The Protective Effects of Religiosity on Depression: A 2-Year Prospective Study

Abstract

Depression is a major concern in the United States, as more than 5% of the general population over 12 years old reports being depressed at any given time ( Pratt & Brody, 2008 ). The prevalence of depression becomes even more alarming at older ages as 20% of those 65 years and older report being depressed ( Hurst, Williams, King, & Viken, 2008 ; Paukert et al., 2008 ). Because depression is one of the most common mental health issues facing older adults ( Administration on Aging, 2012 ), the study of depression and its correlates has become a priority among scholars looking to improve the quality of life among this population ( Administration on Aging, 2012 ).

Although conflicting results have been reported (e.g., positive, negative, or no relationship), recent investigations suggest that involvement in religious activity may serve as a protective factor against depression ( Blay, Batista, Andreoli, & Gastal, 2008 ; Blazer, 2010 ; Hayward, Owen, Koenig, Steffens, & Payne, 2012 ; King et al., 2007 ; Koenig, 2007 , 2009 ; Law & Sbarra, 2009 ; Smith, McCullough, & Poll, 2003 ). These investigations also suggest that individuals who are more religious may not only be more likely to recover from certain ailments such as acute myocardial infarction ( Martin & Levy, 2006 ) and severe mental illness ( Webb, Charbonneau, McCann, & Gayle, 2011 ), but do so more quickly, while experiencing shorter hospitalization stays ( Contrada et al., 2004 ). Together, these findings suggest a potentially important avenue for preventing and/or promoting recovery from depression, especially given the large role that religion plays in the lives of most Americans, 90% of whom report believing in God or a universal spirit ( Gallup, 2013 ) and 90% of whom report engaging in prayer ( Hill et al., 2000 ).

The role that religion plays in people’s lives becomes more pronounced with age. One national survey, for example, found that nearly 70% of adults 50 years or older reported that religion is very important in their lives compared with 44% of adults under 30 years old ( Cohen & Koenig, 2003 ). Older adults also exhibit higher levels of religiosity or actual involvement in religious activities ( Boswell, Kahana, & Dilworth-Anderson, 2006 ). The fact that religiosity appears to increase with age coupled with the high prevalence of depression among older adults suggests the need to further study the effects of religious beliefs and activities on depression among the elderly.

The need to further study the effects of religiosity on depression is also suggested by current research. Most existing research in this area has been cross-sectional ( Blay et al., 2008 ; Branco, 2000 ; Lawler-Row & Elliott, 2009 ; Waddell & Jacobs-Lawson, 2010 ; Yohannes, Koenig, Baldwin, & Connolly, 2008 ). That which is longitudinal has focused on limited population subsets (e.g., African Americans elders and adolescents with psychiatric conditions) ( Dew et al., 2010 ; Ellison & Flannelly, 2009 ), local or regional populations ( Idler & Kasl, 1992 ; King et al., 2007 ; Koenig et al., 1997 ; Koenig, George, & Peterson, 1998 ; Sun et al., 2012 ), and non-U.S. samples (e.g., Australian, Lebanese, Israeli, European elders, or Brazilian) ( Braam et al., 2001 ; Chaaya, Sibai, Fayad, & El-Roueiheb, 2007 ; Iecovich, 2001 ; Law & Sbarra, 2009 ; Payman, George, & Ryburn, 2008 ). Sample sizes also tend to be small and focus exclusively on, for example, the effects of religiosity on depression recovery, rather than both depression onset and recovery ( Bosworth, Park, McQuoid, Hays, & Steffens, 2003 ; Hayward et al., 2012 ; Koenig et al., 1998 ). There is a lack of consistency in measurement as well, with one or more religiosity measures tending to be employed operationalizing such concepts as organizational religiosity, nonorganizational religiosity, intrinsic religiosity, religious salience, religious affiliation, religious orthodoxy, and religious coping, though indicators of the former three domains are most commonly used ( Blay et al., 2008 ; Bosworth et al., 2003 ; Braam, Beekman, Deeg, Smit, & Tilburh, 1997 ; Braam et al., 2004 ; Branco, 2000 ; Hayward et al., 2012 ; Idler & Kasl, 1992 ; King et al., 2007 ; Koenig et al., 1997 , 1998 ; Levin, 2010 ; Schnittker, 2001 ; Sun et al., 2012 ).

The primary goals of this study are to assess depression levels both at baseline and 2 years later, in order to determine (a) whether religiosity protects against depression and (b) whether religiosity aids in the recovery from depression. Shortcomings in extant research are addressed in several ways. First, we use a larger, more representative sample than the previous work, focusing expressly on older adults (residing in the United States), and employ a longitudinal perspective. Second, we employ a comprehensive set of religiosity indicators, including organizational, nonorganizational, and intrinsic measures, as well as religious salience, affiliation, and presence of both friends and relatives at one’s place of worship.

Religiosity, Depression, and Older Adults

The biopsychosocial diathesis-stress model of depression (BPDS) posits that there are certain interconnected biological, psychological, and social factors that can affect an individual’s predisposition to depression ( Schotte, Bossche, Doncker, Claes, & Cosyns, 2006 ; Stein, 2005 ). These include risk factors that can serve both as potential precursors of depression and potential protective factors that can act as buffers against depression. Some individuals are more vulnerable to depression due to biological factors (e.g., age and gender), somatic factors (e.g., health status, chronic conditions, disability, or recent medical setbacks), psychological factors (e.g., mental illness and serious alcoholic use), and social influences (e.g., marital status, education, income, social support, volunteerism, and adverse life events). In this study, religiosity is conceptualized as a protective factor, which may help buffer against one’s total vulnerability for depression.

Religiosity typically refers not only to a belief in a higher entity or something greater than oneself but also formal involvement in organized religious activities and specific, measurable acts such as prayer, meditation, service attendance, religious readings, and affiliation with a particular religion or place of worship ( Hill et al., 2000 ; Iecovich, 2001 ; Yohannes et al., 2008 ). A key characteristic of religion is that it is organized in a hierarchical fashion with an identified authority figure such as a priest, pastor, or rabbi presiding. Although religion refers to someone’s belief system, religiosity is the actual application of such beliefs in daily life.

The literature distinguishes between three general types of religiosity: organizational, nonorganizational, and intrinsic. Organizational religiosity typically involves public or group activities and is most commonly measured by one’s religious service attendance ( Koenig et al., 1998 ; Sun et al., 2012 ). Nonorganizational religiosity, by contrast, is more private and typically occurs on a person’s own time, alone, encompassing activities such as reading religious texts, praying, and/or meditating ( Koenig et al., 1998 ; Sun et al., 2012 ). Intrinsic religiosity is concerned with individuals’ subjective meaning of religiosity and how religious beliefs affect everyday life ( Sun et al., 2012 ). Studies have shown that as individuals age, they are more likely to engage in nonorganizational activities as opposed to organizational modes of religious expression ( Yohannes et al., 2008 ), possibly shifting to more private religious activities, perhaps due to physical decline, rather than giving up on religious involvement altogether.

Nearly 75% of older people who suffer from depression or anxiety partake in some kind of religious activity at least monthly ( Paukert et al., 2009 ). A meta-analysis of 147 studies found higher religiosity to be associated with fewer depressive symptoms or indicators in more than three quarters of the studies analyzed ( Smith et al., 2003 ). Furthermore, individuals who regularly attend religious services display lower rates of depression when compared with individuals who either do not attend services or do attend services but on a more sporadic basis ( Blazer, 2010 ; Braam et al., 2004 ; Koenig et al., 1997 ). In a prospective study focusing on African Americans over the age of 55, it was found that individuals who received guidance from their religion on a regular basis were less likely to suffer from major depression 3–4 years later ( Ellison & Flannelly, 2009 ).

Extant research also demonstrates that religious involvement may benefit clinically depressed individuals ( Koenig et al., 1998 ; Murphy & Fitchett, 2009 ). Depressive symptoms have been shown to decrease across time in persons engaged in organizational religiosity ( Braam et al., 2004 ; Koenig, 2007 ; Law & Sbarra, 2009 ; Levin, 2010 ; Smith et al., 2003 ). However, mixed results abound regarding nonorganizational modes of religious involvement. For instance, one cross-sectional study found nonorganizational religiosity unrelated to depression ( Koenig et al., 1997 ), whereas another found an inverse relationship between nonorganizational religiosity and depression cross-sectionally, but a U-shaped association longitudinally ( King et al., 2007 ). Yet another study found nonorganizational religiosity to be associated with lower depression severity after 3 months ( Hayward et al., 2012 ). Findings around intrinsic religiosity are also inconsistent. Parker and coworkers (2003) found no relationship between intrinsic religiosity and depression, King and coworkers (2007) a positive relationship, and Koenig and coworkers (1998) quicker remission from depression.

Evidence suggests that the impact of religiosity on depression is stronger among women who also tend to be more active participants in both organizational and nonorganizational religious activities than men, including, for example, religious affiliation and private prayer ( Wink & Dillon, 2002 ; Yohannes et al., 2008 ). This tendency is reflected in a 2002 Health and Retirement Study (HRS) of older adults 60 years or older, which found higher ratings of religious importance to be a protective factor against depression in women—but not men ( Waddell & Jacobs-Lawson, 2010 ).

Based on previous research and according to the BPDS model of depression, this study hypothesizes that (a) higher religiosity will be associated with a lower likelihood of depression 2 years later among older adults without depression at baseline (i.e., religiosity will protect against depression onset) and (b) higher religiosity will be associated with a lower likelihood of depression 2 years later for respondents depressed at baseline (i.e., religiosity will aid in depression recovery).

Methods

Data Source

The sample in this study was drawn from the 2006 and 2008 waves of the HRS; the goal was to model depression in 2008 based on respondent characteristics in 2006. The HRS is sponsored by the National Institute on Aging (grant number NIA U01AG009740) and is conducted by the University of Michigan ( Health and Retirement Study, 2006 /2008). The HRS began collecting data in 1992 and continues to do so every 2 years. The HRS is a nationally representative study that contains rich information on more than 22,000 community-dwelling older adults aged 50 or older, with respect to respondent health, functional status, cognition, living arrangements, retirement, religious affiliation, and involvement in assorted activities.

Sample

The sample utilized in this study includes the subset of HRS respondents who completed the 2006 Leave-Behind Questionnaire ( n = 7,732). The rationale for utilizing the Leave-Behind Questionnaire is that it contains much more comprehensive measures of religiosity than the basic HRS survey. In all, 944, or 12% of respondents, were missing information on at least one HRS item. Thus, for purposes of our analyses, we employed multiple imputation of missing data to fill in the missing values. Twenty imputations were conducted and pooled results were used in the analyses reported.

Measurement

Dependent Variable (Depression)

Depression status (in 2008) is the outcome variable in the present study. Depression is assessed with Center for Epidemiological Studies Depression scale (CESD-8). The presence of three or more symptoms, out of eight, indicates a higher likelihood of being clinically depressed ( Steffick, 2000 ). Therefore, respondents reporting three or more depressive symptoms were coded 1 = depressed; those with zero, one, or two symptoms as 0 = not depressed.

Independent Variables (Religiosity)

Five religiosity questions are asked in the basic HRS. Religious affiliation was self-reported as Protestant, Catholic, Jewish, or none/other religion . Respondents were asked about organizational religiosity, via the frequency of attendance at religious services : high (more than once a week or once a week), moderate (two to three times a month), and low/none (one or more times a year or not at all). Additionally, respondents were asked about the presence of both friends and relatives in one’s congregation (yes or no). Lastly, respondents were asked to rate the importance of religiosity : very, somewhat, or not important. Each of these items was coded as a series of dichotomous variables.

The Leave-Behind Questionnaire includes two additional measures of religiosity. The first is an index of religiosity, an intrinsic measure, composed of four items (α = .92)— believe God watches over me, events unfold according to a divine/greater plan, carry religious beliefs into all dealings in life, find strength and comfort in religion . Possible scores range from 1 ( strongly disagree ) to 6 ( strongly agree ) (averaged across the four items) where higher scores indicate higher religiosity levels. The second Leave-Behind Questionnaire item measured the frequency of prayer in private contexts, a nonorganizational measure. The scores (1–8) on this item were reverse coded so that higher scores denote higher frequency of private prayer.

The potential for multicollinearity was examined in several ways. Neither variance inflation factors (all < 4.5) nor correlations (all < 0.62) among the seven religiosity measures revealed problematic multicollinearity. Moreover, each of the seven religiosity variables was entered one by one into the model and as a block, both with and without covariates, both for the depressed and nondepressed samples. Results on the religiosity variables largely remained consistent across these various specifications. The final model therefore includes all seven religiosity variables described previously along with covariates.

Covariates

This study controls for biological, somatic, psychological, and social factors that have been found to be associated with depression. Prior research suggests that older adults, females, and non-Hispanic Blacks exhibit higher rates of depression compared with their younger, male, and white counterparts ( Law & Sbarra, 2009 ; Pratt & Brody, 2008 ). Age is measured as a continuous variable (number of years); gender as a dichotomous variable, with female = 1 and male = 0; and race/ethnicity as a series of dichotomous variables for white, black, Hispanic, and other.

In addition, somatic or health conditions may be related to depression status ( Blazer, 2010 ; Centers for Disease Control and Prevention, 2011a ; Koenig, 1999 ; Lo et al., 2010 ; Schotte et al., 2006 ). At baseline, respondents were asked whether they had ever been diagnosed with each of seven chronic ailments: high blood pressure, diabetes, cancer, lung disease, heart conditions, stroke, and arthritis. The number of chronic conditions was summed (0–7) with a higher count indicating greater comorbidity. Respondents were also asked whether they had recently experienced each of three somatic life events in the last two years (since baseline): stroke, heart attack, and/or cancer. It is important to account for the onset of illnesses such as these, as recently experiencing a negative event has been found to be associated with depression ( Schnittker, 2001 ). A count (0–3) of somatic events was developed, with a higher number indicating greater comorbidity. Self-reported health status was measured using a series of dichotomous indicator variables: excellent, very good, good, fair, or poor. Functional limitations were measured using counts of both instrumental activities of daily living (IADLs) (0–6) and basic activities of daily living (ADLs) (0–5).

Alcohol abuse appears to be associated with depression ( Blay et al., 2008 ; Braam et al., 2004 ; Centers for Disease Control and Prevention, 2011a ; Idler & Kasl, 1992 ; Rodriguez, Schonfeld, King-Kallimanis, & Amber, 2010 ). Consistent with previous research ( Satre, Gordon, & Weisner, 2007 ), respondents were identified as a serious drinker, or abuser of alcohol, if they were (a) a woman that consumes more than two drinks per occasion or (b) a man that consumes more than three drinks per occasion. Also included is a dichotomous variable indicating whether or not an individual had ever been diagnosed with any emotional or psychiatric condition(s ) ( Koenig et al., 1998 ). Both variables have been shown to increase the risk for, or coexist with, depression ( Aina & Suman, 2006 ; Centers for Disease Control and Prevention, 2011b ) and have been used as covariates in similar studies.

Social factors have the potential to predispose individuals toward depression ( Schotte et al., 2006 ). The influences of social and economic considerations are reflected, in part, in sociodemographic variables, including marital status (married, divorced/separated, widowed, or never married), education (in years), and household income (in quartile earnings). Social considerations are also reflected, in part, in living alone , volunteerism , and having family and friends nearby . Certain recent adverse life events such as “serious losses, threatening occurrences, or difficulties in life” are also predictive of depression ( Schnittker, 2001 ; Schotte et al., 2006 , p. 314). These include experiencing divorce/separation, death of a spouse/partner, a nursing home stay, and residential move in the last 2 years. A count has been created (0–4), where a higher number indicates experiencing more recent adverse social events. Lastly, whether respondents were living in a nursing home as opposed to a community setting at the time of the survey was recorded, in addition to whether survey responses were provided by a proxy or not.

Analytical Plan

Basic descriptive statistics are reported, followed by bivariate analyses comparing the baseline characteristics of the depressed and nondepressed samples ( Table 1 ). Results from multivariate analyses are presented next, utilizing logistic regression to model the relationship between depression and religiosity, controlling for other baseline factors. Two logistic regressions models were employed: one with baseline depressed respondents and the second with baseline nondepressed respondents ( Table 2 ).

Results

Table 1 reports descriptive statistics for the entire sample, as well as differentiated by depression status in 2006. Depressed and nondepressed samples had similar religious affiliations (χ ² = 3.94 (3), p > .05). At 45% and 37%, respectively, high frequency of religious service attendance was more likely to be reported by nondepressed than depressed respondents, whereas depressed respondents were more likely to report low or no service attendance than their nondepressed counterparts (51% vs. 43%) (χ ² = 43.19 (2), p < .001). A higher proportion of nondepressed respondents (59%) reported having friends at their congregation than depressed respondents (50%) (χ ² = 44.42 (1), p < .001); approximately one quarter of each group reported sharing their congregation with family (χ ² = 0.01 (1), p > .05). There was a small but significant difference assigned to the importance of religion, with depressed respondents being more likely to report “very important” (70% vs. 68%) and depressed respondents being less likely to report “not important” (9% vs. 12%) (χ ² = 10.60 (2), p < .01). No significant difference could be discerned between the two groups on the religiosity index ( t = −1.26, p > .05), but there was a significant difference in regard to the frequency of private prayer ( t = −3.17, p < .01) with depressed respondents reporting higher frequency (6.25 vs. 6.06 [out of 8]).

Significant differences could also be discerned with respect to all covariates but high alcohol use (χ ² = 1.74 (1), p > .05), social adverse life events ( r = .45, p > .05), the presence of relatives living nearby (χ ² = 0.94 (1), p > .05), and having a proxy respondent (χ ² = 1.88 (1), p > .05). Thus, nondepressed respondents were more likely than depressed respondents to be younger ( r = −3.19, p < .001), male (χ ² = 59.96, p < .001), non-Hispanic white (χ ² = 33.84, p < .001), in excellent very good/good health (χ ² = 1174.17, (4), p < .001), married (χ ² = 216.04, p < .001), have higher education ( t = 13.53, p < .001), have higher income (χ ² = 347.93 (3), p < .001), volunteer (χ ² = 172.90, p < .001), and have friends living nearby (χ ² = 11.80, p < .001). By contrast, depressed respondents were more likely than nondepressed respondents to be chronically ill ( t = −18.46, p < .001), IADL ( t = −15.01, p < .001) and ADL ( t = −19.48, p < .001) impaired, suffer from adverse somatic life events ( t = −2.73, p < .01), have psychological issues (χ ² = 558.35, p < .001), live alone (χ ² = 133.54 (1), p < .001), or live in a nursing home (χ ² = 18.96 (1), p < .001).

Two main logistic regression models were estimated. The first model is composed of individuals who were depressed at baseline ( n = 1,992) ( Table 2 ). Two religiosity variables were significant. The odds of being depressed at follow-up were two times higher among depressed respondents with a Jewish affiliation (odds ratio [OR] = 2.05, p < .05) but lower for those with more frequent engagement in private prayer (OR = 0.93, p < .05).

The first model also indicates that depressed individuals who were in excellent health (OR = 0.43, p < .01), widowed (OR = 0.72, p < .05), had higher household income (OR = 0.73, p < .05; OR = 0.66, p < .05), or who lived in a nursing home (OR = 0.41, p < .05) had a decreased likelihood of being depressed at follow-up. In contrast, depressed persons who reported more somatic life events (OR = 1.57, p < .01), had psychological issues (OR = 1.61, p < .001), reported more social adverse life events (OR = 1.46, p < .05), and lived closer to their relatives (OR = 1.31, p < .05) were more likely to remain depressed 2 years later.

The second model is composed of individuals who were not depressed at baseline ( n = 5,740) ( Table 2 ). Service attendance was the only religiosity variable to prove significant. In particular, nondepressed respondents with high service attendance were 35% less likely to be depressed at follow-up (OR = 0.65, p < .01), and respondents with low/no service attendance were 25% less likely to become depressed (OR = 0.75, p < .05), in comparison to those with moderate service attendance. Other factors associated with increased likelihood of depression onset included female gender (OR = 1.44, p < .001), chronic illness (OR = 1.09, p < .05), fair or poor health (OR = 1.77, OR = 2.69, both p < .001), psychological issues (OR = 1.93, p < .001), adverse social events (OR = 1.42, p < .01), living alone (OR = 1.35, p < .05), and having relatives live nearby (OR = 1.23, p < .05). By contrast, factors that appeared to guard against depression onset included reporting excellent or very good health (OR = 0.54, p < .001; OR = 0.72, p < .01), higher income (OR = 0.69, p < .05), and having a proxy respondent (OR = 0.24, p < .001).

Discussion

This study sought to understand whether religiosity (a) protects against future depression and (b) plays a role in depression recovery, among older adults. Consistent with prior research ( Blazer, 2010 ; Koenig, 2007 ; Smith et al., 2003 ), results provide evidence supporting both of these expectations, though the specific aspect of religiosity found to protect against depression (frequent service attendance) was different from the component found to aid in depression recovery (private prayer frequency). Relative to those with moderate service attendance, individuals who were not depressed at baseline (in 2006) were less likely to be depressed 2 years later if they frequently attended religious services. It was expected that high service attendance would protect against depression, perhaps due to the availability, promotion, or benefits of social support found in one’s place of worship. In particular, the protective pathway stemming from service attendance may derive from the comparatively higher levels of social capital resulting from engagement in public modes of behavior, specifically the interpersonal relationships formed and sustained by active participation in a religious congregation. The presence of more social connections, in turn, may reduce the likelihood of isolation and loneliness, two factors associated with depression.

Counterintuitively, individuals with low service attendance who were not depressed at baseline were also less likely to be depressed 2 years later relative to those with moderate service attendance. It is possible that persons with low or no service attendance may be less likely to be depressed at follow-up because they are more likely to engage in other, less public forms of religiosity that, in turn, provide protective benefits from depression and other ailments. That this may be the case is suggested by the moderate, significant inverse correlation between private prayer frequency and level of service attendance ( r = −.496, p < .05). Thus, whereas the high service attendance group may be disproportionately devoted to organizational forms of religiosity, the low service attendance group may be disproportionately devoted to nonorganizational forms. In contrast, the moderate service attendance group may not be disproportionately devoted to either form of religious behavior and, as such, may be less likely to experience the benefits that derive from each.

Consistent with expectations, persons who started out depressed at baseline were less likely to be depressed 2 years later if they more frequently engaged in private prayer. This finding suggests that persons who become depressed may turn to their faith for support and as a means of coping from adverse life events—financial, health, social, or otherwise. Subsequent engagement in private prayer may serve, in part, to cultivate hope for the future, potentially activating cognitive resources that eventually counter depression.

Interestingly, Jewish respondents were much more likely to remain depressed at follow-up than other respondents. One possible explanation for this finding could be the long-term, negative implications that belonging to a religious minority has on mental health ( Berger, 1977 ). This may be particularly important for the population surveyed because anti-Semitism was much more visible and prevalent during our respondents’ formative years than it is today. Another possible explanation could be that Jewish elders may not benefit in the same way from religious involvement as members of other religious affiliations. Take Christian doctrine, for example, which emphasizes the afterlife or Heaven at which point the body may be restored and a reunion takes place with long deceased loved ones ( Gillman, 2007 ). This belief can be great source of solace, hope, and comfort for those going through hard times (e.g., depression), which may, in turn, support coping and recovery. This is in contrast to Jewish doctrine, which in downplaying the hereafter in favor of the “here and now,” may not provide the same level of solace, hope, and comfort ( Gillman, 2007 ).

One interesting yet surprising finding emerging from this study is that having relatives living nearby was associated with depression at follow-up among both the baseline depressed and nondepressed samples analyzed. It is plausible that there are certain unwanted expectations inherent when family members live closer—whether, for example, caring for a frail and disabled parent or other relative in need of long-term care or watching a young grandchild in need of after school care, that results in burdens and stresses that might not otherwise exist if family lived further away. Simply measuring proximity, moreover, does not account for the frequency or quality of the interactions that take place. For example, some relationships, even with relatives, may not be pursued no matter how convenient, if those relationships are not fulfilling.

There are several limitations worth noting. First, depression is measured using the CESD-8, a self-report tool, rather than using the clinical diagnosis of depression by a health or mental health professional. Although the latter may be the gold standard, the CESD-8 is a commonly used and accepted measure of depression in studies such as this one where clinical diagnosis was not possible (e.g., Steffick, 2000 ). Second, data from the CESD-8 were not utilized to develop a measure of depression based on a continuous count of depressive symptoms but instead used to place individuals into depressed or nondepressed categories based on the presence of three or more of the eight symptoms assessed. One implication is that potentially useful variation may have been missing. This “cutoff approach,” however, is typically employed in studies utilizing the CESD-8 ( Steffick, 2000 ). A third limitation is related to the length of the study. Given the episodic nature of depression, a 2-year longitudinal study may miss signs of depression occurring after the time period analyzed. Future research should extend the follow-up period studied over a longer period of time as additional waves of the HRS become available. Last, the Health and Retirement Study only includes measures of religiosity but not spirituality. Thus, this study is focused exclusively on the former but not the latter. This limitation is important to point out because extant research suggests that spirituality may be associated with lower rates of depression and mental illness as well ( Skarupski, Fitchett, Evans, & Mendes de Leon, 2010 ). Moreover, a growing body of research suggests that spirituality to be a unique construct, though related to religiosity ( Underwood & Teresi, 2002 ). Beyond this understanding experts hold differing views regarding the distinction between religiosity and spirituality, some maintaining that religiosity may be a part of spirituality, whereas others viewing spirituality as a part of religiosity ( Hill et al., 2000 ; MacKinlay, 2006 ).

Conclusion

Several implications for policy and practice follow from the results of this study. One is related to transportation availability and the provision of better access to places of worship so that older adults who are interested in religious services are able to attend and subsequently benefit from organizational, or public, forms of religiosity. Moreover, given the high prevalence of depression among older adults, clinicians should be cognizant of the benefits associated with both religious service attendance and involvement in private prayer, assess individuals’ religious needs and involvement, and determine whether their clients face any barriers to attending services or pursuing their faith if they so desire. Through these assessments, clinicians could help connect interested clients to such services within their communities or help them overcome any barriers they may be experiencing, hindering involvement private prayer. Care plans or therapy goals can be developed, which address these issues as well.

References

Author notes