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Predicting Age of Atheism: Credibility Enhancing Displays and Religious Importance, Choice, and Conflict in Family of Upbringing


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The cultural learning concept of Credibility Enhancing Displays (CREDs) concerns the extent to which behavioral models consistently live out their professed ideals. While researchers have suggested that past CRED exposure is an important variable for predicting who does and does not become a religious believer, it is unclear how CREDs relate to when a person rejects the religious beliefs modelled to them during their upbringing. Using a large sample of formerly believing atheists, two analyses assessed the ability of CREDs to predict the age at which an individual became an atheist. In the first analysis (n = 5,153), CREDs were positively associated with a delay in Age of Atheism, with family-level religious variables (Religious Importance, Religious Choice, and Religious Conflict) moderating this relationship. In the second analysis (n = 3,210), CREDs remained a stable predictor of Age of Atheism while controlling for demographics, parental quality, religious variables, relational variables, and institutional variables. Overall, while findings support a robust relation of CREDs to atheistic outcomes even when controlling for many other variables that influence religious transmission processes, they also highlight the importance of considering how such other variables modify the impact of CREDs on (non)religious outcomes.
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Religion, Brain & Behavior
ISSN: 2153-599X (Print) 2153-5981 (Online) Journal homepage:
Predicting age of atheism: credibility enhancing
displays and religious importance, choice, and
conflict in family of upbringing
Joseph Langston, David Speed & Thomas J. Coleman III
To cite this article: Joseph Langston, David Speed & Thomas J. Coleman III (2018): Predicting
age of atheism: credibility enhancing displays and religious importance, choice, and conflict in
family of upbringing, Religion, Brain & Behavior, DOI: 10.1080/2153599X.2018.1502678
To link to this article:
Published online: 30 Jul 2018.
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Predicting age of atheism: credibility enhancing displays and
religious importance, choice, and conict in family of upbringing
Joseph Langston
, David Speed
and Thomas J. Coleman III
Atheist Research Collaborative, Colorado Springs, CO, USA;
Department of Psychology, University of New
Brunswick, Saint John, NB, Canada;
Centre for Advances in Behavioural Science; Brain, Belief, and Behaviour
Research Lab, Coventry University, Coventry, UK
The cultural learning concept of Credibility Enhancing Displays (CREDs)
concerns the extent to which behavioural models consistently live out
their professed ideals. While researchers have suggested that past CRED
exposure is an important variable for predicting who does and does not
become a religious believer, it is unclear how CREDs relate to when a
person rejects the religious beliefs modelled to them during their
upbringing. Using a large sample of formerly believing atheists, two
analyses assessed the ability of CREDs to predict the age at which an
individual became an atheist. In the rst analysis (n= 5,153), CREDs were
positively associated with a delay in Age of Atheism, with family-level
religious variables (Religious Importance, Religious Choice, and Religious
Conict) moderating this relationship. In the second analysis (n= 3,210),
CREDs remained a stable predictor of Age of Atheism while controlling
for demographics, parental quality, religious variables, relational
variables, and institutional variables. Overall, while ndings support a
robust relation of CREDs to atheistic outcomes even when controlling
for many other variables that inuence religious transmission processes,
they also highlight the importance of considering how such other
variables modify the impact of CREDs on (non)religious outcomes.
Received 28 May 2018
Accepted 15 July 2018
Credibility enhancing
displays; atheism; religious
conict; religious choice;
parental quality; religious
socialization; cognitive
science of religion
1. Introduction
In order to understand the ubiquity of specic concepts and behaviours that have been referred to as
religious, the cognitive science of religion (CSR) focuses upon recurring cognitive and cultural pro-
cesses that have evolved or otherwise developed across the world and over time (Xygalatas, 2014).
Over the last few decades, researchers in this area have proposed a number of cognitive and cultural
constructs linked to varying levels of religious beliefs and ideas (cf. Barrett, 2007). Because CSR is still
a relatively new area of research, many open questions remain concerning these theoretical con-
structs, particularly how they relate to religious conditions and outcomes across dierent cultures
in the modern social landscape. One of these constructs is credibility enhancing displays (CREDs),
introduced in the work of anthropologist Henrich (2009). Derived from a cultural evolution stand-
point, CREDs imply a walk the walknotion: if individuals faithfully engage in the behaviours that
are logical expressions of their own professed beliefs, then this should increase the probability that
those who observe these behaviours will adopt the beliefs that underlie such behaviours. More pre-
cisely, CREDs are behaviours that a cultural model would not perform if they did not believe what
© 2018 Informa UK Limited, trading as Taylor & Francis Group
CONTACT Joseph Langston,
they said they did. As Gervais and colleagues (Gervais, Willard, Norenzayan, & Henrich, 2011,
p. 392) explain:
An unscrupulous [behavioural] model might knowingly transmit false information to others, perhaps to main-
tain a competitive advantage. In this case, it is important for learners to ensure that their models actually hold
the beliefs they espouse before adopting the belief themselves. Actions speak louder than words: they are great
cues of anothers underlying beliefs If models engage in behaviours that would be costly if opposing beliefs
were held (that is, if they engage in credibility-enhancing displays of their beliefs) learners can be more
condent that the model actually holds the belief, and as a result they would be more receptive to these beliefs
(Henrich, 2009).
While CREDs are related to various CSR constructs, such displays are perhaps best described
as constituting a cultural evolution construct, insofar as CREDs were partially developed in
response to, and as a critique of, CSR emphases on content biases rather than context biases
(see Gervais & Henrich, 2010, for a discussion of context versus content biases). As such, the
importance of CREDs can be understood not only in relation to the physical survival and genetic
reproduction of humans via the learning of which behaviours to perform (i.e., obtaining food;
cultural norms) or not perform (i.e., avoiding dangerous areas, foods, and animals), but also
specically in relation to social learning, in this case as it pertains to religious beliefs and beha-
viours (Bandura, 1971,2003; cf. also Dudley, 1999). Stated bluntly, we have an evolved bias
toward the learning of behaviours that keep us alive and enhance or ensure successful reproduc-
tion, but this bias also pertains to how and why we learn the various aspects of our culture from
important cultural models. Consequently, since religious socialization is central to the interge-
nerational transmission of religious beliefs and behaviours (Bengtson, Putney, & Harris, 2013),
evolved cultural learning mechanisms that bias humans toward conforming to the behaviour
of important cultural models should be more inuential than verbal expressions of religious
beliefs from such models. While research shows that either of these aspects may inuence reli-
gious outcomes among ospring (Flor & Knapp, 2001; King, Furrow, & Roth, 2002), CREDs
should play a unique role in the youthful acquisition and later sustainment of religious ideas
and practices.
Although they are not entirely without mixed results, a number of studies provide support for the
ecacy of CREDs in distinguishing between believers (i.e., theists) and nonbelievers (i.e., atheists), as
well as general levels of religiosity in national populations (Gervais & Najle, 2015; Hitzeman &
Wastell, 2017; Lanman, 2010,2012; Lanman & Buhrmester, 2016; Maij et al., 2017; Willard &
Cingl, 2017).
Because such research suggests that CREDs inuence the acquisition and intergenera-
tional transmission of religious belief, a logical implication of this is that CREDs should impact the
age at which one becomes an atheist. However, CREDs do not exist within a vacuum, but are likely
related to other important inuences on the acquisition of (religious) culture (e.g., family-level vari-
ables). That is, if CREDs are related to the age at which one stops believing in a god or gods, then
there is a question of how CREDs might fare next to, interact with, or even compete with other social
and family variables which have been shown to aect religious outcomes. Such variables would
include (among many others; cf. Clark & Worthington, 1990): (1) peer religiosity and religiosity
of social networks (Barry & Christoerson, 2014); (2) family structure (e.g. two-parent versus one
parent) (Petts, 2014); (3) parental religious homogamy (Bruce & Glendinning, 2010); (4) quality
of relationship with parents and other key social relationships (e.g., grandparents, siblings, adoles-
cent and young adulthood peers; Smith & Denton, 2005); (5) degree of personal religious choice
allowed to children by parents (Okagaki, Hammond, & Seamon, 1999; Potvin & Sloane, 1985);
(6) conict over religion in ones family during upbringing (Bengtson et al., 2013, pp. 160161;
Mahoney, 2005; Pasquale, 2009); and (7) formal religious education and institutional religious
contexts (Putney et al., 2013).
Of these factors, religious choice and religious conict are of special interest. The former may
especially be considered in post-industrial, modernized liberal democracies (Norris & Inglehart,
2011), which, purportedly due to their increased levels of existential security, are generally
characterized by elevated levels of personal choice, individualism, and secular liberal values (i.e., per-
sonal autonomy; Thiessen & Wilkins-Laamme, 2017; Voas & Doebler, 2011,2014; cf. also Berkers,
2018, in press). Lanman (2012) has suggested that increased levels of existential security should lower
the overall number of CREDs in the cultural learning environment, thus rendering belief in super-
natural agents less plausible for future generations. At any rate, insofar as the ability and eort of
parents to transmit religious values and ideologies is compromised by such environments (whether
through fewer CREDs or greater personal choice), this could inuence a population increase in athe-
ism. In line with this, Voas and Doebler (2014) suggested that religious change across generations is
closely connected to the relation between religion and childrearing values: parents may have become
less committed than in the past to ensuring religious conformity in their children, and thus perhaps
more committed to allowing their children to make their own choices about religious matters (for
supporting arguments, see also Thiessen, 2016; Manning, 2015, on nonreligious parenting and values
of choice and autonomy).
Religious choice may have an expected relationship with conict over religion in the family. If
children and adolescents in the aforementioned cultural contexts are subject to greater expectations
of personal choice and self-determination, then such an expectation, when upset by (religious)
authoritarian parenting, might lead to conict over religion and subsequently result in degrees of
alienation, personal disappointment, and rebellion, regarding both religion and ones parents.
quale (2009, p. 82) suggested that more aggressive or stringent [religious] doctrinal or behavioural
expectations will tend, on average, to produce greater numbers of individuals who experience con-
fusion, conict, or critical reaction.Similarly, in discussing families of nonreligious youth, Bengtson
et al. (2013, pp. 160161) explicitly stated that family religious conict has been identied in other
research as a common path to atheism. As they pointed out, the religious socialization eorts of
overly demanding and zealous parents can work against the goal of transmitting their religious tra-
dition to ospring. In describing such conict with parents over religion, tellingly, one nonreligious
respondents childhood was described as not allowing for individual choice in matters of religion;
this person went on to become an atheist.
Dening atheism explicitly as non-belief in a god or gods (i.e., a lack of theism; cf. also Cliteur,
2009), and using a sample consisting only of former believers, in the current paper we explored
the relationship between CREDs and the age of atheism using two main analyses. First, we sought
to determine if CREDs predicted age of atheism, and whether this relationship would be inuenced
by three specic family- and parent-level religious variables (i.e., religious importance, religious
choice, and religious conict). As part of this analysis, we also tested statistical interactions between
CREDs and religious importance, religious choice, and religious conict.
Second, we investigated whether the relationship between CREDs and age of atheism was sub-
stantially attenuated or eliminated by the inclusion of a broader assortment of other social and family
covariates (as enumerated above) which have been shown to aect the acquisition and transmission
of religious beliefs. Because CREDs are related to broader (religious) socialization, there is a question
of the relationship to CREDs of other variables which are regarded as mainstays of the religious
socialization process. While we would expect higher levels of parental religious CREDs to be associ-
ated with a delay in the onsetof atheism, little is known about the inuence of other candidate
family, social, and religion variables in relation to CREDs, regarding their collective impact on
age of atheism.
2. Methods
2.1. Participants
Data were collected via an online Qualtrics survey from September to October in 2017. The study
was advertised as research into how family and social processes inuence becoming an atheist.
We explicitly stated that a person was not eligible for the study if they (a) currently believed in
the existence of god(s), or if they (b) believed in a spiritual or higher power. We included two general
instructions prior to the survey, quoted as follows:
(1) In the questions and answers below, we use the words godand gods. Please interpret these
terms to stand for whatever image or idea you primarily associate with them, such as a specic
god or gods you once believed existed, or a specic god or gods that other people believe exist(s).
(2) At least one existing research study indicates that people who call themselves atheistsdo not
uniformly agree on the denition of the term. Other research indicates that not every person
who either (a) believes that god or gods do not exist or (b) lacks a belief in god or gods, self-
identies or uses the label atheistfor themselves. However, for the purposes of this current
study, we use the term nonbelieverand we refer broadly to not believing inthe existence
of god or gods (see #1, above).
We sent our survey to more than 100 atheist, secular, and freethought organizations across a glo-
bal setting, to include social media platforms (e.g., Facebook, Reddit). After removing incomplete
cases and those who incorrectly answered any one of three attention checkquestions, a total of
7,173 respondents remained. In the current study we report on a maximum total of 5,153 respon-
dents who answered all questions of interest. Because our second main analysis included many
additional variables, we provide descriptive statistics for both samples in Table 1, as they were
used in each analysis.
A special note of interpretive caution regarding our sample must be sounded before we can con-
tinue. As one of our reviewers pointed out, our sample was largely acquired via organizational chan-
nels, and thus likely does not represent the growing collection of nonbelievers in Western societies
more generally. In other words, they would be highly atypical outside of contexts and countries
where religionis not (or is no longer) a salient part of history and culture (Garcia & Blankholm,
2016; Zuckerman, 2012). As a result, our sample is likely mostly constituted by persons for whom
religious nonbelief is an important component of their social identities, as they were ultimately
self-selected into a study targeted at a specic subcultural group within the broader atheist milieu.
Consequently, we are probably not studying the kind of nonbelievers that would turn up in a nation-
ally representative probability sample. In this sense, our analysis would most properly be regarded as
centreing upon, not generic atheists or atheism per se, but on the explicit rejection of prior religious
beliefs, or self-aware atheist converts, and the age at which they actively rejected the religion of their
2.2. Measures
2.2.1. Age of atheism
The dependent variable was captured with the question, At what age did you no longer believe in
god(s)?. Because we sought to recruit only those who had once been believers in a god or gods but
were no longer, we chose to exclude from analyses those respondents who reported becoming an
atheist prior to the age of ve.
2.2.2. Demographic covariates
Sex (ref = female), current age, race (ref = non-white), education (ref = high school or less), marital
status (ref = single/never married), religious upbringing (ref = None) and country of residence (ref =
United States; four other categories included Canada, Great Britain, Australia, and Other) were all
included as covariates in predictive analyses. Due to the fact that the Othercountry category
was large (75 countries in total), its meaningfulness as an analytical category in our models should
be considered limited.
Table 1. Descriptive statistics for Model 1 and Model 2.
Model 1
(n= 5,153)
Model 2
(n= 3,210)
M (SD) % M (SD) %
Age of Atheism 23.8 (10.8) 24.1 (10.8)
Other 1.5 1.5
Male 43.2 42.3
Female 55.4 56.2
Age 41.3 (14.8) 41.2 (14.9)
White 91.0 91.0
Non-white 9.0 9.0
High School 6.5 6.6
Some Post-secondary 19.7 19.3
Post-Secondary 42.7 43.0
Graduate School 26.8 26.7
Other 4.2 4.4
Marital Status
Single 18.7 18.3
Married/Common-Law 67.8 68.0
Widowed/Separated/Div. 10.8 11.1
Other 2.8 2.7
Religious Upbringing
None 2.4 2.2
Christian 90.0 90.6
Jewish 1.6 1.5
Muslim 0.85 0.84
Other 5.1 5.0
United States 86.4 86.6
Canada 4.4 4.4
United Kingdom 1.3 1.4
Australia 1.7 1.4
Other 6.3 6.1
Religious Importance 5.2 (2.0) 5.3 (2.0)
Religious Choice 3.5 (2.4) 3.4 (2.3)
Religious Conict 3.5 (2.2) 3.5 (2.2)
CREDs 26.3 (10.8) 26.8 (10.8)
Mother Strict 4.4 (1.6)
Mother Warm 5.0 (1.8)
Mother Talk 4.1 (1.9)
Dad Strict 4.6 (1.8)
Dad Warm 3.9 (1.8)
Dad Talk 3.4 (1.9)
Parental Relationship
Lived with parents 76.2
Did not live with parents 23.8
Parental Religion
Parents dierent relig. 17.2
Parents same relig. 82.8
Non-Believing Friends
Knew other atheists 29.7
Did not know atheists 70.3
Peer Religiosity Index 1 8.9 (6.1)
Peer Religiosity Index 2 9.2 (5.4)
Worship service attend
No 56.3
Yes 37.4
Stopped before age 13 6.3
Years religious school 3.4 (4.9)
2.2.3. Quality of parental relationships
Six questions (cf. Hunsberger, Pratt, & Pancer, 2002) assessed parental quality: While you were
growing up, would you say that your [Mother or Father] was (1) Easy to Talk With, (2) Strict,
and (3) Warm and Loving.Each of these was rated on a seven-point Likert scale (1 = Not at all,
4 = Somewhat, 7 = Completely). In subsequent analyses, Strictness ratings were reverse coded.
2.2.4. Family religion variables
Three items addressed various aspects of religious dynamics in ones family of upbringing, including
Religious Importance (Religion was important in my family.), Religious Choice (My parent(s)/
caretaker(s) allowed me to make my own choices about religious beliefs and practices.), and Reli-
gious Conict (There was conict between my parent(s)/caretaker(s) and I about religion.). Each
item was rated on a seven-point Likert scale (1 = Strongly disagree, 4 = Neither agree nor disagree, 7
= Strongly agree).
2.2.5. Credibility enhancing displays (CREDs)
We used Lanman and Buhrmesters(2016) seven-item CREDs measure (see appendix), which cap-
tures respondentsperceptions and self-reports of a variety of parental and/or caregiver religious
behaviours during upbringing. Each item was rated on a seven-point Likert scale (1 = To no extent
at all, 7 = To an extreme extent). Consistent with previous validation by the scales creators, principal
components analysis and factor analysis (principal axis factoring, Varimax rotation) revealed that all
seven items loaded onto a single factor (Eigenvalue = 4.3, 61.2%); loadings ranged from .70 to .86.
Therefore, we indexed all seven items (Cronbachsα= .91), with higher scores indicating greater
CREDs exposure during upbringing.
2.2.6. Peer religiosity
We employed eight questions from a recently developed measure of peer religiosity (cf. Tratner et al.,
2017). For these items, we asked respondents to think of the one person who they would have con-
sidered to be their best friend for most of their adolescent years (ages 13 to 18). Three questions refer-
enced frequency of certain behaviours (1 = never;7=very often), e.g. We prayed together.The
remaining questions were answered by degree of true or untrue (1 = very untrue;7=very true),
e.g. My friend showed their faith by how they talked and acted.Initial principal components analy-
sis and factor analysis (principal axis factoring, oblimin rotation) revealed a two-factor solution
across the eight items. Based upon weak factor loadings and inter-item correlations, we dropped
one item (We agreed in our religious attitudes and beliefs). A subsequent promax rotation yielded
a more simplied factor structure than the oblimin rotation, and retained a two-factor solution, with
the two factors correlated at .57. The rst 4-item factor was interpreted as the extent to which one
shared religious activities with onesbest friend, whereas the second 3-item factor was interpreted as
synonymous with CREDs; that is, it reected the delity and consistency of peer behavioural reli-
gious modelling.
2.2.7. Family structure and parental religious homogamy
One question addressed whether respondents grew up with (or, while growing up, mostly lived with)
both biological parents (dummy coded, 1 = yes). A second question asked whether respondents
parents shared the same religion while the respondent was growing up (dummy coded, 1 = yes).
2.2.8. Known atheist others
One question addressed whether or not the respondent knew any other atheist(s) prior to themselves
becoming an atheist (dummy coded, 1 = yes), regardless of whether this was a friend, family member,
acquaintance, or signicant other.
2.2.9. Institutional religiosity
One item addressed whether respondents had incurred a two-year gap in religious worship service
attendance between the ages of 13 and 18 (Yes, No, Never/hardly ever attended before age 13).A
second item addressed the number of years an individual attended religious school during upbring-
ing (0 = Never attended religious school, 1 = Attended 1 year of religious school, 2 = Attended 2 years
of religious school, etc.)
2.3. Procedure and analysis plan
The current study had two main analyses, both of which explored the relationship between CREDs
and Age of Atheism, but using dierent variables of interest. The major thrust of all analyses was to
determine how dierent social factors inuenced a persons age of arrival at nonbelief in a god or
gods, in relation to CREDs. We tested underlying statistical assumptions for the analyses used,
and made corrections where appropriate (e.g., correcting standard error terms due to
2.3.1. Approach for the rst set of analyses
The purpose of the rst analysis (Table 2) was twofold: rst, to determine the relationship between
CREDs, Religious Importance, Religious Choice, Religious Conict, and Age of Atheism; and
second, to determine if this relationship was moderated by family-religion variables (importance,
choice, and conict). We used hierarchical linear regression to determine if CREDs and our three
family religion variables predicted Age of Atheism, while controlling for demographic variables.
Because BreuschPagan tests were signicant for heteroscedasticity, χ
= 1111.00, p < .001, we
used robust standard errors (i.e., HC3 corrections) with coecients. Age of Atheism, Religious
Importance, Religious Choice, Religious Conict, and CREDs were all standardized (M=0, SD =
1) to improve the interpretability of the overall models (West, Aiken, & Krull, 1996). As such, the
reported regression coecients for Age of Atheism, Religious Importance, Religious Choice, and
Religious Conict could be interpreted as changes in their respective standard deviations. For
example, in Block 2 of Table 2, CREDs has a B/ß coecient of 0.14. This means that for every 1
unit increase in standard deviation for CREDs, one would expect an increase of 14% of 1 unit of stan-
dard deviation for Age of Atheism. Seeing that Age of Atheism had a standard deviation of 10.4 years
(Table 1), the reader could infer that increasing CREDs one unit of standard deviation was associated
with a delay in the Age of Atheism by approximately 1.5 years (10.4*0.14 = 1.456).
After we determined if CREDs, Religious Importance, Religious Choice, and Religious Conict
predicted Age of Atheism, we then explored moderation terms. Specically, we investigated if
CREDsprediction of Age of Atheism changed as a function of Religious Importance, Religious
Choice, and Religious Conict. That is, we investigated whether CREDs became more or less impor-
tant in predicting Age of Atheism when controlling for whether a respondent had high, moderate, or
low levels of Religious Importance, Religious Choice, and Religious Conict. When or if moderation
terms for CREDs and family religion variables were signicant, meaning that CREDsimportance
changed as a function of Religious Importance, Religious Choice, and Religious Conict, we then
investigated how groups diered from each other using marginal means tests.
2.3.2. Approach for the second set of analyses
We conducted a second analysis (see Table 3) to explore how CREDs predicted Age of Atheism, and
to determine how this relationship was impacted by (religious) socialization variables that we
selected from the research literature explicitly because they have been shown to inuence the acqui-
sition and transmission of religious beliefs and identity. This was accomplished through serial entry
and removal of model blocks. As can be seen in Table 3, CREDs remained in the hierarchical linear
regression model for entire set of analyses, but its coecients uctuate as a product of being entered
into the block along with other candidate variables.
Table 2. Relationship between CREDs and age of atheism moderated by religious importance, choice, and conict (n= 5,153).
Coecients/Robust Standard Error
Block 1 Block 2 Block 3 Block 4 Block 5 Block 6
Constant 1.31 (.12)*** 1.07 (.12)*** .93 (.12)*** 1.10 (.13)*** .99 (.13)*** .92 (.12)***
Ref = Female
Other .08 (.12) .07 (.11) .07 (.11) .07 (.11) .08 (.11) .08 (.11)
Male .05 (.03) .08 (.03)** .10 (.03)** .10 (.03)** .10 (.03)** .10 (.03)**
Age .03 (.001)*** .02 (.001)*** .03 (.001)*** .03 (.001)*** .03 (.001)*** .03 (.001)***
Ethnicity .01 (.05) .02 (.05) .03 (.05) .04 (.05) .03 (.05) .03 (.05)
Ref = High School
Some post-sec .05 (.06) .03 (.06) .03 (.06) .02 (.06) .03 (.06) .03 (.06)
Post-sec .16 (.05)** .13 (.05) * .11 (.05) * .11 (.05) * .11 (.05) * .11 (.05) *
Grad school .07 (.06) .04 (.06) .02 (.06) .01 (.06) .01 (.06) .01 (.06)
Other .16 (.10) .15 (.10) .13 (.09) .12 (.09) .13 (.09) .13 (.09)
Ref = Single
Married .06 (.03) .07 (.03) * .05 (.03) .05 (.03) .05 (.03) .05 (.03)
Wid./Sep./Div .06 (.06) .07 (.06) .06 (.06) .05 (.06) .06 (.06) .05 (.06)
Other .08 (.09) .10 (.09) .07 (.09) .06 (.09) .07 (.09) .07 (.09)
Ref = None
Christian .14 (.09) .08 (.10) .13 (.10) .01 (.11) .08 (.10) .14 (.10)
Jewish .41 (.15)** .55 (.15)*** .58 (.16)*** .46 (.16)** .53 (.16)** .60 (.16)***
Muslim .27 (.13) * .01 (.13) .06(.14) .06 (.14) .02 (.14) .07 (.14)
Other .30 (.11)** .04 (.11) .01 (.12) .11 (.12) .04 (.12) .01 (.12)
Ref = USA
Canada .03 (.07) .03 (.07) .05 (.07) .05 (.07) .04 (.07) .05 (.07)
United Kingdom .51 (.13)*** .44 (.12)*** .43 (.12)*** .47 (.12)*** .44 (.12)*** .41 (.12)**
Australia .15 (.10) .11 (.10) .10 (.10) .11 (.10) .10 (.10) .09 (.10)
Other .08 (.05) .05 (.05) .03 (.05) .03 (.05) .03 (.05) .03 (.05)
CREDs (ß) .14 (.02)*** .06 (.02)** .04 (.02) .06 (.02)** .06 (.02)**
Rel. importance (ß) .11 (.02)*** .16 (.03)*** .12 (.02)*** .11 (.02)***
Rel. choice (ß) .06 (.02)** .06 (.02)** .06 (.02)** .06 (.02)**
Rel. conict (ß) .20 (.01)*** .19 (.01)*** .20 (.01)*** .20 (.01)***
Importance*CREDs .08 (.02)***
Choice*CREDs .03 (.02) *
Conict*CREDs .03 (.02) *
.16 *** .18/.02 *** .22/.04 *** .22/.01 *** .22/.01 * .22/.01 *
Note: We standardized select coecients (ß) to aid with the interpretation of the overall model. This did not change the signicance or meaning of the underlying model. For variables with ß, the
coecient indicates the change in the DV (in units of SD). For example, moving from 0 to 1 on CREDs, which is the equivalent of moving 1 SD unit on CREDs, is associated with a .140 SD increase in
Age of Atheism in Block 2. Also note, ΔR
values for Block 4, Block 5, and Block 6, are giving an indication of change relative to Block 3.
*p<.05, ** p< .01, *** p< .001.
Table 3. Relationship for CREDs predicting age of atheism while controlling for constructs on a rotating basis (n= 3,210).
Block 1 Block 2 Block 3 Block 4 Block 5 Block 6 Block 7
CREDs Only Demo. Variables Parent Quality Religious Variables Relational Variables Institution Variables Complete Model
Constant 19.9 (.51)*** 7.2 (1.5)*** 21.2 (1.1) 24.9 (1.04)*** 19.3 (.56)*** 24.4 (.69)*** 14.2 (1.95)***
CREDs .16 (.02)*** .15 (.02)*** .18 (.02) *** .09 (.02)*** .15 (.02)*** .07 (.02)** .04 (.02)
Female (base)
Other 2.31 (1.5) 2.15 (1.37)
Male .71 (.37) 1.21 (.36)**
Age .28 (.02)*** .28 (.02)***
Non-White/White .40 (.60) .79 (.57)
High School (base)
Some post-sec. .63 (.70) .31 (.68)
Post-sec. 1.20 (.66) .42 (.65)
Grad school .31 (.72) .56 (.7)
Other 1.90 (1.2) 1.1 (1.16)
Single (base)
Mar./Common-law 1.06 (.42)* .79 (.4)
Wid./Sep./Div. 1.64 (.77)* 1.34 (.73)
Other .96 (1.2) .89 (1.1)
None (base)
Christian .36 (1.3) .01 (1.3)
Jewish 4.53 (2.1)* 4.31 (2.1)*
Muslim 1.75 (1.7) 1.73 (1.8)
Other 1.30 (1.4) 1.12 (1.4)
USA (base)
Canada .32 (.85) .4 (.81)
UK 4.89 (1.5)** 4.35 (1.5)**
Australia .99 (1.3) 1.61 (1.3)
Other .7 (.64) .2 (.64)
Mom strict .03 (.14) .06 (.12)
Mom warm .56 (.15)*** .14 (.14)
Mom talk .24 (.14) .05 (.12)
Dad strict .19 (.12) .05 (.11)
Dad warm .02 (.15) .03 (.13)
Dad talk .26 (.15) .16 (.13)
Rel. Conict 1.15 (.08)*** .83 (.08)***
Rel. Choice .4 (.10)*** .04 (.10)
Rel. Importance .31 (.16)* .26 (.15)
Both parents 1.04 (.41)* .14 (.39)
Parents di. rel .81 (.49) 1.05 (.46)*
Knew atheists before .74 (.39) 1.99 (.35)***
Table 3. Continued.
Block 1 Block 2 Block 3 Block 4 Block 5 Block 6 Block 7
CREDs Only Demo. Variables Parent Quality Religious Variables Relational Variables Institution Variables Complete Model
Peer religiosity 1 .04 (.04) .12 (.03)***
Peer religiosity 2 .09 (.04)* 0 (.04)
Never stopped att. (base)
Stopped attending 3.50 (.44)*** 2.26 (.41)***
Never attended 8.67 (.69)*** 6.26 (.70)***
Years in rel. school .08 (.04)* .04 (.04)
.03/.03 *** .19/.16 *** .03/.01 *** .09/.06 *** .03/.002 * .07/.04 *** .26/.23 ***
Note: ΔR
values for each block reected the dierence between the Block 1 (CREDs only) and the current block of interest.
*p< .05, ** p< .01, *** p< .001.
Because the sample size for the second main analysis was substantially lower than the sample size
for the rst analysis, we reran BreuschPagan tests, which were again signicant for heteroscedas-
ticity, χ
= 250.11, p< .001. As a result, we again used robust standard errors (i.e., HC3 corrections)
with coecients. Within this model, no issues of multicollinearity emerged, with the highest non-
dummy-coded variable having a VIF of 2.51 (M
= 1.77). When discussing the impact of
CREDs on Age of Atheism, we provided βvalues along with regular B coecients, as this allowed
for a more intuitive understanding of the CREDs-Age of Atheism relationship.
3. Results
3.1. First set of analyses
Age of Atheism was regressed onto demographic covariates in Block 1 (see Table 2), F(19, 4222) =
28.49, p< .001, R
= .159. CREDs was added in Block 2, F(1, 4221) = 85.67, p< .001, R
= .177, ΔR
= .018, and, as predicted, was associated with a signicant delay in the Age of Atheism. Compared to
average CREDs scores, High CREDs scores (+1 SD) were associated with a 1.5-year delay in becom-
ing an atheist. In Block 3, the addition of Religious Importance, Religious Choice, and Religious
Conict signicantly improved the overall model, F(3, 4218) = 76.07, p< .001, R
= .218, ΔR
= .041. Both Religious Choice and Religious Conict reduced the predicted Age of Atheism, while
Religious Importance increased it.
Overall, our analyses suggest that CREDs and family religion variables (i.e., Religious Importance,
Religious Choice, and Religious Conict) predict Age of Atheism. However, the importance of
whether a parent provides consistency in religious messaging and modelling (i.e., CREDs) for pre-
dicting the Age of Atheism, is likely related to other family religion variables. Given these results, we
set out to determine if Religious Importance, Religious Choice, and Religious Conict moderated the
relationship between CREDs and Age of Atheism. For these analyses, each moderator term was
added after Block 3, meaning that the ΔR
for Block 4, Block 5, and Block 6 are in relation to
Block 3.
3.2. Interaction terms
For each interaction term we compared low (1SD), moderate (M), and high (+1 SD) levels of
Religious Importance, Religious Choice, and Religious Conict, across low (1SD), average (M),
and high (+1 SD) levels of CREDs. We report mean dierences (M
) in terms of absolute values
for signicant interaction terms.
3.2.1. CREDs * religious importance
A moderator term (CREDs*Religious Importance) was added in Block 4, which was statistically sig-
nicant, F(1, 4217) = 13.89, p< .001, R
= .221, ΔR
= .003, with t= 3.73, p< .001, B= 0.08, 95%
CI [0.04, 0.12]. Thus, the relationship that CREDs had with Age of Atheism changed as a function
of Religious Importance.
At low levels of CREDs (1SD), we compared Age of Atheism across low (M= 21.84 years),
moderate (M= 22.76 years), and high (M= 23.71 years) levels of Religious Importance. Dierences
between these groups were signicant, t= 3.56, p< .001, with M
= 0.94 years for high vs. average
levels of Religious Importance, and M
= 1.87 for high vs. low levels for Religious Importance.
At average levels of CREDs (M), we again compared Age of Atheism across low (M= 21.44 years),
moderate (M= 23.19 years), and high (M= 24.95 years) levels of Religious Importance. Dierences
between these groups were signicant, t= 5.84, p< .001, as well as noticeably larger than at low levels
of CREDs (high vs. average Religious Importance, M
= 1.75 years; high vs. low Religious Impor-
tance, M
= 3.51 years).
At high levels of CREDs (+1 SD), we assessed Age of Atheism across low (M= 21.04 years), mod-
erate (M= 23.61 years), and high (M= 26.18 years) levels of Religious Importance. Like previously,
dierences were signicant, t= 5.64, p< .001, and again larger (high vs. average Religious Impor-
tance, M
= 2.57 years; high vs. low Religious Importance, M
= 5.14 years).
3.2.2. CREDs * religious choice
In Block 5, we added a moderator term for CREDs*Religious Choice, F(1, 4217) = 4.26, p< .001,
= .219, ΔR
= .001, with t=2.06, p= .039, B=0.03, 95% CI [0.06, 0.00]. These results
suggest that the relationship of CREDs to Age of Atheism changes with levels of Religious Choice.
At low levels of CREDs (1SD), we compared Age of Atheism across low (M= 23.3 years), mod-
erate (M= 23.01 years), and high (M= 22.7 years) levels of Religious Choice. Dierences between
these groups were not signicant, t=1.05, p= .293.
At average levels of CREDs (M), we again compared Age of Atheism across low (M= 24.3 years),
moderate (M= 23.6 years), and high (M= 22.98 years) levels of Religious Choice. Dierences were
signicant, t=3.39, p< .001 (high vs. average Religious Choice, M
= 0.63 years; high vs. low
Religious Choice, M
= 1.26 years).
At high levels of CREDs (+1 SD), Age of Atheism was assessed across low (M= 25.2 years),
moderate (M= 24.2 years), and high (M= 23.2 years) levels of Religious Choice. As with previous
analyses, dierences were signicant, t=4.08, p< .001, and again larger (high vs. average Religious
Choice, M
= 0.99 years; high vs. low Religious Choice, M
= 1.97 years).
3.2.3. CREDs * religious conict
We removed the moderator term from Block 6, and added the CREDs * Religious Conict modera-
tor term, F(1, 4217) = 3.91, p= .048, R
= .219, ΔR
= .001; this moderator term was signicant,
t=1.98, p= .048, B=.035, 95% CI [0.06, 0.00]. This suggests that the ability of CREDs to
predict Age of Atheism, varied at low, average, and high level of Religious Conict.
At low levels of CREDs (1SD), we compared Age of Atheism across low (M= 24.93 years),
moderate (M= 23.10 years), and high (M= 21.27 years) levels of Religious Conict. Dierences
between these groups were signicant, t=7.89, p< .001, with M
= 1.83 years for high vs. average
levels of Religious Conict, and M
= 3.67 for high vs. low levels for Religious Conict.
At average levels of CREDs (M), we again compared Age of Atheism across low (M= 25.92 years),
moderate (M= 23.78 years), and high (M= 21.63 years) levels of Religious Conict. Dierences
between these groups were signicant, t=13.95, p< .001, as well as noticeably larger than at low
levels of CREDs (high vs. average Religious Conict, M
= 2.15 years; high vs. low Religious Con-
ict, M
= 4.29 years).
At high levels of CREDs (+1 SD), Age of Atheism was assessed across low (M= 26.91 years), mod-
erate (M= 24.45 years), and high (M= 22.00 years) levels of Religious Conict. Like previously,
dierences were signicant, t=11.88, p< .001, and again larger (high vs. average Religious Conict,
= 2.45 years; high vs. low Religious Conict, M
= 4.91 years).
Overall, the data analyses revealed a pattern that was not unexpected: while higher levels of
CREDs continued to predict higher Age of Atheism, this was inuenced by family religion variables.
In a sense, the protectiveinuence of CREDs is stronger in some scenarios (e.g. high Religious
Importance, low Religious Choice, and low Religious Conict) than in others.
3.3. Second set of analyses
Age of Atheism was regressed onto CREDs in Block 1 (see Table 3), F(1, 3208) = 76.06, p< .001, R
= .03, which suggested that CREDs predicted 3% of the variance in Age of Atheism. For CREDs
specically, t= 8.72, p< .001, B= 0.16, 95% CI [0.12, 0.19], which meant that increasing CREDs
by 1 SD corresponded with a 20-month delay in becoming an atheist. Demographic covariates
were entered in Block 2, F(19, 3189) = 23.18, p< .001, R
= .19, ΔR
= .16, but CREDs remained
virtually unchanged, t= 8.79, p< .001, B= 0.15, 95% CI [0.12, 0.19]. Again, increasing CREDs by 1
SD was associated with a 20-month delay in becoming an atheist.
We then removed Block 2 and entered Block 3 (six parental relationship quality items), F(6,
3202) = 4.67, p< .001, R
= .03, ΔR
= .01, and with this CREDs remained with a similar relationship,
t= 8.70, p< .001, B= 0.17, 95% CI [0.13, 0.21], which was approximately a 22-month delay in the age
of atheism. Generally, demographics and parental relationship quality had limited impact on how
CREDs predicted Age of Atheism.
We then added family predictors in Block 4, F(5, 3203) = 43.83, p< .001, R
= .09, ΔR
= .06.
CREDs remained signicant but experienced its rst substantive decline of inuence, t= 3.65, p
< .001, B= 0.09, 95% CI [0.04, 0.13]. With the inclusion of family religion predictors [Religious
Conict, Religious Choice, Religious Importance, Family Structure (lived with both parents), and
Parental Religious Homogamy (whether parents had the same religion or not)], going up 1 SD on
CREDs predicted a delay of just 11 months or so, suggesting that part of CREDs explanatory
power lies in familial structures. We then removed family religion predictors from Block 4 and
entered relational predictors [Peer Religiosity 1, Peer Religiosity 2, and Known Atheist Others] in
Block 5, F(3, 3205) = 2.68, p= .045, R
= .03, ΔR
= .002, but this did not improve the overall
model. With relational predictors, CREDs remained signicant, t= 7.75, p< .001, B= 0.15, 95% CI
[0.11, 0.19], and was associated with a 19-month delay in Atheism.
After removing relational predictors, institutional predictors were entered in Block 6, F(3, 3205)
= 56.20, p< .001, R
= .07, ΔR
= .04, which were signicant. With the inclusion of institutional pre-
dictors [Two-year gap in religious worship service attendance between the ages of 13 and 18, and
number of years of religious schooling during upbringing], CREDs was signicant, t= 3.29, p
= .001, B= 0.06, 95% CI [0.02, 0.11], but only predicted a 9-month delay. Given the performance
of institutional predictors, we attended to the pattern of coecients within this new block. Moving
from No (base) to Stopped attending (before age 13) was especially noteworthy, t=12.49, p< .001, B
=8.67, 95% CI [10.03, 7.31], as it was associated with becoming an atheist 8.5-years earlier.
Despite the obvious conceptual links between ceasing/failing to attend religious worship services
in childhood and the overarching CREDs score, there was only a weak correlation between these
variables (r=.22), and multicollinearity was decidedly not an issue. Overall, knowing whether a
person had ceased attending religious worship services prior to the age 13 made a far more substan-
tial prediction of Age of Atheism than did CREDs.
As a nal step, all variables were entered in Block 7, F(36, 3172) = 24.30, p< .001, R
= .26, ΔR
= .23, which was signicant. With the inclusion of all variables, CREDs was not signicant, t= 1.73,
p= .08, B= 0.04, 95% CI [0.00, 0.09], but given the strong performance of Block 6, this was not
altogether surprising.
4. Discussion
Our rst analysis yielded three noteworthy observations. First, Religious Importance predicted a
delay in the Age of Atheism, whereas Religious Choice and Religious Conict predicted an earlier
onset of Age of Atheism. Second, as hypothesized, CREDs positively predicted Age of Atheism.
Third, there was an interdependency of Religious Importance, Religious Choice, and Religious
Conict with CREDs.
As Figure 1 shows, as Religious Importance increased within the sample, the age at which a person
became an atheist increased. At low levels of CREDs (1SD), the dierence in the timing of atheism
for persons low or high on Religious Importance was not even two years. In contrast, at high levels of
CREDs, this same dierence was over ve years. In other words, Religious Importance matters, but
not in isolation: parents espousing the importance of religion may delay atheism in their progeny,
but consistent modelling enhances this eect.
When investigating the relationship between CREDs and Religious Choice, Religious Choice
negatively predicted Age of Atheism. Conceptually, then, the freedom to choose may be one part
of a familial atmosphere conducive to atheism earlier in life. However, this interaction term was quite
modest, and, when considering persons at the highest levels of CREDs, the contrast in reported Age
of Atheism between participants reporting low and high levels of Religious Choice was less than two
yearsdierence (see Figure 2). That said, the pattern of ndings was such that higher CREDs were
again associated with a protectiveinuence against Age of Atheism, suggesting that even with reli-
gious freedom, high levels of CREDs still pushrespondents toward retaining a belief in god(s).
In the third interaction term, Religious Conict was negatively associated with Age of Atheism,
while CREDs were again positively associated with Age of Atheism. As can be seen in Figure 3,at
lower levels of CREDs the gap between low and high Religious Conict was approximately 3.5
years, while at higher levels of CREDs the gap between low and high Religious Conict was over 5
years. Again, this pattern supports the idea that consistency between messaging and modelling inu-
ences the timing of atheism. In follow-up analysis, we compared low and high CREDs at high levels of
Religious Conict, and found that there was no dierence between Age of Atheism for these two
groups, t=1.51,p= .15. In contrast, when we compared low and high CREDs at low levels of Religious
Conict, the dierence was statistically signicant, t= 3.93, p<.001, M
=2.30 years. Framed
-1SD M +1SD
Age of Atheism
Rel. Import. (-1SD) Rel. Import. (M) Rel. Import. (+1SD)
Figure 1. Dierences in age of atheism by CREDs and religious importance.
-1SD M +1SD
Age of Atheism
Rel. Choice (-1SD) Rel. Choice (M) Rel. Choice (+1SD)
Figure 2. Dierences in age of atheism by CREDs and religious choice.
dierently, this pattern of ndings suggests that in a high Religious Conict home, strong religious
modelling is not associated with a delayed Age of Atheism, but in a low Religious Conict Home it is.
General ndings from regression analyses suggested that higher CREDs levels were associated
with delayed Age of Atheism. Functionally, when participants perceived their parents as having
high degrees of religious credibility, this was associated with a protectiveinuence against atheism,
and this eect was the most pronounced when Religious Importance was high and Religious Conict
was low. However, substantive eects were also present at moderate levels of both Religious Impor-
tance and Religious Conict, but only at high levels of Religious Choice. Also of note, religion of
upbringing had a varied impact on the age at which a person became an atheist. Compared to
those with a nonreligious upbringing, being raised as a Muslim or a religious Other was associated
with a delay in becoming an atheist. However, when controlling for Religious Importance, Religious
Choice, and Religious Conict, these relationships became non-signicant. And yet, even with these
controls, those raised in Judaism were exceptions, and reported an earlier age of atheism (M= 6.02
years) despite the inuence of these family-religion variables. Residence in the United Kingdom and
Northern Ireland also displayed a robust and negative association with Age of Atheism, when com-
pared to the much more religious United States. Thus, both religion of upbringing and nationality
should be considered if we wish to understand the formal inuence of CREDs and other modern or
current relational dynamics on a person becoming an atheist.
All three family religion variables are consequential for the timing of atheism (although only Reli-
gious Conict is retained in Block 7 of the second main analysis, thus surviving the inuence of all
other [religious] socialization candidate variables), and, among their interrelationships, we can
suggest certain possibilities. To the extent that religion is (perceived as) important in the family,
this may diminish Religious Choice, which in turn may lead to Religious Conict. However, even
if parents faithfully model their own religion, religion may or may not always be (perceived as)
important in the family of upbringing. We would suggest that whether or not it is, either arrange-
ment is likely to be dierentially associated with arrangements of higher/lower Religious Choice
and higher/lower Religious Conict.
Our second analysis demonstrated that CREDs had a relatively stable ability to predict Age of
Atheism, and remained relevant to the overall model despite the inclusion of demographics, parental
warmth variables, family variables, and relational variables. However, with the inclusion of insti-
tutional predictors, particularly questions about cessation of religious worship service attendance
during ones adolescent years, CREDs were rendered largely irrelevant to the wider prediction of
Age of Atheism. Yet, we must note that the distribution of CREDs scores across these categories
-1SD M +1SD
Age of Atheism
Rel. Conflict (-1SD) Rel. Conflict (M) Rel. Conflict (+1SD)
Figure 3. Dierences in age of atheism by CREDs and religious conict.
was not uniform: 50% of persons who reported that they had stopped attending religious worship
services prior to the age of 13 scored in the lowest CREDs quintile. When looking at the lowest
two CREDs quintiles this value increased to 75% of all respondents in the category. In other
words, respondents who had stopped attending religious worship services prior to the age of 13,
tended to have parents who scored near the bottom of the overall CREDs measure. We may also
point out that, relative to the Yes and No categories, those in the Stopped attending prior to age
13category reported elevated levels of Religious Choice and diminished levels of Religious Conict.
For these reasons, the performance of the institutional predictors in our analysis does not, in our
view, genuinely overturn the robust contribution of CREDs to Age of Atheism.
4.1. Future Research
Hitzeman and Wastell (2017) suggested that future research should consider both context and con-
tent biases regarding changing levels of religious belief. We second this suggestion, and further
suggest that, if successive generations are becoming less religious (and at younger ages) in post-
industrial countries, this should be examined in reference to changing patterns of (non)religious
socialization (to include levels to CREDs). We have focused primarily on CREDs, but recent work
highlights the role of explicitly nonreligious socialization as an explanation for increasing numbers
of religious Nones(which would include atheists) across birth cohorts. Bengtson, Hayward, Zuck-
erman, and Silverstein (2018) argued that some amount of the increasing number of Nones is due to
increasingly explicit nonreligious socialization across generations, that is, not due only to weak or
absent religious socialization. This brings up the question of what kind of CREDs exist in nonreli-
gious families or if they are needed at all to sustain whatever positive or substantive worldviews
such parents might wish to instill.
Clearly, family and social environments in which religion is highly salient are not wholly incom-
patible with religious peacebetween family members and peers, or with allowing ospring to make
some Religious Choices for themselves. And yet, this is where a comparative approach might serve
well: Do atheists reect levels of Religious Choice and Religious Conict that are dierent from their
theistic counterparts? Relatedly, were most formerly believing atheists subject to authoritarian, as
opposed to authoritative, parenting styles?
Given weak eects of parental quality items, a more comprehensive measure of parental closeness
and overall family quality might be deployed in future research, as such measures have often been
found to inuence the transmission of religious beliefs. Regarding Bengtson et al. (2018) study, it
may be that parental and family quality considerations eectively facilitate both religious beliefs
and atheism across generations. For example, even high-delity religious parents may unknowingly
inuence the turn to atheism if certain parental qualities and Religious Choice or Religious Conict
are associated.
4.2. Limitations
First, we only collected data from respondents themselves, and not respondentsparents and peers.
Second, such data inevitably rely upon retrospective self-reports and human memory. This is of par-
ticular concern because as our sample consisted of members of atheist groups, and, just as do reli-
giouspersons, such individuals use narrative and biography to explain to fellow group members and
others their transition from believer to atheist. And like their religious counterparts, there may be
considerable incentives for atheists to modify, or selectively re-remember, their narratives in
order to t in with their groups. Studying former atheists who had become Christians, Langston
and colleagues (Langston, Albanesi, & Facciani, under review) noted that such conversion narratives
might be just as subject to recall error and retroactive identity construction via biographical narra-
tive, as the narratives of those who stop believing in a god or gods. Eectively, then, in any kind of
(non)religious transition (e.g., from believer to nonbeliever, or vice versa), people are likely to
remembertheir histories in accordance with creating a positive characterization of their transition,
especially when joining a group or social milieu with preexisting narrative elements which are
learned by converts during transition (Hefner, 1993). Because people are often not fully aware of
the factors that inuence their beliefs and behaviours, there is a tendency for rational (or at least con-
scious) reasons to be emphasised, which could probably best be described as rationalizationof what
are otherwise unknown or unrecognized causal inuences on behaviour (Bargh & Chartrand, 1999).
Considered together, such problems underscore the need to very cautiously interpret self-reports and
personal narratives.
Third, we do not know what Religious Conicts were specically about in these families, and this
would be important information for determining how, if at all, such conicts informed later atheism.
A related and critical consideration is whether Religious Conict is antecedent to or consequent of
atheism. Previous research suggests that one might be as likely as the other (cf. Hunsberger, 1983),
and our design does not allow us to disentangle the temporal order of these two items. While both
orders are logically feasible, our argument rests upon Religious Conict as an antecedent contri-
bution to becoming an atheist (cf. Pasquale, 2009). Furthermore, even if a person disagrees that
there was family conict about religion, this does not mean that they do not harbour misgivings
about parental religious beliefs and practices. It is certainly possible that unspoken qualms of
these kinds can manifest in later change and dissent from ones religious upbringing, especially if
they are suppressed or nursed silently over time. This may be all the more true during the rst several
years after a person leaves their parentshome and achieves greater liberation in general, but also
from parental supervision and control (Dudley, 1999).
5. Conclusion
Sociological perspectives are often overlooked in the cognitive science of religion. Yet, families, social
relationships, and (religious) institutional contexts have long been understood as primary sites of
religious socialization processes which are inuential in religious outcomes. As such, work in CSR
should be integrated with such perspectives. Because discussing changes in the modern religious
landscape also requires a consideration of where atheism is increasing (Norris & Inglehart, 2011),
it is important to note broad social and intergenerational change in such societies, especially as
they impact (and are impacted by) broader changes in family formation patterns and socialization
processes. This also ts well regarding considerations of context and content biases, and with con-
siderations of both ultimate and proximate mechanisms that underpin (non)religious phenomena.
Our study provides a glimpse into how CREDs work in tandem with other religion variables func-
tioning in family and relational processes, and we envision it as a way forward in linking the cogni-
tive science of religion to more sociologically oriented approaches to (non)religious outcomes.
1. In Pasquales study of secular group aliates, of those current secularists who were raised in a Roman Catholic
background (n= 128), 37.5% reported conict with parents over religion. For those with a Protestant back-
ground (n= 469), 24.3% reported such conict, whereas for those raised with a secular background (n=
105), this gure was only 2.9%.
2. A majority of these studies specically measure parental CREDs, and not CREDs in general (e.g., religious auth-
ority gures, relatives, members of the community). See also Turpin, Andersen, & Lanman, 2018; while they
found no immediate eects of CRED exposure on measures of explicit and implicit belief using an experimental
manipulation, they did nd further correlational evidence linking past CRED exposure to self-reported reli-
gious belief.
Disclosure statement
No potential conict of interest was reported by the authors.
Joseph Langston
David Speed
Thomas J. Coleman III
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CREDs Exposure Scale (see Lanman & Buhrmester, 2016)
Instructions: The following questions ask about experiences during your upbringing that relate to religion. Specically,
the questions ask about your perceptions of your primary caregiver or caregivers (i.e., parents or guardians). Please
answer each of the following according to your overall impression of your caregiver(s) on the following scale:
To no extent at all To an extreme extent
(1) To what extent did your caregiver(s) attend religious services or meetings?
(2) To what extent did your caregiver(s) engage in religious volunteer or charity work?
(3) Overall, to what extent did your caregiver(s) act as good religious role models?
(4) Overall, to what extent did your caregiver(s) make personal sacrices to religion?
(5) To what extent did your caregiver(s) act fairly to others because their religion taught them so?
(6) To what extent did your caregiver(s) live a religiously pure life?
(7) To what extent did your caregiver(s) avoid harming others because their religion taught them so?
... Using their own correlational measure and a large sample of 67,000 individuals, Maij and colleagues (2017) argued that exposure to Credibility Enhancing Displays plays a much larger role in generating religious belief than individual differences in sensitivity to content features. Langston and colleagues also found that higher exposure predicted a later age of religious rejection among members of online New Atheist communities (Langston, Speed, & Coleman, 2020). While most studies have been correlational, Willard and colleagues found that people were more amenable to believing counterintuitive scientific information if they saw an experimental confederate performing a supporting Credibility Enhancing Display for the information in question (Willard, Henrich, & Norenzayan, 2016). ...
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Credibility Enhancing Displays have been shown to be an important component in the transmission of empirically unverifiable cultural content such as religious beliefs. Decreased Credibility Enhancing Displays are a major predictor of religious decline. However, because declines in belief are often paired with decreasing importance of religious institutions, existing research has not yet shown the effect of Credibility Enhancing Displays as separate from this institutional decline. Here, we assess the role of past Credibility Enhancing Display exposure among the baptised Catholic population of Ireland in predicting who retains a Catholic identity and religious beliefs among those who reject the Catholic Church. We find that leaving Catholicism outright (i.e. ‘Ex-Catholicism’) is predicted by low Credibility Enhancing Display exposure, but rejecting the Church while retaining a Catholic identity (i.e. ‘Liminal Catholicism’) and theistic belief is not. High perceived prevalence of clerical paedophiles (i.e., religious hypocrisy) predicts both groups similarly. Higher exposure to Credibility Enhancing Displays predicts higher orthodox Catholic beliefs and Catholic morality among Catholics, but with inconsistent and even negative effects among the other groups. High perceived prevalence of clerical paedophiles predicts the rejection of orthodox Catholic beliefs, but not the rejection of theism or a Catholic identity.
... In other words, for example, factors such as the importance of religion in one's family and the family's religious background (e.g. Jewish; cf., [9]) exert similar influences on the religiosity of academics [26], as well as nonreligiosity in general [51]. In sum, variables like family income, marital status, number of children, age, race, political orientation, and geographic location, have all been found to impact the religiosity of academics and the general public [36], [58], [66], [89], (see also [46]). ...
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The religiosity of academics has been studied for over a decade. With few exceptions, this research has been conducted on American “elite” scientists, and data from non-Western countries is lacking. Drawing from psychological and sociological literature, the present exploratory study investigates the religiosity of Turkish academics (N = 361) and their perceptions on the relationship between religion and science, and associated variables such as interpretation of the Quran, and belief in evolution and creationism. Moreover, we address criticism directed at previous research by probing for different God concepts among believing academics. Although cultural differences can be identified, the results generally support the idea that academics are less religious with 54% identifying as “less religious” or “not religious,” compared to 24.2% self-identifying as “religious” or “extremely religious.”
... Here, recruitment was online without participant reimbursement (though several raffles were organised to stimulate participation), and participants were mostly recruited through online groups (Facebook pages or newsletters). This means that many of the secular individuals that were reached were involved in digital media and had an interest in, or were part of, a secular organisation (like much of the previous research, e.g.,Kontala, 2016;Langston et al., 2020;Pasquale, 2009;Smith, 2017;Smith & Halligan, 2021). This may indicate that religious non-belief is an important component of their social identities, and it may be that secular individuals in the general population, outside these digital environments, are more indifferent to religion and less cross-culturally similar than the current sample, which warrants exploring.While this research did not aim to cluster secular individuals, and instead focused on exploring potential clusters of secular beliefs, overlaps with previously suggested and demonstrated non-religious groupings(Lee, 2015;Lindeman et al., 2019;Manning, 2015;Silver et al., 2014) were noted. ...
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The global increase in non-religious individuals begs for a better understanding of what non-religious beliefs and worldviews actually entail. Rather than assuming an absence of belief or imposing a predetermined set of beliefs, the current research uses an open-ended approach to investigate which secular beliefs and worldviews non-religious non-theistic individuals in ten countries around the world might endorse. Approximately one hundred participants per country were recruited and completed the online survey (N = 996). A data-driven coding scheme of the open-ended question about the participants’ beliefs and worldviews included 51 categories in 11 supercategories (agency & control, collaboration & peace, equality & kindness, morality, natural laws & the here and now, non-religiosity, reflection & acceptance, science & critical thinking, spirituality, truth, and other). The ten most frequently mentioned categories were science, humanism, critical scepticism, natural laws, equality, kindness & caring, care for the earth, left-wing political causes, atheism, and individualism & freedom. Patterns of beliefs were explored, demonstrating three worldview belief sets: scientific worldviews, humanist worldviews, and caring nature-focused worldviews. This project is a timely data-driven exploration of the content and range of global secular worldviews around the world, and matches previous theoretical work. Future research may utilise these data and findings to construct more comprehensive surveys, to be completed in additional countries.
... This hypothesis has received support from several empirical studies, including some on the factors that contribute to theism [2] and the spread of secularization [3]. Other studies have shown that CREDs seem to be an important factor in differentiating religious believers from non-believers [4] and in predicting the age at which individuals embrace atheism [5]. More recently, scholars have explored the role of credibility-undermining displays, CRUDs (behaviors inconsistent with one's belief) which seem to weaken the power of religion in human populations, as illustrated in research on the response to pedophilia scandals in the Roman Catholic Church in Ireland [6]. ...
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This paper describes an artificial society in which the simulated agents behave and interact based on a computational architecture informed by insights from one of the leading social psychological theories in the scientific study of secularization and religion: “credibility-enhancing displays” (or CREDs) theory. After introducing the key elements of the theory and outlining the computational architecture of our CRED model, we present some of our initial simulation results. These efforts are intended to advance the quest within social simulation for more authentic artificial societies and more plausible human-like agents with complex interactive and interpretative capacities.
... Several of the studies cited above highlight the role of (a lack of) CREDs in predicting religious unbelief or disaffiliation. One recent study found a robust relation between (lack of) CREDs in an individual's experience and environment and the likelihood of that individual being an atheist, but also called for attending to the ways in which other variables can modify the effect of CREDs on nonreligion (Gervais et al. 2020;Langston et al. 2018). Another recent article highlighted the potential role of hypocritical or ' credibility-undermining displays' (CRUDs) as a factor in the rejection of religion. ...
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Statistical models attempting to predict who will disaffiliate from religions have typically accounted for less than 15% of the variation in religious affiliations, suggesting that we have only a partial understanding of this vital social process. Using agent-based simulations in three “artificial societies” (one predominantly religious; one predominantly secular; and one in between), we demonstrate that worldview pluralism within one’s neighborhood and family social networks can be a significant predictor of religious (dis)affiliation but in pluralistic societies worldview diversity is less important and, instead, people move toward worldview neutrality. Our results suggest that there may be two phases in religious disaffiliation: (1) the early adopters initially disaffiliate regardless of social support, and subsequently (2) disaffiliation spreads as support for it within local social networks widens and it appears more acceptable. An important next step is for sociologists to confirm or correct the theoretical findings of this model using real-world social-network data, which will require overcoming the measurement difficulties involved in estimating each individual’s degree of local network pluralism.
Complex systems produce recognizable self-organized patterns across time. This conceptual paper consists of a systematic reflection on what kinds of archetypical patterns systems can show, and in what kinds of cases these patterns could occur. Agent-based models are used to exemplify each pattern. We present a classification of the breadth of typical patterns that agent-based models can show when one runs them. The patterns fall into three categories: resource use, contagion, and output patterns. These are pattern archetypes; most real-world systems, and also most models, could and will show combinations of the patterns. In real systems, the patterns will occur as phases and building blocks of developments. These are patterns frequently occurring in real-world systems. The classification is the first of its kind. It provides a way of thinking and a language to non-mathematicians. This classification should be beneficial to those researchers who are familiar with a real-world pattern in their discipline of interest, and try to get a grasp of pattern causation. It can also serve in education, for giving students from a variety of disciplines an idea of the possibilities of agent-based models.
This paper introduces EMLab-Consumer, an agent-based model developed in the H2020 project Cheetah, on energy efficiency of households. The model builds on the theory of planned behavior, a large European survey and a variety of choice models generated from the same survey. It studies adoption of a number of energy efficient appliances and heating systems in 8 EU countries, under a variety of policy interventions. The paper describes the model and first outcomes on smart thermostats.
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(to appear in Current Opinion in Psychology) Contrary to some conceptualizations, nonbelievers are more than simply those scoring low on religiosity scales. They seem to be characterized by analytic, flexible, and open-minded social-cognitive attributes, although this may interact with sociocultural levels of religiosity. This paper demonstrates that nonbelief, at least in the West, tends to coincide with specific worldviews, namely valuing rationality and science, as well as humanistic and liberal values. Furthermore, nonbelievers seem to parallel believers in various indicators of health. Finally, as all ideologists, nonbelievers may hold prejudicial attitudes toward groups perceived as threatening their (secular) worldviews, although this has some limits. Global increases in secularity make the nascent psychological study of nonbelievers and nonreligious worldviews an important research programme.
What explains the ubiquity and diversity of religions around the world? Widespread cognitive tendencies, including mentalizing and intuitive thinking, offer part of the explanation for recurrent features of religion, and individual differences in religious commitments. However, vast diversity in religious beliefs points to the importance of the cultural context in which religious beliefs are transmitted. Cultural evolutionary theory provides the basis of a unified explanation for how cognition and culture interact to shape religious beliefs, in ways that are uniquely adapted to local ecological pressures. These insights lay the groundwork for future research regarding how cultural learning interacts with other evolved aspects of human psychology to generate the recurrent and the diverse forms of religious commitments observed around the world.
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In this study, the link between atheistic beliefs and two child-rearing values (obedience and autonomy) is explored. Atheists would be more likely to show preferences for autonomy and less likely for obedience. Two individual-level explanations, namely educational attainment and expressive individualism, are tested. Moreover, the contextual effects of both religious climate and collectivistic-individualistic culture in a country are investigated. Using data from 30 countries from the European Values Study [(2011) 4th wave, Integrated Dataset ZA4800. Data File Version 3.0.0. (November 2011). Cologne: GESIS Data Archive. doi:10.4232/1.11004], it was found that both educational attainment and expressive individualism are explanations of why individuals with atheistic beliefs prefer autonomy more compared to other individuals. However, for obedience, expressive individualism could only explain the difference in preferences between religious individuals and atheists, but not the difference between atheists and those who are unsure about their religious belief. In addition, contrary to our expectations, no moderating effect of the religious context and collectivistic-individualistic culture on the relationship between atheistic beliefs and child-rearing values was found.
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The ability to mentalize has been marked as an important cognitive mechanism enabling belief in supernatural agents. In five studies we cross-culturally investigated the relationship between mentalizing and belief in supernatural agents with large sample sizes (over 67,000 participants in total) and different operationalizations of mentalizing. The relative importance of mentalizing for endorsing supernatural beliefs was directly compared with credibility enhancing displays–the extent to which people observed credible religious acts during their upbringing. We also compared autistic with neurotypical adolescents. The empathy quotient and the autism-spectrum quotient were not predictive of belief in supernatural agents in all countries (i.e., The Netherlands, Switzerland and the United States), although we did observe a curvilinear effect in the United States. We further observed a strong influence of credibility enhancing displays on belief in supernatural agents. These findings highlight the importance of cultural learning for acquiring supernatural beliefs and ask for reconsiderations of the importance of mentalizing.
Recent polls show that an increasing number of young adults profess no religious affiliation. Prior research has suggested several explanations for this, among them older ages at marriage, higher education rates, reaction against the priest/pedophile scandal, and political backlash against the religious right, as well as the traditional explanation of youthful rebellion against religious parents. In this article, we propose another theory: intergenerational transmission, an increase in the number of parents and grandparents who have been explicitly socializing their children to a nonreligious worldview. We use a mixed methods approach with data from the 34‐year Longitudinal Study of Generations to examine parents’ and grandparents’ influence on youth over several decades. The rate of nonreligious young persons in our sample tripled between 1971 and 2005. Though this undoubtedly reflects broader cohort trends, we can trace a significant portion of this growth to family intergenerational continuity brought about by explicitly nonreligious socialization by parents as well as grandparents. Qualitative data provide insight into processes of nonreligious influence over generations, seen in three types: multigenerational socialization of humanism, of atheism, and of the unintended socialization of “religious rebels” from highly religious parents.
Data in this study supported a model of internalization that included both transmission and transactional variables. Two sets of hierarchical linear regression models were conducted on data collected from the fathers, mothers, and adolescents (10 to 12 years old) in 171 intact Caucasian families. One set predicted adolescent religious behavior; the other predicted the importance of religion to child. Transmission variables (parental religious behavior and parental desire for child to be religious) predicted the most variance in all models. Dyadic discussions of faith (transactional) predicted significant variance in all models. Child gender had a direct effect only on adolescent religious behavior. A significant 3-way interaction occurred between child gender, parental desire for child to be religious, and dyadic discussions when predicting importance of religion to child, with child and parent gender dyads interacting in a complex manner.
Previous research on credibility-enhancing displays (CREDs) suggests that long-term exposure to religious role models “practicing what they preach” aids the acceptance of religious representations by cultural learners. Likewise, a considerable amount of anecdotal evidence implicates its opposite, perceived “religious hypocrisy” (forthwith credibility-undermining displays or CRUDs), as a factor in the rejection of religion. However, there is currently little causal evidence on whether behaviors of either kind displayed by religious authorities directly affect pre-existing religious belief. The current study investigated this question by priming Irish self-identified “Catholic Christian” participants with either a clerical CRED or CRUD and subsequently measuring levels of explicit and implicit belief. Our results revealed no effects of immediate CRED or CRUD exposure on either implicit religious belief or three different measures of explicit religiosity. Instead, explicit (but not implicit) religiosity was predicted by past CRED exposure. Prospects and limitations of experimental approaches to CREDs and CRUDs are discussed.
Childhood religious experiences with peers are important in the development of religiosity. However, peers' influence on these experiences has not been properly operationalized and measured. We addressed this limitation by developing the Childhood Religious Experiences with a Peer Inventory (CREPI). In Study 1 (n = 254), an act nomination procedure generated 106 items describing childhood religious experiences with a same-sex peer. These experiences were specific things that the peer said to, did to, or did with a participant during their childhood. In Study 2 (n = 458), participants indicated how frequently each item occurred in their childhood. Factor analysis yielded 27 items organized into three factors: Peer Proselytization, Shared Activities, and Peer Dialogue. The CREPI allows researchers to quantify peer influence on childhood religious experiences, enabling future investigation of whether and how these influences predict adult religiosity.
The rise in the numbers of religious "nones" is an almost universal phenomenon across the Western world. The purpose of this study is to explore the extent to which religious nones are socialized to adopt a "no religion" position as children, as compared with disaffiliating during their teen or adult years. Related, among those religious nones who come from a religious background, we examine the timing and depth of a person's disaffiliation. This study sheds light on these issues by combining a quantitative analysis of religious nones samples in Alberta, Canada, America, and other international contexts with a qualitative analysis of 30 semistructured interviews with religious nones. Building on a stage of decline framework, we argue that while disaffiliation has been a lead catalyst for the growth among the religious none population-and we offer several observations of what fuels disaffiliation-moving forward we can and should expect irreligious socialization to gradually take the lead in explaining rising religious none figures.
The Cognitive Science of Religion commonly advances the view that religious beliefs emerge naturally via specific cognitive biases without cultural influence. From this perspective comes the claim that self-proclaimed atheists harbour traces of supernatural thinking. By exploring the potential influence of the cultural learning mechanism Credibility Enhancing Displays (creds), which affirms beliefs, current disparities between studies involved in priming the implicit theism of atheists, might be reconciled. Eighty-eight university students were randomly assigned to either a religious or control prime condition. A dictator game was completed to obtain an indication of pro-social behaviour (psb). Lifetime theists reported significantly higher religious creds exposure levels than lifetime atheists, though not convert atheists. Conversely, lifetime atheists reported significantly lower creds exposure scores than convert atheists. Convert atheists in the prime condition were significantly more pro-social than lifetime atheists. Additionally, higher scores on the creds exposure measure equated to higher psb in the religious condition than the control condition. The results are consistent with the view that supernatural belief formation is an interactive process between both context and content biases, and that in order to accurately test for implicit theism, past personal differences in exposure to religious creds should be considered.