ORI GIN AL PA PER

Declining Religious Authority? Confidencein the Leaders of Religious Organizations, 1973–2010

John P. Hoffmann

Received: 16 March 2012 / Accepted: 12 October 2012 / Published online: 20 October 2012

� Religious Research Association, Inc. 2012

Abstract One view of secularization is that it can be conceived of as declining

religious authority. Although studies conducted in the 1990s suggested that confi-

dence in the leaders of religious organizations—a promising indicator of religious

authority—decreased in the 1970s and 1980s, research has not examined recent

trends. The goals of this study are to (1) examine trends in confidence using data

from the early 1970s through 2010 and (2) use recent advances in age-period-cohort

analysis to provide a more robust empirical examination of these trends. Using data

from the cumulative General Social Surveys, 1973–2010, the results suggest that,

even after considering age effects, period declines in confidence have continued, but

declines by birth cohort were primarily among those born in the boomer and early

post-boomer generations (roughly 1945–1970) relative to those born earlier (pre-

1945) or later (post-1970). Moreover, these effects appear to be due mainly to

differences in religious participation, especially among more recent cohorts. In

particular, there has been a rebound in confidence among members of the younger

generation who attend religious services.

Keywords Confidence in religious organizations � Declining religious authority �Secularization � Trend data

An earlier version of this paper was presented at the 2010 annual meeting of the Association for the

Sociology of Religion, Atlanta, GA. I thank the following for helpful suggestions and for sharing their

ideas about secularization theory with me: Jose Casanova, the late Alan Miller, James Phillips, Lance

Erickson, and the anonymous RRR reviewers.

J. P. Hoffmann (&)

Department of Sociology, Brigham Young University, Provo, UT 84602, USA

e-mail: john_hoffmann@byu.edu

123

Rev Relig Res (2013) 55:1–25

DOI 10.1007/s13644-012-0090-1

The debate concerning secularization in the United States and Europe continues

unabated. Although the 1980s and 1990s may have seen the most vigorous

arguments about secularization, in the 2000s there continue to be disputes regarding

the various positions (Bruce 2011; Gorski and Altinordu 2008; Martin 2011; Norris

and Inglehart 2004). For example, some observers contend that secularization, if it

occurred at all, has diminished (at least in the U.S.), as can been seen by the

contentious social and political debates over issues such as abortion, evolution, and

the role of religion in schools and in the public square; as well as high levels of

belief in God and other religious symbols (Berger 2008; Stark 1999, 2008). Others

assert that secularization continues to march onward, as indicated by declining

levels of religious service attendance, especially among younger cohorts, and the

increasing number of people who say they are not affiliated with any religious group

(the religious ‘‘nones’’; Kosmin et al. 2009; Miller and Nakamura 1996; Marwell

and Demerath 2003). Another line of reasoning is that those investigating

secularization have approached it in the wrong manner (e.g., Gorski and Altinordu

2008). Although particular issues may be used as evidence to support or reject this

perspective, historical data show that pre-enlightenment people were not necessarily

more religious in some way than those in the modern world (Butler 2010).

Furthermore, the assumption that differentiation of institutional spheres necessarily

leads to secularization is problematic and masks myriad historical and sociological

complexities regarding institutions and individual behavior (Gorski 2000). Thus, the

manifold forms of secularization make any general claims questionable (Martin

2011).

Yet, there remains a lack of attention to one key aspect of secularization. This is

perhaps most evident in recent debates over the role that religious institutions play

in guiding the presumed moral fabric of the nation, as well as in the related

argument that religious sensibilities have become increasingly privatized and

decoupled from institutional control (Chaves 2011; Houtman and Aupers 2007).

One manifestation of this asks whether religious organizations, or more properly

their leaders, have the trust and confidence of the populace to provide guiding

principles, values, authority, and beliefs. As Chaves (1994) recognized some time

ago, a vital, yet typically overlooked, issue is not whether people continue to

participate in religious activities or believe in supernatural phenomena, but rather

whether their guiding organizations and leaders are still seen as having the authority

to direct the lives of everyday people or provide services not available elsewhere. In

general, following the lead of several observers such as Dobbelaere and Lechner,

Chaves argued that secularization may be envisioned fruitfully as declining

religious authority, or whether religious institutions have had a diminished influence

on other social spheres.

There have been relatively few empirical attempts to examine Chaves’s

argument. Some studies have addressed whether people’s decisions about sexual

behavior, family problems, health, political preferences, or other issues are

influenced by religious thoughts or perceptions (e.g., Yamane 1997). However,

there has been little research that has examined the issue of religious authority using

data across a sufficient length of time to provide an adequate test. After all, it is

widely recognized that secularization, if it occurs, is a gradual process that unfolds

2 Rev Relig Res (2013) 55:1–25

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over several decades (Bruce 2011). One attempt to examine shifts in religious

authority (Hoffmann 1998) is now almost 15 years old. This study showed, using

trend data from the 1970s to early 1990s, some evidence of secularization as

declining religious authority. In particular, there were decreases in confidence in the

leaders of religious organizations over time and among younger cohorts in the U.S.

However, a limitation of this research is that the decreasing confidence levels were

driven mainly by those born in the 1950s and 1960s (boomers and post-boomers), a

group identifiable by their countercultural or anti-establishment tendencies and

declining traditional religious practices and beliefs (Flory and Miller 2008; Sherkat

1998). Moreover, there was a slight increase in confidence among those born in the

early 1970s, which might portend increasing confidence.1

The goals of this research are to (1) furnish a more complete test of Chaves’s

model by updating Hoffmann’s research with data through 2010; and (2) use recent

advances in age-period-cohort (APC) analysis to provide a more robust empirical

examination of trends in reported confidence. Using data from the cumulative

General Social Surveys (GSS), 1973–2010, the results suggest that although period

declines in confidence have continued, the cohort declines were primarily among

those born in the boomer and early post-boomer generations (roughly 1945–1970)

relative to those born earlier (pre-1945) or later (post-1970). These effects appear to

be due mainly to differences in religious participation, especially among more

recent cohorts. In particular, there has been a rebound in confidence among

members of the younger generation who attend religious services. However, the

general decrease on confidence across a variety of institutions suggests that societal

changes more general than secularization have occurred.

Background

Secularization theory has been a large force in religious studies. Research

addressing this theory was particularly vibrant in the 1980s and 1990s as proponents

argued that we were witnessing a period of declining attendance at religious

services, an increasing number of atheists and religious ‘‘nones,’’ and an era when

many religious organizations, especially in the U.S. and Western Europe, saw their

membership declining almost to insignificance (Chaves 1989; Marwell and

Demerath 2003; Swatos and Christiano 1999). Those skeptical of this theory

claimed that, in reality, recent history had experienced a relatively vibrant religious

culture in the U.S. Compared to, say, the early 19th century, attendance levels were

high and personal religious practices robust (Stark 1999). Trend data actually

showed little change during a period when secularization should have been

accelerating (Greeley 1989). More recent evidence of the continued vitality of

religion includes stable attendance rates (Presser and Chaves 2007; Schwadel 2010),

the presumed rise of Evangelical denominations (and others such as Mormons and

Jehovah’s Witnesses) and non-Christian faiths, megachurches, and the home-

1 The cohort used in the analysis that was born in the early 1970s was relatively small, so sampling error

may have accounted for any increase in the trend.

Rev Relig Res (2013) 55:1–25 3

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schooling movement (Chaves 2006; Cooper and Sureau 2007; Perrin et al. 1997).

Religion has also continued to play an influential role in politics and in discussions

about the education system, marriage, parenting, and several other issues.

An alternative argument is that the secularization debate has missed some

important nuances. In particular, secularization is not an all-encompassing

movement that marches in lockstep with modernity. Instead, there are elements

of secularization that may occur at different times and in different places. Moreover,

as Casanova (1994); Chaves (1994) and Dobbelaere (1999) recognized, there are

several layers of secularization. Chaves argued, in particular, that religious

authority—a key aspect of how religious institutions affect societies—may be

affected by three trends: (1) nonreligious institutions gain increasing autonomy from

religious institutions; (2) religious institutions become less differentiated in function

and structure from secular institutions; and (3) there is a decreasing trend in

religious practices and beliefs among individuals. Any of these may occur and be

indicative of secularization, but they need not occur together. Thus, observing a

decrease, increase, or no change in religious practices and beliefs does not provide

complete or sufficient evidence concerning secularization.

Although there are various ways one might examine declining religious authority

(Yamane 1997), one promising approach is to consider whether religious organi-

zations and those who lead them continue to inspire confidence. This was an

approach used by Kleiman et al. (1996) and Hoffmann (1998) to study declining

religious authority. They argued that key evidence of secularization in modern

society is when religious leaders and the organizations they direct lose influence and

credibility in a world where rationalism is increasingly appreciated and scientific

explanations abound. A disenchantment with supernatural explanations, detradition-

alization, individualization of religious sensibilities, and a decoupling of religious

authority from other spheres of influence (political, cultural) may all lead to less

confidence, which points toward one important form of secularization (Bruce 2011;

Houtman and Aupers 2007; Taylor 2007). Admittedly, focusing on confidence is best

understood as an indirect approach to testing Chaves’s secularization model. Yet it

contains a useful analogue for at least two aspects of waning religious authority: ‘‘the

declining capacity of religious elites to exercise authority over other institutional

spheres [and] … the decrease in the extent to which individual actions are subject to

religious control’’ (1994: 757). After all, if religious leaders do not inspire confidence

among the laity, it is very unlikely that they will be able to exercise authority over

social institutions or substantially affect individual actions.

Confidence Revisited

Exploring trends in confidence in religious organizations as a test of changes in

religious authority is a useful approach, yet there have been few empirical

investigations of these trends. As mentioned earlier, Kleiman et al. (1996) and

Hoffmann (1998) examined confidence in the leaders of religious institutions from

the early 1970s to the early 1990s. Both studies found evidence in favor of Chaves’s

model: There were declines in confidence that generalized across demographic

groups. Moreover, Hoffmann determined that declining confidence occurred due to

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period and cohort effects. Particularly consequential were declines across cohorts:

members of younger cohorts (born in the 1950s and 1960s) expressed significantly

lower confidence than those born during earlier periods of the 1900s. There was also

a bifurcation in confidence among younger cohorts by religious service attendance,

with those attending services more often reporting substantially higher confidence

than others (among older cohorts, there was no distinction by attendance).

In general, the results of these studies are suggestive of declining religious

authority. However, there are some important limitations to this research that

recommend additional analyses. First, Hoffmann (1998) also found evidence of

declining confidence in several other organizations, such as banks, the press,

organized labor, and educational institutions. Recent evidence suggests that

generally declining confidence has continued (Chaves 2011; Gallup 2012; Owens

2012; Pew Research Center 2010). Hence, we are seeing a trend of disenchantment

with and lack of trust of many organizations and institutions (Keele 2007; Robinson

and Jackson 2001); religious organizations may simply be caught in this broader

inclination toward skepticism and disillusionment. There may have been particular

influences on confidence in the leadership of religious organizations, however. In

particular, the televangelist scandals of the 1980s (Smith 1992) and the clergy

scandals of the 2000s (Shupe 2008) have likely shaped public opinion about

religious organizations and their place as a source of guidance and authority. Yet,

the general trend of diminished confidence across institutions seems indicative of

something broader and more abstract than secularization alone.

Second, the cohort declines in confidence observed by Hoffmann and Kleiman

et al.—as well as diminishing trust and confidence in other institutions (Robinson and

Jackson 2001)—were driven largely by those who were born in the 1950s and 1960s

(see Hoffmann 1998; Fig. 1). This is a group that is well-known for its countercultural

and anti-establishment orientations and its idiosyncratic behaviors relative to other

cohorts, both before and after (Sherkat 1998, 2008). There was tentative evidence,

however, that confidence increased among those born in the early 1970s. This could

reflect a resurgence in confidence or, because it was based on a relatively small

subsample size, it might be due to sampling error (see Hoffmann 1998; Table 1).

Third, the empirical methods used in these earlier analyses were inadequate for

capturing the relative influences of age, periods, and cohorts on changes in

confidence. Given the well-known empirical conundrum of sorting out APC effects in

models that use repeated cross-sectional data (Glenn 2005), earlier studies were

forced to assume that age effects were constant so that they could focus on period and

cohort changes. In the interim, better empirical methods have been developed to study

APC effects (e.g., Yang et al. 2008) and have been used fruitfully to study changes in

religious beliefs and practices (Schwadel 2010, 2011). These methods allow the

disentanglement of APC effects, thus allowing the observation of, say, cohort effects

on changes in attitudes while statistically adjusting for age and period effects.

Research Questions

The goals of this research, therefore, are to, first, update the earlier trend analyses

with data that span 1973–2010 to determine whether the shifts in confidence noted

Rev Relig Res (2013) 55:1–25 5

123

in previous studies have continued, thus providing important evidence with which to

judge part of Chaves’s (1994) model of declining religious authority. Second, it

utilizes better methods for studying APC effects. This is especially important since

the earlier analyses were forced to assume constant age effects in order to highlight

period and cohort effects.

In general, the following research questions guide the analyses:

• Are changes in confidence by period and cohort independent of age effects?

• Have declines in confidence in the leaders of religious organizations continued

or abated?

• Is the attendance by cohort effect found in the earlier analysis still notable?

• How do shifts in confidence in the leaders of religious institutions compare to

shifts when considering the leaders of other institutions?

Data and Methods

The pooled GSSs from 1973 to 2010 are used to examine trends in confidence. The

GSSs are based on repeated cross-sectional samples of noninstitutionalized persons

residing in the U.S. Each sample is independently drawn and includes approxi-

mately 1,500–2,000 respondents. Many of the survey questions, including those that

address confidence in institutions, are repeated regularly, thus making the GSSs

optimal for studying attitudinal trends in the U.S.

The relevant questions used in this research were asked from 1973 to 2010. Since

1994, the survey has been conducted in even years. To create a consistent periodicity,

odds years prior to this time point were combined with adjacent even years (e.g.,

1973 ? 1974; 1976 ? 1977). Thus, 19 periods are available, although, as described

later, these are collapsed into five-year time intervals. Sampling weights are used to

(1) compensate for oversampling in certain years to minimize coverage error; and (2)

to adjust for different sample sizes across the years (thus, reducing the risk of

heteroscedastic errors). The sample size used in the analysis is 35,959.

The principal outcome variable, confidence in the leaders of religious organi-

zations, is measured by the following question: ‘‘As far as the people running these

institutions are concerned, would you say you have a great deal of confidence, only

some confidence, or hardly any confidence at all?: Organized Religion’’ (It was not

asked in 1972). It is important to note that this question asks about ‘‘people running

these institutions’’ rather than the institutions in general. This provides a more

precise view of Chaves’s ideas about the influence of ‘‘religious elites’’ rather than

generalized views of an amorphous organization. In the analyses presented later,

these responses are coded as 1 = great deal of confidence and 0 = only some or

hardly any confidence. Other specifications, such as coding the responses as

{1 = great deal or some, 0 = hardly any} made little difference in the general

results.2 I also considered additional confidence items that asked about leaders of

2 The particular coding strategy was used for two reasons: (a) one of the key analytic techniques (IE)

used to assess APC trends does not allow ordinal responses; thus, I opted to examine the outcome as a

binary response variable. (b) I examined other specifications such as a proportional odds (ordinal logistic)

regression model, a partial proportional odds regression model, and a multinomial logistic regression

6 Rev Relig Res (2013) 55:1–25

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the following organizations and institutions: Banks and financial institutions,

educational organizations, organized labor, the press, medicine, and science. The

variables representing these questions are coded in an identical manner as the

variable measuring organized religion.3

In order to specify within- and between-cohort (cohort replacement) and age

effects over time, it is necessary to measure survey year, birth year, at age at

interview for each respondent. Thus, GSS variables measuring each of these are

used. To make them comparable and consistent, and to smooth the trends, I recoded

each into approximate five-year intervals (e.g., birth year: 1905–1909, 1910–1914;

age: 30–34, 35–39; year: 1980–1984, 1990–1994; cf. Yang et al. 2008). This

resulted in five survey periods, 13 age groups, and 19 birth cohorts.

Since this research is partially replicative of Hoffmann’s (1998) analysis, the

models include most of the same covariates that were used in this earlier study and

that are commonly used in research on confidence in institutions (e.g., Cook and

Gronke 2005; Gronlund and Setala 2010; Kleiman et al. 1996; Lipset and Schneider

1983). These include years of formal education (coded 0–20); marital status

represented by four dummy variables with ‘‘married’’ as the omitted reference

category; two dummy variables representing race/ethnicity (African-American and

other Racial Group) with Caucasian as the reference category; residence in the

South (l = yes, 0 = no); work status (represented by six dummy variables with full-

time employment as the reference category); number of children; sex (female = l,

male = 0); family income (represented by deviations from within-year means); and

size of community. Studies also indicate that there is substantial variation in

confidence by both political party affiliation and political ideology (Cook and

Gronke 2005; Lipset and Schneider 1983). In particular, there is a U-shaped

relationship between confidence and party affiliation: survey respondents who

describe themselves as Democrats or Republicans tend to report more confidence in

organizations than those who describe themselves as Independents. The relation-

ships between confidence and political ideology are also nonlinear, but they vary

depending on the institution considered. Therefore, two dummy variables were

Footnote 2 continued

model (Hilbe 2009). However, with one important exception (see footnote 7), these other specifications

did not change the results much, nor did they change the interpretations of the APC trends.3 As noted by reviewers of an earlier draft of this article, there are a few different analytical approaches

that might be used to examine confidence in religious organization vis-a-vis other organizations and

institutions. First, the other confidence measures might be included as control variables in models that use

confidence in religious organizations as the outcome variable. The models’ parameters could then be

conceptualized as the association between, say, cohort and confidence in religious organizations when

confidence in the other organizations and institutions is constantly low. Although promising, including the

other confidence measures led to severe problems with model convergence due to multicollinearity. In

other words, there are relatively strong statistical associations among the confidence measures. Second,

one might include a difference score (Wilcox et al. 1989) wherein confidence in religious institutions is

measured as a deviation from the mean of the other confidence measures. Although this works well with

continuous outcomes, it results in severely truncated scores with categorical indicators. Nevertheless, as

discussed in footnote 7, I estimated a set of models using a deviation score as the outcome variable. Third,

similar to earlier studies (e.g., Hoffmann 1998; Kleiman et al. 1996) parallel models may be used for each

confidence measure. As explained in the results section, the trends are similar regardless of the confidence

item used.

Rev Relig Res (2013) 55:1–25 7

123

created for each: Democrat and Republican (‘‘strong’’ or ‘‘not very strong’’ for each)

versus Independents/Others (reference group); and liberals and conservatives

(‘‘extremely liberal’’ and ‘‘liberal,’’ or ‘‘extremely conservative’’ and ‘‘conserva-

tive’’) versus moderates (reference group).

Religious affiliation is also considered in the models. The measurement is based

on the common RELTRAD approach that distinguishes the following groups:

Evangelicals, Mainline Protestants, Black Protestants, Catholics, Jews, those of

other faiths, and nonaffiliates (Steensland et al. 2000). Although the RELTRAD

scheme has been used widely and is appealing, mainly because of its ability to

identify Evangelicals, it suffers from an important limitation: collapsing moderate

and liberal Protestants into one mainline category. Yet, other research suggests that

distinguishing these two groups is important when examining attitudes toward

various issues (e.g., Hoffmann and Johnson 2005; Sherkat 2012). Hence, the

mainline category is split into liberal and moderate Protestant faith traditions.

Details about the two groups in the GSS are provided in Smith (1990). Those who

reported no organized religious affiliation serve as the reference category because

they tend to have the lowest confidence levels (Hoffmann 1998).

Finally, the effects of religious service attendance are examined by using the GSS

variable that asks ‘‘How often do you attend religious services?’’ This variable

ranges from 0 = ‘‘never’’ to 8 = ‘‘more than once a week’’ (cf. Schwadel 2010).

There are two other variables measured in the GSS that have relevance for

confidence in organizations, trust (‘‘Generally speaking, would you say that most

people can be trusted or that you can’t be too careful?’’) and anomia (‘‘Most public

officials (people in public offices) are not really interested in the problems of the

average man’’). Although past research (Lipset and Schneider, 1983) and

preliminary analyses implies that both variables have the expected effect on

confidence in religious and other organizations, each is affected by missing values

problems (more than 20 % for trust and 35 % for anomia) that would reduce the

usable sample size considerably if one were to use leastwise deletion. Models with

and without these two variables indicate that, although their inclusion improved

model fit, they did not modify the effects of other relevant variables. Since the

analyses are concerned mainly with APC effects and in the interests of analyzing an

unbiased nationally representative sample, these two variables are omitted from the

analysis.4

Analytic Methods

As mentioned earlier, in the years since the earlier studies of confidence in religious

organizations, there have been important advances in APC analysis. Because of

identification problems (e.g., period = age ? cohort), most methods force one to

assume that, for example, age effects are constant in order to estimate period and

cohort effects (e.g., Firebaugh 1997; Glenn 2005), or to make quite restrictive

4 Although the GSS questions are asked in a randomly rotated manner, an analysis of the missing data

properties for these two variables indicated, among the subsample of those who responded to questions

about confidence, that they were not missing at random (MAR). Thus, an imputation model may lead to

biased parameter estimates (Allison 2000).

8 Rev Relig Res (2013) 55:1–25

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assumptions about one or more of the APC effects (Miller and Nakamura 1996).

However, a recent model, known as the intrinsic estimator (IE), makes assumptions

that do not depend on specific parameters of interest (Yang et al. 2008) and thus may

be used to estimate unbiased effects of age, period, and cohort. The IE approach does

not require the researcher to impose constraints such as constant age effects. Instead,

the constraints are not based on the variables in the model and thus are independent of

these variables. Moreover, the results may be interpreted in a manner familiar to those

with a basic understanding of regression analysis. For example, in the analyses

presented later, the results are based on a logistic regression model using the IE

estimator and thus may be interpreted in terms of log-odds ratios.

Specifically, the IE approach uses a principal components (PC) method to

estimate a constrained parameter vector b that is a linear function of the parameter

vector b of the unconstrained APC accounting model:

b ¼ Bþ sB0

In this representation, s represents a scalar corresponding to a specific solution

and B0 is a unique eigenvector of length 1. B0 does not depend on the observed

outcomes, but rather on the design matrix X, or the number of age groups and

periods in the model. In order to estimate this function, the model computes a set of

eigenvalues and eigenvectors that are normalized to have length 1, including

eigenvector B0 that corresponds to a unique eigenvalue of zero; estimates a PC

regression with response y along with a design matrix with column vectors that are

PC; and then uses an orthogonal matrix to transform the resulting coefficients to

APC estimates of standard form (Yang et al. 2008). The IE thus eliminates the need

for equality constraints or other restrictive assumptions. Yang et al. (2004) and Fu

and Hall (2006) provide additional technical details and proofs regarding the IE.

Since the outcome, confidence in institutions, is measured as a binary variable, I use

the IE along with a generalized linear model with a logit link and a binomial

distribution. This results in APC coefficients that are interpretable as log-odds.

Although the IE is useful for examining APC trends and allows for covariates, I

also extend the analysis to examine group-specific changes in confidence. This

analysis relies on a cross-classified random-effects model (CCREM) advocated by

Yang and Land (2008). Specifically, a multilevel logistic model with period and

cohort as random effects and other covariates as fixed effects is specified. This

includes the following specification:

Level 1 : lnPrfConfidence ¼ 1g

1� PrfConfidence ¼ 1g

� �ijk

¼ b0jk þ b1ageijk þ b2age2ijk þ bqXijk þ eijk

Level 2 : b0jk ¼ c0 þ l0j þ m0k

These equations imply that individual i is nested within cohort j and period k. The

error terms from the equations (eijk, l0j, m0k) are assumed normally distributed with

constant variance (although weights are used to compensate for the effects of different

sample sizes across the periods, thus reducing the likelihood of heteroscedasticity).

The respondents’ log-odds of having confidence in a particular institution is a function

Rev Relig Res (2013) 55:1–25 9

123

of age, age-squared, and a set of individual-specific covariates (Xijk).5 The intercept

varies by period and birth cohort. Cross-level interaction terms allow an examination

of group-specific changes, either by cohort or by period. In particular, cross-level

interactions between religious service attendance and birth cohort provide a test of

whether confidence is affected by attendance more among young cohorts than among

older cohorts (cf. Hoffmann 1998). The CCREMs are estimated using SAS’s glimmixand Stata’s xtmelogit procedures.

Results

Figure 1a–c provide trends in the probabilities of a great deal of confidence in the

leaders of religious organizations by age, period, and cohort. The trend lines are

accompanied by 95 % confidence bands in gray. The age effects are quadratic and

indicate that the lowest degree of confidence appears among those between the ages

of 30 and 50, with increasing confidence among older people. The period effects

show that confidence decreased substantially from the 1970s to the 2000s, falling

from a probability of about 0.37 to a probability of just above 0.2 (cf. Chaves 2011).

The cohort effects demonstrate a nonlinear pattern, with falling confidence that

flattened out by the 1950–1980 cohorts, followed by an uptick among those born

from about 1985 onward. Thus, there is tentative support for Hoffmann’s (1998)

finding that confidence increased among younger cohorts. However, the three trends

shown in these figures do not disentangle APC effects, so the IE approach is a

necessary step.

As a preliminary approach, however, Table 1 provides a depiction of simulta-

neous period and cohort influences. It shows the probability of high confidence by

birth year and year of survey (both in approximate five-year intervals) (cf.

Hoffmann 1998; Yang et al. 2008). The rows and columns that show specific cohort

and year probabilities are accompanied by v2 and p values derived from a series of

weighted logistic regression models to test whether the differences are statistically

significant.

The results suggest little change over time among the oldest cohorts and the

youngest cohorts, with varying degrees of change among others. They also indicate

that there are statistically significant differences among cohorts within each year-

group. In particular, during the earlier periods there was a generally decreasing trend

in confidence among younger generations. However, between about 2002 and 2010

there was a nonlinear pattern, with higher levels of confidence among the oldest and

the youngest cohorts than among the middle cohorts. Once again, this points to an

upswing in confidence among the youngest cohort members represented by the

GSSs.

Table 2 provides the results of the IE analysis designed to examine age, period,

and cohort effects. The first model provides these effects without covariates,

5 Positing a quadratic effect of age is based on the curvature found in the observed confidence

probabilities (see Fig. 1a).

10 Rev Relig Res (2013) 55:1–25

123

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General Social Surveys, 1973 – 2010

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Fig. 1 a Age effects on confidence in religious organizations b period effects on confidence in religiousorganizations c cohort effects on confidence in religious organizations

Rev Relig Res (2013) 55:1–25 11

123

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12 Rev Relig Res (2013) 55:1–25

123

whereas the second model includes the covariates. Note that the coefficients are

presented in terms of log-odds.

The results of the first model indicate that those between the ages of 25 and 49

report the lowest odds of having a great deal of confidence. The group that shows

higher odds of confidence includes those 75 and older. The period effects

demonstrate a negative trend that appears to have accelerated in the 2000s. The

cohort effects are the most complex, however, with varying trends across birth

groups. Yet, as suggested by Fig. 1c, the lowest odds occur among those born in the

1940s through the early 1970s, or the baby boomer and the early post-boomer

generations (Flory and Miller 2008; Wuthnow 2007). Yet those born from about

1975 to the early 1990s are not lower than average in the odds of reporting a great

deal of confidence, thus further demonstrating a rebound among the most recent

adult cohorts.

The second model in Table 2 includes the additional covariates. Not surprisingly,

those who belong to a faith tradition report higher confidence than nonaffiliates, as

do those who attend religious services more often. Education and higher family

income are associated with lower odds of reporting confidence in religious

organizations, whereas the other covariates have little influence on this outcome.

Introducing these covariates has a modest influence on the age, period, and cohort

effects; however, they do help account for the higher confidence among those aged

65–74 and for the lower confidence among those born in 1950–1954 and

1970–1974. An auxiliary analysis indicates that once religious service attendance

is included in the model, the log-odds of reporting a great deal of confidence moves

closer to zero. Therefore, it is useful to explore differences in confidence by age,

cohort, and attendance in greater detail.

The next set of results is from the CCREM analysis described earlier.6 These

are presented in Table 3. The first model includes only the age effects and the

period and cohort random effects. As implied by the earlier analyses, age has a

quadratic association with confidence, decreasing until an inflection point at about

age 60 and increasing thereafter. The period effects are primarily negative, as

shown in the random effects panel. This is also consistent with the APC–IE

analysis presented earlier. There is a little variation in the cohort random effects,

but also a great deal of consistency. In particular, those who were born in the mid-

6 As mentioned in footnote 2, I relied on a logistic regression model in both the IE analysis and the

CCREM analysis. However, the original measure of confidence was ordinal, thus suggesting that an

ordinal or multinomial logistic might be preferable. Thus, I also estimated models that considered the

outcome variable as an ordinal variable and as a multinomial variable. These included the following

models: a cumulative odds model, a partial proportional odds model, and a multinomial logistic model

(see Hilbe 2009 for details about these models). The cumulative odds model was estimated using SAS’s

glimmix command. The partial proportional odds and multinomial logistic model were estimated

piecemeal. For example, I created a set of outcome variables that were coded as (a) 1 = great deal of

confidence versus 0 = some/hardly any confidence; and (b) 1 = great deal/some confidence versus

0 = hardly any confidence and estimated two CCREMs to approximate a partial proportional odds

model. Although there was some variation in the results of these models relative to the logistic regression

with the binary outcome, the general results were similar. One exception occurred in the partial

proportional odds model: the increasing confidence among the younger cohorts was even more dramatic

in this model than in the model presented in Table 2. The results of these alternative models are available

upon request.

Rev Relig Res (2013) 55:1–25 13

123

Table 2 Age-period-cohort IE models of confidence in religious organizations, GSSs, 1973–2010

Variable Model 1 Model 2

Log-odds p value Log-odds p value

Intercept -0.865 \0.001 -1.923 \0.001

Age

18–24 -0.004 0.927 0.121 0.020

25–29 -0.156 \0.001 0.017 0.726

30–34 -0.187 \0.001 -0.095 0.047

35–39 -0.203 \0.001 -0.122 0.014

40–44 -0.217 \0.001 -0.168 \0.001

45–49 -0.199 \0.001 -0.153 0.006

50–54 -0.064 0.203 -0.066 0.237

55–59 -0.101 0.048 -0.150 0.007

60–64 -0.027 0.632 -0.079 0.185

65–69 0.123 0.029 0.018 0.769

70–74 0.124 0.041 -0.013 0.855

75–79 0.397 \0.001 0.237 0.003

80 and older 0.513 \0.001 0.454 \0.001

Period

1973–1978 0.351 \0.001 0.355 \0.001

1980–1984 0.261 \0.001 0.263 \0.001

1986–1989 -0.020 0.597 -0.035 0.370

1990–1994 -0.107 \0.001 -0.142 \0.001

1996–2000 0.074 0.024 0.073 0.038

2002–2004 -0.287 \0.001 -0.313 \0.001

2006–2010 -0.273 \0.001 -0.202 \0.001

Birth cohort

Pre-1900 -0.050 0.749 -0.132 0.482

1900–1904 0.073 0.488 -0.005 0.964

1905–1909 0.226 0.012 0.212 0.036

1910–1914 0.104 0.171 0.060 0.468

1915–1919 0.074 0.266 0.002 0.975

1920–1924 0.231 \0.001 0.210 \0.001

1925–1929 0.053 0.350 0.021 0.745

1930–1934 0.076 0.200 0.039 0.556

1935–1939 0.080 0.180 0.056 0.391

1940–1944 0.016 0.776 0.026 0.660

1945–1949 -0.158 0.002 -0.126 0.024

1950–1954 -0.145 0.002 -0.082 0.102

1955–1959 -0.261 \0.001 -0.207 \0.001

1960–1964 -0.249 \0.001 -0.213 \0.001

1965–1969 -0.127 0.019 -0.148 0.012

1970–1974 -0.131 0.030 -0.085 0.206

14 Rev Relig Res (2013) 55:1–25

123

Table 2 continued

Variable Model 1 Model 2

Log-odds p value Log-odds p value

1975–1979 -0.039 0.589 -0.006 0.942

1980–1984 0.051 0.617 0.163 0.182

1985–1992 0.175 0.162 0.216 0.167

Religious attendance 0.159 0.001

Religious tradition

Evangelical 0.903 \0.001

Mainline Protestant 0.831 \0.001

Liberal Protestant 1.014 \0.001

Black Protestant 1.087 \0.001

Catholic 1.031 \0.001

Jewish 0.532 \0.001

Other faith 0.680 \0.001

Female -0.075 0.022

Number of children 0.013 0.158

Education -0.036 \0.001

Family income -0.019 0.004

Lives in South -0.014 0.668

Size of community -0.004 0.340

Race/ethnicity

African-American 0.014 0.830

Other ethnic -0.043 0.570

Marital status

Widowed 0.025 0.662

Divorced/separated -0.020 0.670

Never married 0.087 0.078

Work status

Part-time 0.010 0.851

Unemployed 0.004 0.950

Retired 0.012 0.849

Student 0.143 0.113

Keep house 0.033 0.481

Political affiliation

Democrat 0.125 \0.001

Republican 0.252 \0.001

Political ideology

Liberal -0.059 0.155

Conservative 0.035 0.302

Sample size 35,959 35,959

Rev Relig Res (2013) 55:1–25 15

123

1940s through the mid-1960s report the lowest level of confidence in both

analyses. The main difference is that the rebound effect in confidence among

those born from 1985 on is statistically significant in the first CCREM model.

Note also that the variance components indicate that there is statistically

significant variation in confidence across both periods and cohorts even after

accounting for age.

Model 2 adds the covariates to the analysis. This changes the results somewhat,

especially the cohort effects. In particular, only the 1950–1964 cohorts remain

lower, on average, in the odds of having a great deal of confidence in religious

organizations. Moreover, the cohort effect among those born between 1985 and

1992 is reduced by about half and is no longer statistically significant. As with the

APC–IE analysis, an auxiliary analysis indicates that the addition of religious

service attendance leads to this reduction. Thus, the next step is to determine

whether attendance moderates the association between cohort and confidence.

The results of a CCREM model that tests for this moderating effect indicates

that there is a statistically significant interaction between birth cohort and religious

service attendance (p \ 0.05). In particular, differences in confidence by religious

attendance are significantly greater among the 1985–1992 cohort than among the

1980–1984 or the 1950–1974 birth cohorts. Since birth cohort is measured

categorically, it is challenging to provide a clear sense of these effects in a table.

Therefore, Fig. 2 shows trends in the predicted probabilities of confidence by

cohort and attendance. High attendance includes those in the 75th percentile and

higher attendance includes those in the lower 25th percentile. In order to

determine whether the differences implied by the two lines are statistically

significant, I used a bootstrap approach with 500 resamples to estimate within- and

between-cohort effects. The results indicate that statistically significant differences

by attendance occur among all of the cohort comparisons, but that these

differences increased from about 47 % in the cohort born early in the 20th century

to 72 % among those born between 1985 and 1992. Much of this is due to the

rebound in confidence that occurred among those attending more frequently; their

confidence increased from a probability of about 0.37 among those born between

roughly 1945 and 1970 to about 0.46 among those born between 1985 and 1992.

On the other hand, the probability of reporting confidence among those attending

rarely or never has remained close to 0.13 since the 1945 cohort. Thus, in support

Table 2 continued

Variable Model 1 Model 2

Log-odds p value Log-odds p value

BIC 33,959.8 31,489.0

Note: The variable used to measure confidence in religious organizations is based on the following

question: ‘‘As far as people running these institutions are concerned, would you say you have a great deal

of confidence, only some confidence, or hardly any confidence at all in them.’’ It is coded 1 = great deal

of confidence; 0 = some/hardly any confidence. The model specifies this as a binomial variable with a

logit link. The p values are based on two-tailed tests

16 Rev Relig Res (2013) 55:1–25

123

Table 3 Cross-classified random effects model of confidence in religious organizations, GSSs,

1973–2010

Model 1 Model 2

Variable Log-odds p value Log-odds p value

Intercept -0.448 0.036 -1.148 0.001

Age -0.033 \0.001 -0.038 \0.001

Age2 0.004 \0.001 0.004 \0.001

Religious attendance 0.163 \0.001

Religious tradition

Evangelical 0.844 \0.001

Mainline protestant 0.823 0.001

Liberal protestant 0.989 \0.001

Black protestant 0.982 \0.001

Catholic 0.967 \0.001

Jewish 0.524 \0.001

Other faith 0.638 \0.001

Female -0.060 0.039

Number of children 0.011 0.166

Education -0.038 \0.001

Family income -0.021 0.002

Lives in South -0.016 0.582

Size of community -0.004 0.433

Race/ethnicity

African-American -0.012 0.829

Other ethnic -0.059 0.410

Marital status

Widowed 0.004 0.425

Divorced/separated -0.032 0.309

Never married 0.043 0.898

Work status

Part-time 0.006 0.898

Unemployed 0.011 0.833

Retired -0.009 0.861

Student 0.070 0.372

Keep house -0.004 0.928

Political affiliation

Democrat 0.112 0.003

Republican 0.256 \0.001

Political ideology

Liberal -0.047 0.155

Conservative 0.029 0.342

Rev Relig Res (2013) 55:1–25 17

123

Table 3 continued

Model 1 Model 2

Variable Log-odds p value Log-odds p value

Random effects

Period

1973–1978 0.379 \0.001 0.395 \0.001

1980–1984 0.279 0.007 0.274 0.007

1986–1989 -0.021 0.838 -0.067 0.515

1990–1994 -0.135 0.189 -0.178 0.079

1996–2000 0.051 0.617 0.039 0.705

2002–2004 -0.288 0.010 -0.287 0.009

2006–2010 -0.266 0.011 -0.175 0.095

Birth cohort

Pre-1900 -0.001 0.988 -0.008 0.912

1900–1904 0.088 0.281 0.038 0.567

1905–1909 0.035 0.633 -0.002 0.975

1910–1914 0.094 0.161 0.044 0.438

1915–1919 0.087 0.157 0.062 0.233

1920–1924 0.133 0.021 0.100 0.043

1925–1929 0.017 0.764 0.002 0.961

1930–1934 0.041 0.464 0.008 0.868

1935–1939 0.045 0.401 0.063 0.186

1940–1944 -0.126 0.015 -0.077 0.096

1945–1949 -0.127 0.010 -0.035 0.425

1950–1954 -0.207 \0.001 -0.130 0.003

1955–1959 -0.170 \0.001 -0.122 0.008

1960–1964 -0.137 0.020 -0.108 0.035

1965–1969 -0.089 0.172 -0.058 0.303

1970–1974 0.015 0.840 0.028 0.651

1975–1979 -0.042 0.611 0.011 0.877

1980–1984 0.102 0.263 0.067 0.361

1985–1992 0.292 0.004 0.121 0.126

Variance components

Year 0.068 0.047 0.065 0.047

Cohort 0.018 0.025 0.008 0.057

Sample size 35,959 35,959

BIC 42,242.3 38,254.6

Note: The variable used to measure confidence in religious organizations is based on the following

question: ‘‘As far as people running these institutions are concerned, would you say you have a great deal

of confidence, only some confidence, or hardly any confidence at all in them.’’ It is coded as 1 = great

deal of confidence; 0 = some/hardly any confidence. The model specifies this as a binomial variable with

a logit link. The p values are based on two-tailed tests

18 Rev Relig Res (2013) 55:1–25

123

of earlier analyses of these trends (Hoffmann 1998), there is a divergence of

confidence in the leaders of religious organizations within younger birth cohorts

that is tied to patterns of attendance.7

As a final step, I imposed the same APC–IE and CCREM models using the other

confidence measures as outcomes. These included confidence in the leaders of the

following: banks and financial institutions, educational organizations, organized

labor, the press, medicine, and science. In results not shown here, the trends were

remarkably similar regardless of the institution examined. There was greater general

confidence in some institutions (e.g., medicine) than in others (e.g., labor, banks),

but changes across age, periods, and cohorts were similar. In particular, boomer and

early post-boomer generations reported the least confidence; earlier cohorts and

older people reported relatively high confidence. Moreover, there was evidence of a

High attendance

Low Attendance

47%

57% 72%

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Fig. 2 Confidence in religious organizations, by birth cohort & attendance, GSS 1973–2010

7 As suggested by a reviewer, I also estimated a set of models based on deviation scores (see footnote 3).

The deviation score was defined as P(great deal of confidence in religious organizations)—Mean(P(great

deal of confidence in other organizations)). The resulting score was not normally distributed, although

there was evidence of continuity. Thus, I treated it as a continuous variable in the APC–IE and the

CCREM models and used a linear parameterization. The results of both sets of models demonstrated

remarkable consistency with the models presented in Tables 2 and 3, as well as the results shown in

Fig. 2. One exception concerned the quadratic effect of age in the CCREM model. Rather than a clear

concave pattern with the age coefficient negative and the age2 coefficient positive (see Table 3), the

model with the deviation score included a non-statistically significant age coefficient (b = -0.0049,

p = 0.58) and a positive age2 coefficient (b = 0.002, p = 0.002). This suggests that the deviation score is

relatively flat through roughly age 60 and then begins to increase at older ages once period and cohort

effects are taken into account.

I also estimated the cohort by attendance interactions that are illustrated in Fig. 2, but substituted the

deviation score as the outcome variable. The resulting pattern again showed remarkable consistency with

the earlier analyses. For example, the difference in the deviation score for those high in attendance versus

those low in attendance in the 1905–1909 birth cohort was about 88 %; the difference in the 1940–1944

birth cohort was 202 %; and the difference in the 1985–1992 cohort was 222 %. The results of these

analyses and the figure that illustrates the differences across birth cohorts are available upon request.

Rev Relig Res (2013) 55:1–25 19

123

rebound effect among younger cohorts (born 1985 and thereafter). However, the

larger rebound among younger cohort members who attended religious services

more often (see Fig. 2) was not apparent in these other analyses. Details of analyses

with the other confidence items are available upon request.

Discussion

Although secularization theory continues to generate widespread debate (Berger

2008; Bruce 2011; Gorski and Altinordu 2008; Martin 2011), much of the research

has focused on whether religious activities or beliefs have declined or remained the

same; or whether there are a growing number of atheists or nonaffiliates. Yet,

secularization likely has several levels, including a general societal disenchantment

with religious organizations and the authority that their leaders claim to have

(Casanova 1994; Chaves 1994; Dobbelaere 1999; Taylor 2007). As Chaves (1994)

reminds us, secularization may occur at one level but not another. For instance, the

loss of authority among organizational leaders may occur even as individual beliefs

and activities remain constant.

In this analysis, the notion of secularization as declining religious authority is

examined in the U.S. by considering trends in confidence in the leaders of religious

organizations. Although this approach has been used in past studies (Hoffmann

1998; Kleiman et al. 1996), recent trends have not been explored. Moreover, there

are now better empirical methods for exploring trends by age, period, and cohort

(Yang and Land 2008). Thus, as mentioned earlier, three research questions guided

the analyses concerning religious organizations:

(1) Are changes in confidence by period and cohort independent of age effects?

(2) Have declines in confidence in the leaders of religious organizations continued

or abated?

(3) Is the attendance by cohort effect found in the previous study still notable?

Moreover, since earlier research has found similar declines in confidence in other

institutions, such as banks, the press, organized labor, and education, another

research question asked

(4) How do shifts in confidence in religious institutions and their leaders compare

to shifts in confidence among other institutions?

The results indicate, first, that changes in confidence in religious organizations by

period and cohort do appear to be independent of age effects. According to the

APC–IE and CCREM analyses age has a concave association with confidence, with

the lowest levels among those in their 30s, 40s, and 50s. Yet the decreasing period

trend and the nonlinear cohort effects are similar to those found in earlier analyses

even after considering these age effects (cf. Chaves 2011).

Second, the results demonstrate that declines in confidence have continued across

periods, but the decreases across cohorts have abated. Recall that Hoffmann (1998)

found that there was a slight increase in confidence among those born in the early

1980s that followed a linear decrease among those born in earlier years. The present

20 Rev Relig Res (2013) 55:1–25

123

analysis does not support this increase; there is no empirical evidence that the

1970–1974 or 1975–1979 cohorts (the post-boomers) increased in confidence

relative to earlier cohorts.

Nevertheless, members of these cohorts have not become less confident than their

predecessors; rather, the average probability flattened out. This could reflect a lower

bound or asymptote of confidence, or it might reflect shifts in perceptions of the

leaders of religious organizations among younger people. Moreover, there is some

indication of an uptick in confidence among the cohort born between 1985 and 1992

(see Table 3). It is interesting to note, though, that this significant increase is

attenuated with the introduction of religious service attendance.

Therefore, the third question becomes especially relevant since it considers the

role of attendance. Earlier analyses found that there was a larger gap in confidence

among younger cohorts than in older cohorts when considering those who attended

often compared to those who rarely attended (Hoffmann 1998). The present findings

reinforce this observation. Whereas attending religious services is consistently

associated with higher confidence, this has increased in magnitude among more

recent cohorts. It appears, therefore, that a rebound in confidence is driven largely

by younger cohorts who attend more often. Those who rarely attend or do not attend

at all have quite low confidence in religious organizations (see Fig. 2). Of course,

this may be interpreted in a couple of different ways since the data do not allow a

determination of causal direction. First, perhaps confidence is a consequence of

greater attendance, particularly among young cohorts. Or, second, certain members

of the younger cohorts may have greater confidence for some reason and this

translates into higher attendance. Regardless of the temporal order, the key insight is

that the analyses do point toward an increasing bifurcation of confidence among

young cohorts that is linked to attendance patterns. This is important for

understanding shifts in how religious organizations and their leaders are perceived

by the general populace.

Such a phenomenon also has important implications for and is informed by

studies of religious revitalization among young people (Achterberg et al. 2009;

Roeland et al. 2010). Religious young people, even though they may be increasingly

in the minority, tend to resist calls for secularist-oriented social relationships and

have been crucial to revitalization efforts in many nations. They may have

diminished in relative numbers, but these young people have been influential in

calling for a return to, or increase in, religion to the public square, in conservative

religious political mobilization, and in interfaith conflicts. Thus, their relatively high

confidence may be either a byproduct of the way they participate in public and

private religion, or a direct result of it.

The final research question asks whether shifts in confidence generalize across

institutions and organizations. The brief answer is that they do in a consistent way.

Decreasing confidence is generalizable to several organizations, both religious and

secular. Studies confirm that the level of confidence in banks and financial

institutions, political parties, government bodies, and labor unions continued to

decline throughout the 2000s (Gallup 2012; Keele 2007; Owens 2012). Some blame

this growing lack of confidence on a rise in societal skepticism (Cook and Gronke

2005). It has also been accompanied by increasing distrust of many types of

Rev Relig Res (2013) 55:1–25 21

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organizations and individuals (e.g., Paxton 2005; Robinson and Jackson 2001).

Nevertheless, as described in the results section, I found that boomer and early post-

boomer generations reported the least confidence in several organizations, yet there

was evidence of a rebound in confidence among the echo boomers, or those born in

the 1980s and early 1990s. Therefore, secularization as declining religious authority

may simply be derivative of increasing skepticism or anti-establishment attitudes

that have persisted among the baby boomers (Sherkat 1998), which some argue is

due to their heightened tendency to favor rationalism and scientism. These have led

to an increased inclination to require firm, substantiable evidence before believing

organizational claims, whether religious or secular. Yet, these tendencies may be

waning among the echo boomers.

What implications do these results have for secularization theory? A concern

with confidence is important for determining whether religious organizations have

some type of unique authority that is not found among secular groups. Yet, if

religious organizations and their leaders are seen as lacking unique authority, then it

seems likely that they have become less differentiated in function and structure from

secular institutions (Chaves 1994). The results suggest, though, that declining

religious authority is not uniform in the U.S. Rather, there is a growing divide

between younger cohorts who participate in religious organizations and those who

do not. In general, there has been a growing bifurcation in confidence that is due, in

part, to differences in patterns of attendance.

However, it is especially important to note that the results might be used to argue

that secularization theory is too parochial. There is little evidence that declining

confidence is unique to religious organizations and their leaders. Rather, especially

among the baby boomers and post-boomers, diminished confidence in several

institutions is manifest. Moreover, a return of confidence is found among younger

cohorts. This group may be rejecting or attenuating the anti-establishment attitudes

and general skepticism of their older peers. They came of age in a period—the

1990s and early 2000s—of general economic and domestic peace, at least compared

to those who came of age during the Vietnam and post-Vietnam eras. In general,

then, secularization, if it has occurred among some groups, is not a unique or

independent trend in American society. Instead, it is simply one element of a more

complex process that has led to a general decline in confidence and trust in

institutions.

Finally, there are some practical implications suggested by these results. First,

there continues to be a need to improve our understanding of what it means to have

confidence in an organization or institution. A recent experiment illustrates this by

showing that confidence in organizations is most closely related to approval of

organizations, rather than some generalized sense that an organization can be

counted on to do what is right (Cook and Gronke 2005). Thus, if this is a recent

phenomenon, it is not surprising that increasing confidence in religious organiza-

tions has occurred only among those who participate in religious services.

Second, leaders of religious and other organizations should evaluate what it

means to have the confidence of members and non-members alike. Organizational

vitality clearly requires a committed membership that trusts and approves of its

leaders. Yet it is also important, especially when organizations are trying to grow

22 Rev Relig Res (2013) 55:1–25

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and remain vital and useful, to maintain a general aura of trust and confidence that

they are doing good work and making a positive difference for people and the

community. Assuming a rise in skepticism, individualism, and disenchantment with

various types of organizations and institutions, religious and other groups share

many of the same challenges. Therefore, religious leaders need to find better ways to

show how their organizations differ from secular institutions and can be counted on

to provide distinctive services that cannot be obtained by alternative or individ-

ualistic means.

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