J Relig Health DOI 10.1007/s10943-015-0033-6 ORIGINAL PAPER

Depressed Affect and Dimensions of Religiosity in Family Caregivers of Individuals with Dementia Laraine Winter1,2 • Helene J. Moriarty3,2 • Faith Atte3 Laura N. Gitlin4

•

Ó Springer Science+Business Media New York 2015

Abstract Religiosity and mood have long been recognized as associated, but some patterns of associations suggest complex relationships. Using a multidimensional measure of religiosity, we explored the possibility that dimensions of religiosity may have (1) different strengths of association and (2) directions of association with depressed mood. We measured five dimensions of religiosity in 1227 family caregivers of persons with dementia, testing associations of each dimension to caregivers’ depressive symptoms. In zero-order associations, higher scores on each religiosity dimension were associated with lower depression. Yet in hierarchical multiple regressions models, adjusting for other religiosity dimensions, different dimensions showed either no independent association, an independent association, or an inverse association with depressed mood. Frequency of prayer reversed directions of association—showing higher depression in caregivers who prayed more. Findings underscore the complex and sometimes bidirectional association between depressed mood and religiosity and argue for recognition of distinct dimensions of religiosity. Keywords

Depression
Religiosity
Dementia caregiving

& Laraine Winter [email protected] 1

Philadelphia Research and Education Foundation, Department of Veterans Affairs Medical Center, Philadelphia VA Medical Center, Philadelphia, PA, USA

2

Nursing Service, Department of Veterans Affairs Medical Center, Philadelphia, PA, USA

3

Villanova University College of Nursing, Villanova, PA, USA

4

The Center for Innovative Care in Aging, School of Nursing, Johns Hopkins University, Baltimore, MD, USA

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Introduction Evidence for an association between religiosity and psychological well-being has been compelling, usually indicating that more religious people tend to be less depressed and have higher positive scores on other aspects of psychological well-being (Bonelli and Koenig 2013; Braam et al. 1997; Hebert et al. 2007; Koenig 2007, 2009; Koenig et al. 2004; Moreira-Almeida et al. 2006; Richardson et al. 2012; Ronneberg et al. 2014; Strawbridge et al. 1998; Sun et al. 2012; Taylor et al. 2013). Based on an assumption that religiosity leads to better psychological wellbeing, most studies examine religiosity as the predictor and mood (as well as other aspects of health) as the outcome. Such findings suggest that religiosity can serve as an effective coping mechanism, a source of strength and support, and a means of infusing difficult life situations with meaning and purpose, as research in a wide variety of populations has suggested (e.g., Kaye and Robinson 1994a, b; Koenig 2007; Smith et al. 2003; Wykle and Segal 1991). On the other hand, religiosity’s role as a coping strategy would suggest an inverse relationship with mood: Depressed mood may drive greater religiosity as a coping mechanism, leading to the prediction that more depressed people would score higher on religiosity measures. This would be consistent with research on religious coping, which posits that poor health motivates engagement in religious practices (Koenig et al. 1988). Ferraro and Kelley-Moore (2000) termed this phenomenon religious consolation. It would predict a negative association whereby worse mood would be associated with higher religiosity. Indeed, some research has documented associations between religious and higher depression (Herrera et al. 2009; Braam et al. 2007; Koenig, et al. 2014), and other studies have shown mixed results depending on which dimension of religiosity is measured (Braam et al. 2004: King et al. 2007; McCullough and Larson 1999). Both hypotheses about causal relationship between mood and religiosity are conceptually compelling, and both have empirical support. Yet they lead to opposite predictions about the direction of the association between religiosity and mood. These raise interesting and important questions about how and in what direction religiosity and mood are related and also about which aspects of religiosity may relate to mood. It has long been recognized that religiosity is a broad and complex construct, encompassing multiple cognitive, emotional, behavioral, and interpersonal dimensions (Fetzer Institute 1999; Hill and Hood 1999; e.g., organizational (e.g., services as a source of help/comfort) versus non-organization components (prayer et al. 1989; Strawbridge et al. 1998). Do only some aspects of religiosity account for the associations with psychological well-being? Exclusive reliance on global measures of religiosity may mask the precise mechanisms that link religiosity with depressive symptomatology (Hill and Pargament 2003), and failure to include multiple dimensions may account for the contradictory findings regarding religiosity and mood associations. The use of delineated measures of religious and spiritual experiences may capture distinct dimensions, to derive an understanding of how aspects of religiosity are associated with mood (Berrara et al. (1981); Blazer 2007). These two issues—multidimensional and direction of causality— should therefore be considered simultaneously because different dimensions of religiosity may have differential and even opposite associations with depressed mood. Prayer is a good example of how individual dimensions may predict different directions of causality and have different types of associations with depressed mood. Pain, stress, and impairment may motivate more frequent prayer as a coping resource (McCullough 1995). Consistent with this, Braam et al. (2007) found an inverse association among those not religiously affiliated, showing frequency of prayer to be associated with higher levels of depressive symptoms and no association with depressive symptoms in their total sample.

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Strawbridge et al. (1998) found that both organizational and non-organizational religiosity seemed to exacerbate depression with different type of life stressors. In a cross-sectional survey of African-American older adults, Gitlin et al. (2011) found that depressed individuals reported using prayer and faith more often than non-depressed. Braam et al. (2007) reported that prayer was associated with more depressive symptoms among those not religiously affiliated. Non-organization or intrinsic religiosity has been associated with worse mental health (Herrera et al. 2009) and depressive symptoms (King et al. 2007). Thus, frequency of prayer has a complicated record as an associate of mood. Such contradictory findings indicate the need for more careful investigation of the topic (Blazer 2007) (Fig. 1). Associations between religiosity and mood have been documented in caregiving research. Caring for a relative with dementia is a well-documented stressor, posing threats to both mental and physical health (e.g., Haley et al. 1995; Ory et al. 1999; Pinquart and Sorensen 2003; Schulz et al. 1995). Approximately 11 million Americans care for a family member with dementia, who number approximately 5.2 million (Alzheimer’s Association of America 2014). A sense of relationship with God, a reliance on faith, and the use of prayer provide spiritual guidance for many caregivers (Paun 2004; Kaye and Robinson 1994a, b; Stuckey 2001; Wykle and Segal 1991), suggesting benefits of religiosity for caregiver mental health. Some dementia caregiving research has explored distinct dimensions of religiosity in relation to caregivers’ mental health. Herbert et al. (2007) found that frequency of church attendance, frequency of prayer, and importance of religion and spirituality were each associated with less depressive symptomatology in dementia caregivers. By contrast, LeBlanc et al. (2004) reported that greater self-perceived religiosity was associated with feelings of role overload and greater depressive symptomatology among caregivers with their own health problems.

Importance of religion

Services as source of comfort/help

Frequency of service attendance

Depressed Mood

Prayer as a source of comfort/help

Frequency of prayer

Fig. 1 Relationships among depressed mood and five dimensions of religiosity

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The present study extends research on religiosity and caregiver well-being by distinguishing several dimensions of religiosity and examining their associations with mood both individually and after adjusting for the other dimensions, to identify potentially distinct patterns of association. For example, a given dimension of religiosity may by itself be associated with depressed mood but make no independent contribution over and above other dimensions. Or it may be independently associated with mood over and above other dimensions’ contributions. It may also be inversely associated with mood when the other dimensions are controlled. The last possibility would be consistent with the religious consolation notion regarding prayer that depressed individuals pray more often than non-depressed. The present study, though sharing with other cross-sectional research limitations on inferences about cause and effect, examined of patterns of association within the same data set, to test seemingly contradictory findings about mood and religiosity from previous research. Dementia caregivers provide an ideal sample for examining these questions because of their well-documented high prevalence of depressed mood. Like Hebert and his associates (2007), we used the NIH REACH I data to examine associations between caregiver depressed mood and dimensions of religiosity but included two additional aspects of religiosity that Hebert and his associates excluded—prayer as source of help/comfort and services as source of help/comfort.

Method Sample and Procedure The present study used data from the (Resources for Enhancing Alzheimer’s Caregiver Health(REACH I) project, a multisite study of ADRD family caregivers sponsored by the Table 1 Sample characteristics Caregivers Mean (SD) Age

Care recipients Percentage

62.1 (13.6)

Mean (SD)

Percentage

79.3 (10.0)

Gender (% female)

81.5

55.7

Race (% White)

56.2

56.1

Years of education Less than HS grad

19.2

46.1

HS grad/GED

24.4

23.0

Some college or graduate

45.9

24.2

Postgraduate

10.4

6.8

Financial difficultya

2.2 (1.1)

Relationship to care recipient (% spouses)

– 48.0

Years caregiving

4.3 (4.2)

CES-D

15.4 (11.4)

ADL score

–

–

–

–

–

–

–

3.9 (2.5)

IADL score

–

–

7.3 (1.3)

# problem behaviors

–

–

10.2 (4.2)

a

–

–

‘‘How difficult is it for you to pay for the basics like food and medicine?’’ Of scale values from 1 (not at all) to 4 (extremely), scale value 2 indicates ‘‘some difficulty’’

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National Institute on Aging and the National Institute of Nursing Research that evaluated six innovative interventions to support caregivers. REACH was conducted in six US cities (Birmingham, AL; Boston, MA; Memphis, TN; Miami, FL; Palo Alto, CA; and Philadelphia, PA) and recruited 1228 family caregivers between 1997 and 2000 from a wide variety of sources (Wisniewski et al. 2003). Table 1 presents characteristics of both caregivers and care recipients. This sample has also been described by Hebert et al. (2007). We obtained informed consent from eligible participants using an approved Institutional Review Board consent form. The interview was conducted in caregivers’ home. The present study used REACH baseline data only. Among these dyads, 1227 had complete data for the variables included in the present analyses.

Measures Depressive Symptoms Depressive symptomatology was measured using the Center for Epidemiologic Studies Depression Scale (CES-D; Radloff 1977). This is a 20-item scale that assesses the frequency with which individuals experience depressive symptoms or feelings during the past week. The response format is 0 (rarely/none of the time) to 3 (most/almost all the time). Total scores range from 0 to 60, with higher scores indicating greater depressive symptomatology. CES-D score for the sample ranged from 0 to 56, with a mean score of 15.36 (SD = 11.40). Forty-one percent scored at or above the cutoff of 16, indicating the presence of depressive symptomatology for those individuals and a high proportion of individuals with depressed mood in this sample.

Religiosity/Spirituality The REACH investigators (Schulz et al. 2003) selected five items from previous scales and studies to represent important domains of religiosity and spirituality for use in the baseline interview battery: (1) How often do you attend religious services, meetings, and/or activities? Response options are on a 6-point scale ranging from ‘‘never’’ (1) to ‘‘nearly everyday’’ (6) (M = 3.48, SD = 1.61); (2) How often do you pray or meditate? Response options are on a 6-point scale ranging from ‘‘never’’ (1) to ‘‘nearly everyday’’ (6) (M = 5.40, SD = 1.35); (3) to what extent has participation in religious services, meetings, and/or activities been a source of help and comfort to you in providing care to your relative? Response options are on a 4-point scale ranging from ‘‘not at all’’ (1) to ‘‘a great deal’’ (4) (M = 2.85, SD = 1.14); (4) How important is your spirituality or religious faith to you? Response options are on a 4-point scale ranging from ‘‘very unimportant’’ (1) to ‘‘very important’’ (4) (M = 3.47, SD = .90); and (5) to what extent have prayer or meditation been a source of help and comfort to you in providing care to your relative? Response options are on a 4-point scale ranging from ‘‘not at all’’ (1) to ‘‘a great deal’’ (4) (M = 3.29, SD = .95). Because prayer as a source of help or comfort/services as a source of help/comfort were not asked of participants who had said they did not pray or attend services, we assigned the lowest possible value (1) to these variables for these participants, to avoid loss of data from subjects who did not attend services or pray. Failure to do this would have biased the sample by dropping subjects with the lowest religiosity.

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Social Support Three types of social support were assessed. (1) Social integration was measured using the 9-item Lubben Social Network Scale (LSNS; Lubben 1988). Mean scores ranged from 0 to 5, with a mean of 12.94 (SD = .88). Cronbach’s alpha for the sample was .76. (2) The 17-item Berrara et al. (1981) Inventory of Socially Supportive Behaviors (ISSB), which encompasses received support, tangible support, emotional support, information and satisfaction with support, was used to assess socially supportive behaviors. The mean score was 1.28 (SD = .59), with a range from 0 to 3. This scale was internally consistent (Cronbach’s alpha = .86). (3) Negative interactions were assessed using the 4-item Krause (1995) scale. These scores ranged from 0 to 3 and had a mean of .72 (SD = .75). Cronbach’s alpha was .82. For each scale, the mean score was used in the analyses.

Memory and Problem Behaviors The Revised Memory and Behavior Problems Checklist (RMBPC; Teri et al. 1992) was used to assess caregiver distress with care recipients’ memory and problem behaviors. The RMBPC consists of 24 items and asks caregivers whether the care recipient manifested any of the 24 behaviors (seven memory-related, eight care recipient mood, and nine disruptive) in the past week. Caregivers who responded ‘‘yes’’ to any of the problem behaviors also rate how bothered or upset they were by the behavior using a 5-point scale ranging from 0 (‘‘not at all’’) to 4 (‘‘extremely’’). Upset scores were summed across behaviors and a rating of 0 given to those behaviors that did not occur. Higher scores represented greater caregiver upset.

Financial Difficulty Caregivers rated how difficult they find it to pay for basic needs such as food and health care using a response scale from 1 (‘‘not at all difficult’’) to 4 (‘‘extremely difficult’’) (Schulz et al. 2003).

Relationship to Care recipient Caregiver–care recipient relationship was coded spouse or non-spouse. Overall, about half of caregivers were spouses, although this proportion varied by race (Table 1). Relationship was included in analyses because spouse caregivers tend to report greater depressive symptoms than non-spouse caregivers (e.g., George and Gwyther 1986).

Race Race was coded as White or non-White.

Years of Caregiver Education Caregiver’s years of education represented the number of years of education that the caregiver completed and ranged from 0 to 17 years (M = 13.01, SD = 2.31).

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Mini Mental Status Exam (MMSE) The Mini Mental Status Exam (MMSE; Folstein et al. 1975) was used to assess disease severity. The MMSE assesses the cognitive status of the care recipient. Scores range from 0 to 30. Lower scores are indicative of greater cognitive impairment.

Impairment in Activities of Daily Living Functional impairment was assessed using seven activities of daily living (ADL; Katz et al. 1963). For each item, caregivers rated whether the care recipient needed help (1) or did not need help (0). The ADL score therefore had a theoretical range from 0 to 7.

Data Analysis Selection of Covariates To identify covariates, we examined the association of CES-D score to a set of sociodemographic variables based on previous research showing significant associations with psychological well-being. These were caregiver age, gender, years of education, financial difficulty, relationship with the care recipient (spouse vs. non-spouse), years of caregiving, number of hours/day caregiving, social network, ISSB, negative interactions, and self-rated health; and care recipient’s age, gender, race and functional impairment with ADL and IADL, and number of problem behaviors at baseline. Their association with CES-D scores was tested using t tests or Pearson product-moment correlations, as appropriate.

Intercorrelations of Religiosity Items Associations among the five religiosity items were examined using Spearman’s rho.

Multiple Regression Analyses Five multiple regression models were conducted to evaluate each of the five religiosity items’ contributions to caregiver depressive symptoms. In each regression model, the sociodemographic variables listed above were entered in block 1. In block 2, one of the religiosity items was entered, and on block 3 the remaining four religiosity items were entered. Thus, in the first regression model, prayer as a source of comfort/help was entered on block 2 and the four other religiosity items in block 3. In the subsequent four regression models, block 2 entered frequency of prayer, services as a source of comfort/help, frequency of service attendance, or importance of religion as single variable in the block. The focus of interest in these analyses was the change in the b coefficients for the religiosity items in block 2 after the other religiosity variables were introduced in block 3. If the coefficient was smaller in block 3, this would suggest that the item was strongly associated with other religiosity dimensions in its contribution to caregiver depressive symptoms. On the other hand, if the b coefficient became larger, this would argue that the item’s association with caregiver depressive symptoms was not entirely shared with the other items but had been partially suppressed in block 2 (Cohen and Cohen 1988). If the block 3 b coefficient changed in direction from the block 2 coefficient, this would argue that the

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association with depressed mood is complex, with aspects of the variable having opposite associations with depressed mood. This would be expected based on the consolation hypothesis (i.e., caregivers who are more depressed pray more often).

Collinearity Examining multiple intercorrelated dimensions of religiosity poses the potential problem of collinearity (or multilinearity), in which one independent variable is a linear function of another. If collinearity exists, the coefficients obtained by the simultaneous model for the entire set may be misleading, showing spuriously small coefficients (Cohen and Cohen 1988). To address this problem, collinearity statistics were run in each multiple regression.

Results Sociodemographic and Illness Characteristic: Selection of Covariates All five religiosity items intercorrelated significantly and in the predicted direction (i.e., positively), with Spearman’s rho coefficients ranging from .31 to .70. Table 2 presents these associations.

Depressed Affect and Sociodemographic and Illness Characteristics CES-D was found to be associated with caregiver age (r = -.07, p = .02), gender [t (1226) = 4.63, p \ .001], years of education (r = .10, p \ .001), financial difficulty (r = .21, p \ .001), hours/day spent caregiving (r = .10, p \ .001), care recipient’s age (r = -.06, p = .028), gender [t (1226) = 3.36, p = .001), ADL score (r = .13, p \ .001], and number of problem behaviors (r = .30, p \ .001), and all three social support measures, viz., ISSB (r = -.16, p = \ .001), social network (r = -.31, p = \ .001), and negative interactions (r = .27, p \ .001). The multiple regression models therefore adjusted for these covariates.

Depressive Affect and the Five Dimensions of Religiosity Table 3 presents the b coefficients for the religiosity items in the five regression analyses. Findings for block 3 were identical in the five regressions and are therefore presented only once. In each analysis, block 2 revealed that individually each dimension of religiosity was Table 2 Spearman’s rho coefficients among the five dimensions of religiositya Prayer as source of help

Frequency of services

Frequency of prayer

Services as source of help

Importance of religion

Prayer source of help/comfort

1.00

.36

.64

.50

.63

Frequency of services

–

1.00

.31

.70

.37

Frequency of prayer

–

–

1.00

.35

.57

Services source of help/comfort

–

–

–

1.00

.45

Importance of religion

–

–

–

–

1.00

a

All coefficients are significant at p \ .001

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J Relig Health Table 3 Depressive affect and dimensions of religiosity: results of five multiple regression analyses Block 3a

Block 2 B (SE)

P

B (SE)

P

Importance of religion

-1.05 (.33)

.001

.38 (.44)

.385

Services as source of comfort/help

-1.29 (.23)

.001

-.52 (.33)

.116

Frequency of service attendance

-.84 (.18)

.001

-.38 (.24)

.121

Prayer as source of comfort/help

-1.71 (.27)

.001

-2.17 (.42)

.001

Frequency of prayer

-.43 (.21)

.041

.80 (.30)

.004

a

Identical in all five multiple regression models

significantly associated with depressed mood in the expected direction, i.e., higher scores were associated with lower depressive affect. But on block 3 all religiosity dimensions except the two concerning prayer lost significance when the other dimensions were controlled. This suggests that importance of religion, frequency of religious attendance, and services as a source of help/comfort overlap in their associations with mood, with no individual item contributing independently. Prayer as source of help or comfort, however, contributed independently to depressed affect on block 3, its association becoming even somewhat stronger when the other religiosity dimensions were controlled. Finally, and in contrast to the other four religiosity items, frequency of prayer was significantly associated with depressed affect after the other religiosity items were entered in block 3 but in the opposite direction of the other religiosity dimensions and its block 2 associations. More frequent prayer was associated with greater depressive affect; all other religiosity domains held fixed. Collinearity diagnostics for the five religiosity items revealed tolerance values ranging from .441 (services as source of help) to .583 (frequency of prayer) and variance inflation factors (VIF), ranging from 1.72 (for frequency of prayer) to 2.27 (for services as source of help/comfort). Tolerance and VIF are useful measures for detecting multicollinearity. These indicate a low risk of collinearity among the five religiosity dimensions (Cohen and Cohen 1988).

Discussion Different dimensions of religiosity had different patterns of associations with depressed mood: (1) Neither importance of religion, frequency of religious service attendance, nor service as a source made independent contributions to depressive affect over and above the other religiosity dimensions and the sociodemographic characteristics. This would be expected if the religiosity dimensions represented a unitary construct. (2) Prayer as a source of help/comfort was associated with depressive affect before the other items were introduced and even more strongly associated after they were introduced. This pattern suggests its independent role in relation to caregiver depressed mood. (3) Frequency of prayer was positively correlated with the other religiosity items in the expected direction before other dimensions were entered; but when the other items were introduced, its sign reversed, indicating that frequency of prayer was associated with greater depressive affect. The reversal of association for frequency of prayer suggests a special role for frequency of prayer in depressive symptomatology. When entered alone (block 2), frequency of

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prayer seems to represent an aspect of religiosity with effects parallel to those of other dimensions—that is, more frequent prayer is associated with lower depressed mood. However, when the analysis adjusts for the other four other dimensions of religiosity, frequency of prayer has the opposite association with mood: More frequent prayer is associated with greater depressed mood. This is what would be expected if depressed individuals prayed more frequently to cope with their depressed mood, echoing the religious consolation phenomenon described by Ferraro and Kelley-Moore (2000). This finding underscores the idea that depressed mood is not necessarily the outcome of religiosity; more frequent prayer may be the outcome of depressed mood. It is also consistent with the idea of religion as a coping strategy (Koenig et al. 1988). The finding of three patterns supports the argument for the multidimensionality and complexity of religiosity and justifies examining its components individually as they relate to mental health. The present study contributes to previous research on religiosity and mood in several ways. Findings highlight the distinctiveness of aspects of religiosity and support Hill and Pargament’s (2003) argument for a careful examination of various dimensions of religiosity in relation to psychological well-being. Most previous research on religiosity and health has relied on religious service attendance and found a robust association with physical and mental health (e.g., Koenig et al. 2004; McCullough et al. 2000; Hill and Pargament 2003). In the present study, however, frequency of service attendance did not emerge as a significant predictor of caregiver depressive symptoms when other religiosity dimensions were controlled. This is consistent with Meisenhelder and Chandler’s (2002) finding that attitudes rather than practices are the important correlates of mental health in the elderly. It suggests that service attendance represents an aspect of the religiosity construct that is highly correlated with others—not independent. This is an argument for evaluating various aspects of religiosity as well as conducting analyses that identify a variety of religiosity dimensions (e.g., prayer-related items) that have the potential to affect caregiver emotional well-being. The inclusion of a broader spectrum of items would more accurately represent the complexity of religion and spirituality and uncover their association with caregiver well-being. The present research also contributes by helping to integrate research that views religiosity as an effect on health and the religious coping literature, according to which religious behavior is itself a response to suffering. The role of prayer revealed in our analyses represents an interesting topic in itself for future research on religiosity and mental health. Prayer appears to represent a component of religiosity that plays a complex role in the lives of caregivers.

Study Strengths and Limitations A particular strength of the study was its use of the REACH data set, a geographically diverse and representative sample of caregivers in six US cities. Its size and diversity lend credibility to the external validity of study findings. The prevalence of depressed mood was also quite high in this sample, with 41 % scoring at or above the CES-D cutoff of 16. This distribution made it an ideal sample for a study of depressed mood in caregivers. However, the present analysis was limited to the religiosity items that were selected for that study. As a result, it may not reflect all of the domains of religiosity relevant to emotional well-being. Nevertheless, the use of multiple dimensions of religiosity and spirituality expands on the growing body of research focusing on the impact of religiosity and spirituality on emotional well-being. Given that caregivers vary in support, coping strategies, and religiosity, religious coping is another important dimension of religiosity that should be considered for future research (e.g., Pargament et al. 2004).

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The large sample, though usually an advantage, raises the possibility that significant study effects may be small. Finally, like nearly all of the literature on religiosity and mood, the present study shares the limitation of being cross-sectional. This limitation, though, is at the core of the present study’s questions. An additional shortcoming was that the sample was limited to family caregivers of dementia patients. Yet the same issues regarding dimensions of religiosity and depressed mood should be true for the general population. Future research should examine this relationship in a sample of adults from the population.

Implications Different aspects of religiosity have distinctive roles in the emotional well-being of dementia caregivers. Research on caregiver well-being would benefit from the inclusion of distinct dimensions of religiosity, especially prayer-related items. Findings also suggest a bidirectional relationship between religiosity and mood, underscoring the caveat concerning interpretation of associations. Although this is widely acknowledged, in fact much of the mood–religiosity literature has implicitly assumed that religiosity affects mental health. In terms of both its multiple dimensionality and the issue of direction of causality, religiosity is associated with mental health in complex ways. These have been inadequately investigated and warrant further research.

References Alzheimer’s Association of America. (2014). Alzheimer’s disease 2014—facts and figures. http://Alz.org/ Alzheimer’s Disease Factors and Figures. 3 March 2015. Berrara, M. J., Sandler, I. N., & Ramsay, T. B. (1981). Preliminary development of a scale of social support: Studies on college students. Journal of Community Psychology, 9, 435–447. Blazer, D. G. (2007). Religious beliefs, practice and mental health outcomes: What is the research question? American Journal of Geriatric Psychiatry, 15(4), 269–272. Bonelli, R. M., & Koenig, H. G. (2013). Mental disorders, religious, and spirituality 1990 to 2010: A systematic evidence-based review. Journal and Religion and Health, 52(2), 657–673. Braam, A. W., Beekman, A. T., van Tilburg, R. G., Deeg, D. J., & van Tilburg, W. (1997). Religious involvement and depression in older Dutch citizens. Society of Psychiatry and Psychiatric Epidemiology, 32(50), 284–291. Braam, A. W., Deeg, D. J. H., Poppelaars, J. L., Beekman, A. T. F., & Tilburg, W. (2007). Prayer and depressive symptoms in a period of secularization: Patterns among older adults in The Netherlands. American Journal of Geriatric Psychiatry, 15(4), 273–281. Braam, A. W., Hein, E., Deeg, D. J., Twisk, J. W., Beekman, A. T., & van Tilburg, W. (2004). Religious involvement and 6-year course of depressive symptoms in older Dutch citizens: Results from the Longitudinal Aging Study Amsterdam. Journal of Aging and Health, 16(4), 467–489. Cohen, J., & Cohen, P. (1988). Applied multiple regression/correlation analysis for the behavioral sciences. Hillsdale, N.J: Lawrence Erlbaum. Ferraro, K. F., & Kelley-Moore, J. A. (2000). Religious consolation among men and women: Do health problems spur seeking? Journal for the Scientific Study of Religion, 39(2), 220–234. Fetzer Institute (1999). Multidimensional Measurement of Religiousness/spirituality for Use in Health Research: A Report of the Fetzer Institute/National Institute on Aging Working Group. Kalamazoo, MI: Fetzer Institute. Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). Mini-mental state. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3), 189–198. George, L., & Gwyther, L. (1986). Caregiver well-being: A multi-dimensional examination of family caregivers of demented adults. The Gerontologist, 26(3), 253–259.

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J Relig Health Gitlin, L. N., Chernett, N. L., Dennis, M. P., & Hauck, H. (2011). Identification of and beliefs about depressive symptoms and preferred treatment approaches among community-living older African Americans. Manuscript under review. Haley, W. E., West, C. A., Wadley, V. G., Ford, G. R., White, F. A., Barrett, J. J., et al. (1995). Psychological, social, and health impacts of caregiving: A comparison of Black and White dementia family caregivers and noncaregivers. Psychology and Aging, 10(4), 54–552. Hebert, R. S., Dang, Q., & Schulz, R. (2007). Religious beliefs and practices are associated with better mental health in family caregivers of patients with dementia: Findings from the REACH study. American Journal of Geriatric Psychiatry, 15(4), 292–300. Herrera, A. P., Lee, J. W., Nanyonjo, R. D., Laufman, L. E., & Torres-Vigil, I. (2009). Religious coping and caregiver well-being in Mexican-American families. Aging and Mental Health, 13(1), 84–91. Hill, P. C., & Hood, R. W. (1999). Measures of religious behavior. Birmingham, AL: Religious Education Press. Hill, P. C., & Pargament, K. I. (2003). Advances in the conceptualization and measurement of religion and spirituality: Implications for physical and mental health research. American Psychologist, 58(1), 64–74. Katz, S., Ford, A. B., Moskowitz, R. W., Jackson, B. A., & Jaffe, M. W. (1963). Studies of illness in the aged. The Index of ADL: A standardized measure of biological and psychosocial function. Journal of the American Medical Association, 185(12), 914–919. Kaye, J., & Robinson, K. M. (1994a). Spirituality among caregivers. Image, 26, 218–221. Kaye, J., & Robinson, K. M. (1994b). Spirituality among caregivers. Image—The Journal of Nursing Scholarship, 26(3), 218–221. King, D. A., Lyness, J. M., Duberstein, P. R., He, H., Tu, X. M., & Seaburn, D. B. (2007). Religious involvement and depressive symptoms in primary care elders. Psychological Medicine, 37(12), 1807–1815. Koenig, H. G. (2007). Religion and depression in older medical inpatients. American Journal of Geriatric Psychiatry, 15(4), 282–291. Koenig, H. G. (2009). Research on religion, spirituality, and mental health: A review. Canadian Journal of Psychiatry, 54(5), 23–291. Koenig, H. G., Berk, L. S., Daher, N. S., Pearce, M. J., Bellingver, D. L., Robins, D. J., et al. (2014). Religious involvement is associated with greater purpose, optimism, generality and gratitude in persons with major depression and chronic medical illness. Journal of Psychosomatic Research, 77(2), 135–143. Koenig, H. G., George, L. K., & Siegler, I. C. (1988). The use of religion and other emotion-regulating coping strategies along older adults. The Gerontologist, 28(30), 303–310. Koenig, H. G., George, L. K., & Titus, P. (2004). Religion, spirituality and health in medically ill hospitalized older patients. Journal of the American Geriatric Society, 52(4), 554–562. Krause, N. (1995). Negative interaction and satisfaction with social support among older adults. Journal of Gerontology: Psychological Sciences, 50B(2), P59–P73. LeBlanc, A. J., Driscoll, A. K., & Pearlin, L. I. (2004). Religiosity and the expansion of caregiver stress. Aging and Mental Health, 8(5), 410–421. Lubben, J. E. (1988). Assessing social networks among elderly populations. Family and Community Health, 11, 42–52. McCullough, M. E. (1995). Prayer and health: Conceptual issues, research review, and research agenda. Journal of Psychology and Theology, 23(1), 15–29. McCullough, M. E., Hoyt, W. T., Larson, D. B., Koenig, H. G., & Thoresen, C. (2000). Religious involvement and mortality; A meta-analytic review. Health Psychology, 19(3), 2111–2222. McCullough, M. E., & Larson, D. B. (1999). Religion and depression: A review of the literature. Twin Research, 2(2), 126–136. Meisenhelder, J. B., & Chandler, E. N. (2002). Spirituality and health outcomes in the elders. Journal of Religion and Health, 41(3), 243–252. Moreira-Almeida, A., Neto, L. N., & Koenig, H. G. (2006). Religiousness and mental health: A review. Rev Bras Psiqui, 28(3), 242–250. Ory, M. G., Hoffman, R. R., Yee, J. L., Tennstedt, S., & Schulz, R. (1999). Prevalence and impact of caregiving: A detailed comparison between dementia and nondementia caregivers. The Gerontologist, 39(2), 177–185. Pargament, K. I., Koenig, H. G., Tarakeshwar, N., & Hahn, J. (2004). Religious coping methods as predictors of psychological, physical and spiritual outcomes among medically ill elderly patients: A twoyear longitudinal study. Journal of Health Psychology, 9(6), 713–730.

123

J Relig Health Paun, O. (2004). Female Alzheimer’s patient caregivers share their strength. Holistic Nursing Practice, 18, 11–17. Pinquart, M., & Sorensen, S. (2003). Associations of stressors and uplifts of caregiving with caregiver burden and depressive mood: A meta-analysis. Journal of Gerontology: Psychological Sciences & Social Sciences, 58B(2), 112–128. Radloff, L. S. (1977). The CES-D scales: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1(3), 385–401. Richardson, T. M., Friedman, B., Podgorski, C., Knox, K., Fisher, S., He, H., & Conwell, Y. (2012). Depression and its correlates among older adults accessing aging services. American Journal of Geriatric Psychiatry, 20(4), 346–354. Ronneberg, C. R., Miller, E. A., Dugan, E., & Porell, F. (2014). The protective effects of religiosity on depression: A 2-year prospective study. The Gerontologist, July 25. Pii:gnu073. Schulz, R., Belle, S. H., Czaja, S. J., Gitlin, L. G., Wisniewski, S. R., & Ory, M. G. (2003a). Introduction to the special section on Resources for enhancing Alzheimer’s caregiver health (REACH). Psychology and Aging, 18(3), 357–360. Schulz, R., Burgio, L., Burns, R., Eisdorfer, C., Gallagher-Thompson, D., Gitlin, L. N., & Mahoney, D. F. (2003b). Resources for enhancing alzheimer’s caregiver health (REACH): Overview, site-specific outcomes, and future directions. The Gerontologist, 43(4), 514–520. Schulz, R., O’Brien, A. T., Bookwala, J., & Fleissner, K. (1995). Psychiatric and physical morbidity effects of dementia caregiving: Prevalence, correlates, and causes. The Gerontologist, 35(6), 771–791. Smith, T. B., McCullough, M. E., & Poll, J. (2003). Religiosity and depression: Evidence for a main effect and the moderating influence of stressful life events. Psychological Bulletin, 129(4), 614–636. Strawbridge, W. J., Shema, S. J., Cohen, R. D., Roberts, R. E., & Kaplan, G. A. (1998). Religiosity buffers effects of some stressors on depression but exacerbates others. Journal of Gerontology: Social Sciences, 53B(3), S118–S126. Stuckey, J. C. (2001). Blessed assurance: The role of religion and spirituality in Alzheimer’s disease caregiving and other significant life events. Journal of Aging Studies, 15(1), 69–85. Sun, F., Park, N. S., Roff, L. L., Klemmack, D. L., Parker, M., Koenig, H. G., et al. (2012). Predicting the trajectories of depressive symptoms among southern community-dwelling older adults: The role of religiosity. Aging and Mental Health, 16(2), 189–198. Taylor, R. J., Chatters, L. M., & Nguyen, A. W. (2013). Religious participation and DSM IV major depressive disorder among Black Caribbeans in the United States. Journal of Immigrant and Minority Health, 15(5), 903–909. Teri, L., Truax, P., Logsdon, R., Uomoto, J., Zarit, S., & Vitaliano, P. P. (1992). Assessment of behavioral problems in dementia: The revised memory and behavior problems checklist. Psychology and Aging, 7(4), 622–631. Wisniewski, S. R., Belle, S. H., Coon, D. W., Marcus, S. M., Ory, M. G., Burgio, L. D., et al. (2003). The Resources for Enhancing Alzheimer’s Caregiver Health (REACH): Project design and baseline characteristics. Psychology and Aging, 18(3), 375–384. Wykle, M., & Segal, M. (1991). A comparison of black and while family caregiver experience with dementia. Journal of the National Black Nurses Association, 5(1), 29–41.

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