research paper_experimental_psychology

Running head: INTUITION OR REFLECTION: WHAT IS MORE FAVORABLE? 1

Intuition or Reflection: What is More Favorable When It Comes to Beliefs in God?

Iuliia Klymenko

Hunter College

INTUITION OR REFLECTION: WHAT IS MORE FAVORABLE? 2

Abstract

The purpose of our study was to examine the relationship between intuitive and reflective

thinking abilities and a belief in God. Fifty-five Hunter College students completed the Cognitive

Reflection Test (CRT; Frederick, 2005), which employs math problems that, although easily

solvable, have intuitively persuasive incorrect answers. CRT results were then compared to

beliefs in God’s existence. Females were more likely to believe in God and had greater intuitive

scores than males, who had greater reflective scores. It appears that gender and type of thought

process play a role in determining one’s belief in God.

Keywords: Cognitive Reflection Test, Religious beliefs, Intuitive reasoning, Reflective

reasoning


Intuition or Reflection: What is More Favorable When It Comes to Beliefs in God?.

A New Harris Poll (2013) finds that a strong majority (74%) of U.S. adults believe in God.

An explosion of recent research suggests that religious beliefs and behaviors are universal, arise

from deep-seated cognitive mechanisms, and were favored by natural selection over human

evolutionary history (Johnson, 2004). The term "cognition" refers to all processes by which the

sensory input is transformed, reduced, elaborated, stored, recovered, and used. According to

Ulric Neisser, it is apparent that cognition is involved in everything a human being might

possibly do; that every psychological phenomenon is a cognitive phenomenon. At the same time,

logic and reasoning skills are the abilities to reason, prioritize, and plan.

Most contemporary psychological studies have explored the competing concepts of

cognitive ability performance, as it is not always clear-cut that those who are more analytic in

thinking are prone to rejecting God (Pennycook & Cheyne, 2012). Considerable research in

recent decades has focused on two contrasting styles of problem-solving and decision-making,

often formalized as distinct reasoning types or systems (Shenhav, Rand, & Greene, ).

The first, sometimes referred to as Type 1 processing, is characterized as intuitive, fast,

unconscious, associative, and heuristic. Alternatively, problem solving and decision-making

proceed in a more analytic manner, sometimes called Type 2 processing, which tends to be more

time consuming, deliberative, and effortful.

The studies conducted by Caplovitz and Sherrow (1977) showed that intellectualism has

been found to be an important predictor of religious apostasy among college students. The

studies conduct by Pennycook and colleagues suggest that individuals with an analytic cognitive

style are more likely to reject religious beliefs simply because such beliefs are vulnerable to


being evaluated in a more analytic, logical manner (2012). Participants who gave more intuitive

answers on the CRT reported a stronger belief in God. It is therefore hypothesized that when

intuitions conflict with reasoning, less religious people will display a more analytic cognitive

style than more religious people. Demographics have been shown to be poor predictors of

religious and paranormal beliefs. The only exception is gender. Women have consistently been

shown to have more paranormal (Vyse, 1997) and religious beliefs (Stark, 2002) than men, and

we expected to find women to also have more religious beliefs in the present study. According to

Frederick (2005), women were also found to have lower scores on the CRT, with lower scores

indicative of a more intuitive, and less reflective and analytical, thought process.

In our study we decided to replicate the research of Shenhav, Rand, & Greene (2012) to

determine the connection between cognitive thinking type and a belief in God. Therefore, the

purpose of our study was to examine the relationship between the cognitive thinking styles

(intuitive versus reflective), and whether females have a higher intuitive score (i.e. a lower CRT

score) and a lower reflective score than males higher beliefs in God. We hypothesize that males

will score better on reflective style, and females will have higher intuitive score. As a result,

females will have higher beliefs in God.


Method

Participants

Fifty-five students on the Hunter College campus (38 females, 13 males, while 4 did not

specify their gender, M age = 23.55, range 18 – 41) were asked to complete a survey without

compensation.

Setting and Materials

The Cognitive Reflection Test (CRT: Frederick, 2005) was provided to students to measure

whether they preferred to answer cognitive math questions in an intuitive and spontaneous

fashion (resulting in an incorrect answer) versus in a more reflective way (resulting in the correct

answer). The CRT consisted of three items, which are math problems with intuitively attractive

but incorrect answers. For example: “A bat and a ball cost $1.10 in total. The bat costs $1.00

more than the ball. How much does the ball cost?” The response $0.10 springs immediately to

mind, but the correct answer is $0.05. Choosing the attractive but incorrect answer signals

greater reliance on intuition and less reliance on reflection. Students were also asked to complete

three questions about their belief in God’s existence, such as “How confident are you in your

belief in God?”

Experimental Design and Procedure

Participants were given an unlimited amount of time to take the CRT and religiosity survey.

After the survey, students were debriefed and explained the purpose of the study.


Results

With the collected data, the alpha level used was .05. From the survey, a total intuitive

and total reflective score was calculated based on the number of incorrect and correct answers

students provided on the CRT. Overall, using Spearman’s rank order correlation, total intuitive

and total reflective scores were negatively correlated, rs (53) = -.756, p < .001. Total intuitive

score was positively correlated with a student being female, rs (49) = .336, p < .05 while total

reflective score was correlated with a student being male, rs (51) = -.377, p < .01.

Given these correlations, an independent t-test was conducted between males and females

on their total intuitive scores. Females (M = 2.32, SD = 0.84) had significantly higher intuitive

scores then males (M =1.538, SD = 1.13), t (49) = -2.631, p < .05. A t-test was also conducted

between males and females on their total reflective scores. As a Levene’s test for equality of

variances was significant, we did not assume equal variances. Males (M =1.15, SD = 1.34) had

significantly higher reflective scores than females (M = 0.26, SD = 0.64), t(13.933) = 2.30, p

< .05.

Regarding belief in God’s existence, an independent t-test was conducted on total

intuitive scores on whether participants said they did or did not have an experience that

convinced them of God’s existence. While those who said yes had an overall higher intuitive

score (M = 2.28) than those who said no (M = 1.82), the difference was not significant, t(53) = -

1.754, p = .085. An independent t-test on this question on total reflective score was also not

significant.


An independent t-test was also conducted on question 6, which asked whether a

participants’ belief in God has increased or decreased since childhood. There was no significant

difference between total intuitive score on how one answered the question. However, total

reflective score was also looked at as Levene’s test for equality of variances was significant, we

did not assume equal variances. Those who reported that their belief in God had decreased since

childhood (M = 0.83, SD = 1.19) had significantly higher total reflective scores than those who

reported that their belief in God had increased since childhood (M = 0.27, SD = 0.64), t (31.61)

= 2.04, p = .05.

As the scale testing a range from completely believing God’s exist to completely

believing God does not exist was on an ordinal scale, a Mann-Whitney U test was used instead

for between males and females. Males (mean rank = 32.69) were significantly more likely to not

believe in the existence of God than females (mean rank = 23.71), U = 160.00, p < .05.

To test the predictability power of gender and age on the likelihood of saying they had an

experience that convinced them of God’s existence, a logistic regression was conducted, because

question 5 only had two choices as answers, and not a continuous score. Age was not a

significant predictor, but gender was (p = .040), although the model only explained 13.2% of the

variance and only approached significance (Nagelkerke R2), χ2 (2) = 5.174, p = .075. A 1-unit

increase in gender (from male to female) was associated with a 1.395 increase in the logistic

variable (likelihood of being convinced of God’s existence via an experience). In addition,

looking at the odds ratio, controlling for individual differences in age, there was a 4.034 greater

likelihood of females saying “yes” than “no”. Therefore, gender is a helpful predictor in looking

at belief in God.


We also looked at the relationship between total intuitive scores and gender, and total

reflective scores and gender. A regression found gender significantly predicted intuitive scores, b

= .777, t(48) = 2.60, p < .05, but overall did not account for a large amount of the variance (R2

= .089). Another regression using gender to predict reflective scores was also significant, b =

-.891, t(48) = -3.16, p < .01, R2 = .144.

Discussion

Gender seems to have a small but significant effect on predicting total intuitive and

reflective scores, and as well as on predicting whether someone believes in God. Gender

differences can also be seen between whether someone believes or does not believe in God’s

existence and in total intuitive and reflective scores, with females higher in the first and males

higher in the second. Those who reported a decreased belief in God since childhood tended to

have higher reflective scores, also based on the results of Shenhav, Rand, & Greene (2012). The

finding that females had higher intuitive scores while males had higher reflective scores supports

my hypothesis.

However, our study had a few limitations that may have affected its results. The first

limitation of our experiment was that for question 6 “Has your belief in God increased or

decreased since childhood?”, the only options available were a) increased or b) decreased. In the

future it could be improved by providing the option: c) ‘hasn’t changed’, since without it people

are left making a clear choice, when maybe they do not really know, like in agnosticism. We did

not also look at ethnic group and income, which may have affect on religious beliefs. Also, other

studies has been suggested that more highly educated individuals may be less likely to accept

specific religious beliefs than less educated individuals at equivalent levels of religious


engagement. In the future it will be interesting to research this phenomenon. Also, it will be

interesting to observe the tendency of political views, and how it might influence our findings

(will more conservative participants be significantly more religious?). Another possibility for

future research is to look at how education level and college major have an affect, as those with a

higher level degree or a more scientific college major may take a different view on God than the

normal population.


References

American Psychological Association. (2010). Publication Manual of the American

Psychological Association (6th ed.). Washington, D.C: American Psychological

Association.

Americans' Belief in God, Miracles and Heaven Declines. Belief in Darwin's theory of evolution

rises. (2013). Retrieved from

http://www.harrisinteractive.com/NewsRoom/HarrisPolls/tabid/447/ctl/ReadCustom

%20Default/mid/1508/ArticleId/1353/Default.aspx

Shane Frederick. Cognitive Reflection and Decision Making. Journal of Economic Perspectives

—Volume 19, Number 4—Fall 2005—Pages 25–42.

Shenhav, Amitai; Rand, David G, Greene, Joshua D. Divine intuition: Cognitive style influences

belief in God. Journal of Experimental Psychology: General, Vol 141(3), Aug 2012, 423-428.

Stark, R. 2002. Physiology and faith: Addressing the "universal" gender difference in religious

commitment. Journal for the Scientific Study of Religion 41(3), 495-507.

Vyse, S. A. (1997). Believing in magic: The psychology of superstition. New York: Oxford

University Press.

Johnson, D.D.P. The Biological and Evolutionary Logic of Human Cooperation. (Harvard

University Press, 2004).

http://www.harrisinteractive.com/NewsRoom/HarrisPolls/tabid/447/ctl/ReadCustom%20Default/mid/1508/ArticleId/1353/Default.aspx

http://www.harrisinteractive.com/NewsRoom/HarrisPolls/tabid/447/ctl/ReadCustom%20Default/mid/1508/ArticleId/1353/Default.aspx


Pennycook, G., Cheyne, J., Seli, P., Koehler, D., Fugelsang, J.(2012). Analytic cognitive style predicts

religious and paranormal belief. Department of Psychology, University of Waterloo,

Canada.


Group Statistics

Q5 N Mean Std. Deviation Std. Error Mean

Total_intuitiveno 23 1.8261 1.07247 .22363

yes 32 2.2813 .85135 .15050

Total_reflectiveno 23 .7391 1.09617 .22857

yes 32 .3438 .78738 .13919

Independent Samples Test

t-test for Equality of Means

Sig. (2-tailed) Mean Difference Std. Error

Difference

Total_intuitiveEqual variances assumed .085 -.45516 .25954

Equal variances not assumed .099 -.45516 .26955

Total_reflectiveEqual variances assumed .125 .39538 .25371

Equal variances not assumed .148 .39538 .26761



95% Confidence Interval of the

Difference

Lower Upper

Total_in Equal variances assumed -.97572 .06540


tuitive Equal variances not assumed -.99972 .08940

Total_re

flective

Equal variances assumed -.11350 .90426

Equal variances not assumed -.14653 .93729

T-Test

Group Statistics

Q6 N Mean Std. Deviation Std. Error Mean

Total_intuitivedecreased 23 1.8261 1.19286 .24873

increased 30 2.3333 .71116 .12984

Total_reflectivedecreased 23 .8261 1.19286 .24873

increased 30 .2667 .63968 .11679


Levene's Test for Equality of

Variances

t-test for Equality of

Means

F Sig. t df

Total_intuitive

Equal variances assumed 9.883 .003 -1.928 51

Equal variances not

assumed

-1.808 33.724

Total_reflective

Equal variances assumed 15.406 .000 2.194 51

Equal variances not

assumed

2.036 31.605





Difference







95% Confidence Interval of the Difference

Lower Upper

Total_intuitiveEqual variances assumed -1.03550 .02101

Equal variances not assumed -1.07762 .06313

Total_reflectiveEqual variances assumed .04750 1.07134

Equal variances not assumed -.00057 1.11941

Group Statistics

Gender N Mean Std. Deviation Std. Error Mean

Total_intuitivemale 13 1.5385 1.12660 .31246

female 38 2.3158 .84166 .13654

Total_reflectivemale 13 1.1538 1.34450 .37290

female 38 .2632 .64449 .10455



Levene's Test for Equality of

Variances

t-test for Equality of

Means

F Sig. t df

Total_intuitive

Equal variances assumed 2.726 .105 -2.631 49

Equal variances not

assumed

-2.280 16.821

Total_reflective

Equal variances assumed 17.856 .000 3.187 49

Equal variances not

assumed

2.300 13.933




Difference







95% Confidence Interval of the Difference

Lower Upper


Total_intuitiveEqual variances assumed -1.37113 -.18352

Equal variances not assumed -1.49734 -.05732

Total_reflectiveEqual variances assumed .32914 1.45223

Equal variances not assumed .05968 1.72169

Descriptive Statistics

N Mean Std. Deviation Minimum Maximum

Q4 55 3.1818 2.22020 1.00 7.00

Gender 51 .75 .440 0 1

Mann-Whitney Test

Ranks

Gender N Mean Rank Sum of Ranks

Q4

male 13 32.69 425.00

female 38 23.71 901.00

Total 51

Test Statisticsa

Q4

Mann-Whitney U 160.000

Wilcoxon W 901.000

Z -1.966


Asymp. Sig. (2-tailed) .049

Nonparametric Correlations

Correlations

Total_intuitive Total_reflective Q5

Spearman's rho

Total_intuitive

Correlation Coefficient 1.000 -.756** .222

Sig. (2-tailed) . .000 .104

N 55 55 55

Total_reflective

Correlation Coefficient -.756** 1.000 -.203

Sig. (2-tailed) .000 . .136

N 55 55 55

Q5

Correlation Coefficient .222 -.203 1.000

Sig. (2-tailed) .104 .136 .

N 55 55 55

Q6

Correlation Coefficient .186 -.247 .653**

Sig. (2-tailed) .182 .075 .000

N 53 53 53

Gender

Correlation Coefficient .336* -.377** .294*

Sig. (2-tailed) .016 .006 .036

N 51 51 51

Age Correlation Coefficient -.055 .038 -.135

Sig. (2-tailed) .703 .791 .347

N 51 51 51


Q4

Correlation Coefficient -.428** .416** -.653**

Sig. (2-tailed) .001 .002 .000

N 55 55 55

Correlations

Q6 Gender Age Q4

Spearman's rho

Total_intuitive

Correlation Coefficient .186 .336** -.055 -.428

Sig. (2-tailed) .182 .016 .703 .001

N 53 51 51 55

Total_reflective

Correlation Coefficient -.247** -.377 .038 .416

Sig. (2-tailed) .075 .006 .791 .002

N 53 51 51 55

Q5

Correlation Coefficient .653 .294 -.135 -.653**

Sig. (2-tailed) .000 .036 .347 .000

N 53 51 51 55

Q6

Correlation Coefficient 1.000 .131 -.052** -.712

Sig. (2-tailed) . .369 .722 .000

N 53 49 49 53

Gender

Correlation Coefficient .131* 1.000** -.088* -.278

Sig. (2-tailed) .369 . .541 .048

N 49 51 51 51

Age Correlation Coefficient -.052 -.088 1.000 .105

Sig. (2-tailed) .722 .541 . .464


N 49 51 51 51

Q4

Correlation Coefficient -.712** -.278** .105** 1.000**

Sig. (2-tailed) .000 .048 .464 .

N 53 51 51 55

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

Descriptives


N Minimum Maximum Mean Std. Deviation Skewness

Statistic Statistic Statistic Statistic Statistic Statistic Std. Error

Total_intuitive 55 .00 3.00 2.0909 .96748 -.951 .322

Total_reflective 55 .00 3.00 .5091 .94031 1.845 .322

Gender 51 0 1 .75 .440 -1.159 .333

Age 51 18 41 23.55 5.725 1.797 .333

Q4 55 1.00 7.00 3.1818 2.22020 .468 .322

Valid N (listwise) 51

Gender


Descriptive Statisticsa

N Minimum Maximum Mean Std. Deviation

Gender 0

Total_intuitive 4 1.00 3.00 1.7500 .95743

Total_reflective 4 .00 2.00 .7500 .95743


Gender = male



Gender 13 0 0 .00 .000

Total_intuitive 13 .00 3.00 1.5385 1.12660

Total_reflective 13 .00 3.00 1.1538 1.34450


Gender = female



Gender 38 1 1 1.00 .000

Total_intuitive 38 .00 3.00 2.3158 .84166

Total_reflective 38 .00 3.00 .2632 .64449



a. Gender = female

Logistic Regression

Case Processing Summary

Unweighted Casesa N Percent

Selected Cases

Included in Analysis 51 92.7

Missing Cases 4 7.3

Total 55 100.0

Unselected Cases 0 .0

Total 55 100.0

a. If weight is in effect, see classification table for the total number of

cases.

Dependent Variable Encoding

Original Value Internal Value


no 0

yes 1

Categorical Variables Codings

Frequency Parameter

coding

(1)

Gendermale 13 .000

female 38 1.000

Block 0: Beginning Block

Iteration Historya,b,c

Iteration -2 Log likelihood Coefficients

Constant

Step 0

1 67.352 .510

2 67.350 .521

3 67.350 .521


a. Constant is included in the model.

b. Initial -2 Log Likelihood: 67.350

c. Estimation terminated at iteration number 3

because parameter estimates changed by less

than .001.

Classification Tablea,b

Observed Predicted

Q5 Percentage

Correctno yes

Step 0Q5

no 0 19 .0

yes 0 32 100.0

Overall Percentage 62.7

a. Constant is included in the model.

b. The cut value is .500

Variables in the Equation

B S.E. Wald df Sig. Exp(B)

Step 0 Constant .521 .290 3.240 1 .072 1.684


Variables not in the Equation

Score df Sig.

Step 0Variables

Gender(1) 4.401 1 .036

Age .806 1 .369

Overall Statistics 5.211 2 .074

Block 1: Method = Enter

Iteration Historya,b,c,d

Iteration -2 Log likelihood Coefficients

Constant Gender(1) Age

Step 1

1 62.228 .551 1.304 -.043

2 62.177 .682 1.393 -.049

3 62.177 .685 1.395 -.050

4 62.177 .685 1.395 -.050

Omnibus Tests of Model Coefficients

Chi-square df Sig.

Step 1 Step 5.174 2 .075


Block 5.174 2 .075

Model 5.174 2 .075

Model Summary

Step -2 Log likelihood Cox & Snell R

Square

Nagelkerke R

Square

1 62.177a .096 .132

Hosmer and Lemeshow Test

Step Chi-square df Sig.

1 10.827 8 .212

Contingency Table for Hosmer and Lemeshow Test

Q5 = no Q5 = yes Total

Observed Expected Observed Expected

Step 1 1 4 3.910 2 2.090 6

2 4 3.527 2 2.473 6

3 2 2.320 3 2.680 5

4 1 1.724 4 3.276 5

5 0 1.445 5 3.555 5


6 3 1.084 1 2.916 4

7 3 2.090 5 5.910 8

8 0 .755 3 2.245 3

9 2 1.213 3 3.787 5

10 0 .934 4 3.066 4

Classification Tablea

Observed Predicted

Q5 Percentage

Correctno yes

Step 1Q5

no 8 11 42.1

yes 5 27 84.4

Overall Percentage 68.6


B S.E. Wald df Sig. Exp(B) 95%

C.I.for

EXP(B)

Lower

Step 1a Gender(1) 1.395 .680 4.202 1 .040 4.034 1.063

Age -.050 .053 .865 1 .352 .952 .857


Constant .685 1.356 .255 1 .613 1.985


95% C.I.for EXP(B)

Upper

Step 1a

Gender(1) 15.305

Age 1.056

Constant

Means

Case Processing Summary

Cases

Included Excluded Total

N Percent N Percent N Percent

Q4 * Gender 51 92.7% 4 7.3% 55 100.0%

Report

Q4

Gender Mean N Std. Deviation Median

male 4.0769 13 2.32600 4.0000

female 2.6842 38 2.09382 1.5000

Total 3.0392 51 2.21775 2.0000


Regression


Mean Std. Deviation N

Total_reflective .4902 .94599 51

Gender .75 .440 51

Age 23.55 5.725 51

Correlations

Total_reflective Gender Age

Pearson Correlation

Total_reflective 1.000 -.414 -.080

Gender -.414 1.000 .001

Age -.080 .001 1.000

Sig. (1-tailed)

Total_reflective . .001 .288

Gender .001 . .497

Age .288 .497 .

N

Total_reflective 51 51 51

Gender 51 51 51

Age 51 51 51

Variables Entered/Removeda


Model Variables

Entered

Variables

Removed

Method

1 Age, Genderb . Enter

a. Dependent Variable: Total_reflective

b. All requested variables entered.

Model Summary

Model R R Square Adjusted R

Square

Std. Error of the

Estimate

1 .422a .178 .144 .87531

a. Predictors: (Constant), Age, Gender

ANOVAa

Model Sum of Squares df Mean Square F Sig.

1

Regression 7.969 2 3.985 5.201 .009b

Residual 36.776 48 .766

Total 44.745 50

a. Dependent Variable: Total_reflective

b. Predictors: (Constant), Age, Gender


Coefficientsa

Model Unstandardized Coefficients Standardized

Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 1.464 .564 2.596 .012

Gender -.891 .281 -.414 -3.166 .003

Age -.013 .022 -.080 -.610 .545

Regression


Mean Std. Deviation N

Total_intuitive 2.1176 .97256 51

Gender .75 .440 51

Age 23.55 5.725 51

Correlations

Total_intuitive Gender Age

Pearson Correlation

Total_intuitive 1.000 .352 .038

Gender .352 1.000 .001

Age .038 .001 1.000

Sig. (1-tailed)

Total_intuitive . .006 .394

Gender .006 . .497

Age .394 .497 .


N

Total_intuitive 51 51 51

Gender 51 51 51

Age 51 51 51

Variables Entered/Removeda

Model Variables

Entered

Variables

Removed

Method

1 Age, Genderb . Enter

a. Dependent Variable: Total_intuitive

b. All requested variables entered.

Model Summary

Model R R Square Adjusted R

Square

Std. Error of the

Estimate

1 .354a .125 .089 .92840

ANOVAa

Model Sum of Squares df Mean Square F Sig.

1

Regression 5.921 2 2.961 3.435 .040b

Residual 41.373 48 .862

Total 47.294 50


Coefficientsa

Model Unstandardized Coefficients Standardized

Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 1.386 .598 2.318 .025

Gender .777 .298 .352 2.606 .012

Age .006 .023 .038 .282 .779

a. Dependent Variable: Total_intuitive


GGraph

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