The Gerontologist cite as: Gerontologist, 2015, Vol. 55, No. 6, 961–971 doi:10.1093/geront/gnu020 Advance Access publication April 15, 2014
Research Article
Listening to Religious Music and Mental Health in Later Life Matt Bradshaw, PhD,*,1 Christopher G. Ellison, PhD,2 Qijuan Fang, MA,3 and Collin Mueller MA4 Department of Sociology, Baylor University, Waco, Texas, 2Department of Sociology, University of TexasSan Antonio, 3Department of Psychology, Bowling Green State University, Ohio, 4Department of Sociology, Duke University, Durham, North Carolina.
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*Address correspondence to Matt Bradshaw, PhD, Department of Sociology, Baylor University, 316 Draper Academic Building, One Bear Place #97326, Waco, TX 76798-7326. E-mail: [email protected] Received May 16, 2013; Accepted February 24, 2014
Decision Editor: Helen Kivnick, PhD
Abstract Purpose of the Study: Research has linked several aspects of religion—including service attendance, prayer, meditation, religious coping strategies, congregational support systems, and relations with God, among others—with positive mental health outcomes among older U.S. adults. This study examines a neglected dimension of religious life: listening to religious music. Design and Methods: Two waves of nationally representative data on older U.S. adults were analyzed (n = 1,024). Results: Findings suggest that the frequency of listening to religious music is associated with a decrease in death anxiety and increases in life satisfaction, self-esteem, and a sense of control across the 2 waves of data. In addition, the frequency of listening to gospel music (a specific type of religious music) is associated with a decrease in death anxiety and an increase in a sense of control. These associations are similar for blacks and whites, women and men, and low- and high-socioeconomic status individuals. Implications: Religion is an important socioemotional resource that has been linked with desirable mental health outcomes among older U.S. adults. This study shows that listening to religious music may promote psychological well-being in later life. Given that religious music is available to most individuals—even those with health problems or physical limitations that might preclude participation in more formal aspects of religious life—it might be a valuable resource for promoting mental health later in the life course. Key Words: Religion, Psychological well-being, Aging, Coping, Resilience
There is a complex relationship between age and psychological well-being. Some older adults report better mental health than their working-age counterparts, whereas others
experience declines in psychological well-being in later life (Wu, Schimmele, & Chappell, 2012; Yang, 2007). These disparate outcomes are the result of individual differences
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Background Research has shown that listening to music is associated with lower levels of anxiety (Evans & Rubio, 1994), greater satisfaction with life and feelings of escape from the hardships of life (Hayes & Minichiello, 2005), lower levels of anger and antisocial orientations (Baker & Bor, 2008; Krahe & Bieneck, 2012), and reduced depressive symptoms and other forms of psychopathology (Chan, Wong, Onishi, & Thayala, 2011; Erkkila et al., 2011). Research on physiological processes—including neuroimaging studies (e.g., functional magnetic resonance imaging and positron emission tomography)—shows that listening to music is associated with the activation of pleasure and reward circuits in the brain (Blood & Zatorre, 2001; Koelsch, Fritz, Yves v. Cramon, Muller, & Friederici, 2006). Other research has
linked listening to music with the dopaminergic system (Salimpoor, Benovoy, Larcher, Dagher, & Zatorre, 2011; Sutoo & Akiyama, 2004), which has been implicated in the initiation, regulation, and termination of emotions. Considerable research has even examined music as a form of therapy for dealing with stress and pain (Aldridge, 1995; Bailey, 1984). Most of this research has focused on secular music, but there are reasons to expect religious music to be associated with mental health. To begin with, religious music is an important avenue for the expression of—and connection with—one’s spirituality and, thus, its health benefits (Lipe, 2002; Miller & Strongman, 2002). Many religious teachings in the Christian tradition emphasize hope, optimism, love, and peace, and to the extent that religious music contains these themes, it could help promote psychological well-being (Aldridge, 1995; Bailey, 1984). The literature also shows that music is capable of altering emotional states in health-promoting ways (Chafin, Roy, Gerin, & Christenfeld, 2004; McCraty, Atkinson, & Rein, 1996). Religious music might serve this function, in part, by shifting thoughts and energy away from the undesirable and painful aspects of life and toward more desirable and healthy ones (TraugerQuerry & Haghighi, 1999) (For example, Gregorian chanting may promote serenity, set a somber spiritual mood, or trigger certain types of religious thoughts or emotional responses.). Research in this area also suggests that religious music serves as a source of strength and meaning in the face of suffering and that it also promotes a closer relationship with God (Jones, 1993; Viladesau, 2000) (For example, upbeat black gospel or bluegrass gospel may inspire relief and reassurance about one’s ultimate fate.). We also know that music may facilitate relaxation and promote a sense of calm (Chlan, 1998; Krout, 2007), and this may be particularly true for religious music. Listening to religious music may be particularly important among older adults because they may have difficulty participating in more traditional aspects of religion (e.g., religious services) because of physical limitations or other health problems (Lipe, 2002). Religious music can be accessed from most locations, including one’s home, and from a variety of sources including the Internet, recorded CDs, television, and radio. Religious music is also available to most individuals, young and old, and it is generally free of charge. Given that older adults tend to be more religious than working-age adults (Dillon & Wink, 2007), listening to religious music may be relatively common among this segment of the population. Further, although the experiences of adults in late life are heterogeneous and broad generalizations are difficult (George, 1993), many older adults may face declines in physical health, social resources (e.g., secular friendship ties), and opportunities for stimulation. For some persons, enjoying religious music may, therefore, fill an important void. Religious music might be one of the most valuable and easily accessible religious resources available to older adults.
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in (a) biological and environmental risk factors that undermine mental health and (b) psychosocial resources that either directly enhance psychological well-being or buffer against risk factors (Blazer & Hybels, 2005). This study examines whether listening to religious music—for example, genres of music such as gospel, contemporary Christian, and some forms of bluegrass, among others, that are composed for religious purposes or are focused on religious or sacred topics—functions as a mental health-promoting resource among older U.S. adults. Considerable research has examined the connection between religion and mental health (Krause, 2008; Smith, McCullough, & Poll, 2003). Much of this research has focused on organization-based activities such as service attendance, private practices including prayer, and various beliefs such as life after death (Bradshaw & Ellison, 2010). Some attention has also been devoted to religious coping strategies (Pargament, 1997), congregational support systems (Krause, 2008), and attachments to God (Bradshaw et al., 2010; Kirkpatrick, 2005). Relatively little work, however, has examined the relationship between listening to religious music and mental health in later life (Hamilton, Sandelowski, Moore, Agarwal, & Koenig, 2013; Lipe, 2002). Despite this neglect, the role of religious music fits nicely with research on complementary and alternative medicine, which includes both music and spirituality (Ellison, Bradshaw, & Roberts, 2012; Lipe, 2002). It is also consistent with a “holistic approach” to health (Micozzi, 2010), which emphasizes wellness and disease prevention, and focuses on the integration of physical, mental, and spiritual aspects of well-being. In this study, the relationship between listening to religious music and mental health in later life will be examined by initially reviewing the literature in this area. Several hypotheses will then be formulated and tested using two waves of data from a large national sample of older U.S. adults. The findings will then be summarized, and their implications for future research on religious music and mental health will be discussed.
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Hypotheses •• HI: Listening to religious music will be associated with improvements in mental health over time among older U.S. adults. •• H2: The relationship between listening to religious music and mental health will be stronger among blacks compared with whites. •• H3: The relationship between listening to religious music and mental health will be stronger among women compared with men. •• H4: The relationship between listening to religious music and mental health will be stronger among lowSES individuals compared with high-SES individuals.
Design and Methods Sample Data for this study come from two waves of the nationwide Religion, Aging, and Health Survey (2001, 2004) of older black and white U.S. adults (Krause, 2002). The study population was defined as all household residents who were either black or white, noninstitutionalized, English speaking, and at least 65 years of age. Geographically, the study population was restricted to eligible persons residing in the coterminous United States (i.e., residents of Alaska and Hawaii were excluded). Because it is difficult to devise a comprehensive set of religion measures for a large-scale study of religious life that are suitable for persons of all faiths, the researchers who designed the Religion, Aging, and Health Survey decided to only collect data from individuals who were (a) currently practicing Christians, (b) Christians in the past but no longer practice any religion, and (c) not affiliated with any faith at any point in their lifetime. Individuals who practice a religion other than Christianity (e.g., Jews or Muslims) were not included in the study design or sample. The final sample had the following characteristics: 91.8% Christian, 3% declined to answer the question about religious preference, 0.2% said they were not sure about their religious preference, and 5% said other (but not Jewish, Muslim, Buddhist, Hindu, Scientology, Bahai, or no religious preference). The sampling frame consisted of all eligible persons contained in the Health Care Financing Administration (HCFA) Medicare Beneficiary Eligibility List (HCFA is now called the Centers for Medicare and Medicaid Services— CMS). This list contained the name of everyone in the United States who has a Social Security number. The study design and survey instrument were constructed by Krause (2002), and the data collection was conducted by Louis Harris and Associates (now Harris Interactive). Baseline interviews were conducted face-to-face in the homes of the study participants in March–August 2001. Initial contact with study participants was made by sending a letter that outlined the purpose and nature of the study. The response rate for the baseline study was 62%. A total of 1,500 interviews were completed at baseline, and respondents were paid $30 for participation. Older blacks were oversampled. The sample consisted of 752 older blacks and 748 older whites. Data from the Current Population Survey was used to weight the sample by age, gender, education, and region of the country within each racial group at the time the sample was collected. Sampling weights were also included to adjust for the oversampling of older blacks. Three years later, a follow-up survey was conducted. Because the sample focused on older adults, there was some attrition across the two waves of data. The effective n for this study was 1,024, which represents the number of respondents who participated in the follow-up survey. Attrition across the two waves of data was caused by several factors: mortality (208 cases), inability to locate the
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The connection between religious music and mental health may work in distinctive ways for specific subgroups within the elderly population. For example, prior research has established that music holds a special place in the religious lives of African Americans (Frame & Williams, 1996; Jones, 1993). According to Hamilton and colleagues (2013, p. 27), who have reviewed this topic in detail: “Religious music, in particular, is an important part of African American culture and therefore a source of knowledge relevant to social and personal issues confronted by that population.” In addition, several studies have reported gender differences in the association between various facets of religiosity and mental health although the direction of these patterns has been inconsistent (Maselko & Kubzansky, 2006; McFarland, 2010). Further, researchers have reported that some dimensions of religiosity may be more salient for mental health among individuals who are socioeconomically deprived compared with those who are relatively or objectively privileged (Bradshaw & Ellison, 2010; Ellison, 1991). Overall, these findings raise the possibility that the association between listening to religious music and mental health may vary by race, gender, and socioeconomic status (SES). To summarize, this study will examine the relationship between listening to religious music and mental health using two waves of data on older U.S. adults. Relatively little work has been done on this topic, and the small literature that does exist suffers from three major limitations (Hamilton et al., 2013; Lipe, 2002). First, most studies on this topic are narrative descriptions or small case studies that may not be generalizable to a larger population. Second, most published studies were conducted in clinical contexts (i.e., there are no previously published studies based on community or national samples), so we do not currently know how the relationship between listening to religious music and mental health works in the broader population that includes healthy individuals. Third, no longitudinal studies have been conducted to date, so the causal order between listening to religious music and mental health is not known. This study will address each of these weaknesses.
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respondent at the second wave (112 cases), the respondent refused to participate at the second wave (75 cases), the respondent was ineligible to participate at the second wave due to institutionalization, and so on (81 cases). A total of 476 cases were lost between the two waves of data.
Dependent Variables
Independent Variables Frequency of listening to religious music at baseline was measured with the following question: “How often do you listen to religious music outside church—like when you are home or driving in your car?” This variable was coded 1 = never to 8 = several times a day. In addition, a measure of frequency of listening to gospel music at baseline was examined using the following item: “Now I have some questions about gospel music only. How often do you listen to gospel music?” This variable was also coded 1 = never to 8 = several times a day. Religious music is a broad category that includes, but is not limited to, gospel music. It may also include Gregorian chanting, contemporary Christian, and even some forms of bluegrass music, among others. For both of these variables, a series of categories was also constructed to check for nonlinear relationships with mental health. No clear nonlinear patterns were observed, so each was treated as a continuous variable in the models. Both of these questions were only asked at baseline, so it is not possible to examine changes in the frequency of listening to religious or gospel music in this study.
Covariates Age was a continuous measure with a range of 65–101. Race (1 = black compared with 0 = white), marital status (1 = married compared with 0 = not currently married), and gender (1 = women compared with 0 = men) were all dichotomous variables. Education was measured in total years of schooling, whereas perceived financial strain was tapped with the following two items: (1) “How much difficulty do you have in meeting the monthly payments on (your / your family’s) bills?” (response categories ranged from 1 = none to 4 = a great deal) and (2) “In general, how do (your / your family’s) finances work out at the end of the month?” (response categories ranged from 1 = money left over to 3 = not enough to make ends meet). Because these two items do not have identical response categories, they were converted to equivalent z-scores prior to the construction of the composite measure (α = .760). Self-rated fair
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Psychological distress at both baseline and follow-up was measured with an index composed of the mean value from the following eight items (Cronbach’s α = .869 at baseline and .880 at follow-up), which were taken from the Center for Epidemiologic Studies Depression scale (CES-D; see Hertzog, Van Alstine, Usala, Hultsch, & Dixon, 1990; Krause & Ellison, 2003): (1) “I felt I could not shake off the blues even with the help of my family and friends.” (2) “I felt depressed.” (3) “I had crying spells.” (4) “I felt sad.” (5) “I did not feel like eating, my appetite was poor.” (6) “I felt that everything I did was an effort.” (7) “My sleep was restless.” and (8) “I could not get going.” Each item was coded 1 = rarely or none of the time to 4 = most or all of the time. These eight items were the only ones available in the data that could be used to measure psychological distress. Death anxiety was measured with a mean index (Cronbach’s α = .849 at baseline and .895 at follow-up) of four items taken from scales in the literature (Krause & Ellison, 2003; Neimeyer, 1994): (1) “I find it hard to face up to the fact that I will die.” (2) “Thinking about death makes me feel uneasy.” (3) “I do not feel prepared to face my own death.” and (4) “I am disturbed by the shortness of life.” Each item was coded 1 = strongly disagree to 4 = strongly agree. No other items on death anxiety were available in the data. Life satisfaction was tapped with a mean index (Cronbach’s α = .735 at baseline and .731 at follow-up) of four items that were available at both waves of the data: (1) “These are the best years of my life.” (2) “As I look back on my life, I am fairly well satisfied.” (3) “I would not change the past even if I could.” and (4) “Now please think about your life as a whole. How satisfied are you with it.” The first three items are from the Life Satisfaction Index A (Neugarten, Havighurst, & Tobin, 1961); response categories ranged from 1 = strongly disagree to 4 = strongly agree. The fourth item assessed satisfaction with life as a whole, and response categories ranged from 1 = not satisfied at all to 5 = completely satisfied. Because these three items did not have identical response categories, they were converted to equivalent z-scores prior to the construction of the composite measure. Self-esteem was measured with a three-item mean index using questions developed by Rosenberg (1965). Specific items included (1) “I feel I am a person of worth, or at least on an equal plane with others.” (2) “I feel I have a number of good qualities.” and (3) “I take a positive attitude toward myself.” Response categories ranged from 1 = strongly disagree to 4 = strongly agree. The Cronbach’s α for this index
was .903 at baseline and .904 at follow-up. These three items were the only ones available in the data that could be used to measure self-esteem. A sense of control was measured with a mean index (Cronbach’s α = .848 at baseline and .862 at follow-up) composed of the following four items, which are similar to those developed by Rotter (1966) and Mirowsky and Ross (1991): (1) “I have a lot of influence over most things that happen in my life.” (2) “I can do just about anything I really set my mind to.” (3) “When I make plans, I’m almost certain to make them work.” and (4) “When I encounter problems, I don’t give up until I solve them.” Each item is coded 1 = strongly disagree to 4 = strongly agree. No other measures of personal control were available in the data.
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or poor health, which was coded 1 = fair or poor health and 0 = excellent or good, was controlled because it is an important predictor of mental health. Religious attendance was coded 1 = never to 9 = more than once a week, and prayer was coded 1 = never to 8 = daily.
effects of listening to religious and gospel music at baseline on mental health at follow-up were examined controlling for baseline mental health. Differences by race, gender, and SES were examined by introducing interaction terms between listening to religious and gospel music, and these variables, into the models one at a time.
Interaction Terms
Missing Data Missing data on all variables were dealt with using multiple imputation techniques in SAS 9.3. The number of missing cases was less than 5% for most measures. The results presented subsequently are based on five imputed data sets.
Analytic Strategy Data analysis was conducted in three steps. First, descriptive statistics were calculated. Second, bivariate correlations between key dependent and independent variables were estimated. Third, a series of ordinary least squares (OLS) regression models were fitted to the data. The main
Results Descriptive Statistics Table 1 presents descriptive statistics. On scales of 1–4, mean levels of the dependent variables for Waves 1 and 2, respectively, were 1.565 and 1.465 for psychological distress, 2.042 and 1.994 for death anxiety, 2.891 and 2.830 for life satisfaction, 3.444 and 3.495 for self-esteem, and 3.020 and 2.988 for a sense of control. The differences in means across the two waves of data were small for all measures but were statistically significant at p < .05 or less for each measure except for death anxiety. The sample was equally split between blacks and whites. Nearly 62% of the respondents were women, 47.3% were married, and 43.1% reported that their health was fair or poor (compared with good or excellent). The average respondent was around 75 years old, with roughly 11.3 years of formal education. Levels of financial strain, as measured at baseline, were relatively low (M = 1.769 on a 1–4 scale). The average respondent reported attending religious services roughly two to three times a month and praying approximately daily. Of particular importance to this study, the average respondent reported listening to religious music outside of church about once a week (M = 4.947). This variable had a range of 1 (never) to 8 (several times a day), and its distribution had a slight negative skew. The frequency
Table 1. Descriptive Statistics Variable
Mean/proportiona
SD
Range
Psychological distress T1/T2 Death anxiety T1/T2 Life satisfaction T1/T2 Self-esteem T1/T2 Sense of control T1/T2 Black (%) Female (%) Age Education Financial strain Married (%) Fair or poor health (%) Religious attendance Prayer Listening to religious music Listening to Gospel music
1.565/1.465b 2.042/1.994 2.891/2.830b 3.444/3.495b 3.020/2.988b 49 62 75.139 11.281 1.769 47 43 5.729 6.774 4.947 4.277
0.619/0.598 0.595/0.670 0.592/0.570 0.494/0.515 0.509/0.559 — — 6.670 3.484 0.993 — — 2.723 1.877 2.468 2.582
1–4 1–4 1–4 1–4 1–4 — — 65–101 1–25 1–4 — — 1–9 1–8 1–8 1–8
Notes: T1 = time 1; T2 = time 2. n = 1,024. a Means are reported for continuous measures and proportions for dichotomous measures. b Two-tailed t test indicates that the difference between these two means is statistically significant at p < .05.
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To test for race, gender, and SES differences in the relationship between listening to religious music and mental health, interaction terms were constructed for listening to religious (and gospel) music times: (1) black, (2) women, (3) education, and (4) financial strain. To reduce multicollinearity, all continuous variables were zero centered prior to constructing the interaction terms (Aiken & West, 1991), and all interaction terms were entered into the models one at a time. Variance Inflation Factor statistics indicated that multicollinearity was not a problem in the models.
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Bivariate Correlations Table 2 shows bivariate correlations for key dependent and independent variables. The correlations between baseline and follow-up levels of the dependent variables were .265 for psychological distress, .256 for death anxiety, .290 for life satisfaction, .193 for self-esteem, and .197 for a sense of control (all are statistically significant at p < .001 or less). The correlations between the frequency of listening to religious music and four of the five mental health variables (death anxiety, life satisfaction, self-esteem, and sense of control) were salutary and statistically significant, but relatively weak, at both waves; correlations ranged from .076 to .171 in magnitude. The correlations between listening to religious music and the remaining mental health outcome—psychological distress—measured at baseline and at follow-up were negligible and not statistically significant. The findings for gospel music were similar with
one exception: this variable was associated with psychological distress as well, especially at Wave 2. Overall, these bivariate patterns suggested that listening to religious and/ or gospel music had a statistically significant, yet weak, relationship with several different aspects of mental health in late life.
Regression Analyses Table 3 shows OLS parameter estimates from the regression of follow-up (Wave 2) mental health on baseline (Wave 1) mental health, covariates, and the frequency of listening to religious music. These models tested H1, which stated that listening to religious music would be associated with decreases in psychological distress and death anxiety and increases in life satisfaction, self-esteem, and a sense of control among older U.S. adults. Findings provided support for this hypothesis. The frequency of listening to religious music was inversely associated with levels of death anxiety at Wave 2 (b = −.035; p < .001) controlling for death anxiety at baseline. This means that listening to religious music was associated with a decline in death anxiety across the two waves of data. The frequency of listening to religious music was also associated with increases in life satisfaction (b = .019; p < .05), self-esteem (b = .015; p < .05), and a sense of control (b = .021; p < .01). It was not associated with psychological distress, however. The literature suggests that religious music is central in the lives of African Americans, so the analyses were conducted separately for blacks and whites. Contrary to H2, no significant differences were found between these two groups in the relationship between the frequency of listening to religious music and mental health. Similarly, there was no evidence of meaningful gender differences in these patterns, so H3 was not supported. Finally, the effects of
Table 2. Bivariate Correlations
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
1.000*** 0.265*** 0.131*** 0.085*** −0.298*** −0.106*** −0.186*** −0.132*** −0.348*** −0.115*** 0.015 ns 0.025+
1.000*** 0.099*** 0.185*** −0.141*** −0.276*** −0.103*** −0.205*** −0.134*** −0.202*** 0.022 ns 0.042**
1.000*** 0.256*** −0.158*** −0.127*** −0.296*** −0.113*** −0.137*** −0.027+ −0.117*** −0.071***
1.000*** −0.096*** −0.249*** −0.077*** −0.257*** −0.034** −0.155*** −0.024+ −0.043**
1.000*** 0.290*** 0.343*** 0.140*** 0.437*** 0.157*** 0.137*** 0.091***
1.000*** 0.124*** 0.377*** 0.122*** 0.377*** 0.171*** 0.184***
1.000*** 0.193*** 0.355*** 0.160*** 0.091*** 0.066***
1.000*** 0.137*** 0.406*** 0.119*** 0.159***
1.000*** 0.197*** 1.000*** 0.076*** 0.119*** 1.000*** 0.073*** 0.139*** 0.742*** 1.000***
Notes: 1 = psychological distress T2; 2 = psychological distress T1; 3 = death anxiety T2; 4 = death anxiety T1; 5 = life satisfaction T2; 6 = life satisfaction T1; 7 = self-esteem T2; 8 = self-esteem T1; 9 = sense of control T2; 10 = sense of control T1; 11 = listening to religious music; 12 = listening to Gospel music. n = 1,024; ns = not statistically significant at p < .05. ***p < .001; **p < .01; *p < .05; +p < .10.
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of listening to gospel music was slightly lower, averaging a few times a month (M = 4.277), and it had a similar distribution to religious music. Ancillary analyses (not shown) revealed that listening to religious music was more common among blacks than whites (M = 6.201 and 3.920, respectively), women compared with men (M = 5.215 and 4.643, respectively), individuals with a below average level of education compared with their better-educated counterparts (M = 5.663 and 4.580, respectively), and individuals who experienced above average levels of financial hardship compared with those who experienced below average levels (M = 5.631 and 4.547, respectively). All differences were statistically significant at p < .05 or less. Differences in the frequency of listening to gospel music by race, gender, and SES were similar to the patterns reported for listening to religious music in general.
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Table 3. OLS Parameter Estimates (Standard Errors in Parentheses) From the Regression of Follow-Up (Wave 2) Mental Health Variables on Baseline (Wave 1) Mental Health Variables, Covariates, and Frequency of Listening to Religious Music Death anxiety
Life satisfaction
1.072 (0.078)*** 0.209*** (0.033) −0.069 (0.044) 0.090* (0.040) 0.005+ (0.003) −0.013* (0.006) 0.041* (0.021) 0.034 (0.040) 0.114*** (0.039) −0.014+ (0.008) 0.011 (0.012) 0.000 (0.009) 0.101
1.613 (0.098)*** 2.004*** (0.105) 0.267*** (0.035) 0.225*** (0.031) 0.011 (0.050) 0.070+ (0.041) −0.005 (0.045) 0.042 (0.038) −0.010*** (0.003) −0.004 (0.003) −0.022 (0.007) 0.008 (0.006) 0.021 (0.023) −0.042* (0.019) −0.011 (0.044) 0.092** (0.037) 0.057 (0.043) −0.111*** (0.037) 0.006 (0.009) 0.008 (0.007) −0.022+ (0.013) 0.008 (0.011) −0.035*** (0.010) 0.019* (0.008) 0.106 0.116
Self-esteem
Sense of control
2.822*** (0.124) 0.168*** (0.033) 0.007 (0.039) 0.023 (0.035) −0.004+ (0.003) 0.008 (0.005) −0.041* (0.018) 0.032 (0.035) −0.051 (0.034) 0.000 (0.007) 0.019+ (0.011) 0.015* (0.007) 0.053
2.345*** (0.123) 0.186*** (0.036) −0.047 (0.042) −0.035 (0.038) −0.007** (0.003) 0.004 (0.006) −0.040* (0.019) 0.039 (0.037) −0.043 (0.037) 0.020** (0.007) −0.011 (0.012) 0.021** (0.008) 0.057
Notes: n = 1,024. ***p < .001; **p < .01; *p < .05; +p < .10.
Table 4. OLS Parameter Estimates (Standard Errors in Parentheses) From the Regression of Follow-Up (Wave 2) Mental Health Variables on Baseline (Wave 1) Mental Health Variables, Covariates, and Frequency of Listening to Gospel Music
Intercept Mental health variable T1 Black Female Age Education Financial strain Married Fair or poor health Religious attendance Prayer Listening to Gospel music Adjusted R2
Psychological distress
Death anxiety
Life satisfaction
Self-esteem
Sense of control
1.063*** (0.074) 0.209*** (0.032) −0.080 (0.046) 0.090* (0.040) 0.005+ (0.003) −0.015** (0.006) 0.036+ (0.020) 0.032 (0.039) 0.112*** (0.039) −0.015* (0.008) 0.011 (0.011) 0.004 (0.009) 0.096
1.556*** (0.094) 0.258*** (0.034) 0.001 (0.052) −0.005 (0.045) −0.011*** (0.003) −0.022*** (0.007) 0.019 (0.023) −0.014 (0.044) 0.057 (0.043) 0.004 (0.009) −0.029* (0.013) −0.022* (0.010) 0.089
2.057*** (0.102) 0.231*** (0.031) 0.093+ (0.044) 0.042 (0.038) −0.004 (0.003) 0.007 (0.006) −0.042* (0.019) 0.095** (0.037) −0.108*** (0.037) 0.008 (0.007) 0.015 (0.011) 0.003 (0.008) 0.110
2.863*** (0.121) 0.167*** (0.033) 0.016 (0.040) 0.022 (0.035) −0.004+ (0.003) 0.008 (0.005) −0.042* (0.018) 0.033 (0.035) −0.050 (0.034) 0.000 (0.007) 0.024+ (0.010) 0.008 (0.007) 0.053
2.362*** (0.121) 0.186*** (0.036) −0.058 (0.044) −0.034 (0.038) −0.007** (0.003) 0.005 (0.006) −0.043* (0.019) 0.039 (0.037) −0.043 (0.037) 0.019** (0.007) −0.011 (0.011) 0.021** (0.009) 0.068
Notes: n = 1,024. ***p < .001; **p < .01; *p < .05; +p < .10.
listening to religious music were examined across levels of SES. Contrary to H4, findings did not reveal any differences in the relationship between religious music and mental health by education or financial hardship. Overall, the results suggested that the listening to religious music functioned in broadly similar ways for blacks and whites, women and men, and individuals with different levels of SES. Finally, the data also contained a measure of the frequency of listening to gospel music (a more specific type of religious music), and the analyses described earlier were conducted using this measure as well. The results for this variable (shown in Table 4) revealed significant relationships between this variable and two of the five mental health outcomes examined here: death anxiety (b = −.022; p < .05) and a sense of control (b = .021; p < .01). Once
again, none of these patterns was found to vary by race, gender, or SES.
Discussion There is growing interest in the connection between religion and mental health (Smith et al., 2003). Scholars have linked many different facets of religious life—for example, organizational involvement, prayer, belief in an afterlife, religious coping, congregational support, and attachments to God, among others—with mental health (Bradshaw et al., 2010; Krause, 2008; Pargament, 1997). This study has augmented that list to include listening to religious music (Hamilton et al., 2013; Lipe, 2002). A large literature has linked listening to secular music with emotional and physiological processes (Chan et al., 2011; Erkkila et al., 2011; Hayes &
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Intercept Mental health variable T1 Black Female Age Education Financial strain Married Fair or poor health Religious attendance Prayer Listening to religious music Adjusted R2
Psychological distress
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studies have reported that religion is associated with mental health in part because it promotes social support networks, provides positive coping resources, offers messages of hope and optimism, and allows individuals to develop close intimate relationships with a divine other. Listening to religious music also appears to matter for mental health, either by facilitating one or more of these well-established mechanisms or by conferring additional benefits through other (e.g., physiological) processes. Clarifying the underlying nature of the associations between listening to religious music and desirable mental health outcomes should be a priority for future research. This study is also characterized by several limitations. First, it is unclear how or whether the context in which one listens to religious music matters. The survey item asked how frequently individuals listened to religious music outside of worship services. Although this is useful for isolating the effects of religious music from those of service attendance and prayer, it cannot reveal whether listening to religious music is more helpful in certain circumstances (e.g., in a quiet room at home) than in others (e.g., in traffic or other stressful settings). Second, due to data limitations, it is not feasible to compare the effects of religious versus secular music on mental health. It is possible that persons who listen to religious music also enjoy other types of music and, thus, we cannot definitively establish that religious music carries distinctive benefits. Third, some degree of confounding could result due to the effects of singing or physical movement that may occur when some individuals listen to religious music. However, data limitations preclude exploration of this issue. Fourth, some mental health outcomes were examined using nonstandard measures, and it would be desirable to replicate these findings using additional measures of psychological well-being and psychopathology. Fifth, the focus on a single faith group (i.e., Christians) clearly limits the generalizability of the findings to other religious traditions, and future research should attempt to address this weakness. Sixth, the changing characteristics of the sample over time could have affected the results. The follow-up rate of 68% is relatively low and could have conceivably biased the findings, especially given that older participants and those with health problems were less likely to participate in the follow-up survey: 55.35% of the respondents who did not participate in the follow-up survey reported having fair or poor health (compared with good or excellent) at baseline compared with 37.63% for those who participated in both waves. These processes caused the sample to become more healthy over time (43.28% and 37.63% of the sample, respectively, reported fair or poor health at baseline and follow-up), which could have contributed to the improvements in psychological well-being observed in the data. To build on this study, future research should address the limitations outlined earlier. In addition, investigators might profitably examine the effects of listening to diverse types of religious music. It is not clear whether certain
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Minichiello, 2005; Krahe & Bieneck, 2012), and this work strengthens the basis for expecting that religious music may be associated with mental health. Our analysis of two waves of data from a nationwide survey of older U.S. adults showed that the frequency of listening to religious music at baseline was associated with mental health 3 years later at Wave 2, controlling for baseline mental health, religious service attendance, prayer, self-rated health, and sociodemographic variables. More specifically, listening to religious music was associated with modest, yet statistically significant, declines in death anxiety (effect size = 0.012) and increases in life satisfaction (effect size = 0.008), self-esteem (effect size = 0.005), and a sense of control (effect size = 0.010) across two waves of data that spanned a 3-year period. Listening to gospel music, a specific type of religious music, was associated with two mental health outcomes: death anxiety (effect size = 0.060) and a sense of control (effect size = 0.050). These effect sizes were small, but given that many individuals in later life are exposed to a variety of biological and social–environmental risk factors that undermine mental health (Blazer & Hybels, 2005), the fact that listening to religious or gospel music was associated with improvements in mental health (not simply with a slower rate of decline) is noteworthy. These findings were net of two other important aspects of religious life: service attendance and prayer. Also, the relationship between religious music and mental health did not vary for blacks versus whites, women and men, and low- versus high-SES individuals. The fact that the findings were stronger and more consistent across mental health outcomes for religious music in general suggests that, although some of the salutary effects of listening to religious music may reflect benefits associated with gospel music specifically, other types of religious music may also have implications for mental health. Gospel music is itself a very diverse music genre, ranging from bluegrass gospel to upbeat Black gospel and many other types as well. However, religious music is an even broader and more inclusive label, extending to Gregorian chanting, religious classical and chamber music, and numerous other types of musical expression. These findings contribute to the literature on religion and mental health in several ways. They indicate that the mental health consequences of religious activities are not simply about social interaction or connectedness; indeed, these patterns persisted with controls for individual-level variations in religious service attendance. The findings reported here point to the significance of private aspects of religious life that cannot simply be reduced to social integration. These findings are particularly important for this study population because many older adults experience illnesses or disabilities that prevent them from attending religious services or participating in congregational life on a regular basis. The findings reported here also underscore the fact that religion is a multifaceted phenomenon that affects mental health in a variety of ways. Numerous prior
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health-promoting effects (Szanton, Wenzel, Connolly, & Piferi, 2011). Listening to religious music may help promote feelings of calm, which subsequently enhance psychological well-being. Listening to religious music may serve as a form of “self-care” or “self-comforting” (Hamilton et al., 2013), which could be used profitably in a complementary fashion with more traditional forms of health care. To conclude, listening to religious music appears to be associated with declines in death anxiety and increases in life satisfaction, self-esteem, and a sense of control among older U.S. adults. These findings contribute to research showing the effects of listening to music on mental health, as well as a growing literature on the religion–mental health connection. Much work remains to be done in this area, and future research should seek to understand exactly how and why religious music is associated with mental health in later life.
Acknowledgments A previous version of this paper was presented at the 2012 Meeting of the Association for the Sociology of Religion, Denver, CO. The lead author would like to thank Baylor University for providing start-up funds that contributed to this research. The authors would like to thank Neal Krause and Interuniversity Consortium for Political and Social Research (http://www.icpsr.umich.edu) for providing access to the data used in this study.
References Aiken, L., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Thousand Oaks, CA: Sage. Aldridge, D. (1995). Spirituality, hope and music therapy in palliative care. The Arts in Psychotherapy, 22, 103–109. Bailey, L. M. (1984). The use of songs in music therapy with cancer patients and their families. Music Therapy, 4, 5–17. doi:10.1093/ mt/4.1.5 Baker, F., & Bor, W. (2008). Can music preference indicate mental health status in young people? Australasian Psychiatry, 16, 284– 288. doi:10.1080/10398560701879589 Blazer, D. G., & Hybels, C. F. (2005). Origins of depression in later life. Psychological Medicine, 35, 1–12. doi:10.1017/ S0033291705004411 Blood, A. J., & Zatorre, R. J. (2001). Intensely pleasurable responses to music correlate with activity in brain regions implicated in reward and emotion. Proceedings of the National Academy of Sciences of the United States of America, 98, 11818–11823. doi:10.1073/pnas.191355898 Bradshaw, M., & Ellison, C. G. (2010). Financial hardship and psychological distress: Exploring the buffering effects of religion. Social Science & Medicine, 71, 196–204. Retrieved from http:// dx.doi.org/10.1016/j.socscimed.2010.03.015 Bradshaw, M., Ellison, C. G., & Marcum, J. P. (2010). Attachment to God, images of God, and psychological distress in a nationwide sample of Presbyterians. The International Journal for the Psychology of Religion, 20, 130–147. doi:10.1080/10508611003608049
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specific genres of religious music are more beneficial for mental health than other types, due to tones, rhythms, or lyrical content. For example, Gregorian chanting could promote serenity and calm, set a somber spiritual mood, evoke a sense of awe and majesty, or trigger other religious cognitions or emotional responses that may influence the mental health outcomes studied here. Other types of religious music, such as contemporary Christian, bluegrass, and upbeat Black gospel, tend to embody certain characteristics and emphasize particular lyrical themes that may strengthen faith commitments, reassure believers, and uplift listeners emotionally. One recent study of thematic content of religious music based on interviews with older African Americans provides a useful start on this topic. In this work, Hamilton and colleagues (2013) identified several distinct types of religious songs. Among the most common of these were songs that focused on thanksgiving and praise, connection with God, strength and resilience, and a sense of control. Some religious songs were also instructive, emphasizing a sense of obligation to help others. Hamilton and colleagues and their study participants also pointed to songs that promoted prayerful communication with God, as well as those that reminded the faithful of life everlasting. This latter theme is especially noteworthy because previous studies have associated belief in life after death with desirable mental health outcomes such as reduced anxiety and depressed affect (Ellison, Burdette, & Hill, 2009; Flannelly, Koenig, Ellison, Galek, & Krause, 2006). Although the work of Hamilton and colleagues focused specifically on older African Americans, many of these themes could resonate with other groups as well, and their possible distinctive benefits merit future investigation. Future research should also seek to identify the mechanisms by which listening to religious music affects mental health. For example, to the extent that listening to religious music facilitates a secure attachment to a loving and supportive God, this could be an important mechanism by which religious music affects mental health (Bradshaw et al., 2010; Kirkpatrick, 2005). In addition, research suggests that music actually alters physiological processes in health-promoting ways (Blood & Zatorre, 2001; Koelsch et al., 2006). In particular, future research should certainly attempt to examine the role of neurotransmitters such as dopamine and serotonin in mediating the relationship between listening to religious music and mental health. Given the growth of non-Christian populations in the United States, future research should also examine the effects of religious music among other faith traditions. Many scholars and health practitioners have emphasized the need for holistic approaches to health and personalized forms of medicine that seek to care for the entire individual, mentally, physically, and spiritually. The findings reported here have implications for disease prevention and treatment. A growing literature suggests that meditation and relaxation techniques (e.g., mindfulness) have
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Chafin, S., Roy, M., Gerin, W., & Christenfeld, N. (2004). Music can facilitate blood pressure recovery from stress. British Journal of Health Psychology, 9, 393–403. Chan, M. F., Wong, Z. Y., Onishi, H., & Thayala, N. V. (2011). Effects of music on depression in older people: A randomised controlled trial. Journal of Clinical Nursing, 21, 776–783. doi:10.1111/j.1365-2702.2011.03954.x Chlan, L. (1998). Effectiveness of a music therapy intervention on relaxation and anxiety for patients receiving ventilatory assistance. Heart & Lung, 27, 169–176. Retrieved from http:// dx.doi.org/10.1016/S0147-9563(98)90004-8 Dillon, M., & Wink, P. (2007). In the course of a lifetime: Tracing religious belief, practice, and change. Oakland, CA: University of California Press. Ellison, C. G. (1991). Religious involvement and subjective wellbeing. Journal of Health and Social Behavior, 32, 80–99. Ellison, C. G., Bradshaw, M., & Roberts, C. A. (2012). Spiritual and religious identities predict the use of complementary and alternative medicine among US adults. Preventive Medicine, 54, 9–12. doi:10.1016/j.ypmed.2011.08.029 Ellison, C. G., Burdette, A. M., & Hill, T. D. (2009). Blessed assurance: Religion, anxiety, and tranquility among US adults. Social Science Research, 38, 656–667. doi:10.1016/j.ssresearch.2009.02.002 Erkkila, J., Punkanen, M., Fachner, J., Ala-Ruona, E., Pontio, I., Tervaniemi, M., …, Gold, C. (2011). Individual music therapy for depression: Randomised controlled trial. British Journal of Psychiatry, 199, 132–139. doi:10.1192/bjp.bp.110.085431 Evans, M. M., & Rubio, P. A. (1994). Music: A diversionary therapy. Today’s OR Nurse, 16, 17–22. Flannelly, K. J., Koenig, H. G., Ellison, C. G., Galek, K., & Krause, N. (2006). Belief in life after death and mental health: Findings from a national survey. The Journal of Nervous and Mental Disease, 194, 524–529. doi:10.1097/01.nmd.0000224876.63035.23 Frame, M. W., & Williams, C. B. (1996). Counseling African Americans: Integrating spirituality in therapy. Counseling and Values, 41, 16–28. doi:10.1002/j.2161-007X.1996.tb00859.x George, L. K. (1993). Sociological perspectives on life transitions. Annual Review of Sociology, 19, 353–373. doi:10.1146/ annurev.so.19.080193.002033 Hamilton, J. B., Sandelowski, M., Moore, A. D., Agarwal, M., & Koenig, H. G. (2013). “You need a song to bring you through”: The use of religious songs to manage stressful life events. The Gerontologist, 53, 26–38. doi:10.1093/geront/gns064 Hayes, T., & Minichiello, V. (2005). The contribution of music to quality of life in older people: An Australian qualitative study. Aging & Society, 25, 261–278. doi:10.1017/S0144686X04002946 Hertzog, C., Van Alstine, J., Usala, P. D., Hultsch, D. F., & Dixon, R. (1990). Measurement properties of the Center for Epidemiologic Studies Depression Scale (CES-D) in older populations. Psychological Assessment, 2, 64–72. doi.apa.org/journals/ pas/2/1/64 Jones, A. C. (1993). Wade in the water. The wisdom of the spirituals. Maryknoll, NY: Orbis Books. Kirkpatrick, L. A. (2005). Attachment, evolution, and the psychology of religion. New York: Guilford. Koelsch, S., Fritz, T., Yves V. Cramon, D., Müller, K., & Friederici, A. D. (2006). Investigating emotion with music: An fMRI study. Human Brain Mapping, 27, 239–250. doi:10.1002/hbm.20180
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Research Article
Listening to Religious Music and Mental Health in Later Life Matt Bradshaw, PhD,*,1 Christopher G. Ellison, PhD,2 Qijuan Fang, MA,3 and Collin Mueller MA4 Department of Sociology, Baylor University, Waco, Texas, 2Department of Sociology, University of TexasSan Antonio, 3Department of Psychology, Bowling Green State University, Ohio, 4Department of Sociology, Duke University, Durham, North Carolina.
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1
*Address correspondence to Matt Bradshaw, PhD, Department of Sociology, Baylor University, 316 Draper Academic Building, One Bear Place #97326, Waco, TX 76798-7326. E-mail: [email protected] Received May 16, 2013; Accepted February 24, 2014
Decision Editor: Helen Kivnick, PhD
Abstract Purpose of the Study: Research has linked several aspects of religion—including service attendance, prayer, meditation, religious coping strategies, congregational support systems, and relations with God, among others—with positive mental health outcomes among older U.S. adults. This study examines a neglected dimension of religious life: listening to religious music. Design and Methods: Two waves of nationally representative data on older U.S. adults were analyzed (n = 1,024). Results: Findings suggest that the frequency of listening to religious music is associated with a decrease in death anxiety and increases in life satisfaction, self-esteem, and a sense of control across the 2 waves of data. In addition, the frequency of listening to gospel music (a specific type of religious music) is associated with a decrease in death anxiety and an increase in a sense of control. These associations are similar for blacks and whites, women and men, and low- and high-socioeconomic status individuals. Implications: Religion is an important socioemotional resource that has been linked with desirable mental health outcomes among older U.S. adults. This study shows that listening to religious music may promote psychological well-being in later life. Given that religious music is available to most individuals—even those with health problems or physical limitations that might preclude participation in more formal aspects of religious life—it might be a valuable resource for promoting mental health later in the life course. Key Words: Religion, Psychological well-being, Aging, Coping, Resilience
There is a complex relationship between age and psychological well-being. Some older adults report better mental health than their working-age counterparts, whereas others
experience declines in psychological well-being in later life (Wu, Schimmele, & Chappell, 2012; Yang, 2007). These disparate outcomes are the result of individual differences
© The Author 2014. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: [email protected].
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Background Research has shown that listening to music is associated with lower levels of anxiety (Evans & Rubio, 1994), greater satisfaction with life and feelings of escape from the hardships of life (Hayes & Minichiello, 2005), lower levels of anger and antisocial orientations (Baker & Bor, 2008; Krahe & Bieneck, 2012), and reduced depressive symptoms and other forms of psychopathology (Chan, Wong, Onishi, & Thayala, 2011; Erkkila et al., 2011). Research on physiological processes—including neuroimaging studies (e.g., functional magnetic resonance imaging and positron emission tomography)—shows that listening to music is associated with the activation of pleasure and reward circuits in the brain (Blood & Zatorre, 2001; Koelsch, Fritz, Yves v. Cramon, Muller, & Friederici, 2006). Other research has
linked listening to music with the dopaminergic system (Salimpoor, Benovoy, Larcher, Dagher, & Zatorre, 2011; Sutoo & Akiyama, 2004), which has been implicated in the initiation, regulation, and termination of emotions. Considerable research has even examined music as a form of therapy for dealing with stress and pain (Aldridge, 1995; Bailey, 1984). Most of this research has focused on secular music, but there are reasons to expect religious music to be associated with mental health. To begin with, religious music is an important avenue for the expression of—and connection with—one’s spirituality and, thus, its health benefits (Lipe, 2002; Miller & Strongman, 2002). Many religious teachings in the Christian tradition emphasize hope, optimism, love, and peace, and to the extent that religious music contains these themes, it could help promote psychological well-being (Aldridge, 1995; Bailey, 1984). The literature also shows that music is capable of altering emotional states in health-promoting ways (Chafin, Roy, Gerin, & Christenfeld, 2004; McCraty, Atkinson, & Rein, 1996). Religious music might serve this function, in part, by shifting thoughts and energy away from the undesirable and painful aspects of life and toward more desirable and healthy ones (TraugerQuerry & Haghighi, 1999) (For example, Gregorian chanting may promote serenity, set a somber spiritual mood, or trigger certain types of religious thoughts or emotional responses.). Research in this area also suggests that religious music serves as a source of strength and meaning in the face of suffering and that it also promotes a closer relationship with God (Jones, 1993; Viladesau, 2000) (For example, upbeat black gospel or bluegrass gospel may inspire relief and reassurance about one’s ultimate fate.). We also know that music may facilitate relaxation and promote a sense of calm (Chlan, 1998; Krout, 2007), and this may be particularly true for religious music. Listening to religious music may be particularly important among older adults because they may have difficulty participating in more traditional aspects of religion (e.g., religious services) because of physical limitations or other health problems (Lipe, 2002). Religious music can be accessed from most locations, including one’s home, and from a variety of sources including the Internet, recorded CDs, television, and radio. Religious music is also available to most individuals, young and old, and it is generally free of charge. Given that older adults tend to be more religious than working-age adults (Dillon & Wink, 2007), listening to religious music may be relatively common among this segment of the population. Further, although the experiences of adults in late life are heterogeneous and broad generalizations are difficult (George, 1993), many older adults may face declines in physical health, social resources (e.g., secular friendship ties), and opportunities for stimulation. For some persons, enjoying religious music may, therefore, fill an important void. Religious music might be one of the most valuable and easily accessible religious resources available to older adults.
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in (a) biological and environmental risk factors that undermine mental health and (b) psychosocial resources that either directly enhance psychological well-being or buffer against risk factors (Blazer & Hybels, 2005). This study examines whether listening to religious music—for example, genres of music such as gospel, contemporary Christian, and some forms of bluegrass, among others, that are composed for religious purposes or are focused on religious or sacred topics—functions as a mental health-promoting resource among older U.S. adults. Considerable research has examined the connection between religion and mental health (Krause, 2008; Smith, McCullough, & Poll, 2003). Much of this research has focused on organization-based activities such as service attendance, private practices including prayer, and various beliefs such as life after death (Bradshaw & Ellison, 2010). Some attention has also been devoted to religious coping strategies (Pargament, 1997), congregational support systems (Krause, 2008), and attachments to God (Bradshaw et al., 2010; Kirkpatrick, 2005). Relatively little work, however, has examined the relationship between listening to religious music and mental health in later life (Hamilton, Sandelowski, Moore, Agarwal, & Koenig, 2013; Lipe, 2002). Despite this neglect, the role of religious music fits nicely with research on complementary and alternative medicine, which includes both music and spirituality (Ellison, Bradshaw, & Roberts, 2012; Lipe, 2002). It is also consistent with a “holistic approach” to health (Micozzi, 2010), which emphasizes wellness and disease prevention, and focuses on the integration of physical, mental, and spiritual aspects of well-being. In this study, the relationship between listening to religious music and mental health in later life will be examined by initially reviewing the literature in this area. Several hypotheses will then be formulated and tested using two waves of data from a large national sample of older U.S. adults. The findings will then be summarized, and their implications for future research on religious music and mental health will be discussed.
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Hypotheses •• HI: Listening to religious music will be associated with improvements in mental health over time among older U.S. adults. •• H2: The relationship between listening to religious music and mental health will be stronger among blacks compared with whites. •• H3: The relationship between listening to religious music and mental health will be stronger among women compared with men. •• H4: The relationship between listening to religious music and mental health will be stronger among lowSES individuals compared with high-SES individuals.
Design and Methods Sample Data for this study come from two waves of the nationwide Religion, Aging, and Health Survey (2001, 2004) of older black and white U.S. adults (Krause, 2002). The study population was defined as all household residents who were either black or white, noninstitutionalized, English speaking, and at least 65 years of age. Geographically, the study population was restricted to eligible persons residing in the coterminous United States (i.e., residents of Alaska and Hawaii were excluded). Because it is difficult to devise a comprehensive set of religion measures for a large-scale study of religious life that are suitable for persons of all faiths, the researchers who designed the Religion, Aging, and Health Survey decided to only collect data from individuals who were (a) currently practicing Christians, (b) Christians in the past but no longer practice any religion, and (c) not affiliated with any faith at any point in their lifetime. Individuals who practice a religion other than Christianity (e.g., Jews or Muslims) were not included in the study design or sample. The final sample had the following characteristics: 91.8% Christian, 3% declined to answer the question about religious preference, 0.2% said they were not sure about their religious preference, and 5% said other (but not Jewish, Muslim, Buddhist, Hindu, Scientology, Bahai, or no religious preference). The sampling frame consisted of all eligible persons contained in the Health Care Financing Administration (HCFA) Medicare Beneficiary Eligibility List (HCFA is now called the Centers for Medicare and Medicaid Services— CMS). This list contained the name of everyone in the United States who has a Social Security number. The study design and survey instrument were constructed by Krause (2002), and the data collection was conducted by Louis Harris and Associates (now Harris Interactive). Baseline interviews were conducted face-to-face in the homes of the study participants in March–August 2001. Initial contact with study participants was made by sending a letter that outlined the purpose and nature of the study. The response rate for the baseline study was 62%. A total of 1,500 interviews were completed at baseline, and respondents were paid $30 for participation. Older blacks were oversampled. The sample consisted of 752 older blacks and 748 older whites. Data from the Current Population Survey was used to weight the sample by age, gender, education, and region of the country within each racial group at the time the sample was collected. Sampling weights were also included to adjust for the oversampling of older blacks. Three years later, a follow-up survey was conducted. Because the sample focused on older adults, there was some attrition across the two waves of data. The effective n for this study was 1,024, which represents the number of respondents who participated in the follow-up survey. Attrition across the two waves of data was caused by several factors: mortality (208 cases), inability to locate the
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The connection between religious music and mental health may work in distinctive ways for specific subgroups within the elderly population. For example, prior research has established that music holds a special place in the religious lives of African Americans (Frame & Williams, 1996; Jones, 1993). According to Hamilton and colleagues (2013, p. 27), who have reviewed this topic in detail: “Religious music, in particular, is an important part of African American culture and therefore a source of knowledge relevant to social and personal issues confronted by that population.” In addition, several studies have reported gender differences in the association between various facets of religiosity and mental health although the direction of these patterns has been inconsistent (Maselko & Kubzansky, 2006; McFarland, 2010). Further, researchers have reported that some dimensions of religiosity may be more salient for mental health among individuals who are socioeconomically deprived compared with those who are relatively or objectively privileged (Bradshaw & Ellison, 2010; Ellison, 1991). Overall, these findings raise the possibility that the association between listening to religious music and mental health may vary by race, gender, and socioeconomic status (SES). To summarize, this study will examine the relationship between listening to religious music and mental health using two waves of data on older U.S. adults. Relatively little work has been done on this topic, and the small literature that does exist suffers from three major limitations (Hamilton et al., 2013; Lipe, 2002). First, most studies on this topic are narrative descriptions or small case studies that may not be generalizable to a larger population. Second, most published studies were conducted in clinical contexts (i.e., there are no previously published studies based on community or national samples), so we do not currently know how the relationship between listening to religious music and mental health works in the broader population that includes healthy individuals. Third, no longitudinal studies have been conducted to date, so the causal order between listening to religious music and mental health is not known. This study will address each of these weaknesses.
963
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respondent at the second wave (112 cases), the respondent refused to participate at the second wave (75 cases), the respondent was ineligible to participate at the second wave due to institutionalization, and so on (81 cases). A total of 476 cases were lost between the two waves of data.
Dependent Variables
Independent Variables Frequency of listening to religious music at baseline was measured with the following question: “How often do you listen to religious music outside church—like when you are home or driving in your car?” This variable was coded 1 = never to 8 = several times a day. In addition, a measure of frequency of listening to gospel music at baseline was examined using the following item: “Now I have some questions about gospel music only. How often do you listen to gospel music?” This variable was also coded 1 = never to 8 = several times a day. Religious music is a broad category that includes, but is not limited to, gospel music. It may also include Gregorian chanting, contemporary Christian, and even some forms of bluegrass music, among others. For both of these variables, a series of categories was also constructed to check for nonlinear relationships with mental health. No clear nonlinear patterns were observed, so each was treated as a continuous variable in the models. Both of these questions were only asked at baseline, so it is not possible to examine changes in the frequency of listening to religious or gospel music in this study.
Covariates Age was a continuous measure with a range of 65–101. Race (1 = black compared with 0 = white), marital status (1 = married compared with 0 = not currently married), and gender (1 = women compared with 0 = men) were all dichotomous variables. Education was measured in total years of schooling, whereas perceived financial strain was tapped with the following two items: (1) “How much difficulty do you have in meeting the monthly payments on (your / your family’s) bills?” (response categories ranged from 1 = none to 4 = a great deal) and (2) “In general, how do (your / your family’s) finances work out at the end of the month?” (response categories ranged from 1 = money left over to 3 = not enough to make ends meet). Because these two items do not have identical response categories, they were converted to equivalent z-scores prior to the construction of the composite measure (α = .760). Self-rated fair
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Psychological distress at both baseline and follow-up was measured with an index composed of the mean value from the following eight items (Cronbach’s α = .869 at baseline and .880 at follow-up), which were taken from the Center for Epidemiologic Studies Depression scale (CES-D; see Hertzog, Van Alstine, Usala, Hultsch, & Dixon, 1990; Krause & Ellison, 2003): (1) “I felt I could not shake off the blues even with the help of my family and friends.” (2) “I felt depressed.” (3) “I had crying spells.” (4) “I felt sad.” (5) “I did not feel like eating, my appetite was poor.” (6) “I felt that everything I did was an effort.” (7) “My sleep was restless.” and (8) “I could not get going.” Each item was coded 1 = rarely or none of the time to 4 = most or all of the time. These eight items were the only ones available in the data that could be used to measure psychological distress. Death anxiety was measured with a mean index (Cronbach’s α = .849 at baseline and .895 at follow-up) of four items taken from scales in the literature (Krause & Ellison, 2003; Neimeyer, 1994): (1) “I find it hard to face up to the fact that I will die.” (2) “Thinking about death makes me feel uneasy.” (3) “I do not feel prepared to face my own death.” and (4) “I am disturbed by the shortness of life.” Each item was coded 1 = strongly disagree to 4 = strongly agree. No other items on death anxiety were available in the data. Life satisfaction was tapped with a mean index (Cronbach’s α = .735 at baseline and .731 at follow-up) of four items that were available at both waves of the data: (1) “These are the best years of my life.” (2) “As I look back on my life, I am fairly well satisfied.” (3) “I would not change the past even if I could.” and (4) “Now please think about your life as a whole. How satisfied are you with it.” The first three items are from the Life Satisfaction Index A (Neugarten, Havighurst, & Tobin, 1961); response categories ranged from 1 = strongly disagree to 4 = strongly agree. The fourth item assessed satisfaction with life as a whole, and response categories ranged from 1 = not satisfied at all to 5 = completely satisfied. Because these three items did not have identical response categories, they were converted to equivalent z-scores prior to the construction of the composite measure. Self-esteem was measured with a three-item mean index using questions developed by Rosenberg (1965). Specific items included (1) “I feel I am a person of worth, or at least on an equal plane with others.” (2) “I feel I have a number of good qualities.” and (3) “I take a positive attitude toward myself.” Response categories ranged from 1 = strongly disagree to 4 = strongly agree. The Cronbach’s α for this index
was .903 at baseline and .904 at follow-up. These three items were the only ones available in the data that could be used to measure self-esteem. A sense of control was measured with a mean index (Cronbach’s α = .848 at baseline and .862 at follow-up) composed of the following four items, which are similar to those developed by Rotter (1966) and Mirowsky and Ross (1991): (1) “I have a lot of influence over most things that happen in my life.” (2) “I can do just about anything I really set my mind to.” (3) “When I make plans, I’m almost certain to make them work.” and (4) “When I encounter problems, I don’t give up until I solve them.” Each item is coded 1 = strongly disagree to 4 = strongly agree. No other measures of personal control were available in the data.
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or poor health, which was coded 1 = fair or poor health and 0 = excellent or good, was controlled because it is an important predictor of mental health. Religious attendance was coded 1 = never to 9 = more than once a week, and prayer was coded 1 = never to 8 = daily.
effects of listening to religious and gospel music at baseline on mental health at follow-up were examined controlling for baseline mental health. Differences by race, gender, and SES were examined by introducing interaction terms between listening to religious and gospel music, and these variables, into the models one at a time.
Interaction Terms
Missing Data Missing data on all variables were dealt with using multiple imputation techniques in SAS 9.3. The number of missing cases was less than 5% for most measures. The results presented subsequently are based on five imputed data sets.
Analytic Strategy Data analysis was conducted in three steps. First, descriptive statistics were calculated. Second, bivariate correlations between key dependent and independent variables were estimated. Third, a series of ordinary least squares (OLS) regression models were fitted to the data. The main
Results Descriptive Statistics Table 1 presents descriptive statistics. On scales of 1–4, mean levels of the dependent variables for Waves 1 and 2, respectively, were 1.565 and 1.465 for psychological distress, 2.042 and 1.994 for death anxiety, 2.891 and 2.830 for life satisfaction, 3.444 and 3.495 for self-esteem, and 3.020 and 2.988 for a sense of control. The differences in means across the two waves of data were small for all measures but were statistically significant at p < .05 or less for each measure except for death anxiety. The sample was equally split between blacks and whites. Nearly 62% of the respondents were women, 47.3% were married, and 43.1% reported that their health was fair or poor (compared with good or excellent). The average respondent was around 75 years old, with roughly 11.3 years of formal education. Levels of financial strain, as measured at baseline, were relatively low (M = 1.769 on a 1–4 scale). The average respondent reported attending religious services roughly two to three times a month and praying approximately daily. Of particular importance to this study, the average respondent reported listening to religious music outside of church about once a week (M = 4.947). This variable had a range of 1 (never) to 8 (several times a day), and its distribution had a slight negative skew. The frequency
Table 1. Descriptive Statistics Variable
Mean/proportiona
SD
Range
Psychological distress T1/T2 Death anxiety T1/T2 Life satisfaction T1/T2 Self-esteem T1/T2 Sense of control T1/T2 Black (%) Female (%) Age Education Financial strain Married (%) Fair or poor health (%) Religious attendance Prayer Listening to religious music Listening to Gospel music
1.565/1.465b 2.042/1.994 2.891/2.830b 3.444/3.495b 3.020/2.988b 49 62 75.139 11.281 1.769 47 43 5.729 6.774 4.947 4.277
0.619/0.598 0.595/0.670 0.592/0.570 0.494/0.515 0.509/0.559 — — 6.670 3.484 0.993 — — 2.723 1.877 2.468 2.582
1–4 1–4 1–4 1–4 1–4 — — 65–101 1–25 1–4 — — 1–9 1–8 1–8 1–8
Notes: T1 = time 1; T2 = time 2. n = 1,024. a Means are reported for continuous measures and proportions for dichotomous measures. b Two-tailed t test indicates that the difference between these two means is statistically significant at p < .05.
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To test for race, gender, and SES differences in the relationship between listening to religious music and mental health, interaction terms were constructed for listening to religious (and gospel) music times: (1) black, (2) women, (3) education, and (4) financial strain. To reduce multicollinearity, all continuous variables were zero centered prior to constructing the interaction terms (Aiken & West, 1991), and all interaction terms were entered into the models one at a time. Variance Inflation Factor statistics indicated that multicollinearity was not a problem in the models.
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Bivariate Correlations Table 2 shows bivariate correlations for key dependent and independent variables. The correlations between baseline and follow-up levels of the dependent variables were .265 for psychological distress, .256 for death anxiety, .290 for life satisfaction, .193 for self-esteem, and .197 for a sense of control (all are statistically significant at p < .001 or less). The correlations between the frequency of listening to religious music and four of the five mental health variables (death anxiety, life satisfaction, self-esteem, and sense of control) were salutary and statistically significant, but relatively weak, at both waves; correlations ranged from .076 to .171 in magnitude. The correlations between listening to religious music and the remaining mental health outcome—psychological distress—measured at baseline and at follow-up were negligible and not statistically significant. The findings for gospel music were similar with
one exception: this variable was associated with psychological distress as well, especially at Wave 2. Overall, these bivariate patterns suggested that listening to religious and/ or gospel music had a statistically significant, yet weak, relationship with several different aspects of mental health in late life.
Regression Analyses Table 3 shows OLS parameter estimates from the regression of follow-up (Wave 2) mental health on baseline (Wave 1) mental health, covariates, and the frequency of listening to religious music. These models tested H1, which stated that listening to religious music would be associated with decreases in psychological distress and death anxiety and increases in life satisfaction, self-esteem, and a sense of control among older U.S. adults. Findings provided support for this hypothesis. The frequency of listening to religious music was inversely associated with levels of death anxiety at Wave 2 (b = −.035; p < .001) controlling for death anxiety at baseline. This means that listening to religious music was associated with a decline in death anxiety across the two waves of data. The frequency of listening to religious music was also associated with increases in life satisfaction (b = .019; p < .05), self-esteem (b = .015; p < .05), and a sense of control (b = .021; p < .01). It was not associated with psychological distress, however. The literature suggests that religious music is central in the lives of African Americans, so the analyses were conducted separately for blacks and whites. Contrary to H2, no significant differences were found between these two groups in the relationship between the frequency of listening to religious music and mental health. Similarly, there was no evidence of meaningful gender differences in these patterns, so H3 was not supported. Finally, the effects of
Table 2. Bivariate Correlations
1 2 3 4 5 6 7 8 9 10 11 12
1
2
3
4
5
6
7
8
9
10
11
12
1.000*** 0.265*** 0.131*** 0.085*** −0.298*** −0.106*** −0.186*** −0.132*** −0.348*** −0.115*** 0.015 ns 0.025+
1.000*** 0.099*** 0.185*** −0.141*** −0.276*** −0.103*** −0.205*** −0.134*** −0.202*** 0.022 ns 0.042**
1.000*** 0.256*** −0.158*** −0.127*** −0.296*** −0.113*** −0.137*** −0.027+ −0.117*** −0.071***
1.000*** −0.096*** −0.249*** −0.077*** −0.257*** −0.034** −0.155*** −0.024+ −0.043**
1.000*** 0.290*** 0.343*** 0.140*** 0.437*** 0.157*** 0.137*** 0.091***
1.000*** 0.124*** 0.377*** 0.122*** 0.377*** 0.171*** 0.184***
1.000*** 0.193*** 0.355*** 0.160*** 0.091*** 0.066***
1.000*** 0.137*** 0.406*** 0.119*** 0.159***
1.000*** 0.197*** 1.000*** 0.076*** 0.119*** 1.000*** 0.073*** 0.139*** 0.742*** 1.000***
Notes: 1 = psychological distress T2; 2 = psychological distress T1; 3 = death anxiety T2; 4 = death anxiety T1; 5 = life satisfaction T2; 6 = life satisfaction T1; 7 = self-esteem T2; 8 = self-esteem T1; 9 = sense of control T2; 10 = sense of control T1; 11 = listening to religious music; 12 = listening to Gospel music. n = 1,024; ns = not statistically significant at p < .05. ***p < .001; **p < .01; *p < .05; +p < .10.
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of listening to gospel music was slightly lower, averaging a few times a month (M = 4.277), and it had a similar distribution to religious music. Ancillary analyses (not shown) revealed that listening to religious music was more common among blacks than whites (M = 6.201 and 3.920, respectively), women compared with men (M = 5.215 and 4.643, respectively), individuals with a below average level of education compared with their better-educated counterparts (M = 5.663 and 4.580, respectively), and individuals who experienced above average levels of financial hardship compared with those who experienced below average levels (M = 5.631 and 4.547, respectively). All differences were statistically significant at p < .05 or less. Differences in the frequency of listening to gospel music by race, gender, and SES were similar to the patterns reported for listening to religious music in general.
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Table 3. OLS Parameter Estimates (Standard Errors in Parentheses) From the Regression of Follow-Up (Wave 2) Mental Health Variables on Baseline (Wave 1) Mental Health Variables, Covariates, and Frequency of Listening to Religious Music Death anxiety
Life satisfaction
1.072 (0.078)*** 0.209*** (0.033) −0.069 (0.044) 0.090* (0.040) 0.005+ (0.003) −0.013* (0.006) 0.041* (0.021) 0.034 (0.040) 0.114*** (0.039) −0.014+ (0.008) 0.011 (0.012) 0.000 (0.009) 0.101
1.613 (0.098)*** 2.004*** (0.105) 0.267*** (0.035) 0.225*** (0.031) 0.011 (0.050) 0.070+ (0.041) −0.005 (0.045) 0.042 (0.038) −0.010*** (0.003) −0.004 (0.003) −0.022 (0.007) 0.008 (0.006) 0.021 (0.023) −0.042* (0.019) −0.011 (0.044) 0.092** (0.037) 0.057 (0.043) −0.111*** (0.037) 0.006 (0.009) 0.008 (0.007) −0.022+ (0.013) 0.008 (0.011) −0.035*** (0.010) 0.019* (0.008) 0.106 0.116
Self-esteem
Sense of control
2.822*** (0.124) 0.168*** (0.033) 0.007 (0.039) 0.023 (0.035) −0.004+ (0.003) 0.008 (0.005) −0.041* (0.018) 0.032 (0.035) −0.051 (0.034) 0.000 (0.007) 0.019+ (0.011) 0.015* (0.007) 0.053
2.345*** (0.123) 0.186*** (0.036) −0.047 (0.042) −0.035 (0.038) −0.007** (0.003) 0.004 (0.006) −0.040* (0.019) 0.039 (0.037) −0.043 (0.037) 0.020** (0.007) −0.011 (0.012) 0.021** (0.008) 0.057
Notes: n = 1,024. ***p < .001; **p < .01; *p < .05; +p < .10.
Table 4. OLS Parameter Estimates (Standard Errors in Parentheses) From the Regression of Follow-Up (Wave 2) Mental Health Variables on Baseline (Wave 1) Mental Health Variables, Covariates, and Frequency of Listening to Gospel Music
Intercept Mental health variable T1 Black Female Age Education Financial strain Married Fair or poor health Religious attendance Prayer Listening to Gospel music Adjusted R2
Psychological distress
Death anxiety
Life satisfaction
Self-esteem
Sense of control
1.063*** (0.074) 0.209*** (0.032) −0.080 (0.046) 0.090* (0.040) 0.005+ (0.003) −0.015** (0.006) 0.036+ (0.020) 0.032 (0.039) 0.112*** (0.039) −0.015* (0.008) 0.011 (0.011) 0.004 (0.009) 0.096
1.556*** (0.094) 0.258*** (0.034) 0.001 (0.052) −0.005 (0.045) −0.011*** (0.003) −0.022*** (0.007) 0.019 (0.023) −0.014 (0.044) 0.057 (0.043) 0.004 (0.009) −0.029* (0.013) −0.022* (0.010) 0.089
2.057*** (0.102) 0.231*** (0.031) 0.093+ (0.044) 0.042 (0.038) −0.004 (0.003) 0.007 (0.006) −0.042* (0.019) 0.095** (0.037) −0.108*** (0.037) 0.008 (0.007) 0.015 (0.011) 0.003 (0.008) 0.110
2.863*** (0.121) 0.167*** (0.033) 0.016 (0.040) 0.022 (0.035) −0.004+ (0.003) 0.008 (0.005) −0.042* (0.018) 0.033 (0.035) −0.050 (0.034) 0.000 (0.007) 0.024+ (0.010) 0.008 (0.007) 0.053
2.362*** (0.121) 0.186*** (0.036) −0.058 (0.044) −0.034 (0.038) −0.007** (0.003) 0.005 (0.006) −0.043* (0.019) 0.039 (0.037) −0.043 (0.037) 0.019** (0.007) −0.011 (0.011) 0.021** (0.009) 0.068
Notes: n = 1,024. ***p < .001; **p < .01; *p < .05; +p < .10.
listening to religious music were examined across levels of SES. Contrary to H4, findings did not reveal any differences in the relationship between religious music and mental health by education or financial hardship. Overall, the results suggested that the listening to religious music functioned in broadly similar ways for blacks and whites, women and men, and individuals with different levels of SES. Finally, the data also contained a measure of the frequency of listening to gospel music (a more specific type of religious music), and the analyses described earlier were conducted using this measure as well. The results for this variable (shown in Table 4) revealed significant relationships between this variable and two of the five mental health outcomes examined here: death anxiety (b = −.022; p < .05) and a sense of control (b = .021; p < .01). Once
again, none of these patterns was found to vary by race, gender, or SES.
Discussion There is growing interest in the connection between religion and mental health (Smith et al., 2003). Scholars have linked many different facets of religious life—for example, organizational involvement, prayer, belief in an afterlife, religious coping, congregational support, and attachments to God, among others—with mental health (Bradshaw et al., 2010; Krause, 2008; Pargament, 1997). This study has augmented that list to include listening to religious music (Hamilton et al., 2013; Lipe, 2002). A large literature has linked listening to secular music with emotional and physiological processes (Chan et al., 2011; Erkkila et al., 2011; Hayes &
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Intercept Mental health variable T1 Black Female Age Education Financial strain Married Fair or poor health Religious attendance Prayer Listening to religious music Adjusted R2
Psychological distress
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studies have reported that religion is associated with mental health in part because it promotes social support networks, provides positive coping resources, offers messages of hope and optimism, and allows individuals to develop close intimate relationships with a divine other. Listening to religious music also appears to matter for mental health, either by facilitating one or more of these well-established mechanisms or by conferring additional benefits through other (e.g., physiological) processes. Clarifying the underlying nature of the associations between listening to religious music and desirable mental health outcomes should be a priority for future research. This study is also characterized by several limitations. First, it is unclear how or whether the context in which one listens to religious music matters. The survey item asked how frequently individuals listened to religious music outside of worship services. Although this is useful for isolating the effects of religious music from those of service attendance and prayer, it cannot reveal whether listening to religious music is more helpful in certain circumstances (e.g., in a quiet room at home) than in others (e.g., in traffic or other stressful settings). Second, due to data limitations, it is not feasible to compare the effects of religious versus secular music on mental health. It is possible that persons who listen to religious music also enjoy other types of music and, thus, we cannot definitively establish that religious music carries distinctive benefits. Third, some degree of confounding could result due to the effects of singing or physical movement that may occur when some individuals listen to religious music. However, data limitations preclude exploration of this issue. Fourth, some mental health outcomes were examined using nonstandard measures, and it would be desirable to replicate these findings using additional measures of psychological well-being and psychopathology. Fifth, the focus on a single faith group (i.e., Christians) clearly limits the generalizability of the findings to other religious traditions, and future research should attempt to address this weakness. Sixth, the changing characteristics of the sample over time could have affected the results. The follow-up rate of 68% is relatively low and could have conceivably biased the findings, especially given that older participants and those with health problems were less likely to participate in the follow-up survey: 55.35% of the respondents who did not participate in the follow-up survey reported having fair or poor health (compared with good or excellent) at baseline compared with 37.63% for those who participated in both waves. These processes caused the sample to become more healthy over time (43.28% and 37.63% of the sample, respectively, reported fair or poor health at baseline and follow-up), which could have contributed to the improvements in psychological well-being observed in the data. To build on this study, future research should address the limitations outlined earlier. In addition, investigators might profitably examine the effects of listening to diverse types of religious music. It is not clear whether certain
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Minichiello, 2005; Krahe & Bieneck, 2012), and this work strengthens the basis for expecting that religious music may be associated with mental health. Our analysis of two waves of data from a nationwide survey of older U.S. adults showed that the frequency of listening to religious music at baseline was associated with mental health 3 years later at Wave 2, controlling for baseline mental health, religious service attendance, prayer, self-rated health, and sociodemographic variables. More specifically, listening to religious music was associated with modest, yet statistically significant, declines in death anxiety (effect size = 0.012) and increases in life satisfaction (effect size = 0.008), self-esteem (effect size = 0.005), and a sense of control (effect size = 0.010) across two waves of data that spanned a 3-year period. Listening to gospel music, a specific type of religious music, was associated with two mental health outcomes: death anxiety (effect size = 0.060) and a sense of control (effect size = 0.050). These effect sizes were small, but given that many individuals in later life are exposed to a variety of biological and social–environmental risk factors that undermine mental health (Blazer & Hybels, 2005), the fact that listening to religious or gospel music was associated with improvements in mental health (not simply with a slower rate of decline) is noteworthy. These findings were net of two other important aspects of religious life: service attendance and prayer. Also, the relationship between religious music and mental health did not vary for blacks versus whites, women and men, and low- versus high-SES individuals. The fact that the findings were stronger and more consistent across mental health outcomes for religious music in general suggests that, although some of the salutary effects of listening to religious music may reflect benefits associated with gospel music specifically, other types of religious music may also have implications for mental health. Gospel music is itself a very diverse music genre, ranging from bluegrass gospel to upbeat Black gospel and many other types as well. However, religious music is an even broader and more inclusive label, extending to Gregorian chanting, religious classical and chamber music, and numerous other types of musical expression. These findings contribute to the literature on religion and mental health in several ways. They indicate that the mental health consequences of religious activities are not simply about social interaction or connectedness; indeed, these patterns persisted with controls for individual-level variations in religious service attendance. The findings reported here point to the significance of private aspects of religious life that cannot simply be reduced to social integration. These findings are particularly important for this study population because many older adults experience illnesses or disabilities that prevent them from attending religious services or participating in congregational life on a regular basis. The findings reported here also underscore the fact that religion is a multifaceted phenomenon that affects mental health in a variety of ways. Numerous prior
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health-promoting effects (Szanton, Wenzel, Connolly, & Piferi, 2011). Listening to religious music may help promote feelings of calm, which subsequently enhance psychological well-being. Listening to religious music may serve as a form of “self-care” or “self-comforting” (Hamilton et al., 2013), which could be used profitably in a complementary fashion with more traditional forms of health care. To conclude, listening to religious music appears to be associated with declines in death anxiety and increases in life satisfaction, self-esteem, and a sense of control among older U.S. adults. These findings contribute to research showing the effects of listening to music on mental health, as well as a growing literature on the religion–mental health connection. Much work remains to be done in this area, and future research should seek to understand exactly how and why religious music is associated with mental health in later life.
Acknowledgments A previous version of this paper was presented at the 2012 Meeting of the Association for the Sociology of Religion, Denver, CO. The lead author would like to thank Baylor University for providing start-up funds that contributed to this research. The authors would like to thank Neal Krause and Interuniversity Consortium for Political and Social Research (http://www.icpsr.umich.edu) for providing access to the data used in this study.
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