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Abstract

Racial minority groups in the United States often seek out religious support for mental health struggles. Yet past studies have often overlooked religion as a key explanatory factor shaping racial-ethnic differences in perceptions of mental health conditions such as depression and anxiety. The authors examine whether views of the relationship between religion and science shape agreement with different explanations for mental health conditions. Drawing on a national probability survey collected in 2021 (n = 3,390), the authors find that individuals who draw boundaries between religion and science had higher odds of rejecting biological and social explanations of mental health conditions, whereas individuals who see religion and science as collaborative had higher odds of affirming biological and social explanations. Belief that we trust science too much (and religion not enough) helped explain Black respondents’ support for religious explanations. The findings underscore the importance of beliefs about religion and science in understanding racial-ethnic differences in views of mental health.

Keywords

mental health race religion science

Recent estimates suggest that nearly 20 percent of Americans suffer from some form of mental illness (National Institute of Mental Health 2022). The prevalence of mental health issues and the challenges of receiving care have only been exacerbated by the coronavirus disease 2019 (COVID-19) pandemic (Javed et al. 2020; Manning et al. 2021). This is particularly true in racial-ethnic minority communities; Black, Latino, and Asian Americans all reported larger increases in both anxiety and depression than White Americans during the pandemic (Thomeer, Moody, and Yahirun 2022). However, racial-ethnic minority groups are also less likely to report receiving medical treatment for mental health conditions. Although more than half of White Americans with diagnosed mental illnesses report receiving professional care, just over one third of Latinos (35 percent) and African Americans (37 percent) with diagnosed conditions reported receiving similar care (National Institute of Mental Health 2022).

Research suggests that differential rates of use of mental health professionals cannot be explained only by lack of access to care. A growing body of work has begun to investigate how social identities shape not only behaviors toward seeking mental health care, but also attitudes and understandings of mental health more broadly. For example, ample work finds that members of racial-ethnic minority groups in the United States often seek out spiritual resources, like religious leaders, when facing mental health challenges (Dalencour et al. 2017; Hays 2015). Although much of this research focuses specifically on Black Christians, recent scholarship uncovers similar patterns among Latino Christians (Bolger and Prickett 2021).

One explanation for these findings is that religious individuals seek spiritual resources because they see mental health problems as a product of spiritual or religious causes. For example, past literature highlights how certain religious traditions might socialize congregants into seeing mental health conditions as a spiritual trial, punishment from God, or even demon possession (Payne 2009; Yamada et al. 2019). This explanation might help explain racial disparities in use of mental health care resources given that Black and Latino Americans, in particular, are disproportionately religious (Mohamed et al. 2021; Public Religion Research Institute 2021).

Solutions are connected to perceived problems, and some research argues that documenting how people think about the etiology of mental health conditions may help us understand where and how individuals seek help (Caplan 2019). Most Americans endorse a complex model surrounding the causes of mental illness, which emphasizes some combination of nature, nurture, and stress (Murphy and Hankerson 2018; Pescosolido et al. 2010). Yet past research on how people explain the etiology of mental health issues has often distinguished between biological explanations, like genetics, and social explanations, like an individual’s upbringing or life circumstances (Schnittker 2013). There are racial-ethnic differences in the extent to which such explanations are accepted or rejected. Schnittker, Freese, and Powell (2000), for example, found that Black Americans are more likely than White Americans to reject explanations based on genetics or family upbringing. Nevertheless, this work often overlooks other(worldly) explanations that may shape people’s understandings of the cause of mental health conditions, as well as how explanations overlap in people’s minds.

We argue in this article that past studies of how people explain mental health conditions have overlooked a key explanatory factor shaping racial-ethnic differences in perceptions of mental health: how individuals view the relationship between religion and science. Past literature has certainly acknowledged that views of these two institutions matter. Indeed, Schnittker et al. (2000) argued that one reason Black Americans reject genetic explanations of mental illness is because they reflect the racist logics of eugenics. Similarly, church attendance is associated with lower levels of trust in science (Gauchat 2012), although qualitative and survey evidence suggest this lack of trust is often directed more toward scientists and science educators than science itself (Bolger and Ecklund 2018; Ecklund and Scheitle 2018). Either way, evidence suggests that both race-ethnicity and religious beliefs shape how people view science which, we argue, shapes differences in how people think about the causes of mental health conditions such as depression and anxiety.

Drawing on a nationally representative survey conducted in 2021, we explore the extent to which views on the relationship between science and religion shape agreement with particular explanations for mental health problems, both individually and in combination with one another, and the extent to which such views help explain racial-ethnic differences in perceptions of the etiology of mental health conditions. This helps address several gaps in the literature. For one, studies on perceptions of mental health and subsequent treatment preferences often do not consider religion as an explanatory factor (e.g., Pescosolido et al. 2010; Phelan, Yang, and Cruz-Rojas 2006). This is true even of studies looking specifically at racial differences (e.g., Schnittker et al. 2000) even though many racial-ethnic minority groups, such as Black and Latino Americans, tend to be highly religious.

Meanwhile, studies that do consider religion have used traditional measures like self-reported religiosity, religious attendance, and affiliation (e.g., Blumner and Marcus 2009) without considering how people might explain mental health problems through the relationship between religion and science. In this article, we argue that truly understanding how religion shapes perceptions of mental health conditions requires moving past typical indicators of religiosity to interrogate how people understand religion’s relationship with other social institutions, namely science. Our results build on research on racial differences in beliefs about mental health conditions and access to mental health care by highlighting the complex ways that racial identities intersect with views about religion and science to shape subjective understandings of mental health.

Racial Differences in Views of Etiology

A growing body of interdisciplinary research has explored public perceptions of mental health and how they have evolved over time (for an overview, see Schnittker 2013). One conclusion of this literature is that public belief in certain explanations has increased over time, while belief in other explanations has decreased. Blumner and Marcus (2009), for example, found that the proportion of Americans believing that depression has biological origins increased between 1996 and 2006 (see also Pescosolido et al. 2010). This shift is particularly important given evidence suggesting that belief in genetic or biological explanations is associated with the likelihood of recommending hospitalization or prescription medication for mental illness (Phelan et al. 2006). The increase in support for biological explanations, however, has been largely concentrated among White Americans; Blumner and Marcus (2009) found no significant changes in attitudes among non-White respondents over this time period. This brings up important questions about how race-ethnicity shapes the ways that individuals perceive mental health conditions, like depression and anxiety. Understanding racial differences is particularly important because racial-ethnic minorities in the United States tend to have mental disorders that are both more severe and longer lasting than White Americans (Alvidrez and Barksdale 2022) but are also less likely than White Americans to seek care from a mental health professional (National Institute of Mental Health 2022).

Past research documents important racial-ethnic differences in views on mental health and illness (Broman 2012; Kane and Williams 2000). Black Americans are more likely to view mental illness as highly stigmatizing (Gary 2005), as well as attribute mental health problems like depression to personal weakness and lack of motivation (Conner et al. 2010; Johnson 2000). Such beliefs can limit certain help-seeking behaviors, like consulting medical or mental health care providers. Additionally, race often intersects with other social identities, such as gender, to shape whether people seek care for their mental health. One recent study, for example, found that African American and White men are less likely than African American and White women to perceive a need for mental health care (Villatoro et al. 2018). Such research highlights how multiple identities situated within intersecting systems of stratification shape how, and the extent to which, people understand and seek care for their mental health. Many studies rely on Black-White comparisons, however, and therefore our knowledge of the views of other racial-ethnic groups remains limited (Nguyen 2020).

The limited research that does compare views of mental health across racial-ethnic groups often focuses solely on help-seeking behaviors and finds notable differences by race-ethnicity (Bauldry and Szaflarski 2017; Gary 2005). One stream of research, for example, highlights how trust in doctors and mental health care professionals is often lower among racial-ethnic minority groups (Dovidio et al. 2008; Nickerson, Helms, and Terrell 1994), leading some to forego care. For example, one recent study finds that Black and Hispanic Americans are less likely than White Americans to express satisfaction with treatment they received from mental health professionals (Cai and Robst 2016). Another line of work suggests that it is important to distinguish perceptions of trust from perceptions of efficacy. For example, one study found that African Americans were more likely than White Americans to believe that mental health professionals are efficacious in their ability to treat various mental disorders. Yet African Americans in the study were also more likely to believe that mental health issues would improve without treatment (Anglin et al. 2008).

The Role of Religion

This seeming paradox might be partly explained by religion, which plays an important role in how people explain and cope with mental health challenges (Kane and Williams 2000; Pickard et al. 2019; Ward et al. 2013). For one, religious practices such as service attendance and prayer are consistently associated with better mental health outcomes (Schieman, Bierman, and Ellison 2014). The association between religious practices and mental health may be especially pronounced for racial minorities who draw from religion/spirituality to cope with the difficulties of daily life. Black Americans, for example, are not only more religiously involved than White Americans by almost any measure (Taylor et al. 1996), but also are more likely than White adults to believe that God is in control of earthly affairs (Schieman et al. 2006) and to report that religion is an important form of coping in times of distress (Chatters et al. 2008). Indeed, evidence suggests that religious beliefs and practices can help moderate the deleterious effects of racism and racial discrimination on mental health (Ellison, Musick, and Henderson 2008).

Second, religious beliefs might shape where people go for help when facing mental health issues. For example, a long-standing body of literature highlights how Black and Latino Americans often prefer consulting with religious leaders rather than mental health professionals (Neighbors, Musick, and Williams 1998; Villatoro, Morales, and Mays 2014). Indeed, as Taylor et al. (2000) noted in their assessment of the role of pastors in addressing mental health concerns in Black churches, “For many, a member of the clergy is the first professional contacted for personal problems” (p. 81). Religiosity seems to shape not only the propensity of individuals to seek out the help of clergy, but also how they assess mental health care workers. Some research finds that African Americans who are highly religious are less likely than those who are less religious to express positive attitudes toward mental health care professionals (Davenport and McClintock 2021). This might result from socialization in religious congregations; Payne (2009), for example, found that African American pastors were more likely than White pastors to believe that depression was a spiritual test or trial. Yamada et al. (2019) highlighted a similar pattern when comparing Korean American Presbyterian pastors with their White peers. This highlights how perceptions of mental health and help-seeking behaviors are inextricably linked; views of etiology shape help-seeking patterns but also certain sources of help (e.g., pastors) can socialize individuals into particular ways of thinking about etiology (Caplan 2019).

This does not mean that religious individuals from racial-ethnic minority groups universally avoid mental health care providers. Moreno and Cardemil (2013), for example, highlight multiple circumstances under which Latino Americans might be more likely to seek out mental health professionals. These reasons include experiencing more serious forms of mental illness or perceiving the etiology of mental health problems as biological. Conversely, individuals who see mental health conditions as having a spiritual etiology might be more likely to seek a religious leader. Collectively, such evidence suggests that beliefs about the cause(s) of mental health conditions matter for where people seek help, thus only further reinforcing the importance of understanding the factors shaping assessments of etiology.

Integrating Views on Religion and Science

We argue here that truly understanding how religion and race-ethnicity intersect to shape perceptions of mental health conditions requires moving past typical indicators of religiosity, like religious attendance and affiliation, to interrogate how people understand religion vis-à-vis other social institutions, such as science. Surprisingly, little work has investigated how trust in science intersects with religion and other social identities to influence perceptions around the causes of mental health issues. This is despite the fact that both religion and science are deeply racialized institutions that shape, both individually and together, how people assess various life domains, including health issues (Evans and Hargittai 2020; Noy and O’Brien 2016, 2018). In reviewing literature on public conceptions of the causes of mental illness, Schnittker (2013) argued that views on mental health “bear the imprint of long-standing cultural legacies, including theologies, but they also reflect the influence of modern science and the secular-rational mindset” (p. 75).

There are certainly long-standing divisions between science and religion when it comes to understanding mental health. Sigmund Freud’s distrust of religion famously informed his view that religious practices are signs of obsessive neurosis and infantile thinking and therefore a threat to both individual well-being and broader society. According to Freud, “religion and science are moral enemies and that every attempt at bridging the gap between them is bound to be futile” (quoted in Gay 1989:xxiii). Although Freud’s views might be extreme, a 2020 poll conducted by Gallup suggests considerable skepticism about the role that science can play in helping treat mental illness. For example, only one third of respondents in the poll agreed that science could explain a lot about how feelings and emotions work, and fewer than one third (31 percent) believed that science can help a lot to treat anxiety or depression (Wellcome Global Monitor 2021).

The idea that science is a discrete activity conducted in isolation from religion may influence how individuals understand both domains as well as their perceptions of mental health issues. Boundary work (i.e., the demarcation between science and nonscience) may concern moral authority as well as the legitimacy of health care professionals, emerging health technologies, and health care industries (Ecklund, Park, and Sorrell 2011; Ecklund and Scheitle 2018; Evans and Evans 2008). Theoretically, we might expect that individuals who distrust science because of, or despite, religion may be more inclined to endorse domain specific explanations for the causes of mental health (i.e., religious-only versus biological-only explanations). Boundary drawing between science and religion may also influence beliefs about the causes and appropriate treatments of mental health concerns to the extent that individuals see science and medicine as interconnected (Scheitle and Guthrie 2019).

Yet people can also view science and religion as working collaboratively, an approach encouraged by many mental health professionals (Levin 2014). The collaborative model holds that neither science nor religion holds a monopoly on truth, but rather, the two work together to provide a fuller understanding of reality. Under the “collaboration model,” the boundaries between religion and science overlap to produce a framework highlighting assistance and cooperation instead of conflict and competition (Barbour 1990; Ecklund and Scheitle 2018; Scheitle 2011). For example, past research has highlighted how adherence to the collaboration model among Black Protestant Christians was linked to positive assessments of emerging medical technologies like stem cell research (Tinsley, Prickett, and Ecklund 2018). Arguably, the pursuit of collaboration between science and religion has been best tackled within medicine, in which collaboration—defined by its emphasis on cultural competency, mutual respect, and a more holistic framework—has often been seen as beneficial to both individuals (Robinson et al. 2018) and institutions (Levin 2016). Thus, theoretically, we might expect that individuals holding to a collaborative view of science and religion might be more likely to see a range of factors contributing to mental health conditions (e.g., endorsing religious, biological, and social explanations together) rather than relying on domain-specific explanations (e.g., endorsing only religious explanations). To date, however, research has not tested out these assumptions when it comes to mental health.

Racial Differences in Views toward Science and Religion

Few studies have directly tested how views of religion and science may help explain racial-ethnic differences in views on mental health, net of religious involvement. For one, research on the extent to which racial-ethnic minority groups express positive attitudes toward science remains mixed. For example, one recent study by the Pew Research Center suggests that the majority of Black Americans hold positive views toward science and medicine (Funk 2022), but longitudinal work drawing on the General Social Survey suggests that racial-ethnic minorities in the United States tend to have less trust in science than White Americans (Gauchat 2012). The reasons for such disparities in trust are complex. Plutzer (2014), for example, argues that religion helps explain some of the Black-White gap in trust in science, given that African Americans are about twice as likely as White Americans to believe in a literal interpretation of the Bible. But this accounts for only about one sixth of the racial gap in trust in science between these two groups. Other factors, including (but not limited to) the underrepresentation of Black Americans in science professions and the legacy of racism in scientific and medical experiments, might also help explain the gap (Kennedy, Mathis, and Woods 2007).

Qualitative research has provided more nuance to the discussion of potential mechanisms underlying racial differences in trust in science. Recent work, for example, suggests that Black Protestant Christians often perceive tension, or incompatibility, between religion and science, although social class also plays an important role in shaping perceptions of the compatibility between the two institutions. When science is thought to contribute to improving health conditions, however, individuals framed religion and science as compatible regardless of socioeconomic background (Tinsley et al. 2018). Other work suggests that certain groups, such as Black and Latino Christians, do not distrust science as much as they distrust scientists and science educators (Bolger and Ecklund 2018). These results highlight how contrasting important racial-ethnic perceptions of moral authority shape how members of racial-ethnic minority groups in particular draw boundaries between religion and science.

Understanding the relationship between race-ethnicity and views of mental health also requires acknowledging the stigma that is often attached to mental illness (Pescosolido 2013), which can be particularly salient in many racial-ethnic minority communities (Caplan 2019; Parcesepe and Cabassa 2013). Mental health stigma is not divorced from broader patterns of racial stratification and discrimination in the United States. Schnittker et al. (2000), for example, speculated that the propensity of Black Americans to reject biological and environmental explanations of mental illness is because such explanations have historically been used to justify racial inequality in U.S. society, either by framing Black Americans as genetically inferior to White Americans or perpetuating stereotypes about the purported dysfunction of Black families.

Thus, notable gaps remain in our knowledge of the relationships among religion, race-ethnicity, and views of mental health. Studies of racial differences in how people explain the etiology of mental health issues often pay limited attention to the role of religion, despite ample qualitative research suggesting that religion matters for how people explain mental health concerns and where they subsequently seek help (Bolger and Prickett 2021; Kane and Williams 2000; Pickard et al. 2019; Ward et al. 2013). Furthermore, despite evidence that both religion and science individually shape the ways that people explain mental health problems, researchers have yet to explore the significance of how people understand the relationship between the two. In the present article we help fill these gaps by exploring how views of religion and science shape views of the etiology of mental health problems, and the extent to which they explain differences in views of etiology across racial-ethnic groups. We proceed in two steps. First, we look at how race-ethnicity and views of science and religion are associated with six different explanations of mental health conditions. In doing so, we examine whether views on science and religion help explain any observed racial-ethnic differences in support for particular explanations of mental health issues net of other measures of religious involvement. Second, we look at how people combine explanations together to examine the correlates of belief in particular clusters of explanations.

Methods

We draw on data from a survey collected online in April 2021 by Ipsos using KnowledgePanel, the oldest and largest probability-based online panel in the United States. The aim of the project was to examine beliefs and perceptions about the boundaries between religion and science on four key areas related to the human body: mental health, aging, death and dying, and beginning-of-life technologies.¹ Ipsos recruits KnowledgePanel members using address-based sampling methods to ensure full coverage of all households in the nation. Address-based sampling improves population coverage by recruiting hard to reach households, including cellphone-only households, households without Internet access, young adults, and persons of color. Households without Internet access were provided with Web-enabled devices and free Internet service.

The target population for the survey comprised noninstitutionalized adults, aged 18 years and older, residing in the United States mirroring Current Population Survey race-ethnicity proportions. The survey was available in either English or Spanish and oversampled on respondents who identified as African American or Black, Hispanic, and Asian. A sample of 5,666 Ipsos KnowledgePanel panelists were invited to take part in the survey. In total, 3,467 responded to the invitation and 3,467 qualified for the survey, yielding a study completion rate of 61.2 percent and a qualification rate of 100 percent. The data were weighted using weights provided by Ipsos. Study-specific poststratification weights adjusted for nonresponse and the study-specific sample design relative to expected demographic distributions from the U.S. Census Bureau’s Current Population Survey and the American Community Survey in a multistep weighting process. We use all available data; therefore the analytical sample varies by outcome. However, listwise deletion resulted in few missing cases: n = 69 to 79 (<2.5 percent) of lost cases depending on the outcome. All data analyses were conducted using Stata version 15.1.

Measures

Causes of Mental Health Conditions

Respondents were given six explanations for mental health conditions, like depression and anxiety, which reflect three broad orientations toward mental health: biological, religious, and social. Two items capture a biological orientation by asking respondents how strongly they agree that symptoms are the result of a “biological/chemical imbalance in the brain” and/or “genetic inheritance.” Three explanations reflect a religious orientation toward mental health, including “a test from God,” “absence of faith in God,” and/or “possession of evil spirits.” Finally, a social explanation was captured by asking respondents how strongly they agree that mental health conditions are the result of “stress or other external pressures.” Original response categories ranged from 1 = “strongly agree” to 5 = “strongly disagree.” We dichotomized each of these six items (1 = “strongly agree” and “agree” vs. 0 = all others) because distributions tended to be skewed and binary operationalization allowed for parsimonious interpretation across all six items.² Similar items have been used in other studies to capture subjective understandings of the causes of mental health (Schnittker et al. 2000).

Previous research also suggests that many individuals support overlapping, at times competing, explanations of mental health conditions (Murphy and Hankerson 2018). Therefore, we were also interested in how these three broad explanations (i.e., biological, social, and religious) overlapped. On the basis of exploratory analysis we found respondents overwhelmingly supported one of four explanation sets: (1) a combination of biological and social explanations, (2) a solely social explanation, (3) religious+ (supports religious explanation[s], either alone or in combination with other explanations), and (4) no explanation (does not support any biological, social, or religious explanation). We constructed a series of dummy variables, with the “no explanation” group serving as our reference category.

Views on Science and Religion

Two independent items were used to assess the respondents’ views on science and religion: (1) “We trust too much in science and not enough in religious faith” (trust science too much) and (2) “Both science and religion can help heal the human body.” Response categories across the two statements ranged from 1 = “strongly agree” to 5 = “strongly disagree.” Items were reverse-coded so that higher scores reflect stronger agreement with the statement. Items used to assess views on science and religion were either original questions or adapted from the Religious Understandings of Science Study (Ecklund and Scheitle 2018).

Covariates

We control for several key background factors that are known or suspected correlates of the dependent and independent variables, and therefore could confound the associations of interest, including common sociodemographic variables. These include age (in years); relationship status (never married and other relationship status; married serves as the reference category), education (high school diploma or GED, some college, college degree, or master’s degree or higher; less than high school serves as the reference category), household income (seven categories ranging from <$10,000 to ≥$150,000), employment status (employed vs. other status), and region (South vs. all other regions). We also control for different dimensions of individual religiosity, including two indicators of religious involvement: (1) religious affiliation, adapted from the RELTRAD typology (Steensland et al. 2000), with a series of dummy variables (1 = mainline Protestant, 1 = Black Protestant, 1 = Catholic, 1 = other religion [i.e., Jewish, Mormon], 1 = unaffiliated/nothing in particular, 1 = atheist; Evangelical Protestant serves as the reference category), and (2) religiosity, a three-item index including (a) frequency of religious attendance (i.e., “Prior to the COVID-19 pandemic, how often do you attend religious services”), (b) subjective religiosity (i.e., “To what extent do you consider yourself a religious person?”), and (c) religious coping (i.e., “I find strength and comfort in my religion”). The three items were standardized and averaged; higher scores reflect greater religiosity. Cronbach’s α coefficient is .74. Last, we control for a series of subjective health measures including subjective mental health and subjective physical health (i.e., “How would you rate your overall mental [physical] health at the present time?”). Response categories ranged from 1 = “excellent” to 5 = “poor” and were reverse-coded so that higher scores reflect better subjective health for both measures. We also control for medical mistrust, a six-item averaged index that includes such statements as “Hospitals provide the same level of medical care for racial and ethnic minorities as they do for white people” and “My doctor takes my concerns about my body less seriously, because of my gender.” The items used in the medical mistrust have been widely used and validated for examining differences in medical mistrust measures, including between Black and White patients (e.g., Williamson and Bigman 2018). The Cronbach’s α coefficient for this index is .98.

Analytical Strategy

We begin our analysis with the presentation of weighted descriptive statistics for the study sample (Table 1). We used logistic regression to test associations between race-ethnicity and views on science and religion on the beliefs about the cause of mental health issues. First, we estimate a base model that examines the association between race-ethnicity and causes of mental health controlling for sociodemographic variables, religious involvement, and medical mistrust (model 1). Model 2 adds the two measures of views on science and religion. These results are presented in Table 2. We also calculated variance inflation factors (VIFs) for all key independent variables in Table 2. A VIF of 10 or greater is often taken to indicate a possible multicollinearity problem (Franke 2010). In our models, VIF scores ranged from 1.3 to 1.6.

Table 1.

Descriptive Statistics of Causes of Mental Health Conditions.

	Range	Mean/%	SD	White (%)	Black (%)	Hispanic (%)	Other (%)	n
Chemical imbalance	0 to 1	.76		81	65^a	66^a	75	3,394
Genetic inheritance	0 to 1	.58		62	50^a	52^a	56	3,394
Test from God	0 to 1	.07		6	14^a	7	3	3,396
Absence of God	0 to 1	.12		10	15	16^a	7	3,398
Possession of evil spirits	0 to 1	.06		5	14^a	7	2	3,388
Social stress	0 to 1	.78		80	73^a	73^a	78	3,397
								(n = 3,399)
Biological and social	0 to 1	46.1%		50	36^a	37^a	47	1,583
Social only	0 to 1	29.6%		28	33	33	30	1,016
No explanations	0 to 1	16.1%		13	23^a	20^a	19	519
Religious+	0 to 1	8.3%		9	9	9	4	281
Trust science not religion	1 to 5	2.82	1.16
Science and religion can heal	1 to 5	3.80	1.06
Female	0 to 1	50.9%
White, non-Hispanic	0 to 1	63.2%
Black, non-Hispanic	0 to 1	11.6%
Hispanic	0 to 1	16.5%
Other race	0 to 1	8.8%
Age	18 to 94	48.2	.32
Income	1 to 7	4.66	.03
Married	0 to 1	58%
Never married	0 to 1	27.4%
Other marital status	0 to 1	15.7%
Less than high school	0 to 1	11.1%
High school diploma/GED	0 to 1	27.3%
Some college	0 to 1	30.1%
Bachelor’s degree	0 to 1	18.0%
Master’s degree or higher	0 to 1	13.5%
Employment	0 to 1	62.1%
Region (South = 1)	0 to 1	38.3%
Evangelical Protestant	0 to 1	20.2%
Mainline Protestant	0 to 1	7.6%
Black Protestant	0 to 1	6.2%
Catholic	0 to 1	24.6%
Other religion	0 to 1	8.1%
Nonreligious	0 to 1	25.8%
Atheist/agnostic	0 to 1	7.7%
Religiosity	−1 to 1	-.03	.90
Medical mistrust	1 to 5	2.35	.70
Subjective mental health	1 to 5	3.55	1.00
Subjective physical health	1 to 5	3.36	.90

Note: Data come from the Science and Religion of the Body Survey (2021).

Significantly different from Whites.

Table 2.

Logistic Regression Models Predicting the Etiology of Mental Health, Science and Religion Views, and Covariates.

	Biological Explanations				Religious/Spiritual Explanations						Social Explanation
	Chemical Imbalance		Genetic Inheritance		Test from God		Absence of God		Possession of Evil Spirits		Social Stress
	Model 1	Model 2	Model 1	Model 2	Model 1	Model 2	Model 1	Model 2	Model 1	Model 2	Model 1	Model 2
	OR (SE)	OR (SE)	OR (SE)	OR (SE)	OR (SE)	OR (SE)	OR (SE)	OR (SE)	OR (SE)	OR (SE)	OR (SE)	OR (SE)
Black^a	.52 (.12)**	.55 (.14)*	.77 (.17)	.78 (.17)	2.39 (.80)**	2.01 (.68)*	1.524 (.53)	1.25 (.43)	3.14 (1.15)**	2.41 (.92)*	.92 (.22)	.95 (.23)
Hispanic	.67 (.09)**	.67 (.09)**	.72 (.09)*	.71 (.09)**	.81 (.22)	.78 (.21)	1.42 (.27)	1.37 (.26)	1.34 (.39)	1.29 (.35)	.84 (.12)	.83 (.12)
Other	.56 (.09)***	.56 (.09)**	.61 (.09)**	.61 (.08)**	.63 (.23)	.66 (.24)	.89 (.23)	.89 (.24)	.60 (.24)	.61 (.24)	.86 (.15)	.85 (.15)
Trust science too much		.79 (.04)***		.90 (.03)*		1.63 (.17)***		1.74 (.13)***		1.92 (.21)***		.85 (.04)***
Science and religion can heal		1.34 (.07)***		1.23 (.06)***		1.23 (.14)		1.19 (.12)		.97 (.12)		1.38 (.07)***
Gender (female = 1)	1.22 (.12)*	1.20 (.07)	1.34 (.11)***	1.33 (.11)***	.95 (.16)	.99 (.18)	.71 (.09)**	.73 (.10)*	.73 (.14)	.78 (.15)	1.18 (.11)	1.15 (11)
Age	1.00 (.00)	1.00 (.00)	.99 (.00)***	.99 (.00)***	.98 (.01)	.98 (.01)**	.98 (.00)***	.98 (.00)***	.98 (.01)**	.99 (.01)*	.99 (.00)***	.98 (.00)***
High school^b	1.32 (.22)	1.27 (.21)	.99 (.16)	.96 (.16)	.85 (.24)	.83 (.25)	.66 (.15)	.65 (.15)	1.08 (.33)	1.12 (.35)	1.33 (.23)	1.27 (.22)
Some college	2.08 (.35)***	1.87 (.32)***	1.48 (.24)*	1.39 (.23)	.61 (.19)	.69 (.23)	.59 (.14)*	.68 (.16)	.65 (.21)	.82 (.28)	1.74 (31)**	1.58 (.28)*
Bachelor’s degree	2.91 (.56)***	2.47 (.48)***	2.26 (.40)***	2.07 (.37)***	.68 (.23)	.87 (.31)	.44 (.11)**	.55 (.15)*	.62 (.23)	.95 (.36)	2.19 (.42)***	1.91 (.38)**
Master’s degree or higher	2.86 (.59)***	2.32 (.49)***	2.20 (.40)***	1.99 (.37)***	.62 (.23)	.80 (.32)	.55 (.15)*	.73 (.21)	.50 (.22)	.78 (.34)	2.32 (.48)***	1.98 (.42)**
Income	1.12 (.04)***	1.11 (.04)**	1.00 (.03)	.99 (.03)	.76 (.05)***	.78 (.05)***	.87 (.034)**	.90 (.04)*	.78 (.05)***	.79 (.05)***	1.03 (.03)	1.02 (.03)
Never married^c	1.24 (.17)	1.18 (.17)	1.06 (.12)	1.04 (.12)	1.06 (.23)	1.15 (.26)	.76 (.15)	.80 (.16)	1.11 (.27)	1.21 (.30)	.93 (.13)	.90 (.12)
Other relationship status	.90 (.12)	.90 (.12)	1.02 (.11)	1.03 (.12)	.81 (.22)	.78 (.21)	1.29 (.24)	1.26 (.24)	.85 (.23)	.80 (.21)	1.04 (.13)	1.05 (.14)
Employment (employed = 1)	.87 (.10)	.91 (.10)	1.10 (.10)	1.12 (.10)	1.12 (.22)	1.09 (.21)	.88 (.13)	.83 (.13)	1.04 (.21)	1.05 (.21)	.96 (.10)	.97 (.11)
Region (South = 1)	.97 (.10)	.99 (.10)	1.03 (.09)	1.04 (.09)	1.09 (.19)	1.01 (.18)	.98 (.13)	.92 (.13)	.97 (.18)	.92 (.17)	1.02 (.10)	1.03 (.10)
Mainline Protestant^d	1.50 (.30)*	1.39 (.28)	1.10 (.17)	1.07 (.17)	.35 (.16)*	.45 (.20)	.81 (.20)	1.08 (.27)	.55 (.22)	.76 (.31)	.86 (.15)	.81 (.14)
Black Protestant	1.24 (.37)	1.18 (.37)	.79 (.22)	.78 (.22)	.48 (.21)	.57 (.26)	.63 (.26)	.76 (.33)	.23 (.10)**	.29 (.14)**	.92 (.29)	.91 (.29)
Catholic	.82 (.12)	.81 (.12)	1.14 (.14)	1.15 (.14)	.98 (.25)	1.18 (.31)	.77 (.14)	.95 (.18)	.31 (.09)***	.37 (.11)**	.94 (.13)	.96 (.14)
Other religion	1.05 (.21)	1.07 (.21)	1.05 (.17)	1.07 (.17)	1.19 (.35)	1.42 (.42)	1.07 (.24)	1.27 (.30)	.52 (.17)	.63 (.20))	.83 (.16)	.86 (.17)
Religion none	.99 (.16)	.98 (.16)	1.13 (.16)	1.14 (.16)	.88 (.27)	1.06 (.33)	.66 (.16)	.79 (.20)	.49 (.16)*	.58 (.19)	.93 (.15)	.94 (.15)
Atheist	2.58 (.74)**	2.49 (.72)**	2.15 (.45)***	2.12 (.48)***	.14 (.16)	.22 (.26)	.36 (.21)	.60 (.35)	.25 (.19)	.45 (.33)	1.75 (.44)	1.85 (.48)*
Religiosity	.90 (.09)	.90 (.09)	1.08 (.08)	1.05 (.09)	2.27 (.35)***	1.66 (.28)**	2.89 (.36)***	2.13 (.29)***	2.89 (.56)***	2.16 (.43)***	.96 (.09)	.92 (.09)
Medical mistrust	.79 (.06)**	.78 (.06)	.91 (.06)	.91 (.06)	1.06 (.15)	1.14 (.16)	.88 (.10)	.95 (.11)	1.52 (.23)**	1.65 (.23)***	.70 (.05)	.69 (.05)***
Subjective mental health	.95 (.06)	.97 (.06)	.86 (.05)**	.84 (.04)	.76 (.08)**	.75 (.08)**	1.09 (.09)	1.08 (.09)	1.15 (.15)	1.13 (.14)	.87 (.05)*	.86 (.05)*
Subjective physical health	.97 (.06)	.97 (.06)	1.01 (.05)	1.01 (.05)	1.36 (.15)**	1.38 (.15)**	1.06 (.09)	1.07 (.09)	1.20 (.15)	1.20 (.15)	1.01 (.07)	1.02 (.07)
n	3,394		3,394		3,396		3,398		3,388		3,397

Reference category: White.

Reference category: less than a high school diploma.

Reference category: married.

Reference category: Evangelical Protestant.

p ≤ .05. **p ≤ .01. ***p ≤ .001.

Second, given our interest in how race-ethnicity and views on science and religion are associated with overlapping explanations of mental health, we use multinomial logistic regression to examine these associations of interest. We use the same analytical strategy described above: after estimating a base model including race-ethnicity and covariates (model 1), we added our views on science and religion variables (model 2) with the “no explanation” group serving as the reference group for analysis.

Results

Table 1 provides weighted descriptive statistics of study variables for the total sample but also stratified by race-ethnicity. More than three quarters of the study respondents either agree or strongly agree that mental health conditions such as depression and anxiety are caused by a “chemical imbalance” (76 percent) and “social stress” (78 percent), and 58 percent support a “genetic” explanation. Comparatively, roughly 6 percent to 7 percent of respondents agree or strongly agree that mental health problems result from “possession of evil spirits” or a “test from God,” respectively, while 12 percent endorse “absence of God” as an explanation of mental health issues. We see some important differences by race-ethnicity: Black and Hispanic respondents are significantly less likely to endorse biological explanations (i.e., chemical and genetic) than White adults. We also find that Black and Hispanic adults are significantly more likely to endorse none of the provided explanations for the causes of mental health compared with their White peers. On average, respondents report modest support (mean = 2.82) for “trust science too much,” but stronger support for the more collaborative “science and religion can heal” (mean = 3.80; range = 1–5). Demographically, 63 percent of the sample identified as White, 51 percent identified as women, the average age was 48.2 years, 58 percent reported being married at the time of the survey, and 62 percent reported completing “at least some college.”

Table 2 shows the results of the weighted logistic regression models on the independent causes of mental health conditions. We turn to the results for the two biological explanations first. Black (odds ratio [OR] = .52, p < .01), Hispanic (OR = .67, p < .01), and other-race adults (OR = .56, p < .001) report significantly lower odds of supporting “chemical imbalance” as an explanation of mental health problems compared with White adults, net of covariates including religious involvement. After the inclusion of the views on science and religion predictors in model 2, the coefficient for Black adults increases to .55 and remains statistically significant, while the coefficients for Hispanic and other-race adults remain virtually unchanged. Results of model 2 reveal “trust science too much” is associated with lower odds of endorsing “chemical imbalance” as a cause of poor mental health (OR = .79, p < .001). However, stronger agreement with “science and religion can heal” is associated with higher odds (OR = 1.34, p < .001) of supporting the “chemical imbalance” explanation. Looking at the results for “genetic inheritance,” we see that Hispanic and other-race adults report lower odds of supporting the “genetic inheritance” explanation compared with White adults. We find no significant differences between Black and White adults in support of this explanation. Model 2 results for genetic inheritance mirror the findings for chemical imbalance: “trust science too much” is significantly associated with lower odds of supporting “genetic inheritance” (OR = .90, p < .05), while “science and religion can heal” is associated with increased odds of endorsing genetic inheritance as a cause of poor mental health (OR = 1.23, p < .001). These results suggest that views on religion and science do little to explain racial-ethnic differences in supporting biological explanations for mental health, and may in fact slightly suppress Black adults’ agreement that mental health is caused by a “chemical imbalance.”

Results for the three religious explanations reveal few racial-ethnic differences. The exceptions are that, net of covariates, Black adults are more than twice as likely as White adults to support the “test from God” explanation (model 1: OR = 2.01, p < .05) and three times as likely to support “possession by evil spirts” compared with their White peers (OR = 3.14, p < .01). In model 2, which adds our predictors for views on science and religion, “trust science too much” is associated with an increase in odds for endorsing all three religious explanations: test from God (OR = 1.63), absence of God (OR = 1.74), and possession of evil spirts (OR = 1.92) at p < .001. In model 2, Black adults are still significantly more likely to endorse “test from God” and “possession of evil spirits” compared with White adults, but there are 15 percent and 23 percent decreases in the sizes of the coefficients after the inclusion of the views on science and religion predictors, respectively. An ancillary decomposition³ of the total effect into indirect and direct effects revealed that “trust science too much” is a significant confounding factor (p < .05, two-tailed tests) explaining Black-White differences in these explanations. Last, there are no significant differences by race-ethnicity in affirmation of the social explanation. Model 2 reveals that agreement with “trust science too much” is associated with lower odds of believing that poor mental health is the result of social stress (model 2: OR = .85, p < .001), while agreement with “science and religion can heal” is associated with higher odds of endorsing this explanation (OR = 1.38, p < .001).

Our second aim was to examine how race-ethnicity and views on science and religion are associated with overlapping explanations of mental health conditions. In other words, what explanations do people tend to espouse in combination with each other and what factors predict these combinations? To pursue this aim, we estimated a new set of multinomial logistic regression models, which uses maximum likelihood to estimate the log-odds of endorsing a given explanation (i.e., biological and social, social only, religious+) compared with the respondents who did not support any of the provided explanations for the cause of mental health (i.e., no explanation). The regression results are provided in Table 3 and include regression coefficients, standard errors, and relative risk ratios (RRRs; i.e., exponentiated coefficients). Here again, we see significant racial-ethnic differences in supporting “biological and social explanations” compared with endorsing “no explanations” as the cause of mental health problems. Hispanic and other race adults report significantly lower odds than White adults of supporting this combination of explanations about the cause of mental health problems compared with those supporting no explanation. The coefficient for Black adults reached only marginal significance (p < .10). Model 2, which adds views on science and religion predictors, does little to explain these racial-ethnic differences. “Trust science too much” (RRR = .73, p < .001) appears to have a significant inverse association on supporting “biological and social explanation” versus no explanations, while “science and religion can heal” results in an increase in odds of endorsing “biological and social explanations” versus no explanation (RRR = 1.62, p < .001) for the cause of poor mental health.

Table 3.

Multinomial Logistic Regression Predicting Mental Health Explanation.

	Biological and Social Explanations				Social-Only Explanation				Religious+ Explanations
	Model 1		Model 2		Model 1		Model 2		Model 1		Model 2
	b (SE)	RRR	b (SE)	RRR	b (SE)	RRR	b (SE)	RRR	b (SE)	RRR	b (SE)	RRR
Black^a	−.56 (.29)	.57	−.52 (.30)	.60	.07 (.29)	1.07	.10 (.29)	1.11	−.21 (.41)	.81	−.24 (.41)	.79
Hispanic	−.38 (.19)	.68*	−.39 (.19)	.67*	.10 (.19)	1.11	.10 (.19)	1.11	−.25 (.27)	.78	−.26 (.27)	.77
Other	−.65 (.20)	.52**	−.65 (.20)	.52**	−.16 (.21)	.85	−.17 (.21)	.84	−1.14 (.35)	.32**	−1.16 (.36)	.31***
Trust science too much			−.32 (.06)	.73***			−.17 (.07)	.84**			.00 (.09)	1.00
Science and religion can heal			.48 (.06)	1.62***			.30 (.07)	1.35***			.23 (.10)	1.26*
Gender (female = 1)	.36 (.12)	1.43**	.33 (.12)	1.40**	−.01 (.12)	.99	−.03 (.12)	.97	.01 (.17)	1.01	−.00 (.17)	1.00
Age	−.02 (.00)	.98***	−.02 (.00)	.98***	−.00 (.00)	1.00	−.01 (.00)	.99	.00 (.01)	1.00	−.00 (.01)	1.00
High school^b	.37 (.22)	1.45	.30 (.22)	1.36	.21 (.21)	1.24	.17 (.22)	1.18	−.36 (.30)	.70	−.38 (.30)	.68
Some college	.87 (.22)	2.40***	.72 (.23)	2.06**	.34 (.22)	1.40	.25 (.22)	1.29	−.05 (.29)	.95	−.07 (.30)	.93
Bachelor’s degree	1.44 (.25)	4.22***	1.21 (.26)	3.37***	.47 (.25)	1.60	.34 (.26)	1.41	.31 (.33)	1.36	.28 (.33)	1.33
Master’s degree or higher	1.49 (.27)	4.42***	1.22 (.27)	3.38***	.56 (.27)	1.75*	.40 (.27)	1.50	.33 (.36)	1.39	.29 (.36)	1.34
Income	.05 (.04)	1.06	.04 (.04)	1.041	.05 (.04)	1.05	.04 (.04)	1.04	.01 (.06)	1.01	.01 (.06)	1.01
Never married^c	.07 (.17)	1.08	.01 (.17)	1.01	.01 (.18)	1.01	−.03 (.18)	.97	.44 (.23)	1.56	.42 (.23)	1.53
Other relationship status	−.03 (.16)	.97	−.02 (.16)	.98	.05 (.17)	1.05	.06 (.17)	1.07	−.03 (.23)	.97	−.02 (.23)	.98
Employment (employed = 1)	.02 (.13)	1.03	.06 (.14)	1.06	−.09 (.14)	.92	−.07 (.14)	.93	−.01 (.19)	.99	−.01 (.19)	.99
Region (South = 1)	−.05 (.12)	.95	−.03 (.12)	.97	−.02 (.12)	.98	−.01 (13)	.99	−.11 (.17)	.89	−.12 (.17)	.89
Mainline Protestant^d	−.06 (.23)	.94	−.17 (.23)	.85	−.31 (.24)	.74	−.35 (.24)	.70	.00 (.31)	1.00	.03 (.31)	1.04
Black Protestant	.09 (.39)	1.07	.07 (.39)	1.07	−.06 (.38)	.94	−.08 (.38)	.93	−.45 (.54)	.64	−.40 (.54)	.67
Catholic	−.10 (.17)	.91	−.09 (.18)	.92	−.26 (.18)	.77	−.24 (.19)	.78	−.10 (.26)	.90	−.04 (.26)	.96
Other religion	−.25 (.24)	.78	−.21 (.24)	.81	−.24 (.25)	.79	−.18 (.25)	.83	−.07 (.32)	.93	.02 (.33)	1.02
Religion none	−.11 (.20)	.90	−.10 (.20)	.90	−.29 (.21)	.75	−.26 (.21)	.77	−.16 (.29)	.85	−.09 (.29)	.92
Atheist	1.13 (.33)	3.10**	1.17 (.35)	3.21***	.58 (.36)	1.79	.63 (.37)	1.88	.97 (.45)	2.64*	1.13 (.46)	3.10*
Religiosity	.01 (.12)	1.01	−.03 (.12)	.97	−.04 (.12)	.96	−.08 (.13)	.92	.33 (.15)	1.39*	.23 (.16)	1.26
Medical mistrust	−.50 (.09)	.60***	−.52 (.09)	.59***	−.57 (.09)	.56***	−.59 (.09)	.56***	−.25 (.14)	.78	−.25 (.14)	.78
Subjective mental health	−.21 (.08)	.81**	−.23 (.08)	.80**	−.10 (.08)	.91	−.11 (.08)	.89	−.07 (.12)	1.112	−.09 (.12)	.92
Subjective physical health	−.03 (.08)	.97	−.03 (.08)	.97	.02 (.08)	1.02	.03 (.08)	1.03	.11 (.12)	.87	.12 (.12)	1.13

Note: All models are compared with no explanations. RRR = relative risk ratio.

Reference category: White.

Reference category: less than a high school diploma.

Reference category: married.

Reference category: Evangelical Protestant.

p ≤ .05. **p ≤ .01. ***p ≤ .001.

The next set of models assesses the odds of endorsing “social explanation only” (i.e., only social stress) versus “no explanation” and reveals no statistically significant racial-ethnic differences. Model 2 reveals that for every one-unit increase in agreement that “we trust science too much” lowers the odds of endorsing a “social explanation only” versus “no explanations” by 16 percent. Here again, holding a more collaborative view of religion and science results in a 35 percent increase in the odds of endorsing a “social-only explanation” as the cause of mental health conditions versus no explanations. Last, other race adults are significantly less likely than their White peers to support some combination of a religious and other explanation (i.e., religious+) of mental health compared with no explanation (model 1: RRR = .32). Model 2 reveals that “trust science too much” fails to reach statistical significance. However, stronger support of “science and religion can heal” results in an increase in odds for endorsing a “religious+” explanation versus no explanations (RRR = 1.26). That is, every one-unit increase in agreement with “science and religion can heal” results in a 26 percent increase in the odds of endorsing “religious+” explanations over no explanations as the cause of poor mental health. These results suggest that while views on science and religion have a significant direct impact on individual understandings of the cause of mental health, they do little to explain any racial-ethnic differences.

Figures 1a and 1b shows predicted probabilities of endorsing various explanations of mental health by our two measures of views on science and religion stratified by race-ethnicity. These results stem from model 2 in Table 3, which shows these associations holding all other covariates at their means. Figure 1a reveals that as agreement with “we trust science too much” increases, support for a “biological and social” explanations of mental health declines across all four racial-ethnic subgroups, ranging from a 42 percent decline for Black adults to a 35 percent decline for White adults. Increased support for “we trust science too much” also results in increased support for “no explanations” across race-ethnicity. The figures also reveal relatively flat lines for the “social only” explanation as “trust science too much” increases across racial-ethnic groups. “Trust science too much” is not significantly associated with endorsing “religious+ explanations” for the cause of mental health in the multivariate models, which is reflected here in the flat slopes.

Figure 1.

(a and b) Predicted probabilities of explanations of the cause mental health by views of science-religion and race-ethnicity.

Figure 1b can be read similarly: an increase in “science and religion can heal” is associated with increased support for “biological and social explanations” across all racial-ethnic subgroups. We also see a decline in the endorsement of “no explanations” across all racial-ethnic groups as beliefs in “science and religion can heal” increases. Across all racial-ethnic subgroups, the slope of the lines for “social-only explanations” and “religious+ explanations” remain relatively flat as support for “science and religion can heal” increases. These results reveal that views on science and religion have a larger impact on shaping individual support for “biological and social explanations” and “no explanation” across racial-ethnic groups

Discussion

In the aftermath of COVID-19, both public and scholarly attention have turned to mental health, especially access to and options for adequate care (Thomeer et al. 2022). In concert with other scholars (Caplan 2019; Murphy and Hankerson 2018), we argue that addressing disparities in access to mental health care requires understanding how people understand the causes of mental health problems. In the present article, we highlight how views on the relationship between religion and science may help explain racial-ethnic differences in how people explain mental health conditions.

When looking across racial-ethnic groups, we see a complex set of patterns. First, we find that Black, Hispanic, and other-race respondents are less likely to endorse “chemical imbalance” as an explanation for mental health problems compared with their White peers. Surprisingly, Black respondents were no less likely than White respondents to agree that mental health conditions were caused by genetic inheritance. This finding departs from past literature suggesting that Black Americans reject all biological explanations at higher rates than White Americans (Schnittker et al. 2000). Black respondents were also more likely to affirm religious explanations compared with White respondents, namely, that mental health conditions can be a result of a test from God or a form of possession by evil spirits. Although past research suggests Black adults often turn to religion to cope with mental health issues (Neighbors et al. 1998; Villatoro et al. 2014), research also shows that Black pastors are more likely than White pastors to believe that mental illness is a product of spiritual factors (e.g., Payne 2009). These findings suggest that mental health explanations among Black respondents may not be exclusively explained by individual religiosity.

We also argued that understanding public perceptions of the cause(s) of mental health problems requires attention to how people view the relationship between religion and science rather than simply self-reported religious involvement. In this article, we expand measures of religion beyond affiliation and service attendance with the assumption that trust in science vis-à-vis religion is a key explanatory factor in mental health etiology. Our results bear out this assumption. First, we find that the belief that we trust too much in science and not enough in religious faith was consistently associated with how people explained poor mental health. Net of controls, belief that we trust science too much was associated with lower odds of affirming all biological explanations and higher odds of affirming all religious explanations, as expected. More surprising, however, was that individuals believing that we trust too much in science also had higher odds of rejecting social explanations for mental illness. Whether such respondents are predisposed to disagree with any nonreligious explanation or believe that social stress explanations are based in untrustworthy science remains an open question.

Our results also suggest that the belief that we trust science too much (and religion not enough) does indeed help explain, in part, Black adults support for religious explanations of mental health conditions, specifically as a test from God and possession of evil spirits. Mounting evidence suggests that the tensions between religion and science can often be explained by concerns over the moral influence of science (Evans 2013) and scientists (Ecklund and Scheitle 2018) on society, and the struggle for authoritative power between these two institutions (Evans and Evans 2008). The “faith versus science” mindset has been found to influence COVID-19 vaccine acceptance (Upenieks, Ford-Robertson, and Robertson 2022), beliefs about evolution (Evans and Evans 2008), and other social issues (Noy and O’Brien 2016). The present results add to this growing body of work to argue that drawing clear moral boundaries between religion and science has consequences for beliefs about health rather than simply sociopolitical attitudes. These mediating effects may also be explained by the higher externalizing health beliefs held by Black Americans, including health fatalism (Egede and Bonadonna 2003) and deferring health control to God (Hayward et al. 2016). Last, the potential skepticism in science and medicine among Black Americans may also stem from a long history of medical mistreatment and racism (Kennedy et al. 2007), as well as the stigma proceeding from racial bias and prejudice, which may shape the propensity of Black adults to draw clear lines between the role of religion and science in health matters.

Conversely, our results also suggest that a collaborative view of the relationship between religion and science was associated with higher odds of affirming both biological and social explanations of mental illness, but not significantly associated with any religious explanation. In other words, the belief that religion and science can work together to promote healing does not seem to lead individuals to either embrace or reject religious explanations for mental health conditions, but it does make them more likely to espouse nonreligious explanations. A recent survey finds that that 40 percent of American adults understand religion and science to be a relationship of collaboration rather than conflict (Ecklund and Scheitle 2018). Recent work within public health stemming from the COVID-19 pandemic calls for more collaboration between religion and science to effectively address health equity issues (Hong and Handal 2020). Our findings suggest that another avenue for potential collaboration can be found in understanding and addressing mental health issues.

Views on religion and science are also formative for an emergent group in the findings: those who combine multiple explanations, or reject all explanations, to explain mental health conditions. To date, the biopsychosocial model—which recognizes the culmination of biological (e.g., genetic), social (i.e., trauma and stress) and the psychological (e.g., coping and appraisal) factors—is the most widely accepted framework from medical professionals for understanding mental health (Alonso 2004). However, little research attention has been given to what factors shape public support for this more complex approach to understanding mental health. We find that nearly half of our sample affirmed some combination of biological and social explanations, but fully 16 percent did not agree or strongly agree with any of the six causes presented to them. We also found important differences by race-ethnicity in support of this category. Although it is possible that such respondents might have expressed agreement with explanations not presented in the survey (e.g., social upbringing, religious sin), it is also possible that a certain segment of respondents do not fall neatly into existing scholarly categories for explaining mental health. There may be explanations beyond the biological, religious, and social that people may employ and are worthy of future inquiry. The reality that this “no explanation” group comprised nearly one sixth of the sample suggests that this gap in our understanding is a pressing area for further research.

Our results also provide insight into how members of this “no explanation” group differ from individuals using other explanation sets. Again, we find race-ethnicity and views of religion and science to be important; individuals believing that we trust too much in science had lower odds of being in the “social only” explanation group as well as the “biological and social” group relative to the “no explanation” group. Here again, we see that drawing clear boundaries between religion and science has consequences for embracing a more holistic understanding of health and well-being (O’Brien and Noy 2015). This pattern was reversed for individuals believing that science and religion can collaborate, as such individuals had higher odds of being in the “social only” and “biological and social” groups relative to the no explanation group. These patterns remain consistent across race-ethnicity. Embracing a collaborative view of the relationship between religion and science was also associated with higher odds of affirming an explanation that includes religion rather than no explanation at all. Overall, views on religion and science seem to be a key factor influencing perceptions of mental health, even among those with “no explanation.” Embracing a biopsychosocial framework of mental health may lower barriers to and increase acceptance of treatment for mental health issues (Alonso 2004). Additional research that investigates how and why individuals come to hold more collaborative beliefs about the relationship between religion and science is certainly needed.

It is worth dwelling briefly on the practical implications of our results and how they might inform the work of frontline mental health workers. First, teaching that religion and science can be collaborative, which was associated with identifying mental health issues as being a product of multiple causes, might be one means through which pastors and other clergy can help their congregants be open to a variety of treatment options. Our results suggest this would not undermine the perceived veracity of religious explanations; respondents espousing a collaboration model did not have higher or lower odds of espousing a religious explanation. A collaborative view of religion and science may also lessen certain types of stigma if mental illness is seen as having multiple causes rather than a single cause (e.g., lack of faith). Second, the fact that 16 percent of our respondents did not espouse agreement with any explanation of mental illness suggests the need for further psychoeducation in clinical settings. Indeed, our results may not be about skepticism as much as lack of knowledge about what causes people to struggle with their mental health.

Conclusion

Although our study contributes to a better understanding of the social factors that influence perceptions of mental health, it also has several limitations. First, the data were collected in April 2021, shortly after COVID-19 vaccines became widely available to the American public. Given the widespread debates about the efficacy of vaccines, coupled with past research suggesting that views of the religion-science interface shape vaccine acceptance (Upenieks et al. 2022), it is possible that distrust of science might have been heightened during this time. Second, because the associations examined here are based on cross-sectional data, we cannot establish the causal direction of these relationships. Third, while this study sought to highlight racial-ethnic differences, given the small sample size of some groups we were unable to examine these processes among Asian Americans.

Last, although this study examines connections between religion and science previously unexplored in earlier research on mental health, future work should look to expand these items to consider the ways in which social location may influence beliefs and values not captured in the present study. For example, research suggests that both women (compared with men) and individuals of lower socioeconomic status (compared with individuals of higher socioeconomic status) are more likely to see God as involved in life and in control (Schieman et al. 2014) but also more likely to experience conditions such as anxiety and depression (American Psychiatric Association 2017; Lorant et al. 2003). Views on the religion-science interface might also help explain differences in views of etiology among these groups. We have also only used two measures of the religion-science interface here, and future work might draw on other measures to further explain differences across groups as well as include measures of science literacy to determine the impact of ideological orientation net of scientific knowledge and understanding. Despite these limitations, our study highlights how race-ethnicity, religion and views on science and religion are formative in shaping how people understand and explain the causes of mental health. Overall, the findings reveal there is a need for further research to uncover the nuances in views on science and religion, specifically related to mental health.

Footnotes

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Data collection was funded by “How Different Racial and Gender Groups View the Science and Religion of the Human Body,” Ecklund, Elaine Howard, PI, Andrea Henderson-Platt, Co-PI, a sub award of “The Sociology of Science and Religion: Identity and Belief Formation,” Ecklund, Elaine Howard, PI, John H. Evans, PI. Funded by the Templeton Religion Trust (TRT-2019-10205) and administered through The Issachar Fund (TIF0205A).

ORCID iDs

Daniel Bolger

Elaine Howard Ecklund

Notes

Author Biographies

Daniel Bolger is a postdoctoral research associate at the Center for Research on Child & Family Wellbeing in the School of Public and International Affairs at Princeton University.

Andrea K. Henderson is an associate professor in the Department of Sociology at the University of South Carolina.

Bianca Mabute-Louie is a doctoral student and graduate research assistant in the Sociology Department at Rice University.

Elaine Howard Ecklund is the Herbert S. Autrey Chair in Social Sciences, professor of sociology, and director of the Boniuk Institute for the Study and Advancement of Religious Tolerance at Rice University.

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The Intersections among Race,Religion,and Science in Explaining Mental Health Conditions

Abstract

Keywords

Racial Differences in Views of Etiology

The Role of Religion

Integrating Views on Religion and Science

Racial Differences in Views toward Science and Religion

Methods

Measures

Causes of Mental Health Conditions

Views on Science and Religion

Covariates

Analytical Strategy

Results

Discussion

Conclusion

Footnotes

Funding

ORCID iDs

Notes

Author Biographies

References