- Email: [email protected]
Individual differences in fast-and-frugal decision making: Neuroticism and the recognition heuristic
Journal of Research in Personality 42 (2008) 1641–1645
Contents lists available at ScienceDirect
Journal of Research in Personality journal homepage: www.elsevier.com/locate/jrp
Brief Report
Individual differences in fast-and-frugal decision making: Neuroticism and the recognition heuristic q Benjamin E. Hilbig * University of Mannheim, Center for Doctoral Studies in Social and Behavioral Sciences, D7 27, 68131 Mannheim, BW, Germany
a r t i c l e
i n f o
Article history: Available online 16 July 2008
Keywords: Decision making Individual differences Big 5 Neuroticism Intelligence Recognition heuristic Fast-and-frugal heuristics
a b s t r a c t The fast-and-frugal recognition heuristic (RH) claims that people base inferences on recognition only, thus ignoring further knowledge they possess. This claim has been repeatedly challenged, while recent evidence suggests that there are substantial individual differences in adhering to the RH. However, no personality or ability factors driving (non-)use of the RH have, as yet, been identified. In the present study, neuroticism was hypothesized to be a determinant of using the RH: participants high in neuroticism were expected to avoid making use of their knowledge beyond recognition, thus avoiding a diagnostic test of their abilities. The results corroborate this hypothesis: neuroticism predicted participants’ adherence to the RH while the other Big 5 factors and intelligence yielded no additional explanatory power. Moreover, the effect of neuroticism was not mediated by the accessibility of knowledge thus lending preliminary support for the notion that this effect may, in fact, be genuinely motivational in nature. Ó 2008 Elsevier Inc. All rights reserved.
1. Introduction As part of the fast-and-frugal heuristics approach, the recognition heuristic (RH)—which claims that people make inferences in pair-wise comparisons based solely on their recognition of objects (Goldstein & Gigerenzer, 2002)—has been proposed. While a substantial debate about the properties and actual application of the RH by decision makers has taken place, both proponents and critiques of the RH have recently concluded that there are individual differences in adherence to the RH which need to be studied in more detail (Pachur, Bröder, & Marewski, 2008). On a somewhat different note, personality and motivation researchers have repeatedly shown that neuroticism influences performance behaviour (e.g. Chamorro-Premuzic & Furnham, 2003) and predicts differences in decision making (e.g. Maner et al., 2007). It is therefore investigated as a potential determinant of applying the fast-and-frugal recognition heuristic within this article. A brief introduction of the RH and an outline of the hypothesized relationships will be followed by the presentation and discussion of a study the results of which are in line with the conjectures. 1.1. The recognition heuristic For paired comparisons in any domain in which recognition of objects and the to-be-inferred criterion are related, the RH posits to choose the recognized of the two objects—given that only one is recognized. More importantly, the RH is proposed
q I thank Edgar Erdfelder, Rüdiger F. Pohl, Ken Sheldon, and two anonymous reviewers for many insightful comments on earlier versions of this manuscript. Also, I am indebted to Inga Niedtfeld and Christopher Schriner for their assistance in data collection. * Fax: +49 621 181 2042. E-mail address: [email protected]
0092-6566/$ - see front matter Ó 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.jrp.2008.07.001
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B.E. Hilbig / Journal of Research in Personality 42 (2008) 1641–1645
to be a one-reason non-compensatory strategy, claiming that search is stopped if recognition discriminates between objects. Thus, any additional knowledge about the recognized object is ignored: the decision is based on recognition alone (Goldstein & Gigerenzer, 2002). Recently, different studies have challenged the claim that recognition is used by people in a non-compensatory manner and that further knowledge is inconsequential (for overviews see Hilbig and Pohl (2008) and Pachur et al. (2008)). In sum, these studies show that the recognition cue is not used in isolation. More importantly, recent findings also indicate that there are noteworthy individual differences in adhering to the RH in the sense of relying on recognition irrespective of further knowledge (e.g. Pachur et al., 2008). However, there is a lack of studies identifying personality traits which might explain these differences—a gap I hereby hope to bridge to some small extent. 1.2. Individual differences in decision making The study of individual differences in decision making is not exactly a new endeavour though some scholars have noted a lack of systematic investigations (e.g. Shiloh, Koren, & Zakay, 2001). Especially, few studies have assessed potential links between dispositional factors and fast-and-frugal heuristics. As one of the few to look into such issues, Bröder (in press) summarized that not one of the many personality factors (including achievement motivation, the Big 5, and need for cognition) investigated in his studies predicted participant’s use of the take-the-best heuristic. Intelligence and experimental manipulations of the processing capacity were also not consistently related to preferences for particular strategies, whereas they did predict greater use of the more appropriate strategy with respect to different environmental structures. In sum, Bröder and Newell (2008) recently concluded that ‘there are large individual differences in strategy selection. The attempt to find personality dimensions as correlates of strategy preferences has not been successful so far [. . .]’ (p. 208). 1.3. Neuroticism and decision making One dispositional factor which has been linked to performance behaviour consistently, is neuroticism (Pham, 2007) or, as Humphreys and Revelle (1984) put it, ‘Anxiety is one of the most commonly accepted causes of motivationally induced deficits in performance’ (p. 175). This dispositional tendency to experience negative emotions is the probably least disputed of all personality factors (McCrae & John, 1992) and has been associated with a lack of control, low self-esteem, less successful problem solving (McCrae & Costa, 1987), and especially decision making deficits (e.g. Davis, Patte, Tweed, & Curtis, 2007). It has further been linked to risk-avoidant decision making (Lauriola & Levin, 2001) and decisional task avoidant procrastination (Milgram & Tenne, 2000). However, I am unaware of any study connecting neuroticism to fast-and-frugal heuristics. With respect to using the RH—as opposed to considering further knowledge beyond recognition—the influence of neuroticism is herein proposed to be motivational in nature: individuals high in neuroticism should be motivated to render a given task less diagnostic of their abilities by making less use of their knowledge. This is plausible since such individuals are more likely to experience hopelessness and shame upon failure and tend to generalize it to the global self (McGregor & Elliot, 2005). Consequently, they should be more likely to apply the RH. Similarly, individuals high in neuroticism could trust their knowledge less and therefore prefer a one-reason decision making strategy such as the RH. However, it is also possible that the effect of neuroticism is not genuinely motivational but rather a matter of processing capacity and the availability of knowledge. That is, neuroticism could simply hamper participants’ access to their knowledge and thus leave them with few alternatives but to apply the RH. So, in this case, the relationship between neuroticism and using the RH would be mediated by lower accessibility of knowledge.
2. Study As outlined, individuals high in neuroticism were expected to be more likely to apply the RH than other—less anxious— individuals. So, faced with the city-size task (Goldstein & Gigerenzer, 2002) which demands paired comparisons between cities and which is typically applied to study the RH, these participants were hypothesized to adhere to the RH. In statistical terms, neuroticism should be negatively related to the degree to which participants made use of further knowledge beyond recognition. As stated above, it is also possible that the effect of neuroticism on applying the RH is mediated by lower accessibility of knowledge. However, since a genuinely motivational effect of neuroticism is proposed here, it was hypothesized that the amount and validity of participants’ knowledge would not be related to neuroticism and would not provide a better explanation of participants’ use of further knowledge beyond recognition. Finally, no additional explanatory power was expected from the remaining four of the Big 5 personality factors besides neuroticism. Essentially, none of these factors should elicit a motivation to render the task less diagnostic of one’s knowledge (and thus one’s abilities) which is the mechanism proposed to explain links between neuroticism and use of the RH as outlined above. Finally, intelligence should provide no better explanation of participants’ use of knowledge, since the effect of neuroticism—if considered genuinely motivational in nature—should be independent of actual abilities. In sum, it was hypothesized that the other personality and ability traits would not contribute to explaining participants’ use of further knowledge after controlling for the predicted effects of neuroticism.
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2.1. Methods and materials Participants’ use vs. non-use of the RH was studied by means of the classical city-size task: from a list of the 62 most populous cities of the world, a sample of 11 cities was randomly selected (listed in Appendix A) which were exhaustively paired resulting in 55 comparisons for the inference task. The degree of using one’s knowledge (vs. the RH) in the paired-comparison task was assessed through individual absolute scores of the discrimination index (DI, Hilbig & Pohl, 2008): these are the (absolute) difference between the proportion of choosing the recognized object when this is a correct decision and the proportion of doing so when this represents a false inference. That is, the DI score is computed across all cases in which a participant recognizes one object but not the other. A DI score of zero is necessary for being a user of the RH, since relying solely on recognition does not allow for discriminating cases in which an inference is correct vs. false. By contrast, any DI score different from zero is sufficient to conclude that a person must have considered some other information beyond recognition. Individual scores of neuroticism as well as the remaining four of the Big 5 were assessed using the NEO personality inventory in a German short form (Borkenau & Ostendorf, 1994). Finally, intelligence was assessed using the 1-hour-form of a German general mental ability test (Berliner Intelligenz-Struktur-Test, Jäger, Süß, & Beauducel, 1997). 2.2. Participants and procedure Sixty-eight participants (39 female) were recruited from the University of Applied Sciences Cologne participating in an introductory course. Participants’ age ranged from 19 to 44 years (M = 22.7 years SD = 4.6). All assessments were carried out in a group session. Participants completed the intelligence test first followed by the NEO. Then, the city-size task was administered: participants first indicated for each pair which of the two cities was more populous on a one-page questionnaire containing all 55 pairs of cities in random order. On a second questionnaire, participants were asked to indicate for each of the cities, listed in alphabetical order, whether they recognized its name and, if so, merely recognized it or possessed further knowledge about it (cf. Pohl, 2006). After completion of the intelligence test, participants were told to work at their own pace. 2.3. Results Participants recognized M = 5.6 (SD = 1.6) of the 11 objects on average resulting in M = 27.3 (SD = 3.8) cases in which only one object was recognized. The mean recognition validity, i.e. the proportion of correct choices possible from strictly following the RH, of Alpha = .72 (SD = .14) was significantly above guessing level with t(67) = 12.7, p < .001 which is an important prerequisite of the RH. On average, participants chose the recognized object in 84% (SD = 14%) of all cases in which only one object was recognized and achieved a proportion of 67% (SD = 14%) correct decisions in these cases. Individual absolute DI scores were computed as outlined above. To test the central hypothesis that neuroticism would be negatively related to use of further knowledge, individual absolute DI scores were regressed on individual scores of neuroticism. Neuroticism predicted DI with an explained variance of R2 = .137, F(1, 62) = 9.8, p = .003, and the standardized regression coefficient of neuroticism was b = .37. From the adjusted R2 = .123, f2 = .14 was obtained, resembling a medium effect size. Thus, neuroticism was negatively related to the degree to which participants considered further knowledge beyond recognition. Secondly, it was tested whether the amount or validity of participants knowledge was linked to neuroticism and whether either provided a better explanation of DI scores. The bivariate correlation between neuroticism and the proportion of objects for which participants reported to possess further knowledge was r = .05, p = .67. Likewise, neuroticism was not related to the proportion of correct choices in knowledge cases, i.e. cases in which both objects were recognized, which is a proxy of knowledge validity (Goldstein & Gigerenzer, 2002), r = .01, p = .94. Thus, neuroticism was not linked to the amount or validity of participants knowledge. Next, both measures of knowledge were added into the regression equation of neuroticism predicting DI. As a result, R2 increased by .006 and thus insignificantly, F(2, 60) = .22, p = .81. To ensure that this finding is not merely due to insufficient statistical power, a criterion power analysis using G*Power (Faul, Erdfelder, Lang, & Buchner, 2007) was computed: For N = 64, a medium effect size (f2 = .15), a desired power of 1 b = .95, and two predictors added to one, a critical F-value of 1.4 was obtained. However, the reported F-statistic of .22 is well below this critical value which makes a refutation of the H1 possible within a conventional level of significance. Taken together, these results rule out that the effect of neuroticism is mediated by participants’ accessibility of knowledge. Finally, the hypothesis that none of the other personality or ability factors would contribute additionally to explaining participants’ use of further knowledge was tested. Again, the restricted model containing only neuroticism as a predictor competed against an unrestricted model with all other factors added—assessing the change in explained variance. When the remaining five predictors (agreeableness, conscientiousness, openness, extraversion, and intelligence) were added into the regression model, R2 changed by .04 which is an insignificant increase, F(5, 57) = .57, p = .72. Moreover, the adjusted R2, which is a less biased estimate in case of small sample sizes and an increasing number of predictors, actually decreased from .123 to .09. Taken together, these results indicate that the unrestricted model yielded no better explanation than the restricted model.1
1 Note that reversed analyses entering all other variables into the regression equation first and then adding neuroticism in a second step yielded very similar results.
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Addressing, once again, the caveat of insufficient statistical power, a criterion power analysis was computed. The resulting critical F = .97 (for N = 64, f2 = .15, and 1 b = .95) is clearly above the reported F = .57. Thus, the H1 can again be refuted with a type-IIerror probability below .05. 3. Discussion In the current study, neuroticism was investigated as potential determinant of adhering to the fast-and-frugal recognition heuristic (RH, Goldstein & Gigerenzer, 2002). Since individuals high in neuroticism are more likely to experience shame upon failure, I hypothesized that they should more strongly avoid a strategy which is diagnostic of their abilities and should thus refrain from incorporating their knowledge in inferences. The obtained results are in line with this conjecture: neuroticism explained substantial variance in the degree to which participants made use of further knowledge—as opposed to adhering to the RH (Hilbig & Pohl, 2008). Specifically, neuroticism was negatively related to the degree of incorporating knowledge beyond recognition. At the same time, neuroticism was not related to the amount or validity of participant’s knowledge and the latter did not predict use or non-use of the RH. This is in line with the assumption that the effect of neuroticism is motivational in nature rather than being mediated by the accessibility of participant’s knowledge. Finally, an unrestricted model additionally incorporating agreeableness, conscientiousness, openness, extraversion, and intelligence performed no better than the restricted model including only neuroticism. Concerning the interpretation of these results, it should be noted that the discrimination index (DI, Hilbig & Pohl, 2008) applied in the current study as a measure of using knowledge bears a caveat: a DI score of zero is necessary for being a true RH user, but it is not sufficient. By contrast, the more strongly a DI score differs from zero, the more often a participant must have incorporated some additional information. It may thereby be concluded, that the lower participants’ scores of neuroticism were, the less likely they were to adhere to the RH. This could be explained by assuming that individuals low in neuroticism did not flinch from putting their knowledge to a test. One reason why Bröder (in press) did not find similar effects of neuroticism on use of simple heuristics may be an important methodological difference between his investigations and studies of the RH: in all of Bröder’s experiments, participants first learned all the information (objects and cues) which they could later use (or ignore) when making inferences. Thus, their knowledge was exclusively induced by the experiment and may thereby not have been considered to be diagnostic of one’s abilities by any of the participants. In such a case, neuroticism would not be expected to predict use of simple heuristics vs. additional knowledge. However, since the results reported herein are correlational and thus necessary but not sufficient for the hypothesized relationships, there are plausible alternative interpretations of the findings. As such, one may claim that individuals high in neuroticism simply trust their knowledge less and therefore refrain from applying it. Alternatively, such participants could have adhered to the RH more because it seemed the faster strategy allowing them to exit the aversive choice situation more speedily. They may also be more impulsive or less patient and therefore opt for the potentially faster strategy. Finally, it is possible that administering a test of general mental abilities could have elicited anxiety or worry, thus exacerbating the effects found. The only explanation which can be ruled out at this point would attribute the effect of neuroticism on the RH to accessibility of knowledge. In light of the results reported above, accessibility of knowledge is an unlikely mediator of the impact of neuroticism on adherence to the RH. Since many alternative interpretations remain, the theoretical explanation provided herein will need to be tested more thoroughly in future research, e.g. by investigating whether participants’ mood differs before and after the decision task or by analysing decision times. Whether applying simple heuristics really is a strategy to regulate negative emotions (e.g. the fear to perform badly and thus experience shame), is thus an open question for which the reported results can only lend some preliminary support. However, obeying the recently expressed call for investigations of individual differences in fastand-frugal decision making (Pachur et al., 2008), this work may hopefully provide a first toe-hold indicating what directions future research might take. Appendix A Cities used in the study Rank
City name
Country
Population
2 11 14 19 26 34 37 42
Delhi Jakarta Kinshasa Bogotá Bangalore Saint Petersburg Chengdu Ahmedabad
India Indonesia Democratic Rep. of the Congo Colombia India Russia People’s Rep. of China India
10,927,986 8,540,121 7,785,965 7,102,602 4,931,230 4,039,745 3,950,437 3,719,710
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Appendix A (continued)
Rank
City name
Country
Population
48 52 57
Ibadan Saigon Harbin
Nigeria Vietnam People’s Rep. of China
3,565,108 3,467,331 3,229,883
Note. Cities selected randomly from Wikipedia’s list of the largest cities of the world without metropolitan areas (Wikipedia, n.d., Liste der größten Städte der Welt [list of the largest cities of the world]. Retrieved April 15, 2006, from http://de.wikipedia.org/wiki/Liste_der_gr%C3%B6%C3%9Ften_ St%C3%A4dte_der_Welt).
References Borkenau, P., & Ostendorf, F. (1994). NEO-Fünf-Faktoren-Inventar (NEO-FFI): Handanweisung. Göttingen, Germany: Hogrefe. Bröder, A. (in press). The quest for take the best—insights and outlooks from experimental research. In P. M. Todd, G. Gigerenzer, & The ABC Research Group (Eds.), Ecological rationality: Intelligence in the world. New York: Oxford University Press. Bröder, A., & Newell, B. R. (2008). Challenging some common beliefs: Empirical work within the adaptive toolbox metaphor. Judgment and Decision Making, 3(3), 205–214. Chamorro-Premuzic, T., & Furnham, A. (2003). Personality traits and academic examination performance. European Journal of Personality, 17(3), 237–250. Davis, C., Patte, K., Tweed, S., & Curtis, C. (2007). Personality traits associated with decision-making deficits. Personality and Individual Differences, 42(2), 279–290. Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. Goldstein, D. G., & Gigerenzer, G. (2002). Models of ecological rationality: The recognition heuristic. Psychological Review, 109(1), 75–90. Hilbig, B. E., & Pohl, R. F. (2008). Recognizing users of the recognition heuristic. Experimental Psychology, 55(6), 394–401. Humphreys, M. S., & Revelle, W. (1984). Personality, motivation, and performance: A theory of the relationship between individual differences and information processing. Psychological Review, 91(2), 153–184. Jäger, A. O., Süß, H.-M., & Beauducel, A. (1997). Berliner Intelligenz-Struktur-Test. Göttingen, Germany: Hogrefe. Lauriola, M., & Levin, I. P. (2001). Personality traits and risky decision-making in a controlled experimental task: An exploratory study. Personality and Individual Differences, 31(2), 215–226. Maner, J. K., Richey, J., Cromer, K., Mallott, M., Lejuez, C. W., Joiner, T. E., et al (2007). Dispositional anxiety and risk-avoidant decision-making. Personality and Individual Differences, 42(4), 665–675. McCrae, R. R., & Costa, P. T. (1987). Validation of the five-factor model of personality across instruments and observers. Journal of Personality and Social Psychology, 52(1), 81–90. McCrae, R. R., & John, O. P. (1992). An introduction to the five-factor model and its applications. Journal of Personality, 60(2), 175–215. McGregor, H. A., & Elliot, A. J. (2005). The shame of failure: Examining the link between fear of failure and shame. Personality and Social Psychology Bulletin, 31(2), 218–231. Milgram, N., & Tenne, R. (2000). Personality correlates of decisional task avoidant procrastination. European Journal of Personality, 14(2), 141–156. Pachur, T., Bröder, A., & Marewski, J. (2008). The recognition heuristic in memory-based inference: Is recognition a non-compensatory cue? Journal of Behavioral Decision Making, 21, 183–210. Pham, M. T. (2007). Emotion and rationality: A critical review and interpretation of empirical evidence. Review of General Psychology, 11(2), 155–178. Pohl, R. F. (2006). Empirical tests of the recognition heuristic. Journal of Behavioral Decision Making, 19(3), 251–271. Shiloh, S., Koren, S., & Zakay, D. (2001). Individual differences in compensatory decision-making style and need for closure as correlates of subjective decision complexity and difficulty. Personality and Individual Differences, 30(4), 699–710.
Contents lists available at ScienceDirect
Journal of Research in Personality journal homepage: www.elsevier.com/locate/jrp
Brief Report
Individual differences in fast-and-frugal decision making: Neuroticism and the recognition heuristic q Benjamin E. Hilbig * University of Mannheim, Center for Doctoral Studies in Social and Behavioral Sciences, D7 27, 68131 Mannheim, BW, Germany
a r t i c l e
i n f o
Article history: Available online 16 July 2008
Keywords: Decision making Individual differences Big 5 Neuroticism Intelligence Recognition heuristic Fast-and-frugal heuristics
a b s t r a c t The fast-and-frugal recognition heuristic (RH) claims that people base inferences on recognition only, thus ignoring further knowledge they possess. This claim has been repeatedly challenged, while recent evidence suggests that there are substantial individual differences in adhering to the RH. However, no personality or ability factors driving (non-)use of the RH have, as yet, been identified. In the present study, neuroticism was hypothesized to be a determinant of using the RH: participants high in neuroticism were expected to avoid making use of their knowledge beyond recognition, thus avoiding a diagnostic test of their abilities. The results corroborate this hypothesis: neuroticism predicted participants’ adherence to the RH while the other Big 5 factors and intelligence yielded no additional explanatory power. Moreover, the effect of neuroticism was not mediated by the accessibility of knowledge thus lending preliminary support for the notion that this effect may, in fact, be genuinely motivational in nature. Ó 2008 Elsevier Inc. All rights reserved.
1. Introduction As part of the fast-and-frugal heuristics approach, the recognition heuristic (RH)—which claims that people make inferences in pair-wise comparisons based solely on their recognition of objects (Goldstein & Gigerenzer, 2002)—has been proposed. While a substantial debate about the properties and actual application of the RH by decision makers has taken place, both proponents and critiques of the RH have recently concluded that there are individual differences in adherence to the RH which need to be studied in more detail (Pachur, Bröder, & Marewski, 2008). On a somewhat different note, personality and motivation researchers have repeatedly shown that neuroticism influences performance behaviour (e.g. Chamorro-Premuzic & Furnham, 2003) and predicts differences in decision making (e.g. Maner et al., 2007). It is therefore investigated as a potential determinant of applying the fast-and-frugal recognition heuristic within this article. A brief introduction of the RH and an outline of the hypothesized relationships will be followed by the presentation and discussion of a study the results of which are in line with the conjectures. 1.1. The recognition heuristic For paired comparisons in any domain in which recognition of objects and the to-be-inferred criterion are related, the RH posits to choose the recognized of the two objects—given that only one is recognized. More importantly, the RH is proposed
q I thank Edgar Erdfelder, Rüdiger F. Pohl, Ken Sheldon, and two anonymous reviewers for many insightful comments on earlier versions of this manuscript. Also, I am indebted to Inga Niedtfeld and Christopher Schriner for their assistance in data collection. * Fax: +49 621 181 2042. E-mail address: [email protected]
0092-6566/$ - see front matter Ó 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.jrp.2008.07.001
1642
B.E. Hilbig / Journal of Research in Personality 42 (2008) 1641–1645
to be a one-reason non-compensatory strategy, claiming that search is stopped if recognition discriminates between objects. Thus, any additional knowledge about the recognized object is ignored: the decision is based on recognition alone (Goldstein & Gigerenzer, 2002). Recently, different studies have challenged the claim that recognition is used by people in a non-compensatory manner and that further knowledge is inconsequential (for overviews see Hilbig and Pohl (2008) and Pachur et al. (2008)). In sum, these studies show that the recognition cue is not used in isolation. More importantly, recent findings also indicate that there are noteworthy individual differences in adhering to the RH in the sense of relying on recognition irrespective of further knowledge (e.g. Pachur et al., 2008). However, there is a lack of studies identifying personality traits which might explain these differences—a gap I hereby hope to bridge to some small extent. 1.2. Individual differences in decision making The study of individual differences in decision making is not exactly a new endeavour though some scholars have noted a lack of systematic investigations (e.g. Shiloh, Koren, & Zakay, 2001). Especially, few studies have assessed potential links between dispositional factors and fast-and-frugal heuristics. As one of the few to look into such issues, Bröder (in press) summarized that not one of the many personality factors (including achievement motivation, the Big 5, and need for cognition) investigated in his studies predicted participant’s use of the take-the-best heuristic. Intelligence and experimental manipulations of the processing capacity were also not consistently related to preferences for particular strategies, whereas they did predict greater use of the more appropriate strategy with respect to different environmental structures. In sum, Bröder and Newell (2008) recently concluded that ‘there are large individual differences in strategy selection. The attempt to find personality dimensions as correlates of strategy preferences has not been successful so far [. . .]’ (p. 208). 1.3. Neuroticism and decision making One dispositional factor which has been linked to performance behaviour consistently, is neuroticism (Pham, 2007) or, as Humphreys and Revelle (1984) put it, ‘Anxiety is one of the most commonly accepted causes of motivationally induced deficits in performance’ (p. 175). This dispositional tendency to experience negative emotions is the probably least disputed of all personality factors (McCrae & John, 1992) and has been associated with a lack of control, low self-esteem, less successful problem solving (McCrae & Costa, 1987), and especially decision making deficits (e.g. Davis, Patte, Tweed, & Curtis, 2007). It has further been linked to risk-avoidant decision making (Lauriola & Levin, 2001) and decisional task avoidant procrastination (Milgram & Tenne, 2000). However, I am unaware of any study connecting neuroticism to fast-and-frugal heuristics. With respect to using the RH—as opposed to considering further knowledge beyond recognition—the influence of neuroticism is herein proposed to be motivational in nature: individuals high in neuroticism should be motivated to render a given task less diagnostic of their abilities by making less use of their knowledge. This is plausible since such individuals are more likely to experience hopelessness and shame upon failure and tend to generalize it to the global self (McGregor & Elliot, 2005). Consequently, they should be more likely to apply the RH. Similarly, individuals high in neuroticism could trust their knowledge less and therefore prefer a one-reason decision making strategy such as the RH. However, it is also possible that the effect of neuroticism is not genuinely motivational but rather a matter of processing capacity and the availability of knowledge. That is, neuroticism could simply hamper participants’ access to their knowledge and thus leave them with few alternatives but to apply the RH. So, in this case, the relationship between neuroticism and using the RH would be mediated by lower accessibility of knowledge.
2. Study As outlined, individuals high in neuroticism were expected to be more likely to apply the RH than other—less anxious— individuals. So, faced with the city-size task (Goldstein & Gigerenzer, 2002) which demands paired comparisons between cities and which is typically applied to study the RH, these participants were hypothesized to adhere to the RH. In statistical terms, neuroticism should be negatively related to the degree to which participants made use of further knowledge beyond recognition. As stated above, it is also possible that the effect of neuroticism on applying the RH is mediated by lower accessibility of knowledge. However, since a genuinely motivational effect of neuroticism is proposed here, it was hypothesized that the amount and validity of participants’ knowledge would not be related to neuroticism and would not provide a better explanation of participants’ use of further knowledge beyond recognition. Finally, no additional explanatory power was expected from the remaining four of the Big 5 personality factors besides neuroticism. Essentially, none of these factors should elicit a motivation to render the task less diagnostic of one’s knowledge (and thus one’s abilities) which is the mechanism proposed to explain links between neuroticism and use of the RH as outlined above. Finally, intelligence should provide no better explanation of participants’ use of knowledge, since the effect of neuroticism—if considered genuinely motivational in nature—should be independent of actual abilities. In sum, it was hypothesized that the other personality and ability traits would not contribute to explaining participants’ use of further knowledge after controlling for the predicted effects of neuroticism.
B.E. Hilbig / Journal of Research in Personality 42 (2008) 1641–1645
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2.1. Methods and materials Participants’ use vs. non-use of the RH was studied by means of the classical city-size task: from a list of the 62 most populous cities of the world, a sample of 11 cities was randomly selected (listed in Appendix A) which were exhaustively paired resulting in 55 comparisons for the inference task. The degree of using one’s knowledge (vs. the RH) in the paired-comparison task was assessed through individual absolute scores of the discrimination index (DI, Hilbig & Pohl, 2008): these are the (absolute) difference between the proportion of choosing the recognized object when this is a correct decision and the proportion of doing so when this represents a false inference. That is, the DI score is computed across all cases in which a participant recognizes one object but not the other. A DI score of zero is necessary for being a user of the RH, since relying solely on recognition does not allow for discriminating cases in which an inference is correct vs. false. By contrast, any DI score different from zero is sufficient to conclude that a person must have considered some other information beyond recognition. Individual scores of neuroticism as well as the remaining four of the Big 5 were assessed using the NEO personality inventory in a German short form (Borkenau & Ostendorf, 1994). Finally, intelligence was assessed using the 1-hour-form of a German general mental ability test (Berliner Intelligenz-Struktur-Test, Jäger, Süß, & Beauducel, 1997). 2.2. Participants and procedure Sixty-eight participants (39 female) were recruited from the University of Applied Sciences Cologne participating in an introductory course. Participants’ age ranged from 19 to 44 years (M = 22.7 years SD = 4.6). All assessments were carried out in a group session. Participants completed the intelligence test first followed by the NEO. Then, the city-size task was administered: participants first indicated for each pair which of the two cities was more populous on a one-page questionnaire containing all 55 pairs of cities in random order. On a second questionnaire, participants were asked to indicate for each of the cities, listed in alphabetical order, whether they recognized its name and, if so, merely recognized it or possessed further knowledge about it (cf. Pohl, 2006). After completion of the intelligence test, participants were told to work at their own pace. 2.3. Results Participants recognized M = 5.6 (SD = 1.6) of the 11 objects on average resulting in M = 27.3 (SD = 3.8) cases in which only one object was recognized. The mean recognition validity, i.e. the proportion of correct choices possible from strictly following the RH, of Alpha = .72 (SD = .14) was significantly above guessing level with t(67) = 12.7, p < .001 which is an important prerequisite of the RH. On average, participants chose the recognized object in 84% (SD = 14%) of all cases in which only one object was recognized and achieved a proportion of 67% (SD = 14%) correct decisions in these cases. Individual absolute DI scores were computed as outlined above. To test the central hypothesis that neuroticism would be negatively related to use of further knowledge, individual absolute DI scores were regressed on individual scores of neuroticism. Neuroticism predicted DI with an explained variance of R2 = .137, F(1, 62) = 9.8, p = .003, and the standardized regression coefficient of neuroticism was b = .37. From the adjusted R2 = .123, f2 = .14 was obtained, resembling a medium effect size. Thus, neuroticism was negatively related to the degree to which participants considered further knowledge beyond recognition. Secondly, it was tested whether the amount or validity of participants knowledge was linked to neuroticism and whether either provided a better explanation of DI scores. The bivariate correlation between neuroticism and the proportion of objects for which participants reported to possess further knowledge was r = .05, p = .67. Likewise, neuroticism was not related to the proportion of correct choices in knowledge cases, i.e. cases in which both objects were recognized, which is a proxy of knowledge validity (Goldstein & Gigerenzer, 2002), r = .01, p = .94. Thus, neuroticism was not linked to the amount or validity of participants knowledge. Next, both measures of knowledge were added into the regression equation of neuroticism predicting DI. As a result, R2 increased by .006 and thus insignificantly, F(2, 60) = .22, p = .81. To ensure that this finding is not merely due to insufficient statistical power, a criterion power analysis using G*Power (Faul, Erdfelder, Lang, & Buchner, 2007) was computed: For N = 64, a medium effect size (f2 = .15), a desired power of 1 b = .95, and two predictors added to one, a critical F-value of 1.4 was obtained. However, the reported F-statistic of .22 is well below this critical value which makes a refutation of the H1 possible within a conventional level of significance. Taken together, these results rule out that the effect of neuroticism is mediated by participants’ accessibility of knowledge. Finally, the hypothesis that none of the other personality or ability factors would contribute additionally to explaining participants’ use of further knowledge was tested. Again, the restricted model containing only neuroticism as a predictor competed against an unrestricted model with all other factors added—assessing the change in explained variance. When the remaining five predictors (agreeableness, conscientiousness, openness, extraversion, and intelligence) were added into the regression model, R2 changed by .04 which is an insignificant increase, F(5, 57) = .57, p = .72. Moreover, the adjusted R2, which is a less biased estimate in case of small sample sizes and an increasing number of predictors, actually decreased from .123 to .09. Taken together, these results indicate that the unrestricted model yielded no better explanation than the restricted model.1
1 Note that reversed analyses entering all other variables into the regression equation first and then adding neuroticism in a second step yielded very similar results.
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Addressing, once again, the caveat of insufficient statistical power, a criterion power analysis was computed. The resulting critical F = .97 (for N = 64, f2 = .15, and 1 b = .95) is clearly above the reported F = .57. Thus, the H1 can again be refuted with a type-IIerror probability below .05. 3. Discussion In the current study, neuroticism was investigated as potential determinant of adhering to the fast-and-frugal recognition heuristic (RH, Goldstein & Gigerenzer, 2002). Since individuals high in neuroticism are more likely to experience shame upon failure, I hypothesized that they should more strongly avoid a strategy which is diagnostic of their abilities and should thus refrain from incorporating their knowledge in inferences. The obtained results are in line with this conjecture: neuroticism explained substantial variance in the degree to which participants made use of further knowledge—as opposed to adhering to the RH (Hilbig & Pohl, 2008). Specifically, neuroticism was negatively related to the degree of incorporating knowledge beyond recognition. At the same time, neuroticism was not related to the amount or validity of participant’s knowledge and the latter did not predict use or non-use of the RH. This is in line with the assumption that the effect of neuroticism is motivational in nature rather than being mediated by the accessibility of participant’s knowledge. Finally, an unrestricted model additionally incorporating agreeableness, conscientiousness, openness, extraversion, and intelligence performed no better than the restricted model including only neuroticism. Concerning the interpretation of these results, it should be noted that the discrimination index (DI, Hilbig & Pohl, 2008) applied in the current study as a measure of using knowledge bears a caveat: a DI score of zero is necessary for being a true RH user, but it is not sufficient. By contrast, the more strongly a DI score differs from zero, the more often a participant must have incorporated some additional information. It may thereby be concluded, that the lower participants’ scores of neuroticism were, the less likely they were to adhere to the RH. This could be explained by assuming that individuals low in neuroticism did not flinch from putting their knowledge to a test. One reason why Bröder (in press) did not find similar effects of neuroticism on use of simple heuristics may be an important methodological difference between his investigations and studies of the RH: in all of Bröder’s experiments, participants first learned all the information (objects and cues) which they could later use (or ignore) when making inferences. Thus, their knowledge was exclusively induced by the experiment and may thereby not have been considered to be diagnostic of one’s abilities by any of the participants. In such a case, neuroticism would not be expected to predict use of simple heuristics vs. additional knowledge. However, since the results reported herein are correlational and thus necessary but not sufficient for the hypothesized relationships, there are plausible alternative interpretations of the findings. As such, one may claim that individuals high in neuroticism simply trust their knowledge less and therefore refrain from applying it. Alternatively, such participants could have adhered to the RH more because it seemed the faster strategy allowing them to exit the aversive choice situation more speedily. They may also be more impulsive or less patient and therefore opt for the potentially faster strategy. Finally, it is possible that administering a test of general mental abilities could have elicited anxiety or worry, thus exacerbating the effects found. The only explanation which can be ruled out at this point would attribute the effect of neuroticism on the RH to accessibility of knowledge. In light of the results reported above, accessibility of knowledge is an unlikely mediator of the impact of neuroticism on adherence to the RH. Since many alternative interpretations remain, the theoretical explanation provided herein will need to be tested more thoroughly in future research, e.g. by investigating whether participants’ mood differs before and after the decision task or by analysing decision times. Whether applying simple heuristics really is a strategy to regulate negative emotions (e.g. the fear to perform badly and thus experience shame), is thus an open question for which the reported results can only lend some preliminary support. However, obeying the recently expressed call for investigations of individual differences in fastand-frugal decision making (Pachur et al., 2008), this work may hopefully provide a first toe-hold indicating what directions future research might take. Appendix A Cities used in the study Rank
City name
Country
Population
2 11 14 19 26 34 37 42
Delhi Jakarta Kinshasa Bogotá Bangalore Saint Petersburg Chengdu Ahmedabad
India Indonesia Democratic Rep. of the Congo Colombia India Russia People’s Rep. of China India
10,927,986 8,540,121 7,785,965 7,102,602 4,931,230 4,039,745 3,950,437 3,719,710
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Appendix A (continued)
Rank
City name
Country
Population
48 52 57
Ibadan Saigon Harbin
Nigeria Vietnam People’s Rep. of China
3,565,108 3,467,331 3,229,883
Note. Cities selected randomly from Wikipedia’s list of the largest cities of the world without metropolitan areas (Wikipedia, n.d., Liste der größten Städte der Welt [list of the largest cities of the world]. Retrieved April 15, 2006, from http://de.wikipedia.org/wiki/Liste_der_gr%C3%B6%C3%9Ften_ St%C3%A4dte_der_Welt).
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