turn. Furthermore, sterilized plastic vials were used to store the saliva samples.
Predator-prey game. In the predator-prey game there are two possible roles: the predator and the prey. Participants in both roles start each trial with a fictitious amount of money (10 in our case), and then decide how much to invest from that amount. If the amount invested by the predator is larger than the one invested by the prey, the predator wins the trial and gets all the money that was not invested (by both the predator and the prey). If the amount invested by the predator is equal to or smaller than the one invested
by the prey, then each player wins the money they did not invest. Participants played this game on a computer through a software specifically developed for this purpose.
Questionnaires. All the questionnaires used in the study are reported in the Appendix. They included: briefing on the study (Appendix A); informed consent form (Appendix B); information on the participant’s behavior of the day (Appendix C); participant’s general, medical and lifestyle information (Appendix D); pre-test PANAS questionnaire (Appendix E); post-test impressions and PANAS questionnaire (Appendix F); self-assessment questionnaire (Appendix G); social value orientation questionnaire (Appendix H); debriefing on the study (Appendix I).
Procedure
The experiment took place in the university labs between 11:00 and 18:00, to avoid that
fluctuations in the hormonal levels would confound the results (see Granger, Shirtcliff, Booth, Kivlighan, & Schwartz, 2004). Upon arrival, participants were welcomed and they started filling up the first set of forms and questionnaires, namely: briefing, consent form, information on the participant’s behavior of the day, participant’s general, medical and lifestyle information, pre-test PANAS questionnaire, self-assessment questionnaire, and the social value orientation questionnaire; this was also done in order to stabilize the participant’s hormonal levels. After completing these forms, the first sample of saliva was collected from the participant, and stored vertically in a freezer. At this point, the participant would take part in the predator-prey game. The software started by presenting the instructions of the game along with some questions to check if the participants properly understood the game and its roles; the software used neutral labeling, without mentioning the predator and prey roles (but rather describing them as “Role A” and “Role B”). After reading the instructions and answering correctly all the questions, the actual game started.
The role condition determined which role the participants played, which was the same throughout the game, whereas the order condition determined their opponents’ pattern of investments. There were two distributions of possible investments, low (ranging from 0 to 5) and high (ranging from 5 to 10); in the low-high condition, the first 30 trials were drawn from the low distribution, and the last 30 trials were drawn from the high distribution; this order was reversed in the high-low condition. However, participants were told that their opponent’s investments would be drawn at random from a pool of investments previously made by other players. In each trial, participants had to choose from the screen how much to invest (from 0 to 10), after which they would see their opponent’s investment, and their reward for that trial. The trials were divided in2 blocks of 30, with the possibility of a break in between the blocks, for a total of 60 trials.
At the end of the decision making task the second saliva sample was collected from the participants and stored in the freezer. Finally, the participants had to fill in the second set of questionnaires: the post-test impressions and PANAS questionnaire, and the self-assessment questionnaire; the debriefing was also given along with these questionnaires. After completing all the questionnaires, participants were thanked for their participation and also had the chance to give feedback on the study.
Results Player’s investments
A two-way ANOVA was conducted to look at differences in investments between conditions. The analysis revealed that there was a statistically significant difference between roles (predator/prey) (F(1,46) = 5.15, p = .028), opponent strategy (soft/tough) (F(1,46) = 39.42, p < .001), and a significant interaction between role and strategy (F(1,46) = 32.14, p < .001). To further investigate the interaction between roles and strategies, four t-tests were conducted between each levels of roles and opponent strategy, using Bonferroni adjusted Alpha levels of .0125 per test (.05/4).
First, two paired-sample t-tests were conducted to look at differences in investments between tough and soft strategies, in both the predator and the prey roles. The analysis showed a significant
difference between tough (M = 6.44, SE = 0.41) and soft (M = 4.6, SE = 0.34) strategies in the prey condition (t(24) = 9.11, p < .001), but no differences in the predator condition (t(24) = 0.46, p = .65).
Second, two independent sample t-tests were conducted to look at differences in investments between predator and preys in both tough and soft strategies. The analysis showed a significant difference between predator (M = 4.38, SE = 0.5) and prey (M = 6.45, SE = 0.28) distributions in the tough strategy (t(38) = 3.61, p < .001), but no differences in the soft strategy (t(45) = 0.46, p = .48).
Table 1 and Figure 1 in the Appendix J summarize the results, along with the means and standard deviations per each level of the conditions. As can be seen, predator investments were not affected by their opponent’s strategy—they invested similarly when playing against tough and soft preys; preys, however, were influenced, so that they invested more when facing tough rather than soft predators. Put differently, prey did, and predators did not, adapt their investments to changes in their opponent’s strategy.
Frequency of aggression
As in the study by De Dreu and his colleagues (2014) frequency of aggression was computed as the number of trials in which the participant invested something (as opposed to invest 0). A two-way ANOVA was conducted to look at differences in the frequency of aggression between conditions. The analysis resulted in a significant difference between roles (F(1,46) = 4.21, p = .045), opponent strategies (F(1,46) =
4.99, p = .030), and a significant interaction between role and opponent strategies (F(1,46) = 16.07, p < .001). To further investigate the interaction, four t-tests were conducted between each levels of roles and strategies, using Bonferroni adjusted Alpha levels of .0125 per test (.05/4).
First, two paired-sample t-tests were conducted to look at differences in the frequency of aggression between tough and soft opponent strategies, in both the predator and the prey roles. The analysis showed a significant difference between tough (M = 21.47, SE = 1.81) and soft (M = 24.98, SE = 1.67) strategies in the predator condition (t(24) = -3.15, p = .004), but no differences in the prey condition (t(24) = 2.18, p = .04).
Second, two independent sample t-tests were conducted to look at differences in the frequency of aggression between predator and preys in both tough and soft opponent strategies. The analysis showed a significant difference between predator (M = 4.38, SE = 0.5) and prey (M = 6.45, SE = 0.28) in the tough strategy (t(32) = 2.89, p = .007), but no differences in the soft strategy (t(41) = 1.32, p = .196).
Table 2 and Figure 2 in the Appendix J summarize the results, along with the means and standard deviations per each level of the conditions. The results show that preys invested more often and regardless of the opponent’s strategy, whereas predators adapted more to their opponent’s strategy – they invested more often when the opponent was playing softer, and less often when playing against a tough opponent. This indicates that predators, but not preys, adapted their frequency of investment to changes in the strategy played by their opponent.
Force of aggression
Similarly to the way frequency of aggression was computed, force of aggression was also computed as in the study by De Dreu and his colleagues (2014), representing the mean investment across trials excluding no-investment trials. A two-way ANOVA was then conducted to look at differences in the force of aggression between conditions. The analysis showed a significant difference between opponent strategies (F(1,46) = 95.02, p < .001) and a significant interaction between role and strategy (F(1,46) = 5.46, p = .024). To further investigate this interaction, four t-tests were conducted between each levels of roles and opponent strategies, using Bonferroni adjusted Alpha levels of .0125 per test (.05/4).
First, two paired-sample t-tests were conducted to look at differences in the force of aggression between tough and soft strategies, in both the predator and the prey roles. The analysis showed a significant difference between tough (M = 6, SE = 0.28) and soft (M = 4.82, SE = 0.28) strategies in the predator condition (t(24) = 4.75, p < .001), and a significant difference between tough (M = 6.62, SE = 0.27) and soft (M = 4.73, SE = 0.28) strategies in the prey condition (t(24) = 9.79, p < .001).
Second, two independent sample t-tests were conducted to look at differences in the force of aggression between predator and preys in both tough and soft strategies. No differences were found in neither the tough strategy (t(39) = 1.73, p = .091), nor in the soft strategy (t(48) = 0.2, p = .845).
Table 3 and Figure 3 in the Appendix J summarize the results, along with the means and standard deviations per each level of the conditions. The results indicate a similar pattern in both predators and preys, in that the investments of both roles were conditioned by the strategy of their opponent – they invested more against a tougher than against a softer opponent. This shows that both roles similarly adapted the amount to invest to changes in their opponents’ strategies, investing more heavily against a tougher opponent, and investing less against a softer opponent.
Reaction times
A two-way ANOVA was conducted to look at differences in reaction times between conditions. The analysis did not yield any statistically significant difference between groups. However, a trend was
observed in the difference between reaction times in predators and preys (F(1,46) = 3.48, p = .068). Table 4 and Figure 4 in the Appendix J summarize the results, along with the means and standard deviations per each level of the conditions. The results suggest that although the difference in reaction times between the two roles was not significant, predators did take more time to make their investments than preys.
Discussion
As shown by our results, all our behavioral hypotheses were supported. First of all, we looked at the average investment between roles and opponent strategies, and this showed not only that preys invested more than predators overall, but also that they adapted more to changing opponents’ strategies: while predators did not change their investment pattern against different opponents’ strategies, preys invested more or less according to their opponent’s strategy (tough/soft respectively). These findings offer support for hypothesis 1a and 3.
Secondly, we looked at the frequency of aggression in the different roles and opponents’ strategies, and this analysis revealed that preys invest more often than predators, in line with our hypothesis 1b. Looking at differences in frequency of aggression, we also found that predators invest more often against soft preys than against tough preys, whereas this difference was not found in preys. This could be
interpreted against the third prediction, in that we predicted that preys would be more responsive than predators to changes in their opponent’s strategies. However, I will argue that this is not the case, and that this pattern of findings is actually in line with what was hypothesized. Indeed, we would expect the prey to
invest more frequently than the predator regardless the strategy of their opponent: while the predator can afford not invest and still win 10 every time, the prey always needs to invest in order to win, unless the predator is not investing at all. For this reason, a prey is always expected to invest more often, both against a tough and against a soft opponent, whereas a predator has more freedom to adapt his or her strategy to the opponent’s one. In line with this idea, the observed role differences in frequencies of investment were only found when playing against a tougher opponent: this is because while preys always needed to invest against a tough opponent strategy in order to survive the aggressions, predators are expected to invest less against a tougher opponent, because by not investing they already win 10; the more they would invest against a tough opponent, the more the chance to win less than 10.
Thirdly, we analyzed differences in the force of investment between roles and strategies. The results showed that the mean force of investment was higher for both roles against the tough opponent than the soft one, and this is also as it would be expected. However, predators would be expected to invest less overall on average, and this could be an indicator of irrational behavior: it would then be interesting to look at how this effect correlates with the hormonal data collected, to see if higher cortisol levels actually correlate with more rational behavior or not. Furthermore, the analyses showed that the patterns for the force of investment were similar for both roles. This shows that when we exclude the times in which participants did not invest, the two roles actually invest similarly on average. Since looking only at the times in which participants did invest shows no differences in average investments between roles, this might indicate that preys are better than predators in understanding when they can afford not to invest, rather than investing more all the time. This is also in line with what was previously said and with hypothesis 3, in that preys must be more responsive to changes in their opponents’ strategies in order to win the game, whereas predators can afford to invest less and less often, and still win.
Finally, we looked at different reaction times between the two roles. Although the difference observed was not statistically significant, the pattern of reaction times between roles offers support for the hypothesized trend. Preys were on average faster in their decisions, while predators were slower. This is in line with hypothesis 2 and confirms the results that had been previously observed by De Dreu and
colleagues (2014). Although the topic has been source of disagreement among researchers (see for example Malle & Neubauer, 1991), response latencies have often been used to assess impulsivity, which has traditionally been conceptualized as a tendency in people to respond quickly and with little
considerations about the accuracy of their response (Kagan, 1966). This observed trend might thus be caused by strategic differences specific to the ways the two roles process information: preys’ behavior is more fear-driven and defensive, resulting in more impulsivity; on the other hand, predators’ can afford to be more calculated in their greed-driven aggressive behavior. Furthermore, men have been shown to be generally more impulsive and risk-seeking (Cross, Copping, & Campbell, 2011); for this reason, it would be
interesting to investigate whether these gender differences would also be reflected in dissimilar trends in the reaction times between roles.
This last point calls attention to a considerable limitation of the current study: its focus on the male population. A follow-up research could then look at how women compare to men in predator-prey
interactions. In fact, there is a vast amount of research looking at how gender differences influence competitive and aggressive behavior. In addition to what has been previously discussed on gender differences on impulsivity, there is evidence that males are more competitive than females (Croson & Gneezy, 2009) and that they are more likely to initiate unprovoked attacks in war games (for a review of gender differences in competition and aggression, see Van Vugt, 2009). These findings could be partly explained by hormonal differences: men have (on average) considerably higher basal testosterone levels than women (Torjesen & Sandnes, 2004), and higher testosterone levels correlate with aggressive and competitive behavior (Bateup, Booth, Shirtcliff, & Granger, 2002). Accordingly, it would be interesting to look at the hormonal data gathered in this study and compare it with a follow-up research involving female participants. Such experiment could concurrently test whether men invest more aggressively in a predator-prey context, and whether this aggression is moderated by hormonal levels.
Connecting to the previously discussed line of research, not only there is evidence that men are more competitive than females, but also that men tend to react more than women to inter-group threats (Van Vugt, De Cremer, & Janssen, 2007). Indeed, the present study was limited to individual predator-prey interactions, but it would be interesting to see how groups of individuals would behave in the same kind of interactions, considering that most real life instances of competition or aggression are handled by groups rather than individuals, such as a committee in a company or a task force at war. According to this line of research, grounded on fields such as evolutionary psychology and anthropology, groups of men adapted to be most competitive to increase their chances of survival in situations of aggression. Therefore, in the predator-prey game, the difference between men and women in inter-group situations should be observed in the predator role, where the players’ investment represent an aggression, but not in the prey role, where the players invest only to defend themselves.
Summing up, the discussed findings confirm the results of the original study by De Dreu (2015, unpublished): investments of participants in the prey role were more impulsive and frequent than the ones of participants in the predator role, which instead were more calculated and greed-driven. Furthermore, preys were better in adapting their investment strategies according to the opponents they played against, in line with the arguments formerly presented. Future research could now be used to share light on the other aspects of this kind of interactions discussed, as well as their hormonal underpinnings.
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Appendix A - Briefing on the study
Informatiebrochure voor deelnemers ‘Investeringsbeslissingen’
Geachte proefpersoon,U gaat deelnemen aan het experiment ‘investeringsbeslissingen’. Deze brochure is bedoeld om u informatie te verschaffen over de aard en de procedure van het experiment. Het is daarom belangrijk dat u deze brochure van tevoren goed doorneemt.
Als extra documenten ontvangt u tevens:
• Informed Consent formulier (graag invullen)
• Debriefing Experiment (na de tweede, tevens laatste, sessie) Doel van het experiment
Mensen nemen constant beslissingen, soms om er beter van te worden en soms om te voorkomen dat de zaken minder gaan. In dit onderzoek laten we u een serie investeringsbeslissingen nemen, waarbij uw startkapitaal kan vermeerderen of verminderen. Wat u aan het einde van de beslissingstaak heeft verdiend met uw beslissingen, wordt daadwerkelijk uitbetaald (maximaal 10 Euro extra). We gaan ervan uit dat de beslissingstaak involverend is en we goed zicht krijgen op het soort investeringen die u doet.
Wat gaat er gebeuren?
Nadat u deze brochure heeft doorgelezen en de informed consent formulieren heeft ingevuld, zal u getraind worden in de investeringstaak. Belangrijk om te weten is dat u zich te allen tijden kunt terugtrekken uit het onderzoek, zonder opgave van reden, zonder dat dit gevolgen heeft. In twee aparte sessies (minimaal een week van elkaar gescheiden), zult u investeringsbeslissingen nemen. In elke sessie heeft u te maken met een aantal andere tegenspelers. Telkens wordt prestatie en verdienste gemeten. Aan het einde van de laatste sessie ontvangt u de debriefing en worden eventuele extra verdiensten per bankgiro aan u overgemaakt.
Voorafgaand aan, en direct na afloop van de investeringstaak, wordt u gevraagd speeksel af te geven in een daarvoor bestemd, steriel buisje. We doen dit om te onderzoeken welke lichameljike stoffen zoals cortisol betrokken zijn bij beslissingen. Speekselmonsters worden zodanig gelabeld dat wij ze kunnen koppelen aan uw investeringsbeslissingen, maar niet aan uw persoonlijke identiteit. Wij stellen de gegeven uit dit onderzoek aan niemand anders beschikbaar, gebruiken deze voor puur wetenschappelijke doeleinden en zullen alleen gemiddelden over alle deelnemers en nooit over individuele gevallen rapporteren.
In totaal neemt u deel aan 2 sessies van 1 uur (10 euro per sessie), los van eventuele verdiensten (maximaal 10 Euro per sessie). In totaal zult u dus minimaal 20 euro ontvangen, doch dit kan aanzienlijk meer worden, afhankelijk van uw investeringsbeslissingen.
Vrijwilligheid
Als u nu besluit af te zien van deelname aan dit experiment, zal dit op geen enkele wijze gevolgen voor u hebben. Als u tijdens het onderzoek zelf besluit uw medewerking te staken, zal dat eveneens op geen enkele wijze gevolg voor u hebben. Tevens kunt u 24 uur na dit onderzoek alsnog uw toestemming om gebruik te maken van uw gegevens intrekken. U kunt uw medewerking dus te alle tijden staken. U bent vrij
om dit te doen zonder opgave van redenen. Mocht u uw medewerking nu willen staken, of binnen 24 uur uw toestemming intrekken, dan zullen uw gegevens worden verwijderd uit onze bestanden.
Vertrouwelijkheid van onderzoeksgegevens
Alle gegevens uit dit experiment zullen anoniem blijven. De verdiensten uit de investeringstaak worden berekend door de hoofdonderzoeker, nadat alle deelnemers zijn geweest. De hoofdonderzoeker heeft geen inzicht in uw identiteit en geeft de uit te betalen bedragen door aan de financieele afdeling van de UvA, die op hun beurt zorgen dat verdiensten op de door u opgegeven bankrekening worden bijgeschreven. Hierdoor weet de proefleider dus nooit hoeveel geld er door u is verdient.
Debriefing
Na de laatste experimenten krijgt u een korte debriefing over de bedoelingen en aard van het onderzoek. Vragen over het onderzoek kunt u altijd kenbaar maken of (na de experimenten) mailen naar
c.k.w.dedreu@uva.nl
Appendix B - Informed consent form
Informed consent bij standaardonderzoek
‘Ik verklaar hierbij op voor mij duidelijke wijze te zijn ingelicht over de aard en methode van het onderzoek, zoals uiteengezet in de bovenstaande informatie brochure ‘Investeringsbeslissingen I’. Mijn vragen zijn naar tevredenheid beantwoord.
Ik stem geheel vrijwillig in met deelname aan dit onderzoek. Ik behoud daarbij het recht deze instemming weer in te trekken zonder dat ik daarvoor een reden behoef op te geven en besef dat ik op elk moment mag stoppen met het experiment. Indien mijn onderzoeksresultaten gebruikt zullen worden in wetenschappelijke publicaties, dan wel op een andere manier openbaar worden gemaakt, zal dit volledig geanonimiseerd gebeuren. Mijn persoonsgegevens zullen niet door derden worden ingezien zonder mijn uitdrukkelijke toestemming.
Voor dit onderzoek ontvang ik een financiele tegemoetkoming die bestaat uit een vast deel per sessie (10 Euro) en een variabel deel dat bepaald wordt door de verdienste tijdens het uitvoeren van de taken. Het totaalbedrag dat ik met dit onderzoek verdien, dient aan het einde van dit onderzoek overgemaakt te worden op
Bankrekening _____________ ten name van _____________ te _________________
Als ik nog verdere informatie over het onderzoek zou willen krijgen, nu of in de toekomst, kan ik me wenden tot Dr. De Dreu (telefoon: 020 525 6865 e-mail: c.k.w.dedreu@uva.nl; Weesperplein 4, 1018 XA Amsterdam, kamer 4.06). Voor eventuele klachten over dit onderzoek kunt u zich wenden tot het lid van de Commissie Ethiek van de afdeling Psychologie van de Universiteit van Amsterdam, Dr F.S. Ten Velden (telefoon: 020 5256860; e-mail: F.S.tenvelden @uva.nl, Weesperplein 4, 1018 XA Amsterdam).
Aldus in tweevoud getekend:
……… ………
‘Ik heb toelichting verstrekt op het onderzoek. Ik verklaar mij bereid nog opkomende vragen over het onderzoek naar vermogen te beantwoorden.’
……… ………
Naam onderzoeker Handtekening
Appendix C - Information on the participant’s behavior of the day Behavior the Day of
Have you had any stressful events occur in the last week and if so when? _____________
_______________________________________________________________________________________ __________
How many hours of sleep did you get last night? _________________________hours.
What time did you wake up? _______________________o’clock.
What have you had to eat today? ___________________________________________________________ At what time(s): _____________________________________o’clock
Have you had any caffeine today? YES No
If so how much? ___________________cups.
At what times? _____________________o’clock
Have you consumed alcohol in the last 24 hours? YES NO If so, how much? ________________________ drinks.
Have you taken any recreational drugs in the last 24 hours? YES NO If so, what? ________________________.
Have you exercised in the last 24 hours (gym, jog, etc)? YES NO If so, when _______________________o’clock
General Personal Information
Nationality _____________________________ Age: _____________________ years.
Weight: __________________kg.
Height: ________________________cm.
YES NO Are you currently taking any medications?
If so, what and how much: __________________________________
________________________________________________________________
Have you taken any of the following in the last 30 days?
YES NO Antidepressants (SSRI’s, MAOI’s, or others; such as Prozac, Luvox, Zoloft, Elavil, Nardil, etc.)
If so, which, and how much: _______________________________
YES NO Anxiety Medication (such as Xanax, Valium, Klonopin, etc.)
If so, which, and how much: ________________________________
________________________________________________________________
YES NO Cigarettes
If so, when, and how many: ________________________________
YES NO Stimulants (such as Cocaine, MDMA, etc.)
If so, which, and how much: ________________________________ _____________________________________________________________ ___
If so, which, and how much: ________________________________ _____________________________________________________________ ___
YES NO Painkillers (such as Vicodin, Oxycontin, etc)
If so, which, and how much: ________________________________ _____________________________________________________________ ___
YES NO Any other drug (prescription or illicit)
If so, what, and how much:_________________________________ _____________________________________________________________ ___
Did you at the moment or in the past have any of these mental conditions, as shown below?
YES NO Asthma
YES NO Form of lung disease
YES NO (Past) Epilepsy / Epileptic Attack / Seizures YES NO Repeatedly Returning Migraines
YES NO Hepatic / Renal Impairment YES NO (Past) ‘Black-Outs' / Fainting
YES NO (Past) Diabetes
YES NO (Past) High Blood Pressure YES NO (Past) Heart Problems
YES NO Inability to Perform Moderate Effort Exercises
Did you at the moment or in the past have any of these mental conditions, as shown below? YES NO Current Depressive Episode
YES NO Current Manic Episode YES NO Current Psychotic Episode
YES NO Psychotic Episode in the Past YES NO Anxiety Disorder
If yes which one: Lifestyle Information
Sleeping Habits (how many hours per night on average): ____________________hours per night.
Eating Habits (Vegetarian? Special diet?): ________________________________________________ _______________________________________________________________________________________ __________
Exercising Habits (how often each week):__________________________ times per week.
Type of exercise: ________________________________________________________________
Sexual Behavior (how active on average per week): __________________ times per week.
Drinking habits (how many alcoholic beverages, on average, per night and/or Week):____________________ drinks per night/ week (circle one)
Appendix E - Pre-test PANAS questionnaire
De volgende lijst bestaat uit woorden die een bepaald gevoel of emotie uitdrukken. Geef aan in
welke mate jij je zo gevoeld hebt het afgelopen uur. Geef antwoord op een schaal van 1 tot 5 door
het omcirkelen van het cijfer van jouw keuze. De betekenis van de antwoordcijfers is in dit
onderdeel als volgt:
1
2
3
4
5
(bijna) nooit soms regelmatig vaak
zeer vaak
1.
Kalm
1
2
3
4
5
2.
Uitgelaten
1
2
3
4
5
3.
Alert
1
2
3
4
5
4.
Verbaasd
1
2
3
4
5
5.
Bang
1
2
3
4
5
6.
Boos
1
2
3
4
5
7.
Beschaamd
1
2
3
4
5
8.
Ontmoedigd
1
2
3
4
5
9.
Futloos
1
2
3
4
5
10.
Aandachtig
1
2
3
4
5
11.
Verwonderd
1
2
3
4
5
12.
Angstig
1
2
3
4
5
13.
Minachtend
1
2
3
4
5
14.
Tekort schietend
1
2
3
4
5
15.
Overstuur
1
2
3
4
5
16.
Lusteloos
1
2
3
4
5
17.
Ontspannen
1
2
3
4
5
18.
Gelukkig
1
2
3
4
5
19.
Bevreesd
1
2
3
4
5
20.
Afkerig
1
2
3
4
5
21.
Schuldig
1
2
3
4
5
22.
Teneergeslagen
1
2
3
4
5
23.
Vermoeid
1
2
3
4
5
24.
Opgetogen
1
2
3
4
5
25.
Blij
1
2
3
4
5
26.
Geconcentreerd
1
2
3
4
5
27.
Verrast
1
2
3
4
5
28.
Verdrietig
1
2
3
4
5
29.
Op mijn gemak
1
2
3
4
5
Appendix F - Post-test impressions and PANAS questionnaire
Wat is jouw algemene indruk van de tegenspekrs waarmee je te maken had
Voorspelbaar
1
2
3
4
5
Onvoorspelbaar
Slim
1
2
3
4
5
Dom
Intelligent
1
2
3
4
5
Niet intelligent
Dominant
1
2
3
4
5
Onderdanig
Actief
1
2
3
4
5
Passief
Cooperatief
1
2
3
4
5
Competitief
Betrokken
1
2
3
4
5
Niet betrokken
Egoistisch
1
2
3
4
5
Altruistisch
Drammerig
1
2
3
4
5
Meegaand
Roekeloos
1
2
3
4
5
Voorzichtig
Dapper
1
2
3
4
5
Lafhartig
De volgende lijst bestaat uit woorden die een bepaald gevoel of emotie uitdrukken. Geef aan in
welke mate jij je zo gevoeld hebt het afgelopen uur. Geef antwoord op een schaal van 1 tot 5 door
het omcirkelen van het cijfer van jouw keuze. De betekenis van de antwoordcijfers is in dit
onderdeel als volgt:
1
2
3
4
5
(bijna) nooit soms regelmatig vaak
zeer vaak
1.
Kalm
1
2
3
4
5
2.
Uitgelaten
1
2
3
4
5
3.
Alert
1
2
3
4
5
4.
Verbaasd
1
2
3
4
5
5.
Bang
1
2
3
4
5
6.
Boos
1
2
3
4
5
7.
Beschaamd
1
2
3
4
5
8.
Ontmoedigd
1
2
3
4
5
9.
Futloos
1
2
3
4
5
10.
Aandachtig
1
2
3
4
5
11.
Verwonderd
1
2
3
4
5
12.
Angstig
1
2
3
4
5
13.
Minachtend
1
2
3
4
5
14.
Tekort schietend
1
2
3
4
5
15.
Overstuur
1
2
3
4
5
16.
Lusteloos
1
2
3
4
5
17.
Ontspannen
1
2
3
4
5
18.
Gelukkig
1
2
3
4
5
19.
Bevreesd
1
2
3
4
5
20.
Afkerig
1
2
3
4
5
21.
Schuldig
1
2
3
4
5
22.
Teneergeslagen
1
2
3
4
5
23.
Vermoeid
1
2
3
4
5
24.
Opgetogen
1
2
3
4
5
25.
Blij
1
2
3
4
5
26.
Geconcentreerd
1
2
3
4
5
27.
Verrast
1
2
3
4
5
28.
Verdrietig
1
2
3
4
5
29.
Op mijn gemak
1
2
3
4
5
Appendix G - Self-assessment questionnaire
ZELF-BEOORDELINGS VRAGENLIJST
Hierna volgen een aantal uitspraken, die mensen hebben gebruikt om zichzelf te beschrijven. Lees iedere
uitspraak door en zet dan een kringetje om het cijfer rechts van die uitspraak om daarmee aan te geven
hoe u zich nu voelt, dus nu op dit moment. Er zijn geen goede of foute antwoorden. Denk niet te lang na
en geef uw eerste indruk, die is meestal de beste. Het gaat er dus om dat u weergeeft wat u op dit moment
voelt.
Geheel
niet
Een
beetje
Tamelijk
veel
Zeer
veel
1.
Ik voel me kalm . . .
1
2
3
4
2.
Ik voel me veilig . . .
1
2
3
4
3.
Ik ben gespannen . . .
1
2
3
4
4.
Ik voel me onrustig . . .
1
2
3
4
5.
Ik voel me op mijn gemak . . .
1
2
3
4
6.
Ik ben in de war . . .
1
2
3
4
7.
Ik pieker over nare dingen die kunnen
gebeuren . . .
1
2
3
4
8.
Ik voel me voldaan . . .
1
2
3
4
9.
Ik ben bang . . .
1
2
3
4
11.
Ik voel me zeker . . .
1
2
3
4
12.
Ik voel me nerveus . . .
1
2
3
4
13.
Ik ben zenuwachtig . . .
1
2
3
4
14.
Ik ben besluiteloos . . .
1
2
3
4
15.
Ik ben ontspannen . . .
1
2
3
4
16.
Ik voel me tevreden . . .
1
2
3
4
17.
Ik maak me zorgen . . .
1
2
3
4
18.
Ik voel me gejaagd . . .
1
2
3
4
19.
Ik voel me evenwichtig . . .
1
2
3
4
20.
Ik voel me prettig . . .
1
2
3
4
ZELF-BEOORDELINGS VRAGENLIJST
Hierna vindt u een aantal uitspraken die door mensen zijn gebruikt om zichzelf te beschrijven. Lees
iedere uitspraak door en zet een kringetje om het cijfer rechts van die uitspraak om daarmee aan te
geven hoe u zich in het algemeen voelt. Er zijn geen goede of foute antwoorden. Denk niet te lang na
en geef uw eerste indruk. Het gaat er om dat u bij deze vragenlijst weergeeft hoe u zich in het
algemeen voelt.
bijna
nooit
soms
vaak
bijna
altijd
21.
Ik voel me prettig. . .
1
2
3
4
22.
Ik voel me nerveus en onrustig . . . .
1
2
3
4
23.
Ik voel me tevreden. . .
1
2
3
4
24.
Ik kan een tegenslag maar heel moeilijk verwerken . . . 1
2
3
4
25.
Ik voel me in vrijwel alles tekort schieten . . . 1
2
3
4
26.
Ik voel me uitgerust . . .
1
2
3
4
27.
Ik voel me rustig en beheerst . . .
1
2
3
4
28.
Ik voel dat de moeilijkheden zich opstapelen zodat
ik er niet meer tegenop kan
1
2
3
4
Appendix H - Social value orientation questionnaire
Er volgen nu nog een aantal vragen.
Bij deze vragen zul je enkele keuzes maken. Dit kun je doen door straks vakje A of B aan te
klikken. Jouw keuzes bepalen het aantal punten dat jij en een fictief iemand ontvangen (dat is dus
geen andere deelnemer aan dit experiment). Ga ervan uit dat deze andere persoon ook keuzes
maakt in precies dezelfde taak.
Wie is deze ander?
Je moet je voorstellen dat deze ander een persoon is die je niet kent (nog nooit hebt ontmoet) en dat
je deze ander ook nooit zult ontmoeten (of zult leren kennen). Het is dus een geheel onbekende
ander.
Wat betekenen punten?
Aan de hand van punten wordt weergegeven wat je waardevol vindt. Ga er dus van uit dat elk punt
waardevol is. Hoe meer je er van krijgt hoe beter. Hetzelfde geldt voor de ander: hoe meer hij of
zij ervan krijgt hoe beter voor hem of haar.
Voorbeeld:
A B
30.
Ik ben gelukkig . . .
1
2
3
4
31.
Ik word geplaagd door storende gedachten . . .
1
2
3
4
32.
Ik heb gebrek aan zelfvertrouwen . . .
1
2
3
4
33.
Ik voel me veilig . . .
1
2
3
4
34.
Ik voel me op mijn gemak . . .
1
2
3
4
35.
Ik ben gelijkmatig van stemming . . . .
1
2
3
4
36.
Ik ben tevreden . . .
1
2
3
4
37.
Er zijn gedachten die ik heel moeilijk los kan laten . . . .
1
2
3
4
38.
Ik neem teleurstellingen zo zwaar op
dat ik ze niet van me af kan zetten . . . .
1
2
3
4
39.
Ik ben een rustig iemand . . .
1
2
3
4
40.
Ik raak helemaal gespannen en in
beroering als ik denk aan mijn zorgen
Jij krijgt
24.00 24.00
De ander krijgt 11.00 24.00
Voor bovenstaand voorbeeld geldt het volgende. Als je A kiest, krijg je 24.00 punten en de ander
krijgt 11.00 punten; als je B kiest krijg je 24.00 punten en de ander krijgt 24.00 punten.
Klik bij elke van de volgende 24 keuzesituaties ofwel een A ofwel een B aan. Er zijn geen goede of
foute antwoorden. Je kiest voor A of B, afhankelijk van welk alternatief je het meest aantrekkelijk
vindt. Ga er hierbij van uit dat de punten waardevol zijn: hoe meer je ervan hebt hoe beter voor je.
Hetzelfde geldt voor de ander: hoe meer de ander er heeft, hoe beter voor hem/haar.
1. A Self = 22.50 other = 28.00 B Self = 25.60 other = 25.60 2. A Self = 11.10 other = 29.50 B Self = 15.00 other = 30.00 3. A Self = 0.00 other = 15.00 B Self = 0.50 other = 18.90 4. A Self = 29.50 other = 18.90 B Self = 30.00 other = 15.00 5. A Self = 2.00 other = 7.50 B Self = 0.50 other = 11.10 6. A Self = 2.00 other = 22.50 B Self = 4.40 other = 25.60 7. A Self = 30.00 other = 15.00 B Self = 29.50 other = 11.10 8. A Self = 15.00 other = 30.00 B Self = 18.90 other = 29.50 9. A Self = 28.00 other = 7.50 B Self = 25.60 other = 4.40 10. A Self = 18.90 other = 29.50 B Self = 22.50 other = 28.00
11. A Self = 22.50 other = 2.00 B Self = 18.90 other = .050 12. A Self = 15.00 other = 0.00 B Self = 11.10 other = 0.50 13. A Self = 4.40 other = 25.60 B Self = 7.50 other = 28.00 14. A Self = 25.60 other = 25.60 B Self = 28.00 other = 22.50 15. A Self = 29.50 other = 11.10 B Self = 28.00 other = 7.50 16. A Self = 7.50 other = 28.00 B Self = 11.10 other = 29.50 17. A Self = 25.60 other = 4.40 B Self = 22.50 other = 2.00 18. A Self = 4.40 other = 4.40 B Self = 2.00 other = 7.50 19. A Self = 11.10 other = 0.50 B Self = 7.50 other = 2.00 20. A Self = 28.00 other = 22.50 B Self = 29.50 other = 18.90 21. A Self = 0.50 other = 11.10 B Self = 0.00 other = 15.00 22. A Self = 18.90 other = 0.50 B Self = 15.00 other = 0.00 23. A Self = 0.50 other = 18.90 B Self = 2.00 other = 22.50 24. A Self = 7.50 other = 2.00 B Self = 4.40 other = 4.40
Appendix I – Debriefing
Debriefing proefpersonen Predator-Prey Contests among Individuals
Geachte deelnemer,
Hartelijk dank voor uw deelname aan het onderzoek ‘Investeringsbeslissingen I.’
Er is onderzocht of uw investeringsbeslissingen veranderen onder invloed van de mate waarin u probeert een investeringsconflict van uw medespeler te winnen. Daarom heeft u de zogenaamde Predator-Prey Conflict Game verscheidene keren moeten doen, telkens met een verschillende tegenspeler. Daarnaast heeft u enkele keren speeksel afgegeven, van waaruit wij twee hormonen (testosteron, cortisol) kunnen aflezen. We zijn met name benieuwd of deze hormonen betrokken zijn bij investeringsbeslissingen in de rol van “predator” en “prey”.
Bent u geïnteresseerd in meer informatie dan kunt u altijd contact opnemen via onderstaand emailadres:
c.k.w.dedreu@uva.nl
Nogmaals hartelijk dank voor uw deelname aan dit onderzoek! Carsten K.W. De Dreu, Ph D
Appendix J – Tables and graphs
Table 1. Results of paired-sample t-tests for players’ mean investments between opponent strategies for each role, together with means and standard errors for each group.
Tough Strategy Soft Strategy
Role M SE M SE t p
Predator 4.34 0.42 4.28 0.35 0.46 .65
Prey 6.44 0.41 4.6 0.34 9.11 < .001
Figure 1. Mean investments per role and opponent strategy. Mean investment range: 0-10, error bars: +/- 1 SE.
Table 2. Results of paired-sample t-tests for players’ frequency of aggression between opponent strategies for each role, together with means and standard errors for each group.
Tough Strategy Soft Strategy
Role M SE M SE t p
Predator 21.47 1.81 24.98 1.67 -3.15 .004
Prey 28.63 1.77 27.76 1.64 2.18 .04
Figure 2. Mean frequency of aggression per role and opponent strategy. Mean frequency of aggression range: 0-30, error bars: +/- 1 SE.
Table 3. Results of paired-sample t-tests for players’ mean force of aggression between opponent strategies for each role, together with means and standard errors for each group.
Tough Strategy Soft Strategy
Role M SE M SE t p
Predator 6 0.28 4.82 0.28 4.75 < .001
Prey 6.62 0.27 4.73 0.28 9.79 < .001
Figure 3. Mean force of aggression per role and opponent strategy. Mean force of aggression range: 0-10, error bars: +/- 1 SE.
Table 4. Results of paired-sample t-tests for players’ mean reaction time (in milliseconds) between opponent strategies for each role, together with means and standard errors for each group.
Tough Strategy Soft Strategy
Role M SE M SE
Predator 2107.59 211.99 2412.69 243.62 Prey 1650.99 207.87 1855.26 238.89
Graph 4. Mean reaction time (in milliseconds) per role and opponent strategy. Mean reaction time range: 0-3000, error bars: +/- 1 SE.
