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Intelligence and Religiosity among Dating Site Users

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  • Ulster Institute for Social Research

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We sought to assess whether previous findings regarding the relationship between cognitive ability and religiosity could be replicated in a large dataset of online daters (maximum n = 67k). We found that self-declared religious people had lower IQs than nonreligious people (atheists and agnostics). Furthermore, within most religious groups, a negative relationship between the strength of religious conviction and IQ was observed. This relationship was absent or reversed in nonreligious groups. A factor of religiousness based on five questions correlated at −0.38 with IQ after adjusting for reliability (−0.30 before). The relationship between IQ and religiousness was not strongly confounded by plausible demographic covariates (β = −0.24 in final model versus −0.30 without covariates).
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Article
Intelligence and Religiosity among Dating Site Users
Emil O. W. Kirkegaard 1,* and Jordan Lasker 2
1Ulster Institute for Social Research, London NW26 9LQ, UK
2Independent Scholar, Atlanta, GA 30332, USA; lasker@tutanota.de
*Correspondence: emil@emilkirkegaard.dk
Received: 12 September 2019; Accepted: 18 December 2019; Published: 23 December 2019


Abstract:
We sought to assess whether previous findings regarding the relationship between cognitive
ability and religiosity could be replicated in a large dataset of online daters (maximum n=67k).
We found that self-declared religious people had lower IQs than nonreligious people (atheists and
agnostics). Furthermore, within most religious groups, a negative relationship between the strength
of religious conviction and IQ was observed. This relationship was absent or reversed in nonreligious
groups. A factor of religiousness based on five questions correlated at
0.38 with IQ after adjusting for
reliability (
0.30 before). The relationship between IQ and religiousness was not strongly confounded
by plausible demographic covariates (β=0.24 in final model versus 0.30 without covariates).
Keywords:
intelligence; religion; religious belief; atheism; agnosticism; Christianity; Catholicism;
Hinduism; Judaism; Islam; OKCupid; cognitive ability
1. Introduction
There has been long-standing interest in the relationship between religious beliefs and the behaviors
and traits of the people who hold them, including crime proneness and antisocial behavior [
1
],
personality [
2
], health [
3
], happiness, resilience [
4
], and cognitive ability or intelligence [
5
9
].
With respect to cognitive ability, over sixty studies spanning more than eight decades have consistently
found that the nonreligious and nonbelieving tended to be somewhat, perhaps 4–8 IQ points (on a
regular mean 100, SD 15 scale), more intelligent than the religious [
10
,
11
]. This result has also been
found when analyzing aggregate data at the country level of analysis (r=
0.60 between religiosity
and cognitive ability) [
10
] and across the states of the USA (r=
0.55) [
12
]. Similar patterns have been
seen with related constructs such as science knowledge [
13
]. While some studies used binary measures
of religiousness (e.g., “do you believe in God?” or “are you an atheist?”), some studies investigated the
relationship between the intensity or seriousness of religious belief and cognitive ability, generally
finding that more devout believers tended to display lower cognitive ability than more liberal believers,
excluding nonbelievers [
14
]. Those findings primarily concerned the belief in Christianity, because
they were mostly conducted on Western populations. For example, Nyborg [
15
] computed average
IQs by religious denomination for whites in the National Longitudinal Survey of Youth 1979 dataset;
these results have been reproduced in Table 1.
Psych 2020,2, 25–33; doi:10.3390/psych2010003 www.mdpi.com/journal/psych
Psych 2020,226
Table 1. Mean cognitive ability scores (IQ) for Christian denominations. From Nyborg [15].
Denomination IQ SD
Episcopal/Anglican 113.43 11.68
Jewish 112.43 13.14
Atheist 111.08 12.78
Agnostic 109.13 14.21
Methodist 108.33 13.41
Presbyterian 107.74 13.55
Lutheran 107.51 12.01
Protestant 107.42 13.38
Disciples of Christ 106.90 12.99
Roman Catholic 106.66 12.98
Other 106.43 13.65
Mormon 106.16 12.87
United Church of Christ 106.14 12.47
Bible Church 106.09 14.21
Islam 104.87 9.94
Personal Philosophy 103.98 14.54
Holiness 103.56 12.88
Baptist 102.13 13.78
Pentecostal 101.89 13.05
Total 106.09 13.57
Nyborg also ranked the denominations according to his own judgments of religious fundamentalism
and found that more liberal denominations displayed higher IQs. Nyborg’s rankings of religions by
their liberality were not objective, however, as at least one critic has pointed out [
12
]. The relationship
between religiosity and cognitive ability deserves further investigation with reported measures of religious
conviction included alongside the consideration of multiple religions instead of Christianity alone.
We aimed to do just that.
2. The Present Study
The present study examined the relationships between religious orientation, intensity of belief,
and cognitive ability in the large, diverse OKCupid dataset. We hypothesized that:
1.
Atheists and agnostics would be more intelligent than believers, with the possible exception of
believers in Judaism (Jews).
2. Within religions, more devout individuals would be less intelligent than less devout ones.
3.
For nonreligious groups (atheists/agnostics), we expected the more devout to be more intelligent.
A confirmation of our first hypothesis would replicate the findings from a large literature
(referenced above and below) that generally finds advantages in cognitive ability for both atheists
and agnostics (see above) and Jews [
16
18
]. Our second hypothesis relates to a common question
in the literature regarding how religious fundamentalism—which we indexed through stated belief
strength—is related to cognitive ability. Most studies of this question have found that both within
and between (some religions are rated as generally more fundamentalist than others) religions,
fundamentalism is related to lower cognitive ability. Our third hypothesis was not a replication.
We supposed that among non-believers, those with greater certainty in their disbelief would be more
Psych 2020,227
intelligent. The idea behind this hypothesis was that certainty in disbelief would signal convictions
regarding the validity of beliefs that cannot be addressed—perhaps through some mediator like
cognitive style or reliance on intuition that we could not assess—and that beliefs that cannot be
addressed (i.e., the existence of a god or gods) are likely to be “pseudoprofound” [
19
]. Addressing this
hypothesis more fully would require data that are unavailable in our dataset, so any results regarding
this hypothesis can only be taken tentatively.
The analysis by Kirkegaard and Bjerrekær [
20
] plotted estimated cognitive ability by religious
orientation and the relationship between strength of belief and cognitive ability irrespective of religious
group. We extended their analysis by including estimates of the relationship between strength of belief
and cognitive ability within each group and assessing the impacts of various demographic variables
such as sexual orientation, age, race/ethnicity, and country of origin on “latent religiousness,” a factor
score based on answers to five questions discussed in greater depth below.
3. Materials and Methods
We used data from the OKCupid dataset, a large (n
70k) public dataset of dating service
users [
20
]. Users of the service filled out many questions the site used in order to match them with
potential partners. There were thousands of questions concerning diverse topics, including many
devoted to religion. The data used in the present study were collected from 2014 to 2015 before being
released in anonymized form, and covered responses to roughly 2500 questions. The dataset primarily
contained subjects from English-speaking (Anglophone) countries (~85%), but also had a significant
number from other Western European countries like Germany. The sample was almost entirely Western
(~95%). As such, our sample probably suered from WEIRD sampling bias [21].
We searched the documentation of the dataset to find variables related to religion or belief in god.
We found there were two variables relating to user religious self-representation in the profile (religion
box) and five questions related to religious belief. We used a previously compiled collection of fourteen
questions used to measure cognitive ability [
20
]. While the full set of questions included in this cognitive
ability measure was small, it has been found to be related to variables with known relationships
to cognitive ability, including crime/antisocial behavior [
22
] and political interest/participation [
20
].
Paraphrased, these items included
1. Which is bigger, the earth or the sun?
2. STALE is to STEAL as 89475 is to what?
3. What is next in this series? 1, 4, 10, 19, 31, __
4. If you turn a left-handed glove inside out, it fits on your left or right hand?
5. In the line ‘’Wherefore art thou Romeo?” what does ‘’wherefore” mean?
6. How many fortnights are in a year?
7.
Half of all policemen are thieves and half of all policemen are murderers. Does it follow logically
that all policemen are criminals?
8. Which is longer, a mile or a kilometer?
9. When birds stand on power lines and don’t get hurt, it’s most likely because of what?
10.
Etymology is?
11.
If some men are doctors and some doctors are tall, does it follow that some men are tall?
12.
A little grade 10 science: what is the Ideal Gas Law?
13.
If you flipped three pennies, what would be the odds that they all came out the same?
14.
Which is the day before the day after yesterday?
In the future it may be useful to assess the relationship these items have to gold standard cognitive
test results, but that option was unavailable to us. We scored the items using item response theory with
the R mirt package [
23
]. We included only subjects who had answered at least five cognitive ability
questions in order to avoid low quality data. Given the number and ease of the questions, the possible
Psych 2020,228
selectiveness of the sample (i.e., dating site users can expect to be dierent from the general population
in various ways), and the ability to cheat on these questions, it is likely there was range restriction.
The scores from this approach were very strongly correlated with those scored using all available data
(r=0.97). The scores were then standardized to have a mean of zero and an SD of one. We used this
scale instead of the more common 100/15, because this sample was likely above average in IQ to an
unknown degree and we did not want to mislead the reader by setting 100 equal to our sample mean.
We used other demographic indicators (sex, sexual orientation, age, location, and race), which were
also given by users in their profiles as covariates.
4. Results
4.1. Religious Orientation and Certainty
During the process of building a profile, each user was given the choice to select their religious
orientation from a dropdown menu. If they did, they were given a follow-up question asking them to
describe their level of seriousness about their chosen stance on a four-point Likert-like scale with the
options of “laughing about it”, “not too serious about it”, “somewhat serious about it”, or “very serious
about it”. Figure 1depicts mean cognitive ability scores by religious orientation, coded as the
combination of position and the seriousness/strength of the (non)belief/stance.
Psych 2019, 1, FOR PEER REVIEW 4
13. If you flipped three pennies, what would be the odds that they all came out the same?
14. Which is the day before the day after yesterday?
In the future it may be useful to assess the relationship these items have to gold standard
cognitive test results, but that option was unavailable to us. We scored the items using item response
theory with the R mirt package [23]. We included only subjects who had answered at least five
cognitive ability questions in order to avoid low quality data. Given the number and ease of the
questions, the possible selectiveness of the sample (i.e., dating site users can expect to be different
from the general population in various ways), and the ability to cheat on these questions, it is likely
there was range restriction. The scores from this approach were very strongly correlated with those
scored using all available data (r = 0.97). The scores were then standardized to have a mean of zero
and an SD of one. We used this scale instead of the more common 100/15, because this sample was
likely above average in IQ to an unknown degree and we did not want to mislead the reader by
setting 100 equal to our sample mean. We used other demographic indicators (sex, sexual orientation,
age, location, and race), which were also given by users in their profiles as covariates.
4. Results
4.1. Religious Orientation and Certainty
During the process of building a profile, each user was given the choice to select their religious
orientation from a dropdown menu. If they did, they were given a follow-up question asking them
to describe their level of seriousness about their chosen stance on a four-point Likert-like scale with
the options of “laughing about it”, “not too serious about it”, “somewhat serious about it”, or “very
serious about it.'' Figure 1 depicts mean cognitive ability scores by religious orientation, coded as the
combination of position and the seriousness/strength of the (non)belief/stance.
Figure 1. Mean cognitive ability by religious orientation and certainty. Error bars are 95% confidence
intervals. Shaded regions are the 95% confidence intervals for the individual-level regression results.
Groups without at least five cases are not shown.
In our data, the nonreligious had the highest mean cognitive ability but believers in Judaism
were also notably above the sample mean. A similar pattern held inside most of the religious
orientations: the least devout were the most intelligent. Some of the groups, particularly believers in
Hinduism and Islam, were small (n <200), and thus less likely to be representative, so their results
should be taken tentatively. For the nonreligious stances, there was a weak pattern in the opposite
Figure 1.
Mean cognitive ability by religious orientation and certainty. Error bars are 95% confidence
intervals. Shaded regions are the 95% confidence intervals for the individual-level regression results.
Groups without at least five cases are not shown.
In our data, the nonreligious had the highest mean cognitive ability but believers in Judaism were
also notably above the sample mean. A similar pattern held inside most of the religious orientations:
the least devout were the most intelligent. Some of the groups, particularly believers in Hinduism
and Islam, were small (n<200), and thus less likely to be representative, so their results should be
taken tentatively. For the nonreligious stances, there was a weak pattern in the opposite direction for
agnostics such that those who expressed more certainty in their beliefs were more intelligent than
those who showed less certainty. This relationship was insignificant among atheists. It is possible
that the insignificant result for atheists can be explained by an alternative interpretation; namely,
that the correlation is there, but atheists are simply agnostics with greater certainty. The viability of
this alternative explanation is something we were unable to assess. To evaluate these patterns further,
Psych 2020,229
we split the data by religious orientation and correlated cognitive ability with certainty. These results
are given in Table 2.
Table 2.
Religious orientation and polyserial correlation of cognitive ability with certainty. While
Catholics are Christian, “Christianity” here refers to all non-Catholic Christians.
Religious Orientation NMean Cognitive Ability Correlation
with Certainty SE p
Agnosticism 5994 0.315 0.030 0.017 0.042
Atheism 6991 0.441 0.011 0.016 0.240
Buddhism 621 0.025 0.148 0.048 0.001
Catholicism 2901 0.305 0.141 0.023
<0.001
Christianity 5762 0.308 0.085 0.017
<0.001
Hinduism 168 0.320 0.236 0.100 0.009
Islam 149 0.541 0.062 0.126 0.310
Judaism 906 0.247 0.103 0.041 0.007
Other 4324 0.117 0.115 0.019
<0.001
For the large religious groups (n>500), the results were all negative (p
0.01). For the nonreligious
groups, they were closer to zero and only barely p<0.05 in the case of agnostics. Our results were
only arguably consistent with Sickles et al.’s ([
24
], p.8) hypothesis that “controlling for levels of
fundamentalist belief [is] likely to make any dierences between theists and non-theists disappear.”
As a robustness check, we carried out the analyses above in a subset of the data composed of only
white Americans. The findings for Catholics, Christians, Buddhists, Jews, and others replicated in
this subsample (all p’s <0.05, and similar rs; values given in supplementary notebook). The lack of
findings for the remaining groups could not be interpreted substantively due to very small sample sizes
(
e.g., nwhite
Hindus =9). All relationships investigated in the body of this paper were conducted for
every racial group separately in the supplement.
4.2. Demographic Covariates
To see if the relationship between religiousness and intelligence was due to demographic
confounders, we carried out a series of regressions incorporating demographic covariates. We utilized a
variety of demographic labels that had not been extensively covered in prior literature, including sexual
orientation and country of origin. Insofar as religions stigmatize nonheterosexual sexual orientations,
it might be expected that these individuals would be particularly irreligious. Alternatively, as a
response to religious or other stigmas, nonheterosexual individuals might gravitate towards spirituality
as a means of managing that even if they do not gravitate towards organized religion per se. There
are many possible hypotheses about and explanations for relationships between these variables and
religiosity, but this is not the space for their elaboration, only their investigation. For this purpose,
we created a religiousness factor based on five questions which were as follows:
1.
How important is religion/god in your life? [“extremely”, “somewhat”, “not very”, “not at all”]
2. Is your duty to religion/god the most important thing in your life? [yes/no]
3.
Would you consider dating someone whose religion or spirituality is the primary focus in their
life? [yes/no]
4. Do you believe in god? [yes/no]
5. Are you an atheist? [yes/no]
While the latter two questions may seem redundant, analysis revealed they were not,
as approximately 24% of people who answered “no” to (4) answered “no” to (5), perhaps because
Psych 2020,230
they identified as agnostic or they interpreted atheism as something other than a lack of belief in
god(s), or took it to imply other beliefs such as materialism. The items were subjected to a factor
analysis, scored, and standardized. Individuals who answered fewer than three religion questions
were excluded in order to avoid low-quality data. All items loaded as expected (i.e., positive loadings
for 1–4, and negative for 5). After this, we fit regression models to predict each subject’s level of
religiousness (as the factor score). Results are given in Table 3.
Table 3. Regression models for predicting religiousness.
Model 1 2 3 4 5
Cognitive Ability 0.30 (0.0057) 0.30 (0.0058) 0.30 (0.0058) 0.27 (0.0060) 0.24 (0.0058)
Age (nonlinear) (nonlinear) (nonlinear) (nonlinear)
Heterosexual
Female (ref) (ref) (ref)
Bisexual Female 0.29 (0.0269) 0.29 (0.0278) 0.26 (0.0269)
Homosexual
Female 0.15 (0.0516) 0.18 (0.0538) 0.18 (0.0520)
Homosexual Male 0.11 (0.0278) 0.15 (0.0280) 0.19 (0.0272)
Bisexual Male 0.31 (0.0407) 0.31 (0.0423) 0.29 (0.0409)
Heterosexual Male 0.22 (0.0139) 0.24 (0.0142) 0.24 (0.0138)
White (ref) (ref)
Mixed 0.29 (0.0195) 0.25 (0.0191)
Asian 0.27 (0.0293) 0.18 (0.0321)
Hispanic 0.40 (0.0297) 0.35 (0.0297)
Black 0.71 (0.0301) 0.64 (0.0294)
Other 0.08 (0.0360) 0.15 (0.0350)
Indian 0.30 (0.0603) 0.31 (0.0649)
Middle Eastern 0.32 (0.0948) 0.31 (0.0961)
Native American 0.31 (0.1288) 0.17 (0.1244)
Pacific Islander 0.43 (0.1369) 0.46 (0.1324)
Country/State (yes)
n37156 36436 36062 33158 33158
Adjusted R20.088 0.105 0.114 0.143 0.205
Standard errors are in parentheses. Nonlinear age was modeled using a restricted cubic spline.
Country/state eects include dummies for US and Canadian states, and countries for everywhere
else. Coecients are standardized betas. “Ref” indicates that a category was a reference category
for following variants of the same category; for instance, the reference category for the eect of
sexual orientation was heterosexual females, so heterosexual males appear less religious than they do.
The “(yes)” next to country/state indicates that those variables (of which there were many due to the
large number of regions included in the dataset; see the supplement) were included.
Across all models, religiousness was negatively associated with cognitive ability. The inclusion
of age (nonlinear), sex, sexual orientation, race, and residence (country/state) only modestly
aected this finding (
20%,
β
changed from 0.30 to 0.24). Of note is that nonheterosexual sexual
orientations, especially bisexuality, were negatively associated with religiousness in both sexes
(except for homosexual males). All nonwhite races had higher levels of religiousness in this dataset.
These associations were not meaningfully aected by the inclusion of location information. We also ran
Psych 2020,231
a model without the country/state variable and with an interaction term for whether the subject resided
in an Anglophone country, but this term was insignificant (
β
=
0.019, p=0.35). An interaction term
for Western residence was also insignificant (
β
=0.017, p=0.56), indicating that the relationship was
unaected by Western location. The full output from these models can be found in the supplementary
materials notebook.
One particular limitation of the regression models above was that Jewish ethnicity was not
separated from non-Jewish (gentile) white because the profiles did not oer an option to identify
one’s race/ethnicity as Jewish. However, another question was used to add clarity on this issue:
“Are you Jewish?” [yes/no]. While this question was itself ambiguous regarding Jewish religion or
Jewish ethnicity/race, it could be used to subset with since someone who is either should answer
in the armative. The correlation between cognitive ability and religiousness among people who
answered “yes” was
0.24 (95% confidence interval:
0.29 to
0.19), in line with the other results.
The smaller value for this subset might have been due to range restriction, since only 1490 people
answered this question.
Measurement error was likely to be a problem given our simple and limited measures. Estimated
empirical reliabilities [
25
] for the two scales were 0.63 (cognitive ability) and 0.80 (religiousness).
Correcting the observed correlation between cognitive ability and religiousness for measurement
error using the Spearman–Brown prophecy formula resulted in a corrected estimate of
0.42 (from
0.30) [
26
]. This correction was necessary, because the factor score was derived from an exploratory and
not a confirmatory factor analysis. Due to the exploratory nature of our factor analysis, we lacked more
intricate model fit measures, and we cannot contest that our variables may have been more appropriately
modeled with multiple dimensions; the fact that none of the variables had high uniqueness in the single
factor model challenges this possibility, however. Alas, we had too few indicators to begin to address
this issue. Thankfully, it is unlikely that our measures suer from issues related to sample size or model
complexity [27] because our sample size was large and a unidimensional model seemed appropriate.
5. Discussion
Previous research has documented a negative relationship between cognitive ability and religious
belief [10,11,14]. Among the religious, the strength of religiosity has also been found to be negatively
associated with cognitive ability [
15
]. Our results replicated both of these findings. On the other
hand, the relationship between cognitive ability and the strength of religious convictions was absent
or reversed in nonreligious groups like atheists and agnostics. Generally speaking, these results
supported the general thrust of Nyborg’s and many others’ findings with regards to religiousness
and cognitive ability [
10
,
15
]. The strength of the relationship in our dataset was stronger than in the
meta-analysis we cited, which found an overall mean correlation of
0.16 [
11
], whereas ours was
0.30. The meta-analysis did not utilize adjustments for measurement error, so the values may not be
comparable. However, we suspected that the dierence was mostly due to dierences in the measures
used and the sampled population. Many of the studies in the meta-analysis relied on cognitive ability
measures such as SAT scores among college students, which are likelier to have had restricted range
and which frequently feature erroneous score reporting. Consistent with this, the mean correlation
found among adult noncollege samples was
0.23, which is somewhat closer to our own. A recent
large, multisample study that utilized measures of science knowledge and religiousness also found
correlations around
0.30, though these were reduced to about
0.20 when the questions did not
include contested information (e.g., questions about global warming, and evolution) [
13
]. Item bias
still has the potential to explain part or all of these relationships, as it did recently for the results of an
actively open-minded thinking questionnaire [
28
]. It remains possible—though we were unable to test
this—that these results may be explained by other mediators such as death salience, moral concern,
conformism, attachment style, executive control, or analytical thinking style [2932].
Psych 2020,232
Limitations
There were a number of limitations to this study. First, data came from an online dating site where
people answer questions in order to be better matched with potential partners. In this way, subjects
had an incentive to answer truthfully insofar as this would enable them to be matched with similar
people. However, the medium may also result in social desirability bias in responding; this response
bias is probably more likely to be reflected in the answers to questions about one’s religion than in
answers to the cognitive ability-related questions unless cheating on these questions reflects social
desirability bias. A previous study using this dataset for criminal and antisocial behavior did not
indicate that social desirability bias was strong enough to remove expected criterion relationships [
22
].
Second, as an extension of the first limitation, the data were not particularly representative of the
national populations they were drawn from but instead reflected mainly younger persons looking
for love online. The regressions did not indicate notable biases from this sample selection. Third, the
measure of intelligence was of somewhat questionable validity since it has not been tested against
a well-validated test and is quite brief (14 items total and subjects did not usually respond to all 14).
Future studies should test this battery against well-known cognitive ability tests in order to ascertain
its psychometric qualities and potential demographic biases. Fourth, our sample is drawn mostly from
Anglophone (about 85%) and nearly entirely from Western (about 95%) countries, so it is unclear to
what degree these findings should generalize to populations not covered at all or which were only
inadequately covered by our study. We suggest that future studies examine the relationship between
cognitive ability and religiosity in countries with markedly dierent cultures than Western ones such
as Brazil or China. Fifth, previous reviews on the topic highlighted the possible mediating role of
education [
11
], but we were unable to test this mediation because our sample consisted mostly of
people who had not yet finished formal education and, as a result, the education data available to us
were not suitable for this analysis.
Supplementary Materials:
Full statistical output and R code is available at http://rpubs.com/EmilOWK/intell_rel
igion_OKCupid, data files are available following pointers in https://openpsych.net/paper/46.
Author Contributions:
Conceptualization, E.O.W.K.; methodology, E.O.W.K.; formal analysis, E.O.W.K.; data
curation, E.O.W.K.; writing—original draft preparation, E.O.W.K., J.L.; writing—review and editing, J.L.;
visualization, J.L. All authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Conflicts of Interest: The authors declare no conflicts of interest.
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... User profiles were freely accessible to all web users with a free profile at the time of data collection, and the collected data was anonymized by deleting user names and any other information which would permit identification. The analysis of such web-based, pre-existing data constitutes archival rather than human research (Bruckman, 2002;Herring, 1996;Kosinski et al., 2015) and generally does not require permission from an ethical board (Catanese et al., 2011;Gjoka et al., 2010;Kim & Escobedo-Land, 2015;Kirkegaard & Lasker, 2020;Rahman, 2012;Subirats et al., 2018). Our research did not violate specific guidelines (Kosinski et al., 2015) which would render closer ethical scrutiny necessary: ...
... Responses to a set of these questions were used to extract a latent cognitive ability factor and a latent chronotype factor using item response theory (IRT; DeMars, 2010), implemented by the mirt R-package. (For a similar approach with the same dataset, see Kirkegaard & Lasker, 2020). We used the 2PL model, allowing for items to vary in difficulty and factor loading. ...
... This demonstrated the validity of our methods of estimating chronotype and cognitive ability and allowed further fine-grained global analyses about the possible moderating effects of geography, sex and age. Importantly, the validity of our chronotype and cognitive ability measures complement similar recent research using the same dataset and the same statistical approach (Figueroa, 2018;Kirkegaard, 2018;Kirkegaard & Lasker, 2020) suggesting that using IRT on non-targeted questions may be a generally valid way of measuring psychological phenotypes. ...
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Chronotype and cognitive ability are two human phenotypes with an uneven geographic distribution due to both selective migration and causal environmental effects. In our study, we aimed to examine the relationship between geographic variables, cognitive ability and chronotype. We used a large anonymized sample (n = 25,700, mostly from the USA, UK, Canada and Australia) of dating site users to estimate chronotype and cognitive ability from questionnaire responses using item response theory. We matched each user to geographic coordinates and city size using the reported locations and geographic databases. In line with previous research we found that male sex, younger age, residence in a more populous locale, higher cognitive ability and more westward position within the same time zone were associated with later chronotype. Male sex, younger age, residence in a more populous locale, later chronotype and higher latitude were associated with higher cognitive ability, but the effect of population on chronotype and latitude on cognitive ability was only present in the USA. The relationship between age and chronotype was stronger in males, and the relationship between chronotype and cognitive ability was stronger in males and in older participants. Population density had an independent association with cognitive ability, but not chronotype. Our results confirm the uneven geographic distribution of chronotype and cognitive ability. These findings generalize across countries, but they are moderated by age and sex, suggesting both biological and cultural effects.
... (2004) examined scores on standardized tests of academic achievement, Kanazawa (2010) utilized a receptive language test, Nyborg (2009) incorporated a computerized adaptive test, and Kirkegaard and Lasker (2019) analyzed performance on items included in a questionnaire on an online dating site. While some of these approaches may be methodologically defensible in their individual studies (e.g., receptive language tests may serve as proxies for IQ, academic achievement correlates strongly with IQ; Frey & Detterman, 2004;Koenig et al., 2008;Zagar & Mead, 1983), dissimilarities among these operational definitions of IQ and measures used to assess the construct are apparent, limiting direct comparisons between studies and generalizations drawn from this body of work. ...
... Importantly, variables known to be empirically related to performance on cognitive ability tests include age (Bugg et al., 2006;Salthouse, 2014), years of formal education (Dutton & Lynn, 2014;Furnham & Cheng, 2017), socioeconomic status and income (Furnham & Cheng, 2017;Strenze, 2007), and gender (Feingold, 1992;Wai et al., 2018). Unfortunately, few studies controlled for some demographic covariates in reporting mean differences (e.g., Kirkegaard & Lasker, 2019), some acknowledge demographic covariates in other analyses but do not control for them in reported mean differences (e.g., Kanazawa, 2010), and others still do not address demographic covariates at all (e.g., Clark, 2004). As such, careful attention to theoretically and empirically relevant covariates when describing mean differences across groups is prudent whenever possible. ...
... For example, Verhage (1964, as cited in Dutton, 2014 reported means on a sample of exclusively Dutch adults, Nyborg (2009) recruited only White, American adolescents, and Clark (2004) included primarily racial/ethnic minority students from a prestigious university in the Western USA with high average IQs (M IQ = 116). Also, Kirkegaard and Lasker's (2019) sample included self-selected individuals who registered from an online dating site, who tended to be English speakers from nearly exclusively Western nations. Such specific demographic characteristics may limit the extent to which conclusions may be drawn to other specific (or general, population-based) groups of persons. ...
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An inverse relationship between religiousness/spirituality (R/S) and psychometric intelligence (IQ) is well-documented in previous literature. However, the studies that have examined group differences on IQ regarding R/S have limited generalizability. The present study contributed to the literature by evaluating IQ among participants identifying as differentially religious/spiritual (i.e., religious only, spiritual only, both religious and spiritual, or neither religious nor spiritual) and among those classified as either Christian/Catholic, Atheist, or Agnostic. Four hundred and thirty-two participants (M age = 37.9; 36% men) participated online via Amazon’s Mechanical Turk as part of a larger study and completed a brief measure of IQ, a scale of religiousness and spirituality, and a demographics questionnaire. Correlations between IQ and self-reported religiousness/spirituality were small and negative (Mean r = −0.17), consistent with previous literature. Multivariate analyses of covariance (MANCOVAs) controlling for age, gender, education, and socioeconomic status (operationalized by estimated annual household income) indicated that IQ scores tended to be lowest (p < 0.001) for “religious only” participants (estimated marginal mean [EMM] = 93.0) and highest for “neither religious nor spiritual” participants (EMM = 103.7). Furthermore, IQ scores were significantly lower (ps < 0.001) for Christian/Catholic participants (EMM = 96.7) compared to both Atheist (EMM = 104.9) and Agnostic participants (EMM = 107.5). Discussion of these findings, relationships to previous theoretical and empirical work, limitations of the present study, and directions for future inquiry are provided.
... A recent meta-analysis has, once more, found that the relationship between religious belief and IQ is approximately − 0.2 (Zuckerman et al., 2020), and a meta-analysis of measures of reflective thinking similarly found a negative association of − 0.18 (Pennycook et al., 2016). This relationship has also been replicated using the very large OKCupid dataset with 33-37 k subjects in the main regressions (Kirkegaard & Lasker, 2020) using a religiousness factor based on five questions. The standardized beta in the final model (controlling for age, sex, race, sexual orientation, and country/state) was − 0.24. ...
... So, this is congruous with Nyborg's model whereby, overall, we all need a way to make sense of our world and those who lack the intelligence to be able to do so using science will turn towards religion. Kirkegaard and Lasker (2020) replicated Nyborg's thesis using a large sample of dating users, finding that within every religious group with sufficient sample size, the least religious were the highest in intelligence. Consistent with Dutton and Van der Linden, they may also be less instinctive, due to their intelligence, meaning that their cognitive bias towards religiosity is lower. ...
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A recent study by Dutton et al. (J Relig Health 59:1567–1579. https://doi.org/10.1007/s10943-019-00926-3, 2020) found that the religiousness-IQ nexus is not on g when comparing different groups with various degrees of religiosity and the non-religious. It suggested, accordingly, that the nexus related to the relationship between specialized analytic abilities on the IQ test and autism traits, with the latter predicting atheism. The study was limited by the fact that it was on group-level data, it used only one measure of religiosity that measure may have been confounded by the social element to church membership and it involved relatively few items via which a Jensen effect could be calculated. Here, we test whether the religiousness-IQ nexus is on g with individual-level data using archival data from the Vietnam Experience Study, in which 4462 US veterans were subjected to detailed psychological tests. We used multiple measures of religiosity—which we factor-analysed to a religion-factor—and a large number of items. We found, contrary to the findings of Dutton et al. (2020), that the IQ differences with regard to whether or not subjects believed in God are indeed a Jensen effect. We also uncovered a number of anomalies, which we explore.
... Responses to a set of these questions were used to extract a latent cognitive ability factor and a latent chronotype factor using item response theory (IRT [52]), implemented by the mirt R-package. (For a similar approach with the same dataset, see [51] In the analytical sample we included participants who 1) reported a location which was successfully matched to a place name with geographical coordinates, 2) answered enough OKCupid questions to permit the estimation of both chronotype and cognitive ability We used ordinary least square (OLS) regression models to investigate the demographic and geographic correlates of cognitive ability and chronotype. STATISTICA 12 was used for all statistical analyses. ...
... First, we did not use psychometric tools to assess cognitive ability or chronotype, but instead relied on questionnaire responses. While we did not validate these directly against psychometric tools, we successfully replicated the geographic and demographic correlates of the phenotypes in question, which together with previous results from the same dataset [51,[67][68] demonstrates the validity of our method. Second, our database was not representative and the correlation between our variables of interest and likelihood of participation in the database (that is, the use of OKCupid to find romantic partners) carried the risk of collider bias [70]. ...
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Chronotype and cognitive ability are two psychological phenotypes with an uneven geographical distribution due to both selective migration and causal environmental effects. In our study we aimed to unravel the relationship between geographical variables, cognitive ability and chronotype. We used a large anonymized sample (N=25700) of dating site users to estimate chronotype and cognitive ability from questionnaire responses using item response theory. We matched each user to geographical coordinates and city size using the reported locations and geographical databases. In line with previous research we found that male sex (β=0.029), younger age (β=-0.178), residence in a more populous locale (β=0.02), higher cognitive ability (β=0.05) and more westward position within the same time zone (β=-0.04) was associated with later chronotype. Male sex (β=0.065), younger age (β=-0.04), residence in a more populous locale (β=0.149), later chronotype (β=0.051) and higher latitude (β=0.03) was associated with higher cognitive ability, but the effect of population on chronotype and latitude on cognitive ability was only present in the United States. The relationship between age and chronotype was stronger in males, and the relationship between chronotype and cognitive ability was stronger in males and in older participants. Population density had an independent association with cognitive ability, but not chronotype. Our results confirm the uneven geographical distribution of chronotype and cognitive ability. Country-wise analyses distinguish universal cultural/biological and country-specific effects. The moderating effect of age on the cognitive ability-chronotype relationship suggests that cultural rather than biological effects underlie this relationship.
... The same point applies to our measures of religious belonging, which are simple either or measures. In reality, someone can be more or less extreme or dedicated in their beliefs in the doctrines of the Church (or Catholic doctrines, etc.), and a perfect study would allow for this (see Kirkegaard & Lasker, 2020). As mentioned earlier, though it the norm to measure political ideology using a self-placement question, this approach has been found to be suboptimal since the political ideology of many people cannot be accurately summarized only in one dimension (Carmines et al., 2012;Swedlow, 2008). ...
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