Beyond Self-Control: Mechanisms of Hedonic Goal Pursuit and Its Relevance for Well-Being

Abstract

Self-control helps to align behavior with long-term goals (e.g., exercising to stay fit) and shield it from conflicting hedonic goals (e.g., relaxing). Decades of research have shown that self-control is associated with numerous positive outcomes, such as well-being. In the present article, we argue that hedonic goal pursuit is equally important for well-being, and that conflicting long-term goals can undermine it in the form of intrusive thoughts. In Study 1, we developed a measure of trait hedonic capacity, which captures people’s success in hedonic goal pursuit and the occurrence of intrusive thoughts. In Studies 2A and 2B, people’s trait hedonic capacity relates positively to well-being. Study 3 confirms intrusive thoughts as major impeding mechanism of hedonic success. Studies 4 and 5 demonstrate that trait hedonic capacity predicts successful hedonic goal pursuit in everyday life. We conclude that hedonic goal pursuit represents a largely neglected but adaptive aspect of self-regulation.

Keywords

hedonic goals self-control self-regulation well-being

Personal experience and empirical studies confirm that it requires self-control to act in line with a long-term goal and to shield it from conflicting hedonic goals (Baumeister et al., 2007; Hofmann et al., 2012). For example, working on a paper gets more difficult if you had also wanted to join your colleagues for after-work drinks. The literature to date suggests that people’s capacity to act in line with a long-term goal, despite of more appealing hedonic alternatives, is highly adaptive and contributes to people’s performance, health, and subjective well-being (de Ridder et al., 2012; Moffitt et al., 2011). It is perhaps due to the high relevance of self-control, that hedonic goals are usually conceptualized as less important counterparts to long-term goals and their pursuit as a case of self-control failure. This negative view on hedonic goals is surprising given that exclusively striving for long-term goals at the expense of hedonic goals is undesirable (Fromm, 1976; Koole et al., 2014), and that experiencing pleasure is part of adaptive self-regulation (Friese & Hofmann, 2016; Huta & Waterman, 2014; Inzlicht & Schmeichel, 2012; Kuhl, 2000). Nevertheless, research on the consequences of successful hedonic goal pursuit as well as on its mechanisms is scarce.

The present research addresses both gaps. Taking an individual difference perspective, we, first, developed a measure of people’s trait hedonic capacity and investigated its overlap with subjective well-being. Second, we examined the activation of intrusive thoughts about conflicting long-term goals as a major impeding mechanism undermining success in hedonic goal pursuit. After all, it should be more difficult to enjoy an after-work drink with your colleagues if you keep thinking you should have stayed in the office.

The Relevance of Hedonic Goals for Well-Being

In accordance with previous research, we define hedonic goals as cognitive representations of desired affective states that are associated with immediate pleasure or relief from displeasure that motivate specific behaviors toward their attainment (Aarts & Dijksterhuis, 2000; Hofmann & Van Dillen, 2012; Stroebe et al., 2008). For example, the tasty piece of cake that evokes an instant desire to consume and enjoy it. The concept of hedonic goals, therefore, includes the motivational and affective charge of desires (Hofmann & Van Dillen, 2012) as well as the behavioral readiness of impulses (Strack & Deutsch, 2004).

In the self-control literature, hedonic goals are usually understood as jeopardizing important long-term goals and the positive outcomes associated with pursuing them, such as subjective well-being (de Ridder et al., 2012; Hofmann et al., 2014; Klug & Maier, 2015). However, research and theorizing in various subdisciplines of psychology emphasizes the relevance of hedonic goals for subjective well-being. First, positive psychology proposes two different paths to well-being: engaging in activities that provide immediate pleasure (hedonia) and working toward self-realization in the long-run (eudaimonia; Huta & Waterman, 2014; Waterman, 1993). Research suggests that highest levels of well-being are achieved by people who walk both paths (Huta & Ryan, 2010). Second, stress and recovery research suggests that recovery during off-job time is important for employee’s well-being as well as their mental health (e.g., burnout; for a meta-analysis, see Wendsche & Lohmann-Haislah, 2017). Third, research in the clinical domain stresses the potential negative consequences of the chronic activation of long-term goals, because it can reduce access to one’s emotional preferences, intuitions, and desires (i.e., ‘ego fixation’; Koole et al., 2014). Moreover, a chronic lack of pleasure (i.e., anhedonia) or a general inability to savor positive experiences has been related to clinical disorders, such as depression (Bryant, 2003; Riso et al., 2003; Rizvi et al., 2016). Finally, research and theorizing on self-regulation suggests that positive affect can facilitate goal pursuit (Kuhl, 2000; Mead et al., 2016) and that people’s ability to upregulate positive affect and downregulate negative affect (e.g., through mindfulness) is vital for emotional stability and well-being (Friese & Hofmann, 2016; Gröpel & Kuhl, 2006; Quoidbach et al., 2010).

These lines of research suggest that the successful pursuit of hedonic goals is as important for well-being as the pursuit of long-term goals. However, even if previous work on hedonia has demonstrated a connection with well-being, conceptualizations and measurement vary largely between studies (for an overview, see Huta & Waterman, 2014). Moreover, little is known about the mechanisms supporting hedonic goal pursuit. This is also because research on self-regulation has focused solely on self-control and long-term goal pursuit. Addressing those limitations, we developed an individual difference measure of trait hedonic capacity. It not only measures the degree to which people experience pleasure during hedonic goal pursuit, it also captures what we propose might be the key impeding mechanism of hedonic success, namely intrusive thoughts about conflicting long-term goals.

Goal Conflict Impedes Hedonic Goal Pursuit

We propose that goal conflict is one factor undermining successful hedonic goal pursuit. This prediction is based on goal system theory (Kruglanski et al., 2002), which posits that people’s goals are organized in an associative network and that the pursuit of a focal goal is supported by the inhibition of conflicting goals (i.e., goal shielding; Shah et al., 2002; Shah & Kruglanski, 2002). The success of goal shielding depends on either the degree to which the conflicting goal is spontaneously activated (situationally or chronically) or the degree to which it is successfully inhibited—or both.

So far goal system theory has helped to understand the mechanisms underlying long-term goal pursuit in the face of conflicting hedonic goals (Fishbach et al., 2006; Fishbach & Shah, 2006; Trope & Fishbach, 2000). However, this mechanism should also apply when the focal goal is hedonic in nature. Although hedonic goals may be more intrusive because of their visceral and affective components (Hofmann & Van Dillen, 2012), goal system theory would predict that highly activated long-term goals should be intrusive as well (Kruglanski et al., 2002). We therefore assume that a major impeding mechanism for hedonic goal pursuit is the experience of intrusive thoughts about conflicting long-term goals. Research on food cravings suggests that intrusive thoughts about palatable foods are mainly responsible for failing to reach dieting goals, because they divert participants’ attention and resources away from a focal task (Kavanagh et al., 2005; Tiggemann et al., 2010). Likewise, thoughts about long-term goals should divert attention and pull resources away from the pursuit of a hedonic goal (Van der Wal & Van Dillen, 2013). Supporting this line of argument, recent research shows that people are less happy with a hedonic food choice if they experienced high levels of conflict with a healthier option beforehand (Becker et al., 2019).

The Present Research

The overall goal of the present work was to study the mechanisms and consequences of hedonic goal pursuit. To do that we combined an individual difference and goal system perspective akin to the concept of trait self-control (Tangney et al., 2004). In Study 1, we developed a self-report scale to assess people’s trait hedonic capacity. Studies 2A and 2B examined whether trait hedonic capacity is positively associated with subjective well-being in two diverse adult samples. Study 3 investigated spontaneous activation of intrusive thoughts as the mechanism underlying successful hedonic goal pursuit. Finally, Studies 4 and 5 investigated whether higher trait hedonic capacity predicts more successful hedonic goal pursuit in everyday life. All studies were approved by the institutional review board. All materials and data are publicly available on the Open Science Framework: https://osf.io/uypg3/.

Study 1

The aim of Study 1 was to develop a self-report scale to assess individual differences in hedonic goal pursuit. We generated a pool of 28 items that covered two aspects: (a) whether people are successful in pursuing hedonic goals and (b) whether they experience intrusive thoughts about conflicting long-term goals during hedonic goal pursuit. A third aspect addressed whether people plan hedonic goal pursuit or engage in it spontaneously. However, exploratory and confirmatory factor analyses showed that this third aspect was not represented by a sufficient number of items and was, therefore, omitted from the final scale.

Method

Procedure and participants

The 28 items were administered at the end of three independent 20-min online questionnaires that assessed other measures unrelated to the present research question. Items were presented in random order and participants rated the degree to which each statement was a fitting description of themselves (1 = not at all like me, 5 = very much like me).

Participants were recruited via the student mailing list of the University of Tübingen (Germany). Sample A consisted of N = 590 students (411 females, 172 males, 7 na, M_age = 23.66 years, SD_age = 3.68, range = 18–50). Sample B consisted of N = 394 students (272 females, 116 males, 6 na, M_age = 23.61 years, SD_age = 3.73, range = 18–44) and Sample C of N = 246 students (177 females, 63 males, 6 na, M_age = 23.74 years, SD_age = 5.14, range: 18–60).

Measures

In Samples A and C, we also assessed participants’ trait self-control with an adapted version of the Trait Self-Control Scale (Bertrams & Dickhäuser, 2009; Tangney et al., 2004), consisting of 12 items in Sample A (e.g., “I am good at resisting temptation,” α = .82), and nine items in Sample C (α = .81) due to time constraints. In both studies, items were rated on a 5-point Likert-type scale (1 = not at all like me, 5 = very much like me) and averaged to one scale with high values representing high trait self-control.

Results

Factor structure

First, we explored the factor structure by conducting parallel analyses using the “psych” package (Revelle, 2013) in R (R Core Team, 2017, version 3.3.3). Parallel analyses is a simulation-based method that compares eigenvalues of simulated versus empirical factors (Horn, 1965). In Sample A, four factors exceeded the eigenvalues of the simulated factors, whereas in Sample B and Sample C, three factors did. Because in Sample A the eigenvalue of the fourth factor only slightly exceeded the eigenvalue of the respective simulated factor (1.37 vs. 1.28), we decided to extract three factors in the subsequent confirmatory factor analyses.

Next, we conducted three confirmatory factor analyses and extracted three factors using maximum likelihood estimation and oblique rotation, because we expected the factors to be negatively correlated based on our theoretical considerations. Across samples, the first factor consisted of five items assessing how well people manage to pursue their hedonic goals (hedonic success). The second factor was represented by five items (except for one crossloading in Sample A) measuring the experience of intrusive thoughts about long-term goals during hedonic goal pursuit (intrusive thoughts). Because only two items consistently loaded on the third factor, we dropped this factor from the final version of the scale. Table 1 shows item wordings, factor loadings, reliabilities, and descriptive statistics for the two factors representing the final scale. In all three samples the correlated two-factor model fits the covariance matrix well, χ²(28) < 40.59, ps > .060, root mean square error of approximation (RMSEA) < .044, Tucker–Lewis Index (TLI) > .980, Comparative Fit Index (CFIs) > .988.

Table 1.

Items of the Trait Hedonic Capacity Scale and Results of the Confirmatory Factor Analysis With Oblique Rotation in Study 1.

Items		Sample A (N = 590)		Sample B (N = 346)		Sample C (N = 246)
Items		HS	IT	HS	IT	HS	IT
1.	I am good at pursuing my desires.	0.69	−0.04	0.62	−0.01	0.71	0.02
2.	I can follow my desires in the here and now.	0.66	−0.08	0.66	−0.10	0.75	−0.05
3.	I often do what I feel like doing.	0.68	0.04	0.59	0.13	0.52	0.07
4.	In my spare time, I can relax well.	0.43	−0.38	0.56	−0.36	0.79	−0.07
5.	In my spare time, I can “switch off” well.	0.35	−0.47	0.59	−0.36	0.70	−0.20
6.	In my spare time, I find it difficult to turn off thoughts about what is still left to do.	−0.01	0.54	−0.08	0.52	−0.22	0.45
7.	Thoughts about my work sometimes prevent me from enjoying pleasant activities and moments.	−0.01	0.77	−0.10	0.69	−0.23	0.67
8.	Sometimes I cannot stop myself from thinking about things I still need to do.	−0.03	0.68	−0.16	0.63	−0.20	0.59
9.	I often think about my duties even while I am enjoying a good moment.	0.06	0.72	0.10	0.70	0.11	0.78
10.	I often think after the fact that I should have enjoyed the moment more.	0.02	0.69	0.00	0.72	−0.04	0.66
Variance explained		0.24	0.51	0.32	0.40	0.42	0.31
Eigenvalue		1.71	7.91	2.40	8.04	7.55	2.36
Cronbach’s α		0.81	0.78	0.81	0.79	0.84	0.79
M		3.40	3.47	3.50	3.37	3.38	0.81
SD		0.73	0.82	0.73	0.86	3.49	0.85

Note. Items were rated on a scale from 1 = not at all like me to 5 = very much like me. Item loadings >.40 are presented in bold. HS = hedonic success subscale; IT = intrusive thoughts subscale.

Intercorrelation of subscales

The two subscales were highly negatively correlated across samples, rs = −.51/−.46/−.53, supporting our theoretical assumption that intrusive thoughts undermine hedonic success.

Internal consistency

Both subscales had good internal consistency, αs = .78 to .84 (see Table 1). Due to their high intercorrelation, we also tested the internal consistency of all 10 items with items covering intrusive thoughts being reverse scored. Across samples the reliability of the full scale was good, αs = .85 to .88, suggesting that it is also appropriate to average all items to one measure of the trait hedonic capacity.

Correlation with trait self-control

Because the correlations with trait self-control were consistent across samples, we report the results for the combined Samples A and C (N = 836). Results showed that the hedonic success subscale, r(834) = −.04, p = .293, the intrusive thought subscale, r(834) = −.08, p = .016, and the combined scale, r(834) = .03, p = .392, showed only small overlap with the trait self-control scale, suggesting that trait hedonic capacity and trait self-control resemble independent constructs.

Gender differences

We explored gender differences in trait hedonic capacity. Because the results converged across samples we report them here for the combined sample (N = 1,230, 352 males, 860 females, 18 na). Welch’s two-sample t-tests showed that female participants reported lower hedonic success (M = 3.38, SD = 0.75) than male participants (M = 3.56, SD = 0.71), t(685.39) = 4.09, p < .001, d = 0.25, and also reported a higher frequency of intrusive thoughts (M = 3.53, SD = 0.83) than their male counterparts (M = 3.25, SD = 0.83), t(652.87) = −5.20, p < .001, d = −0.33. On the combined scale female participants reported a significantly lower trait hedonic capacity (M = 2.92, SD = 0.70) than male participants (M = 3.15, SD = 0.68), t(671.29) = 5.30, p < .001, d = 0.33.

Discussion

Study 1 showed a consistent factor structure underlying our proposed measure of trait hedonic capacity: One factor covers hedonic success, that is, whether people are generally more or less successful in hedonic goal pursuit. The second factor covers the experience of intrusive thoughts as undermining mechanism. Because both factors are highly negatively correlated and reliability of the combined scale was good, the two subscales can be collapsed to a single indicator of trait hedonic capacity. The scale was virtually uncorrelated with trait self-control suggesting that trait hedonic capacity does not resemble low trait self-control. Due to the gender differences in trait hedonic capacity, gender will be controlled in the following studies.

Studies 2A and 2B

The aim of correlational studies 2A and 2B was to investigate whether people high versus low in trait hedonic capacity experience greater subjective well-being. The hypotheses were tested in two diverse adult samples and were preregistered for Study 2B (see H3 and H4 in https://aspredicted.org/blind.php?x=7zt5ae).

Method

Procedure and participants

The sample for Study 2A was recruited via posts on online social networks (e.g., Facebook, LinkedIn) for a 10-min online questionnaire on well-being in the workplace. Overall, N = 165 German-speaking adults (119 females, 44 males, 2 na, M_age = 35.30, SD_age = 13.72, range: 18–61) participated, which translates into a power of 1 − β = .81 to find a small effect in a multiple regression analysis (f² = 0.05, α = .05). Regarding working status 57.6% worked full-time, 40.0% worked part-time, 2.3% studied or were retired.

The sample for Study 2B was recruited via posts on prolific.com for a 40-min online questionnaire on personality (for full list of variables, see Supplemental Material). Participants received £5.00 as compensation. We recruited N = 350 English-speaking adults (213 females, 136 males, 1 gender queer/nonconforming; M_age = 32.93, SD_age = 11.30, range: 18–77), which translates into a power of 1 − β = .98 to find a small effect in a multiple regression analysis (f²= 0.05, α = .05). Regarding working status 50.0% worked full-time, 21.3% worked part-time, 10.9% were looking for work, 3.7% were retired, and 14.1% studied.

Measures

The following measures were assessed in the order as described.¹ Descriptive statistics, reliabilities, and zero-order correlations are summarized in Table 2.

Table 2.

Descriptive Statistics and Zero-Order Correlations for Main Variables of Studies 2A and 2B.

	Variable	α	M	SD	1	2	3	4	5	6
Study 2A
1	Trait hedonic capacity	.87	3.15	0.71
2	Hedonic success^a	.82	3.37	0.73	.86
3	Intrusive thoughts^a	.82	3.08	0.86	−.90	−.57
4	Trait self-control	.77	3.51	0.64	.17	.12	−.17
5	WHO-5 well-being	.80	4.12	0.78	.53	.48	−.46	.38
6	Physical symptoms^b	.82	1.63	0.63	−.37	−.25	.39	−.35	−.42
7	Age	—	35.30	13.72	−.03	−.09	−.03	.12	−.04	−.10
Study 2B
1	Trait hedonic capacity	.84	2.87	0.69
2	Hedonic success^a	.83	3.31	0.84	.83
3	Intrusive thoughts^a	.82	3.58	0.83	−.83	−.37
4	Trait self-control	.86	2.90	0.73	.24	.13	−.26
5	Life satisfaction	.91	4.17	1.53	.41	.50	−.18	.27
6	Physical symptoms^b	.95	1.68	0.64	−.39	−.20	.44	−.42	−.26
7	Age	—	32.93	11.30	.07	−.01	−.13	.20	−.01	−.12

Note. Significant correlations are presented in bold, r(164) > |.16|, r(349) > |.11|, p < .05. WHO = World Health Organization.

Statistics for the respective subscale. ^bCorrelation for log-transformed measure (count + 1), because of skewness.

Subjective well-being

In Study 2A, subjective well-being was assessed with the World Health Organization (WHO)-5 general well-being scale (Brähler et al., 2007). This measure comprises cognitive and affective aspects of well-being and consists of five items (e.g., “I have felt cheerful and in good spirits”) that participants rated on a scale from 1 = never to 6 = all the time. In Study 2B, subjective well-being was assessed using the Satisfaction With Life Scale (Diener et al., 1985).² Participants rated their agreement with five items (e.g., “In most ways my life is close to my ideal”) on a 7-point scale from 1 = strongly disagree to 7 = strongly agree. In the averaged scales, higher scores reflect higher well-being.

Physical symptoms

In Study 2A, we assessed physical symptoms related to somatization with the Brief Symptom Inventory (Franke et al., 2017) with six items (e.g., “Faintness or dizziness”). In Study 2B, we additionally assessed symptoms for depression and anxiety with six items each (depression: e.g., “Feeling no interest in things”; anxiety: e.g., “Nervousness or shakiness inside”). Participants rated how often they had experienced each symptom within the past two weeks on a 5-point scale from 1 = not at all to 5 = nearly every day, such that higher scores reflected more frequent symptoms. Because the results were consistent across symptom categories and reliability was high for all 12 symptoms (see Table 2), results are reported for the averaged indicator of symptoms.

Trait hedonic capacity

In both studies, trait hedonic capacity was assessed with the 10 items of the Trait Hedonic Capacity Scale introduced in Study 1. The five items of the intrusive thoughts subscale were recoded such that higher scores on the averaged scale reflect higher trait hedonic capacity.

Trait self-control

Last, trait self-control was assessed with the short version of the Trait Self-Control Scale (e.g., “I am good at resisting temptation”; Tangney et al., 2004). Items were rated on a 5-point scale from 1 = not at all to 5 = very much. On the averaged scale, higher scores reflect higher trait self-control.

Results

Factor structure

First, we confirmed the factor structure of the English version of the scale in Study 2B. In the final set of 10 items, the exploratory factor analysis indicated two factors to be retained (eigenvalues = 4.12 and 2.02). Again, the two-factor model fit the data well, χ²(25) = 34.67, p = .094, RMSEA = .033, TLI = .988, CFI = .994. Internal consistencies for both subscales and the full scale were good, αs > .82. Thus, we replicated the factor structure.

Subjective well-being

We ran two linear regression models predicting general well-being (Study 2A) and life satisfaction (Study 2B) with trait hedonic capacity (z-transformed), controlling for trait self-control (z-transformed), and gender (0 = male, 1 = female). The results are summarized in Table 3 (left column). Replicating previous research, trait self-control was positively related to general well-being and life satisfaction with a medium effect size (Cohen, 1992). Over and above this effect, trait hedonic capacity was significantly and positively related to general well-being and life satisfaction with a medium-to-large effect size. More specifically, trait hedonic capacity explained 21% of variance in general well-being, ΔR²= .21, F(1, 159) = 53.56, p < .001, and 13% in life satisfaction, ΔR²= .13, F(1, 346) = 57.18, p < .001, when controlling for trait self-control. In comparison, trait self-control explained 8% in general well-being, ΔR²= .08, F(1, 159) = 21.59, p < .001, and 3% of variance in life satisfaction, ΔR² = .03, F(1, 346) = 13.69, p < .001. Thus, the effects of trait hedonic capacity were at least twice as large as the effects of trait self-control.

Table 3.

Results of Multiple Linear Regression Models Predicting Subjective Well-Being and Physical Symptoms in Study 2A (N = 165) and Study 2B (N = 350).

	Subjective well-being^a							Physical symptoms
Predictor	b	95% CI		SE	t	β	p	b	95% CI		SE	t	β	p
Study 2A
Intercept	4.15	3.96	4.34	0.10	43.32			1.56	1.38	1.73	0.09	17.89
Gender	−0.04	−0.27	0.18	0.11	−0.40	−.03	.691	0.10	−0.11	0.30	0.10	0.94	.07	.350
Trait self-control	0.23	0.13	0.33	0.05	4.65	.30	<.001	−0.19	−0.28	−0.10	0.05	−4.14	−.30	<.001
Trait hedonic capacity	0.37	0.27	0.47	0.05	7.32	.48	<.001	−0.19	−0.28	−0.10	0.05	−4.22	−.31	<.001
Study 2B
Intercept	4.06	3.83	4.30	0.12	33.96			1.81	1.71	1.90	0.05	38.49
Gender	0.18	−0.12	0.48	0.15	1.17	.06	.241	−0.21	−0.33	−0.09	0.06	−3.44	−.16	.001
Trait self-control	0.28	0.13	0.43	0.08	3.70	.18	<.001	−0.23	−0.29	−0.17	0.03	−7.56	−.35	<.001
Trait hedonic capacity	0.59	0.43	0.74	0.08	7.56	.38	<.001	−0.22	−0.28	−0.16	0.03	−7.31	−.35	<.001

Note. CI = confidence interval.

The measure of subjective well-being was general well-being in Study 2A and life satisfaction in Study 2B.

Physical symptoms

We ran two similar regression models to predict physical symptoms in both samples. Trait self-control had a negative effect on physical symptoms with a medium effect size (see Table 3, right column). Over and above this effect, trait hedonic capacity was negatively related to symptoms with a medium effect size. Trait hedonic capacity explained 8% in Study 2A, ΔR² = 0.08, F(1, 159) = 17.83, p < .001, and 11% of variance in Study 2B, ΔR² = 0.11, F(1, 346) = 53.41, p < .001, whereas trait self-control explained 8% in Study 2A, ΔR² = 0.08, F(1, 159) = 17.13, p < .001, and 12% of variance in Study 2B, ΔR² = 0.12, F(1, 346) = 57.21, p < .001. Thus, effects were of similar size for physical symptoms.

We also explored interactive effects of trait hedonic capacity and trait self-control on the respective outcomes, which were nonsignificant for well-being and inconsistent across samples for physical symptoms. Therefore, the overall the results speak for additive effects on well-being.

Discussion

In two diverse samples, we found that people’s trait hedonic capacity was positively related to different indicators of subjective well-being. These effects were independent of the well-established effects of trait self-control on well-being and of similar size or larger. Given its relevance for well-being, an important question is what mechanisms underlie success in hedonic goal pursuit.

Study 3

Based on goal system theory (Kruglanski et al., 2002; Trope & Fishbach, 2000), we proposed that one major impeding mechanism might be the experience of intrusive thoughts about conflicting long-term goals. To test this idea, we conducted a lab study in which we, first, examined whether individuals low versus high in trait hedonic capacity actually experience more intrusive thoughts about conflicting long-term goals (e.g., work, chores) while engaging in hedonic goal pursuit (i.e., relax) and, second, whether the experience of intrusive thoughts is negatively related to hedonic success (i.e., change in relaxation). The hypotheses were preregistered: http://aspredicted.org/blind.php?x=67987j.³

Method

Design

Trait hedonic capacity was assessed in an online pre-survey at least two days before participants came to the laboratory and engaged in a 10-min relaxation phase. During this phase, we assessed the number of intrusive thoughts experienced. In addition, we included a between-subjects manipulation of long-term goal activation prior to the relaxation phase. The rationale behind this manipulation was twofold: to increase the number of intrusive thoughts in one condition, because we suspected floor effects and to explore why people high in trait hedonic capacity experience less intrusive thoughts. If external activation attenuates the negative effect of trait hedonic capacity on number of intrusive thoughts, this would speak for individual differences in the spontaneous activation of long-term goal-related thoughts. If people high in trait hedonic capacity experience less intrusive thoughts despite external long-term goal activation, this would rather suggest more effective inhibition of intrusive thoughts.

Participants

Based on a priori power analyses, we aimed to collect data of at least N = 148 participants with α = .05, 1 − β = .95, f² = .15 (small effect). We recruited N = 222 participants via the institute’s participant pool. Twenty-two participants filled in the online pre-survey but did not come to the laboratory session and six participants did not fill in the pre-survey, reducing the final sample with complete data sets to n = 194 (154 females, 39 males, 1 na; M_age = 23.47, SD_age = 3.49). Participants received €10.00 for completing both parts of the study.

Procedure

Upon registration participants received the link to the online pre-survey which they were instructed to fill in at least 2 days before the laboratory session (M_delay = 2.87, SD_delay = 2.92). The laboratory session started with a 30-min study that was unrelated to the present research. After that, participants were randomly assigned to the goal activation condition (n = 97) or the control condition (n = 94). Participants in the goal activation condition were asked to name three personal goals they want to pursue in the upcoming months, relating to study/work, social relations, and leisure. For each goal, they also named three steps of how to pursue it. Participants in the control condition skipped this part. Directly before the relaxation phase, all participants filled in a self-report measure of relaxation. Then they were instructed that for the next 10 min their only goal should be to relax. During this time, they listened to quiet piano music and chose among different relaxing activities (e.g., coloring mandalas, solving crossword puzzles, doodling, or doing nothing). Crucially, they were asked to report every thought coming to their mind that did not let them relax. For that, they received an empty list and were instructed to write down a word representing the thought and add a tally mark on the side if the same thought occurred again. After the relaxation phase, participants filled in the relaxation measure again. Last, participants rated each thought listed regarding its intensity, frequency in everyday life, and content (i.e., 45.95% were related to studies/work, 22.01% to social chores, 8.60% to leisure chores, and 23.44% related to other content).

Measures of the online pre-survey

Reliabilities, descriptive statistics, and zero-order correlations of the measures are presented in Table 4.

Table 4.

Descriptive Statistics and Zero-Order Correlations for Main Variables of Study 3 (n = 194).

	Variable	α	M	SD	1	2	3	4	5	6
1	Trait hedonic capacity	.84	3.09	0.66
2	Hedonic success^a	.81	3.51	0.69	.80
3	Intrusive thoughts^a	.82	3.34	0.85	−.88	−.41
4	Trait self-control	.84	2.89	0.77	.10	−.05	−.20
5	Relaxation pre	.84	3.44	0.74	.26	.27	−.17	.20
6	Relaxation post	.76	3.75	0.62	.28	.32	−.17	.23	.77
7	#Intrusive thoughts^b	−	6.34	5.39	−.25	−.20	.22	−.07	−.14	−.26

Note. Significant correlations, r(193) > .|15|, p < .05, are presented in bold.

Statistics for the respective subscale. ^bCorrelation calculated with log-transformed measure because of skewness.

Trait hedonic capacity

We assessed trait hedonic capacity with the 10 items of the Trait Hedonic Capacity Scale. Higher scores reflect higher trait hedonic capacity (for subscales more hedonic success and more intrusive thoughts, respectively).

Trait self-control

Trait self-control was assessed with the German short version of the Trait Self-Control Scale (Bertrams & Dickhäuser, 2009). Higher scores reflect higher trait self-control.

Measures of the laboratory session

Number of intrusive thoughts

We summed the number of intrusive thoughts participants listed during the relaxation phase.

Relaxation

Levels of relaxation were assessed before and after the relaxation phase with the relaxation-stress subscale of the multidimensional mood questionnaire (Steyer et al., 1997). Participants indicated how they felt in that moment with regard to four items (i.e., “calm,” “relaxed,” “tensed” [R], “nervous” [R]). Items were rated on a 5-point scale (1 = not at all, 5 = very much). The items were presented among four filler items of the awake-tired subscale of the same measure (e.g., “awake,” “tired” [R]). Because in this scale only one of four items directly targets relaxation, we added two more items (i.e., “refreshed,” “recovered”). On the averaged scale, higher scores reflected greater momentary relaxation.

Results

Intrusive thoughts

Because our measure of intrusive thoughts was a count measure and as such highly right skewed, we fitted a Poisson regression model to test the effect of trait hedonic capacity on the number of intrusive thoughts experienced, controlling for gender, and trait self-control (z-transformed). As expected, trait hedonic capacity was a significant negative predictor of the intrusive thoughts experienced, b = −0.13, 95% confidence interval [CI] = [−0.18, −0.06], SE = 0.03, t(186) = −4.29, p < .001. Trait self-control did not predict the number of intrusive thoughts, b = −0.03, 95% CI = [−0.09, 0.03], SE = 0.03, t(186) = −1.04, p = .296.

Following our preregistered hypotheses, we also tested the effect separately for the two subscales. As expected, the intrusive thoughts subscale was a positive predictor, b = 0.08, 95% CI = [0.02, 0.14], SE = 0.03, t(186) = 2.59, p = .010, and the hedonic success subscale was a negative predictor of intrusive thoughts, b = −0.14, 95% CI = [−0.20, −0.09], SE = 0.03, t(186) = −4.95, p < .001. These effects mirror the negative correlation between the two subscales (see Table 4) and further support the idea that the experience of intrusive thoughts undermines successful hedonic goal pursuit.

Interactive effects with external goal activation

To explore whether trait hedonic capacity is about the spontaneous activation versus successful inhibition of intrusive thoughts, we ran a regression model predicting number of intrusive thoughts by trait hedonic capacity (z-transformed), a dummy variable coding condition (0 = no treatment, 1 = goal activation), and their two-way interaction (Aiken & West, 1991). The main effect of condition was positive but not significant, b = 0.08, 95% CI = [−0.03, 0.20], SE = 0.06, z(184) = 1.41, p = .158. However, the interaction with trait hedonic capacity was significant, b = 0.12, 95% CI = [0.00, 0.23], SE = 0.06, z(184) = 1.96, p = .050. The pattern of this interaction is depicted in Figure 1 (left panel). Simple slope analyses conducted with the “pequod” package in R (Mirisola & Seta, 2016) showed that in the control condition, people low (−1SD) versus high (+1SD) in trait hedonic capacity experienced significantly more intrusive thoughts, b = −0.35, SE = 0.11, t = 3.18, p = .002. However, when long-term goals were externally activated people high versus low in trait hedonic capacity experienced the same number of intrusive thoughts, b = −0.15, SE = 0.11, t = −1.33, p = .186.

Figure 1.

Predicted number of intrusive thoughts as a function of condition and trait hedonic capacity (left panel) or condition and the intrusive thoughts subscale (right panel).

Again, because the intrusive thoughts subscale is particularly suitable to predict the experience of intrusive thoughts, we also tested the interaction separately for the two subscales. The interaction was significant for the intrusive thoughts subscale, b = −0.25, 95% CI = [−0.37, −0.13], SE = 0.06, z(184) = −4.14, p < .001, but not for the hedonic success subscale, b = −0.07, 95% CI = [−0.18, 0.05], SE = 0.06, z(184) = −1.15, p = .252. The pattern mirrored the pattern for the full scale (see Figure 1, right panel): In the control condition, people scoring high versus low on the intrusive thought subscale experienced significantly more intrusive thoughts, b = 0.31, SE = 0.09, t = 3.45, p < .001. In the goal activation condition, people high versus low in the intrusive thought subscale experienced the same number of intrusive thoughts, b = 0.05, SE = 0.08, t = 0.61, p = .542. To summarize, people low versus high in trait hedonic capacity experience more intrusive thoughts when engaging in hedonic goal pursuit. However, this advantage is attenuated when long-term goals are activated externally. Thus, trait hedonic capacity seems to be about differences in the spontaneous activation of long-term goals rather than about inhibition of intrusive thoughts.

Change in relaxation

Next, we examined whether the number of intrusive thoughts experienced negatively affected change in relaxation from before to after the relaxation phase. We ran a regression analysis and predicted relaxation after the relaxation phase by the number of intrusive thoughts experienced (log-transformed) and controlled for gender, β = −.05, b = −0.07, SE = 0.07, t(187) = −1.00, p = .318, and relaxation prior to the relaxation phase, β = .73, b = 0.61, SE = 0.04, t(187) = 15.83, p < .001. Results showed that the number of intrusive thoughts was a negative predictor of residual change in relaxation, β = −.18, b = −0.15, 95% CI = [−0.23, −0.07], SE = 0.04, t(187) = −3.88, p < .001. Conversely, relaxation prior to the relaxation phase was unrelated to the number of intrusive thoughts experienced (see Table 4). These findings support the notion that intrusive thoughts impede the successful pursuit of hedonic goals.

We also explored whether the manipulation moderated the effect of intrusive thoughts on change in relaxation. However, neither the interaction, β = −.21, b = −0.12, 95% CI = [−0.27, 0.03], SE = 0.08, t(186) = −1.63, p = .104, nor the main effect was significant, t < 1. In both experimental groups, intrusive thoughts hampered change in relaxation.

Discussion

Study 3 supports the idea that intrusive thoughts about conflicting long-term goals undermine hedonic goal pursuit. People high in trait hedonic capacity experienced less intrusive thoughts during a 10-min relaxation phase and the experience of intrusive thoughts was related to less of a positive change in relaxation. Exploratory results showed that the external activation of long-term goals causes more intrusive thoughts among people high in trait hedonic capacity. Thus, trait hedonic capacity seems to reflect differences in the spontaneous activation of long-term goals during hedonic goal pursuit rather than their successful inhibition. One limitation of this study is that participants did not choose the hedonic goal to relax and that hedonic goal pursuit was examined in an unnatural laboratory setting.

Study 4

To address this limitation, Study 4 tested whether trait hedonic capacity predicts people’s success in hedonic goal pursuit in everyday life. For that, we recruited participants in different hedonic contexts (i.e., nature, park, yoga class, café). For educational purposes, we preregistered the hypothesis for each context separately: https://aspredicted.org/blind.php?x=sk6g2r (nature), https://aspredicted.org/blind.php?x=id4xf7 (park), https://aspredicted.org/blind.php?x=ti4yh3 (yoga), https://aspredicted.org/blind.php?x=cy2ff9 (café).

Method

Participants and procedure

We aimed to recruit at least N = 81 participants per context to reach a power of 80%, an alpha of 5%, one tested predictor and a medium effect size (f² = 0.10). Overall, we recruited N = 461 (n = 168 in nature, n = 102 in a park, n = 91 in yoga studios, n = 100 in a café; 303 females, 146 males, 3 diverse, 9 na; M_age = 33.92, SD_age = 14.94, range: 18–86).

In each context, participants filled in a 10-min paper-pencil survey assessing their momentary hedonic experience, reasons for being in the respective context, as well as trait hedonic capacity and trait self-control. In the café, we preregistered to also collect ratings of participant’s hedonic experience from a person accompanying the participant. Thus, we recruited n = 50 companions (26 females, 23 males, 1 na; M_age = 27.06, SD_age = 10.04) and asked them to fill in a questionnaire as well, which asked them to judge the momentary hedonic experience of the participant rather than their own.

Measures

Measures were administered in the order as described below. Reliabilities, descriptive statistics, and zero-order correlations are presented in Table 5.

Table 5.

Means, Standard Deviations, and Zero-Order Correlations for the Variables in Study 4.

	Variable	α	M	SD	1	2	3
1	Trait hedonic capacity^a	.84	3.38	0.68
2	Trait self-control^a	.82	3.32	0.66	.14
3	Hedonic experience (self-rated)^a	.76	3.99	0.76	.25	.18
4	Hedonic experience (other-rated)^b	.63	3.80	0.62	.31	.06	.43

Note. ^aSignificant correlations, r(411) ^> |.10|. p ^< .05, are presented in bold. ^bSignificant correlations, r(49) ^> |.29|, p ^< .05, are presented in bold.

Hedonic experience

We assessed hedonic experience with six items (e.g., “So far, I could fully enjoy the time here”; “So far, I could switch off and relax well”). For other-rated hedonic experience, items were identical in their wording except that “I” was replaced with “he or she.” For both versions, reliability was satisfactory.

Hedonic goal

To assure that participants were pursuing a hedonic goal, we asked, “For what reason, or reasons, are you in nature/in the park/doing yoga/in the café today?” and to indicate all that apply from a list including six hedonic reasons (e.g., relaxation, enjoyment) and four non-hedonic reasons (e.g., health, fitness). The list of reasons was adapted to the context. Participants who did not name at least one hedonic reason for the activity were excluded from the analyses (nature: n = 23 [14%], park: n = 9 [9%], yoga: n = 3 [3%], café: n = 14 [14%]). Thus, the final analyses were based on n = 412 participants (275 females, 126 males, 3 diverse, 8 na, M_age = 33.71, SD_age = 14.80, range: 18–82).

Trait hedonic capacity

Trait hedonic capacity was assessed with the 10 items of the Trait Hedonic Capacity Scale.

Trait self-control

Trait self-control was assessed with the German short version of the Trait Self-Control Scale (Bertrams & Dickhäuser, 2009).

Results

Self-rated hedonic experience

First, we tested whether trait hedonic capacity predicted momentary hedonic experience and controlled for gender, context (dummy-coded), and trait self-control in a multiple linear regression analysis. The results are summarized in Table 6. Contexts differed significantly in their average level of hedonic experience. The hedonic experience in nature was significantly higher than in any other context. Furthermore, there was a significant but small positive effect of trait self-control. People high in trait self-control reported a more positive momentary hedonic experience. Most importantly, however, the effect of trait hedonic capacity was also positive and double in size. As expected, people high in trait hedonic capacity reported a more positive momentary hedonic experience.

Table 6.

Results of Linear Multiple Regression Models Predicting Self-Rated and Other-Rated Hedonic Experience in Study 4.

	Self-rated hedonic experience^a							Other-rated hedonic experience^b
Predictor	b	95% CI		SE	t	β	p	b	95% CI		SE	t	β	p
Intercept	4.36	4.13	4.60	0.12	36.66			4.15	3.60	4.71	0.27	15.19
Gender^c	−0.07	−0.22	0.08	0.07	−0.95	−.05	.342	−0.27	−0.69	0.15	0.21	−1.32	−.21	.194
Nature vs. Park	−0.31	−0.50	−0.12	0.10	−3.26	−.17	.001
Nature vs. Café	−0.62	−0.81	−0.43	0.10	−6.41	−.33	<.001
Nature vs. Yoga	−0.36	−0.55	−0.17	0.10	−3.68	−.20	<.001
Trait self-control	0.08	0.01	0.15	0.04	2.37	.11	.018	0.01	−0.18	0.20	0.09	0.08	.01	.935
Trait hedonic capacity	0.17	0.10	0.24	0.04	4.67	.22	<.001	0.19	0.01	0.37	0.09	2.09	.32	.044

Note. Gender effect for participants identifying as diverse is omitted from table due to low frequency (n = 3). CI = confidence interval.

N = 412. ^bN = 50. ^cEffect of dummy variable coding gender differences between female and male participants (0 = female, 1 = male).

Other-rated hedonic experience

Second, we tested whether trait hedonic capacity also positively predicted other-rated hedonic experience. Self- and other-rated hedonic experience was highly positively correlated (see Table 5), suggesting that people can judge other’s momentary hedonic experience. The effect of trait self-control was positive but not significant (see Table 6, right column). In contrast, trait hedonic capacity was positively and significantly related to other-rated hedonic experience with a medium effect size. Thus, people with higher trait hedonic capacity were also judged by companions as having a more positive hedonic experience.

Discussion

Across four different contexts, people high in trait hedonic capacity reported a more positive hedonic experience and were also judged by others as having a more positive hedonic experience. The latter effect cannot be explained by demand effects but is still not completely independent as raters and targets shared the same situation. This limitation was addressed in Study 5.

Study 5

The first aim of this study was to replicate the finding of Study 4. However, this time trait hedonic capacity was assessed independently of people’s hedonic experience. A second aim was to replicate the findings of Studies 2A and 2B with regard to well-being and extend these findings by assessing people’s affective well-being in everyday life.

Method

Participants and procedure

We recruited N = 224 (194 females, 30 males; M_age = 21.25, SD_age = 3.71) participants in lectures and on campus at the University of Zurich (Switzerland). Participants were all students with a psychology major and received course credit for participating in the study.

Participants filled in two online surveys (T1 and T2) spaced 10 weeks apart assessing trait hedonic capacity and life satisfaction. Furthermore, the study involved an experience-sampling phase starting 3 weeks after the initial survey. Participants received four random signals per day between 9:00 a.m. and 9:00 p.m. over a period of seven consecutive days. Signals were evenly spread over the day and with at least 30 min in between. On average participants completed 79% of signals (range: 14%–100%), resulting in 4,137 experience samples.

Measures of online surveys

The measures of trait hedonic capacity, trait self-control, and life satisfaction were identical to Study 2B. Table 7 summarizes the reliabilities, descriptive statistics, and zero-order correlations of these measures.

Table 7.

Means, Standard Deviations, and Zero-Order Correlations for the Variables in Study 5.

	Variable	α	M	SD	1	2	3	4	5	6^b	7^b
1	Trait hedonic capacity T1	.84	3.09	0.63
2	Trait hedonic capacity T2	.88	3.26	0.73	.70
3	Trait self-control T1	.82	3.11	0.63	.12	.04
4	Life satisfaction T1	.83	5.12	1.06	.42	.39	.21
5	Life satisfaction T2	.87	5.03	1.12	.27	.29	.16	.55
6	Affect valence^a	—	0.66	0.22	.41	.41	.25	.36	.30
7	Affect arousal^a	—	0.60	0.25	−.46	−.48	−.19	−.36	−.24	−.64
8	Enjoyment^a	—	0.59	0.28	.33	.35	.13	.23	.16	.55	.54

Note. Significant correlations, p < .05, are presented in bold.

Correlations represent person-level correlations (i.e., correlation with person mean across signals).

Correlations represent signal-level correlations.

Measures of experience-sampling phase

Affective well-being

At the beginning of each signal, participants indicated how they felt at this moment on two continuous sliders measuring affect valence from 0.00 = very bad to 1.00 = very good (continuous with steps of 0.01) and affect arousal from 0.00 = very tensed to 1.00 = very relaxed. For ease of interpretation, arousal was reverse scored such that higher scores reflect higher arousal.

Momentary enjoyment

Then participants described in an open text field what they were doing at the moment and categorized their current activity into one of 13 categories (adapted from Rom et al., 2019; 37% studying, 14% relax, 12% eat/drink, 9% commute, 9% social activities, 5% chores, 4% job/work, 3% sports, 1% social obligations, 1% social media, 4% other). After that, participants indicated how much they enjoyed the activity on a slider from 0.00 = not at all to 1.00 = very much.

Results

Stability

First, we tested the stability of trait hedonic capacity across 10 weeks. Trait hedonic capacity measured at T1 and T2 were highly positively correlated, r(223) = .70, p <.001, suggesting stabile individual differences.

Life satisfaction

Next, we predicted life satisfaction in the follow-up questionnaire by trait hedonic capacity in a multiple regression model controlling for trait self-control and gender. Replicating Studies 2A and 2B, trait hedonic capacity at T1 was a positive predictor of life satisfaction at T2, β = .27, b = 0.29, 95% CI = [0.14, 0.44], SE = 0.07, t(199) = 3.88, p < .001. It explained 6% of variance. Trait self-control explained 1% of variance.

Everyday affective well-being

Next, we tested whether trait hedonic capacity also predicts affective well-being in everyday life. As experience-samples were nested within participants, we applied a multilevel fixed-effects model (Bryk & Raudenbush, 1992). As in the previous models, we controlled for trait self-control and gender. As expected, trait hedonic capacity was a positive predictor of valence, b = 0.04, 95% CI = [0.03, 0.06], SE = 0.008, t(176) = 5.55, p < .001, and negative predictor of arousal, b = −0.05, 95% CI = [−0.06, −0.03], SE = 0.08, t(176) = −6.52, p < .001. People with high versus low trait hedonic capacity experienced more positive mood and felt more relaxed. Trait hedonic capacity explained 19% of variance on Level 2 for valence and 25% in arousal. Trait self-control explained 7% in valence and 5% in arousal.

Enjoyment

Last, we tested whether trait hedonic capacity predicted enjoyment using the same model as described above. Results showed that trait hedonic capacity was a positive predictor of enjoyment, b = 0.03, 95% CI = [0.02, 0.04], SE = 0.007, t(176) = 4.38, p < .001, while trait self-control was not, b = 0.01, 95% CI = [−0.004, 0.02], SE = 0.007, t(176) = 1.27, p = .207. Trait hedonic capacity explained 16% of variance in enjoyment on Level 2 and trait self-control 1%.

Discussion

Replicating the findings of Study 4, trait hedonic capacity positively predicted people’s momentary enjoyment in everyday life. Thus, people seem to differ in how successful they pursue hedonic goals and can reliably report these differences. Furthermore, the study replicated and extended the findings of Studies 2A and 2B. Trait hedonic capacity positively predicted life satisfaction over a period of 10 weeks, as well as more positive and low arousal affective states assessed in everyday life. Trait self-control was a positive predictor of both life satisfaction and affective well-being but effect sizes were again considerably smaller than those of trait hedonic capacity.

General Discussion

Self-control is commonly defined as successful long-term goal pursuit in the face of conflicting hedonic goals (e.g., staying in the office to work on the paper rather than joining the colleagues at the bar; Baumeister et al., 2007). We argue that not only successful long-term but also successful hedonic goal pursuit is adaptive for well-being. Even though this general point has been made in various subdisciplines of psychology before (e.g., Huta & Waterman, 2014; Koole et al., 2014; Kuhl, 2000), a measure of people’s capacity to pursue hedonic goals as well as an understanding of the mechanisms underlying successful hedonic goal pursuit was missing. Addressing this gap in the literature, we first developed a measure of trait hedonic capacity (Study 1) and examined its relationship with different indicators of subjective well-being. Results from Studies 2A and 2B showed that people high in trait hedonic capacity experienced higher life satisfaction and less physical symptoms of somatization, depression, and anxiety. Furthermore, Study 5 showed that trait hedonic capacity also positively predicted affective well-being in everyday life. Importantly, the effects of people’s trait hedonic capacity on well-being were independent of the well-established effects of trait self-control and often larger size (de Ridder et al., 2012). These findings emphasize the relevance of hedonic goal pursuit as an integral part of adaptive self-regulation.

Regarding the mechanism underlying trait hedonic capacity, we hypothesized and found in Study 3 that intrusive thoughts arising from conflicting long-term goals impede hedonic goal pursuit. Not only did people high versus low in trait hedonic capacity experience less intrusive thoughts, but these thoughts were also negatively related to improvements in relaxation. Furthermore, exploratory results suggest that trait hedonic capacity is about the spontaneous experience of intrusive thoughts rather than their successful inhibition. When long-term goals were experimentally activated before participants entered the relaxation phase, people high and low in trait hedonic capacity experienced the same high amount of intrusive thoughts.

Finally, Study 4 showed that people high in trait hedonic capacity have more positive hedonic experiences in everyday life, as reported by themselves and people around them. These results were also replicated in Study 5, where trait hedonic capacity was measured 3 weeks before participants reported everyday hedonic experience in an experience-sampling phase. People high in trait hedonic capacity seem to be more successful in pursuing their hedonic goals, which can probably be explained by the absence of intrusive thoughts.

Theoretical Contribution

The contribution of the present work is not limited to the development of a scale measuring trait hedonic capacity and the finding that it predicts well-being. Our findings replicate previous work on hedonic and eudaimonic well-being (Huta & Ryan, 2010) and support the general assumption in the self-regulation, clinical and work and organizational literature that hedonic goal pursuit and the experience of pleasure is an important part of adaptive self-regulation (Kuhl, 2000; Riso et al., 2003; Rizvi et al., 2016). Importantly, the present line of studies extends those literatures by focusing on mechanisms undermining hedonic goal pursuit, namely intrusive thoughts about conflicting long-term goals.

The present research broadens our understanding of goal pursuit and self-regulation more generally. For example, our research supports goal system theories’ assumptions regarding the role of goal conflict for success in goal pursuit (Kruglanski et al., 2002). To our knowledge the theory has so far only been tested for situations in which the focal goal was a long-term or task goal (Shah & Kruglanski, 2002; Trope & Fishbach, 2000). Our findings, however, suggest that goal system theory also generalizes to situations when the focal goal is hedonic in nature. More specifically, the pursuit of hedonic goals (e.g., relaxation) became more difficult as conflicting goals become cognitively more accessible (e.g., number of intrusive thoughts). Furthermore, we identified people’s spontaneous experience of intrusive thoughts rather than their inhibition as mechanism that explains individual differences in the capacity to pursue hedonic goals. Interestingly, these findings correspond to a recent discussion in the self-control literature, according to which successful self-control might also be less about the effortful inhibition of conflicting desires and more about avoiding or not experiencing them in the first place (Bernecker et al., 2018; Gillebaart & De Ridder, 2015).

At this point, we would like to clarify that thinking about the future or long-term goals can also be a hedonic experience and increase well-being by, for instance, reducing anxiety (Jing et al., 2016), and improve problem solving and long-term goal pursuit (Oettingen et al., 2016; Schacter et al., 2017; Solbrig et al., 2019; but see Oettingen et al., 2001, 2016). It is even possible that thinking about a long-term goal during hedonic goal pursuit contributes to momentary pleasure—as long as the goal is not perceived as conflicting with the present hedonic activity. Thus, the notion of experienced conflict between thought content and the hedonic activity is central to our conception of intrusive thoughts and its effects on hedonic goal pursuit.

Related to this point we want to emphasize that hedonic and long-term goals are not mutually exclusive. First, it is possible to engage in an activity for mixed reasons, the immediate pleasure associated with it and its long-term benefits. Second, people may experience immediate pleasure even while engaging in a particular activity purely for the reason of a long-term benefit (e.g., exercise, work). However, it is also possible—and perhaps more common than previously acknowledged—that people do not experience pleasure, despite engaging in the activity for hedonic reasons. The notion that hedonic goal pursuit can at times be difficult and fail is new and leads to our second theoretical contribution.

So far, the literature on self-control has framed the pursuit of hedonic goals—or desires and impulses—as being automatic and effortless (Hofmann et al., 2009). Even though new theoretical considerations started to examine the deliberate pursuit of desires (Hofmann & Van Dillen, 2012), these models usually end with the decision for a behavior that is either in line with the person’s long-term goal (“self-control success”) or desire (“self-control failure”). However, what happens as people follow their desires and enter the phase of hedonic goal pursuit is not well understood. It is an empirical question for future research whether the components that have been identified in the past years for shaping long-term goal pursuit in the face of conflicting hedonic goals (e.g., working-memory capacity, for an overview see Kotabe & Hofmann, 2015) also apply to hedonic goal pursuit. Some findings in the eating domain suggest that working memory capacity is relevant for taste perception and may therefore play a role for the enjoyment of food (Van der Wal & Van Dillen, 2013). The present research represents a next step toward understanding when and why people manage to achieve the pleasure they strive for.

Future Directions

Even though the focus of the current work is on hedonic goals, we neither propose that they are superior to long-term goals, nor do we advise to pursue hedonic goals more often. Instead, our aim was to develop a measure to capture the quality of hedonic goal pursuit and to understand its mechanisms and consequences for well-being. Given that thoughts about the conflicting alternative goal undermine long-term as well as hedonic goal pursuit (leading to self-control vs. hedonic “failure,” respectively; Becker et al., 2019), and given that the successful pursuit of both goals predicts well-being, future research should identify factors that decrease goal conflict. One determinant of experiencing goal conflict in everyday life could be the organization of an individual’s goal system (Tomasik et al., 2017). Depending on the number and organization of potentially conflicting goals, intrusions should be more or less likely. Indeed, research on goal system theory suggests that people differ in the degree to which hedonic stimuli (i.e., chocolate) automatically activate conflicting long-term goals (i.e., diet; Fishbach et al., 2003). These activation patterns, in turn, might be related not only to people’s self-regulatory success regarding their long-term goals (e.g., dieting) but also regarding their hedonic goals (i.e., pleasure). Moreover, people’s ability to balance multiple goals also seems to support goal pursuit through reducing goal conflict (Hofmann et al., 2014). This has been shown for long-term goal pursuit but might, through the same process also apply to hedonic goal pursuit.

Future research should also investigate situational factors that contribute to the activation of conflicting long-term goals. For instance, research shows that stress or high job demands negatively affect well-being, because they fuel intrusive thoughts about work during free time (Sonnentag, 2001). Conversely, people might more freely indulge during special occasions (e.g., birthday), when group norms endorse it (e.g., all colleagues join the drinks), or when they have not pursued hedonic goals for a while (Inzlicht & Schmeichel, 2012; but see Herman & Mack, 1975). Such situational factors are important to consider in the future independently of and in interaction with trait hedonic capacity.

Another key direction for future research should be to test the consequences of trait hedonic capacity for other relevant outcomes, such as occupational success, physical health, or relationship quality. Given that in our studies trait hedonic capacity was, if anything, slightly positively related to trait self-control, we would not expect that people high in trait hedonic capacity are worse off regarding those outcomes. In fact, people who have a strong need to pursue hedonic goals but are not successful at it might have a tendency to compensate by either increasing the quantity (Cornil & Chandon, 2016) or the intensity of hedonic experiences (cf. Van Der Wal & Van Dillen, 2013). Thus, trait hedonic capacity might even be positively related to people’s health. More research is needed to study the consequences of trait hedonic capacity on different outcomes.

Conclusion

A balance between long-term and hedonic goals is paramount to psychological adjustment and well-being. Nevertheless, research on self-control has so far only focused on the benefits of and mechanisms supporting long-term goal pursuit. The aim of the present studies was to address this blind spot. First, we developed a valid and reliable measure to quantify individual differences in people’s capacity to pursue hedonic goals and showed that it predicts well-being (independent of trait self-control). We could also show that intrusive thoughts about conflicting long-term goals may be one key mechanism undermining successful hedonic goal pursuit. We conclude that hedonic goal pursuit needs to be taken into account when studying adaptive self-regulation and call upon the field to start seeing and studying its potential.

Supplemental Material

Bernecker_Online_Appendix – Supplemental material for Beyond Self-Control: Mechanisms of Hedonic Goal Pursuit and Its Relevance for Well-Being

Supplemental material, Bernecker_Online_Appendix for Beyond Self-Control: Mechanisms of Hedonic Goal Pursuit and Its Relevance for Well-Being by Katharina Bernecker and Daniela Becker in Personality and Social Psychology Bulletin

Supplemental Material

OnlineSupplement_Fin – Supplemental material for Beyond Self-Control: Mechanisms of Hedonic Goal Pursuit and Its Relevance for Well-Being

Supplemental material, OnlineSupplement_Fin for Beyond Self-Control: Mechanisms of Hedonic Goal Pursuit and Its Relevance for Well-Being by Katharina Bernecker and Daniela Becker in Personality and Social Psychology Bulletin

Footnotes

Acknowledgements

We would like to thank Kai Sassenberg and Michael L.W. Vliek for their helpful comments on an earlier version of the manuscript. Furthermore, we would like to thank Marina Milyavskaya for her assistance in translating the scale.

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by the Leibniz Association.

ORCID iD

Katharina Bernecker

Supplemental Material

Supplemental material is available online with this article.

Notes

References

Aarts

Dijksterhuis

(2000). Habits as knowledge structures: Automaticity in goal-directed behavior. Journal of Personality and Social Psychology, 78(1), 53–63. https://doi.org/10.1037/0022-3514.78.1.53

Aiken

L. S.

West

S. G.

(1991). Multiple regression: Testing and interpreting interactions. SAGE.

Baumeister

R. F.

Vohs

K. D.

Tice

D. M.

(2007). The strength model of self-control. Current Directions in Psychological Science, 16(6), 351–355. https://doi.org/10.1111/j.1467-8721.2007.00534.x

Becker

Jostmann

N. B.

Hofmann

Holland

R. W.

(2019). Spoiling the pleasure of success: Emotional reactions to the experience of self-control conflict in the eating domain. Emotion, 9(8), 1377–1395. https://doi.org/10.1037/emo0000526

Bernecker

Job

Hofmann

(2018). Experience, resistance, and enactment of desires: Differential relationships with trait measures predicting self-control. Journal of Research in Personality, 76, 92–101. https://doi.org/10.1016/j.jrp.2018.07.007

Bertrams

Dickhäuser

(2009). Messung dispositioneller Selbstkontroll-Kapazität. Eine deutsche Adaptation der Kurzform der Self-Control Scale (SCS-K-D) [Measuring dispositional self-control capacity. A German adaptation of the short form of the Self-Control Scale (SCS-K-D)]. Diagnostica, 55(1), 2–10. https://doi.org/10.1026/0012-1924.55.1.2

Brähler

Mühlan

Albani

Schmidt

(2007). Teststatistische Prüfung und Normierung der deutschen Versionen des EUROHIS-QOL Lebensqualität-Index und des WHO-5 Wohlbefindens-Index [Testing and standardization of the German version of the EUROHIS-QOL and WHO-5 quality-of life-indices]. Diagnostica, 53(2), 83–96. https://doi.org/10.1026/0012-1924.53.2.83

Brown

T. A.

(2006). Confirmatory factor analysis. Guilford Press.

Bryant

F. B.

(2003). Savoring beliefs inventory (SBI): A scale for measuring beliefs about savouring. Journal of Mental Health, 12(2), 175–196. https://doi.org/10.1080/0963823031000103489

10.

Bryk

Raudenbush

(1992). Hierarchical linear models: Applications and data analysis methods. SAGE.

11.

Cohen

(1992). A power primer. Psychological Bulletin, 112(1), 155–159. https://doi.org/10.1037/0033-2909.112.1.155

12.

Cornil

Chandon

(2016). Pleasure as a substitute for size: How multisensory imagery can make people happier with smaller food portions. Journal of Marketing Research, 53, 847–864. https://doi.org/10.1509/jmr.14.0299

13.

de Ridder

D. T. D.

Lensvelt-Mulders

Finkenauer

Stok

F. M.

Baumeister

R. F

. (2012). Taking stock of self-control: A meta-analysis of how trait self-control relates to a wide range of behaviors. Personality and Social Psychology Review, 16(1), 76–99. https://doi.org/10.1177/1088868311418749

14.

Diener

Emmons

R. A.

Larsen

R. J.

Griffin

(1985). The satisfaction with Life Scale. Journal of Personality Assessment, 49(1), 71–75. https://doi.org/10.1207/s15327752jpa4901_13

15.

Fishbach

Dhar

Zhang

(2006). Subgoals as substitutes or complements: The role of goal accessibility. Journal of Personality and Social Psychology, 91(2), 232–242. https://doi.org/10.1037/0022-3514.91.2.232

16.

Fishbach

Friedman

R. S.

Kruglanski

A. W.

(2003). Leading us not into temptation: Momentary allurements elicit overriding goal activation. Journal of Personality and Social Psychology, 84(2), 296–309. https://doi.org/10.1037/0022-3514.84.2.296

17.

Fishbach

Shah

J. Y.

(2006). Self-control in action: Implicit dispositions toward goals and away from temptations. Journal of Personality and Social Psychology, 90(5), 820–832. https://doi.org/10.1037/0022-3514.90.5.820

18.

Franke

G. H.

Jaeger

Glaesmer

Barkmann

Petrowski

Braehler

(2017). Psychometric analysis of the brief symptom inventory 18 (BSI-18) in a representative German sample. BMC Medical Research Methodology, 17(1), 1–7. https://doi.org/10.1186/s12874-016-0283-3

19.

Friese

Hofmann

(2016). State mindfulness, self-regulation, and emotional experience in everyday life. Motivation Science, 2(1), 1–14. https://doi.org/10.1037/mot0000027

20.

Fromm

(1976). To have or to be? Continuum.

21.

Gillebaart

De Ridder

D. T. D.

(2015). Effortless self-control: A novel perspective on response conflict strategies in trait self-control. Social and Personality Psychology Compass, 2(10), 88–99. https://doi.org/10.1111/spc3.12160

22.

Gröpel

Kuhl

(2006). Having time for life activities: Life balance and self-regulation. Zeitschrfit Für Gesundheitspsychologie, 14(2), 54–63. https://doi.org/10.1026/0943-8149.14.2.54

23.

Herman

C. P.

Mack

(1975). Restrained and unrestrained eating. Journal of Personality, 43(3), 647–660. https://doi.org/10.1111/j.1467-6494.1975.tb00727.x

24.

Hofmann

Baumeister

R. F.

Förster

Vohs

K. D.

(2012). Everyday temptations: An experience sampling study of desire, conflict, and self-control. Journal of Personality and Social Psychology, 102(6), 1318–1335. https://doi.org/10.1037/a0026545

25.

Hofmann

Friese

Strack

(2009). Impulse and self-control from a dual-systems perspective. Perspectives on Psychological Science, 4(2), 162–176. https://doi.org/10.1111/j.1745-6924.2009.01116.x

26.

Hofmann

Luhmann

Fisher

R. R.

Vohs

K. D.

Baumeister

R. F.

(2014). Yes, but are they happy? Effects of trait self-control on affective well-being and life satisfaction. Journal of Personality, 82(4), 265–277. https://doi.org/10.1111/jopy.12050

27.

Hofmann

Van Dillen

(2012). Desire: The new hot spot in self-control research. Current Directions in Psychological Science, 21(5), 317–322. https://doi.org/10.1177/0963721412453587

28.

Horn

J. L.

(1965). A rationale and test for the number of factors in factor analysis. Psychometrica, 30(2), 179–185. https://doi.org/https://doi.org/10.1007/BF02289447

29.

Huta

Ryan

R. M.

(2010). Pursuing pleasure or virtue: The differential and overlapping well-being benefits of hedonic and eudaimonic motives. Journal of Happiness Studies, 11(6), 735–762. https://doi.org/10.1007/s10902-009-9171-4

30.

Huta

Waterman

A. S.

(2014). Eudaimonia and its distinction from hedonia: Developing a classification and terminology for understanding conceptual and operational definitions. Journal of Happiness Studies, 15, 1425–1456. https://doi.org/10.1007/s10902-013-9485-0

31.

Inzlicht

Schmeichel

B. J.

(2012). What is ego depletion? Toward a mechanistic revision of the resource model of self-control. Perspectives on Psychological Science, 7(5), 450–463. https://doi.org/10.1177/1745691612454134

32.

Jing

H. G.

Madore

K. P.

Schacter

D. L.

(2016). Worrying about the future: An episodic specificity induction impacts problem solving, reappraisal, and well-being. Journal of Experimental Psychology: General, 145(4), 402–418.

33.

Kavanagh

D. J.

Andrade

May

. (2005). Imaginary relish and exquisite torture: The elaborated intrusion theory of desire. Psychological Review, 112(2), 446–467. https://doi.org/10.1037/0033-295X.112.2.446

34.

Klug

H. J. P.

Maier

G. W.

(2015). Linking goal progress and subjective well-being: A meta-analysis. Journal of Happiness Studies, 16, 37–65. https://doi.org/10.1007/s10902-013-9493-0

35.

Koole

S. L.

Tops

Strübin

Bouw

Schneider

I. K.

Jostmann

N. B.

(2014). The ego fixation hypothesis : Involuntary persistence of self-control. In Forgas

J. P.

Harmon-Jones

(Eds.), Motivation and its regulation: The control within (pp. 95–112). Psychology Press.

36.

Kotabe

H. P.

Hofmann

(2015). On integrating the components of self-control. Perspectives on Psychological Science, 10(5), 618–638. https://doi.org/10.1177/1745691615593382

37.

Kruglanski

A. W.

Shah

J. Y.

Fishbach

Friedman

Chun

W. Y.

Sleeth-Keppler

(2002). A theory of goal systems. Advances in Experimental Social Psychology, 34, 331–378. https://doi.org/10.2307/2092805

38.

Kuhl

(2000). A functional-design approach to motivation and self-regulation: The dynamics of personality systems interactions. In Boekaerts

Pintrick

P. R.

Zeidner

(Eds.), Handbook of self-regulation (pp. 111–169). Academic Press.

39.

Mead

N. L.

Patrick

V. M.

Gunadi

M. P.

Hofmann

(2016). Simple pleasures, small annoyances, and goal progress in daily life. Journal of the Association for Consumer Research, 1(4), 527–539.

40.

Mirisola

Seta

(2016). Pequod: Moderated regression package (R package version 0.0-5). https://cran.r-project.org/package=pequod

41.

Moffitt

T. E.

Arseneault

Belsky

Dickson

Hancox

R. J.

Harrington

Houts

Poulton

Roberts

B. W.

Ross

Sears

M. R.

Thomson

W. M.

Caspi

(2011). A gradient of childhood self-control predicts health, wealth, and public safety. Proceedings of the National Academy of Sciences of the United States of America, 108(7), 2693–2698. https://doi.org/10.1073/pnas.1010076108

42.

Oettingen

Mayer

Portnow

(2016). Pleasure now, pain later: Positive fantasies about the future predict symptoms of depression. Psychological Science, 27(3), 345–353. https://doi.org/10.1177/0956797615620783

43.

Oettingen

Pak

Schnetter

(2001). Self-regulation of goal setting: Turning free fantasies about the future into binding goals. Journal of Personality and Social Psychology, 80(5), 736–753.

44.

Quoidbach

Berry

E. V.

Hansenne

Mikolajczak

(2010). Positive emotion regulation and well-being: Comparing the impact of eight savoring and dampening strategies. Personality and Individual Differences, 49(5), 368–373. https://doi.org/10.1016/j.paid.2010.03.048

45.

R Core Team. (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing.

46.

Revelle

(2013). psych: Procedures for personality and psychological research (1.8.12). Northwestern University. https://cran.r-project.org/package=psych

47.

Riso

L. P.

Blandino

J. A.

Penna

Dacey

Duin

J. S.

Pacoe

E. M.

Grant

M. M.

Ulmer

C. S.

(2003). Cognitive aspects of chronic depression. Journal of Abnormal Psychology, 112(1), 72–80. https://doi.org/10.1037/0021-843X.112.1.72

48.

Rizvi

S. J.

Pizzagalli

D. A.

Sproule

B. A.

Kennedy

S. H.

(2016). Assessing anhedonia in depression: Potentials and pitfalls. Neuroscience and Biobehavioral Reviews, 65, 21–35. https://doi.org/10.1016/j.neubiorev.2016.03.004

49.

Rom

S. C.

Katzir

Diel

Hofmann

(2019). On trading off labor and leisure: A process model of perceived autonomy and opportunity cost. Motivation Science. Advance online publication. https://doi.org/https://doi.org/10.31234/osf.io/25gqp

50.

Schacter

D. L.

Benoit

R. G.

Szpunar

K. K.

(2017). Episodic future thinking: Mechanisms and functions. Current Opinion in Behavioral Sciences, 17, 41–50.

51.

Shah

J. Y.

Friedman

Kruglanski

A. W.

(2002). Forgetting all else: On the antecedents and consequences of goal shielding. Journal of Personality and Social Psychology, 83(6), 1261–1280. https://doi.org/10.1037/0022-3514.83.6.1261

52.

Shah

J. Y.

Kruglanski

A. W.

(2002). Priming against your will: How goal pursuit is affected by accessible alternatives. Journal of Experimental Social Psychology, 38, 368–382.

53.

Solbrig

Whalley

Kavanagh

D. J.

May

Parkin

(2019). Functional imagery training versus motivational interviewing for weight loss: A randomised controlled trial of brief individual interventions for overweight and obesity. International Journal of Obesity, 43, 883–894. https://doi.org/10.1038/s41366-018-0122-1

54.

Sonnentag

(2001). Work, recovery activities, and individual well-being: A diary study. Journal of Occupational Health Psychology, 6(3), 196–210. https://doi.org/10.1037/1076-8998.6.3.196

55.

Steyer

Schwenkmezger

Notz

Eid

(1997). Der Mehrdimensionale Befindlichkeitsfragebogen (MDBF) [Multidimensional Mood Questionnaire]. Hogrefe-Verlag GmbH.

56.

Strack

Deutsch

(2004). Reflective and impulsive determinants of social behavior. Personality and Social Psychology Review: An Official Journal of the Society for Personality and Social Psychology, 8(3), 220–247. https://doi.org/10.1207/s15327957pspr0803_1

57.

Stroebe

Mensink

Aarts

Schut

Kruglanski

A. W.

(2008). Why dieters fail: Testing the goal conflict model of eating. Journal of Experimental Social Psychology, 44, 26–36. https://doi.org/10.4324/9781315141817

58.

Tangney

J. P.

Baumeister

R. F.

Boone

A. L.

(2004). High self-control predicts good adjustment, less pathology, better grades, and interpersonal success. Journal of Personality, 72(2), 271–324. https://doi.org/10.1111/j.0022-3506.2004.00263.x

59.

Tiggemann

Kemps

Parnell

(2010). The selective impact of chocolate craving on visuospatial working memory. Appetite, 55(1), 44–48. https://doi.org/10.1016/j.appet.2010.03.010

60.

Tomasik

M. J.

Knecht

Freund

A. M.

(2017). Some evidence for the usefulness of an optimal foraging theory perspective on goal conflict and goal facilitation. Journal of Personality and Social Psychology, 113(6), 962–980. https://doi.org/https://dx-doi-org.web.bisu.edu.cn/10.1037/pspp0000165

61.

Trope

Fishbach

(2000). Counteractive self-control in overcoming temptation. Journal of Personality and Social Psychology, 79(4), 493–506. https://doi.org/10.1037//0022-3514.79.4.493

62.

Van der Wal

R. C.

Van Dillen

L. F

. (2013). Leaving a flat taste in your mouth: Task load reduces taste perception. Psychological Science, 24(7), 1277–1284. https://doi.org/10.1177/0956797612471953

63.

Waterman

A. S.

(1993). Two conceptions of happiness: Contrasts of personal expressiveness (eudaimonia) and hedonic enjoyment. Journal of Personality and Social Psychology, 64(4), 678–691. https://doi.org/10.1037/0022-3514.64.4.678

64.

Wendsche

Lohmann-Haislah

(2017). A meta-analysis on antecedents and outcomes of detachment from work. Frontiers in Psychology, 7, 1–24. https://doi.org/10.3389/fpsyg.2016.02072

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.22 MB

0.03 MB