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What motivates individuals to invest time and effort and overcome obstacles (i.e., strive for primary control) when pursuing important goals? We propose that positive affect predicts primary control striving for career and educational goals, and we explore the mediating role of control beliefs. In Study 1, positive affect predicted primary control striving for career goals in a two-wave longitudinal study of a U.S. sample. In Study 2, positive affect predicted primary control striving for career and educational goals and objective career outcomes in a six-wave longitudinal study of a German sample. Control beliefs partially mediated the longitudinal associations with primary control striving. Thus, when individuals experience positive affect, they become more motivated to invest time and effort, and overcome obstacles when pursuing their goals, in part because they believe they have more control over attaining their goals.
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Personality and Social Psychology
http://psp.sagepub.com/content/early/2012/05/04/0146167212444906
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DOI: 10.1177/0146167212444906
published online 8 May 2012Pers Soc Psychol Bull
Claudia M. Haase, Michael J. Poulin and Jutta Heckhausen
Goals
Happiness as a Motivator: Positive Affect Predicts Primary Control Striving for Career and Educational
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Does happiness make people lazy or does it prompt them to
strive for more? Lay people, artists, philosophers, and
psychologists are divided in their answer to this question
(Veenhoven, 1988).
The present article examines positive affect, a core aspect
of happiness and subjective well-being (Diener, 2000; Diener,
Oishi, & Lucas, 2009). Meta-analytic findings show that
positive affect leads to long-term success in numerous life
domains including work (Boehm & Lyubomirsky, 2008;
Lyubomirsky, King, & Diener, 2005). Happy individuals, for
example, show better job performance and have higher
incomes. In this article, we investigate positive affect as a
motivator. We propose that positive affect predicts primary
control striving, that is, the motivation to invest time and
effort and overcome obstacles, when pursuing important
goals. Our focus in this article is on primary control striving
for career and educational goals.
Primary Control Striving for
Career and Educational Goals
Career and educational goals are highly relevant for people
across the globe, particularly for young people who are transi-
tioning into work (Chang, Chen, Greenberger, Dooley, &
Heckhausen, 2006; Kalakoski & Nurmi, 1998; Schoon &
Silbereisen, 2009). Education and career success in turn have
far-reaching implications for long-term development (e.g.,
Furnée, Groot, & van den Brink, 2008; Morris, Cook, &
Sharper, 1994; Roberts, Walton, Bogg, & Caspi, 2006; Schoon
& Silbereisen, 2009; Schulenberg, Bryant, & O’Malley, 2004).
Although many individual and situational factors influence the
attainment of educational and career goals, one key predictor
of success is an individual’s primary control striving, that is,
the motivation to invest time and effort (i.e., selective primary
control [SPC]) and overcome obstacles (i.e., compensatory
primary control [CPC]) in the pursuit of goals (Heckhausen,
Wrosch, & Schulz, 2010). Findings from longitudinal and
intervention studies show that primary control striving is cru-
cial for success in many life domains, including the domains of
school and work (for a review, see Heckhausen et al., 2010).
Both self-report and behavioral indicators of primary control
XXX10.1177/0146167212444906Haase et al.Personality and Social Psychology Bulletin
1University of California, Berkeley, USA
2University at Buffalo, NY, USA
3University of California, Irvine, USA
Corresponding Author:
Claudia M. Haase, Department of Psychology, Institute of Personality and
Social Research, University of California, Berkeley, 4143 Tolman Hall 5050,
Berkeley, CA 94720-5050, USA
Email: claudia.haase@berkeley.edu
Happiness as a Motivator: Positive Affect
Predicts Primary Control Striving for
Career and Educational Goals
Claudia M. Haase1, Michael J. Poulin2, and Jutta Heckhausen3
Abstract
What motivates individuals to invest time and effort and overcome obstacles (i.e., strive for primary control) when pursuing
important goals? We propose that positive affect predicts primary control striving for career and educational goals, and we
explore the mediating role of control beliefs. In Study 1, positive affect predicted primary control striving for career goals in
a two-wave longitudinal study of a U.S. sample. In Study 2, positive affect predicted primary control striving for career and
educational goals and objective career outcomes in a six-wave longitudinal study of a German sample. Control beliefs partially
mediated the longitudinal associations with primary control striving. Thus, when individuals experience positive affect, they
become more motivated to invest time and effort, and overcome obstacles when pursuing their goals, in part because they
believe they have more control over attaining their goals.
Keywords
happiness, positive affect, motivation, primary control striving, control beliefs
Received February 25, 2011; revision accepted February 12, 2012
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2 Personality and Social Psychology Bulletin XX(X)
striving predict successful outcomes on the subjective level
(e.g., subjective career success and well-being) and on the
objective level (e.g., educational attainment, job attainment;
Duckworth, Peterson, Matthews, & Kelly, 2007; Haase,
Heckhausen, & Köller, 2008; Haase, Heckhausen, &
Silbereisen, in press; Kanfer, Wanberg, & Kantrowitz, 2001;
Nurmi, Salmela-Aro, & Koivisto, 2002; Pinquart, Juang, &
Silbereisen, 2003; Salmela-Aro, 2009; Tomasik, Hardy, Haase,
& Heckhausen, 2009; Wiese, Freund, & Baltes, 2002). Yet,
although much is known about the benefits of primary control
striving, little is known about resources that enhance primary
control striving for career and educational goals.
Positive Affect as a Motivator
of Primary Control Striving
Positive affect can play several roles in the motivation of
behavior. Anticipated positive affect motivates behavior
(e.g., Custers & Aarts, 2005; see review in Heckhausen &
Heckhausen, 2010), and goal-related positive affect stem-
ming from goal pursuit and attainment feeds back into
motivation (e.g., Carver, 2003; Carver & Scheier, 1998;
Louro, Pieters, & Zeelenberg, 2007). The present article
does not address anticipated affect or goal-related affect,
but incidental (e.g., Loewenstein & Lerner, 2003) positive
affect, which stems from goal-unrelated sources.
The motivational theory of lifespan development
(Heckhausen et al., 2010), which grew out of the lifespan
theory of control (Heckhausen & Schulz, 1995), proposes
that positive affect is an important resource for primary con-
trol striving (Schulz & Heckhausen, 1998). This hypothesis
builds on an evolutionary-functionalistic view of emotions,
which proposes that positive and negative emotions serve
adaptive functions (e.g., Averill et al., 1994; Frijda, 1988,
2010; Keltner & Gross, 1999; Levenson, 1999). We should
note that Carver and colleagues have postulated the opposite
effect: Positive affect should decrease primary control striv-
ing with regard to current goals and serve as a “signal to
attend to something else” (Carver, 2003). Yet, their hypothe-
sis focuses on goal-related positive affect, whereas the pres-
ent article examines incidental positive affect.
Surprisingly few studies have examined effects of posi-
tive affect on primary control striving, and the available
studies have yielded mixed findings. For example, Hom
and Arbuckle (1988) found that children in a happy mood
invested more effort on an assigned task than children in a
sad mood. Melton (1995) concluded that “people in posi-
tive moods expend less effort” (p. 788). Williams and
DeSteno (2008) demonstrated that pride induced by a feed-
back manipulation, but not unspecific positive affect, led to
higher perseverance. Foo, Uy, and Baron (2009) found that
state (but not trait) positive affect predicted higher proac-
tive venture efforts among entrepreneurs. Seo, Bartunek,
and Barrett (2010) showed that positive affect predicted
higher effort in an Internet-based investment simulation
study using an experience sampling method. Thus, empirical
findings are mixed. Moreover, what are the mediating
pathways?
There are various pathways by which positive affect
may enhance primary control striving. Positive affect has
restorative neurobiological effects (e.g., Burns et al., 2008;
Richter & Gendolla, 2009) and can repair depleted self-
regulatory resources (Tice, Baumeister, Shmueli, &
Muraven, 2007) that are needed for primary control striv-
ing. Moreover, positive affect may enhance primary con-
trol striving by boosting control beliefs. This particular
mediating pathway will be explored in this article building
on the mood-as-information theory (Schwarz, 2012;
Schwarz & Clore, 1983) and the self-efficacy theory (Ban dura,
1997). Specifically, the mood-as-information theory pro-
poses that incidental positive affect colors cognition
because individuals ask themselves “How do I feel about
it?” and erroneously use their current affect as valid infor-
mation to guide their thoughts. That is, positive affect pro-
vides (not necessarily realistic) information that things
will go well. Supporting this prediction, experimental
studies have shown that positive affect indeed enhances
control beliefs and success expectations (e.g., Lerner &
Keltner, 2001; Richter & Gendolla, 2009). Self-efficacy
theory (Bandura, 1997) in turn proposes that self-efficacy
(i.e., control) beliefs boost processes involved in primary
control striving. This hypothesis has received broad empir-
ical support in experimental and longitudinal studies (for a
review, see Bandura, 1997; e.g., Bouffard-Bouchard, 1990;
Shane, Heckhausen, Lessard, Chen, & Greenberger, in
press). Despite clear evidence for both parts of the medita-
tional chain, few studies (but see Seo et al., 2010) have
combined them to investigate effects of positive affect on
primary control striving mediated by control beliefs, espe-
cially regarding important real-world goals such as career
or educational goals.
The Present Studies
The present studies investigated positive affect as a motivator.
We expected positive affect to predict primary control striving
(i.e., the motivation to invest time and effort and overcome
obstacles) for career and educational goals over time.
Moreover, we examined the mediating role of control beliefs.
We put this hypothesis to the test in two longitudinal studies
of U.S. and German youth during the transition from school
to work. Career and educational goals are important goals
during this life-span transition (e.g., Chang et al., 2006).
In Study 1, a two-wave longitudinal study of a multieth-
nic sample of U.S. youth, we examined longitudinal associa-
tions between positive affect and primary control striving for
career goals. In Study 2, a six-wave longitudinal study of
German youth, we sought to replicate and extend findings
from Study 1, by examining longitudinal associations
between positive affect and primary control striving for
apprenticeship, occupational future, and educational goals as
well as objective career outcomes. In both studies, we sought
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Haase et al. 3
to predict primary control striving over longer time intervals
(i.e., several months). As we did not expect momentary posi-
tive affect to predict primary control striving over these lon-
ger time intervals, we examined somewhat longer lasting
positive affective states (i.e., experienced over a week or a
month) for a more reliable assessment.
Although this article focuses on positive affect as concep-
tually distinct from negative affect (Watson, Wiese, Vaidya,
& Tellegen, 1999), we also examined whether negative affect
predicted primary control striving. However, we did so with-
out formulating specific hypotheses because research indi-
cates that the motivational effects of negative affect may not
be uniform but depend on the specific negative emotion
(e.g., anger or sadness) involved (e.g., Carver, 2006; Carver
& Harmon-Jones, 2009; Wrosch & Miller, 2009).
Study 1
Study 1 examined whether positive affect predicted primary
control striving for career goals over time in a two-wave
longitudinal study of a multiethnic sample of U.S. youth in
the transition after high school. Moreover, we examined the
mediating role of control beliefs. We also explored longitu-
dinal associations between negative affect, specifically,
depressive symptoms and primary control striving.
Method
Participants. The sample consisted of 1,185 youth recruited
from four schools in Los Angeles to capture a multiethnic,
working- and middle-class sample. At the first wave of data
collection, participants were in their senior high school year.
The present analyses are based on 752 participants who par-
ticipated in the first two waves of data collection (mean age
in years = 17.7 years; 60.2% female). The sample was ethni-
cally diverse (22.8% White/European, 11.3% African Amer-
ican, 40.5% Hispanic/Latino, 9.5% South/Southeast Asian,
16.0% Other or Mixed). Parental consent was obtained for
all minors, and all legal adult participants provided informed
consent. Students were compensated at each wave by
being entered into drawings for gift certificates (two US$20
gift certificates per classroom and two US$100 certificates
per school).
Measures
Positive affect. A measure of positive affect experienced
during the last week was created using selected items from
the Center for Epidemiologic Studies Depression Scale
(CESD; Radloff, 1991). Although the CESD is designed to
assess depressive symptoms, it includes four items that have
been used widely (e.g., Moskowitz, Epel, & Acree, 2008;
Sheehan, Fifield, Reisine, & Tennen, 1995) as indicators of
positive affect (i.e., “I was happy,” “I felt hopeful about the
future,” “I felt that I was just as good as other people,” “I
enjoyed life”; 1 = rarely or none of the time, 4 = most or all
of the time; α = .65 at Wave 1, α = .70 at Wave 2).1
Depressive symptoms. Depressive symptoms were assessed
using the remaining 16 CESD items that were not used to
compute our measure of positive affect (Radloff, 1991).
These items measured depressive symptoms (e.g., poor
appetite, crying, “the blues”) experienced during the last
week (1 = rarely or none of the time, 4 = most or all of the
time; α = .89 at Wave 1, α = .88 at Wave 2).
Primary control striving. Primary control striving was mea-
sured using the Optimization in Primary and Secondary Con-
trol (OPS) scale tailored to the career domain, which has
demonstrated adequate measurement properties and validity
in previous studies (Haase et al., 2008; Poulin & Heckhausen,
2007; Tomasik et al., 2009). Primary control striving regard-
ing career goals was measured by four items assessing SPC
(e.g., “I will work hard to have a good career”) and four items
assessing CPC (e.g., “If my career path is not going in the
right direction, I will get help from others”) on a 5-point scale
(1 = completely disagree, 5 = completely agree). The primary
control striving scale showed satisfactory internal consis-
tency (α = .77 at Wave 1, α = .78 at Wave 2).
Control beliefs. Career-related control beliefs were mea-
sured by five items from the Control Agency Means-Ends
in Adulthood Questionnaire (CAMAQ; Heckhausen, 1991)
indicating ability and effort agency beliefs (e.g., “I am fit
for the occupations I apply for”; 1 = completely disagree,
5 = completely agree) as well as expectancies (“How likely
is it that you will attain your desired long-term career?”
1 = very unlikely, 5 = very likely). Internal consistency of
the scale was mediocre (α = .63 at Wave 1, α = .62 at Wave 2).
Design and Procedure. Study 1 used a two-wave longitudinal
design. Data were collected shortly before school graduation
(Wave 1) and 1 year after graduation (Wave 2). For Wave 1,
students completed in-class surveys. For Wave 2, surveys
were mailed to students with a response rate of 63%. All mea-
sures analyzed here were assessed at Wave 1 and 2.
Results
Table 1 shows descriptive statistics and correlations for the
study variables. Multiple regression analyses were used to
test the hypothesis. Analyses were conducted longitudi-
nally, with Wave 1 variables predicting relative increases in
Wave 2 primary control striving. As a first step, Wave 2
career-related primary control striving was regressed on
Wave 1 career-related primary control striving, positive
affect, and depressive symptoms. The resulting model indi-
cated that positive affect predicted relative increases in
primary control striving (β = .11, p = .004) controlling for
all other variables (Table 2, Model 1). Next, career-related
control beliefs were added to test for mediation (Table 2,
Model 2). The regression coefficient of positive affect
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4 Personality and Social Psychology Bulletin XX(X)
Table 1. Study 1: Descriptive Statistics and Correlations for Study Variables (N = 752)
Correlations
Variables M (SD) 1 2 3 4 5 6 7
1. W1 Positive affect 3.27 (0.64)
2. W1 Depressive
symptoms
2.03 (0.59) .37***
3. W1 Control beliefs
(career)
4.07 (0.65) .33*** .12***
4. W1 Primary control
striving (career)
4.34 (0.52) .18*** .01 .24***
5. W2 Positive affect 3.31 (0.66) .41*** .30*** .15*** .11**
6. W2 Depressive
symptoms
1.90 (0.57) .26*** .46*** .08.03 .43***
7. W2 Control beliefs
(career)
4.15 (0.60) .21*** .10** .35*** .18*** .29*** .16*** —
8. W2 Primary control
striving (career)
4.36 (0.50) .13*** .01 .22*** .34*** .19*** .10** .38***
Note: W1 = Wave 1; W2 = Wave 2.
p < .10. **p < .01. ***p < .001.
Table 2. Study 1: Wave 2 Primary Control Striving for Career
Goals Regressed on Wave 1 Predictors (N = 719)
Wave 2 primary control striving
(career)
Wave 1 predictors Model 1 Model 2
Primary control striving
(career)
.32*** .30***
Positive affect .11** .08
Depressive symptoms .06 .06
Control beliefs (career) .13***
Note: Standardized regression coefficients (βs).
p < .10. **p < .01. ***p < .001.
dropped to marginal significance (β = .08, p = .06). A Sobel test
indicated that the indirect path in the postulated mediation model
(i.e., mediation via control beliefs) was significant (z = 3.15, p =
.002). Depressive symptoms (computed without positive affect-
related items) did not predict primary control striving over time.
A set of follow-up analyses examined reverse associations
with a special focus on primary control striving predicting sub-
sequent positive affect. Although there was a positive associa-
tion between Wave 1 primary control striving and Wave 2
control beliefs, controlling for Wave 1 control beliefs (β = .10,
p < .01), Wave 1 control beliefs did not predict Wave 2 positive
affect, controlling for Wave 1 positive affect (β = .00), and the
association between Wave 1 primary control striving and Wave
2 positive affect, controlling for Wave 1 positive affect, was
only marginally significant (β = .07, p < .10). This pattern of
associations indicated that positive affect predicted primary
control striving more strongly than primary control striving
predicted positive affect.
Discussion
Study 1 showed that positive affect predicted relative increases
in primary control striving for career goals over time. That
is, students who were happier subsequently increased their
striving toward their career goals over previously assessed
levels of primary control striving. Moreover, we explored
the mediating role of control beliefs. Our findings were
consistent with the postulated mediation model and pro-
vided a first hint that positive affect may enhance primary
control striving for real-world goals such as career goals
because it enhances beliefs that these goals can actually
be attained. These results were found in a large multieth-
nic sample of U.S. high school seniors transitioning into
work life and engaged in the highly relevant goal of
career attainment. Depressive symptoms (excluding posi-
tive affect-related items) did not predict primary control
striving.
Study 1 had several limitations. Positive affect was
assessed using items not originally designed for that purpose
(but widely used by others; for example, Moskowitz et al.,
2008; Sheehan et al., 1995). Primary control striving was
only assessed by self-report, not by any objective measure of
goal pursuit or success. Moreover, primary control striving
was only assessed in one goal domain and in a U.S. sample,
limiting the generalizability of the findings to other goal
domains and other cultures. Finally, Study 1 used a two-
wave longitudinal design, which has well-known limitations
(Rogosa, 1980).
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Haase et al. 5
Study 2
The aim of Study 2 was to replicate the longitudinal findings
of Study 1 while improving on its limitations. To do so,
Study 2 examined primary control striving in a different
cultural context: a sample of German adolescents in the
transition from high school (in our case Realschule) to
vocational education. The German school-to-work transi-
tion involves particularly great time pressure in that
Realschule youth typically seek so-called apprenticeships
(Hamilton, 1990) after graduation, which are crucial for
their occupational future but are in scarce supply and bound
to a tight deadline (Poulin & Heckhausen, 2007).
The primary question of Study 2 was whether positive
affect would predict primary control striving over time.
Different from Study 1, Study 2 used a dedicated measure of
positive affect (the Positive and Negative Affect Schedule
[PANAS]; Watson, Clark, & Tellegen, 1988), examined objec-
tive outcomes of primary control striving and success
(apprenticeship applications and offers), assessed primary
control striving in several goal domains (for apprenticeship,
occupational future, and educational goals), and used a six-
wave longitudinal design. As in Study 1, we examined the
mediating role of control beliefs. We focused on primary
control striving and control beliefs in the goal domain of
apprenticeship seeking as control beliefs were not assessed
in the other domains. In addition, we explored whether
negative affect predicted primary control striving over time.
Method
Participants. The initial sample consisted of three cohorts of
768 youth from Berlin, Germany. At the first wave of data
collection, participants were in their senior Realschule
school year. In the present analyses, only data from Cohorts
2 and 3 were used because primary control striving was
assessed in a different format in Cohort 1 resulting in a final
sample size of 464 (mean age in years = 16.8; 48.4% female).
Parental consent was obtained for all study participants.
Measures
Positive affect. Positive affect during the last month was
measured at all waves by the positive affect subscale of the
PANAS (Watson et al., 1988; for example, “enthusiastic”;
1 = not at all, 5 = very often; 10 items; αs ranged from .79
to .84).
Negative affect. Negative affect during the last month
was measured at all waves by the negative affect subscale
of the PANAS (Watson et al., 1988; for example, “dis-
tressed”; 1 = not at all, 5 = very often; 10 items; αs ranged
from .79 to .86).
Primary control striving. As in Study 1, primary control
striving was measured by domain-specific versions of the
OPS scale. Previous publications have shown the validity
of the career-related OPS measures (Haase et al., 2008;
Tomasik et al., 2009). Primary control striving for appren-
ticeship goals was measured at all waves by 12 items tai-
lored to the apprenticeship domain (SPC, e.g., “I invest all
my energy to get a suitable apprenticeship position”; CPC,
e.g., “If I fail to find a suitable position, I will look for
unusual and new ways to succeed at last”). Primary control
striving for occupational future goals was measured at all
waves by 9 items tailored to the occupational future domain
(SPC, e.g., “I invest all my energy to get a good occupa-
tional future”; CPC, e.g., “If I fail to get a good occupa-
tional future, I will look for new and unusual ways to
succeed at last”). Primary control striving for educational
goals was measured at all waves by 8 items tailored to the
education domain (SPC, e.g., “I work hard to improve my
achievement in school”; CPC, e.g., “If I fail in improving
my school achievement I will ask others for help”). Items
were presented on a 5-point scale (1 = strongly disagree, 5
= strongly agree). Internal consistencies of all primary con-
trol striving scales were satisfactory (αs at all waves ranged
from .82 to .90).
Apprenticeship applications. At each wave, students
reported whether they had written one or more applications
for an apprenticeship since the prior wave, and if so, how
many. The variable was treated as a continuous count vari-
able at each wave.
Apprenticeship offers. At each wave, students reported
whether they had received one or more offers for an
apprenticeship since the prior wave, and if so, how many.
The variable was treated as a continuous count variable at
each wave.
Apprenticeship-related control beliefs. Apprenticeship-
related control beliefs were measured at all waves by abil-
ity and effort agency beliefs from the CAMAQ scale used
in Study 1. Internal consistency of this five-item measure
was moderate (αs ranged from .71 to .75).
Design and Procedure. Study 2 used a dense longitudinal
design with multiple waves of data collection before and
after graduation. The present analyses draw from six waves:
five waves assessed in 2-monthly intervals during the 10th
grade, the senior school year of German Realschule stu-
dents, and one wave scheduled approximately 2 months
after graduation. Retention rates were acceptable (from
Wave 1 to Wave 5 = 82%; from Wave 1 to Wave 6 = 58%).
For Wave 1 to 5, students filled out written questionnaires
during regular classroom hours while teachers were absent.
These sessions were led by trained personnel and lasted
approximately 90 min. Participants received a candy and a
small token (value < US$1) after completing the question-
naire. For Wave 6, questionnaires were mailed to students
who completed them and mailed them back. These partici-
pants received monetary compensation equivalent to
approximately US$20.
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6 Personality and Social Psychology Bulletin XX(X)
Results
Table 3 shows descriptive statistics and correlations for the
study variables. As expected, apprenticeships were rela-
tively scarce. At each wave, about 16.2% of participants
could expect to receive an apprenticeship offer, and by the
last wave of data collection analyzed here, only a slim
majority (52.2%) had been offered an apprenticeship. As in
Study 1, analyses were conducted longitudinally. Because
Study 2 contained multiple waves, we used random-effects
(multilevel) regressions, which represent the data as time
points nested within individuals. Specifically, outcome vari-
ables were regressed on lagged values (values at time t-1) of
predictors across all waves for which each participant con-
tributed data.2 These analyses were conducted using the
xtreg module in Stata 9.0 (StataCorp, 2005). The standard-
ized coefficients we report are based on standardized vari-
ables (i.e., computed with respect to the total variance on a
given variable at a given wave).
Because control beliefs were assessed specifically with
respect to the goal of obtaining an apprenticeship, our pri-
mary analyses examined the longitudinal associations
between positive affect and outcomes in this domain. As a
first step (Table 4, Model 1, first column), primary control
striving was regressed on lagged primary control striving,
positive affect, and negative affect. Lagged positive affect
predicted primary control striving (β = .11, p < .001).
Similar models (Table 4, Model 1, third and fifth column)
examined the associations between lagged positive affect,
and both efforts to obtain an apprenticeship (in the form of
number of applications) and success in obtaining an
apprenticeship (in the form of number of offers received).
For the latter variable, random-effects Poisson regressions
were used because of the relatively rare occurrence of
apprenticeship offers at each wave. Lagged positive affect
marginally predicted the number of apprenticeship appli-
cations (β = .04, p = .06) and the number of apprenticeship
offers (β = .19, p = .003).
As a second step, apprenticeship-related control beliefs
were added to test for mediation (Table 4, Models 2). Sobel
tests indicated that the indirect path in the postulated media-
tion model (i.e., mediation via control beliefs) was signifi-
cant for the association between lagged positive affect and
primary control striving (Sobel: z = 2.89, p = .01), whereas
the indirect paths were not significant for associations
between lagged positive affect and apprenticeship applica-
tions or offers. Lagged positive affect continued to predict
primary control striving and apprenticeship offers. Moreover,
the association between lagged positive affect and appren-
ticeship applications became fully significant.
As in Study 1, a set of follow-up analyses examined
reverse associations with a special focus on primary control
striving predicting subsequent positive affect. We found
significant associations between lagged control beliefs and
positive affect, controlling for lagged positive affect (β = .09,
p < .001); between lagged primary control striving and con-
trol beliefs, controlling for lagged control beliefs (β = .11,
p < .001); and between lagged primary control striving and
positive affect, controlling for lagged positive affect (β = .07,
p < .01). However, note that especially this last association
was smaller than that for positive affect predicting primary
control striving (β = .11, p < .001, see above). In addition,
because Study 2 offered more data points to work with than
did Study 1, an additional follow-up analysis used a fixed-
effects model to determine whether the observed signifi-
cant associations between positive affect and primary
control striving could be attributed to actual within-person
variability or were instead the result of individual differ-
ences. This model used lagged deviations from individuals’
Table 3. Study 2: Descriptive Statistics and Correlations for Study Variables, Averaged Across Waves (N = 429)
Correlations
Variables M (SD) 1 2 3 4 5 6 7 8
1. Positive affect 3.54 (0.62)
2. Negative affect 2.66 (0.70) 0.07
3. Control beliefs
(apprenticeship)
3.80 (0.67) 0.33*** 0.16**
4. Primary control striving
(apprenticeship)
3.78 (0.69) 0.25*** 0.09 .54***
5. Apprenticeship
applications
7.35 (20.90) 0.07 0.01 0.02 0.00
6. Apprenticeship offers 0.43 (1.55) 0.07 0.07 0.10* 0.03 0.24***
7. Primary control striving
(occupational future)
3.95 (0.69) 0.23*** 0.09 0.48*** 0.73*** 0.02 0.01
8. Primary control
striving (education)
3.66 (0.73) 0.26*** 0.08 0.44*** 0.74*** 0.02 0.04 0.67***
Note: *p < .05. **p < .01. ***p < .001.
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Haase et al. 7
mean positive affect over time to predict deviations from
individuals’ mean primary control striving over time, con-
trolling for lagged deviations in control striving and con-
current deviations in positive affect. Results of this model
indicated that lagged positive affect predicted within-
person increases in primary control strivings (β = .04, p <
.05). By contrast, a separate analysis using deviations in
positive affect as the outcome variable indicated that lagged
primary control striving did not predict within-person
change in positive affect (β = −.02, p = .35). Together, these
findings further indicated that positive affect predicted sub-
sequent primary control striving and that it did so more
strongly than primary control striving predicting subse-
quent positive affect.
A final set of analyses tested whether positive affect
would predict primary control striving for other goals. As a
first step (Table 5, Models 1), primary control striving for
occupational future and educational goals was regressed on
lagged primary control striving, positive affect, and nega-
tive affect. Lagged positive affect predicted primary con-
trol striving for occupational future (β = .08, p < .001) and
educational goals (β = .11, p < .001). As a second step,
apprenticeship-related control beliefs were added to test for
mediation (Table 5, Models 2). Sobel tests indicated that
the indirect paths in the postulated mediation model (i.e.,
mediation via control beliefs) were significant for associa-
tions between lagged positive affect and primary control
striving for occupational future (Sobel: z = 3.20, p = .005)
and educational goals (z = 3.20, p = .002). Lagged positive
affect continued to predict primary control striving for
occupational future and educational goals.
In most analyses, negative affect did not emerge as a sig-
nificant predictor. However, lagged negative affect predicted
the number of apprenticeship offers (see Table 4).
Discussion
The results of Study 2 replicated key findings of Study 1
and extended them in important ways. First, lagged posi-
tive affect—assessed with a dedicated measure—predicted
primary control striving for career and educational goals.
Unlike Study 1, Study 2 used a sample outside the United
States—increasing the external validity of the findings—
and a six-wave longitudinal design. Study 2 also allowed
us to test and partially replicate this finding in measures of
real-world primary control striving and success: applying
for and obtaining apprenticeships. The ability of positive
affect to predict success in obtaining an apprenticeship
suggests that it has implications beyond self-report mea-
sures of primary control striving.
As in Study 1, we examined the mediating role of control
beliefs. In Study 2, mediation was partial and present for pri-
mary control striving but not apprenticeship applications and
offers. This pattern of partial mediation suggests that mecha-
nisms other than enhanced control beliefs may explain why
positive affect enhances primary control striving. For exam-
ple, positive affect repairs self-regulatory resources (Baumei ster,
Vohs, & Tice, 2007; Tice et al., 2007), which in turn may
enhance primary control striving. Study 2 was conducted in a
context that depletes self-regulatory resources (Poulin &
Heckhausen, 2007): the search for an apprenticeship among
German Realschule students. In this context, feedback is eas-
ily available in the form of rejections or offers in response to
applications. However, this feedback is often negative, which
means that individuals must guard against feelings of hope-
lessness and failure. Accordingly, the associations of positive
affect with outcomes may go beyond perceptions of control
to include emotion regulation and coping efforts.3 In this
vein, it is notable that positive affect predicted both primary
Table 4. Study 2: Primary Control Striving for Apprenticeship, Apprenticeship Applications, and Apprenticeship Offers Regressed on
Lagged Predictors (N = 464)
Primary control striving
(apprenticeship)aApprenticeship applicationsaApprenticeship offersb
Lagged predictors Model 1 Model 2 Model 1 Model 2 Model 1 Model 2
Primary control striving
(apprenticeship)
.49*** .42*** — — — —
Apprenticeship
applications
.36*** .39***
Apprenticeship offers .07** .04
Positive affect .11*** .11*** .04.08** .19** .21*
Negative affect .02 .01 .01 −.03 .03* .08*
Control beliefs
(apprenticeship)
.09*** — −.02 .01
Note: aStandardized random-effects regression coefficients (βs).
bStandardized random-effects Poisson regression coefficients.
p < .10. *p < .05. **p < .01. ***p < .001.
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8 Personality and Social Psychology Bulletin XX(X)
control striving and more “objective” career outcomes, such
as numbers of applications or apprenticeship offers, but con-
trol beliefs appear to mediate this effect more for the former
than the latter.
Again, we obtained mostly nil results for effects of nega-
tive affect predicting primary control striving. However,
negative affect also predicted success in obtaining an
apprenticeship, extending previous findings (Nagy, Köller,
& Heckhausen, 2005).
General Discussion
Does happiness make people industrious or lazy? Building
on the motivational theory of lifespan development
(Heckhausen et al., 2010; Schulz & Heckhausen, 1998),
we found that positive affect predicts primary control
striving, that is, the motivation to invest time and effort
and overcome obstacles in the pursuit of important life
goals. In two longitudinal studies conducted in the United
States and Germany, respectively, we demonstrated that
positive affect predicted both self-report and objective
measures of primary control striving for career and educa-
tional goals. Moreover, control beliefs partially mediated
the longitudinal associations. We should note that the
effect sizes were consistent with our hypothesis but small.
Yet, small does not necessarily mean unimportant (see
Rosenthal, 1990).
Positive Affect Predicts Primary Control
Striving for Career and Educational Goals
Studies have repeatedly shown that primary control striv-
ing predicts many positive outcomes, both objective suc-
cess as well as subjective benefits including positive affect
(for a review, see Heckhausen et al., 2010). Few studies
have examined the reverse association, despite the fact that
primary control striving may itself rely on multiple
resources, including positive affect. Our findings support
the notion that the motivational functions of positive affect
are not limited to goal anticipation (e.g., Custers & Aarts,
2005) or feedback (e.g., Carver, 2003; Louro et al., 2007)
but extend to goal engagement (i.e., primary control striv-
ing). Specifically, our longitudinal studies showed that
positive affect predicted the pursuit of highly important
real-world goals related to career and education, and that
the predictive power of positive affect for primary control
striving was even stronger than the more commonly exam-
ined reverse pattern. We hasten to add, however, that our
results are not evidence that primary control striving does
not predict positive affect. Rather, the relationship between
positive affect and primary control striving may likely be bidi-
rectional—reminiscent of other positive bidirectional rela-
tionships (e.g., Fredrickson & Joiner, 2002) suggesting an
upward spiral of positive affect and primary control striv-
ing that could be further investigated in future studies (see
Vohs & Baumeister, 2008). Future research may also inves-
tigate whether these findings generalize to other specific
goal domains.
The findings further showed that control beliefs either
partially or wholly mediated many of the longitudinal asso-
ciations between positive affect and primary control striv-
ing. This suggests that one mechanism by which positive
affect enhances primary control striving for goals is that
positive affect may bias beliefs that these goals can be
attained. This mediating role of control beliefs is consistent
with propositions by the mood-as-information theory
(Schwarz, 2012; Schwarz & Clore, 1983) and the self-
efficacy theory (Bandura, 1997).
Our findings may provide a new perspective on resources
that reduce or enhance primary control striving toward val-
ued goals. Obstacles to goal pursuit such as stressful life cir-
cumstances (e.g., Poulin & Heckhausen, 2007) or health
impairments (e.g., Hall, Chipperfield, Heckhausen, & Perry,
2010) are characterized by deficits in positive affect. This
common feature may explain, in part, how these factors
inhibit primary control striving—a possibility that should be
addressed in future research. A role for positive affect in pro-
moting control striving also has implications for possible
interventions to bolster primary control striving. Techniques
to increase positive affect are increasingly effective (e.g.,
Cohn & Fredrickson, 2010) and may have fewer unintended
negative consequences than other interventions. For exam-
ple, directly increasing control beliefs might lead to increased
primary control striving but might lead to increased disillu-
sionment and disappointment if goal failure occurs. By con-
trast, increased positive affect predicts not merely increased
control striving but also greater ability to cope with setbacks
and other life stressors (Folkman & Moskowitz, 2000).
Meta-analytic findings show that “happiness leads to suc-
cess” (Lyubomirsky et al., 2005) in many life domains, includ-
ing work (Boehm & Lyubomirsky, 2008). Various pathways
may contribute to this effect (e.g., Folkman & Moskowitz,
2000; Fredrickson, 2001; Isen, 2001; King, Hicks, Krull, &
Table 5. Study 2: Primary Control Striving in Multiple Domains
Regressed on Lagged Predictors (N = 464)
Primary control striving
(occupational future)
Primary control
striving (education)
Lagged predictors Model 1 Model 2 Model 1 Model 2
Primary control
strivinga
.49*** .51*** .59*** .57***
Positive affect .08*** .07** .11*** .11***
Negative affect −.03 −.03 .02 .01
Control beliefs
(apprenticeship)
.09*** — .09**
Note: Standardized random-effects regression coefficients (βs).
aSame goal domain as the outcome variable.
**p < .01. ***p < .001.
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Haase et al. 9
Del Gaiso, 2006). Our findings indicate that the effect of posi-
tive affect on primary control striving may be another pathway
through which positive affect contributes to success, given
that primary control striving promotes success in the same
domains as those enhanced by positive affect (for a review, see
Heckhausen et al., 2010). Thus, the adaptiveness of positive
affect may extend beyond broadening and building thought
and action repertoires (Fredrickson, 2001), coping (Folkman
& Moskowitz, 2000), and decision making (Isen, 2001).
Positive affect may be fuel for persistent goal engagement.
However, it is important to note that persistence is not uni-
formly adaptive. Goals sometimes cannot be attained no mat-
ter how hard one tries (e.g., Heckhausen, Wrosch, & Fleeson,
2001; Wrosch, Scheier, Carver, & Schulz, 2003). Thus, posi-
tive affect may have a “dark side” (Gruber, Mauss, & Tamir,
2011) when it leads to escalating commitment and dysfunc-
tional persistence in situations where it would be more adap-
tive to let go of unattainable goals and move on.
Limitations and Implications
for Future Research
The present studies have limitations that have implications
for future research. First, we examined incidental affect with-
out reference to the source of that affect. It is likely that not
all positive affect is the same. In particular, positive affect
that stems from goal anticipation, progress, or attainment—
as opposed to incidental positive affect—may have very dif-
ferent effects on primary control striving. The control-process
model proposes that positive affect that stems from goal
progress leads to reductions in primary control striving with
regard to that goal (Carver, 2003; Carver & Scheier, 1998).
Future studies may thus compare effects of goal-related and
goal-unrelated positive affect.
Second, the present studies assessed positive affect rather
high in arousal (Watson et al., 1999). A growing body of
evidence indicates that low-arousal positive affect may have
quite different effects than high-arousal positive affect (for
an example study, see De Dreu, Baas, & Nijstad, 2008).
Thus, it is also possible that the primary control striving-
reducing effect of positive affect proposed by Carver and
colleagues (e.g., Carver, 2003) will be found for positive
affective states characterized by low arousal, such as feel-
ings of contentment. In a related vein, it is possible that
positive affect at a very high level ceases to motivate pri-
mary control striving, akin to what Oishi, Diener, and Lucas
(2007) observed for the association between life satisfaction
and numerous outcomes of success such as income. In a
follow-up analysis, we explored nonlinear (i.e., quadratic)
effects of positive affect on primary control striving and did
not find significant effects. Yet, future research may system-
atically compare the effects of positive affect varying in
arousal, frequency, and intensity.
Third, our assessments of positive affect referred to the
previous week or month and, thus, were possibly less
accurate than momentary assessments (Kahneman, Diener, &
Schwarz, 1999). Ideally, one would have measured momen-
tary positive affect repeatedly using an experience sampling
method (e.g., Stone, Shiffman, & DeVries, 1999) and used
the average of these repeated assessments to predict primary
control striving over time.
Fourth, we found that control beliefs mediated the effects
of positive affect on primary control striving. Mediation was
partial and not present for all outcomes. Clearly, other medi-
ating pathways merit further investigation including noncog-
nitive (e.g., repair of self-regulatory resources; Baumeister
et al., 2007; Tice et al., 2007) as well as other cognitive (e.g.,
future temporal focus; Foo et al., 2009) mediators.
Finally, although we assessed negative affect, it was only
examined for exploratory purposes and yielded mostly nil
results. Future research may examine how different negative
emotions predict primary control striving (Carver, 2004).
Conclusion
Does happiness function as a motivator? The present studies
show that positive affect predicts primary control striving
for career and educational goals and that control beliefs par-
tially mediate this effect. Thus, when individuals experience
positive affect, they become more motivated to invest time
and effort and overcome obstacles when pursuing their
goals, in part because they believe they have more control
over attaining their goals.
Acknowledgment
We would like to thank Chuansheng Chen, David Dooley, and
Ellen Greenberger (Study 1: Co-PIs); Olaf Köller (Study 2: Co-PI);
Carrie Carmody, Esther Chang, and Sue Farrugia (Study 1:
Research team); and Gabriel Nagy and Martin J. Tomasik (Study 2:
Research team).
Authors’ Note
Claudia M. Haase and Michael J. Poulin contributed equally to this
work.
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
work was supported by grants from the German Research
Foundation to Claudia M. Haase (Ha 4475/2-1) and Jutta
Heckhausen (He 3068/3-1).
Notes
1. Analyses were also conducted using two truncated measures of
positive affect (i.e., a two-item measure using the “happy” and
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10 Personality and Social Psychology Bulletin XX(X)
“enjoyed life” items, α = .76; a one-item measure using just the
“happy” item). Results were very similar to those using the
four-item measure of positive affect but with somewhat smaller
effect sizes for the association between positive affect and pri-
mary control striving (for the two-item measure, β = .10, p <
.05; for the one-item measure, β = .08, p < .05). As the results
were very similar and to facilitate comparison to prior literature,
we decided to focus on the four-item measure of positive affect.
2. Other time lags (e.g., t-2, t-3, t-4) were examined, but results
indicated that the predictive power of positive affect decreased
with greater lags. For example, positive affect predicted
apprenticeship control strivings more at lag t-2 (β = .08, p < .01)
than at lag t-4 (β = .05, p > .05); a similar pattern held for other
outcome variables.
3. The role of positive affect in emotion regulation might suggest
that positive affect should buffer the effects of negative affect
on primary control striving. However, follow-up analyses
showed that positive affect × negative affect had no interactive
effects on primary control striving in both studies (ps > .05).
Thus, instead of positive and negative affect interacting in their
effect on primary control striving, it seems plausible that posi-
tive affect facilitates primary control striving in part by prevent-
ing the occurrence of negative affect, for example, by
encouraging positive appraisals of disappointing experiences.
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This book presents a thorough overview of a model of human functioning based on the idea that behavior is goal-directed and regulated by feedback control processes. It describes feedback processes and their application to behavior, considers goals and the idea that goals are organized hierarchically, examines affect as deriving from a different kind of feedback process, and analyzes how success expectancies influence whether people keep trying to attain goals or disengage. Later sections consider a series of emerging themes, including dynamic systems as a model for shifting among goals, catastrophe theory as a model for persistence, and the question of whether behavior is controlled or instead 'emerges'. Three chapters consider the implications of these various ideas for understanding maladaptive behavior, and the closing chapter asks whether goals are a necessity of life. Throughout, theory is presented in the context of diverse issues that link the theory to other literatures.
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Psychologists, self-help gurus, and parents all work to make their clients, friends, and children happier. Recent research indicates that happiness is functional and generally leads to success. However, most people are already above neutral in happiness, which raises the question of whether higher levels of happiness facilitate more effective functioning than do lower levels. Our analyses of large survey data and longitudinal data show that people who experience the highest levels of happiness are the most successful in terms of close relationships and volunteer work, but that those who experience slightly lower levels of happiness are the most successful in terms of income, education, and political participation. Once people are moderately happy, the most effective level of happiness appears to depend on the specific outcomes used to define success, as well as the resources that are available. © 2007, Association for Psychological Science. All rights reserved.
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In this article, the author describes a new theoretical perspective on positive emotions and situates this new perspective within the emerging field of positive psychology. The broaden-and-build theory posits that experiences of positive emotions broaden people's momentary thought-action repertoires, which in turn serves to build their enduring personal resources, ranging from physical and intellectual resources to social and psychological resources. Preliminary empirical evidence supporting the broaden-and-build theory is reviewed, and open empirical questions that remain to be tested are identified. The theory and findings suggest that the capacity to experience positive emotions may be a fundamental human strength central to the study of human flourishing.
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It is argued that emotions are lawful phenomena and thus can be described in terms of a set of laws of emotion. These laws result from the operation of emotion mechanisms that are accessible to intentional control to only a limited extent. The law of situational meaning, the law of concern, the law of reality, the laws of change, habituation and comparative feeling, and the law of hedonic asymmetry are proposed to describe emotion elicitation; the law of conservation of emotional momentum formulates emotion persistence; the law of closure expresses the modularity of emotion; and the laws of care for consequence, of lightest load, and of greatest gain pertain to emotion regulation. (PsycINFO Database Record (c) 2012 APA, all rights reserved)