The association between delay discounting and schizotypal personality characteristics in a nonclinical sample.
Immediacy theory of schizophrenia posits that the behavior of
individuals with schizophrenia is controlled to a greater degree by
stimuli in the current environment relative to individuals without
schizophrenia. Prior research supports this idea by finding that
individuals with schizophrenia display steeper rates of delay
discounting than those without it. The present study had 272
undergraduate students complete a questionnaire that assessed the
presence of schizotypal personality characteristics and then a
delay-discounting task that involved five different outcomes. Results
demonstrated that schizotypal traits were rarely correlated with rates
of discounting and that rates of discounting did not differ between
participants scoring low and high on those traits. These results,
obtained from a nonclinical sample, thus suggest that the steep rates of
discounting observed for individuals with schizophrenia in prior
research may have developed after, or as a result of, the schizophrenia
or potentially as a result of treatment.
Key words: delay discounting, schizophrenia, university students
Personality (Social aspects)
Schizophrenia (Physiological aspects)
Schizophrenia (Social aspects)
Social psychology (Research)
|Author:||Weatherly, Jeffrey N.|
|Publication:||Name: The Psychological Record Publisher: The Psychological Record Audience: Academic Format: Magazine/Journal Subject: Psychology and mental health Copyright: COPYRIGHT 2012 The Psychological Record ISSN: 0033-2933|
|Issue:||Date: Summer, 2012 Source Volume: 62 Source Issue: 3|
|Topic:||Event Code: 290 Public affairs; 310 Science & research|
|Geographic:||Geographic Scope: United States Geographic Code: 1USA United States|
Immediacy theory is a long-standing behavioral theory of
schizophrenia (Salzinger, 1984; Salzinger, Portnoy, Pisani, &
Feldman, 1970). In short, this theory posits that the behavior of
individuals diagnosed with schizophrenia is controlled, to a greater
degree than individuals without schizophrenia, by stimuli within the
individual's current environment. Phrased differently,
discriminative stimuli within the immediate environment will exert
greater stimulus control over the behavior of a person with
schizophrenia than will more distal discriminative stimuli. Immediacy
theory has been shown to be consistent with, and potentially an
explanation for, a number of empirical findings regarding schizophrenia
(L. J. Chapman, Chapman, & Miller, 1964; Leibman & Salzinger,
1998; Salzinger et al., 1970; Salzinger & Serper, 2004), although
nonconfirmatory evidence has also been reported (e.g., Johnson &
Bursill, 1973; Salzinger & Serper, 2004).
Inherent in immediacy theory is the idea that individuals with schizophrenia have a different temporal frame of reference than individuals without schizophrenia. That is, if immediate stimuli exert greater stimulus control over behavior of one population of individuals, then the inverse argument would be that temporally distal stimuli exert greater stimulus control over behavior for the alternative population. From a behavioral standpoint, these descriptions can be related to the concepts of self-control and impulsivity. Self-control can be defined as choosing a larger but more delayed reinforcing consequence over a smaller but more immediately available reinforcing consequence (see Logue, 1995, for a review). Impulsivity, on the other hand, would be making the opposite choice (see Madden & Bickel, 2010, for a recent review). Consistent with immediacy theory, evidence suggests that individuals with schizophrenia do indeed display behavioral impulsivity (e.g., Minzenberg, Yoon, & Carter, 2011) and that this tendency needs to be taken into account when evaluating their behavior (e.g., Felthous, 2008).
An increasingly popular way to measure impulsivity from a behavioral viewpoint is to study how individuals discount delayed rewards (see Madden & Bickel, 2010). Delay discounting refers to the finding that the subjective value of a reinforcing outcome tends to decrease as its delivery is delayed. Delay discounting is related to delay of gratification (Rotter, 1954), with the caveat that delay discounting is typically measured across multiple delays. The rate at which the individual discounts is then determined across all of the indifference points (i.e., subjective values) provided by the participant at each of the different delays. Rates of discounting have intrigued researchers because they have been shown to be correlated with a number of behavioral disorders, such as substance abuse (e.g., Kirby, Petry, & Bickel, 1999; see Madden & Bickel, 2010, for a review), attention-deficit/hyperactivity disorder (e.g., Williams, 2010), and pathological gambling (e.g., Dixon, Marley, & Jacobs, 2003; see Petry, 2005, for a review). Whether the process of delay discounting actually contributes to these disorders has been the focus of some debate (e.g., Bickel & Johnson, 2003; Weatherly, 2010).
Both delay of gratification and delay discounting have also been shown to be correlated with schizophrenia. In terms of delay of gratification, evidence suggests that individuals with schizophrenia perform more poorly (i.e., behave more impulsively) than individuals without it (e.g., Knolle-Veentjer, Huth, Ferstl, Aldenhoff, & Hinze-Selch, 2008). In terms of delay discounting, two studies have been conducted to date. The first was by Heerey, Robinson, McMahon, and Gold (2007). They had 42 outpatients who were diagnosed with schizophrenia and 29 control participants complete a delay-discounting task involving hypothetical monetary rewards that ranged from small (e.g., $25) to large (e.g., $85). The delays ranged up to 1 year. Results showed that, for all sizes of reward, the participants with schizophrenia displayed steeper rates of discounting than did the control participants.
More recently, Heerey, Matveeva, and Gold (2010) had 39 participants with schizophrenia and 25 control participants complete a similar delay-discounting task. Consistent with Heerey et al. (2007), participants with schizophrenia again displayed steeper rates of discounting than did controls. When asked to predict future events, the participants with schizophrenia also displayed a response bias toward more immediate events relative to the controls. Thus, the results of Heerey et al. (2007) and Heerey et al. (2010) are consistent with immediacy theory by demonstrating that individuals diagnosed with schizophrenia discount delayed rewards more steeply than do controls.
The present study was designed as an initial step toward addressing these issues. A large sample of undergraduate students completed a questionnaire designed to measure schizotypal personality characteristics. They then completed a delay-discounting task that involved five different outcomes (two sums of money, annual retirement income, obtaining one's ideal body image, and medical treatment for a serious disease). By measuring schizotypal personality characteristics in individuals who have not been diagnosed with schizophrenia, it may be possible to determine whether there is a correlation between these traits and rates of delay discounting prior to the onset of the disorder. By measuring discounting of different outcomes, it is possible to determine if the association between schizotypal personality characteristics and rates of discounting occur for only monetary outcomes or for a variety of outcomes. Based on the results of Heerey et al. (2007) and Heerey et al. (2010), it was predicted that participants scoring high on schizotypal personality characteristics would display steeper rates of delay discounting than participants scoring low on such characteristics. Based on immediacy theory, it was predicted that this relationship would be observed across all five outcomes tested in the delay-discounting task.
The original sample of participants consisted of 300 undergraduate students enrolled in a psychology course at the University of North Dakota. Data from 28 participants were discarded because those participants did not provide a value for each outcome at each delay for each outcome in the delay-discounting task, which did not allow for their rates of discounting to be computed. The final sample therefore consisted of 272 (224 females, 47 males) participants. The mean age of the participants was 19.86 years (SD = 4.03 years), and the mean self-reported grade-point average was 3.49 out of 4.00 (SD = 0.57). The sample was racially homogenous, with 250 of the 272 participants self-reporting as Caucasian. Participants received (extra) course credit in their psychology course for completing the study.
Materials and Procedure
The first item the participants viewed was an informed consent form that outlined the study as approved by the Institutional Review Board at the University of North Dakota. Participants then completed three measures. The first was a demographics form that asked about the information detailed above.
The second measure was the Schizotypal Personality Questionnaire (SPQ; Raine, 1991). The SPQ is a 74-item, yes--no format questionnaire that identifies the presence of schizotypal personality characteristics. Along with a total score, the SPQ also includes nine different subscales: (1) ideas of reference, (2) excessive social anxiety, (3) odd beliefs or magical thinking, (4) unusual perceptual experiences, (5) eccentric or odd behavior, (6) no close friends, (7) odd speech, (8) constricted affect, and (9) suspiciousness. Cronbach's alpha for the SPQ overall is 0.90 and ranges from 0.71 to 0.78 for the individual subscales (Raine, 1991). Test--retest reliability of the SPQ is good (0.82) over a 2-month interval (Raine, 1991). Convergent, discriminant, and criterion validity are also adequate or better (Raine, 1991).
The third measure was a delay-discounting task. Five outcomes were measured (being owed $1,000, being owed $100,000, annual retirement income, obtaining one's ideal body image through diet and exercise, and getting medical treatment for a serious disease). The exact wording of each question can be found in the Appendix. These five outcomes were chosen because they differed qualitatively in the reinforcing consequence and because previous research (Weatherly & Terrell, 2011; Weatherly et al., 2010) has demonstrated that they assess two different domains of consequences. Five delays (6 months, 1 year, 3 years, 5 years, & 10 years) were tested, so participants were asked a total of five questions about each outcome (25 total delay-discounting questions). The present task employed a multiple-choice format for collecting delay-discounting data (see Beck &. Triplett, 2009). That is, participants answered each question by identifying their preferred percentage of the full amount they would accept immediately from a finite list of percentages that were presented. Percentages were presented in 5% increments, with the extremes anchored by qualitative statements (e.g., 100% = willing to wait or 0% = I don't want the money) so as to provide the participants with information as to what the extreme values represented.
Participants viewed and completed all materials online via the SONA Systems, Ltd. (Version 2.72; Tallinn, Estonia) experiment management system. Participants had access to this system through their enrollment in a psychology course. This online system ensured that participants who completed the study as students enrolled in one particular psychology course were not eligible to participate in the study a second time if they happened to be enrolled in a second psychology course. Continuation beyond the informed consent form constituted providing informed consent.
For the demographic form and the SPQ, all participants completed the questions in the same predetermined order. For the delay-discounting task, the order of the five outcomes was determined randomly for every participant. The order that the five different delays were presented was also determined randomly for each participant for each outcome, with all five delays being presented before questions about the next type of outcome were asked.
Data Preparation and Analysis
Determining the rate at which discounting occurs can be accomplished in several different ways, most of which involve analyzing the data across (in the present study) the five different delays and determining a single rate of discounting. Perhaps the most popular method is to fit the data points to a hyperbolic curve using the following equation (Mazur, 1987):
V = A/(1 + kD), (1)
In Equation 1, V represents the subjective value of the delayed outcome, A represents the amount of the outcome, D represents the delay to the full outcome, and k is a free parameter. It is k that describes the rate at which discounting occurs, with higher values indicating steeper rates of discounting (i.e., large decreases in the subjective value of the outcome as it is delayed) and lower values indicating little or no discounting.
A second method for analyzing the rate of discounting is to measure the area found under the data points at each delay. The area under the curve (AUC) can be calculated using the following equation (Myerson, Green, & Warusawitharana, 2001):
[x.sub.1] - [x.sub.2] [([y.sub.1] + [y.sub.2])/2], (2)
Equation 2 measures the AUC by summing the areas of the different trapezoids formed by the subjective value of the outcome at each of the different delays. AUC values can range between 0.0 and 1.0, with small AUC values indicating more discounting and large AUC values indicating little or no discounting.
Equation 1 assumes that discounting is hyperbolic in nature, which may or may not be the case (see Madden & Bickel, 2010, for several discussions on this issue). The k parameter in Equation 1 is estimated from the data and, because it is an estimate, it will be a better estimate for the data of some participants than for others. Finally, Equation 1 produces a skewed data set because k has a lower, but no upper, bound. Thus, a logarithmic transformation is needed before parametric statistics can be conducted. Equation 2, on the other hand, is atheoretical in terms of the form discounting data should take, AUC directly represents the actual data for each participant, and the resulting AUC values do not need to be transformed. Equation 2 was utilized in the present study for those reasons. However, because Heerey et al. (2007) and Heerey et al. (2010) conducted their analyses of discounting rates on the k parameter from Equation 1, the present study also utilized Equation 1. Equation 1 k values were subjected to a logarithmic transformation before any statistical analyses were conducted, and all reported statistics involving k were conducted on the transformed k values. If a participant was willing to wait for the full amount of the outcome, regardless of the delay, a k value could not be computed using Equation 1 (although an AUC value could be computed using Equation 2). In such instances, data from these participants were excluded from the analyses of variance (ANOVAs) conducted using the data from Equation 1 but not Equation 2, which accounts for the different degrees of freedom reported below.
The mean total score on the SPQ was 16.78 (SD = 11.67). For the subscales, the means scores were 2.65 (SD = 2.34) for ideas of reference, 3.10 (SD = 2.33) for excessive social anxiety, 0.84 (SD = 1.26) for odd beliefs or magical thinking, 1.58 (SD = 1.71) for unusual perceptual experiences, 1.28 (SD = 1.84) for eccentric or odd behavior, 1.64 (SD = 1.85) for no close friends, 2.68 (SD = 2.25) for odd speech, 1.23 (SD = 1.47) for constricted affect, and 1.93 (SD = 2.02) for suspiciousness. All of these means were below those for the two samples reported by Raine (1991).
Table 1 represents the bivariate correlations observed between the SPQ scores and rates of discounting for the five different outcomes as measured by Equation 1. The present hypothesis was that high scores on the SPQ would be correlated with steep rates of discounting (i.e., positively correlated with k values). Thus, a one-tailed test was employed. Results indicate that scores on the SPQ subscales were all significantly (i.e., p < .05) positively correlated with each other and with the total score on the SPQ. Likewise, k values for discounting of the different outcomes were all significantly positively correlated. However, only five significant correlations were observed between SPQ scores and rates of discounting measure by k. Scoring high on ideas of reference was significantly correlated with steeper rates of discounting being owed $1,000 and one's annual retirement income. Scoring high on odd beliefs or magical thinking was significantly correlated with steeper rates of discounting being owed $1,000, being owed $100,000, and one's annual retirement income.
To determine whether participants who scored low and high on the SPQ differed in their rates of delay discounting, the sample was divided into quartiles, and the k values for participants scoring in the bottom quartile on the SPQ (SPQ total score [less than or equal to] 8) were compared to the k values for participants scoring in the upper quartile (SPQ total score [greater than or equal to] 23) using a two-way (Quartile x Type of Outcome) mixed-model ANOVA. Quartile served as the grouping factor and type of outcome was a repeated measure. The main effect of quartile was not significant, F < 1, [[eta].sup.2] = .006. The main effect of type of outcome, F(4, 296) = 2.15, p = .075, [[eta].sup.2] = .028, did not reach significance. The interaction between quartile and type of outcome was also not significant, F < 1, [[eta].sup.2] = .011. Thus, these results indicate that the lowest and highest scorers on the SPQ did not differ in how they discounted the five outcomes.
Table 2 represents the bivariate correlations observed between the SPQ scores and rates of discounting for the five different outcomes as measured by Equation 2. Again, the present hypothesis was that high scores on the SPQ would be correlated with steep rates of discounting (i.e., negatively correlated with AUC values) and thus a one-tailed test was employed. Similar to the results using Equation 1, the AUC values for discounting of the different outcomes were all significantly positively correlated. With Equation 2, only three significant correlations were observed between SPQ scores and rates of discounting. Scoring high on odd beliefs or magical thinking was significantly correlated with steeper rates of discounting being owed $100,000 and one's annual retirement income. Scoring high on social anxiety was significantly correlated with steeper rates of discounting obtaining one's ideal body image.
A two-way (Quartile x Type of Outcome) mixed-model ANOVA was again calculated using the AUC values of participants scoring in the bottom and top quartile of the SPQ (total). In this analysis, the main effect of quartile approached, but did not reach, significance, F(1, 134) = 3.38, p = .068, [[eta].sup.2] = .025. The main effect of type of outcome was significant, F(4, 536) = 5.74, p < .001, [[eta].sup.2] = .041, with Tukey HSD post hoc comparisons indicating that participants discounted being owed $1,000 and obtaining their ideal body image more steeply than they did their annual retirement income. The interaction between quartile and type of outcome was not significant, F < 1, [[eta].sup.2] = .003.
Both Equations 1 and 2 incorporate participants' responses across all (five) delays into a single rate of discounting. To test whether participants scoring low and high on the SPQ differed in their decisions about outcomes at the most extreme delay (i.e., 10 years), a two-way (Quartile x Type of Outcome) mixed-model ANOVA was conducted on the participants' percentage of the total amount of each outcome they would accept immediately if the full outcome was delayed 10 years (only). Again, quartile was the grouping factor and type of outcome was the repeated measure. The main effect of quartile was not significant, F(1, 134) = 2.23, p = .138, [[eta].sup.2] = .016. The main effect of type of outcome was significant, F(4, 536) = 7.52, p < .001, [[eta].sup.2] = .053. Tukey HSD post hoc comparisons indicated that participants would accept a lesser percentage of their ideal body image if delayed 10 years than they would both monetary outcomes and their annual retirement income. They would also accept a lesser percentage of perfectly successful medical treatment if delayed 10 years than they would their annual retirement income. The interaction between quartile and type of outcome was not significant, F < 1, [[eta].sup.2] = .007.
The present study was designed to determine whether the relationship between schizophrenia and delay discounting would be observed when measuring schizotypal personality characteristics in a nonclinical population. It was also an attempt to determine whether this relationship would be observed when discounting of other outcomes besides hypothetical amounts of money were measured. Total scores on the SPQ (Rainey 1991) were not significantly correlated with the rates of discounting of any of the five outcomes tested, although scores on several of the subscales of the SPQ were correlated with the discounting rates of some of the outcomes, depending on which measure of delay discounting was analyzed. Differences were observed in the rates of discounting of the different outcomes, but those differences did not vary as a function of scoring low or high on the SPQ.
One could argue that the failure to find a consistent association between SPQ scores and rates of delay discounting lies in the present delay-discounting task. That is, the present study employed a multiple-choice discounting method (e.g., Beck & Triplett, 2009) and several outcomes besides the typically used hypothetical monetary rewards. However, several aspects of the present data suggest that the present method did produce valid results. First, consistent with the magnitude effect (e.g., G. B. Chapman, 1996), steeper discounting was observed for being owed $1,000 (mean AUC = .75) than for being owed $100,000 (mean AUC = .77). Second, the pattern of discounting (i.e., little discounting of annual retirement income relative to monetary sums) was similar to that observed in other research that have studied similar outcomes (e.g., Weatherly & Terrell, 2011; Weatherly et al., 2010).
One argument that cannot be countered, however, is the idea that the value of the present outcomes masked the relationship between schizotypal traits and discounting. That is, less discounting is observed as the value of the outcome increases (e.g., G. B. Chapman, 1996). The studies that reported differences in discounting between individuals diagnosed with schizophrenia and control participants (i.e., Heerey et al., 2007; Heerey et al., 2010) had participants discount sums of money that were small relative to the ones tested in the present study. Future research will be needed to determine whether individuals with schizophrenia still display steeper rates of discounting than control participants when larger sums of money, like those used in the present study, are tested.
A second possibility for the overall lack of association between schizotypal personality characteristics and discounting could be the present sample. Mean scores on the SPQ, and all nine SPQ subscales, were below those reported by Raine (1991), suggesting that the present participants did not display a large number of schizotypal traits. This fact may have contributed to the present results. However, the present analyses were fairly liberal in the sense that one-tailed rather than two-tailed bivariate correlations were employed and discounting data were analyzed several different ways without correcting for Type I errors. Further, even for results that approached significance, the observed effect sizes were small (Cohen, 1988), suggesting that little of the variance in discounting was being accounted for by where (i.e., lower or upper quartile) participants scored on the SPQ. What cannot be countered, however, is the possibility that differences in discounting may have been observed if participants in the present sample had scored higher on the SPQ. Furthermore, it is also the case that the present study relied on an undergraduate population that was racially homogenous. Future replications would be well served to recruit a sample with greater diversity than the present one. Such replications might also want to employ, if possible, a group of participants who have been diagnosed with schizophrenia.
A third possibility for finding a lack of strong predictive relationships between scores on the SPQ and rates of delay discounting may lie with the SPQ itself. That is, although the SPQ measures schizotypal personality characteristics, it does not necessarily measure schizophrenia. Phrased differently, it is possible for an individual to score high on the SPQ and not suffer from schizophrenia. For instance, individuals with Asperger's syndrome have been shown to score higher on the SPQ than control individuals (Kanai et al., 2011), suggesting that the SPQ scores are correlated with more disorders than just schizophrenia. On the other hand, one could also argue that the failure to find strong relationships between scores on the SPQ and rates of delay discounting suggests a weak relationship between the process of delay discounting and any of the potential disorders that the SPQ scores might be correlated.
With that said, the present study was not devoid of statistically significant results. For instance, when measuring discounting with Equation 2, the SPQ subscale of social anxiety correlated with discounting of one's ideal body image but not with the other outcomes. Such a relationship makes intuitive sense. Likewise, regardless of which equation was used to measure rates of discounting, the SPQ subscale of odd beliefs or magical thinking was correlated with discounting of one's annual retirement income. This particular outcome was somewhat unique from the others in the sense that the participants had to make a decision about money and a future event (i.e., their own retirement). Finding that this particular outcome was correlated with a SPQ subscale could be seen as consistent with the results of Heerey et al. (2010), who reported that participants diagnosed with schizophrenia both discounted monetary sums more steeply and differed in their prediction of future events relative to control participants.
Overall, there would seem to be at least two interpretations of the present results. One would be that the present results provide additional information about how schizophrenia and discounting may be related. That is, by demonstrating that the relationship between schizotypal personality characteristics and rates of discounting of a variety of outcomes in a nonclinical sample is seldom significant and relatively weak when present, the current results suggest that the steep rates of discounting displayed by individuals diagnosed with schizophrenia (Heerey et al., 2010; Heerey et al., 2007) may have developed after, or as a result of, the disorder. Phrased another way, it is possible that the factors that change how an individual discounts an outcome also contribute to the development of schizophrenia, but finding that schizotypal personality characteristics are generally not related to rates of discounting prior to diagnosis of the disorder argues against that possibility.
A second possibility is that the results from research that has found steeper rates of delay discounting in individuals diagnosed with schizophrenia relative to control participants (Heerey et al., 2010; Heerey et al., 2007) do not represent a relationship between schizophrenia and discounting, but rather with another factor. The participants in Heerey et al. (2007) and Heerey et al. (2010) who had been diagnosed with schizophrenia had been undergoing treatment, and therefore it is possible that the discounting rates varied as a function of the treatment (e.g., medication) rather than the disorder. Future research will need to assess this possibility, but until it is assessed, the connection between the disorder of schizophrenia and the process involved in delay discounting should be interpreted with caution.
X time = 6 months, 1 year, 3 years, 5 years, & 10 years; wording of the questions was identical to those found in Weatherly, Terrell, & Derenne, 2010)
Someone owes you $1,000 but will not be able to repay you for x time. What is the minimum percentage of the $1,000 you would be willing to accept immediately rather than waiting x time?
100% (willing to wait) 95% 90% 85% 80% 75% 70% 65% 60% 55% 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% (I don't want the money)
Someone owes you $100,000 but will not be able to repay you for x time. What is the minimum percentage of the $100,000 you would be willing to accept immediately rather than waiting than waiting x time?
100% (willing to wait) 95% 90% 85% 80% 75% 70% 65% 60% 55% 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% (I don't want the money)
Your financial advisor informs you that you could retire at a wage of $100,000 per year but that you need to work for x time before that is possible. What is the smallest annual amount of money you would accept today rather than having to work x time?
100% (willing to wait) 95% 90% 85% 80% 75% 70% 65% 60% 55% 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% (I never want to retire)
A specific diet and exercise plan will help you attain your ideal body image if you stay on the plan for x time. However, an alternative plan is available that is less effective but gives you immediate results. What is the smallest percentage of your ideal body image (i.e., of 100%) you would settle for to get immediate results?
100% (willing to wait) 95% 90% 85% 80% 75% 70% 65% 60% 55% 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% (I don't care what I look like)
Suppose you were suffering from a serious disease, and your physician informed you that
you would need to wait x time before getting a treatment that was 100% successful. However, you could immediately begin a different treatment that has a lesser chance of success. What is the minimum percentage of success that the different treatment could have for you to choose it?
100% (willing to wait) 95% 90% 85% 80% 75% 70% 65% 60% 55% 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% (I don't want any treatment)
The author thanks Adam Derenne for his assistance with data analysis.
Correspondence concerning this article should be addressed to Jeffrey N. Weatherly, Department of Psychology, University of North Dakota, Grand Forks, ND 58202-8380. E-mail: email@example.com
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Jeffrey N. Weatherly University of North Dakota
Table 1 Bivariate Correlations Between Scores on the SPQ and Rates of Delay Discounting for the Five Different Outcomes as Measured by Equation 1 SPQ Total lofRef SocAnx OddBel UPE EOB NCF OddSp SPQ 1.000 0.726 0.646 0.519 0.736 0.652 0.638 0.733 Total ** ** ** ** ** ** ** SPQ 1.000 0.384 0.453 0.554 0.364 0.225 0.415 lofRef ** ** ** ** ** ** SPQ 1.000 0.154 0.315 0.217 0.522 0.317 SocAnx ** ** ** ** ** SPQ 1.000 0.571 0.354 0.110 0.315 OddBel ** ** * ** SPQ 1.000 0.481 0.312 0.494 UPE ** ** ** SPQ 1.000 0.288 0.583 EOB ** ** SPQ 1.000 0.334 NCF ** SPQ 1.000 OddSp SPQ ConAff SPQ Sus k $lK k $100K k Ret k Bodl k MedTrt k values ConAff Sus $1K $100K Ret Bodyl MedTrt SPQ 0.690 0.754 0,075 0.038 0.086 0.026 -0.020 Total ** ** SPQ 0.295 0.633 0.131 0.105 0.159 0.079 -0.029 lofRef ** ** * * SPQ 0.524 0.315 0.027 0.011 0.020 0.042 0.004 SocAnx ** ** SPQ 0.202 0.308 0.151 0.192 0.139 0.068 0.035 OddBel ** ** * ** * SPQ 0.377 0.521 0.097 0.079 0.089 0.054 -0.086 UPE ** ** SPQ 0.288 0.405 -0.049 -0.044 -0.019 -0.010 -0.063 EOB ** ** SPQ 0.660 0.445 -0.008 -0.038 -0.010 0.059 0.003 NCF ** ** SPQ 0.454 0.479 0.030 -0.002 -0.011 -0.069 -0.028 OddSp ** ** SPQ 1.000 0.450 0.000 0.007 0.041 0.009 0.004 ConAff ** SPQ 1.000 0.090 0.006 0.132 0.019 0.010 Sus k $lK 1.000 0.700 0.476 0.481 0.514 ** ** ** ** k 1.000 0.505 0.532 0.476 $100K ** ** ** k Ret 1.000 0.478 0.356 ** ** k Bodl 1.000 0.496 ** k 1.000 MedTrt Note. SPQ = Schizotypalty Personality Questionnaire; Ideas of Reference; SocAnx = Social Anxiety; OddBel = Odd Beliefs or Magical Thinking; UPE = Unusual Perceptual Experences; EOB = Eccentric or Odd Behavior; NCF = No Close Friends; OddSp = Odd Speech; ConAff = Constricted Affect; Sus = Suspiciousness; $1K = Owed $100,000; Ret = Annual Retirement Income; Bodyl = Ideal Body Image; MedTrt = Medical Treatment. * p < .05, one-tailed. ** p < 01, one-tailed
Table 2 Bivariate Correlations Between Scores on the SPQ and Rates of Delay Discounting for the Five Different Outcomes as Measured by Equation 2 (I.e., AUC) Total SPQ lofRef SocAnx OddBel UPE EOB NCF OddSp AUC$1K -0.021 -0.049 -0.031 -0.074 -0.053 0.092 -0.015 0,016 AUC -0.052 -0.090 -0.066 -0.133 -0.084 0.074 -0.025 -0.009 $100K * AUC -0.036 -0.076 -0.010 -0.103 -0.042 0.039 -0.002 0.058 Ret * AUC -0.037 -0.038 -0.106 -0.041 -0.071 0.026 -0.097 0.078 Bodl * AUC 0.005 0.061 -0.050 -0.010 0.070 0.038 -0.031 -0.015 MedTrt Total AUC values ConAff Sus $1K $100K Ret Bodyl MedTrt AUC$1K -0.021 -0.014 -0.055 1,000 0.692 0.422 0.439 0.462 ** ** ** ** AUC -0.052 -0.053 -0.034 0.692 1.000 0.334 0.422 0.424 $100K ** ** ** ** AUC -0.036 -0.041 -0.066 0.422 0.334 1.000 0.344 0.368 Ret ** ** ** ** AUC -0.037 -0.041 -0.038 0.439 0.422 0.344 1.000 0.447 Bodl ** ** ** ** AUC 0.005 -0.013 0.002 0.462 0.424 0.368 0.447 1.000 MedTrt ** ** ** ** Note. Correlations between SPQ scores can be found in Table 1. SPQ = Schizotypal Personality Questionnaire; AUC = Area Under the Curve; lofRef = Ideas of Reference; SocAnx = Social Anxiety; OddBel = Odd Beliefs or Magical Thinking; UPE = Unusual Perceptual Experiences; EOB = Eccentric or Odd Behavior; NCF = No Close Friends; OddSp = Odd Speech; ConAff = Constricted Affect; Sus = Suspiciousness; $1K = Owed $1,000; $100K = Owed $100,000; Ret = Annual Retirement Income; Bodyl = Ideal Body Image; MedTrt = Medical Treatment. * p < .05, one-tailed. ** p < .01, one-tailed.'
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