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Effects of Cognitive Load on Trusting Behavior – An Experiment Using the Trust Game

  • Katarzyna Samson ,

    Contributed equally to this work with: Katarzyna Samson, Patrycjusz Kostyszyn

    Affiliation The Robert B. Zajonc Institute for Social Studies, University of Warsaw, Warsaw, Poland

  • Patrycjusz Kostyszyn

    Contributed equally to this work with: Katarzyna Samson, Patrycjusz Kostyszyn

    Affiliation University of Social Sciences and Humanities, Warsaw, Poland


Last decades have witnessed a progressing decline of social trust, which has been predominantly linked to worsening economic conditions and increasing social inequality. In the present research we propose a different type of explanation for the observed decline – cognitive load related to technological development and the accelerating pace of modern life. In an experimental study participants played the trust game while performing one of two different secondary tasks – listening to a disturbing noise or memorizing a sequence of characters – or with no additional task in the control condition. Results show that in both cognitive load conditions participants expressed significantly less trust in the trust game than in case of no cognitive load. Additionally, when cognitive resources were limited, participants’ behavior was more impulsive than when their resources were fully available.


Trust matters. For an individual, trust is a prerequisite for the emergence of a healthy personality and satisfying interpersonal relationships [15]. For a group, it promotes cooperation, improves coordination, sustains social order and permits beneficial long-term exchanges [610]. As a building block of social capital, trust is important for the stability of democracy and general wellbeing of its members [1116]. It is also indispensable in finance and necessary for the efficient functioning of modern economies [1720]. The more complex and dynamic social and economical relations are becoming, the more trust it needed as a lubricant to keep them running [21].

It is thus especially alarming that all around the world trust is declining. Trust in others, as well as confidence in societal institutions, are at their lowest point in over three decades, according to data from two nationally representative surveys in the United States—the General Social Survey of adults and the Monitoring the Future survey of 12th graders—[22]. Similarly in Europe, in the last decade trust has been successively falling [23]. In all advanced industrialized democracies trust towards the government and political institutions has been falling since the late 1960s [24]. What are the reasons for such crisis of trust?

The decline of trust has been linked to a number of phenomena, but mostly to worsening economic conditions [22, 2527]. Economic inequality is the strongest determinant of a lack of trust, as it hinders the creation of bonds in a society—the greater the inequality gap, the less likely that both the advantaged as well as the disadvantaged will consider themselves part of a moral community [27]. Trust is also negatively related to the size of the national debt and unemployment levels [28]. Other factors that have been shown to contribute to erosion of trust are structural changes in the society [15,16, 29,30]. Increased social and geographic mobility, more ethnic and racial diversity, presence of women on the labor market, changes in the traditional model of family and individuation of leisure weaken bonds holding individuals and communities together and, in turn, erode both interpersonal and political trust. Similarly, the decline of trust has been linked to the rapid rise of materialistic value orientation that undermines views about the trustworthiness of others [31]. At an individual level, strongest factors reducing trust are a recent history of trauma, belonging to a group that historically has been discriminated against, lack of economic success, and living in community which is racially diverse or characterized by a high degree of income disparity [25].

Cognitive overload

Our society is developing at a great speed and the social and technological changes of the last decades are not without consequences for people’s cognitive functioning [3234]. The consumption of media is continuously growing. Averaged across all media sources, media delivered in bytes is increasing at a rate of 18% per year [35]. It is estimated that in 2015 Americans will consume on average fifteen and a half hours of both traditional (TV, radio, voice telephony) as well as digital media (tablet computers, mobile gaming devices, smartphones, mobile video) per person per day—and this calculation does not include media consumed in the workplace. While absolute time spent with media is increasing, time spent multitasking with media is growing even more rapidly. Within the first decade of our century, there has been a 120% increase in the time that youth media multitask [36]. British teenagers and young adults on average squeeze 14 hours of media activity into 9 hours of real time [37]. More complexity in our environments along with the omnipresence of information and increased multitasking lead to a state of perpetual cognitive overload [38,39].

Independently of its source, cognitive load decreases performance in all types of tasks [4042]. It also affects decision-making strategies. Under cognitive load people are more impulsive and less analytic [41, 43], they tend to omit available information [44,45], are more likely to use decision heuristics [46], and fall prey to cognitive biases [47,48]. Cognitive load also decreases self-control [49,50] and the willingness to take risks [51]. This happens because under conditions of cognitive load less resources are available to reflect on a decision, what makes analytical processing more difficult and leads to using cognitive shortcuts.

In the present research we hypothesized that cognitive load may be a factor contributing to the decline of trust observed worldwide in the last decades. Trust is a process that has both social as well as cognitive components—it is not only a belief about the intentions of others but also a rational calculation of probability concerning a specific person in a specific situation [3, 5258]. We therefore expected that under conditions of cognitive load people would express less trust than in case of a full availability of cognitive resources. We also expected that under conditions of cognitive load the trusting process would be more impulsive, i.e. to a greater extent dependent on immediate, situational cues, as compared to conditions with a full availability of cognitive resources. The results confirmed our hypotheses.

Materials and Methods

Ethics Statement

All procedures were approved by a Research Ethics Board at the Robert B. Zajonc Institute for Social Studies, University of Warsaw. Potential participants in the study were informed about its general aim, duration, outline of the procedure and remuneration. They were also told that participation is voluntary, that they can withdraw from the study at any point without telling the reason, and that all data is anonymous and will only be used for reasons related to this study. All participants signed an informed consent form prior to participation.


The study was conducted among 90 University of Warsaw students (73% female) aged 19–25 (M = 21.63, SD = 1.50). They received a small remuneration for participating in the study (ca. 1–2 euros in local currency, exact amount depending on their decisions in the study).


To measure trust we used the trust game [59]—an economic game, in which two players can increase their wealth through the expression and reciprocity of trust. At the outset of the game both players are endowed with some amount of money. The first player decides how much of their initial endowment they would like to send to the second player, knowing that the whole transfer will be tripled when the other person receives it. Then, the second player returns any fraction of currently possessed money (i.e. the initial endowment enlarged by the received transfer) to the first player. After both players have made their decisions, a round of the trust game ends. The amount of money sent by the first player is the measure of their trust toward the partner, while the amount returned is a measure of the second player’s trustworthiness. The trust game is currently the most common behavioral measure of trust [60,61].

In this study the players’ initial endowments in each round were 10 units of experimental currency. The game consisted of 10 rounds, but the participants didn’t know how many rounds there would be. After each round the players’ money was transferred to their accounts in the game and the next round started with new initial endowments of 10 units of experimental currency per person. After the game ended experimental money from the accounts was exchanged into real currency at a rate of 25:1 and given to the participants as remuneration for their participation in the study. Participants could monitor both players’ account balances at all times.

The trust game was administered online using dedicated software TGAME, which allows controlling the behavior of one the players by replacing it with a computer strategy. All participants played the role of first players, while the computer always followed the same predefined scenario of the second player’s behavior: in the first “trust-building” stage of the game (rounds one through three) it returned 50% of the money it had; in the second “trust-violation” stage (round four) it kept all the money and returned nothing to the trustor; in the third “trust-recovery” stage (rounds five through ten) it again returned 50% of possessed money. To decrease the probability of uncovering that the second player is in fact imitated by a computer, in all rounds except the fourth (violation of trust) there was a random variability in a 10% range added to its decisions.

Cognitive load manipulation

To impose cognitive load we used two distinct manipulations, the effectiveness of both of which was confirmed in previous research. In case of the first cognitive load manipulation—memory load condition—participants were asked to memorize a password-like string of seven characters including letters, numbers and symbols [6265]. The second manipulation involved exposing participants to a disturbing noise (noise load condition). Noise has a moderate but deleterious effect on performance capacity and cognitive tasks, such as the trust game administered in this study, are known to be among the most vulnerable to noise effects [66]. The noise used in the present study was a mix of two musical tracks recorded simultaneously of which one was playing backwards.


When participants arrived at the lab, they were randomly assigned to one of three experimental conditions: memory load, noise load, or no cognitive load condition. Before the primary task begun we administered the cognitive load manipulations. In the memory load condition participants were presented a string of characters and asked to memorize it until they would be asked to write it down. In the noise cognitive load condition they received headphones that emitted a noise and were asked to keep them on until instructed to take them off. In the no cognitive load condition participants did not receive any secondary tasks. Next, all participants played the trust game. When the trust game was over, participants in memory load condition were instructed to write down what they remembered of the password and in noise load condition they were told to take off the headphones.

After the trust game and the cognitive load manipulation we also measured participants’ propensity to trust and distrust (a set of generalized beliefs about human nature that determine an initial attitude when interacting with strangers) and their cognitive capacities. Propensity to trust and distrust was measured using Eisenberger’s Expectational Trust Scale (it consists of two subscales—propensity to trust and propensity to distrust) translated by Rozycka and Wojciszke [67]. Cognitive capacities were measured using an abridged version of the advanced Raven’s Progressive Matrices Test [68]; the abridged version included every third matrix from the second series: nos. 1, 4, 7, 10, 13, 16, 19, 22, 25, 28, 31, 34; it had a 10-minute time limit.

When the study was over participants were thanked, carefully debriefed and given their remuneration. The study was conducted during the daytime (10am-5pm) to avoid large differences in participants’ levels of fatigue. The procedure took about 20–30 minutes.


Descriptive statistics

We first compared the descriptive statistics of all measured variables (except the dependent variable trust) in three experimental conditions. There were no differences between experimental conditions in terms of age, gender distribution, propensity to trust, propensity to distrust or cognitive capacities. Means, standard deviations and results of group comparison analyses are presented in Table 1. Trust, as measured using the trust game, did not correlate with either propensity to trust, r(89) = .17, p = .11, propensity to distrust, r(89) = -.13, p = .21 or cognitive capacities, r(89) = .04, p = .71.

Table 1. Descriptive statistics of measured variables in each experimental condition along with appropriate tests (ANOVA or chi-square, depending on measurement level) to verify differences between the three conditions in means/frequencies.

Manipulation checks

In the memory load condition we verified that participants really made the effort to remember the password—73% recalled the password flawlessly, another 20% made only one mistake and only 7% made two or more mistakes. In the noise load condition we checked that the track in the headphones was playing throughout the duration of the manipulation and that participants didn’t reduce the volume.

Differences in trust

To verify if levels of trust expressed in the trust game varied between experimental conditions we conducted a repeated measures ANOVA with cognitive load as a between-subject factor and trust in each of the rounds of the trust game as dependent variable. Mauchly’s test indicated that the assumption of sphericity had been violated, χ(9) = 198.29, p < .001, therefore degrees of freedom were corrected using Greenhouse-Geisser estimates of sphericity (ω = .60). Results showed that cognitive load indeed affected the levels of trust expressed toward the partner, F(2,87) = 10.25, p <.001, ηp2 = .19. Analysis of Helmert contrasts showed that in in the control condition with no cognitive load trust was higher, M = 6.92, SD = 1.95, than in case of both cognitive load conditions, p < .001. The difference in trust between the noise load condition, M = 5.23, SD = 1.70, and the memory load condition, M = 4.87, SD = 1.95, was not significant, p = .46. Means of trust in each experimental condition are presented in Fig 1.

Fig 1. Overall means of trust in the trust game in three experimental conditions.

*** p < .001.

Within-subject analysis showed that the average level of trust changed between the rounds of the trust game—across all experimental conditions trust started off at a medium level, increased in the next three rounds, then dropped rapidly in the fifth round and starting from the sixth round increased again to stabilize in the ninth round at a slightly greater value than in begun with, F(5.43, 473.10) = 12.98, p < .001, ηp2 = .13. Repeated contrasts indicated significant differences in mean levels of trust between the first and the second round, F(1,87) = 8.53, p = .004, ηp2 = .09, the second and the third round, F(1,87) = 17.99, p < .001, ηp2 = .17, the fourth and the fifth round, F(1,87) = 58.21, p = .004, ηp2 = .40, the fifth and the sixth round, F(1,87) = 12.60, p = .001, ηp2 = .13, and the seventh and the eighth round, F(1,87) = 4.52, p = .04, ηp2 = .05. These differences follow the assumed pattern stemming from the preprogrammed behavior of the trustee—trust building, trust violation and trust recovery stages. Changes in average levels of trust did not differ between experimental conditions (Fig 2), as the interaction between cognitive load and the round of the trust game was insignificant, F(10.88, 473.10) = .72, p = .72.

Fig 2. Means of trust in each round of the trust game in three experimental conditions.

When we adjusted the analyses for propensity to trust, propensity to distrust and cognitive capacities, the pattern of results did not change. Detailed results are available upon request.

Impulsiveness of decisions

To verify if cognitive load affects the impulsiveness of trust game behavior we first operationalized the concept of impulsive and strategic decisions in the trust game. We operationalized an impulsive decision as one that is guided by the most immediate cue concerning the trustworthiness of the partner, i.e., partner’s last move. This way if the partner was trustworthy in all preceding rounds but betrayed our trust in the last one, an impulsive decision would be not to look on the overall positive history of the interaction but to punish them with distrust for their betrayal. For each trust game decision in rounds two through ten we found the partner’s decision that immediately preceded it and called this predictor impulse. Then we operationalized a strategic decision as one that follows an initially adopted strategy, independently of the actual history of the interaction. Examples of such strategies could be “my best chance at getting the most out of the situation is to always trust” or “never trust a stranger”. We assumed that applying a strategic approach should result in an auto-correlated time series of a participant’s own decisions. For each trust game decision in rounds two through ten we computed the average value of that person’s trust in all preceding rounds of the trust game and called this predictor strategy.

We then conducted multiple regression analyses using the enter method of including variables in the model, with trust in a given round of the game as dependent variable (rounds two through ten) and two standardized predictors: impulse and strategy, independently for both cognitive load conditions and the no cognitive load control group. Results showed that when cognitive resources were limited, either through a memory task or a disturbing noise, impulse was a stronger predictor of trust than strategy. In the control condition with no cognitive load it was strategy that was more strongly related to trust than impulse. Regression coefficients are presented in Table 2.

Table 2. Effects of impulse and strategy on trust in no cognitive load and cognitive load conditions.

Discussion and Conclusions

In the present research we investigated the effect of cognitive load on trust expressed in a dyadic interaction. Participants played the trust game with a preprogrammed computer strategy that imitated the behavior of a second player. At the same time they either performed a secondary task that engaged some of their cognitive resources—keeping a string of characters in their memory or listening to a disturbing noise on headphones—or not. As predicted, cognitive load introduced by secondary tasks decreased the amount of trust participants placed in their interaction partner, independently of the type of cognitive load manipulation. Moreover, when cognitive resources were limited, participants’ behavior was more impulsive than when their resources were fully available, i.e., partner’s last move was a stronger predictor of behavior than own strategy until that moment.

This work has important theoretical implications regarding the declining indicators of social trust around the world [22, 24]. Our results indicate that living under conditions of almost permanent cognitive load may be a factor contributing to the progressing decrease of social trust. As the pace of modern life is accelerating, people’s cognitive resources are being more and more occupied with technology and the necessity to multitask. When faced with a situation involving trust, fewer resources are available to calculate probabilities concerning possible outcomes in a specific situation and, in consequence, a decision to express trust is less likely. Our results show that the observed decrease of trust may be yet another side effect of the social and technological development of societies.

Author Contributions

Conceived and designed the experiments: KS PK. Performed the experiments: KS PK. Analyzed the data: KS PK. Contributed reagents/materials/analysis tools: KS PK. Wrote the paper: KS PK.


  1. 1. Bowlby J. Attachment and loss, vol. 2: Separation: Anxiety & anger. New York: Basic Books; 1973.
  2. 2. Erikson E. Childhood and society. New York: Norton; 1950/1993.
  3. 3. Rempel JK, Holmes JG, Zanna MP. Trust in close relationships. J Pers Soc Psychol. 1985;49: 95–112.
  4. 4. Rotenberg KJ, Addis N, Betts LR, Fox C, Hobson Z, Rennison S, Trueman M, Boulton MJ. The relation between trust beliefs and loneliness during early childhood, middle childhood, and adulthood. Pers Soc Psychol Bull. 2010;36(8): 1086–1100. pmid:20585058
  5. 5. Yamagishi T. Trust as a form of social intelligence. In: Cook KS, editor. Trust in society. New York: Russell Sage Foundation; 2001. Pp. 121–147.
  6. 6. Coleman J. Foundations of social theory. Cambridge, MA: Harvard University Press; 1990.
  7. 7. Cook KS. Trust in society. New York: Russell Sage Foundation; 2001.
  8. 8. Dyer JH, Chu W. The role of trustworthiness in reducing transaction costs. In: Kramer M, editor. Organizational trust: A reader. Oxford: Oxford University Press; 2006. pp. 207–228.
  9. 9. Hirsch F. Social limits of growth. Cambridge, MA: Harvard University Press; 1976.
  10. 10. Ostrom E, Walker J. Trust and reciprocity: Interdisciplinary lessons from experimental research. New York: Russell Sage Foundation; 2003.
  11. 11. Coleman J. Social capital in the creation of human capital. Am J Sociol.1998;94: S95–S120.
  12. 12. Field J. Social capital. London: Routledge; 2008.
  13. 13. Fukuyama F. Social capital, civil society and development. Third World Q. 2001;22: 7–20.
  14. 14. Kenworthy L. Civic engagement, social capital and economic cooperation. Am Behav Sci. 1997;40: 645–656.
  15. 15. Putnam R. Bowling alone: America’s declining social capital. J Democr. 1995;6: 65–78.
  16. 16. Putnam R. Bowling alone: The collapse and revival of American community. New York: Simon and Schuster; 2000.
  17. 17. Hartford T. The economics of trust. Forbes. 7 July 2010. Available: Accessed 2014 December 9.
  18. 18. Johnson R. Rebuilding trust in finance: We can do better. 2013 Oct 25 [cited 9 December 2014]. In: Institute for New Economic Thinking Blog. [about 3 screens]. Available:
  19. 19. Knack S, Keefer P. Does social capital have an economic payoff? A cross-country investigation. Q J Econ.1997;112: 1252–1288.
  20. 20. Zak PJ, Knack S. Trust and growth. Econ J. 2001;111(470): 295–321.
  21. 21. Arrow KJ. The limits of organization. New York: Norton; 1974.
  22. 22. Twenge JM, Campbell WK, Carter NT. Declines in trust in others and confidence in institutions among American adults and late adolescents, 1972–2012. Psychol Sci. 2014;25(10): 1914–1923. pmid:25205784
  23. 23. Papaioannou E. Trust(ing) in Europe? How increased social capital can contribute to economic development. Centre for European Studies report. 2013. Available: Accessed 2014 December 10.
  24. 24. Blind PV. Building trust in government in the twenty-first century: Review of literature and emerging issues; 2006. Paper prepared for the 7th Global Forum on Reinventing Government Building Trust in Government 26–29 June 2007 in Vienna, Austria, UN Department of Economic and Social Affairs. Available: Accessed 2014 December 8.
  25. 25. Alesina A, La Ferrara E. Who trusts others? J Public Econ. 2002;85(2): 207–234.
  26. 26. Pickett K, Wilkinson R. The spirit level: Why greater equality makes societies stronger. New York: Bloomsbury Press; 2010.
  27. 27. Uslaner E. The moral foundations of trust. Cambridge: Cambridge University Press; 2002.
  28. 28. Roth F, Nowak-Lehmann D, Otter T. Has the financial crisis shattered citizens’ trust in national and European governmental institutions? Evidence from EU member states 1999–2010; 2011. CEPS Working Document 343. Available:,d.d24. Accessed 2014 December 8.
  29. 29. Putnam R. Making Democracy Work. Princeton: Princeton University Press; 1993.
  30. 30. Putnam R. E Pluribus Unum: Diversity and Community in the Twenty-First Century: The Johan Skytte Prize Lecture. Scand Polit Stud. 2007;30(2): 134–67.
  31. 31. Rahn WM, Transue JE. Social trust and value change: The decline of social capital in American youth, 1976–1995. Polit Psychol. 1998;19(3): 545–565.
  32. 32. Green CS, Bavelier D. Action-video-game experience alters the spatial resolution of vision. Psychol Sci. 2007;18(1): 88–94. pmid:17362383
  33. 33. Rogers Y. The changing face of human-computer interaction in the age of ubiquitous computing. In: Holzinger A, Miesenberger K, editors. USAB 2009, LNCS 5889. Berlin Heidelberg: Springer-Verlag; 2009. pp. 1–19.
  34. 34. Sparrow B, Liu J, Wegner DM. Google effects on memory: Cognitive consequences of having information at our fingertips. Sci. 2001;333: 776–778.
  35. 35. Short J. How much media? Report on American consumers; 2013. Available: Accessed 2015 February 13.
  36. 36. Rideout V, Foehr U, Roberts D. Generation M2: Media in the Lives of 8- to 18- Year-Olds. Menlo Park, CA: Henry J. Kaiser Family Foundation. 20 January 2010. Available: Accessed 2015 February 13.
  37. 37. Miller J. Britons spend more time on tech than asleep, study suggests. BBC. 7 Aug 2014. Available: Accessed 2015 February 13.
  38. 38. Kirsch D. A few thoughts on cognitive overload. Intellectica. 2000;1(30): 19–51.
  39. 39. Klingberg T. The overflowing brain: Information overload and the limits of working memory. Oxford: Oxford University Press; 2009.
  40. 40. Adcock A. Effects of cognitive load on processing performance; 2000. Available: Accessed 2012 July 18.
  41. 41. Hinson JM, Jameson TL, Whitney P. Somatic markers, working memory, and decision making. Cogn Affect Behav Ne. 2002;2(4): 341–353. pmid:12641178
  42. 42. Rydval O. The causal effect of cognitive abilities on economic behavior: evidence from a forecasting task with varying cognitive load; 2012. CERGE-EI Working Paper no. wp457, The Center for Economic Research and Graduate Education—Economic Institute, Prague. Available: Accessed 2014 December 7.
  43. 43. Duffy S, Smith J. Cognitive load in the multi-player prisoner’s dilemma game: Are there brains in games?; 2012. MPRA Paper no. 38825. Available: Accessed 2014 December 7 7.
  44. 44. Gilbert DT, Pelham BW, Krull DS. On cognitive busyness: When person perceivers meet persons perceived. J Pers Soc Psychol. 1988;54(5): 733–740.
  45. 45. Swann WB, Hixon G, Stein-Seroussi A, Gilbert DT. The fleeting gleam of praise: Cognitive processes underlying behavioral reactions to self-relevant feedback. J Pers Soc Psychol. 1990;59(1): 17–26. pmid:2213486
  46. 46. Bohner G, Ruder M, Erb HP. When expertise backfires: Contrast and assimilation effects in persuasion. Brit J Soc Psychol. 2002;41: 495–519. pmid:12593750
  47. 47. Gilbert DT. Thinking lightly about others: Automatic components of the social inference process. In: Uleman JS, Bargh JA, editors. Unintended thoughts. New York: Guilford Press; 1989. pp. 189–211.
  48. 48. Hernandez I, Preston JL. Disfluency disrupts the confirmation bias. J Exp Soc Psychol. 2013;49(1): 178–182.
  49. 49. Shiv B, Fedorikhin A. Heart and mind in contact: The interplay of affect and cognition in consumer decision making. J Consum Res. 1999;26(3): 278–292.
  50. 50. Ward A, Mann T. Don’t mind if I do: Disinhibited eating under cognitive load. J Pers Soc Psychol. 2000;78(4): 753–763. pmid:10794378
  51. 51. Benjamin D, Brown S, Shapiro J. Who is”Behavioral”? Cognitive ability and anomalous preferences. J Eur Econ Assoc. 2013;11: 1231–1255.
  52. 52. Becker LC. Trust as a non-cognitive security about motives. Ethics. 1996;107: 43–61.
  53. 53. Deutsch M. Trust and suspicion. J Conflict Resolut. 1958;2(4): 265–279.
  54. 54. Deutsch M. The effect of motivational orientation upon trust and suspicion. Hum Relat. 1960;13: 123–139.
  55. 55. Lewicki RJ, Bunker BB. Trust in relationships: A model of development and decline. Bunker BB, Rubin JZ, editors. In: Bunker BB, Rubin JZ, editors. Conflict, cooperation and justice: Essays inspired by the work of Morton Deutsch. San Francisco: Jossey-Bass; 1995. pp. 133–173.
  56. 56. Lewis JD, Weigert AJ. Trust as a social reality. Soc Forces. 1985;63(4): 967–985.
  57. 57. McAllister DJ. Affect- and cognition-based trust as foundations for interpersonal cooperation in organizations. Acad Manage J. 1996;38: 24–59.
  58. 58. Morrow JL, Hansen MH, Pearson AW. The cognitive and affective antecedents of general trust within cooperative organizations. J Manage Iss. 2004;14: 48–64.
  59. 59. Berg J, Dickhaut J, McCabe K. Trust, reciprocity, and social history. Game Econ Behav. 1995;10: 122–142.
  60. 60. Johnson ND, Mislin AA. Trust games: A meta-analysis. J Econ Psychol. 2011;32: 865–889.
  61. 61. Lyon F, Mollering G, Saunders MNK. Handbook of research methods on trust. Cheltenham: Edward Elgar Publishing; 2012.
  62. 62. Conway P, Gawronski B. Deontological and utilitarian inclinations in moral decision-making: A process dissociation approach. J Pers Soc Psychol. 2013;104(2): 216–235. pmid:23276267
  63. 63. Gilbert DT, Osborne RE. Thinking backward: Some curable and incurable consequences of cognitive busyness. J Pers Soc Psychol. 1989;57(6): 940–949.
  64. 64. Van den Bos K, Peters SL, Bobocel DR, Ybema JF. On preferences and doing the right thing: Satisfaction with advantageous inequity when cognitive processing is limited. J Exp Soc Psychol. 2006;42: 273–289.
  65. 65. Lalwani AK. The distinct influence of cognitive busyness and need for closure on cultural differences in socially desirable responding. J Consum Res. 2009;36(2): 305–316.
  66. 66. Szalma JL, Hancock PA. Noise effects on human performance: a meta-analytic synthesis. Psychol Bull. 2011;137: 682–707. pmid:21707130
  67. 67. Rozycka J. Zycie społeczne jako Gra. Kontekst miedzykulturowy [Social life as a Game. Cross-cultural context]. Gdansk: Wydawnictwo Uniwersytetu Gdanskiego; 2012.
  68. 68. Jaworowska A, Szustrowa T. Podrecznik do Testu Matryc Ravena: Wersja dla zaawansowanych [Raven’s Matrices test manual: Advanced version]. Warsaw: Pracownia Testow Psychologicznych PTP; 1991.