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. Author manuscript; available in PMC: 2021 Dec 1.
Published in final edited form as: J Happiness Stud. 2020 Jan 1;21(8):3037–3049. doi: 10.1007/s10902-019-00212-9

Meaning in Life Predicts Decreased Depressive Symptoms and Increased Positive Affect over Time but Does Not Buffer Stress Effects in a National Sample of African-Americans

Crystal L Park 1, Cheryl L Knott 2, Randi M Williams 3, Eddie M Clark 4, Beverly Rosa Williams 5, Emily Schulz 6
PMCID: PMC7747937  NIHMSID: NIHMS1547657  PMID: 33343225

Abstract

Few studies have specifically focused on meaning in life in African Americans and many important questions remain, including whether effects of meaning in life are direct or moderated by levels of stress. In a national sample of 909 African Americans, we tested meaning in life as a prospective predictor of changes in depressive symptoms and positive affect over a 2.5-year period. Controlling for demographics and hassles, meaning in life predicted decreased depressive symptoms and increased positive affect across the span of 2.5 years. Moderation effects were not found for hassles, age, or income. Gender moderated the effect of meaning on positive affect such that effects were stronger for women than for men. These results suggest that, for African Americans, meaning in life appears to robustly protect against future depressive symptoms and promote positive affect over time unaffected by amount of stress experienced or most demographic factors.

Philosophical perspectives have long held that a sense of meaning in life—the sense that one’s life has coherence, purpose and significance (George & Park, 2017)—is an important aspect of wellbeing (see Ryff & Singer, 2008). In recent decades, empirical research has demonstrated that a sense of meaning in life is consistently and positively associated with a wide range of mental and physical health indicators in many different samples (see Czekierda, Banik, Park, & Luszczynska, 2017 for a review), including undergraduates (King, Heintzelman, & Ward, 2016; Steger Oishi, & Kashdan, 2009), older adults (Krause, 2007), adolescents (Dulaney, Graupmann, Grant, Adam, & Chen, 2018), middle aged adults (Disabato et al., 2017), and cancer patients (Scrignaro et al., 2015). Much of this work has focused on the inverse relationship between meaning and negative aspects of wellbeing (e.g., suicidality; Marco, Pérez, & García- Alandete, 2016), although some has demonstrated favorable associations between meaning and positive aspects of wellbeing (e.g., happiness; Cavazos Vela, Castro, Cavazos, Cavazos, & Gonzalez, 2015).

In spite of increasing research attention, however, many questions about meaning in life remain unanswered. One key question regarding the meaning in life-wellbeing association is whether salutary effects of meaning in life accrue over time. Most of the extant research on this topic has been conducted cross-sectionally, merely demonstrating a contemporaneous association between meaning and wellbeing (e.g., Mascaro & Rosen, 2006; Sinclair, Bryan, & Bryan, 2016). Only a few studies have tested whether meaning in life has salutary benefits that extend over time. For example, one study of adolescents found that higher meaning in life predicted lower symptoms of depression seven months later (Dulaney et al., 2018) and a study of an international (mostly Asian and European) adult sample found that meaning in life predicted changes in depressive symptoms at 3 but not at 6 months subsequently (Disabato et al., 2017). Finally, a study of older adults found that meaning in life predicted decreases in depressive symptoms across two years (Krause, 2007).

A second important question is whether meaning in life is equally related to wellbeing for everyone, or whether its effects on wellbeing differ for different groups. For example, might meaning in life have a stronger effect on wellbeing for younger or older people? For men or women? For those with higher or lower socioeconomic status? Studies of meaning in life have generally reported few differences by demographic factors (e.g., Dezutter et al., 2013; Steger et al., 2006), but these studies were typically conducted with demographically fairly homogenous samples (e.g., college students). Thus, very few studies have examined the potential differential effects of demographics on the relationship between meaning in life and wellbeing (cf. Henry et al., 2014). This lack of focus on demographic factors means that we have little information on how meaning in life may operate within specific groups, such as racial minorities. Perhaps meaning in life serves as a protective factor in the face of disparities in access to other resources. For example, in the US, African Americans disproportionately face chronic stress associated with a history of pernicious racism and discrimination (e.g., Chae et al., 2014; Quillian, Pager, Hexel, & Midtbøen, 2017) yet often show resilient mental health (Williams et al., 2012). To date, the very little research that has focused on meaning in life in African Americans has demonstrated its importance to wellbeing (e.g., Ajibade, Hook, Utsey, Davis, & Van Tongeren, 2016).

Finally, the relationship between meaning in life and wellbeing is complicated by the notion that meaning in life may especially or even primarily facilitate wellbeing when people are coping with high levels of stress. Several studies have demonstrated these moderating effects of meaning cross-sectionally. For example, in a nationwide survey of adults, a greater sense of meaning in life buffered the effects of financial strain on poly-drug use and of experiencing loss or desecration of something held sacred on physical health (Krause, Pargament, & Ironson, 2018; Krause, Pargament, Ironson & Hill, 2017). In a sample of survivors of Hurricane Katrina, those who reported having higher meaning in life following the disaster reported significantly less severe posttraumatic stress in response to resource loss relative to survivors who reported lower spiritual meaning (Haynes et al., 2017). In a study of college undergraduates, meaning in life moderated the relationship between stress and depression such that there was a strong relationship between depression and stress for individuals with low levels of meaning but no relationship between stress and depression for individuals with high levels of meaning (Mascaro & Rosen, 2006). One study of adolescents found that meaning in life moderated effects of bullying on suicidal ideation, but only for boys, such that the association between bullying and suicidal ideation was weaker for boys with higher meaning in life (Henry et al., 2014).

However, all of these studies of buffering assessed both meaning and distress at one time point, and the few studies that have examined whether meaning can be protective of subsequent effects of stress on changes in wellbeing have produced little evidence of buffering. In the study of older adults described above, while meaning in life cross-sectionally buffered deleterious impacts of traumatic events on depressive symptoms, it did not demonstrate longitudinal buffering at a second assessment two years later (Krause, 2007). Finally, a study that demonstrated meaning in life moderated the relationship between stress exposure and depressive symptoms in urban high school students over seven months; however, the effect size for meaning was very small (r=.05), statistically significant in the large sample but of modest practical significance (Dulaney et al., 2018).

Given the demonstrated importance of meaning in life, we aimed to contribute to our understanding of its relations with wellbeing by examining its prospective role in a sample of African Americans, a group that is not only at higher risk for stress (Chae et al., 2014) but also for lower levels of subjective wellbeing (Matthews, Hammond, Nuru-Jeter, Cole-Lewis, & Melvin, 2013), including less positive affect (Hughes, Kiecolt, Keith, & Demo, 2015). We addressed three specific questions: (1) Does meaning in life have direct effects on psychological wellbeing over time for African American adults? To address this question, we focused on two related but distinct aspects of wellbeing, depressive symptoms and positive affect. (2) Are the influences of meaning in life on depressive symptoms and positive affect particularly strong for some demographic groups (e.g., age, income, or gender)? And (3) Does meaning in life buffer the effects of stress on psychological wellbeing? We hypothesized that those with higher meaning in life at baseline would demonstrate decreased depressive symptoms and increased positive affect at Time 2 and that it would buffer the effects of stress; the question of demographic moderators was exploratory.

Method

We conducted a secondary analysis of data from the Religion and Health in African Americans (RHIAA) initiative, which involved telephone surveys of African American households across the U.S.

Procedure

Data collection methods for RHIAA have been reported in detail elsewhere (Debnam et al., 2012). Interviewers from a subcontracted professional sampling firm telephoned potential participants using a probability sampling list of households within the United States and introduced the project. Contacted adults who expressed interest completed a short eligibility screener to determine whether they self-identified as African American and were at least 21 years old. Individuals with a cancer history were excluded due to assessments of cancer screening in the interview. Those deemed eligible in screening provided verbal assent following an informed consent script. Participants who completed the interview received a $25 gift card. An additional wave of data was collected 2.5 years later.

Measures

Background demographics.

A standard demographic module assessed participant characteristics including sex, age, and household income before taxes.

Meaning in life.

A sense of meaning in life was assessed using a 14-item instrument (Krause, 2004). Participants rated each item (e.g., “I have a philosophy of life that helps me understand who I am.”; “I feel good when I think of what I have done in the past.”) using a 4-point Likert-type scale regarding how much they agree with each item from 1 (not at all) to 4 (a great deal). The instrument evidenced reliability and validity in previous work (Krause, 2004). In the present sample, internal consistency reliability was very good (α=.90).

Depressive symptoms.

Depressive symptoms were assessed with the Center for Epidemiological Studies-Depression Scale (CES-D) (Radloff, 1977). Participants rated how frequently they experienced each of 20 symptoms (e.g., “I had crying spells.”, “I felt that everything I did was an effort.”) in the previous week from 1 (rarely/less than 1 day) to 4 (all of the time/5-7 days). High internal consistency has been reported in both normal and patient populations (Radloff, 1977), as well as in the present sample (Time 1 α = .90, Time 2 α=.92). The CES-D has been shown to be valid in African American samples (Makambi, et al., 2009; Roth et al., 2008).

Positive affect.

Positive and negative affect were assessed with the Positive and Negative Affect Schedule (PANAS) (Watson, Clark, & Tellegen, 1988). The widely-used PANAS consists of 20 adjectives [10 positive (e.g., interested, excited) and 10 negative (e.g., distressed, upset)]. Participants indicate the extent to which they have felt that way in the past week from 1 (“very slightly or not at”) to 5 (“extremely”). The scale has demonstrated factorial, convergent, and discriminant validity in previous research (Watson et al., 1988). Internal reliability was high in the present study (Time 1 α=.88, Time 2 α=.89).

Stress.

A revised version of the Daily Hassles Scale (Kanner, Coyne, Schaefer, & Lazarus, 1981; Kohn & MacDonald, 1992) was used to measure levels of daily stress. From a list of 10 hassles (e.g., Conflicts with boyfriend/girlfriend/spouse), participants endorsed each ones they had experienced in the past month and rated the severity of each hassle they had experienced as somewhat severe, moderately severe, or extremely severe. Each endorsed hassle. A total stress score of intensity x frequency was calculated.

Analytic Plan

We first characterized our sample and examined bivariate correlations among our variables of interest. We then conducted a hierarchical linear regression analysis for each wellbeing measure (depressive symptoms, positive affect) and then separately tested whether hassles and demographics moderated the links between stress and wellbeing. Because meaning in life was assessed at T1, 2.5 years prior to our assessment of wellbeing, our longitudinal and prospective analyses provided a rigorous test of the influence of meaning in life over time and extended the empirical base, which primarily consists of cross-sectional studies. We used SPSS 24.0 for all analyses.

Results

Sample characteristics

From the original RHIAA baseline sample, we used the subset that included the variables of interest in the present analyses (depressive symptoms, meaning in life). Thus, the present sample consisted of 909 participants; demographics are shown in Table 1. Relative to the U.S. black population at the time of the survey, the current sample was older than the U.S. median age of 32.7 years (current median = 54.0); contains fewer men (current = 38.2%; U.S. = 47.7% male); and was more educated (current % attended 4+ years of college = 26%; U.S. = 18.4%) (U.S. Census Bureau, 2011).

Table 1.

Demographic characteristics of the sample

Mean (SD) or Percent
Age 57.18 (13.45) years
Gender
 Female 65.5
 Male 34.5
Education
 Less than a high school diploma 11.7
 High school diploma or equivalent 31.5
 Some college 28.7
 College graduate or higher 28.2
Relationship Status
 Never married 11.9
 Separated/divorced 18.4
 Single 16.3
 Widowed 16.1
 Married 37.3
Employment Status
 Employed full time 33.3
 Employed part-time 12.1
 Disabled or not working 22.8
 Retired 31.7
Household income
 Less than $10,000/year 19.0
 $10,000 to $20,000/year 16.5
 $20,000 to $30,000/year 14.5
 $30,000 to $40,000/year 11.9
 $40,000 to $50,000/year 8.7
 $50,000 to $60,000/year 8.6
 $60,000 or more/year 20.8
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Correlations among Study Variables

To examine associations among primary study variables, bivariate correlational analyses were conducted (see Table 2). Results indicate that age, gender and income were all significantly positively correlated with meaning, although gender was unrelated to either depressive symptoms or positive affect. Both age and income were inversely associated with Time 2 daily hassles. Age was associated with fewer depressive symptoms at both time points, but inversely associated with positive affect at Time 2. Income was consistently related to fewer depressive symptoms and more positive affect. Hassles were moderately strongly positively related to depressive symptoms and were also inversely associated with positive affect.

Table 2.

Bivariate correlations among primary study variables

Gender Income T1
Meaning		 T2
Hassles		 T1
Depressive
Symptoms		 T2
Depressive
Symptoms		 T1
Positive
Affect		 T2
Positive
Affect
Age .03 −10** .15*** −.26*** −.12*** −.11*** −.03 −.11**
Gender -------- −.13*** .10** .00 .01 −.01 .04 −.03
Income -------- .09* −.15*** −.31*** −.30*** .22*** .21***
T1 Meaning -------- −.21*** −.34*** −.36*** .36*** .30***
T2 Hassles -------- .44*** .57*** −.19*** −.15***
T1 Depressive Symptoms -------- .57*** −.43*** −.27***
T2 Depressive Symptoms -------- −.32*** −.41***
T1 Positive Affect -------- .47***
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Note: Gender: 1= male, 2 = female.

***

p < .001.

**

p < .01.

*

p < .05.

Meaning in Life as a Predictor of Subsequent Depressive Symptoms

To determine the extent to which meaning in life assessed at baseline predicted subsequent depressive symptoms, a longitudinal hierarchical linear regression analysis was conducted in which age, gender, and income along with meaning in life and daily hassles were entered together to determine if meaning in life predicted depressive symptoms assessed 2.5 years later when also controlling for demographics and life stress. Income was the only demographic that emerged as a significant predictor (inversely) of depressive symptoms, while hassles strongly predicted increased depressive symptoms. Even after accounting for demographics and life stress, meaning in life predicted lower depressive symptoms 2.5 years later (See Table 3, Step 1).

Table 3.

Hierarchical Regression Analyses Predicting Time 2 Depressive Symptoms and Positive Affect

Depressive Symptoms Positive Affect
B SEB β B SEB β
Step 1 Longitudinal Models
 Age .002 .021 .003 −.090 .023 −.144***
 Gender −.734 .574 −.038 −.072 .625 −.004
 Income −.877 .122 −.215*** .602 .133 .166***
 Meaning −.364 .048 −.226*** .412 .053 .285***
 Hassles .521
R2= .437		 .032
R2Δ =.437		 .508*** −.104
R2=.158		 .035
R2Δ =.158		 −.114**
Step 2 Prospective Models (Controlling for Baseline Levels of Depressive Symptoms or Positive Affect)
 Meaning −.187 .048 .−116*** .222 .053 .153***
 Hassles .403 .032 .393*** −.069 .032 −.076*
 Baseline Depressive Symptoms or Positive Affect .310 .031
R2 =.510		 .338***
R2Δ =.26		 .339
R2 =.265		 .034 .373***
R2Δ =.07
Steps 3 (Each Interaction entered in a separate model)
 Meaning x Hassles .001
R2 =.510		 .005 .009
R2Δ =.00		 −.003
R2 =.266		 .005
R2Δ =.01		 −.041
 Meaning x Age −.001
R2 =.510		 .003 −.006
R2Δ =.00		 .001
R2 =.265		 .004
R2Δ =.00		 .011
 Meaning x Gender −.044
R2 =.510		 .030 −.013
R2Δ =.00		 .213
R2 =.274		 .097
R2Δ =.01		 .072*
 Meaning x Income .012
R2 =.510		 .019 .017
R2Δ = .00		 −.004
R2=.265		 .021
R2Δ =.00		 −.07
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Note: Results for meaning and hassles, initially entered in step 1, are shown in step 2 as well to show their prediction of residual change in depressive symptoms and positive affect. Gender: 1= male, 2 = female.

***

p < .001.

**

p < .01.

*

p < .05.

In a second step, baseline depressive symptoms scores were entered to determine whether meaning in life predicted residual change in depressive symptom scores when controlling for demographics and life stress; baseline meaning in life remained statistically significant, predicting reductions in depressive symptoms over time even controlling for life stress (See Table 3, Step 2).

This regression analysis was then repeated four times with the addition of an interaction term of meaning in life by, respectively, age, gender, income, and hassles, to determine whether any of these factors interacted with meaning in life. The interaction terms were created by first centering the variables and then computing a multiplication term (Aiken & West, 1991). Results indicated that none of the interaction effects were significant (See Table 3, Step 3).

Meaning in Life as a Predictor of Subsequent Positive Affect

To determine the extent to which meaning in life assessed at baseline predicted subsequent positive affect, a longitudinal hierarchical linear regression analysis was conducted in which age, gender, and income along with meaning in life and hassles were entered together to determine if meaning in life predicted later positive affect when also controlling for demographics and life stress. Income predicted higher subsequent positive affect while both higher age and more hassles strongly predicted lower positive affect. Even after accounting for demographics and life stress, meaning in life predicted greater positive affect 2.5 years later (See Table 3, Step 1).

In a second step, baseline positive affect scores were entered to determine whether meaning in life predicted residual change in positive affect when controlling for demographics and life stress; baseline meaning in life remained statistically significant, predicting increases in positive affect over time even controlling for life stress (See Table 3, Step 2).

This regression analysis was then repeated four times with the addition of an interaction term of meaning in life by, respectively, age, gender, income, and hassles, to determine whether any of these factors interacted with meaning in life. Results indicated that only one of the interaction effects was significant: meaning in life x gender (See Table 3, Step 3). This interaction effect is shown graphically in Figure 1. While higher meaning is associated with more positive affect in both men and women, the effect appears to be stronger for women.

Figure 1.

Figure 1.

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Role of Gender on Meaning in Life and Positive Affect.

Discussion

This study aimed to advance our knowledge of how meaning in life may carry forward to promote greater wellbeing across a substantial period of time and to determine whether its salutary effects are experienced across the board or are contingent on other factors, such as demographics or the amount of stress an individual encounters. Further, we examined these issues in a sample of African Americans, a group for whom meaning in life has not been well-studied in spite of its potential relevance, especially given the myriad adversities they have historically and currently face (e.g., Chae et al., 2014; Quillian, Pager, Hexel, & Midtbøen, 2017).

In general, our results were consistent with our expectations, particularly that meaning in life would be favorably associated with subsequent wellbeing both in terms of reduced depressive symptoms and increased positive affect over a fairly substantial period of time. Indeed, these favorable associations remained when accounting for both demographic factors and for life stress, a well-established factor detrimental to mental health and wellbeing (Hammen, 2015; Menard et al., 2017).

Copious prior research has established robust relationships between meaning in life and wellbeing (George & Park, 2017; Heisel, Neufeld, & Flett, 2016). However, most of this work has been cross-sectional and thus of limited utility in understanding whether meaning in life might actually help foster better wellbeing. The prospective nature of our data suggests that feeling a greater sense of meaning in life may indeed set the stage for greater wellbeing over time, both in terms of fewer depressive symptoms and in terms of increased positive affect. Further, meaning in life does not appear to buffer stress, as has sometimes been hypothesized (Haynes et al., 2017), but, at least in the present sample of African Americans, functions as an independent resource promoting wellbeing regardless of the levels of stress individuals are experiencing. It should be noted that meaning in life was assessed 2.5 years prior to the assessment of hassles and wellbeing; it is possible that assessed more contemporaneously, buffering effects might be observed.

In our sample, meaning in life appears to be equally relevant to wellbeing regardless of individuals’ age or income. However, those higher in age and income reported higher meaning in life, as did women relative to men. Further, although gender did not moderate the influence of meaning on wellbeing for depression, we did find that for women, meaning in life was more strongly linked to their increased positive affect over time than it was for men. Post-hoc analyses showed that while, for both men and women, higher levels of meaning in life predicted more subsequent positive affect, this effect was stronger for women than for men. Reasons for this are not clear, but one hypothesis that awaits further research is that perhaps the sources of meaning differ for African American women and men, such that women derive relatively more of their meaning from interpersonal relationships and spirituality while men derive relatively more of their meaning from work (Debats, 1999; Schnell, 2009); while all of these sources provide a sense of meaning in life, relationships and spirituality might be more strongly associated with positive emotions such as joy and peace.

Clearly, caution is necessary in interpreting our results. The study relied on a correlational design, and thus directionality cannot be inferred. Further, it is possible that psychological wellbeing influences one’s sense of meaning in life as well as being influenced by it. The timeframe over which we examined effects was relatively short; replication of these results over a longer time period, such as decades, would add to our understanding of these relationships.

In addition, our sample consisted entirely of African Americans. While a strength of the study overall, in that meaning in life has rarely received empirical attention in this group, sample composition precludes testing race as a potential moderator of the meaning-wellbeing relationship. Previous research has demonstrated that African Americans may experience and cope with stress differently than do Whites (McCallum, Longmire, & Knight, 2007). In particular, they may endeavor to be self-reliant and feel pressure to be strong and invulnerable, sometimes to their detriment (Blackmon, Coyle, Davenport, Owens, & Sparrow, 2016; Harrington, Crowther, & Shipherd, 2010; Matthews, Hammond, Nuru-Jeter, Cole-Lewis, & Melvin, 2013). Future research is needed to determine how a sense of meaning in life may mitigate (or exacerbate) these tendencies.

In spite of these limitations, the fact that a higher sense of meaning in life may lead to improved wellbeing—across a fairly substantial period of time and independent of the stressfulness of one’s circumstances—has implications for promoting African Americans’ psychological wellness: Enhancing a sense of meaning in life may be helpful not only in achieving higher levels of life meaning (which may be a satisfying end in and of itself; Park et al., in press) but also in improving psychological wellbeing over time. Multiple factors that can give rise to meaning have been identified in prior research (although none of this work has been done with African American samples). Among the most common sources of meaning reported are satisfying relationships, engaging work, and spirituality (Wong, 1988). One way to promote a greater sense of meaning, then, may be to provide means for improving one’s interpersonal relationships, finding significance and purpose in one’s vocation, and developing a deeper spiritual life (Shin & Steger, 2014).

To date, few interventions have been tested in any population to determine whether meaning in life can be directly enhanced, and much of the research on meaning promotion has been conducted in patients with serious illnesses such as cancer (see Park et al., in press; Shin & Steger, 2014, for reviews). Such interventions may not only bolster meaning in life but perhaps also promote experiencing less depressive symptoms over time, a promising possibility that awaits future research.

Footnotes

Publisher's Disclaimer: This Author Accepted Manuscript is a PDF file of an unedited peer-reviewed manuscript that has been accepted for publication but has not been copyedited or corrected. The official version of record that is published in the journal is kept up to date and so may therefore differ from this version.

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