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. Author manuscript; available in PMC: 2024 Mar 1.
Published in final edited form as: Emotion. 2022 Apr 14;23(2):589–594. doi: 10.1037/emo0001087

Fluid and Crystallized Cognitive Resources Differentially Linked to Emotion Regulation Success in Adulthood

Claire M Growney 1, Tammy English 1
PMCID: PMC9985456  NIHMSID: NIHMS1844174  PMID: 35420833

Abstract

Effective emotion regulation (ER) is theorized to require cognitive resources. Past work has identified inconsistent relationships between cognitive ability and ER success, and has focused on implementation of instructed ER strategies. In the present study, we examine a wide range of cognitive abilities as predictors of ER success in the absence of constraints on strategy selection. An age-diverse sample of participants (N = 129, age 25–83) completed an ER task in which they viewed film clips eliciting disgust, sadness, and amusement under instructions to regulate in a pro-hedonic fashion. ER success was measured through self-reports of positive emotion (PA) and negative emotion (NA) following each clip. Fluid and crystallized cognitive ability were assessed with tasks from the NIH Toolbox Cognitive Battery. Effects of fluid cognition varied by film type, such that fluid cognition was generally less associated with ER success for the disgust clip. Effects of fluid cognition also varied by facet (e.g., processing speed and inhibitory control related to lower NA with the sadness clip, while working memory and episodic memory related to higher PA with the amusement and disgust clips). Crystallized cognition was positively associated with ER success (lower NA) across film types. Findings suggest that both fluid and crystallized cognition are important resources for effective emotion regulation. We propose that crystallized cognition may be particularly important when regulators can rely on life experience to select ER strategies.

Keywords: Emotion regulation, fluid cognition, crystallized cognition, well-being, adult lifespan

The ability to regulate one’s emotions is a key component of well-being. Emotion regulation (ER) refers to processes involved in modulating when, how long, and to what extent one experiences and expresses emotions (Gross, 1998). After identifying the need to regulate, effective ER involves selecting an ER strategy, implementing that strategy in service of one’s emotional goals, and monitoring emotion to determine whether regulation efforts should be stopped or modified (Gross, 2015). These processes are viewed as effortful and demanding of cognitive resources (Isaacowitz & Blanchard-Fields, 2012). However, despite normative decrements in fluid cognition which occur with age (Salthouse, 2009), emotional well-being is maintained or improved (Burr et al., 2020; Carstensen et al., 2011), at least until near the end of life (Gerstorf & Ram, 2015). One explanation for this pattern of findings is that older adults’ stronger motivation to maintain emotional well-being (Carstensen, 2006) may lead them to utilize other available resources to help meet their emotional goals (Urry & Gross, 2010), such as expertise gained through life experience (Blanchard-Fields, 2007) which may be reflected more in crystallized cognition. In the present study, we investigate how ER success is related to individual differences in various aspects of cognitive ability in an age-diverse sample.

The majority of research examining associations between cognitive resources and ER success has focused on fluid cognitive ability, which is thought to rely on biological factors and involves accessing, processing, and manipulating information (McArdle et al., 2002). Fluid cognition is a multifaceted construct, and therefore may be important for ER success in a number of ways. Working memory may be useful for monitoring change in one’s situation and emotions. Cognitive flexibility may be involved in altering emotional responses to changes in one’s environment. Inhibitory control may be used to direct attention regarding environmental features or thoughts in a way that helps meet emotional goals. Processing speed may be implicated in quickly assessing one’s situation and need for ER. Episodic memory may be important for remembering the source of emotions which need to be regulated or remembering previous situations where strategies were or were not successfully used. Prior studies examining associations between cognition and ER success have focused primarily on the first three facets, known as cognitive control processes (Miyake et al., 2000), and have yielded mixed findings (e.g., Hendricks & Buchanan, 2016; Liang et al., 2017; McRae et al., 2012; Malooly et al., 2013; Schmeichel et al., 2014). These studies assessing facets of fluid cognitive ability have typically examined ER effectiveness using instructed strategies (e.g., reappraisal; Opitz et al., 2014), which fails to consider how strategy selection draws on cognitive ability. Prior work in this area also primarily involves younger adults, who likely do not represent the wide range of fluid cognitive ability observed throughout adulthood.

Crystallized cognitive ability, broadly defined as acquired knowledge, is relatively maintained into older adulthood (McArdle et al., 2002) and may reflect the accumulated life experience on which older adults are theorized to rely for effective ER (Blanchard-Fields, 2007). In the present paper we refer to crystallized cognitive ability rather than crystallized intelligence because of the applied nature of the assessments we use to measure this construct. Additionally, crystallized cognitive ability better reflects that access to knowledge largely relies on fluid abilities (Horn & Hofer, 1992), with both fluid and crystallized abilities being neurobiologically instantiated. Research examining crystallized cognition as a predictor of ER success is limited, and there is no consensus across the few existing studies. Emotional intelligence researchers have identified positive relationships between crystallized cognitive ability and emotion management in theoretical situations (see Fiori & Vesely-Maillefer, 2018 for review). However, there was no relationship between vocabulary skills and ER success in two other studies (with sad stimuli: Opitz et al., 2014; with high-arousal negative stimuli: McRae et al., 2012) in which participants were instructed to use a particular ER strategy.

We hypothesized that both fluid and crystallized cognitive ability will be associated with greater ER success when strategy selection is unconstrained. To test this idea, we presented participants with emotional clips under instructions to regulate in a pro-hedonic fashion, decreasing negative emotions and increasing positive emotions. Importantly, we did not instruct use of specific strategies, forming a context in which ER success depends on both effective strategy selection and implementation. We assessed a broad range of cognitive abilities (working memory, cognitive flexibility, inhibitory control, processing speed, episodic memory, and language).

Given the importance of arousal level (Charles, 2010) and emphasis on maintaining positive affect (rather than minimizing negative affect) in older adulthood (Riediger et al., 2014), we used a within-subjects design to examine regulation during film clips that each primarily elicit one of three emotions: disgust (a high-arousal negative emotion), sadness (a lower-arousal negative emotion), and amusement (a positive emotion). We explored whether effects of fluid and crystallized cognition vary across film type.

Methods

All materials and procedures were approved by the Institutional Review Board at Washington University in St. Louis.

Participants

Participants were recruited through community postings and paid for their participation. Individuals were ineligible if they were not fluent in English or scored above 1 on the Ascertain Dementia 8-item Questionnaire (adapted from Galvin et al., 2005). The sample included 129 adults aged 25–83 (M = 55.42, SD = 17.33; 52.7% women), diverse in terms of race (26.4% African-American, 60.5% European-American/White, 13.1% other or multiple races).

Procedure

After providing informed consent, participants completed the ER film task, then a trained experimenter administered the NIH Toolbox cognitive battery using an iPad. Demographics and additional questionnaires not relevant to the present study were also completed.

Materials

ER Task

The ER task involved an initial reactivity block followed by a regulation block. Each of these blocks included three trials in which short film clips eliciting disgust, sadness, and amusement were presented in a random order. The reactivity block was under natural viewing conditions: “Just watch the film as though you were watching TV at home or in a movie theater. Try to respond naturally without changing how you feel in any way.” In the ER block participants were instructed to regulate in a pro-hedonic fashion: “This time, as you watch the clip, please try to manage your emotions so that you feel more positive and less negative. Use any strategy you have available to turn negative feelings into positive ones and to keep your positive feelings going.” All films were validated to elicit target emotions in age-diverse samples (e.g., Gyurak et al., 2012; Shiota & Levenson, 2009; for additional information see Table S3).

After each clip, participants rated their current experience of emotions (1 = Not at all to 7 = Extremely). At each point, we computed the average negative affect (NA; sad, disgusted, and anxious; average 𝛼=.60) and positive affect (PA; amused, excited, and happy; average 𝛼=.79).

Cognitive Ability Assessments

A broad range of cognitive abilities were assessed using the NIH Toolbox Cognitive Battery, validated for use in adults up to age 85 (Mungas et al., 2014). Higher scores indicate better performance. The present study uses uncorrected standard scores, which compare an individual’s performance with the general U. S. population (normative M=100, SD=15). Five facets of fluid cognition were assessed to create a fluid cognitive ability composite: cognitive flexibility, inhibitory control, working memory, episodic memory, and processing speed (Cronbach’s α=.76). Tests of vocabulary knowledge and reading decoding skill form the composite score of crystallized cognitive ability (Cronbach’s α=.81). Information about each test is available in Supplemental Materials.

Results

Analytic Plan

Descriptive statistics and bivariate correlations are displayed in Tables 1 and S1. In general, the disgust and sadness films elicited NA and the amusement film elicited PA. Age was largely uncorrelated with regulation success or reactivity.

Table 1.

Descriptive statistics and correlations for study variables

Variable M (SD) 1 2 3 4 5 6 7 8 9 10 11 12 13
1. Age 55.42 (17.37) -
2. Crystallized Composite 110.96 (10.21) .16 -
3. Fluid Composite 99.77 (12.68) −.56** .17 -
4. Processing Speed 96.71 (18.05) −.53** −.05 .79** -
5. Cognitive Flexibility 101.84 (9.79) −.37** .18* .79** .50** -
6. Inhibitory Control 94.45 (8.03) −.29** .22* .74** .52** .79** -
7. Working Memory 100.88 (12.04) −.34** .33** .68** .32** .44** .40** -
8. Episodic Memory 101.98 (13.49) −.47** .29** .68** .38** .38** .31** .45** -
9. NA- Disgust Clip 3.15 (1.19) .04 −.27** .03 .12 −.07 −.11 .03 −.07 -
10. NA- Sadness Clip 3.99 (1.21) .05 −.12 −.13 −.11 −.14 −.21* −.08 −.03 .42** -
11. NA- Amusement Clip 1.98 (1.14) −.01 −.18* −.07 .04 .08 .09 −.18* .06 .12 .28** -
12. PA- Disgust Clip 2.12 (1.46) .04 −.02 −.04 −.04 −.02 .02 −.02 −.02 −.20* .03 .07 -
13. PA- Sadness Clip 1.47 (0.93) .19* −.11 −.22* −.10 −.20* −.14 −.18* −.22* .09 .17 .25** .55** -
14. PA- Amusement Clip 4.35 (1.88) .03 .02 .03 −.09 −.04 −.06 .12 .16 .07 .07 −.23** .26** .07
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Note. Items 9–14 refer to average experience of negative affect (NA) or positive affect (PA) under instructions to regulate emotions for the specified clip type

*

p < .05

**

p < .01

To test hypotheses about cognitive ability and ER success, we began with models including one of the two composite scores (fluid or crystallized) then examined each fluid cognition test. We did not examine the crystallized cognition tests separately, as they are both representative of language skills and highly correlated (r=.74, p<.001). Multilevel modeling was used to account for film clips being nested within individuals. Cognitive ability scores and age were grand-mean centered, and film type (a categorical within-person variable) was effect-coded with a Disgust Film variable (coded as ‘1’, sadness as ‘0’, and amusement as ‘−1) and Sadness Film variable (coded as ‘1’, disgust as ‘0’, and amusement as ‘−1’). Models estimated random intercept and random slopes. Effect sizes for model parameters were estimated using semi-partial R2.

We predicted NA and PA following regulation trials, controlling for age as well as NA and PA following reactivity trials. These multilevel modeling results are in Table 2. Findings were largely unaltered by the inclusion of reactivity in the models, with one exception. As shown in Table S2, Disgust Film Type significantly moderated the effect of fluid cognitive ability on ER success when not taking into account reactivity, with the effect on NA being weaker for the disgust film than the other films (Fluid Cognition X Disgust Film: b=0.01, SE=0.01, t(123.55)=2.11, p=.037; R2β=.0347). However, this effect was no longer significant when controlling for reactivity, b=0.01, SE=0.01, t(123.61)=1.86, p=.066; R2β=.0271. The results reported below control for reactivity because this approach better isolates effects specific to regulation by accounting for cognition-related differences in natural responses to stimuli.

Table 2.

Fixed effects of cognitive ability and film type as predictors of emotion regulation success controlling for emotional reactivity.

Experience of Negative Emotion Experience of Positive Emotion
b (SE) 95% CI R 2 β b (SE) 95% CI R 2 β
Ability Composites
Fluid Cognition
 Intercept 3.41 (0.09) [3.23, 3.60] .9163 2.65 (0.09) [2.47, 2.83] .8667
 Age 0.003 (0.01) [−0.01, 0.02] .0022 0.01 (0.01) [−0.01, 0.02] .0078
 Cog Ability −0.001 (0.01) [−0.02, 0.02] .0001 −0.001 (0.01) [−0.02, 0.02] .0002
 Reactivity 0.26 (0.08)** [0.10, 0.42] .0472 0.17 (0.05)** [0.06, 0.27] .0542
 Disgust Film Type −0.12 (0.10) [−0.31, 0.07] .0105 −0.34 (0.10)** [−0.53, −0.15] .0660
 Sadness Film Type 1.47 (0.09)** [1.29, 1.64] .6837 −1.18 (0.08)** [−1.33, −1.03] .6711
 Cog Ability X Dis Film 0.01 (0.01)+ [−0.001, 0.02] .0271 −0.0003 (0.01) [−0.01, 0.01] .00002
 Cog Ability X Sad Film −0.01 (0.01) [−0.02, 0.004] .0151 −0.01 (0.01)+ [−0.02, 0.001] .0247
Crystallized Cognition
 Intercept 3.41 (0.09) [3.23, 3.59] .9208 2.65 (0.09 [2.47, 2.84] .8572
 Age 0.01 (0.01) [−0.01, 0.01] .0091 0.01 (0.01)+ [0.003, 0.02] .0432
 Cog Ability −0.02 (0.01)** [−0.04, −0.01] .0544 −0.01 (0.01) [−0.02, 0.01] .0027
 Reactivity 0.26 (0.08)** [0.10, 0.42] .0455 0.16 (0.05)** [0.04, 0.21] .0332
 Disgust Film Type −0.12 (0.10) [−0.32, 0.07] .0103 −0.34 (0.10)** [−0.57, −0.20] .1021
 Sadness Film Type 1.47 (0.09)** [1.29, 1.64] .6837 −1.18 (0.08)** [−1.32, −1.05] .6964
 Cog Ability X Dis Film −0.01 (0.01) [−0.02, 0.01] .0092 −0.0001 (0.01) [−0.02, 0.02] .000001
 Cog Ability X Sad Film 0.01 (0.01) [−0.01, 0.03] .0131 −0.01 (0.01) [−0.02, 0.01] .0045
Fluid Cognition Subtests
Processing Speed
 Intercept 3.41 (0.10) [3.23, 3.60] .9171 2.65 (0.09) [2.47, 2.84] .8664
 Age 0.01 (0.01) [−0.003, 0.02] .0175 0.01 (0.01) [−0.002, 0.02] .0179
 Cog Ability 0.01 (0.01) [−0.004, 0.02] .0141 −0.002 (0.01) [−0.01, 0.01] .0006
 Reactivity 0.25 (0.08)** [0.10, 0.41] .0463 0.16 (0.05)** [0.06, 0.27] .0511
 Disgust Film Type −0.12 (0.10) [−0.31, 0.07] .0100 −0.34 (0.10)** [−0.53, −0.15] .0673
 Sadness Film Type 1.47 (0.09)** [1.29, 1.64] .6903 −1.18 (0.08)** [−1.33, −1.03] .6597
 Cog Ability X Dis Film 0.01 (0.004)* [0.001, 0.02] .0412 0.001 (0.004) [−0.01, 0.01] .0008
 Cog Ability X Sad Film −0.01 (0.01)* [−0.02, −0.002] .0436 0.001 (0.004) [−0.01, 0.01] .0003
Inhibitory Control
 Intercept 3.41 (0.09) [3.23, 3.60] .9170 2.65 (0.09) [2.47, 2.83] .8721
 Age 0.002 (0.01) [−0.008, 0.01] .0015 0.01 (0.01) [−0.001, 0.02] .0191
 Cog Ability −0.01 (0.01) [−0.004, 0.02] .0089 −0.004 (0.01) [−0.03, 0.02] .0010
 Reactivity 0.25 (0.08)** [0.10, 0.41] .0563 0.16 (0.05)** [0.06, 0.27] .0523
 Disgust Film Type −0.12 (0.10) [−0.31, 0.07] .0135 −0.34 (0.10)** [−0.68, −0.36] .0675
 Sadness Film Type 1.47 (0.09)** [1.29, 1.64] .6908 −1.18 (0.08)** [−0.53, −0.15] .6688
 Cog Ability X Dis Film 0.03 (0.01) [−0.01, 0.02] .0006 0.01 (0.01) [−1.34, −1.03] .0091
 Cog Ability X Sad Film −0.03 (0.01)* [−0.05, −0.01] .0490 −0.01 (0.01) [−0.03, 0.01] .0035
Working Memory
 Intercept 3.43 (0.09) [3.24, 3.61] .9180 2.64 (0.09) [2.47, 2.82] .8657
 Age 0.001 (0.01) [−0.02, 0.01] .0003 0.01 (0.004)+ [−0.0002, 0.02] .0247
 Cog Ability −0.01 (0.01) [−0.02, 0.01] .0070 0.01 (0.01) [−0.01, 0.02] .0050
 Reactivity 0.26 (0.08)** [0.10, 0.42] .0452 0.13 (0.04)** [0.04, 0.22] .0460
 Disgust Film Type −0.12 (0.10) [−0.32, 0.07] .0103 −0.38 (0.09)** [−0.56, −0.20] .0731
 Sadness Film Type 1.48 (0.09)** [1.30, 1.65] .6844 −1.18 (0.07)** [−1.31, −1.05] .6671
 Cog Ability X Dis Film 0.01 (0.01) [−0.003, 0.02] .0177 −0.004 (0.01) [−0.02, 0.01] .0030
 Cog Ability X Sad Film −0.002 (0.01) [−0.02, 0.01] .0006 −0.01 (0.01)* [−0.03, −0.003] .0480
Episodic Memory
 Intercept 3.43 (0.09) [3.24, 3.61] .9176 2.64 (0.09) [2.46, 2.83] .8635
 Age 0.002 (0.01) [−0.01, 0.01] .0006 0.01 (0.01) [−0.003, 0.02] .0197
 Cog Ability −0.002 (0.01) [−0.02, 0.01] .0005 0.01 (0.01) [−0.01, 0.02] .0048
 Reactivity 0.27 (0.08)** [0.11, 0.43] .0470 0.16 (0.05)** [0.06, 0.26] .0411
 Disgust Film Type −0.29 (0.10) [−0.32, 0.07] .0109 −0.35 (0.10)** [−0.54, −0.16] .0728
 Sadness Film Type 1.48 (0.09)** [1.30, 1.66] .6847 −1.18 (0.07)** [−1.33, −1.03] .7758
 Cog Ability X Dis Film 0.003 (0.01) [−0.01, 0.02] .0027 −0.004 (0.01) [−0.02, 0.01] .0036
 Cog Ability X Sad Film 0.004 (0.01) [−0.01, 0.01] .0032 −0.02 (0.01)* [−0.03, −0.01] .0809
Cognitive Flexibility
 Intercept 3.43 (0.09) [3.24, 3.61] .9178 2.64 (0.09) [2.46, 2.83] .8659
 Age 0.002 (0.01) [−0.01, 0.01] .0013 0.01 (0.01) [−0.003, 0.02] .0138
 Cog Ability −0.01 (0.01) [−0.03, 0.01] .0037 −0.01 (0.01) [−0.03, 0.01] .0026
 Reactivity 0.28 (0.08)** [0.12, 0.43] .0521 0.15 (0.05)** [0.05, 0.25] .0447
 Disgust Film Type −0.14 (0.10) [−0.33, 0.06] .0124 −0.36 (0.10)** [−0.55, −0.17] .0739
 Sadness Film Type 1.48 (0.09)** [1.30, 1.66] .6871 −1.18 (0.08)** [−1.33, −1.03] .6595
 Cog Ability X Dis Film −0.001 (0.01) [−0.02, 0.02] .0001 0.01 (0.01) [−0.01, 0.02] .0029
 Cog Ability X Sad Film −0.1 (0.01) [−0.03, 0.01] .0109 −0.01 (0.01) [−0.02, 0.01] .0077
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Note. Unstandardized estimates are reported with standard errors in parentheses. Cog Ability represents effects of the cognitive ability listed at the headers (e.g., fluid cognition). Dis Film and Sad Film represent Disgust and Sadness Film Types, respectively. In models predicting negative experience of emotion, the Reactivity covariate refers to NA reactivity. In the models predicting positive experience of emotion, the Reactivity covariate refers to PA reactivity.

+

p < .10

*

p < .05

**

p < .01

Fluid and Crystallized Cognitive Ability as Predictors of ER Success

Crystallized cognition was associated with greater ER success in terms of lower NA (b= −0.02, SE=0.01, t(124.50)= −2.68, p=.008; R2β=.0544), and this small effect did not vary by film type (ps>.20). Although there was not a significant effect of the fluid cognition composite on ER success (p=.066, R2β=.0271), there were significant, small effects of all the specific tests of fluid cognition, except cognitive flexibility (ps>.21). Effects of processing speed varied by film type: the link to lower NA was stronger for the sadness clip (Processing Speed X Sadness Film: b= −0.01, SE=0.004, t(123.74)= −2.38, p=.019; R2β=.0436) and weaker for the disgust clip (Processing Speed X Disgust Film: b=0.01, SE=0.004, t(122.47)=2.29, p=.024; R2β=.0412). The effect of inhibitory control on ER success (lower NA) was also stronger with the sadness film (Inhibitory Control X Sadness Film interaction: b= −0.03, SE=0.01, t(123.47)= −2.20, p=.013; R2β=.0490). In contrast, effects of working memory and episodic memory on ER success were less associated with ER success (in terms of higher PA) with the sadness film (Working Memory X Sadness Film: b= −0.01, SE=0.01, t(122.21)= −2.30, p=.023; R2β=.0480; Episodic Memory X Sadness Film: b= −0.02, SE=0.01, t(122.21)= −3.07, p=.003; R2β=.0809).

Discussion

The goal of the present work was to examine relationships between different types of cognitive ability and ER success. Previous work examining such relationships has focused primarily on cognitive control abilities predicting younger adults’ regulation of negative emotions using instructed strategies. Building on that prior research, we included participants aged 25–83 and assessed five facets of fluid cognitive ability as well as crystallized cognition in predicting spontaneous ER success with a variety of stimuli types. In this age-diverse sample, there were effects of both facets of fluid and crystallized cognitive ability on ER success. Effects of fluid cognition varied by emotional stimulus and specific facet (processing speed and inhibitory control effects on NA being stronger for sadness; episodic and working memory effects on PA being weaker for sadness). Crystallized cognitive ability was associated with NA regardless of stimuli type. Relationships between cognition and ER success generally held when controlling for emotional reactivity, providing stronger evidence that these findings speak to conscious attempts to regulate emotion, rather than simply naturally occurring emotional responses.

Fluid cognitive ability is important for quickly accessing and utilizing information (Salthouse, 1996). The present results are in line with prior work suggesting that fluid cognition may be useful for effectively regulating emotion (e.g., McRae et al., 2012; Opitz et al., 2014; Schmeichel et al., 2014). Exploratory findings showing that fluid cognition was generally less associated with ER success when faced with a high arousal negative stimulus may suggest there is a threshold of difficulty past which fluid cognition is no longer helpful in supporting effective ER. However, this pattern varied across cognitive tasks: although processing speed and inhibitory control were more strongly associated with ER success with the sadness clip, episodic and working memory were less strongly linked to ER success for the sadness clip. Given the exploratory and complex natures of these findings, they need to be replicated before drawing any firm conclusions. Further, although older adults had lower performance on all tests of fluid cognitive ability, age was unrelated with ER success (or emotional reactivity). These results echo a growing body of literature suggesting that age differences in ER strategy use and effectiveness may be minimal (e.g., Brady et al., 2018; Eldesouky & English, 2018) despite age disparities in fluid cognition.

Crystallized cognitive ability reflects accumulated life experience, including experience navigating the social world. Such expertise is theorized to account for the maintained ER skills of older adults (Blanchard-Fields, 2007). The SOC-ER framework (Urry & Gross, 2010; Opitz et al., 2012) suggests that these knowledge-based resources may be relied upon to a greater extent than cognitive control with increasing age. Knowledge-based resources may be particularly important for selecting or adjusting strategies. Effects of crystallized cognition on ER success may be reduced in studies that instruct strategy use, as individuals may be less able to rely on their expertise when unable to select an ER tactic of their choice. Accordingly, our lack of constraints on strategy selection may reconcile the present findings with previous studies reporting no association between crystallized cognition and ER success under instructed strategy use (e.g., McRae et al., 2012; Opitz et al., 2014).

This study represents an initial examination of relationships between cognition and effective ER in the absence of instructed strategies, identifying both fluid and crystallized cognition as important resources. In light of the present findings, we suggest several additional directions for future research. First, results should be replicated using a counterbalanced study design with multiple stimuli of each emotion type in order to robustly test for emotion specificity (e.g., weaker effects of cognition when regulating high arousal emotion). Researchers should be mindful of potential heterogeneity in effects due to various aspects of stimuli features (e.g., arousal, age relevance, familiarity or prior experience with the stimuli), especially in age-diverse samples. Second, effects of cognition on ER success should be examined using metrics such as facial expression and physiological response alongside self-reports of emotion. Third, there is a particular need for more work examining resources supporting ER targeting positive stimuli across various contexts. Contra-hedonic ER (e.g., attempts to reduce positive emotion), which is less typical in daily life than pro-hedonic ER, may require more cognitive resources or draw on different facets. Finally, future work should establish causal effects and examine mechanisms through which different types of cognition contribute to emotional well-being. This may involve considering cognition and the selection of specific strategies as predictors of successful ER. We suggest that life experience, as reflected by crystallized cognition, predicts selection of effective emotion regulation strategies for a given context.

Supplementary Material

Supplemental Material

Acknowledgments

Our work was supported by Grant T32AG000030 from the National Institute on Aging. This data was collected prior to the 2018 Common Rule, and we do not have IRB approval to publicly share this data.

Footnotes

We have no conflicts of interest to disclose.

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