Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2024 Mar 18.
Published in final edited form as: Mindfulness (N Y). 2022 Oct 22;13(11):2796–2811. doi: 10.1007/s12671-022-01996-3

Trait mindfulness and emotion regulation responsiveness to negative affect in daily life

Megan E Fisher 1, Elizabeth Duraney 1, Katherine Friess 1, Patrick Whitmoyer 2, Rebecca Andridge 3, Ruchika S Prakash 1,4
PMCID: PMC10948115  NIHMSID: NIHMS1928151  PMID: 38500843

Abstract

Objectives:

Recent conceptualizations of adaptive emotion regulation is predicated on the ability to flexibly use emotion regulation strategies to meet changing contextual demands. Although trait mindfulness has been linked to enhanced emotional well-being and use of adaptive emotion regulation strategies, there is a dearth of literature examining associations between trait mindfulness and emotion regulation flexibility. Further, despite a rich literature suggesting that emotion regulation processes change with age, no study to date has assessed whether the role of trait mindfulness on emotion regulation responsiveness to negative emotions—a component of emotion regulation flexibility—differs between young and older adults.

Methods:

The current study recruited 130 young adults and 130 older adults to assess trait mindfulness, emotion regulation strategy use, and emotion regulation responsiveness of six distinct strategies in daily life.

Results:

Across the full sample, trait mindfulness was related to reduced distraction (β = −0.11, t(238.09) = −3.02, p = .003) and expressive suppression (β = −0.15, t(237.70) = −4.62, p < .001) strategy use. Age moderation analyses revealed that trait mindfulness was associated with reduced expressive suppression responsiveness (β = 0.12, t(247) = 2.31, p = .022) in young adults and increased detached reappraisal responsiveness among older adults (β = 0.15, t(247) = −2.95, p = .003).

Conclusions:

The current findings highlight the importance of understanding how trait mindfulness is associated with strategy use and responsiveness to negative affect changes in daily life as well as how these patterns may shift across the lifespan.

Manuscript Pre-registration:

Open Science Framework, registration number: z5g8v.

Keywords: trait mindfulness, emotion regulation, emotion regulation flexibility, aging

Contemporary scientific definitions of the construct mindfulness generally refer to it as a dispositional characteristic involving the intentional and non-judgmental self-regulation of attention to present moment experiences (Kabat-Zinn, 1990; Rau & Williams, 2016; but see Van Dam et al., 2018 for a critical discussion on issues defining mindfulness). In corroborating theoretical accounts that hypothesize the benefits of mindfulness for emotional health, higher trait mindfulness has been linked with lower anxiety and depressive symptoms (Lyvers et al., 2014; Tamagawa et al., 2013), lower emotion dysregulation (McLaughlin et al., 2019; Prakash et al., 2017), and greater emotional well-being (Fiocco & Mallya, 2015). Furthermore, mindfulness-based intervention studies have also demonstrated increases in trait mindfulness (Kiken et al., 2015), reductions in both psychological distress and perceived stress (Dark-Freudeman et al., 2021), and increases in emotion regulation flexibility (Alkoby et al., 2019), suggesting that the positive effects of mindfulness for emotional health can also be cultivated through repeated engagement in meditative practices.

Consistent links between trait mindfulness and better emotional functioning have spurred considerable interest in understanding how mindfulness confers its beneficial effects. Theoretical conceptualizations of mindfulness suggest that attending to emotional states with an open, accepting, and non-judgmental attitude may facilitate adaptive emotion regulation (Holzel et al., 2011; Roemer et al., 2015; Teper et al., 2013). Specifically, by adopting an open and accepting attitude toward momentary experiences, individuals with higher levels of trait mindfulness may be less likely to change, extend, or avoid emotional experiences (Bravo et al., 2022). In doing so, more mindful individuals may exhibit less emotional reactivity thereby altering the way in which their emotions are processed (see Bravo et al., 2022 and Desbordes et al., 2015 for reviews).

As such, the process and strategies through which one attempts to modulate the type, occurrence, and experience or expression of their emotions (Gross, 2015, 1998), also referred to as emotion regulation, has been extensively studied with respect to its association with trait mindfulness. Strategies most commonly studied include detached reappraisal (i.e., reinterpreting situations from an unemotional and distanced perspective; Liang et al., 2017; Shiota & Levenson, 2009), positive reappraisal (i.e., reinterpreting situations to emphasize positive outcomes; Liang et al., 2017; Shiota & Levenson, 2009), distraction (i.e., shifting attention away from emotional information and toward unrelated thoughts; Kobayashi et al., 2021; Wolgast & Lundh, 2017), expressive suppression (i.e., hiding any outward expression of emotion; Livingstone & Isaacowitz, 2018; Prakash et al., 2017); situation selection (i.e., seeking out or avoiding situations; Livingstone & Isaacowitz, 2021; Sands & Isaacowitz, 2017), and, more recently, acceptance (i.e., allowing or accepting one’s feelings; Prakash et al., 2017; Wolgast et al., 2011). Self-report studies have linked trait mindfulness with greater use of adaptive strategies, such as acceptance and positive reappraisal (Boelen & Lenferink, 2017; Hanley & Garland, 2014). Trait mindfulness has also been associated with a reduced use of maladaptive strategies, including thought avoidance and suppression (Feldman et al., 2007; Prakash et al., 2017). Furthermore, one pathway through which trait mindfulness may be associated with better emotional functioning is, in part, due to reduced reliance on maladaptive strategies (Desrosiers et al., 2013; Prakash et al., 2017). These findings suggest individual differences in trait mindfulness influence the types of emotion regulation strategies one consistently employs, yet much of this work has relied on global trait-like measures of strategy use.

Early emotion regulation work conceptualized strategies as inherently adaptive or maladaptive based on their associations with psychopathology (Aldao et al., 2010; Nolen-Hoeksema & Aldao, 2011). However, contemporary theories posit that although some strategies may be effective at reducing negative emotions in the short-term, consistent use across varying contexts may produce poorer long-term consequences (Aldao et al., 2015; Pruessner et al., 2020). Consequently, adaptive emotion regulation may be better reflected by the ability to use emotion regulation strategies in a flexible manner that synchronizes with contextual demands and aligns with one’s emotion regulation goals. Although mindfulness is thought to promote flexible awareness of and engagement with momentary emotional states (Teper et al., 2013), relatively few studies have explicitly examined whether being mindful actually facilitates flexible, context-dependent emotion regulation (Roemer et al., 2015). This could partly be attributed to the fact that emotion regulation flexibility is a relatively nascent and nebulous process to conceptualize and measure. However, across the literature, emotion regulation flexibility is generally comprised of several distinct, yet interrelated components. For example, individuals must evaluate contextual demands and opportunities, select a strategy from all available strategies, and monitor/flexibly adjust their strategy use based on whether regulation goals have been achieved (Aldao et al., 2015; Bonanno & Burton, 2013). Other components of emotion regulation flexibility are assessed by an individual’s preference for specific types of strategies based on the affective intensity of the situation (Alkoby et al., 2019; Sheppes et al., 2011).

Using an emotion regulation choice task comparing cognitive reappraisal and distraction use in response to negatively valanced images, Alkoby et al. (2019) found that individuals (ages 21–40; Mage = 25.12) who completed a mindfulness-based stress reduction course used distraction more frequently during high intensity images but used cognitive reappraisal more frequently during low intensity images relative to controls. Additionally, Keng et al. (2018) used ecological momentary assessment to examine the relationship between trait mindfulness and variability on seven coping strategies in college students (Mage = 19.88). Their findings revealed that more mindful individuals exhibited greater use of multiple strategies within a single stressful situation in daily life. Although promising, neither study assessed how strategy use covaries with changes in emotional contexts in everyday life—thereby limiting interpretations about how trait mindfulness might relate to patterns of contextual strategy use. Moreover, because both trait mindfulness and emotion regulation strategy patterns have been shown to differ with age (see Allen & Windsor, 2019 for a review on age differences in strategy use; Shook et al., 2017), it remains unclear whether findings in young adults from Alkoby et al. (2019) and Keng et al. (2018) would generalize to older adults.

Specifically, evidence from the broader aging and emotion regulation literatures suggests that emotion regulation patterns change across the adult lifespan. Older adults prioritize using emotion regulation strategies that facilitate positive emotional states (see Allen & Windsor, 2019 for a systematic review). Although a full discussion on the age differences in emotion regulation processes is beyond the scope of the present study (see Scheibe & Carstensen, 2010; Urry & Gross, 2010 for theoretical reviews), more recent studies have begun to explore how emotion regulation flexibility patterns differ across the adult lifespan. For example, Benson et al. (2019) examined age differences in cognitive reappraisal and expressive suppression flexibility across relational and emotional contexts in a sample of adults between the ages of 18–89 years. Their findings showed that older age was associated with a reduced use of expressive suppression flexibility during relational contexts. Results from the parent study (Whitmoyer et al., 2022), from which the current data was drawn, have shown that relative to younger adults (aged 22–35), older adults (aged 65–85) exhibited reduced strategy responsiveness across six emotion regulation strategy types. Further, despite that trait mindfulness tends to increase with age (Mahoney et al., 2015; Prakash et al., 2017), some evidence suggests that emotion regulation abilities mediate the relationship between trait mindfulness and reduced stress in both older and younger adults (Prakash et al., 2015). However, age has also been shown to moderate mediations between trait mindfulness and emotion dysregulation through thought avoidance, such that this effect is stronger among younger adults (Prakash et al., 2017). This constellation of findings highlights the need to assess whether the observed relationships between trait mindfulness and components of emotion regulation flexibility will generalize in a more age-diverse sample.

The current study aimed to assess whether trait mindfulness is associated with a component of emotion regulation flexibility. As such, we will hereafter refer to co-fluctuations between strategy use and negative affect as “emotion regulation responsiveness”. In doing so, we hope to better characterize how individuals shift their strategy use based on changes in negative affect intensity across everyday life situations. Specifically, we examined associations between trait mindfulness and emotion regulation strategy use and responsiveness for six strategies (acceptance, positive reappraisal, detached reappraisal, distraction, expressive suppression, and situation selection) in daily life. Our sample included both young (aged 22–35) and older adults (aged 65–85) to assess whether observed findings are generalizable to the entire sample or are age group specific. First, we predicted that higher trait mindfulness would be associated with greater acceptance use given their conceptual overlap. Further, because prior evidence has linked higher trait mindfulness with reduced use of avoidance-based strategies, we hypothesized that higher trait mindfulness would be associated with less distraction, expressive suppression, and situation selection use. Despite the dearth of prior work examining the relationship between trait mindfulness and emotion regulation flexibility, mindful individuals may be better positioned to use emotion regulation strategies that best align with the demands of their current situation (such as in response to increasing negative affect). Therefore, we predicted that higher trait mindfulness would be associated with greater use of all six emotion regulation strategies as negative affect increases (i.e., within-strategy responsiveness) across multiple emotional situations. Second, because prior evidence suggests that the “adaptiveness” of expressive suppression may vary by age (Allen & Windsor, 2019), we hypothesized that higher trait mindfulness would be negatively associated with expressive suppression responsiveness among young adults but would be positively associated among older adults. Lastly, we predicted that higher trait mindfulness would be positively associated with situation selection but only among older adults.

Method

Participants

This study was conceptualized and performed as a secondary analysis of the parent study (Whitmoyer et al., 2022), so an a priori power analysis was not conducted to test the aims of the current study. The current study included 130 young (aged 22–35) and 130 older (aged 65–85) adults to assess age-differences in emotion regulation responsiveness and their relationship to emotion dysregulation and well-being. All participants were required to meet the following eligibility criteria: (1) normal or corrected-to-normal vision; (2) high school degree or equivalent (e.g., GED); (3) the absence of a self-reported, diagnosed neurological disorder or another disease that significantly impairs cognitive abilities; (4) no history of self-reported mania or psychosis; (5) no self-reported history of substance use problems within the last two years; (6) no self-reported current treatment with electroconvulsive therapy; (7) the absence of the regular use of medications that significantly alters cognitive function (e.g., sedatives and chemotherapy treatments); (8) self-reported English fluency; and (9) not living in long-term care facilities (e.g., hospital or retirement home). In addition, older adults were required to obtain a score > 31 on the Telephone Interview for Cognitive Status (TICS-M; Welsh et al., 1993).

Procedure

Participants were recruited on a rolling basis between February 2019 and June 2019 from across the United States using ResearchMatch (an NIH-funded non-profit research database designed to link eligible research volunteers with available study opportunities) and online advertisements. A total of 579 participants first completed the consent form and an online screening survey to collect basic eligibility information via REDCap (Harris et al., 2009). Next, participants underwent a ~15-minute phone interview to gather additional demographic and clinical information (n = 295). During this phone interview, the TICS-M was administered to older adults to ensure adequate global cognitive function. Eligible participants (n = 294) were sent a link to complete a battery of self-report assessments presented in a randomized order via Qualtrics (Qualtrics, 2019). Once questionnaires were completed (n = 279), participants were sent a second link two days later to complete the modified Day Reconstruction Method (DRM; Kahneman et al., 2004) assessment via Qualtrics. All participants were compensated with $10 Amazon gift cards for completing each set of online surveys, totaling $20 in Amazon gift cards for individuals who completed the entire study. A total of 130 young and 130 older adults (260 out of 294 eligible adults) completed the entire study. All study procedures were approved by the Ohio State University Institutional Review Board (IRB# 2018B0146).

Measures

Descriptions for covariate variables (sex and social desirability bias) can be found in the Supplementary Material.

Dispositional mindfulness.

Trait mindfulness was assessed using the Mindful Attention and Awareness Scale (MAAS; Brown & Ryan, 2003) that has been used in prior studies with both older and younger adults (Mahoney et al., 2015; Prakash et al., 2017). The scale consists of 15-items measured using a Likert scale ranging from 1 (“almost always”) to 6 (“almost never”). Each individual item is reverse-worded such that higher scores reflect greater levels of trait mindfulness (i.e., “I find it difficult to stay focused on what’s happening in the present”). Individual scores were calculated by taking the average of all 15 items. Cronbach’s alpha coefficient and McDonald’s omega reliability coefficient calculations suggests that the MAAS demonstrated good internal consistency reliability for both young adults (α = .86; ω = .86, 95% CI [.81, .89]) and older adults (α = 0.91; ω = .91, 95% CI [.88, .93]).

Day reconstruction method.

Daily emotional episodes were measured using an adapted version of the Day Reconstruction Method (DRM; Kahneman et al., 2004), which exhibits good correspondence with experience sampling methods in both young and older adults (Lucas et al., 2021; Schneider et al., 2020). Participants were instructed to break up the prior day into a series of emotional episodes lasting between 15 minutes and 2 hours in duration, reporting on a maximum of 30 emotional episodes. Next, participants were asked to rate the extent to which they experienced negative affect during each episode using a Likert scale ranging from 0 (“not at all”) to 10 (“very much”). For each episode, participants also reported the extent to which they used each of the six emotion regulation strategies (acceptance, positive reappraisal, detached reappraisal, distraction, expressive suppression, and situation selection) using a Likert scale ranging from 0 (“not at all”) to 3 (“a lot”). The DRM assessment method was administered online using Qualtrics.

Within-strategy responsiveness scores were calculated using general recommendations from Aldao et al., (2015). Specifically, within-strategy responsiveness scores were calculated by cross-correlating the time series of strategy use frequency (i.e., acceptance, positive reappraisal, detached reappraisal, distraction, expressive suppression, or situation selection strategy use) with their respective negative affect rating across all emotional episodes. This process was repeated for each strategy type so that each participant had a total of six within-strategy responsiveness scores. Larger correlation coefficients indicated greater covariation between strategy use and negative affect, and thus reflect greater emotion regulation responsiveness (i.e., as negative affect intensity increases, strategy use increases).

Data Analyses

All data was assessed for exclusion and outliers prior to conducting our pre-registered statistical analyses. Specifically, participants who reported an insufficient number of DRM emotional episodes (< 5 episodes; per recommendations from Wilhelm & Grossman, 2010 to obtain adequate variation in mood) were excluded (young adults = 3, older adults = 4). Additionally, participants whose scores on the MCSDS (young adults = 1, older adults = 2) and MAAS (young adults = 2, older adults = 1) exceeded +/− 2.5 SDs from their age group’s mean were deemed as outliers and their scores were replaced with scores equivalent to +/− 2.5 SDs from their age group mean. A final sample of 127 younger adults and 126 older adults was used for all subsequent analyses. Effect coding was used to re-code sex (males = −0.5, females = 0.5,) and age group (young adults = −0.5, older adults = 0.5) variables to facilitate the interpretation of main and interaction effects. Descriptive statistics were calculated for age, sex, education, race, ethnicity, social desirability bias, number of DRM episodes, trait mindfulness, strategy use frequency for all six strategies, negative affect, and within-strategy responsiveness for all six strategies. To test for age group differences in the descriptive statistics, independent samples t-tests and Mann-Whitney U tests were conducted for normally and non-normally distributed data, respectively. For all primary analyses in which separate models were constructed to examine six strategies, a Bonferonni correction of .008 was applied to correct for multiple comparisons. For all exploratory analyses examining age moderations of the relationship between trait mindfulness, emotion regulation strategy use, and emotion regulation responsiveness, the standard p < .05 criteria for statistical significance was used. Prior to conducting our primary and exploratory analyses, social desirability bias and trait mindfulness were both grand mean-centered to facilitate interpretation.

Our primary aim examined how trait mindfulness was related to patterns of emotion regulation strategy use and strategy use responsiveness across the full sample. To assess the relationship between trait mindfulness and strategy use, six separate linear mixed models with two levels (strategy use within episodes nested within persons) were constructed for each strategy type (acceptance, positive reappraisal, detached reappraisal, distraction, expressive suppression, and situation selection). In each model, trait mindfulness was entered as a fixed effect, participant intercepts were entered as random effects, sex and social desirability bias were entered as covariates, strategy use was entered as the dependent variable, and restricted maximum likelihood (REML) estimation methods were used to account for unbalanced data due to participants reporting different numbers of episodes. To assess the relationship between trait mindfulness and patterns of emotion regulation responsiveness (within-strategy responsiveness), six multiple linear regression models were constructed for each strategy type (acceptance, positive reappraisal, detached reappraisal, distraction, expressive suppression, and situation selection). For each of these analyses, trait mindfulness was included as the predictor, sex and social desirability bias were entered as covariates, and within-strategy responsiveness was entered as the dependent variable.

Our exploratory aim examined whether age moderated relationships between trait mindfulness, strategy use, and strategy responsiveness. To assess for an age moderation of the relationship between trait mindfulness and strategy use, six separate linear mixed models with two levels (strategy use within episodes nested within persons) were constructed for each strategy type (acceptance, positive reappraisal, detached reappraisal, distraction, expressive suppression, and situation selection). In each model, age group, trait mindfulness, and the age X trait mindfulness interaction term were entered as fixed effects, participant intercepts were entered as random effects, sex and social desirability bias were entered as covariates, strategy use was entered as the dependent variable, and restricted maximum likelihood (REML) estimation methods were used to account for unbalanced data due to participants reporting different numbers of episodes. To assess whether age group moderated the relationship between trait mindfulness and within-strategy responsiveness, six stepwise multiple linear regression models were constructed for each strategy type (acceptance, positive reappraisal, detached reappraisal, distraction, expressive suppression, and situation selection). For each of these analyses, model 1 included age group and trait mindfulness as predictors, sex and social desirability bias as covariates, and within-strategy responsiveness as the dependent variable. Model 2 included the age group X trait mindfulness interaction term, in which significant improvements in model 2 indicate age as a moderator. If the interaction term of model 2 was significant, we conducted simple slopes analysis to further assess the directionality and significance of the interaction. Visual depictions of the multilevel models and all model equations can be found in Figure 1 of the Supplementary Material.

Figure 1. Age Moderation of Trait Mindfulness on Detached Reappraisal Responsiveness.

Figure 1.

Open in a new tab

Note: Separate trendlines reflect the relationship between trait mindfulness and detached reappraisal responsiveness within the two age groups. X-axis: Grand mean-centered trait mindfulness scores; Y-axis: Detached reappraisal responsiveness scores. Simple slopes analysis displayed using 95% confidence intervals. Solid line represents a significant slope and dashed line represents a non-significant slope.

All analyses were conducted in RStudio. Multilevel and multiple linear regression models were fit using the lme4 (Bates et al., 2015) and stats packages, respectively. The significance of parameter estimates for all multilevel models were assessed using the lmerTest package (Kuznetsova et al., 2017) and simple slope analyses for significant interactions were conducted using the emmeans (Lenth, 2021) and reghelper packages (Hughes & Beiner, 2022). Participant demographic variables are presented in Table 1. Descriptive statistics and group comparison tests for questionnaire data, strategy use, and strategy responsiveness variables are included in Table 2.

Table 1.

Descriptive statistics for participant demographic variables

Demographic Variable Young Adults (n = 127) Older Adults (n = 126) Combined Sample (n = 253)
n (%) Mean(SD) n (%) Mean(SD) n (%) Mean(SD)
Age - 28.59(3.91) - 70.69(4.32) - 49.56(21.49)
Sex (females) 64 (50.39) - 64(50.79) - 128(50.59) -
Education - 17.19(2.39) - 17.48(2.59) - 17.34(2.49)
Race †
 White 93 (73.23) - 118(93.65) - 211(83.40) -
 American Indian/ Alaskan Native 1 (0.78) - 0 (0.00) - 1 (0.40) -
 Asian 10 (7.89) - 0 (0.00) - 10 (3.95) -
 Black/African American 11 (8.67) - 4 (3.17) - 15 (5.93) -
 Multiracial 9 (7.09) - 3 (2.38) - 12 (4.74) -
 Other 1 (0.78) - 0 (0.00) - 1 (0.40) -
Ethnicity †
 Non-Hispanic or Latino 120 (94.49) - 122(96.83) - 242 (95.65) -
 Hispanic or Latino 6 (4.72) - 1 (0.79) - 7 (2.77) -
Open in a new tab
†

Race data was missing for three participants (2 young adults, 1 older adult) and ethnicity data was missing for four participants (1 young adult, 3 older adults).

Table 2.

Descriptive statistics for self-report questionnaires and emotion regulation metrics

Young Adults (n = 127) Older Adults (n = 126) Combined (n = 253) Group Comparison
Mean (SD) Mean (SD) Mean (SD)
MCSDS 15.41 (5.16) 18.73 (5.34) 17.06 (5.50) t(251) = −5.03***
MAAS 3.67 (0.85) 4.20 (0.98) 3.93 (0.95) U = 5,313.00***
Number of DRM Episodes 12.11 (5.11) 10.92 (4.32) 11.52 (4.76) U = 8,917.50
Strategy Use
Acceptance 1.69 (0.84) 2.27 (0.74) 1.98 (0.84) U = 4,743.50***
Positive Reappraisal 0.93 (0.75) 1.01 (0.81) 0.97 (0.78) U = 7,668.00
Detached Reappraisal 0.65 (0.58) 0.74 (0.68) 0.69 (0.63) U = 7,656.50
Distraction 0.76 (0.61) 0.36 (0.40) 0.56 (0.55) U = 11,459.00***
Expressive Suppression 0.57 (0.49) 0.42 (0.49) 0.50 (0.50) U = 10,056.00***
Situation Selection 0.53 (0.63) 0.41 (0.58) 0.47 (0.61) U = 9,306.00*
Strategy Responsiveness
Acceptance −0.03 (0.43) −0.09 (0.45) −0.06 (0.44) U = 8,571.50
Positive Reappraisal 0.23 (0.41) 0.17 (0.45) 0.20 (0.43) U = 8,650.50
Detached Reappraisal 0.32 (0.34) 0.21 (0.40) 0.27 (0.37) U = 9,306.50*
Distraction 0.26 (0.36) 0.15 (0.37) 0.21 (0.37) U = 9,649.50**
Expressive Suppression 0.37 (0.33) 0.25 (0.39) 0.31 (0.36) U = 9,432.00*
Situation Selection −0.02 (0.34) −0.01 (0.32) −0.02 (0.33) U = 7,809.50
Open in a new tab

Note. Independent samples t-tests were used for normally distributed data. Mann-Whitney-Wilcoxon tests were used for non-normally distributed data. MCSDS: Marlowe-Crowne Social Desirability Scale; MAAS: Mindful Attention Awareness Scale.

*

p < .05

**

p < .01

***

p < .001.

Results

Associations Between Trait Mindfulness, Strategy Use, and Strategy Responsiveness

Results from all six mixed linear models assessing the relationship between trait mindfulness and strategy use can be found in Table 3. Consistent with our predictions, higher trait mindfulness was associated with less distraction use (β = −0.11, t(238.09) = −3.02, p = .003, 99.2% CI: [−0.20, −0.01]) and less expressive suppression use (β = −0.15, t(237.70) = −4.62, p < .001, 99.2% CI: [−0.23, −0.06]) after controlling for sex and social desirability bias. Results from all multiple linear regression analyses examining associations between trait mindfulness and within-strategy responsiveness for all six strategies can be found in Table 4. After correcting for multiple comparisons, we did not find a significant relationship between trait mindfulness and any of the six within-strategy responsiveness scores (all ps ≥ .029).

Table 3.

Mixed linear models examining the effect of trait mindfulness on strategy use

Model Description Fixed Effects Estimate (SE) t-value p-value 99.2% CI
Acceptance Strategy Use ~ Sex + MCSDS + MAAS Intercept 1.97 (0.05) 37.26 < .001*** [1.83, 2.11]
Sex 0.10 (0.11) 0.93 .354 [−0.18, 0.38]
MCSDS 0.02 (0.01) 1.56 .119 [−0.01, 0.04]
MAAS 0.02 (0.06) 0.35 .730 [−0.14, 0.18]
Positive Reappraisal Strategy Use ~ Sex + MCSDS + MAAS Intercept 0.96 (0.05) 19.87 < .001*** [0.83, 1.09]
Sex 0.13 (0.10) 1.33 .185 [−0.13, 0.39]
MCSDS 0.00 (0.01) 0.34 .733 [−0.02, 0.03]
MAAS −0.08 (0.05) −1.42 .157 [−0.22, 0.67]
Detached Reappraisal Strategy Use ~ Sex + MCSDS + MAAS Intercept 0.69 (0.04) 17.50 < .001*** [0.58, 0.79]
Sex −0.11 (0.08) −1.35 .178 [−0.32, 0.10]
MCSDS −0.01 (0.01) −1.52 .130 [−0.03, 0.01]
MAAS −0.01 (0.04) −0.31 .755 [−0.13, 0.10]
Distraction Strategy Use ~ Sex + MCSDS + MAAS Intercept 0.55 (0.03) 17.37 < .001*** [0.47, 0.64]
Sex −0.07 (0.06) −1.08 .284 [−0.24, 0.10]
MCSDS −0.02 (0.01) −3.82 < .001*** [−0.04, −0.01]
MAAS −0.11 (0.04) −3.02 .003** [−0.20, −0.01]
Expressive Suppression Strategy Use ~ Sex + MCSDS + MAAS Intercept 0.49 (0.03) 17.19 < .001*** [0.41, 0.56]
Sex 0.00 (0.06) 0.02 .986 [−0.15, 0.15]
MCSDS −0.02 (0.01) −2.98 .003** [−0.03, −0.00]
MAAS −0.15 (0.03) −4.62 < .001*** [−0.23, −0.06]
Situation Selection Strategy Use ~ Sex + MCSDS + MAAS Intercept 0.46 (0.04) 12.56 < .001*** [0.36, 0.56]
Sex 0.07 (0.07) 0.92 .360 [−0.13, 0.26]
MCSDS 0.00 (0.01) 0.04 .972 [−0.02, 0.02]
MAAS −0.08 (0.04) −1.82 .071 [−0.18, 0.03]
Open in a new tab

Note. MCSDS = Marlow-Crowne Social Desirability Scale, MAAS = Mindful Attention and Awareness Scale. Intercepts represent the grand-centered mean, sex is effect coded (males = 0.5 and females = 0.5), and participant intercepts were entered as random effects for all models.

*

p < .05

**

p < .01

***

p < .001.

Table 4.

Multiple linear regression models examining the effect of trait mindfulness on strategy responsiveness

Model Description Fixed Effects Estimate (SE) t-value p-value 99.2% CI
Acceptance Strategy Responsiveness ~ Sex + MCSDS + MAAS Intercept −0.06 (0.03) −2.28 .024* [−0.14, 0.01]
Sex −0.04 (0.06) −0.78 .436 [−0.19, 0.10]
MCSDS 0.00 (0.01) 0.17 .867 [−0.01, 0.02]
MAAS 0.05 (0.03) 1.60 .111 [−0.03, 0.13]
R2 = .02
Positive Reappraisal Responsiveness ~ Sex + MCSDS + MAAS Intercept 0.20 (0.03) 7.43 <.001*** [0.13, 0.27]
Sex −0.02 (0.05) −0.42 .672 [−0.17, 0.12]
MCSDS 0.00 (0.01) 0.20 .874 [−0.01, 0.01]
MAAS 0.07 (0.03) 2.19 .029 [−0.01, 0.15]
R2 = .02
Detached Reappraisal Responsiveness ~ Sex + MCSDS + MAAS Intercept 0.27 (0.02) 11.38 <.001*** [0.20, 0.33]
Sex 0.02 (0.05) 0.46 .649 [−0.10, 0.15]
MCSDS −0.01 (0.00) −1.39 .166 [−0.02, 0.01]
MAAS −0.00 (0.03) −0.02 .986 [−0.07, 0.07]
R2 = .01
Distraction Strategy Responsiveness ~ Sex + MCSDS + MAAS Intercept 0.20 (0.02) 8.93 <.001*** [0.14, 0.27]
Sex 0.01 (0.05) 0.13 .896 [−0.12, 0.13]
MCSDS −0.01 (0.00) −1.22 .225 [−0.02, 0.01]
MAAS −0.03 (0.03) −1.27 .205 [−0.10, 0.04]
R2 = .02
Expressive Suppression Responsiveness ~ Sex + MCSDS + MAAS Intercept 0.31 (0.02) 13.51 <.001*** [0.25, 0.27]
Sex 0.05 (0.05) 1.03 .306 [−0.08, 0.17]
MCSDS −0.01 (0.00) −1.47 .143 [−0.02, 0.01]
MAAS −0.02 (0.03) −0.87 .387 [−0.09, 0.05]
R2 = .02
Situation Selection Strategy Responsiveness ~ Sex + MCSDS + MAAS Intercept −0.02 (0.02) −0.84 .400 [−0.07, 0.04]
Sex −0.06 (0.04) −1.55 .123 [−0.18, 0.05]
MCSDS −0.00 (0.00) −0.48 .633 [−0.01, 0.01]
MAAS 0.01 (0.02) 0.42 .674 [−0.05, 0.07]
R2 = .01
Open in a new tab

Note. MCSDS = Marlow-Crowne Social Desirability Scale, MAAS = Mindful Attention and Awareness Scale. Intercepts represent the grand-centered mean and sex is effect coded (males = −0.5 and females = 0.5).

*

p < .05

**

p < .01

***

p < .001.

Age Moderations of Associations Between Trait Mindfulness, Strategy Use, and Strategy Responsiveness

Results from all six mixed linear models examining age moderations of the relationship between trait mindfulness and strategy use for each of the six strategies can be found in Table 5. After controlling for sex and social desirability bias, age group was not a significant moderator of associations between trait mindfulness and strategy use for any of the six strategies (all ps ≥ .110). Results from all six stepwise multiple linear regression models assessing potential age moderations in the relationship between trait mindfulness and within-strategy responsiveness are presented in Table 6. After controlling for sex and social desirability bias, age group moderated the relationship between trait mindfulness and detached reappraisal responsiveness (β = 0.15, t(247) = −2.95, p = .003, 95% CI: [0.05, 0.25], ΔR2 = .04; see Figure 1). The follow-up simple slopes analysis revealed that higher trait mindfulness was associated with greater detached reappraisal responsiveness among older adults, whereas young adults did not exhibit a significant association between trait mindfulness and detached reappraisal responsiveness (older adults: β = 0.08, t(247) = 2.21, p = .028; young adults: β = −0.08, t(247) = −1.93, p = .055).

Table 5.

Mixed linear models assessing age differences in the effect of trait mindfulness on strategy use

Model Description Fixed Effects Estimate (SE) t-value p-value 95% CI
Acceptance Strategy Use ~ Sex + MCSDS + Age + MAAS + AgeXMAAS Intercept 1.98 (0.05) 37.88 < .001*** [1.88, 2.08]
Sex 0.08 (0.10) 0.82 .413 [−0.11, 0.28]
MCSDS 0.00 (0.01) 0.37 .712 [−0.02, 0.02]
Age 0.58 (0.11) −5.39 < .001*** [0.37, 0.79]
MAAS −0.04 (0.06) −0.64 .524 [−0.15, 0.08]
AgeXMAAS −0.05 (0.11) 0.40 .688 [−0.26, 0.17]
Positive Reappraisal Strategy Use ~ Sex + MCSDS + Age + MAAS + AgeXMAAS Intercept 0.98 (0.05) 19.64 < .001*** [0.89, 1.08]
Sex 0.15 (0.10) 1.51 .132 [−0.04, 0.34]
MCSDS 0.00 (0.01) 0.19 .848 [−0.02, 0.02]
Age 0.12 (0.10) 1.11 .266 [−0.09, 0.32]
MAAS −0.08 (0.06) −1.42 .157 [−0.19, 0.03]
AgeXMAAS −0.17 (0.11) −1.60 .110 [−0.38, 0.04]
Detached Reappraisal Strategy Use ~ Sex + MCSDS + Age + MAAS + AgeXMAAS Intercept 0.69 (0.04) 17.02 < .001*** [0.61, 0.77]
Sex −0.11 (0.08) −1.35 .179 [−0.26, 0.04]
MCSDS −0.01 (0.01) −1.86 .064 [−0.03, 0.00]
Age 0.15 (0.08) 1.79 .075 [−0.01, 0.31]
MAAS −0.03 (0.05) −0.60 .552 [−0.11, 0.06]
AgeXMAAS −0.04 (0.09) −0.42 .674 [−0.21, 0.13]
Distraction Strategy Use ~ Sex + MCSDS + Age + MAAS + AgeXMAAS Intercept 0.55 (0.03) 17.14 < .001*** [0.49, 0.61]
Sex −0.06 (0.06) −0.94 .348 [−0.18, 0.06]
MCSDS −0.02 (0.01) −2.82 .005** [−0.03, −0.01]
Age −0.28 (0.07) 4.29 < .001*** [−0.41, −0.15]
MAAS −0.08 (0.04) −2.26 .025* [−0.15, −0.01]
AgeXMAAS 0.01 (0.07) −0.15 .879 [−0.12, 0.14]
Expressive Suppression Strategy Use ~ Sex + Age + MCSDS + MAAS + AgeXMAAS Intercept 0.49 (0.03) 16.75 < .001*** [0.44, 0.55]
Sex 0.01 (0.06) 0.15 .884 [−0.10, 0.12]
MCSDS −0.02 (0.01) −2.80 .006** [−0.03, −0.00]
Age −0.01 (0.06) −0.12 .907 [−0.13, 0.11]
MAAS −0.14 (0.03) −4.37 < .001*** [−0.21, −0.08]
AgeXMAAS −0.05 (0.06) −0.84 .404 [−0.18, 0.07]
Situation Selection Strategy Use ~ Sex + MCSDS + Age + MAAS +AgeXMAAS Intercept 0.48 (0.04) 12.49 < .001*** [0.40, 0.55]
Sex 0.09 (0.07) 1.17 .244 [−0.06, 0.23]
MCSDS 0.00 (0.01) 0.43 .665 [−0.01, 0.02]
Age −0.10 (0.08) −1.26 .209 [−0.25, 0.05]
MAAS −0.06 (0.04) −1.37 .173 [−0.14, 0.02]
AgeXMAAS −0.12 (0.08) −1.45 .147 [−0.28, 0.04]
Open in a new tab

Note. MCSDS = Marlow-Crowne Social Desirability Scale, MAAS = Mindful Attention and Awareness Scale. Intercepts represent the grand-centered mean, sex and age group are effect coded (males = 0.5 and females = 0.5; young adults = −0.5 and older adults = 0.5), and participant intercepts were entered as random effects for all models.

*

p < .05

**

p < .01

***

p < .001.

Table 6.

Stepwise multiple linear regression models assessing age differences in the effect of trait mindfulness on strategy responsiveness

Model Description Fixed Effects Estimate (SE) t-value p-value
Model 1: Acceptance Responsiveness ~ Sex + MCSDS + Age + MAAS Intercept −0.06 (0.03) −2.29 .023*
Sex −0.04 (0.06) −0.72 .470
MCSDS 0.00 (0.01) 0.55 .581
Age −0.10 (0.06) −1.68 .094
MAAS 0.06 (0.03) 1.91 .058
Model 2: Acceptance Responsiveness ~ Sex + MCSDS + Age + MAAS + AgeXMAAS Intercept −0.07 (0.03) −2.28 .023*
Sex −0.04 (0.06) −0.76 .448
MCSDS 0.00 (0.01) 0.52 .603
Age −0.10 (0.06) −1.66 .099
MAAS 0.06 (0.03) 1.85 .065
AgeXMAAS 0.02 (0.06) −0.31 .755
Model 1 R2 = 0.03
Model 2 R2 = 0.03		 Δ R2 = 0.00
Model 1: Positive Reappraisal Responsiveness ~ Sex + MCSDS + Age + MAAS Intercept 0.20 (0.03) 7.46 < .001***
Sex −0.02 (0.05) −0.36 .720
MCSDS 0.00 (0.01) 0.60 .550
Age −0.11 (0.06) −1.92 .057
MAAS 0.08 (0.03) 2.54 .012*
Model 2: Positive Reappraisal Responsiveness ~ Sex + MCSDS + Age + MAAS + AgeXMAAS Intercept 0.18 (0.03) 6.64 < .001***
Sex −0.03 (0.05) −0.64 .521
MCSDS 0.00 (0.01) 0.42 .678
Age −0.10 (0.06) −1.80 .073
MAAS 0.07 (0.03) 2.30 .022*
AgeXMAAS 0.12 (0.06) 1.97 .050
Model 1 R2 = 0.04
Model 2 R2 = 0.05		 Δ R2 = 0.01
Model 1: Detached Reappraisal Responsiveness ~ Sex + MCSDS + Age + MAAS Intercept 0.27 (0.02) 11.44 < .001***
Sex 0.02 (0.05) 0.53 .599
MCSDS −0.00 (0.00) −0.90 .367
Age −0.10 (0.05) −1.96 .051
MAAS 0.01 (0.03) 0.38 .708
Model 2: Detached Reappraisal Responsiveness ~ Sex + MCSDS + Age + MAAS + AgeXMAAS Intercept 0.25 (0.02) 10.30 < .001***
Sex 0.00 (0.05) 0.10 .921
MCSDS −0.01 (0.00) −1.19 .236
Age −0.09 (0.05) −1.81 .072
MAAS 0.00 (0.03) 0.02 .981
AgeXMAAS 0.15 (0.05) 2.95 .003**
Model 1 R2 = 0.02
Model 2 R2 = 0.06		 Δ R2 = 0.04
Model 1: Distraction Responsiveness ~ Sex + MCSDS + Age + MAAS Intercept 0.20 (0.02) 8.96 < .001***
Sex 0.01 (0.05) 0.19 .846
MCSDS −0.00 (0.00) −0.77 .442
Age −0.09 (0.05) −1.81 .072
MAAS −0.02 (0.03) −0.89 .375
Model 2: Distraction Responsiveness ~ Sex + MCSDS + Age + MAAS + AgeXMAAS Intercept 0.19 (0.02) 8.19 < .001***
Sex −0.00 (0.05) −0.03 .978
MCSDS −0.00 (0.00) −0.91 .364
Age −0.08 (0.05) −1.72 .088
MAAS −0.03 (0.03) −1.07 .287
AgeXMAAS 0.08 (0.05) −1.52 .130
Model 1 R2 = 0.03
Model 2 R2 = 0.04		 Δ R2 = 0.01
Model 1: Expressive Suppression Responsiveness ~ Sex + MCSDS + Age + MAAS Intercept 0.31 (0.02) 13.58 < .001***
Sex 0.05 (0.05) 1.10 .272
MCSDS −0.00 (0.00) −0.97 .332
Age −0.10 (0.05) −2.01 .045*
MAAS −0.01 (0.03) −0.45 .652
Model 2: Expressive Suppression Responsiveness ~ Sex + MCSDS + Age + MAAS + AgeXMAAS Intercept 0.29 (0.02) 12.49 < .001***
Sex 0.03 (0.05) 0.76 .447
MCSDS −0.01 (0.00) −1.19 .235
Age −0.09 (0.05) −1.88 .061
MAAS −0.02 (0.03) −0.73 .466
AgeXMAAS 0.12 (0.05) −2.31 .022*
Model 1 R2 = 0.04
Model 2 R2 = 0.06		 Δ R2 = 0.02
Model 1: Situation Selection Responsiveness ~ Sex + MCSDS + Age + MAAS Intercept −0.02 (0.02) −0.84 .401
Sex −0.06 (0.04) −1.55 .122
MCSDS −0.00 (0.00) −0.52 .605
Age 0.01 (0.04) 0.24 .814
MAAS 0.01 (0.02) 0.36 .716
Model 2: Situation Selection Responsiveness ~ Sex + MCSDS + Age + MAAS + AgeXMAAS Intercept −0.02 (0.02) −0.98 .327
Sex −0.07 (0.04) −1.62 .106
MCSDS −0.00 (0.00) −0.57 .567
Age 0.01 (0.04) 0.27 .785
MAAS 0.01 (0.04) 0.29 .775
AgeXMAAS 0.03 (0.05) 0.62 .535
Model 1 R2 = 0.01
Model 2 R2 = 0.01		 Δ R2 = 0.00
Open in a new tab

Note. MCSDS = Marlow-Crowne Social Desirability Scale, MAAS = Mindful Attention and Awareness Scale. Intercepts represent the grand-centered mean, sex and age group are effect coded (males = 0.5 and females = 0.5; young adults = −0.5 and older adults = 0.5).

*

p < .05

**

p < .01

***

p < .001.

Additionally, age group significantly moderated the relationship between trait mindfulness and expressive suppression responsiveness (β = 0.12, t(247) = 2.31, p = .022, 95% CI: [0.02, 0.22], ΔR2 = .02; see Figure 2) such that higher trait mindfulness was associated with less expressive suppression responsiveness among young adults (β = −0.08, t(247) = −2.02, p = .045) but not among older adults (β = 0.04, t(247) = 1.16, p = .246). Age group did not significantly moderate the relationship between trait mindfulness and within-strategy responsiveness for acceptance, positive reappraisal, distraction, or situation selection (all ps ≥ .050). All age moderation analyses for strategy use and strategy responsiveness were also conducted using age as a continuous predictor, but results were unchanged (see Results, Table S1, and Table S2 of the Supplementary Material).

Figure 2. Age Moderation of Trait Mindfulness on Expressive Suppression Responsiveness.

Figure 2.

Open in a new tab

Note: Separate trendlines reflect the relationship between trait mindfulness and expressive suppression responsiveness within the two age groups. X-axis: Grand mean-centered trait mindfulness scores; Y-axis: Expressive suppression responsiveness scores. Simple slopes analysis displayed using 95% confidence intervals. Solid line represents a significant slope and dashed line represents a non-significant slope.

Discussion

The present study examined the relationship between trait mindfulness and patterns of emotion regulation strategy use and responsiveness in daily life using a day reconstructive measurement method (Kahneman et al., 2004). Across the full sample, trait mindfulness was associated with reduced expressive suppression and distraction use. Contrary to our hypotheses, no significant relationships were observed for acceptance, positive reappraisal, detached reappraisal, or situation selection strategy use. Age did not significantly moderate the relationship between trait mindfulness and strategy use for any of the six strategies. Although our strategy use hypotheses were largely unsupported, these findings suggest that trait mindfulness, irrespective of age, is negatively associated with strategies aimed at minimizing or avoiding negative emotions in daily life. Despite prior studies linking trait mindfulness with greater use of adaptive strategies, much of past work has relied on global trait-like measures of strategy use, such as the Acceptance and Action Questionnaire (Boelen & Lenferink, 2018; Hayes et al., 2004) and the Cognitive and Emotion Regulation Questionnaire (Garnefski & Kraaij, 2007; Hanley & Garland, 2014). The current study, in contrast, employed an idiographic day reconstruction method which measures strategy use collected across multiple emotional episodes within a single day.

Additionally, in contrast to findings from Keng et al. (2018), we did not find a significant relationship between trait mindfulness and any of the six within-strategy responsiveness metrics across the full sample. These null findings suggest that prior evidence linking trait mindfulness to increased flexibility components may not replicate in a sample of both young and older adults. To test this hypothesis explicitly, our exploratory aim assessed whether age moderated relationships between trait mindfulness and emotion regulation responsiveness metrics. In line with our predictions, trait mindfulness was negatively associated with expressive suppression responsiveness among young adults only. Unexpectedly, trait mindfulness was positively associated with detached reappraisal responsiveness among older adults only. However, inconsistent with our predictions, age did not moderate associations between trait mindfulness and situation selection responsiveness.

Taken together, these findings suggest that the effect of trait mindfulness on context-dependent emotion regulation strategy use, relative to consistent strategy use, may be more sensitive to age-related differences. Our finding that trait mindfulness was negatively related to expressive suppression responsiveness (i.e., as negative affect increases, expressive suppression use decreases) in young adults might suggest that being mindful facilitates greater openness to expressing negative emotions. Being mindful may be particularly advantageous for young adults in which expressive suppression has been reliably associated with poorer emotional outcomes (Aldao & Dixon-Gordon, 2014; Moore et al., 2008). In contrast, for older adults the adaptiveness of expressive suppression remains more equivocal. Supporting this notion, results from the parent study (Whitmoyer et al., 2022) showed that greater expressive suppression responsiveness was linked to increased emotion dysregulation and reduced affect balance in young adults but was negatively associated with emotion dysregulation among older adults.

Although unexpected, our finding that trait mindfulness was associated with greater detached reappraisal responsiveness (i.e., as negative affect increases, detached reappraisal use increases) among older adults might reflect that those with higher trait levels of present-moment awareness have an increased tendency to respond to negative situations using a distanced, “third-person” perspective. This result is surprising given that detached reappraisal is considered a more cognitively demanding strategy that older adults are less able to implement effectively compared to young adults—potentially due to age-related declines in cognitive abilities (Liang et al., 2017; Shiota & Levenson, 2009). Our result suggests that older adults who are more mindful may be better equipped to implement detached reappraisal, and this could be due to their increased ability to attend to present-moment experiences. Along these lines, a recent meta-analysis found that unidimensional measurements of trait mindfulness, such as the MAAS, are associated with better attentional outcomes (Verhaeghen, 2021). However, because attention and other cognitive measures were not included in our current study, this interpretation remains speculative. To test this hypothesis, future studies should examine the moderating and/or mediating role of cognition in the relationship between trait mindfulness and components of emotion regulation flexibility.

Although our primary hypotheses were largely unsubstantiated, a subtle but potentially critical difference between the current study and prior work lies in the measurement of trait mindfulness itself. Prior studies assessing emotion strategy use and components of flexibility have utilized multi-faceted measures of trait mindfulness, such as the Five Facet Mindfulness Questionnaire (Hanley & Garland; Keng et al., 2018) which consists of five facets—observing, describing, acting with awareness, nonjudging, and nonreactivity. The MAAS, used in the current study, is widely considered a unitary measure of “awareness” and it does not explicitly assess for other mindfulness-related attributes, such as acceptance or nonreactivity. Consequently, despite strong conceptual overlap between trait mindfulness and acceptance strategy use, one reason that we were unable to find support for the hypothesized relationship between trait mindfulness and acceptance use/responsiveness may lie in the fact that the MAAS does not explicitly assess for the acceptance of emotional states.

Limitations and Future Research

The present study demonstrated several notable strengths. First, the current study utilized a hybrid diary and experience sampling method approach, and this provided a more ecologically valid assessment of negative affect and emotion regulation strategy use in daily life situations compared to typical laboratory-based tasks. Asking participants to separate a single day into multiple emotional episodes also allows for repeated measurements while reducing the risks common to longitudinal designs (e.g., participant dropout). Second, we assessed trait mindfulness and patterns of emotion regulation in a community sample of older and younger adults, thereby increasing the generalizability of our findings to a broader adult population and enabling the investigation of age-related effects. Our findings provide preliminary support that trait mindfulness differentially relates to patterns of emotion regulation responsiveness in daily emotional situations with increasing age, providing an empirical foundation from which to further understand how trait mindfulness relates to emotion regulation across the lifespan.

Although our study assessed how trait mindfulness relates to strategy responsiveness in daily life using a sample of young and older adults, the current findings were limited by several factors. First, considerable conceptual and methodological ambiguities associated with the measurement of trait mindfulness challenge the interpretation of observed outcomes. Although a full discussion on this topic is beyond the scope of the present study and is discussed elsewhere (see Van Dam et al., 2018), one of the primary criticisms of self-report assessments of trait mindfulness lies in their measurement. For example, the MAAS is a reverse-scored measure, and this makes it difficult to determine whether mindfulness or a lack thereof is being measured (Grossman & Van Dam, 2011). Second, the correlational design of the current study precludes any interpretations about causality. Mindfulness-based intervention studies could be conducted to assess whether changes in trait mindfulness as a function of long-term mindfulness training mediate changes in emotion regulation strategy use and responsiveness.

Third, environmental differences in the lives of young and older adults limit interpretations of the observed age-related differences in emotion regulation responsiveness. Specifically, young adults, relative to older adults, typically have less stable environments and tend to experience more negatively valanced emotional situations in daily life (Charles & Carstensen, 2010). As such, age-related environmental differences and their impact on emotionality may have contributed to the observed moderations. Future studies would benefit from assessing multiple environmental features of each emotional episode to delineate whether emotional contexts differ between young and older adults. Fourth, our study did not include middle-aged adults (ages 35–65) and our sample was less racially and ethnically diverse than the U.S. population (U.S. Census Bureau, 2021), particularly for our older adult sample. Therefore, it remains unclear when age-related shifts in the observed findings occur and whether these effects would replicate with a more demographically diverse sample. To address this limitation, future studies could conduct an accelerated longitudinal design with multiple age cohorts (i.e., young, middle-aged, and older adults) that are more racially and ethnically diverse. Doing so would allow researchers to explicitly test for both within- and between-age group differences in the relationship between trait mindfulness and emotion regulation strategy use/responsiveness.

Finally, because the current study was a secondary analysis of the parent study, a priori power analyses for the current aims were not conducted. As such, we may have been underpowered to detect effects between trait mindfulness and emotion regulation responsiveness. Two post-hoc sensitivity analyses were conducted using G*Power 3 (Faul et al., 2007) for our aims focused on emotion regulation responsiveness using our final sample size (N = 253). For our primary aim assessing the relationship between trait mindfulness and emotion regulation responsiveness across the full sample, using an alpha level of .008 with three predictors at .80 power, we would need to observe an effect size (R2) of .06 to detect a significant effect. For our exploratory aim assessing age moderations of this relationship, using an alpha level of .05 with five predictors at .80 power, we would need to observe an increase in R2 of .03 to detect a significant age interaction effect.

Despite these limitations, the current study provided several directions for future research. First, considering the challenges associated with the measurement of trait mindfulness via self-report questionnaires, future studies may benefit from employing more direct behavioral measures of mindfulness, such as the breath counting task (Levinson et al., 2014). By utilizing both self-report and behavioral indices of mindfulness, researchers could explicitly examine whether study findings are mirrored or differ across measurements of mindfulness (see Lin et al., 2021 for a prescriptive approach). Second, given concerns about participants’ ability to retrospectively recall emotional experiences from the day prior, EMA methods could be used to capture real-time measures of negative valence and emotion strategy use. By leveraging this approach, researchers can reduce the likelihood of recall bias and assess emotional experiences over the course of several days, weeks, or months. Moreover, behavioral measures of mindfulness could also be assessed using EMA approaches and aggregated into a composite score to provide a more robust and ecologically valid measure of trait mindfulness. Lastly, although the current study found age-differences in the relationship between trait mindfulness and within-strategy emotion regulation responsiveness, future studies should conduct longitudinal mindfulness training studies with more racially and ethnically diverse samples to test explicitly whether changes in trait mindfulness produce meaningful changes in emotion regulation responsiveness. Not only would this design provide a more powerful approach to assessing whether the effects differ between age groups but would also allow for stronger inferences to be made about the generalizability of findings to a more racially and ethnically representative sample of adults.

Supplementary Material

Supplementary Materials

Acknowledgements.

This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under grant number 1840280. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. This research was also supported by the National Institute of Aging of the National Institutes of Health under award number R01AG054427. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Health.

Ethical Standards

The current study was approved by the appropriate ethics committee and was performed in accordance with the ethical standards laid down in the Declaration 164 of Helsinki and its later amendments. All study procedures were approved by the Ohio State University Institutional Review Board (IRB# 2018B0146) and all participants provided informed consent prior to participating.

Footnotes

Conflict of Interest

The authors declare that they have no conflict of interest.

Data Availability Statement

All hypotheses and statistical analyses used for the current manuscript were pre-registered (osf.io/z5g8v) on Open Science Framework. Additionally, all data and code used for the current manuscript are available on Open Science Framework (osf.io/57es9).

References

  1. Aldao A, & Dixon-Gordon KL (2014). Broadening the scope of research on emotion regulation strategies and psychopathology. Cognitive Behaviour Therapy, 43(1), 22–33. 10.1080/16506073.2013.816769 [DOI] [PubMed] [Google Scholar]
  2. Aldao A, Nolen-Hoeksema S, & Schweizer S. (2010). Emotion-regulation strategies across psychopathology: A meta-analytic review. Clinical Psychology Review, 30(2), 217–237. 10.1016/j.cpr.2009.11.004 [DOI] [PubMed] [Google Scholar]
  3. Aldao A, Sheppes G, & Gross JJ (2015). Emotion regulation flexibility. Cognitive Therapy and Research, 39(3), 263–278. 10.1007/s10608-014-9662-4 [DOI] [Google Scholar]
  4. Alkoby A, Pliskin R, Halperin E, & Levit-Binnun N. (2019). An eight-week mindfulness-based stress reduction (MBSR) workshop increases regulatory choice flexibility. Emotion, 19(4), 593–604. 10.1037/emo0000461 [DOI] [PubMed] [Google Scholar]
  5. Allen VC, & Windsor TD (2019). Age differences in the use of emotion regulation strategies derived from the process model of emotion regulation: A systematic review. Aging & Mental Health, 23(1), 1–14. 10.1080/13607863.2017.1396575 [DOI] [PubMed] [Google Scholar]
  6. Bates D, Mächler M, Bolker B, & Walker S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1–48. 10.18637/jss.v067.i01 [DOI] [Google Scholar]
  7. Benson L, English T, Conroy DE, Pincus AL, Gerstorf D, & Ram N. (2019). Age differences in emotion regulation strategy use, variability, and flexibility: An experience sampling approach. Developmental Psychology, 55(9), 1951–1964. 10.1037/dev0000727 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Boelen PA, & Lenferink LIM (2018). Experiential acceptance and trait-mindfulness as predictors of analogue post-traumatic stress. Psychology and Psychotherapy: Theory, Research and Practice, 91(1), 1–14. 10.1111/papt.12138 [DOI] [PubMed] [Google Scholar]
  9. Bonanno GA, & Burton CL (2013). Regulatory flexibility: An individual differences perspective on coping and emotion regulation. Perspectives on Psychological Science, 8(6), 591–612. 10.1177/1745691613504116 [DOI] [PubMed] [Google Scholar]
  10. Bravo AJ, Lindsay EK, & Pearson MR (2022). Nature, assessment, and mechanisms of mindfulness. In Medvedev ON, Krägeloh CU, Siegert RJ, & Singh NN (Eds.), Handbook of Assessment in Mindfulness Research (pp. 1–12). Springer International Publishing. 10.1007/978-3-030-77644-2_2-1 [DOI] [Google Scholar]
  11. Brown KW, & Ryan RM (2003). The benefits of being present: Mindfulness and its role in psychological well-being. Journal of Personality and Social Psychology, 84(4), 822–848. 10.1037/0022-3514.84.4.822 [DOI] [PubMed] [Google Scholar]
  12. Charles ST, & Carstensen LL (2010). Social and emotional aging. Annual Review of Psychology, 61, 383–409. 10.1146/annurev.psych.093008.100448 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Dark-Freudeman A, Jones C, & Terry C. (2021). Mindfulness, anxiety, and perceived stress in university students: Comparing a mindfulness-based intervention (MBI) against active and traditional control conditions. Journal of American College Health,. 10.1080/07448481.2020.1845180 [DOI] [PubMed] [Google Scholar]
  14. Desbordes G, Gard T, Hoge EA, Hölzel BK, Kerr C, Lazar SW, Olendzki A, & Vago DR (2015). Moving beyond mindfulness: Defining equanimity as an outcome measure in meditation and contemplative research. Mindfulness, 6(2), 356–372. 10.1007/s12671-013-0269-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Desrosiers A, Vine V, Klemanski DH, & Nolen-Hoeksema S. (2013). Mindfulness and emotion regulation in depression and anxiety: Common and distinct mechanisms of action. Depression and Anxiety, 30(7), 654–661. 10.1002/da.22124 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Faul F, Erdfelder E, Lang A-G, & Buchner A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. 10.3758/BF03193146 [DOI] [PubMed] [Google Scholar]
  17. Feldman G, Hayes A, Kumar S, Greeson J, & Laurenceau J-P (2007). Mindfulness and emotion regulation: The development and initial validation of the cognitive and affective mindfulness scale-revised (CMS-R). Journal of Psychopathology and Behavioral Assessment, 29(3), 177–190. psyh. 10.1007/s10862-006-9035-8 [DOI] [Google Scholar]
  18. Fiocco AJ, & Mallya S. (2015). The importance of cultivating mindfulness for cognitive and emotional well-being in late life. Journal of Evidence-Based Complementary & Alternative Medicine, 20(1), 35–40. 10.1177/2156587214553940 [DOI] [PubMed] [Google Scholar]
  19. Garnefski N, & Kraaij V. (2007). The cognitive emotion regulation questionnaire. European Journal of Psychological Assessment, 23(3), 141–149. 10.1027/1015-5759.23.3.141 [DOI] [Google Scholar]
  20. Gross JJ (1998). Antecedent-and response-focused emotion regulation: Divergent consequences for experience, expression, and physiology. Journal of Personality and Social Psychology, 74(1), 224. [DOI] [PubMed] [Google Scholar]
  21. Gross JJ (2015). Emotion regulation: Current status and future prospects. Psychological Inquiry, 26(1), 1–26. 10.1080/1047840X.2014.940781 [DOI] [Google Scholar]
  22. Grossman P, & Van Dam NT (2011). Mindfulness, by any other name…: Trials and tribulations of sati in western psychology and science. Contemporary Buddhism, 12(1), 219–239. 10.1080/14639947.2011.564841 [DOI] [Google Scholar]
  23. Hanley AW, & Garland EL (2014). Dispositional mindfulness co-varies with self-reported positive reappraisal. Personality and Individual Differences, 66, 146–152. 10.1016/j.paid.2014.03.014 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Harris P, Taylor R, Thielke R, Payne J, Gonzalez N, & Conde J. (2009). Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics support. Journal of Biomedical Informatics, 42, 377–381. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Hayes SC, Strosahl K, Wilson KG, Bissett RT, Pistorello J, Toarmino D, Polusny MA, Dykstra TA, Batten SV, Bergan J, Stewart SH, Zvolensky MJ, Eifert GH, Bond FW, Forsyth JP, Karekla M, & McCurry SM (2004). Measuring experiential avoidance: A preliminary test of a working model. Psychological Record, 54(4), 553–578. 10.1007/BF03395492 [DOI] [Google Scholar]
  26. Holzel BK, Carmody J, Vangel M, Congelton C, Yerramsetti SM, Gard T, & Lazar SW (2011). Mindfulness practice leads to increase in regional brain gray matter density. Psychiatry Research: Neuroimaging, 191, 36–43. 10.1016/j.psychresns.2010.08.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Hughes J, & Beiner D. (2022). Helper functions for regression analysis (1.1.1) [R]. [Google Scholar]
  28. Kabat-Zinn J. (1990). Full catastrophe living: Using the wisdom of your body and mind to face stress, pain, and illness. Delta. [Google Scholar]
  29. Kahneman D, Krueger AB, Schkade DA, Schwarz N, & Stone AA (2004). A survey method for characterizing daily life experience: The day reconstruction method. Science, 306(5702), 1776–1780. 10.1126/science.1103572 [DOI] [PubMed] [Google Scholar]
  30. Keng S-L, Choo X, & Tong EMW (2018). Association between trait mindfulness and variability of coping strategies: A diary study. Mindfulness, 9(5), 1423–1432. 10.1007/s12671-018-0885-4 [DOI] [Google Scholar]
  31. Kiken LG, Garland EL, Bluth K, Palsson OS, & Gaylord SA (2015). From a state to a trait: Trajectories of state mindfulness in meditation during intervention predict changes in trait mindfulness. Personality and Individual Differences, 81, 41–46. 10.1016/j.paid.2014.12.044 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Kobayashi R, Miyatani M, & Nakao T. (2021). High working memory capacity facilitates distraction as an emotion regulation strategy. Current Psychology, 40(3), 1159–1167. 10.1007/s12144-018-0041-2 [DOI] [Google Scholar]
  33. Kuznetsova A, Brockhoff PB, & Christensen RHB (2017). lmerTest Package: Tests in linear mixed effects models. Journal of Statistical Software, 82(1), 1–26. 10.18637/jss.v082.i13 [DOI] [Google Scholar]
  34. Lenth R. (2021). emmeans: Estimated marginal means, aka least-squares means. [R package version 1.6.2–1]. https://CRAN.R-project.org/package=emmeans [Google Scholar]
  35. Levinson DB, Stoll EL, Kindy SD, Merry HL, & Davidson RJ (2014). A mind you can count on: Validating breath counting as a behavioral measure of mindfulness. Frontiers in Psychology, 5. 10.3389/fpsyg.2014.01202 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Liang Y, Huo M, Kennison R, & Zhou R. (2017). The role of cognitive control in older adult cognitive reappraisal: Detached and positive reappraisal. Frontiers in Behavioral Neuroscience, 11. 10.3389/fnbeh.2017.00027 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Lin Y, Tang R, & Braver TS (2021). Investigating mindfulness influences on cognitive function: On the promise and potential of converging research strategies. Psychonomic Bulletin & Review. 10.3758/s13423-021-02008-6 [DOI] [PubMed] [Google Scholar]
  38. Livingstone KM, & Isaacowitz DM (2018). The roles of age and attention in general emotion regulation, reappraisal, and expressive suppression. Psychology and Aging, 33(3), 373–383. 10.1037/pag0000240 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Livingstone KM, & Isaacowitz DM (2021). Age and emotion regulation in daily life: Frequency, strategies, tactics, and effectiveness. Emotion, 21(1), 39–51. 10.1037/emo0000672 [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Lucas RE, Wallsworth C, Anusic I, & Donnellan MB (2021). A direct comparison of the day reconstruction method (DRM) and the experience sampling method (ESM). Journal of Personality and Social Psychology, 120(3), 816–835. 10.1037/pspp0000289 [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Lyvers M, Makin C, Toms E, Thorberg FA, & Samios C. (2014). Trait mindfulness in relation to emotional self-regulation and executive function. Mindfulness, 5(6), 619–625. 10.1007/s12671-013-0213-y [DOI] [Google Scholar]
  42. Mahoney CT, Segal DL, & Coolidge FL (2015). Anxiety sensitivity, experiential avoidance, and mindfulness among younger and older adults: Age differences in risk factors for anxiety symptoms. International Journal of Aging & Human Development, 81(4), 217–240. 10.1177/0091415015621309 [DOI] [PubMed] [Google Scholar]
  43. McLaughlin LE, Luberto CM, O’Bryan EM, Kraemer KM, & McLeish AC (2019). The indirect effect of positive affect in the relationship between trait mindfulness and emotion dysregulation. Personality and Individual Differences, 145, 70–74. 10.1016/j.paid.2019.03.020 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Moore SA, Zoellner LA, & Mollenholt N. (2008). Are expressive suppression and cognitive reappraisal associated with stress-related symptoms? Behaviour Research and Therapy, 46(9), 993–1000. 10.1016/j.brat.2008.05.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Nolen-Hoeksema S, & Aldao A. (2011). Gender and age differences in emotion regulation strategies and their relationship to depressive symptoms. Personality and Individual Differences, 51(6), 704–708. 10.1016/j.paid.2011.06.012 [DOI] [Google Scholar]
  46. Prakash RS, Hussain MA, & Schirda B. (2015). The role of emotion regulation and cognitive control in the association between mindfulness disposition and stress. Psychology and Aging, 30(1), 160–171. 10.1037/a0038544 [DOI] [PubMed] [Google Scholar]
  47. Prakash RS, Whitmoyer P, Aldao A, & Schirda B. (2017). Mindfulness and emotion regulation in older and young adults. Aging & Mental Health, 21(1), 77–87. 10.1080/13607863.2015.1100158 [DOI] [PubMed] [Google Scholar]
  48. Pruessner L, Barnow S, Holt DV, Joormann J, & Schulze K. (2020). A cognitive control framework for understanding emotion regulation flexibility. Emotion, 20(1), 21–29. 10.1037/emo0000658 [DOI] [PubMed] [Google Scholar]
  49. Qualtrics (Version 2019). (2019). Qualtrics. https://www.qualtrics.com [Google Scholar]
  50. Rau HK, & Williams PG (2016). Dispositional mindfulness: A critical review of construct validation research. Personality and Individual Differences, 93, 32–43. 10.1016/j.paid.2015.09.035 [DOI] [Google Scholar]
  51. Roemer L, Williston SK, & Rollins LG (2015). Mindfulness and emotion regulation. Current Opinion in Psychology, 3, 52–57. 10.1016/j.copsyc.2015.02.006 [DOI] [Google Scholar]
  52. Sands M, & Isaacowitz DM (2017). Situation selection across adulthood: The role of arousal. Cognition & Emotion, 31(4), 791–798. 10.1080/02699931.2016.1152954 [DOI] [PubMed] [Google Scholar]
  53. Scheibe S, & Carstensen LL (2010). Emotional aging: Recent findings and future trends. Journals of Gerontology Series B-Psychological Sciences and Social Sciences, 65(2), 135–144. 10.1093/geronb/gbp132 [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Schneider S, Junghaenel DU, Gutsche T, Mak HW, & Stone AA (2020).Comparability of emotion dynamics derived from ecological momentary assessments, daily diaries, and the day reconstruction method: Observational study. Journal of Medical Internet Research, 22(9):e19201. 10.2196/19201 [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Sheppes G, Scheibe S, Suri G, & Gross JJ (2011). Emotion-regulation choice. Psychological Science, 22(11), 1391–1396. 10.1177/0956797611418350 [DOI] [PubMed] [Google Scholar]
  56. Shiota MN, & Levenson RW (2009). Effects of aging on experimentally instructed detached reappraisal, positive reappraisal, and emotional behavior suppression. Psychology and Aging, 24(4), 890–900. 10.1037/a0017896 [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Shook NJ, Ford C, Strough J, Delaney R, & Barker D. (2017). In the moment and feeling good: Age differences in mindfulness and positive affect. Translational Issues in Psychological Science, 3(4), 338–347. 10.1037/tps0000139 [DOI] [Google Scholar]
  58. Tamagawa R, Giese‐Davis J, Speca M, Doll R, Stephen J, & Carlson LE (2013). Trait mindfulness, repression, suppression, and self-reported mood and stress symptoms among women with breast cancer. Journal of Clinical Psychology, 69(3), 264–277. 10.1002/jclp.21939 [DOI] [PubMed] [Google Scholar]
  59. Teper R, Segal ZV, & Inzlicht M. (2013). Inside the mindful mind: How mindfulness enhances emotion regulation through improvements in executive control. Current Directions in Psychological Science, 22(6), 449–454. 10.1177/0963721413495869 [DOI] [Google Scholar]
  60. Urry HL, & Gross JJ (2010). Emotion regulation in older age. Current Directions in Psychological Science, 19(6), 352–357. 10.1177/0963721410388395 [DOI] [Google Scholar]
  61. U.S. Census Bureau. (2021). U.S. Census Bureau QuickFacts: United States. https://www.census.gov/quickfacts/fact/table/US/PST045221 [Google Scholar]
  62. Van Dam NT, van Vugt MK, Vago DR, Schmalzl L, Saron CD, Olendzki A, Meissner T, Lazar SW, Kerr CE, Gorchov J, Fox KCR, Field BA, Britton WB, Brefczynski-Lewis JA, & Meyer DE (2018). Mind the hype: A critical evaluation and prescriptive agenda for research on mindfulness and meditation. Perspectives on Psychological Science, 13(1), 36–61. 10.1177/1745691617709589 [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Verhaeghen P. (2021). Mindfulness as attention training: Meta-analyses on the links between attention performance and mindfulness interventions, long-term meditation practice, and trait mindfulness. Mindfulness, 12(3), 564–581. 10.1007/s12671-020-01532-1 [DOI] [Google Scholar]
  64. Welsh KA, Breitner JC, & Magruder-Habib KM (1993). Detection of dementia in the elderly using telephone screening of cognitive status. Neuropsychiatry, Neuropsychology,& Behavioral Neurology, 6(2), 103–110. [Google Scholar]
  65. Whitmoyer P, Fisher M, Duraney E, Manzler C, Isaacowitz D, Andridge R, & Prakash RS (2022). Age differences in emotion regulation strategy use in daily life: Implications for emotional well-being. PsyArXiv. https://psyarxiv.com/z2swh [DOI] [PubMed] [Google Scholar]
  66. Wolgast M, & Lundh LG (2017). Is distraction an adaptive or maladaptive strategy for emotion regulation? A person-oriented approach. Journal of Psychopathology &Behavioral Assessment, 39(1), 117–127. 10.1007/s10862-016-9570-x [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Materials
NIHMS1928151-supplement-Supplementary_Materials.docx (312.2KB, docx)

Data Availability Statement

All hypotheses and statistical analyses used for the current manuscript were pre-registered (osf.io/z5g8v) on Open Science Framework. Additionally, all data and code used for the current manuscript are available on Open Science Framework (osf.io/57es9).

RESOURCES