Meaning in Life and Coping With Everyday Stressors

Abstract

Meaning in life (MIL) has been proposed to improve coping and resilience. Yet MIL’s association with coping has primarily been investigated in the context of extreme stressors and trauma, often using varied measures of MIL. Is MIL associated with varied coping strategies, coping self-efficacy, and distress in relation to commonly experienced, everyday challenges? Using diverse methodological designs, five studies (total N = 1,646) investigated the association between MIL and coping strategies/appraisals pertaining to varied challenging, stressful events. Across recalled (Studies 1 and 2), anticipated (Study 3), and experienced stressors (Studies 3–5), MIL was consistently associated with positive reinterpretation, proactive planning, coping self-efficacy, and stress. MIL was inconsistently related to threat/emotion-coping.

Keywords

meaning in life coping

Is finding life meaningful a resource for coping with life’s vicissitudes? Meaning in life (MIL)—the subjective evaluation that one’s existence has significance, purpose, and coherence (King et al., 2006)—has been proposed to improve coping and resilience (Krause, 2007; Park, 2010).¹ People with high MIL have improved health and coping (Halama, 2014; Miao & Gan, 2019) and experience lower distress after challenging events (Bryan et al., 2013; Hooker et al., 2018). These findings suggest that MIL is a coping resource. Yet, many aspects of this link remain unclear. Using varied methods, this investigation probed the link between MIL and coping within the context of common, everyday stressors.

These studies address four open questions from past research. First, because most research has examined severe or uncommon stressors—including health crises or natural disasters (e.g., Park et al., 2008)—it is uncertain whether MIL predicts coping responses to more common stressors. Second, research has often evaluated MIL’s association with coping with past stressors, rather than ongoing or future stressors (although compare Miao et al., 2017; Miao & Gan, 2019). We investigated MIL’s link to coping and stress in general and in response to recalled, current (experimentally induced or naturally experienced), and future stressors to better illuminate its relevance to coping. Third, research has often examined MIL’s association with one specific coping strategy or with stress. Taking a comprehensive approach, we examined MIL’s association with multiple coping strategies, coping self-efficacy, and stress. Fourth, investigations of meaning and coping have included varied measures of MIL, including some with psychometric limitations, obfuscating the coping correlates of MIL as it is contemporarily measured and conceptualized. We used the presence subscale of the Meaning in Life Questionnaire (Steger et al., 2006) to clarify MIL’s coping correlates. Understanding the precise nature of MIL’s association with coping can help to explain its links to myriad aspects of health and well-being.

Theories of coping and meaning focus primarily on how trauma incites meaning-making efforts and whether restored meaning improves adjustment (Park, 2010; Park & Folkman, 1997; Silver & Updegraff, 2013). This literature typically examines situational meaning in specific traumatic events (e.g., Updegraff et al., 2008), which is often treated as a predictor of adjustment. Less is known about how individual differences in MIL relate to coping and stress, although some links have been documented (e.g., Bryan et al., 2013; Halama, 2014; Miao & Gan, 2019). MIL and situational meaning are conceptually distinct and may relate differently to coping and stress. Here, we examine how relatively stable perceptions of MIL relate to coping.

Why Is MIL Linked to Coping?

Coping efficacy is influenced by whether stressors are cognitively appraised as threats or challenges (Lazarus & Folkman, 1984; Park & Folkman, 1997). Threat appraisals can spur distress, denial, avoidance, and self-blame, hindering coping (Lazarus & Folkman, 1984). In contrast, challenge appraisals—believing one can conquer stressors or take action to remedy them—typically facilitate adaptive coping. Coping responses reflect the instantiation of these general appraisals (Carver et al., 1989) and can be broadly categorized as focused on meaning-making, problems, or emotions (e.g., Riley & Park, 2014).² Meaning-focused coping involves positive reinterpretation of events or benefit finding (e.g., Park, 2010). Problem-focused coping reflects actively trying to take steps to handle stressors. Finally, emotion-focused coping reflects experiencing, processing, or downplaying stressor-relevant emotions.

These studies examined MIL’s association with three coping dimensions representing broad coping categories: (a) positive reinterpretation, capturing meaning-focused coping; (b) proactive planning, representing problem-focused coping; and (c) threat appraisals/emotion-focused coping. We also measured coping-self-efficacy as a broad indicator of problem-focused coping. We selected these specific constructs because they captured an array of coping responses applicable to the diverse stressors we examined. They have all been linked to MIL within the context of health disorders and trauma (Krok & Telka, 2019; Miao et al., 2017; Park et al., 2008; Sherman & Simonton, 2012; Taubman-Ben-Ari et al., 2012). Positive reinterpretation reflects beliefs that one can benefit by overcoming challenges (Carver et al., 1989). Proactive planning involves actions aimed at addressing potential problems (Carver et al., 1989). In these studies, threat appraisals/emotion-focused coping (aggregated due to strong item overlap³) captured concerns that one cannot sufficiently address stressors and concomitant negative emotions (e.g., worry, hopelessness). Coping self-efficacy captures confidence about one’s capacity to deploy different adaptive coping responses and persevere through challenges. Coping dimensions were expected to be interrelated. Measuring multiple coping dimensions simultaneously allowed us to identify their independent links to MIL, controlling for shared variance with other strategies. We also examined MIL’s association with general stress and distressed emotions. Distress results from appraising stressors as threats and failing to adaptively cope with such stressors (e.g., Krok & Telka, 2019; Park & Folkman, 1997). MIL is negatively related to stress (Bryan et al., 2013; Hooker et al., 2018). If MIL facilitates adaptive coping responses, it may subsequently reduce distress.

The precise mechanisms that explain MIL’s association with coping and stress are difficult to pinpoint and theoretically uncharted (e.g., Hooker et al., 2018; Krause, 2007). We propose that MIL’s multidimensionality helps it serve as a comprehensive resource for coping with common life stressors. MIL involves experiencing life as coherent, purposeful, and significant (King et al., 2006). Coherence captures whether experiences make sense. Purpose involves pursuing personally valued, important life goals. Significance involves the social importance of one’s existence and contributions—that one matters. Coherence, purpose, and significance may benefit adaptive coping through their links to cognitive, affective, and motivational features of MIL.

Due to its multifaceted nature, MIL may mobilize diverse cognitive, affective, and motivational components that influence coping with stressful everyday events. Figure 1 illustrates how these features of MIL may influence meaning, problem, and emotion-focused coping as well as distress. Rather than influencing one specific aspect of coping, MIL is expected to be broadly relevant to varied adaptive coping strategies and to people’s confidence about successfully deploying these strategies—coping self-efficacy. Next, we outline reasons for these proposed links.

Figure 1.

Links between meaning in life and coping.

Cognitive Components

MIL involves having a coherent narrative for one’s life and motivations, facilitating the assimilation of past, present, and future events (e.g., McAdams, 2008). Integrating negative events into one’s life narrative and understanding their relevance to the present is crucial for adjustment (e.g., Park, 2010). Coherence may provide a cognitive framework that allows people to easily integrate negative experiences into a larger life narrative, thus mitigating distress that often arises from failed attempts to make sense of negative experiences (e.g., Park, 2010; Ward & King, 2017). As a meaning-focused coping strategy, positive reinterpretation involves construing challenges as personally meaningful and recognizing their potentially beneficial consequences. MIL may enable positive reinterpretation of everyday challenges because it stimulates “big picture” thinking and the reconciliation of past negative events, thereby promoting sensemaking and benefit finding (e.g., Krause, 2007; Park, 2010; Ward & King, 2017).

By integrating negative experiences into a coherent life narrative, MIL may also foster greater acceptance of life’s challenges and a willingness to directly, proactively confront them. People with high MIL tend to view experiences as fated and “meant to be,” bolstering the likelihood that difficult experiences are accepted and confronted head-on, rather than viewed as unexpected diversions that warrant extensive sensemaking (e.g., Ward & King, 2017). MIL may encourage future-oriented thinking, potentially dampening emotion-focused coping and improving people’s capacity to plan specific steps to overcome daily struggles. For instance, instead of experiencing distress, a person with high MIL may eagerly tackle a difficult work project (proactive planning), viewing it as a chance to illustrate competence and suitability for a future promotion.

MIL is linked to cognitive flexibility (e.g., Tan et al., 2021), potentially enabling the creative deployment of myriad coping strategies to address stressors, rather than an overreliance on one coping strategy. The agile cognitive flexibility stemming from recognizing life’s meaningfulness may help people to envision myriad alternate positive outcomes during challenges, motivating coping self-efficacy and varied proactive actions to successfully overcome challenges (e.g., Krause, 2007). By raising awareness about effective coping strategies, the potential cognitive flexibility conferred by MIL may also reduce emotion-focused coping and distress.

Motivational Components

MIL helps marshal self-regulatory resources that benefit goal pursuit and perseverance during obstacles. Much of MIL’s motivational coping benefits are attributable to its link to purpose. Purpose involves having important reasons for living and prioritizing the pursuit of personally valued goals. Having a strong purpose can facilitate adaptive coping by strengthening identity and encouraging the steadfast pursuit of important goals amid setbacks. By motivating behaviors aimed at achieving cherished personal goals (e.g., Hooker et al., 2018; Krause, 2007), purpose may enable people to strategically plan how to achieve valued goals when stressors threaten goal progress. Because MIL enhances people’s awareness about the broader purpose of their lives, it may facilitate recognition about the purpose and value of personal challenges, encouraging positive reinterpretation. MIL may also benefit coping through significance. Feeling that one matters in the world may motivate coping self-efficacy by making people feel that their coping efforts will be personally and socially impactful.

Because MIL confers certainty about the purpose and significance of one’s existence, it can improve goal clarity, fostering coping self-efficacy and proactive planning during unexpected setbacks that could impede goal pursuit (e.g., Krause, 2007). Clear goals increase motivation and life structure, assuring people that energy is being directed toward desired outcomes and that setbacks may be part of a bigger plan (Krause, 2007). People with high MIL may resolutely believe that tough challenges are surmountable, confidently pursuing actions to directly alleviate them, rather than allowing them to thwart goal progress. By experiencing self-efficacy regarding one’s coping capacity and taking proactive actions to address stressors, people with high MIL may also experience lower emotion-focused coping and distress.

Affective Components

Finally, affective features of MIL may explain its relevance to coping. MIL shares a robust relationship with positive affect (e.g., King et al., 2006) and the regulation of negative emotions, namely, stress (e.g., Hooker et al., 2018). The mechanisms underlying MIL’s affective benefits are uncertain (see Hooker et al., 2018, for a review). The aforementioned cognitive and motivational features of MIL may help explain its association with lower stress reactivity. Focusing on the “big picture” and future while confidently pursuing personally valued, purposeful goals might provide affective benefits, rendering daily hassles less emotionally impactful to people with high MIL. During chaotic events, coherence may promote perceptions of controllability and equanimity, thereby reducing threat appraisals, emotion-focused coping, and distress (e.g., Park, 2010). By lowering threat appraisals and emotion-focused coping, MIL may help people identify and engage in proactive actions to overcome life’s difficulties.

Complex Links and Causal Directions

Although the preceding analysis highlighted the potential cognitive, motivation, and affective coping benefits of MIL separately, these functional coping benefits are likely deeply intertwined. Viewing a stressful event as concordant with one’s worldview is likely to decrease distress and other negative emotions (Park, 2010), facilitating affective coping benefits. Similarly, successfully regulating negative emotions may enhance motivation during coping efforts and promote more positive construals of stressors. MIL likely influences coping responses in dynamic, multifaceted ways.

MIL and coping strategies have complex associations that are not easily accounted for by one specific mechanism (e.g., Hooker et al., 2018; Miao & Gan, 2019). MIL’s association with coping strategies holds controlling for numerous potential confounds, including social support, religiosity, self-efficacy, and social desirability bias (Sherman & Simonton, 2012). Therefore, we did not expect any single mechanism to comprehensively explain MIL’s association with varied coping dimensions.

Although we have focused on reasons why MIL could benefit coping and reduce distress (Figure 1), it is also plausible that coping and distress may influence MIL. MIL may result from successful past attempts of coping with life’s challenges. People who find their lives highly meaningful have found ways to effectively function in the world, pursuing purposeful goals that enhance significance and maintaining coherence despite unexpected, difficult life experiences. Coping adaptively and experiencing lower stress in response to challenges might bolster MIL. Endorsing high MIL may reveal a person’s history of successful coping, even if MIL also simultaneously serves as a coping resource. MIL and coping may share bidirectional relationships, which cannot be ascertained from past research primarily employing correlational and cross-sectional designs (although see Miao & Gan, 2019; Park et al., 2008; for discussion, see Hooker et al., 2018). Longitudinal research corroborates that adaptive coping may facilitate MIL, just as MIL may foster adaptive coping. Among adults with congestive heart failure, positive reinterpretation and religious coping predicted increased MIL 6 months later, controlling for baseline MIL (Park et al., 2008). Active coping and positive reinterpretation among people with cancer predicted subsequent increases in some meaning-relevant dimensions (e.g., life perspective; Jim et al., 2006). This investigation included experimental and daily studies to test potential causal associations between MIL and coping.

Coping Context

The preceding discussion highlights the broad relevance of MIL to multiple coping dimensions. In contrast to past research, we aimed to evaluate MIL’s relevance to varied coping dimensions across contexts, time frames, and samples. Divergent coping strategies may be adaptive in different situations and provide context-specific benefits (e.g., Hooker et al., 2018; Krok & Telka, 2019; Park & Folkman, 1997). Identifying the coping dimensions to which MIL is robustly associated can help to identify the contexts where it may be most beneficial for adjustment.

MIL is considered an especially effective resource for coping with trauma because of its durability and role in helping to reinterpret disturbing, shocking events (Krause, 2007). MIL’s coping benefits may be limited to traumatic events—versus common, everyday stressors—because trauma dramatically threatens fundamental beliefs and worldviews that MIL buttresses (e.g., Park, 2010; Park & Folkman, 1997). MIL may be less applicable to threat appraisals and emotion-focused coping during mild daily stressful events because such events are unlikely to shatter assumptions and elicit strong negative emotions. It is important to test whether MIL is linked to diverse coping dimensions in the context of commonly experienced challenges. Aside from MIL’s documented link to proactive coping with everyday stressors (Miao et al., 2017; Miao & Gan, 2019), its association with everyday coping is unknown.

Coping research is often limited by an overreliance on retrospective designs (Carver & Connor-Smith, 2010; Park, 2010). MIL might foster bias in recalling the nature or magnitude of stressors or to optimistic evaluations of anticipated stressors (e.g., Carver & Connor-Smith, 2010). Studying recently experienced and expected future stressors allowed us to examine whether MIL would be similarly linked to anticipatory and post-stressor coping. Studies 3 and 5 examined uniform stressful events, providing consistency in stressor magnitude and mitigating problems with self-selected stressors. These methodological choices helped to illuminate whether MIL’s association with coping strategies is consistent across past, current, and future stressors.

Overview

Five studies examined MIL’s association with positive reinterpretation (all studies), proactive planning (Studies 1–4), coping self-efficacy (Studies 2–5), and threat/emotion-focused coping (Studies 1–3, 5). We predicted that MIL would be linked to adaptive coping appraisals and strategies and to reduced distress in relation to common, everyday stressors. We examined stressors and challenges that were experienced recently or recalled from the past (Studies 1, 2, and 4), anticipated (Study 3), and experimentally induced (Study 5), aiming to clarify the robustness of MIL’s link to different coping dimensions across diverse stressors. We also probed the potential causal influence of MIL on coping. Study 4 examined bidirectional associations between MIL and coping in daily life, and Study 5 tested whether experimentally manipulating MIL influenced coping.

Measurement

Studies 1 and 4 included established general coping measures. Coping measures in Studies 2, 3, and 5 were tailored to the stressors in these studies, consistent with extant research approaches (e.g., Study 3, Carver et al., 1989; Study 4, Endler & Parker, 1994). Because no single extant coping inventory encompasses all dimensions of interest, we drew from multiple validated measures to assess coping responses applicable to varied situations (Stress Appraisal Measure, Peacock & Wong, 1990; Coping Orientation to Problems Experienced (COPE) Inventory, Carver et al., 1989; Coping Inventory for Stressful Situations, Endler & Parker, 1994). Ad hoc items (adapted from the aforementioned scales and Park, 2010; Park et al., 2016) were added to increase subscale depth when established scales were brief. Coping item content was similar across studies.

As preregistered, we used a data-driven approach to compute coping scales. Threat appraisal and emotion-focused coping items were aggregated because they were strongly correlated and represented the same underlying factor. Coping self-efficacy captured appraisals of challenge and controllability but was termed as such to best represent the full measure and maintain consistency with prior research (e.g., Taubman-Ben-Ari et al., 2012). The supplemental material reports all items (and additional positive reinterpretation and expectancy violations items).

Preregistration and Exclusion Details

All studies were preregistered, https://osf.io/u9t7a/?view_only=12e6a43a25f24c8e925be52d1a84e3cb⁴

Participants were excluded from analyses if they failed multiple attention checks (Studies 1, 2, and 5) or wrote essays not comporting with instructions (Studies 2 and 5). Reported sample sizes reflect final samples’ post-exclusions (supplemental material includes pre-exclusion sample sizes). Some preregistered hypotheses addressed predictions that were too complex for these datasets (e.g., disentangling the roles of MIL vs. positive affect and optimism on coping). Here, we focus on more circumscribed research questions.

Study 1

Study 1 examined MIL and coping strategies in an adult sample. Coping subscales included active coping, planning, and positive reinterpretation—associated with adaptive coping—and emotion-focused coping, associated with anxiety and maladaptive coping (Carver et al., 1989). We predicted that MIL would correlate positively with active coping, planning, and positive reinterpretation and negatively with emotion-focused coping.

Method

Participants recruited from Mechanical Turk (MTurk) completed this online cross-sectional study (N = 560; 57% women, 42% men, n = 5 other identity/unreported); M (SD) age = 39.40 (13.19). Sample size was determined by budgetary constraints (here and in Studies 2 and 5). See supplemental material for detailed demographics for all studies. Measures were completed in the order described. Unless noted otherwise, all items (here and in subsequent studies) were rated from 1 to 7; higher scores reflect higher endorsement. Table 1 shows descriptive statistics.

Table 1.

Correlations Between Measures and Regression Coefficients for Multivariate Analyses, Study 1.

Variables	1	2	3	4	5	6
1. Meaning in life	.91
2. Proactive planning	.37**	.92
3. Positive reinterpretation	.46**	.58**	.85
4. Emotion-focused coping	−.32**	−.13*	−.13*	.84
5. Perceived stress	−.47**	−.29**	−.34**	.65**	.88
6. Trait anxiety	−.37**	−.19**	−.23**	.64**	.67**	.91
β for meaning^a	—	.12*	.29**	−.32**	—	—
R² change	—	.01**	.07**	.08**	—	—
M	5.08	5.47	5.17	3.65	3.60	3.85
(SD)	(1.47)	(1.03)	(1.29)	(1.35)	(1.17)	(1.68)

Note. N = 560. Alpha reliabilities are shown on the diagonal.

These are regression coefficients for MIL entered in models predicting the corresponding coping strategies (proactive planning, positive reinterpretation, or emotion-focused coping) when controlling for the other two coping strategies listed.

p < .05. p** < .001.

We preregistered that analyses would exclude participants failing ≥2 attention checks. The second and third attention check items were not used for exclusions due to survey errors with these items.

Measures

MIL

MIL was assessed with the five-item presence of meaning subscale (e.g., “I understand my life’s meaning”; Steger et al., 2006), the same measure used in all subsequent studies.

Coping

Participants indicated how they generally respond and feel during stressful events (from I usually don’t do this at all to I usually do this a lot). Three four-item subscales from the COPE Scale (Carver et al., 1989) assessed active coping (e.g., “I take direct action to get around the problem.”), planning (e.g., “I make a plan of action.”), and positive reinterpretation (e.g., “I look for something good in what is happening.”). Six items captured emotion-focused coping (e.g., “I worry about what I am going to do”; Endler & Parker, 1994).

All coping strategy items were submitted to an exploratory factor analysis with principal axis extraction. The scree plot indicated a three-factor solution; eigenvalues = 6.72, 3.22, 1.69; representing 37%, 18%, and 9% of the variance, respectively. Active coping and planning subscale items loaded onto one factor, which was aggregated, and will henceforth be called proactive planning to maintain consistency with subsequent studies.

Stress and anxiety

The Perceived Stress Scale (10 items; Cohen et al., 1983) captured the frequency of stressful experiences and emotions during the past month; rated from never to very often. Trait anxiety was assessed with seven items from the International Personality Item Pool (e.g., “I am afraid that I will do the wrong thing”; Goldberg et al., 2006).

Results

As expected (see Table 1), MIL correlated positively with proactive planning and positive reinterpretation. MIL correlated negatively with emotion-focused coping, perceived stress, and trait anxiety. Next, analyses probed whether MIL would be associated with each coping strategy, controlling for the shared overlap among coping strategies (e.g., MIL’s association with positive reinterpretation, controlling for proactive planning and emotion-focused coping). Controlling for all other coping strategies, MIL remained significantly associated with proactive planning, positive reinterpretation, and emotion-focused coping (Table 1).

Table 2 shows the results of mediation models (using the PROCESS macro with 10,000 bootstrapped resamplings; Hayes, 2022) assessing whether coping strategies mediate MIL’s association with perceived stress or trait anxiety. Positive reinterpretation, proactive planning, and emotion-focused coping mediated the association between MIL and perceived stress. Only emotion-focused coping mediated the association between MIL and trait anxiety.

Table 2.

Mediation Models Predicting Stress Outcomes Across Studies from Meaning in Life.

Mediators	Meaning in life to mediator	Mediator to DV	Direct effect	Indirect effect
Study 1	DV: Perceived stress
Positive reinterpretation	0.45 (0.04)***	−0.18 (0.05)***	−0.47 (0.05)***	−0.08 [−0.13, −0.03]
Proactive planning	0.36 (0.04)***	−0.16 (0.05)***	−0.49 (0.05)***	−0.06 [−0.10, −0.02]
Emotion-focused coping	−0.31 (0.04)***	0.67 (0.04)***	−0.34 (0.04)***	−0.21 [−0.27, −0.15]
	DV: Trait anxiety
Positive reinterpretation	0.46 (0.04)***	−0.12 (0.07)	−0.56 (0.07)***	−0.06 [−0.13, 0.02]
Proactive planning	0.35 (0.04)***	−0.10 (0.07)	−0.58 (0.07)***	−0.04 [−0.09, 0.02]
Emotion-focused coping	−0.31 (0.04)***	0.99 (0.06)***	−0.31 (0.06)***	−0.31 [−0.40, −0.22]
Study 2	DV: Distressed emotions
Positive reinterpretation	0.30 (0.06)***	−0.23 (0.12)	−0.36 (0.11)**	−0.07 [−0.17, 0.005]
Coping self-efficacy	0.32 (0.06)***	−0.54 (0.11)***	−0.26 (0.11)*	−0.17 [−0.28, −0.08]
Proactive planning	0.35 (0.06)***	−0.27 (0.12)*	−0.34 (0.12)**	−0.09 [−0.21, −0.005]
Threat/emotion coping	−0.15 (0.06)*	0.80 (0.10)***	−0.31 (0.10)**	−0.12 [−0.24, −0.02]
Study 3	DV: Distressed emotions (post-exam)
Positive reinterpretation	0.21 (0.87)*	−0.30 (0.12)*	−0.05 (0.12)	−0.06 [−0.14, 0.003]
Coping self-efficacy	0.19 (0.07)*	−0.29 (0.13)*	−0.07 (0.12)	−0.06 [−0.13, 0.002]
Study 4 (multilevel mediation results)	DV: Distressed emotions
Positive reinterpretation	0.40***	−0.09***	−0.18***	−0.06 [−0.10, −0.02]
Coping self-efficacy	0.37***	−0.18***	−0.16***	−0.09 [−0.13, −0.05]
Proactive planning	0.36***	−0.04	−0.22***	0.001 [−0.04, 0.04]
	DV: COVID-19-specific stress
Positive reinterpretation	0.40***	−0.06*	−0.08**	−0.04 [−0.07, −0.005]
Coping self-efficacy	0.37***	−0.10***	−0.06**	−0.05 [−0.08, −0.02]
Proactive planning	0.36***	−0.07*	−0.09**	−0.03 [−0.06, 0.002]
Study 5	DV: Distressed emotions
Coping self-efficacy	0.35 (0.04)***	−0.13 (0.08)	−0.37 (0.07)***	−0.05 [−0.10, 0.01]
Threat/emotion coping	−0.21 (0.04)***	0.81 (0.06)***	−0.24 (0.06)**	−0.17 [−0.25, −0.10]

Note. 95% confidence intervals are shown in brackets (credibility intervals for Study 4). CIs for bolded indirect effects do not include zero. Standardized predictors were used in models. Study 4 models included random intercepts and slopes and a fixed effect of survey number (time) entered as a control. Study 5 analyses included a measure of state meaning in life. Coping variables were only tested as mediators if they shared significant bivariate associations with MIL and stress-relevant outcomes. DV = dependent variable; COVID-19 = coronavirus disease 2019.

p < .05. **p < .01. ***p ≤ .001.

Brief Discussion

Study 1 provides initial evidence for MIL’s association with adaptive coping strategies and stress in a broad sample. Examining MIL’s association with coping dimensions regarding a specific stressor would help establish the robustness of these associations.

As reported in the supplemental material, in Study 1, we also tested multiple variables that might account for MIL’s association with coping strategies and stress, including life satisfaction, positive affect, optimism, future time perspective, self-efficacy, perceived control, emotional reappraisal, social support, conscientiousness, resilience, and religiosity. Although these variables related to MIL and coping in theoretically expected directions, none consistently accounted for MIL’s association with coping strategies and stress. Optimism, self-efficacy, conscientiousness, and resilience were most influential in accounting for these associations, revealing the difficulty and complexity of identifying why MIL—a multifaceted construct—matters to varied coping strategies and stress.

Study 2

In Study 2, participants described a recently experienced, difficult situation, and then rated coping dimensions and distress. If MIL is associated with these varied coping dimensions, these data would provide additional evidence that MIL is broadly associated with coping processes in common stressful situations.

Method

MTurk participants, N = 232; 64.2% women, 35.3% men; M (SD) age = 35.67 (11.46) rated MIL and demographics. Then, they wrote a few sentences describing the most challenging, difficult, and stressful situation they experienced during the past month (after Park, 2006). Examples were provided (e.g., getting fired, getting sick). Afterward, participants rated current distressed emotions (anxious, worried, and nervous). Table 3 shows descriptive statistics.

Table 3.

Correlations Between Measures and Regression Coefficients for Multivariate Analyses, Study 2.

Variables	1	2	3	4	5	6
1. Meaning in life	.91
2. Positive reinterpretation	.31**	.90
3. Coping self-efficacy	.33**	.65**	.88
4. Threat/emotion-coping	−.16*	−.20*	−.43**	.83
5. Proactive planning	.36**	.58**	.68**	−.23**	.89
6. Distressed emotions	−.25**	−.19*	−.36**	.48**	−.22**	.92
β for meaning^a	—	.07	.04	−.04	.13*	—
R² change	—	.004	.001	.002	.015*	—
M (SD)	4.78 (1.52)	4.62 (1.27)	4.73 (1.31)	4.77 (1.09)	4.81 (1.42)	3.90 (1.77)

Note. N = 232. Alpha reliabilities are shown on the diagonal.

These are regression coefficients for MIL entered in models predicting the corresponding coping dimensions (positive reinterpretation, coping self-efficacy, threat/emotion-coping, or proactive planning) when controlling for the other three coping dimensions listed.

p* < .05. **p ≤.001.

Measures

Coping

Coping items (28 items total; adapted from Carver et al., 1989; Endler & Parker, 1994; Peacock & Wong, 1990; see supplemental material) referencing participants’ recalled stressor, were rated in randomized order. As preregistered, items were submitted to principal axis factoring with varimax rotation to identify interpretable subscales. Items loaded onto five factors, eigenvalues = 9.80, 3.90, 2.10, 1.41, and 1.14; representing 35%, 14%, 7%, 5%, and 4% of the variance, respectively. Three factors represented positive reinterpretation, coping self-efficacy, and proactive planning. The other two factors represented both threat appraisals and anxiety/distress (10 items). These items were conceptually very similar and internally reliable (α = .83). Extracting four factors resulted in four interpretable factors exhibiting minimal cross loadings (>.30). Final composite coping measures (representing these factors) included positive reinterpretation (eight items, e.g., “I would look for something positive in this experience.”), coping self-efficacy (six items, e.g., “I would overcome this situation successfully.”), proactive planning (four items, e.g., “I took concrete actions to deal with this situation”), and threat/emotion-coping (10 items, e.g., “I would feel hopeless in this situation.”).

Results

MIL correlated positively with positive reinterpretation, coping self-efficacy, and proactive planning, and negatively with threat/emotion-coping and distressed emotions (Table 3). Controlling for all other coping strategies, MIL remained significantly associated only with proactive planning (Table 3). Coping self-efficacy, proactive planning, and threat/emotion-coping mediated the association between MIL and distressed emotions (Table 2).

Brief Discussion

MIL was linked to coping dimensions (positive reinterpretation, coping self-efficacy, proactive planning, and threat/emotion-coping) and distress in response to recently experienced difficult situations. The stressors rated in Studies 1 and 2 varied greatly. Study 3 addressed this issue.

Study 3

Study 3 evaluated whether MIL would be associated with coping regarding an exam, a common stressor for college students. Exams are a naturally occurring stressor, providing external validity and high situational consistency. Extending the previous studies, Study 3 employed a new participant sample (college students) and tested associations over a longer time period (before and after an exam). We predicted that MIL would relate to adaptive coping dimensions before and after the exam—specifically higher positive reinterpretation, coping self-efficacy, and proactive planning and lower threat/emotion-coping—and to lower distressed emotions post-exam.

Method

Students in two undergraduate psychology courses at a university in the Midwestern United States completed this study (N = 207 for Time 1 measures; N = 164 for Time 2 measures). The final sample included those completing measures at both time points, N = 156; 71% women, 29% men; M (SD) age = 19.64 (1.32). Sample size was determined by the number of students in these courses. Table 4 shows descriptive statistics. Coping items appear in the supplemental material.

Table 4.

Correlations Between Well-Being and Coping Variables Pre- and Post-Exam (Time 1 and Time 2) and Regression Coefficients for Multivariate Analyses, Study 3.

Variables	1	2	3	4	5	6	7	8	9	10
1. Meaning in life	.90
2. Positive reinterpretation T1	.31***	.67
3. Coping self-efficacy T1	.25***	.43***	.77
4. Proactive planning T1	.40***	.53***	.30***	.87
5. Threat/emotion-coping T1	−.05	−.00	−.36***	−.00	.80
6. Positive reinterpretation T2	.21**	.34***	.05	.19*	−.13	—
7. Coping self-efficacy T2	.20*	.27***	.15	.28***	−.12	.45***	.75
8. Threat/emotion-coping T2	−.08	−.00	−.17*	.05	.42***	−.25***	−.54***	.78
9. Positive emotions T2	.22**	.21**	.00	.13	−.10	.33***	.53***	−.31***	.85
10. Distressed emotions T2	−.09	−.06	−.14	−.09	.35***	−.22**	−.19*	.52***	−.32***	.88
11. Exam grade	.01	.12	.12	.11	−.07	.10	.43**	−.48**	.31**	−.09
β for meaning^a	—	.07	.09	.26***	−.003	.13	.10	.03	—	—
R² change	—	.004	.007	.059***	.000	.015	.009	.001	—	—
M (SD)	4.85 (1.39)	5.14 (1.09)	5.00 (0.95)	4.44 (1.27)	4.38 (1.08)	4.90 (1.35)	4.77 (1.13)	3.70 (1.46)	4.31 (1.20)	4.21 (1.53)

Note. N = 156 for analyses between Time 1 and Time 2 variables; N = 211 for Time 1 analyses. Alpha reliabilities are shown on the diagonal.

These are regression coefficients for MIL entered in models predicting the corresponding coping dimensions when controlling for other coping dimensions at the same time point (Time 1: proactive planning; Time 1 and 2: positive reinterpretation, coping self-efficacy, and threat/emotion-coping).

p* < .05. **p < .01. ***p ≤ .001.

Time 1 measures

Participants rated MIL, embedded within other well-being measures. Then, they rated coping strategies regarding exam preparation, including positive reinterpretation (three items), coping self-efficacy (five items), and threat/emotion-coping (six items). Proactive planning (five items) was measured only at Time 1, given items’ anticipatory nature.

Time 2 measures

Approximately 2 to 3 weeks later, participants completed an exam. Immediately afterward, they rated distressed emotions (anxious, worried, and stressed) and positive emotions (happy, satisfied, and proud). Then, they rated the coping strategies they used during the exam, including positive reinterpretation (one item), coping self-efficacy (four items), and threat/emotion-coping (three items). The average score on the exam was 81.66 (100 total; SD = 13.14). See the supplemental material for exam score analyses.

Results

Preliminary

Students completing both Time 1 and 2 measures and those completing only Time 1 measures did not differ on MIL, t(209) = 0.61, p = .54. Among those completing both measures, classes did not differ on MIL, coping, or post-exam emotions, ts(154) < ± 1.98, ps > .05, so class data were aggregated.⁵

Primary

As Table 4 shows, MIL (measured at Time 1) correlated positively with Time 1 and Time 2 positive reinterpretation, coping self-efficacy, and proactive planning, consistent with previous results (proactive planning was only measured at Time 1). MIL was unrelated to threat/emotion-coping at both time points. MIL correlated positively with Time 2 positive emotions. Although MIL was unrelated to Time 2 distressed emotions overall, MIL could be related to distress through its links to Time 2 positive reinterpretation and coping self-efficacy, which correlated negatively with distressed emotions. However, Time 2 positive reinterpretation and coping self-efficacy did not mediate MIL’s association with distressed emotions (Table 2).

Analyses assessed MIL’s association with each coping dimension, controlling for others (within each time point). MIL was only significantly associated with Time 1 proactive planning, controlling for all other Time 1 coping measures (Table 4).

Prospective Analyses

Analyses examined how controlling for Time 1 coping measures affected the association between Time 1 MIL and the coping measure at Time 2. Coping measures were applicable to the current time frame and thus differed between Times 1 and 2. Controlling for Time 1 coping self-efficacy, β = .10, p = .25, MIL remained significantly associated with Time 2 coping self-efficacy, β = .18, p = .04; ΔR² = .03. Controlling for Time 1 positive reinterpretation, β = .30, p < .001, MIL was unrelated to Time 2 positive reinterpretation, β = .10, p = .23; ΔR² = .008.

Brief Discussion

In Study 3, MIL was associated with positive reinterpretation and coping self-efficacy, both pre-exam and post-exam. MIL prospectively predicted Time 2 coping self-efficacy. These results help assuage concerns that the results of Studies 1 and 2 were due to measures being completed at the same time. Study 3 provided additional evidence that MIL’s association with proactive planning is independent of other coping strategies. MIL was unrelated to threat/emotion-coping, in contrast to Studies 1 and 2. Study 3 had a relatively small sample size, limiting power.

Study 4

Study 4 examined whether within-person fluctuations in daily MIL predict coping strategies and stress. We also assessed trait-level MIL, measured before the daily study period. Although daily and trait MIL measures are highly correlated (Newman et al., 2018), they could have distinct links to coping processes. We predicted that within-person variations in daily MIL would be associated with adaptive coping responses and reduced stress, consistent with between-person associations found in Studies 1 to 3.

MIL may be an antecedent and outcome of adaptive coping (Park et al., 2008), a possibility the previous studies could not address. Study 4 examined time-lagged associations between daily MIL and coping to better understand potential causality. Daily designs do not establish causality, but this approach allowed us to probe whether MIL or coping temporally precedes the other (controlling for each at a prior time). Temporal precedence is necessary but not sufficient for establishing causality, as third variables may still potentially explain relationships (West & Hepworth, 1991). Daily adaptive coping responses might facilitate higher future MIL (controlling for past MIL), just as MIL may predict future adaptive coping (controlling for past coping).

Study 4 occurred during the coronavirus disease 2019 (COVID-19) pandemic. We tested whether MIL would predict reduced daily COVID-19-related stress. We used general coping measures (vs. COVID-19-specific measures) because responses to our initial survey indicated that COVID-19 was not participants’ most prominent stressor (see supplemental material).

Method

Participants from an undergraduate research pool at a large university in the Midwestern United States, N = 251 post-exclusions described in the following; 63% women, 37% men; M (SD) age = 20.07 (1.16) completed this study for research participation credit. We ran the maximum number of participants possible to reach this sample size. The sample included 12.7% students residing outside of the United States. There were small sample differences on stress but not on other variables (see supplemental material), so, as preregistered, we retained the full sample to maximize statistical power and sample diversity.

Measures

Part 1 trait MIL

Participants rated trait MIL in an initial survey.

Part 2 daily measures

Approximately one week later, participants were emailed daily surveys for 12 consecutive days at 6:00 p.m. in their local time zone. Survey links expired at 2:00 a.m. Some participants completed makeup surveys to meet the 11-survey requirement for earning research credit (see supplemental material for description).

Daily measures were completed in the order described in the following, with instructions to rate items according to one’s experiences that day, from the time they awoke to the time of survey completion. All items were rated on 7-point scales.

Distressed emotions

Participants rated how much they felt stressed and anxious that day, from very rarely or never to very often or always.

Daily MIL

Two items (“Today, how meaningful did your life feel?” “Today, how much did you feel like your life has purpose?” Kashdan & Steger, 2007), rated from not at all to extremely, captured daily MIL.

Coping

Participants were instructed to think about their current life and goals and then rate the coping strategies (adapted from Carver et al., 1989) employed that day, from strongly disagree to strongly agree. These included positive reinterpretation (“Today, I felt that the situation I’m in will help me become stronger.”; “Today, I tried to look for something positive in my current situation.”), coping self-efficacy (“Today, I felt I had the ability to do well handling my current situation.”), and proactive planning (“Today, I have a plan of action for working toward my current goals.”; “Today, I concentrated my efforts on doing what I can to succeed in my current situation.”). Threat/emotion coping was not measured due to time constraints and the weaker associations exhibited in earlier studies. Daily emotional support was measured for exploratory purposes and is not discussed further.

COVID-19 stress

Participants rated how stressful the COVID-19 situation was to them overall (“your life, academic experience, work, etc.”) from not at all stressful to extremely stressful.

Exclusions

Survey responses were excluded from analyses for one or more of the following (preregistered) reasons: <45 s completion time (n = 4 responses), <50% of items completed, duplicate survey responses within participants (retaining the first survey completed; n = 19 dropped for this and the previous reason), enrollment in first author’s current class (n = 2 participants). Participants (n = 25) who completed fewer than four total surveys were excluded to mitigate unreliability due to noncompliance (Nezlek, 2012). Our preregistered exclusion rule regarding entering identical responses within questionnaires would have been too stringent, resulting in very high exclusions. Instead, we excluded responses containing identical ratings for >80% of items with 1 to 7 rating scales (n = 51, 1.8% of responses).

Results

Preliminary Analyses

Analyses included 2,731 reports across 251 participants (average of 11 reports per participant). We used multilevel modeling, using Mplus, as daily survey responses were nested within participants. Unconditional (null) models with key variables listed as dependent variables were used to generate variance estimates. Intercepts were entered as a random factor in models. Reliability estimates were calculated using multilevel confirmatory factor analyses (Geldhof et al., 2014), which generated level-specific omega (ω) reliabilities. Measures with only two items were constrained to be equal at both levels. Reliabilities could not be calculated for single-item measures. Residuals were constrained to be >0 to remedy model fitting problems (where applicable) and when estimating coping self-efficacy’s variance (due to negative variance estimates without constraint).

Table 5 shows descriptive statistics. Approximately, 44% of the variability in MIL was within-person. Around 31% to 59% of the variability in coping and stress variables was within-person. Within-person reliabilities for MIL and coping variables were moderate to high.

Table 5.

Descriptive Statistics for Daily Measures, Study 4.

	Variance			1-ICC	Reliability, ω
Variables	M	Within	Between	1-ICC	Within	Between
Meaning in life	4.58	0.84	1.07	.44	.85	.99
Coping measures
Coping self-efficacy	5.02	0.93	0.74	.55	—	—
Positive reinterpretation	5.08	0.66	0.65	.50	.63	.93
Proactive planning	5.07	0.72	0.63	.53	.67	.95
Distressed emotions	3.83	1.58	1.11	.59	.77	.92
COVID-19 stress	3.55	0.98	2.20	.31	—	—

Note. N = 2,731 responses. Coping self-efficacy and COVID-19 stress were one-item measures. 1-ICC values represent the proportion of total variability that is within-person. Means represent average scores on aggregate variables across all participants. ICC = intraclass correlation coefficient; COVID-19 = coronavirus disease 2019.

Primary Analyses

Level-1 (daily) measures were mean-centered within participants (Enders & Tofighi, 2007). Models included random intercepts and slopes, enabling participants to have different mean levels of outcome variables and different associations (slopes) between predictor and outcome variables. Survey number (time) was entered as a control variable (fixed effect) to account for potential linear trends. Visual inspection suggested no apparent time trends in MIL, coping, or stress over the study period. The supplemental material shows within-participant correlations among coping variables.

Table 6 shows that, within-participants, daily MIL was significantly associated with coping dimensions, distressed emotions, and COVID-19 stress. The variance of these slopes was significant but small, suggesting only minor differences in the associations between MIL and coping between participants. Multivariate analyses showed that, controlling for all other coping strategies, daily MIL significantly related to coping self-efficacy, proactive planning, and positive reinterpretation; bs > 0.11, ts > 6.94, and ps < .001. See the supplemental material for full results.

Table 6.

Within-Person Associations Between Daily Meaning in Life and Coping.

Outcomes	Within-person estimates			Slope variance (between-person variability)
Outcomes	Coefficient (SE)	95% CI	t ratio	Coefficient (SE)	95% CI	t ratio
Coping self-efficacy	0.41 (0.03)	[0.35, 0.46]	14.96	0.07 (0.01)	[0.04, 0.10]	5.02
Positive reinterpretation	0.37 (0.02)	[0.33, 0.42]	16.33	0.05 (0.01)	[0.03, 0.07]	4.90
Proactive planning	0.35 (0.03)	[0.30, 0.40]	14.15	0.06 (0.01)	[0.04, 0.08]	4.75
Distressed emotions	−0.32 (0.04)	[−0.39, −0.25]	9.06	0.11 (0.02)	[0.07, 0.16]	4.69
COVID-19 stress	−0.13 (0.03)	[−0.19, −0.08]	4.82	0.05 (0.01)	[0.02, 0.08]	3.54

Note. All models include random intercepts and slopes for the predictor variable and a fixed effect of survey number (time) entered as a control. CI = confidence interval; COVID-19 = coronavirus disease 2019.

All ps ≤ .001.

Lagged analyses between daily MIL and coping

Lagged analyses examining MIL and coping variables measured on consecutive days probed the potential temporal direction of these associations. For example, MIL on day n − 1 was used to predict coping on day n, controlling for coping on day n − 1. If the previous day’s MIL significantly predicts the next day’s coping controlling for the previous day’s coping, it would provide suggestive evidence that MIL causally precedes coping. Because coping might also predict MIL, we tested reverse-effects (coping on day n − 1 predicting MIL on day n, controlling for MIL on day n − 1). Testing these possibilities helped illuminate temporal precedence and potential causal directions between MIL and coping.

We computed separate models for each coping variable. As we were interested in within-person effects only, random slopes were not included. As Table 7 shows, the previous day’s MIL significantly predicted the next day’s coping self-efficacy, proactive planning, and positive reinterpretation but not distress or COVID-19 stress (controlling for each variable on the previous day). The previous day’s positive reinterpretation and proactive planning also significantly predicted the next day’s MIL (controlling for MIL on the previous day). Thus, MIL shares significant bidirectional relationships with positive reinterpretation and proactive planning over time. The lagged coefficients for these prospective links did not significantly differ from each other (compared using lavaan package in R; Table 7). The comparable strength of these bidirectional associations suggests that both temporal directions are equally supported.

Table 7.

Lagged Associations Between Coping Strategies, Stress, and Meaning in Life.

	Predicting next day’s meaning in life from previous day’s coping/stress				Predicting next day’s coping/stress from previous day’s meaning in life				Difference between coefficients [95% CI]	p
Variables	Coefficient (SE)	95% CI	t ratio	p	Coefficient (SE)	95% CI	t ratio	p	Difference between coefficients [95% CI]	p
Coping self-efficacy	0.04 (0.02)	[−0.006, 0.09]	1.70	.089	0.08 (0.03)	[0.03, 0.13]	3.12	.002	−0.04 [−0.12, 0.03]	.252
Positive reinterpretation	0.13 (0.03)	[0.07, 0.18]	4.63	<.001	0.06 (0.02)	[0.01, 0.10]	2.52	.012	0.07 [−0.003, 0.15]	.059
Proactive planning	0.09 (0.03)	[0.04, 0.14]	3.34	.001	0.07 (0.02)	[0.03, 0.12]	3.21	.001	0.02 [−0.06, 0.09]	.656
Distressed emotions	−0.01 (0.02)	[−0.05, 0.02]	0.67	.501	−0.03 (0.03)	[−0.09, 0.03]	1.11	.265	—	—
COVID-19 stress	0.00 (0.02)	[−0.04, 0.04]	0.01	.992	0.02 (0.02)	[−0.03, 0.07]	0.70	.484	—	—

Note. Models control for the dependent variable on the previous day and survey number (time). CI = confidence interval; COVID-19 = coronavirus disease 2019.

Mediation models

Multilevel mediation analyses (using multilevel structural equation modeling [MSEM], Preacher et al., 2010) probed whether positive reinterpretation, coping self-efficacy, or proactive planning mediated MIL’s association with distress or COVID-19 stress. Models used Bayes’ estimation (to account for the non-normality of indirect effects) with latent mean-centered predictors (Muthén & Asparouhov, 2012). As shown in Table 2, coping self-efficacy and positive reinterpretation mediated the effect of MIL on distress and COVID-19 stress (in separate models) as the Bayesian credibility intervals for the models’ indirect effects excluded zero. Thus, coping dimensions account for MIL’s negative association with distress.

Trait-level meaning in life

Trait MIL (Level-2 measure standardized prior to analyses; Nezlek, 2012) was associated with daily MIL, b (SE) = 0.62 (0.06), p < .001, 95% confidence interval (CI) = [0.51, 0.73], t = 10.84. Controlling for time, trait MIL was significantly associated with daily coping self-efficacy, b (SE) = 0.41 (0.05), p < .001, 95% CI = [0.30, 0.51], t = 7.72; proactive planning, b (SE) = 0.37 (0.05), p < .001, 95% CI = [0.28, 0.47], t = 7.68; positive reinterpretation, b (SE) = 0.39 (0.05), p < .001, 95% CI = [0.29, 0.48], t = 7.92; distressed emotions, b (SE) = −0.38 (0.07), p < .001, 95% CI = [−0.51, −0.24], t = 5.52; and COVID-19-specific stress, b (SE)= −0.20 (0.10), p = .035, 95% CI = [−0.39, −0.02], t = 2.11. Thus, trait MIL is associated with daily adaptive coping responses and reduced stress, similar to daily MIL.

Explanatory variable analyses

We also examined whether trait conscientiousness or daily positive affect, optimism, or life satisfaction (measured for another project) would account for the within-person associations between daily MIL and coping strategies, distressed emotions, or COVID-19 stress. As reported in the supplemental material, controlling for optimism, positive affect, life satisfaction, and (trait) conscientiousness, daily MIL remained significantly associated with proactive planning, positive reinterpretation, and coping self-efficacy. Daily MIL was no longer negatively correlated with distressed emotions or COVID-19 stress when controlling for all of these explanatory variables.

Brief Discussion

Within participants, daily MIL was positively associated with coping self-efficacy, proactive planning, and positive reinterpretation, and it was negatively associated with distressed emotions and COVID-19 stress. Associations were similar to the between-person relationships observed in Studies 1 to 3, corroborating MIL’s potential adaptive coping benefits. Coping self-efficacy and positive reinterpretation mediated the effect of MIL on distress and COVID-19 stress.

Lagged models showed that daily MIL predicted subsequent coping self-efficacy, proactive planning, and positive reinterpretation, demonstrating the robustness of MIL’s link to coping over time. Positive reinterpretation and proactive planning also predicted subsequent MIL, showing that MIL is both an antecedent and outcome of adaptive coping responses. Study 5 aimed to test the potential causal effect of MIL on adaptive coping.

Study 5

To directly probe causation, Study 5 investigated whether experimentally manipulating MIL would influence coping with a stressor. Participants completed difficult, timed typing tasks for a potential financial reward and then rated distress and coping. We predicted that participants randomly assigned to a meaning boost condition (prior to the task) would exhibit more adaptive appraisals of the task—heightened positive reinterpretation and coping self-efficacy and lower threat/emotion-coping—than participants in a meaning threat condition. We also measured trait MIL (prior to the manipulation) to test whether it would relate to adaptive coping. Study 5 participants experienced the same stressor, further addressing whether MIL was differentially related to personally recalled (Studies 1, 2, and 4) versus uniform stressors (Study 3).

Method

Participants on MTurk, N = 457; 61% women, 38% men; M (SD) age = 38.30 (13.70) rated MIL and demographics and completed measures in the order described below.

Measures

Meaning manipulation

Participants were assigned randomly to meaning boost (n = 153), meaning threat (n = 156), or control conditions (n = 148). Meaning boost participants described reasons why their life is meaningful and purposeful (adapted from Burrow et al., 2016). Meaning threat participants described why their life (or someone else’s life, if they did not find this true for themselves) is meaningless. Control participants described a typical weekday (adapted from Ward & King, 2016). Then, participants rated a state MIL manipulation check, ranging from 1 (not at all meaningful) to 7 (extremely meaningful).

Challenging task

Participants were asked to quickly and accurately type three passages (1 min per passage) featuring jargon-laden descriptions of computer science and statistics (presented as image files to prevent copy and pasting; adapted from Ward & King, 2018). If their overall performance (speed and accuracy) on the three passages was in the top 10% with ≥95% accuracy, they would receive a US$0.25 bonus. Pilot testing suggested that task difficulty and stressfulness compared favorably with other potential stressful online tasks.

Most (96%) participants attempted all three passages (i.e., typing at least the first three words accurately); 2% attempted two passages. Participants who attempted <2 passages (reflecting low task engagement) were excluded from analyses (n = 10, final N = 447). This was an unexpected deviation from preregistered exclusions but seemed prudent considering poor response quality.

Coping

Participants rated current distressed emotions (anxious, worried, and nervous) and coping strategy/appraisal dimensions (appearing in randomized order), including positive reinterpretation (four items), coping self-efficacy (nine items), and threat/emotion coping (five items). See the supplemental material for items. Three items assessed perceived performance (e.g., “I think my overall performance was better than most other people on the task”). Table 8 shows descriptive statistics.

Table 8.

Correlations Between Measures and Regression Coefficients for Multivariate Analyses, Study 5.

Variables	1	2	3	4	5	6	7
1. Trait meaning in life	.92
2. State meaning in life	.75**	—
3. Positive reinterpretation	.27**	.30**	.86
4. Coping self-efficacy	.30**	.35**	.62**	.88
5. Threat/emotion-coping	−.23**	−.22**	−.15**	−.42**	.92
6. Perceived performance	.16**	.16**	.21**	.51**	−.54**	.84
7. Distressed emotions	−.29**	−.28**	−.04	−.17**	.55**	−.22**	.89
β for state meaning^a	—		.10*	.13**	−.10*	—	—
R² change	—		.009*	.015**	.009*	—	—
M (SD)	4.95 (1.61)	4.85 (1.77)	4.29 (1.42)	5.34 (1.04)	3.47 (1.63)	3.98 (1.67)	2.86 (1.53)

Note. N = 446. Alpha reliabilities are shown on the diagonal.

These are regression coefficients for state MIL entered in models predicting the corresponding coping dimensions (positive reinterpretation, coping self-efficacy, or threat/emotion-coping) when controlling for the other two coping dimensions.

p* < .05. **p ≤ .001.

Results

Conditions significantly differed on the state MIL manipulation check, F(2, 444) = 10.03, p < .001. The meaning boost led to higher state MIL than control and meaning threat conditions, ps < .001 (Bonferroni corrected), which did not differ from each other, p = 1.00. Conditions did not differ on positive reinterpretation, coping self-efficacy, threat/emotion coping, distressed emotions, or perceived performance, Fs < 0.78, ps > .46. See supplemental material for means. Neither trait nor state MIL interacted with (dummy coded) meaning boost/threat conditions to predict coping strategies or distressed emotions, interaction βs < ± .12, ps > .07. Consequently, we collapsed across conditions for further analyses.

Correlational analyses examined both trait and state MIL, which were highly correlated, r = .75, to evaluate whether they were similarly linked to coping variables. As Table 8 shows, trait and state MIL correlated positively with positive reinterpretation, coping self-efficacy, and perceived performance, and negatively with threat/emotion-coping and distressed emotions. Controlling for all other coping dimensions (see Table 8), state MIL remained significantly associated with positive reinterpretation, coping self-efficacy, and threat/emotion coping.

Mediation tests examined whether coping dimensions accounted for the association between state MIL and distressed emotions. Analyses collapsed across conditions due to the lack of MIL X condition interactions. As shown in Table 2, only threat/emotion-coping mediated the association between MIL and distressed emotions.

Brief Discussion

Contrary to predictions, the meaning manipulations did not influence coping or distress. Two potential reasons may explain these unexpected results. First, although the manipulations influenced the state MIL manipulation check, they may have been insufficient to induce the broad feeling that one’s life is meaningful (or not). Changes in state MIL could reflect demand characteristics. Second, completing the cognitively taxing task before rating coping and distress may have eliminated condition effects. We describe other potential approaches for manipulating MIL in the “General Discussion” section.

Nevertheless, Study 5 showed that, assessed at either the state or trait-level, MIL correlated positively with positive reinterpretation and coping self-efficacy, and negatively with threat/emotion-coping and distressed emotions, in the context of a standardized, stressful task.

General Discussion

MIL is associated with myriad health and well-being benefits. Using varied methods and samples, these studies investigated MIL’s association with three broad coping strategies, coping self-efficacy, and distress in relation to common, everyday stressors. Across studies, MIL was consistently linked to positive reinterpretation, proactive planning, and coping self-efficacy in different stressful situations. These consistent links are especially notable because the specific coping items referred to diverse challenges and stressors (e.g., general stressors, exam, and timed typing task). Across studies, MIL was related to threat/emotion-coping (except in Study 3). This investigation provides clarity on the coping dimensions that are reliably linked to MIL in the context of everyday stressors.

MIL was robustly correlated with adaptive coping strategies within the context of common daily stressors, similar to its role in adaptive coping with severe trauma. Although past research documented MIL’s relation to threat/emotion coping regarding severe stressors, we found less consistent associations for mild stressors. Means for threat/emotion coping were generally low across studies, suggesting that mild stressors do not elicit strong negative emotions. MIL did not prospectively predict distressed emotions (Studies 3 and 4), although it shared cross-sectional associations with distress and other stress-relevant outcomes. MIL may be less relevant to future distress in relation to common everyday challenges.

Mechanisms

Across studies, MIL’s association with distressed emotions and other stress-relevant outcomes was most consistently mediated by threat/emotion-coping and less consistently mediated by positive reinterpretation, proactive planning, and coping self-efficacy (Table 2; see supplemental material for simultaneous multiple mediator models). Thus, MIL may help reduce stress by mitigating perceptions of threat and preoccupation with negative emotions. Indeed, emotion-focused coping is more consistently linked to reduced stress than problem- or meaning-focused coping (e.g., Park, 2010). In Study 4, MIL’s association with daily distress and COVID-19-specific stress was mediated by positive reinterpretation and coping self-efficacy. These results illustrate that meaning-focused coping and confidence in one’s capacity to cope are specific mechanisms through which MIL provides stress reduction benefits in daily life.

The precise features of MIL that explain its association with adaptive coping strategies are difficult to specify (e.g., Hooker et al., 2018; Krause, 2007), reflecting the widely recognized complexity of identifying how and why meaning-making influences coping (Park, 2010; Silver & Updegraff, 2013; Updegraff et al., 2008). Numerous cognitive, affective, and motivational aspects of MIL may account for its links to coping and stress (see Figure 1). Positive interpretation, coping self-efficacy, and proactive planning are distinguishable coping dimensions and different mechanisms may account for MIL’s association with each. This investigation did not endeavor to identify these mechanisms. Exploratory Study 1 analyses (see supplemental material) suggested that no single explanatory mechanism consistently accounts for MIL’s association with coping dimensions, although many fully or partially accounted for these links (e.g., self-efficacy, optimism, and conscientiousness).

Probing the diverse mechanisms that explain MIL’s links to coping and distress requires methods and statistical approaches that can address the complex dynamics among these variables (e.g., Diener et al., 2017; Hooker et al., 2018). Prospective longitudinal studies could provide clarity on the processes and mechanisms linking MIL to coping and distress, potentially evaluating the mechanisms uncovered as most influential in Study 1’s exploratory analyses (e.g., optimism). Future research might also fruitfully probe whether MIL’s link to coping strategies accounts for its association with health and disease. MIL may be linked to health outcomes because it mitigates stressors’ negative impacts (Hooker et al., 2018).

Causal Links Between Meaning and Coping

We examined the association between MIL and coping, using cross-sectional, prospective, daily report, and experimental designs. Individual differences in MIL were related to coping dimensions across studies. Certainly, conclusions about causality remain tentative. In Study 5, manipulated meaning did not affect coping, and thus failed to show a causal link between MIL and coping. MIL is relatively durable over time and not easily changed by extraneous influences (Honkinen et al., 2008). MIL may be easier to manipulate through related constructs (e.g., gratitude) or by targeting a specific component (e.g., purpose, Burrow & Hill, 2013).

Although MIL is believed to causally facilitate adaptive coping, it is also plausible that adaptive coping enhances MIL (e.g., Hooker et al., 2018; Park et al., 2008). Study 4 demonstrated bidirectional associations between MIL and coping over time. MIL predicted subsequent positive reinterpretation and proactive planning, and these coping dimensions similarly predicted subsequent MIL. MIL predicted subsequent coping self-efficacy, but coping self-efficacy did not predict subsequent MIL (although this effect was marginal and the lagged coefficients did not significantly differ, see Table 7). Experiments and intervention studies could provide greater insight into these intriguing bidirectional associations.

Limitations and Future Directions

Some features of these studies may limit the generalizability of conclusions. Participants were undergraduate students and adults recruited through MTurk. Although MTurk participants’ personality and mental health are largely representative of the general U.S. population, they do report higher negative affect and lower social engagement (McCredie & Morey, 2019). These differences could have influenced our results (e.g., MTurk samples exhibiting heightened reactions to stressors). In addition, most participants were from the United States, and it is uncertain whether MIL would be similarly linked to coping and stress in other countries.

We used different coping items across studies because of the distinct stressful, challenging situations examined and the varied study contexts. Studies 2, 3, and 5 included some ad hoc coping items. Our use of varied items underscores our interest in the underlying constructs measured (rather than scales). The observed relationships between MIL and coping were largely consistent across studies, but measurement differences might have affected results. It would be valuable to address MIL’s association with coping strategies beyond the dimensions we investigated, such as acceptance or seeking social support. MIL has been linked to improved social support (Carver & Connor-Smith, 2010), which may be especially important during stress.

We measured self-reports of coping, the most common measurement approach (e.g., Park, 2010). Self-reports are potentially limited by self-presentational biases and poor introspective accuracy. Assessing coping more indirectly, such as adjustment reflected in natural language patterns or observer-rated coping, could be useful. We examined minor to moderate stressors and challenging events across studies, aiming to identify whether MIL was related to coping with common, quotidian stressors. Comprehensively investigating MIL’s association with varied coping strategies pertaining to more severe stressors could be useful.

In the absence of specific conceptually sensible predictions, we did not test interactions between coping and MIL. Examining interplays between coping processes and MIL could provide greater clarity about their relationships. Probing the nexus between situational meaning and trait MIL during stressful events may be informative. Having a stable understanding of the world and one’s purpose may safeguard against the deterioration of situational meaning amid stressors (e.g., George & Park, 2017; Park, 2010).

Meaning has been important in scholarly conversations about coping with profound, traumatic events. This research contributes to our understanding of how MIL is linked to coping with everyday challenges and stressors.

Supplemental Material

sj-doc-1-psp-10.1177_01461672211068910 – Supplemental material for Meaning in Life and Coping With Everyday Stressors

Supplemental material, sj-doc-1-psp-10.1177_01461672211068910 for Meaning in Life and Coping With Everyday Stressors by Sarah Ward, Jake Womick, Liudmila Titova and Laura King in Personality and Social Psychology Bulletin

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Sarah Ward

Jake Womick

Supplemental Material

Supplemental material is available online with this article.

Notes

References

Bryan

C. J.

Elder

W. B.

McNaughton-Cassill

Osman

Hernandez

A. M.

Allison

(2013). Meaning in life, emotional distress, suicidal ideation, and life functioning in an active duty military sample. The Journal of Positive Psychology, 8(5), 444–452. https://doi.org/10.1080/17439760.2013.823557

Burrow

A. L.

Hill

P. L.

(2013). Derailed by diversity? Purpose buffers the relationship between ethnic composition on trains and passenger negative mood. Personality and Social Psychology Bulletin, 39(12), 1610–1619.

Burrow

A. L.

Hill

P. L.

Sumner

(2016). Leveling mountains: Purpose attenuates links between perceptions of effort and steepness. Personality and Social Psychology Bulletin, 42(1), 94–103. https://doi.org/10.1177/0146167215615404

Carver

C. S.

Connor-Smith

(2010). Personality and coping. Annual Review of Psychology, 61, 679–704. https://doi.org/10.1146/annurev.psych.093008.100352

Carver

C. S.

Scheier

M. F.

Weintraub

J. K.

(1989). Assessing coping strategies: A theoretically based approach. Journal of Personality and Social Psychology, 56(2), 267. https://doi.org/10.1037//0022-3514.56.2.267

Cohen

Kamarck

Mermelstein

(1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24, 386–396. https://doi.org/10.2307/2136404

Diener

Pressman

S. D.

Hunter

Delgadillo-Chase

(2017). If, why, and when subjective well-being influences health, and future needed research. Applied Psychology: Health and Well-Being, 9(2), 133–167.

Enders

C. K.

Tofighi

(2007). Centering predictor variables in cross-sectional multilevel models: A new look at an old issue. Psychological Methods, 12, 121–138. https://dx-doi-org.web.bisu.edu.cn/10.1037/1082-989X.12.2.121

Endler

N. S.

Parker

J. D. A.

(1994). Assessment of multidimensional coping: Task, emotion, and avoidance strategies. Psychological Assessment, 6(1), 50–60. https://doi.org/10.1037/1040-3590.6.1.50

10.

Geldhof

G. J.

Preacher

K. J.

Zyphur

M. J.

(2014). Reliability estimation in a multilevel confirmatory factor analysis framework. Psychological Methods, 19(1), Article 72. https://doi.org/10.1037/a0032138s

11.

George

L. S.

Park

C. L.

(2017). Meaning in life and violations of beliefs and goals: Reciprocal relations among individuals with congestive heart failure. Anxiety, Stress, & Coping, 30(3), 282–289. https://dx-doi-org.web.bisu.edu.cn/10.1080/10615806.2016.1253067

12.

Goldberg

L. R.

Johnson

J. A.

Eber

H. W.

Hogan

Ashton

M. C.

Cloninger

C. R.

Gough

H. G.

(2006). The international personality item pool and the future of public-domain personality measures. Journal of Research in Personality, 40(1), 84–96. https://doi.org/10.1016/j.jrp.2005.08.007

13.

Halama

(2014). Meaning in life and coping: Sense of meaning as a buffer against stress. In Batthyany

Russo-Netzer

(Eds.), Meaning in positive and existential psychology (pp. 239–250). Springer.

14.

Hayes

A. F.

(2022). Introduction to mediation, moderation, and conditional process analysis (3rd ed.). Guilford Press.

15.

Honkinen

Suominen

Helenius

Aromaa

Rautava

Sourander

Sillanpää

(2008). Stability of the sense of coherence in adolescence. International Journal of Adolescent Medicine and Health, 20, 85–91. https://dx-doi-org.web.bisu.edu.cn/10.1515/ijamh.2008.20.1.85

16.

Hooker

S. A.

Masters

K. S.

Park

C. L.

(2018). A meaningful life is a healthy life: A conceptual model linking meaning and meaning salience to health. Review of General Psychology, 22(1), 11–24. https://doi.org/10.1037/gpr0000115

17.

Jim

H. S.

Richardson

S. A.

Golden-Kreutz

D. M.

Andersen

B. L.

(2006). Strategies used in coping with a cancer diagnosis predict meaning in life for survivors. Health Psychology, 25(6), 753–761. https://doi.org/10.1037/0278-6133.25.6.753

18.

Kashdan

T. B.

Steger

M. F.

(2007). Curiosity and pathways to well-being and meaning in life: Traits, states, and everyday behaviors. Motivation and Emotion, 31, 159–173.

19.

King

L. A.

Hicks

J. A.

Krull

Del Gaiso

A. K.

(2006). Positive affect and the experience of meaning in life. Journal of Personality and Social Psychology, 90, 179–196. https://doi.org/10.1037/0022-3514.90.1.179

20.

Krause

(2007). Evaluating the stress-buffering function of meaning in life among older people. Journal of Aging and Health, 19(5), 792–812. https://doi.org/10.1177/0898264307304390

21.

Krok

Telka

(2019). The role of meaning in gastric cancer patients: Relationships among meaning structures, coping, and psychological well-being. Anxiety, Stress, & Coping, 32(5), 522–533. https://doi.org/10.1080/10615806.2019.1633578

22.

Lazarus

R. S.

Folkman

(1984). Stress, appraisal, and coping. Springer.

23.

McAdams

D. P.

(2008). Personal narratives and the life story. In John

O. P.

Robins

R. W.

Pervin

L. A.

(Eds.), Handbook of personality: Theory and research (3rd ed., pp. 242–262). Guilford Press.

24.

McCredie

M. N.

Morey

L. C.

(2019). Who are the Turkers? A characterization of MTurk workers using the personality assessment inventory. Assessment, 26(5), 759–766. https://doi.org/10.1177/1073191118760709

25.

Miao

Gan

(2019). How does meaning in life predict proactive coping? The self-regulatory mechanism on emotion and cognition. Journal of Personality, 87(3), 579–592. https://doi.org/10.1111/jopy.12416

26.

Miao

Zheng

Gan

(2017). Meaning in life promotes proactive coping via positive affect: A Daily Diary Study. Journal of Happiness Studies, 18(6), 1683–1696. https://doi.org/10.1007/s10902-016-9791-4

27.

Muthén

Asparouhov

(2012). Bayesian structural equation modeling: A more flexible representation of substantive theory. Psychological Methods, 17(3), Article 313. https://doi.org/10.1037/a0026802

28.

Newman

D. B.

Nezlek

J. B.

Thrash

T. M.

(2018). The dynamics of searching for meaning and presence of meaning in daily life. Journal of Personality, 86(3), 368–379.

29.

Nezlek

J. B.

(2012). Multilevel modeling analyses of diary-style data. In Mehl

M. R.

Conner

T. S.

(Eds.), Handbook of research methods for studying daily life (pp. 357–383). Guilford Press.

30.

Park

C. L.

(2006). Exploring relations among religiousness, meaning, and adjustment to lifetime and current stressful encounters in later life. Anxiety, Stress, and Coping, 19(1), 33–45. https://doi.org/10.1080/10615800600581259

31.

Park

C. L.

(2010). Making sense of the meaning literature: An integrative review of meaning making and its effects on adjustment to stressful life events. Psychological Bulletin, 136(2), 257–301. https://doi.org/10.1037/a0018301

32.

Park

C. L.

Folkman

(1997). Meaning in the context of stress and coping. Review of General Psychology, 1(2), 115–144. https://doi.org/10.1037/1089-2680.1.2.115

33.

Park

C. L.

Malone

M. R.

Suresh

D. P.

Bliss

Rosen

R. I.

(2008). Coping, meaning in life, and quality of life in congestive heart failure patients. Quality of Life Research, 17(1), 21–26. https://doi.org/10.1007/s11136-007-9279-0

34.

Park

C. L.

Riley

K. E.

George

L. S.

Gutierrez

I. A.

Hale

A. E.

Cho

Braun

T. D.

(2016). Assessing disruptions in meaning: Development of the global meaning violation scale. Cognitive Therapy and Research, 40(6), 831–846.

35.

Peacock

E. J.

Wong

P. T.

(1990). The stress appraisal measure (SAM): A multidimensional approach to cognitive appraisal. Stress Medicine, 6(3), 227–236. https://doi.org/10.1002/smi.2460060308

36.

Preacher

K. J.

Zyphur

M. J.

Zhang

(2010). A general multilevel SEM framework for assessing multilevel mediation. Psychological Methods, 15(3), Article 209. https://doi.org/10.1037/a0020141

37.

Riley

K. E.

Park

C. L.

(2014). Problem-focused vs. meaning-focused coping as mediators of the appraisal-adjustment relationship in chronic stressors. Journal of Social and Clinical Psychology, 33(7), 587–611.

38.

Sherman

A. C.

Simonton

(2012). Effects of personal meaning among patients in primary and specialized care: Associations with psychosocial and physical outcomes. Psychology & Health, 27(4), 475–490. https://doi.org/10.1080/08870446.2011.592983

39.

Silver

R. C.

Updegraff

J. A.

(2013). Searching for and finding meaning following personal and collective traumas. In Markman

K. D.

Proulx

Lindberg

M. J.

(Eds.), The psychology of meaning (pp. 237–255). American Psychological Association. https://doi.org/10.1037/14040-012

40.

Skinner

E. A.

Edge

Altman

Sherwood

(2003). Searching for the structure of coping: A review and critique of category systems for classifying ways of coping. Psychological Bulletin, 129(2), Article 216. https://doi.org/10.1037/0033-2909.129.2.216

41.

Steger

M. F.

Frazier

Oishi

Kaler

(2006). The Meaning in Life Questionnaire: Assessing the presence of and search for meaning in life. Journal of Counseling Psychology, 53(1), 80–93. https://doi.org/10.1037/0022-0167.53.1.80

42.

Tan

C. S.

Hashim

I. H. M.

Pheh

K. S.

Pratt

Chung

M. H.

Setyowati

(2021). The mediating role of openness to experience and curiosity in the relationship between mindfulness and meaning in life: Evidence from four countries. Current Psychology, 1–11. https://doi.org/10.1007/s12144-021-01430-2

43.

Taubman-Ben-Ari

Shlomo

S. B.

Findler

(2012). Personal growth and meaning in life among first-time mothers and grandmothers. Journal of Happiness Studies, 13(5), 801–820. https://doi.org/10.1007/s10902-011-9291-5

44.

Updegraff

J. A.

Silver

R. C.

Holman

E. A.

(2008). Searching for and finding meaning in collective trauma: Results from a national longitudinal study of the 9/11 terrorist attacks. Journal of Personality and Social Psychology, 95(3), Article 709. https://doi.org/10.1037/0022-3514.95.3.709

45.

Ward

S. J.

King

L. A.

(2016). Poor but happy? Income, happiness, and experienced and expected meaning in life. Social Psychological and Personality Science, 7(5), 463–470. https://doi.org/10.1177/1948550615627865

46.

Ward

S. J.

King

L. A.

(2017). Making sense: Meaning in life in a cognitive context. In Robinson

M. D.

Eid

(Eds.), The happy mind: Cognitive contributions to well-being (pp. 409–425). Springer.

47.

Ward

S. J.

King

L. A.

(2018). Moral self-regulation, moral identity, and religiosity. Journal of Personality and Social Psychology, 115(3), 495–525. https://doi.org/10.1037/pspp0000207

48.

West

S. G.

Hepworth

J. T.

(1991). Statistical issues in the study of temporal data: Daily experiences. Journal of Personality, 59(3), 609–662.

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