2012. Vol.3, No.4, 328-336
Published Online April 2012 in SciRes (
Copyright © 2012 SciRes.
Exercise Frequency, High Activation Positive Affect, and
Psychological Well-Being: Beyond Age, Gender, and Occupation
Danilo Garcia1*, Trevor Archer2, Saleh Moradi2, Ann-Christine Andersson-Arntén2
1Institute of Neuroscience and Physiology, Psychiatry and Neurochemistry, Forensic Psychiatry,
The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
2Department of Psychology, University of Gothenburg, Gothenburg, Sweden
Email: *
Received January 25th, 2012; revised February 17th, 2012; accepted March 21st, 2012
Regular physical exercise contributes to marked reductions in psychosocial stress, the enhancing of posi-
tive affect and well-being. However, affect can be measured as high (e.g., engaged) or low (e.g., content)
activation affect. To ascertain further these interactions, we examined the relationship between exercise
frequency (i.e., how often an individual engages in physical activities) and affect and Psychological
Well-Being (PWB). We investigate this relationship in the context of individuals’ gender, age, psycho-
somatic symptoms (i.e., headaches, pain in shoulders, neck or other parts of the body), sleeping problems,
smoking habits, and Body Mass Index (BMI). Moreover, we also investigate if the relationship between
exercise frequency and affect differs depending on the dimension of affect (low or high activation). In
Study 1 (N = 635), 2 (N = 311), and 3 (N = 135) high activation positive affect (PA) predicted frequently
exercising, while high activation negative affect (NA) predicted being less physically active. Moreover,
high activation PA was negatively related to smoking habits and to how often the participant had sleeping
problems. Finally, the relationship between frequently exercising and high activation affect was still pre-
sent when controlling for age, occupation and gender. Moreover, in Study 2, high activation PA remained
strongly related to exercise frequency even when we controlled for BMI. In Study 3, frequent physical ac-
tivity was also related to PWB. In Study 4, participants (N = 150) self-reported low activation affect. All
findings in regard to exercise frequency were replicated, with the exception of the relationship to affect.
Psychological resources (i.e., PWB), the frequent experience of PA, together with the infrequent experi-
ence of NA may provide for the facilitation of an exercise regime and healthy behavior. Thus, regular
physical exercise remains as a health-ensuring necessity over age, gender, and occupation. Nevertheless,
high activation positive affect should be in focus.
Keywords: Affect; BMI; Exercise; Health; Negative Affect; Positive Affect; Sleeping Problems; Smoking;
Psychosomatic Symptoms
Regular physical exercise has been described as a planned,
structured physical activity which fulfills the purpose of im-
proving one or more aspects of physical fitness and functional
capacity (Morris & Schoo, 2004), encompassing bodily active-
ties that enhance/maintain physical fitness, with frequent and
regular exercise boosting the immune system (Kurth, Moore,
Gaziano, Kase, Stampfer, Berger, & Buring, 2006). The regu-
larity of physical exercise is, for instance, associated to indi-
viduals who experience high positive affect (PA) and low nega-
tive affect (NA; Norlander, Bood, & Archer, 2002). In turn, fre-
quently exercising is associated with mental health, facilitating
the prevention of depression and anxiety, as well as the promo-
tion and maintenance of positive self-esteem in both adoles-
cents (Rees & Sabia, 2010; Rothon, Edwards, Bhui, Viner,
Taylor, & Stansfeld, 2010) and adults (Annesi, 2010; Arciero &
Ormsbee, 2009; Baldwin, 2010). In this regard, the links be-
tween exercise and affect seem to be modulated by individuals’
propensity to perform regular physical exercise (Sjögren, Nis-
sinen, Järvenpää, Ojanen, Vanharanta, & Mälkiä, 2006; Von
Thiele Schwarz, Lindfors, & Lundberg, 2008).
Indeed, the role of affective personality attributes has offered
insights pertaining to health and well-being among varying
populations, both healthy and clinical (Andersson-Arntén, Jans-
son, & Archer, 2008; Archer, Adolfsson, & Karlsson, 2008a;
Archer, Adrianson, Plancak, & Karlsson, 2008b; Garcia, 2011a,
2011b, 2012a, 2012b; Garcia & Archer, 2012; Garcia, Rosenberg,
Erlandsson, & Siddiqui, 2010; Garcia & Siddiqui, 2009a, 2009b;
Karlsson & Archer, 2007; Palomo, Beninger, Kostrzewa, &
Archer, 2008a, 2008b; Palomo, Kostrzewa, Beninger, & Archer,
2007; Zöller & Archer, 2009; Zöller, Karlsson, & Archer, 2009;
for a recent review see Garcia, Ghiabi, Moradi, Siddiqui, &
Archer, 2012). Several studies have indicated that NA is asso-
ciated with feelings such as anger, contempt, guilt, shame, fear,
anxiety, depressiveness, stress, distress and health complaints
whereas PA is linked to enthusiasm, activity, exercise, feelings
of duty and control (Watson & Clark, 1988; Watson, Penne-
baker, & Folger, 1986; Watson, Carey, & Carey, 1988a; Wat-
son & Clark, 1988; Watson, Clark, & Tellegen, 1988b).
Nevertheless, affect can be measured in different dimensions
(e.g., high or low activation). The type of dimension might have
implications regarding the well established relationship be-
tween exercise, affect, and well-being. For instance, Garcia and
Erlandssiuon (2011) demonstrated that different dimensions of
*Corresponding author.
affect predict different association between personality and
well-being. Moreover, in the field of Positive Psychology, re-
search on well-being complements measures of physical (e.g.
health) and material (e.g. income) well-being with assessments
of optimal experience by focusing on people’s full engagement
and optimal performance in existential challenges of life (i.e.,
Psychological Well-Being; PWB, Ryan, & Deci, 2001).
In the present set of studies we aim to investigate the rela-
tionship of frequent exercise habits to different dimensions of
affect (high and low activity) and health (physical and psycho-
logical). We investigate this relationship in the context of indi-
viduals’ gender, age, psychosomatic symptoms, sleeping prob-
lems, smoking habits, and Body Mass Index (BMI). Next we
will briefly present the well established relationship between
frequent exercise and health, the difference between high and
low activation affect, and the notion of psychological resources
(i.e., PWB).
Frequent Exercise and Health
The effect of frequent exercise on health may be illustrated
through reference to two domains: substance use and dietary
habits linked to overweight. Regular physical activity appears
to prevent eventual health-related habits and hazards. Norris
and colleagues (1992), for example, showed that regular exer-
cise and physical training induced beneficial effects against
psychological stress and increased well-being among partici-
pants. In another study (Delisle, Werch, Wong, Bian, & Weiler,
2010), among 822 adolescents attending a large, diverse subur-
ban school, adolescents who engaged in “vigorous physical
activity” expressed lower usage of marijuana, consumed more
healthy carbohydrates and fats, used stress management tech-
niques more frequently and reported a higher quality of sleep
than adolescents engaged in low “vigorous physical activity”
(i.e., those who where more-or-less sedentary). Moreover, Dish-
man and colleagues (2006) have indicated that that frequent
physical activity and sport participation reduced the risk for
depression among adolescent girls by positive influences on
physical self-concept that operate independently of fitness,
Body Mass Index (BMI), and perceptions of sports competence,
body fat, and appearance. That is, regular physical activity
brings beneficial outcomes including body weight status, as
well as self-perception attributes, whereas sedentary behavior
and failure to being regularly physical active brings unhealthy
Beyond Gender, Age, and Occupation
In two studies involving work-related stress and personal at-
tributes, Andersson-Arntén and colleagues (2008) showed that
NA was predicted by stress, anxiety and work stress; further
studies indicated that stress at work induced more anxiety, gen-
eral psychosomatic symptoms, NA, and depression (Anders-
son-Arntén, 2009). Interestingly, whereas work-stress was pre-
dictive for depression, anxiety, general stress and psychological
stress, sexual life satisfaction was counter predictive for all
these variables (Andersson-Arntén, 2009). Nevertheless, long
working hours, lifestyle and working environment factors are
the main predictors of workers’ health status (Hurrell &
Maclancy, 1988) and psychological vulnerability (Michelsen &
Bildt, 2003; Nishikitani, Nakao, Karita, & Tennant, 2001); this
situation is complicated by the pressures created by gender and
the specter raised by unemployment (Bildt & Michelsen, 2002,
2003). Moreover, Takada and colleagues (2009) examined the
links between lifestyle, working environment, depressive sym-
ptoms and suicide ideation in 4118 Japanese business employ-
ees (2834 male and 1284 female). They found that the factors
associated with depressive symptoms over both genders were:
high levels of job stress, drinking problems, insufficient sleep,
lack of social support, and absence of stress reduction tech-
niques such as physical exercise.
Indeed, a wide range of self-report studies have shown that
regular physical exercise reduces stress symptoms, mood dis-
order, anxiety and depressiveness (see also Broman-Fulks &
Storey, 2008; Janisse, Nedd, Escamille, & Nies, 2004; Smith,
Blumentha, Babyak, Georgiades, Hinderliter, & Sherwood,
2007; Tsang, Chan, & Cheug, 2008; Wang, Bannuru, Ramel,
Kupelnick, Scott, & Schmid, 2010). Experimental approaches
point in the same direction. Barnes and colleagues (2010) in-
vestigated pre- and post-exercise attentional bias that may
modulate reported reductions in negative affect and anxiety.
Over consecutive laboratory visits, 30 high trait anxious par-
ticipants completed 30 min of exercise on a cycle ergometer at
70% of their heart rate reserve, or completed a 30-min quiet rest
protocol. During each intervention, pre-test and post-test modi-
fied dot-probe assessments of attentional bias were completed,
as were a series of self-report anxiety and affect questionnaires.
They observed that PA and reaction time improved markedly
after exercise thereby implying that exercise facilitates atten-
tional scope.
High and Low Activation Affect
Although most would agree in viewing positive and negative
experiences as opposite ends of a continuum, there is much
evidence that they are best construed as two separate systems
(for a review see MacLeod & Moore, 2000). In the context of
health, this is important because the two systems are also
measures of anxiety and depression—anxiety is a state of high
NA whereas depression is a mixed state of high NA and low
PA (Clark & Watson, 1991). Moreover, the two systems are
almost synonymous with different constructs of personality
traits. For instance, extrovert behavior is positively related to
high levels of PA and being more reactive to positive stimuli
whereas neurotic behavior is positively related to high levels of
NA and more reactive to negative stimuli (Larsen & Ketelaar,
Watson and Tellegen (1985) have actually presented these as
two independent dimensions: high versus low PA and high
versus low NA. One of the most used instruments to measure
affect is the Positive Affect and Negative Affect Schedule
(PANAS by Watson et al., 1988). Rusell and Carroll (1999)
point out that the PANAS scales are predominated by high
activation items: while some PANAS items (e.g., “interested”)
may not be common in other scales, other items (e.g., “happy”)
are not included in the PANAS. Indeed, findings suggest that
PANAS items reflect engagement with a stimulus (for a review
see Schimmack, 2007).
Hence, the PANAS mainly measures high activation affect
while other scales (e.g., the Emotional Well-Being Scale by
Diener & Biswas-Diener, 2008) assess low activation affects.
This can be seen in light of the circumplex model first pre-
sented by Russell (1980). According to this model the affects
included in the PANAS are all located in the northwest and
Copyright © 2012 SciRes. 329
Copyright © 2012 SciRes.
northeast segments of the circumplex. In other words, they
measure only highly activated PA and NA. This model has two
important implications that may be assumed of importance for
this study. Firstly, that some emotions are similar to each other
yet measurably different than other emotions. Secondly, that the
majority of emotional experience can be captured by two di-
mensions. (Larsen & Diener, 1992).
Psychological Well-Being
Ryff (1989) has proposed six constructs as defining positive
psychological functioning: 1) positive relations with others; 2)
environmental mastery; 3) self-acceptance; 4) autonomy; 5)
personal growth; and 6) purpose in life (see Table 1 for a defi-
nition of each construct). The six constructs define PWB both
theoretically and operationally, and they probably identify what
promotes effective adaptation to life events and emotional and
physical health (Ryff & Singer, 1998). The PWB constructs not
only promote well-being but also are a measure of well-being.
For example, analogous to hunger, autonomy is considered as a
need in human nature that has to be satisfied in order to pre-
serve or increase well-being and adaptive behavior (Deci &
Flaste, 1996).
Comparing PWB between young (aged 18 - 29 years), mid-
life (30 - 64 years), and old (65 years or more) adults, Ryff
found that certain aspects of PWB increased or decreased with
age, while others did not change at all. Environmental mastery
and autonomy increased with age (especially between young to
midlife), purpose in life and personal growth decreased (espe-
cially between midlife to old), and no differences were found in
self-acceptance and positive relations with others.
Recent research has linked PA as a predictor of Psychologi-
cal Well-Being. Urry and colleagues (2004), for example, in-
vestigated whether engaging with goal-directed stimuli contrib-
uted to well-being by exploring correlations between individual
differences in baseline prefrontal activation and PWB. The
results validated the hypothesis and affect, especially high acti-
vation PA (e.g., “interested,” “strong”), emerged as an impor-
tant factor in the prediction of PWB (see also Garcia, 2011c,
2012b; Garcia & Archer, 2012; Garcia & Siddiqui, 2009b).
In this context, it is important to bear in mind that positive
emotions may also broaden people’s mindsets and build endur-
ing personal psychological resources (Fredrickson, 2006). For
instance, participants in a positive-emotion condition listed
significantly more things they would like to do than participants
in a negative-emotion condition (Fredrickson & Branigan,
2005). The effect of broadened thinking may increase the odds
of discovering positive meaning in life events (Fredrickson,
2006). In addition, Tugade and Fredrickson (2004) found that a
person who reports high activated PA before doing a time-
pressured speech preparation experiences, alongside high anxi-
ety feelings, higher levels of happiness and interest. Neverthe-
less, both PA and NA might be adaptive, depending on the
social context. From an evolutionary perspective, it is reason-
able to assume that negative emotions have grown part of the
toolbox of most organic beings. After all, negative emotions
probably increase the chances of survival in life-threatening
situations because they bring attention to threatening stimuli
and facilitate rapid action (Dijksterhuis & Aarts, 2003). Thus,
affectivity may play a role, not only as a measure of well-being,
but also as contributor in the promotion of PWB.
The Present Set of Studies
The health-promoting effects of physical exercise for health
and healthy behavior are well documented. It can be observed
that high BMI is associated positively with sedentary condi-
tions whereas lower scores of physical activity are associated
with high NA. Nonetheless, the positive influences of fre-
quently exercising might go beyond demographical variables
such a gender, age, occupation and even BMI. Personal attrib-
utes involving affectivity may uncover relationships that either
promote or hinder an individual’s propensity for physical exer-
Nonetheless, we suggest that the dimension of affect (high or
low activation) needs to be taken into consideration. Further-
more, the relationship between frequent exercise and PWB
should complement and expand the effects of frequent exercise
on health. We expected frequently exercising being positively
predicted by high activation PA and counter-predicted by high
activation NA. Moreover, this relationship was expected to
remain significant while controlling for gender, age, occupation,
and BMI. Both PA and exercise frequency was expected to be
negatively related to psychosomatic symptoms, sleeping prob-
lems, and smoking. Finally, frequent exercise was also ex-
pected to be positively related to PWB.
Study 1: High Activation Affect
Participants and Procedure
A total of 635 participants (370 females and 265 males) with
an age mean of 18.53 (SD = 5.01) from the different settings
(lower school, high school, university, white collar and blue
collar workers at corporate enterprises, government employees,
and state-owned and health establishments) were guaranteed
Table 1.
The six constructs of psychological well-being.
PWB Construct Definition
Self-acceptance Emphasis on acceptance of self and of one’s past life.
Positive relations with others Symbolizing having strong feelings of empathy and affection for all human beings and as being capable
of greater love, deeper friendship, and more complete identification with others and warm relating to others.
Autonomy Expressions of internal locus of evaluation, thus not looking to others for approval but evaluating oneself
by personal standards.
Environmental mastery The individual’s ability to choose or create environments suitable to his or her psychic conditions.
Purpose in life Having goals, intentions, and a sense of direction, all of which contribute to the feeling that life is meaningful.
Personal growth Emphasis to continued growth and the confronting of new challenges or tasks at different periods of life.
complete anonymity and assured that their collaboration was on
a voluntary basis. First, the participants completed the back-
ground and health questionnaire that provided information re-
garding age, gender, education, etc, but particularly propensity
for regular physical exercise. Second, they completed the in-
strument that measures affect.
Background and Health questionnaire (Karlsson & Archer,
2007). This instrument was applied to collect background data
providing health and health-related information about each
participant. The questionnaire consists of items pertaining to
age, gender and education, occupation, as well as propensity to
perform regular physical exercise, smoking habits, and sleeping
The Positive Affect and Negative Affect Schedule (PANAS;
Watson et al., 1988). The PANAS was used to measure high
activation affect. Participants are instructed to rate to what ex-
tent they generally have experienced 20 different feelings or
emotions (10 PA and 10 NA) for the last weeks, using a 5-point
Likert scale (1 = very slightly, 5 = extremely). The Swedish
version of the PANAS used in the present study has been used
in many other studies (e.g., Archer et al., 2008b; Garcia & Mo-
radi, 2011; Palomo et al., 2007). The 10-item PA scale includes
adjectives such as strong, proud, and interested (Cronbachs α
= .80). The 10-item NA scale includes adjectives such as afraid,
ashamed, and nervous (Cronbachs α = .75).
Results and Discussion
A Correlation analysis was conducted in order to establish
the relationship among the variables in the study. As Table 2
shows, affect was significantly related to smoking, sleeping
problems, and exercise frequency. Specifically, PA was nega-
tively related to the number of cigarettes a participant smoked
on a weekly basis and to how often the participant had prob-
lems falling asleep. In contrast, PA was positively related to
exercise frequency. For NA the relationships were inversed.
A partial correlation analysis was conducted in order to in-
vestigate if the relationship between affect and exercise fre-
quency remained significant beyond demographical variables.
We controlled this relationship for gender, age, and occupation.
As shown in Table 3, affect was strongly related to exercise
frequency in the same manner as depicted above.
A Multiple Regression Analysis (MRA) was conducted in
order to investigate the relationship between affect and exercise
frequency further. Affect was used as the independent variable
and exercise frequency was used as the dependent variable in
the equation. Besides affect, gender and age was used as pre-
dictor of frequently exercising. Both PA and NA predicted how
Table 2.
Correlations among variables in Study 1 (N = 635).
1 2 3 4 5 6 7
1) Positive affect -
2) Negative affect –.08 -
3) Age .05 –.02 -
4) Smoking –.15*.09 –.08 -
5) Psychosomatic
symptoms .04 .03 .04 .29*** -
6) Sleeping problems –.43*** .43*** –.01 .09 –.04 -
7) Exercise frequency.44***–.18*** .01 –.02 .01 –.39*** -
Note: *p < .05; ***p < .001.
Table 3.
Partial correlations between exercise frequency and affect controlling
for gender, age, and occupation (N = 635).
1 2 3
1) Exercise Frequency -
2) Positive Affect .44*** -
3) Negative Affect –.23*** –.089 -
Note: ***p < .001.
often participants reported they were physical active (see Table
As expected, frequently exercising is related to high activa-
tion affect beyond demographical variables such as gender, age,
and occupation. The next study aims to replicate the results
presented here and investigate if the high activation affectiv-
ity-frequent exercise relationship is independent of BMI as well.
Study 2 was conducted among adolescents due to the close
relation between BMI, self-image, and self-esteem during this
period of life.
Study 2: High Activation Affect and BMI
Participants and Procedure
A total of 311 participants (183 boys and 128 girls) were as-
signed to study 2. This sample included lower school pupils (n
= 84, aged 13 - 15 years), high school pupils (n = 133, aged 16 -
18 years), and university students(n = 94, aged 19 - 29 years).
All residents in Kungsbacka, Sweden. As in Study 1, partici-
pants were guaranteed complete anonymity and assured that
their collaboration was on a voluntary basis. First, the partici-
pants completed the background and health questionnaire. In
the background questionnaire we included the measures to cal-
culate BMI. The PANAS was distributed last.
Table 4.
Results of the MRA using gender, age, PA and NA as predictors of exercise frequency (N = 635).
Predictor Variable Outcome Variable Adj R² Unst. B Unst. SE Stand. β F t p
Gender (G) - .27 .11 .10 - 2.46 <.05
Age (A) - –.01 .01 –.01 - –.22 .82
Positive Affect (PA) - .69 .07 .42 - 10.28 <.001
Negative Affect (NA) - –.35 .07 –.20 - –4.71 <.001
G, A, PA, NA
Exercise frequency
.23 - - - 35.07 - <.001
Copyright © 2012 SciRes. 331
Background and Health questionnaire (Karlsson & Archer,
2007). We used the same questionnaire from Study 1 consisting
of items pertaining to age, gender and education, as well as
propensity to perform regular physical exercise, and sleeping
Body Mass Index (BMI). The body mass index, or Quetelet
index, is a heuristic measure of body weight based on a per-
son’s weight and height. Although BMI does not actually
measure the percentage of body fat, it is used to estimate a
healthy body weight based on a person’s height, and with the
assumption of an average body composition. Body mass index
is defined as the individual’s body weight divided by the square
of his or her height. Participants were simply asked to report
their weight and height.
The Positive Affect and Negative Affect Schedule (PANAS;
Watson et al., 1988). The PANAS was again used to measure
high activation affect. Reliability was good for both PA (Cron-
bachs α = .79) and NA (Cronbachs α = .82).
Results and Discussion
High activation affect was again significantly related to
sleeping problems, and exercise frequency (see Table 5). As in
Study 1, while NA was positively related to how often adoles-
cents had problems falling asleep, PA was negatively related.
However, only PA was positively related to frequent physical
activity. On the other hand, NA was positively related to psy-
chosomatic symptoms and sleeping problems. It is word to
notice that BMI was negatively related to exercise frequency.
That is, adolescents who often engage in physical activities had
lower BMI.
We controlled the high activation affect-exercise frequency
relationship for gender, age, and BMI. As shown in Table 6,
PA was still positively correlated to exercise frequency in the
same manner as depicted above.
Table 5.
Correlations among variables in Study 2 (N = 311).
1 2 3 4 5 6 7
1) Positive affect -
2) Negative affect –.10 -
3) Age –.05 –.08-
4) Psychosomatic
symptoms –.08 .27*** .02 -
5) Sleeping problems –.26*** .25*** .07 .31*** -
6) Exercise frequency .24*** –.08–.01 –.02 –.12*-
7) BMI .01 –.01.18* .07 .10 –.16*-
Note: *p < .05; ***p < .001.
Table 6.
Partial correlations between exercise frequency and affect controlling
for gender, age, and BMI (N = 311).
1 2 3
1) Exercise frequency -
2) Positive affect .27*** -
3) Negative affect –.07 –.08 -
Note: ***p < .001.
As expected, the high activation affect-frequent exercise re-
lationship is independent of BMI as well as gender and age.
Hence, the positive effect of frequently exercising goes beyond
such demographic variables. In Study 3 we aim to replicate the
results presented to this point and also to expand the investiga-
tion in regard to the positive effect of frequent exercise and
health by measuring PWB among adolescents.
Study 3: High Activation Affect and PWB
Participants and Procedure
Participants were pupils at two high schools in the county of
Blekinge, Sweden. The total of the participants was 135 (70
boys and 65 girls) with an age mean of 17.00 years (SD = .88).
All participants were guaranteed complete anonymity and as-
sured that their collaboration was on a voluntary basis. All
completed the background and health questionnaire (same as in
Study 1 and 2), the PANAS, and the PWB measure.
Background and Health questionnaire (Karlsson & Archer,
2007). We used the same questionnaire from Study 1 and 2
consisting of items pertaining to age, gender and education, as
well as propensity to perform regular physical exercise, and
sleeping problems.
The Positive Affect and Negative Affect Schedule (PANAS;
Watson et al., 1988). The PANAS was again used to measure
high activation affect. Reliability was good for both PA (Cron-
bachs α = .84) and NA (Cronbachs α = .82).
Ryffs Short Measurement of Psychological Well-Being
(Clarke, Marshall, Ryff, & Wheaton, 2001). PWB was opera-
tionalized with Ryff’s own short version (18 items, 3 for each
construct). The six constructs are: 1) autonomy (e.g., “I have
confidence in my own opinions, even if they are contrary to the
general consensus”); 2) environmental mastery (e.g., “ I am
quite good at managing the responsibilities of my daily life”); 3)
self-acceptance (e.g., “I like most aspects of my personality”); 4)
purpose in life (“Some people wander aimlessly through life,
but I am not one of them”); 5) personal growth (e.g., “For me,
life has been a continuous process of learning, changing, and
growth”) and 6) positive relations with others (e.g., “People
would describe me as a giving person, willing to share my time
with others”).
The Swedish version has been used in previously published
studies (e.g., Garcia, 2011c; Garcia, 2012b; Garcia & Siddiqui,
2009b). For this study we simply summarized all the 18 items
to form a PWB score (Cronbachs α = .78).
Results and Discussion
Affect was again significantly related to psychosomatic
symptoms, sleeping problems, and exercise frequency. More-
over, PA was positively related to PWB. NA, in contrast, was
negatively related to PWB. PWB was also positively related to
frequent exercise and negatively related to psychosomatic
symptoms and sleeping problems. In other words, the more
adolescents scored in the six PWB constructs, the more they
reported exercising in a frequent basis and the less they re-
ported pain in shoulders, head and having sleeping problems
(see Table 7).
A MRA was conducted in order to investigate the relation-
Copyright © 2012 SciRes.
ship between PWB and exercise frequency further. All six
PWB constructs were used as the independent variables and
exercise frequency was used as the dependent variable in the
equation. Although the whole PWB scale was related to fre-
quently exercising, only the construct of self-acceptance was a
significant predictor of routinely engaging in physical activities
(see Table 8). This specific finding is in concordance with the
finding from Study 2 in regard to BMI. It is tentatively to sug-
gest that as long as there is acceptance of the self, the adoles-
cent is able to perform healthy behaviors.
The last study was conducted among adults in order to repli-
cate the findings in regard to PWB and to investigate if frequent
exercise is related to low activation affect.
Study 4: Low Activation Affectivity and PWB
Participants and Procedure
A total of 150 white collar workers (90 females and 60 males)
with an age mean of 43.07 (SD = 12.68) were asked to com-
plete the background and health questionnaire, the affect meas-
ure, and the PWB measure. Participants were guaranteed com-
plete anonymity and assured that their collaboration was on a
voluntary basis.
Background and Health questionnaire (Karlsson & Archer,
2007). We used the same questionnaire from Study 1-3.
Emotional Well-Being Scale (EWS; Diener & Biswas-Diener,
2008). The EWS was used in order to measure low activation
affect. The EWS consist of 16 items, eight of which measure
PA (e.g., pleasant, contented) and the other eight measure NA
(e.g., unpleasant, sad). The EWS went through the formal
process of translation and backtranslation. Although this is the
first time the EWS is used in a Swedish sample, the EWS
showed proper reliability for both PA (Cronbachs α = .83) and
NA (Cronbachs α = .84).
Ryffs Short Measurement of Psychological Well-Being (Clarke
et al., 2001). Ryff’s own short version was again used to meas-
ure PWB. Again, we simply summarized all the 18 items to
form a PWB score (Cronbachs α = .75).
Results and Discussion
In contrast to Study 1-3, affect was not significantly related
to frequently exercising. However, as in Study 1-3, affect was
related to sleeping problems and psychosomatic symptoms.
Specifically, PA was related to less pain and sleeping problem,
NA was related to more pain and regularly experiencing sleep-
ing problems. It is important to point out that, equal to findings
in Study 3, PWB was still related to both affect and exercise
frequency. In other words, while PWB might be promoted by
both affect dimensions, only approach related or high activation
affect (e.g., engaged, interested), rather than low activation af-
fect (e.g., contented, pleasant), might promote frequently exer-
cising (see Table 9).
General Discussion
Taken together, the results from the four studies indicate that
high activation affect and PWB predict the propensity to regu-
larly physical activity. More specifically, high activation PA
and PWB predicted frequent engagement in regular exercise
habits. Frequent exercise, frequent experiencing PA, and psy-
chological resources such self-acceptance predict less smoking,
less sleeping, and less psychosomatic symptoms.
Moreover, the positive relationship of the variables in this
triad (i.e., high activation PA, frequent exercise, and PWB)
goes beyond demographic variables such as gender, age, and
occupation. At least among adolescents this is true despite even
BMI. Perhaps because self-acceptant behavior leads to ap-
proach related affect. Nevertheless, we suggest that the results
of these four studies should be seen as a circle of exer-
cise-approach behavior (see Figure 1). That is, while it is true
that experiencing engagement and enthusiasm, for example,
might broaden people’s mindsets and build enduring personal
psychological resources (Fredrickson, 2006), such as personal
growth, the opposite might be true as well: frequent exercise
might lead to concepts of the self that emphasise continued
growth and the confronting of new challenges, such self-con-
cept, in turn, leading to both high (e.g., proud) and low active-
Table 7.
Correlations among variables in Study 3 (N = 135).
1 2 3 4 5 6 7
(1) Positive affect -
(2) Negative affect –.05-
(3) Age .13 –.01 -
(4) Psychosomatic
symptoms –.15 .27** .06 -
(5) Sleeping
problems –.23** .38*** .02 .44*** -
(6) Exercise frequency .27** –.05 .06 –.10 –.23** -
(7) PWB .51*** –.44*** .11 –.18* –.28***.25** -
Note: *p < .05; **p < .01; ***p < .001.
Table 8.
Results of the MRA using all six PWB constructs as predictors of exercise frequency (N = 135).
Predictor Variable Outcome Variable Adj R² Unst. B Unst. SE Stand. β F t p
Self-Acceptance - .06 .03 .24 - 2.02 <.05
Positive relations with others - .03 .03 .09 - .87 .39
Autonomy - .03 .03 .07 - –.83 .41
Environmental Mastery - –.01 .03 –.01 - –.09 .93
Purpose in life - .04 .03 .13 - 1.39 .17
Personal growth - –.05 .03 –.15 - –1.60 .11
Exercise frequency
.11 - - - 2.53 - <.05
Copyright © 2012 SciRes. 333
Table 9.
Correlations among variables in Study 4 (N = 150).
1 2 3 4 5 6 7 8
(1) Positive affect -
(2) Negative affect –.49*** -
(3) Age –.02 .04 -
(4) Smoking .03 –.14 .20* -
(5) Psychosomatic
symptoms –.23* .30*** –.13 –.01 -
(6) Sleeping
problems –.25** .44*** .03 –.06 .23* -
(7) Exercise
frequency .08 –.11 –.17 –.27** –.06 –.02-
(8) PWB .51*** –.50*** –.15 –.10 –.11 –.19.22*-
Note: *p < .05; **p < .01; ***p < .001.
High Activation
Frequent Physical
Figure 1.
The circle of exercise-approach behaviour.
tion PA (e.g., contentedness). Our suggestions can be seen in
light of recent research that suggest that, among adolescent girls,
intention and perceived behavioral control predicted changes in
physical activity and physical activity predicted changes in
intention, affective attitude, and perceived behavioral control
(Raudsepp et al., 2010). We suggest that the promotion of self-
acceptance and high activated PA might be necessary in order
to create frequent exercise habits.
Being entirely honest with oneself is a good exercise
Sigmund Freud.
We would like to direct our gratitude to The Swedish Na-
tional Centre for Research in Sports (CIF) for supporting this
project (Grant nr. P2012-0097). We would also like to thank
Anders Welin, Nariman Hakiminejad, Patricia Rosenberg, and
Erik Lindskär for their assistance with the data. All authors are
indebted to the participants for their help in facilitating the
study and to the reviewers who helped improve the original
Andersson-Arntén, A. C. (2009). Partnership relation quality modu-
lates the effects of work-stress on health. Doctoral Dissertation, Go-
thenburg: Department of Psychology, University of Gothenburg.
Andersson-Arntén, A. C., Jansson, B., & Archer, T. (2008). Influence
of affective personality type and gender upon coping behavior, mood
and stress. Individual Differences Research, 6, 139-168.
Annesi, J. J. (2010). Relations of changes in self-regulatory efficacy
and physical self-concept with improvements in body satisfaction in
obese women initiating exercise with cognitive-behavioral support.
Body Image, 7, 356-359. doi:10.1016/j.bodyim.2010.05.001
Archer, T., Adolfsson, B., & Karlsson, E. (2008). Affective personality
as cognitive-emotional presymptom profiles regulatory for self-re-
ported health predispositions. Neurotox icity Research, 14, 1-25.
Archer, T., Adrianson, L., Plancak, A., & Karlsson, E. (2007). Influ-
ence of affective personality on cognition-mediated emotional proc-
essing: need for empowerment. European Journal of Psychiatry, 21,
248-262. doi:10.4321/S0213-61632007000400002
Arciero, P. J., & Ormsbee, M. J. (2009). Relationship of blood pressure,
behavioral mood state, and physical activity following caffeine in-
gestion in younger and older women. Applied Physiology, Nutrition
and Metabolism, 34, 754-762. doi:10.1139/H09-068
Baldwin, R. C. (2010). Preventing late-life depression: A clinical up-
date. International Psychogeriatrics, 1, 1-9.
Barnes, R. T., Coombes, S. A., Armstrong, N. B., Higgins, T. J., &
Janelle, C. M. (2010). Evaluating attentional and affective changes
following an acute exercise bout using a modified dot-probe protocol.
Journal of Sports Sciences, 28, 1065-1076.
Bildt, C., & Michélsen, H. (2002). Gender differences in the effects
from working conditions on mental health: A 4-year follow-up. In-
ternational Archives of Occupational and Environmental Health, 75,
Bildt, C., & Michélsen, H. (2003). Occupational conditions exceed the
importance of non-occupational conditions and ill health in explain-
ing future unemployment among women and men. Archives of
Women’s Mental Health, 6, 115-126.
Broman-Fulks, J. J., & Storey, K. M. (2008). Evaluation of a brief
aerobic exercise intervention for high anxiety sensitivity. Anxiety,
Stress and Coping, 21, 117-128. doi:10.1080/10615800701762675
Clarke, P. J., Marshall, V. M., Ryff, C. D., & Wheaton, B. (2001).
Measuring psychological well-being in the Canadian study of health
and aging. International Psyc hog eri atrics, 13, 79-90.
Clark, C. L., & Watson, D. (1991). Tripartite model of anxiety and
depression: Psychometric evidence and taxonomic implications.
Journal of Abnormal Psychology, 100, 316-336.
Deci, E. L., & Flaste, R. (1996). Why we do what we do: Understand-
ing self-motivation. London: Penguin Books.
Delisle, T. T., Werch, C. E., Wong, A. H., Bian, H., & Weiler, R.
(2010). Relationship between frequency and intensity of physical ac-
tivity and health behaviors of adolescents. Journal of School Health,
80, 134-140. doi:10.1111/j.1746-1561.2009.00477.x
Diener, E., & Biswas-Diener, R. (2008). Happiness: Unlocking the my-
steries of psycholo gical wealth. Malden, MA: Blackwell Publishing.
Dishman, R. K., Hales, D. P., Pfeiffer, K. A., Felton, G. A., Saunders,
R., Ward, D. S., Dowda, M., & Pate, R. R. (2006). Physical self-
concept and self-esteem mediate cross-sectional relations of physical
activity and sport participation with depression symptoms among
adolescent girls. Health Psychology, 25, 396-407.
Dijksterhuis, A., & Aarts, H. (2003). On wildebeests and humans: The
preferential detection of negative stimuli. Psychological Science, 14,
14-18. doi:10.1111/1467-9280.t01-1-01412
Fredrickson, B. L. (2006). The broaden-and-build theory of positive
emotions. In M. Csikszentmihalyi, & I. S. Csikszentmihalyi (Eds), A
life worth living: Contributions to positive psychology (pp. 85-103).
New York: Oxford University Press.
Fredrickson, B. L., & Branigan, C. (2005). Positive emotions broaden
Copyright © 2012 SciRes.
the scope of attention and thought-action repertoires. Cognition and
Emotion, 19, 313-332. doi:10.1080/02699930441000238
Garcia, D. (2011a). Adolescents happiness: The role of the affective
temperament model on memory and apprehension of events, subjec-
tive well-being, and psychological well-being. Doctoral Dissertation,
Gothenburg: Department of Psychology, University of Gothenburg.
Garcia, D. (2011b). The affective temperaments: Differences between
adolescents in the big five model and cloninger’s psychobiological
model of personality. Journal of Happiness Studies.
Garcia, D. (2011c). Two models of personality and well-being among
adolescents. Perso nality and Individual Differences, 50, 1208-1212.
Garcia, D. (2012a). Interpretation and recognition for words in a short
story (IRWSS) [Database record]. American Psychological Associa-
tion’s PsycTESTS™.
Garcia, D. (2012b). The affective temperaments and self-acceptance:
adolescents’ life satisfaction and psychological well-being. In M.
Vassar (Ed.), The psychology of life satisfaction. New York: Nova
Science Publishers.
Garcia, D., & Archer, T. (2012). Adolescent life satisfaction and
well-being. Journal of Alternative Medic i ne Research. In press.
Garcia, D., & Erlandsson, A. (2011). The relationship between person-
ality and subjective well-being: Different association patterns when
measuring the affective component in frequency and intensity. Jour-
nal of Happiness Studies, 12, 1023-1034.
Garcia, D., Ghiabi, B., Moradi, S., Siddiqui, A., & Archer, T. (2012).
The happy personality: A tale of two philosophies. In N. G.-C. Vas-
sar (Ed.), Psychology of personality. New York: Nova Science Pub-
Garcia, D., & Moradi, S. (2011). Adolescents’ temperament and char-
acter: A longitudinal study on happiness. Journal of Happiness Stud-
ies. doi:10.1007/s10902-011-9303-5
Garcia, D., Rosenberg, P., Erlandsson, A., & Siddiqui, A. (2010). On
lions and adolescents: Affective temperaments and the influence of
negative stimuli on memory. Journal of Happiness Studies, 11,
477-495. doi:10.1007/s10902-009-9153-6
Garcia, D., & Siddiqui, A. (2009a). Adolescents’ affective tempera-
ments: Life satisfaction, interpretation and memory of events. The
Journal of Positive Psycholog y , 4, 155-167.
Garcia, D., & Siddiqui, A. (2009b). Adolescents’ psychological well-
being and memory for life events: Influences on life satisfaction with
respect to temperamental dispositions. Journal of Happiness Studies,
10, 387-503. doi:10.1007/s10902-008-9096-3
Hurrell, J. J., & Maclancy, M. A. (1988). Exposure to job stress: A new
psychometric instrument. Scandinavian Journal of Work, Environ-
ment and Health, 14, 27-28.
Janisse, H. C., Nedd, D., Escamille, S., & Nies, M. A. (2004). Physical
activity, social support, and family structure as determinants of mood
among European-American and African-American women. Women’s
Health, 39, 101-116. doi:10.1300/J013v39n01_06
Karlsson, E., & Archer, T. (2007). Relationship between personality
characteristics and affect: Gender and affective personality. Individ-
ual Differences Research, 5, 44-58.
Kurth, T., Moore, S. C., Gaziano, J. M., Kase, C. S., Stampfer, M. J.,
Berger, K., & Buring, J. E. (2006). Healthy lifestyle and the risk of
stroke in women. Archives of Internal Medicine, 166, 1403-1409.
Larsen, R. J., & Diener, E. (1992). Promises and problems with the
circumplex model of emotion. In M. S. Clark (Ed.), Emotion: Review
of personality and social psychology (pp. 25-59). Newbury Park, CA:
Larsen, R. J., & Ketelaar, T. (1991). Personality and susceptibility to
positive and negative emotional states. Journal of Personality and
Social Psychology, 61, 132-140. doi:10.1037/0022-3514.61.1.132
MacLeod, A., & Moore, R. (2000). Positive thinking revised: Positive
cognitions, well-being and mental health. Clinical Psychology and
Psychotherapy, 7, 1-10.
Michelsen, H., & Bildt, C. (2003). Psychosocial conditions on and off
the job and psychological illhealth: Depressive symptoms, impaired
psychological wellbeing, heavy consumption of alcohol. Occupa-
tional Environmental Medicine, 60, 489-496.
Morris, M., & Schoo, A. (2004). Optimizing exercise and physical
activity in older adu lts. Edinburgh: Butterworth Heinemann.
Nishikitani, M., Nakao, M., Karita, K., Nomura, K., & Yano, E. (2005).
Influence of overtime work, sleep duration, and perceived job char-
acteristics on the physical and mental status of software engineers.
Industrial Health, 43, 623-629. doi:10.2486/indhealth.43.623
Norlander, T., Bood, S. Å., & Archer, T. (2002). Performance during
stress: Affective personality, age and regularity of physical exercise.
Social Behavior and Personality, 30, 495-508.
Norris, R., Carroll, D., & Cochrane, R. (1992). The effects of physical
activity and exercise training on psychological stress and well-being
in an adolescent population. Journal of Psychosomatic Research, 36,
55-65. doi:10.1016/0022-3999(92)90114-H
Palomo, T., Beninger, R. J., Kostrzewa, R. M., & Archer, T. (2008a).
Focusing on symptoms rather than diagnoses in brain dysfunction:
Conscious and nonconscious expression in impulsiveness and deci-
sion-making. Neur ot ox ic ity Research, 14, 1-20.
Palomo, T., Beninger, R. J., Kostrzewa, R. M., & Archer, T. (2008b).
Affective status in relation to impulsiveness, motor and motivational
symptoms: Personality, development and physical exercise. Neuro-
toxicity Research, 14, 151-168. doi:10.1007/BF03033807
Palomo, T., Kostrzewa, R. M., Beninger, R. J., & Archer, T. (2007).
Treatment consideration and manifest complexity in comorbid neu-
ropsychiatric disorders. Neurotoxicity Research, 12, 43-60.
Raudsepp, L., Viira, R., & Hannus, A. (2010). Prediction of physical
activity intention and behavior in a longitudinal sample of adolescent
girls. Perceptual and Motor Skil l s, 1 10, 3-18.
Rees, D. I., & Sabia, J. J. (2010). Exercise and adolescent mental health:
New evidence from longitudinal data. The Journal of Mental Health
Policy and Economics, 13, 13-25.
Rothon, C., Edwards, P., Bhui, K., Viner, R. M., Taylor, S., & Stans-
feld, S. A. (2010). Physical activity and depressive symptoms in
adolescents: A prospective study. BMC Medicine, 8, 32.
Russell, J. A. (1980). A circumplex model of affect. Journal of Person-
ality and Social Psychology, 39, 1161-1178. doi:10.1037/h0077714
Rusell, J. A., & Carroll, J. M. (1999). On the bipolarity of positive and
negative affect. Ps y c h o l og i c a l Bulletin, 125, 3-30.
Ryan, R. M., & Deci, E. L. (2001). On happiness and human potentials:
A review of research on hedonic and eudaimonic well-being. Annual
Review of Psychology, 52, 141-166.
Ryff, C. D. (1989). Happiness is everything, or is it? Explorations on
the meaning of psychological well-being. Journal of Personality and
Social Psychology, 57, 1069-1081. doi:10.1037/0022-3514.57.6.1069
Ryff, C. D., & Singer, B. (1998). The contours of positive human health.
Psychological Inquiry, 9, 2-28. doi:10.1207/s15327965pli0901_1
Schimmack, U. (2007). Methodological issues in the assessment of the
affective component of subjective well-being. In A. D. Ong, & M. H.
M. Van Dulmen (Eds.), Oxford handbook of methods in positive
psychology (pp. 96-110). New York: Oxford University Press.
Sjögren, T., Nissinen, K. J., Järvenpää, S. K., Ojanen, M. T., Vanha-
ranta, H., & Mälkiä, E. A. (2006). Effects of a physical exercise in-
tervention on subjective physical well-being, psychosocial function-
ing and general well-being among office workers: A cluster random-
ized-controlled cross-over design. Scandinavian Journal of Medicine
and Science in Sports, 16, 381-390.
Copyright © 2012 SciRes. 335
Copyright © 2012 SciRes.
Smith, P. J., Blumenthal, J. A., Babyak, M. A., Georgiades, A., Hinder-
liter, A., & Sherwood, A. (2007). Effects of exercise and weight loss
on depressive symptoms among men and women with hypertension.
Journal of Psychosomatic Re sea rch , 63, 463-469.
Takada, M., Suzuki, A., Shima, S., Inoue, K., Kazukawa, S., & Hojoh,
M. (2009). Associations between lifestyle factors, working environ-
ment, depressive symptoms and suicidal ideation: A large-scale study
in Japan. Industrial H ea l t h, 47, 649-655.
Tennant, C. (2001). Work-related stress and depressive disorders.
Journal of Psychosomatic Re sea rch , 51, 697-704.
Tugade, M. M., & Fredrickson, B. L. (2004). Resilient individuals use
positive emotions to bounce back from negative emotional activation.
Journal of Personality a nd Social Psychology, 86, 320-333.
Tsang, H. W., Chan, E. P., & Cheung, W. M. (2008). Effects of mindful
and non-mindful exercises on people with depression: A systematic
review. British Journal of Clinical Psychol ogy, 47, 303-322.
Urry, H. L., Nitschke, J. B., Dolski, I., Jackson, D. C., Dalton, K. M.,
Mueller, C. J., Rosenkranz, M. A., Ryff, C. D., Singer, B. H., &
Davidson, R. J. (2004). Making life worth living: Neural correlates
of well-being. Psychological Sc ien ce, 15, 367-372.
Von Thiele Schwarz, U., Lindfors, P., & Lundberg, U. (2008).
Health-related effects of worksite interventions involving physical
exercise and reduced workhours. Scandinavian Journal of Work, En-
vironment and Health, 34, 179-188. doi:10.5271/sjweh.1227
Wang, C., Bannuru, R., Ramel, J., Kupelnick, B., Scott, T., & Schmid,
C. H. (2010). Tai chi and psychological well-being: Systematic re-
view and meta-analysis. BMC Complementary and Alternative Me-
dicine, 10, 23-39. doi:10.1186/1472-6882-10-23
Watson, D., & Clark, L. (1988). Positive and negative affectivity and
the relation to anxiety and depressive disorders. Journal of Abnormal
Psychology, 97, 346-353. doi:10.1037/0021-843X.97.3.346
Watson, D., & Tellegen, A. (1985). Toward a consensual structure of
mood. Psycholog i c a l Bulletin, 98, 219-235.
Watson, D., Pennebaker, J. W., & Folger, R. (1986). Beyond negative
affectivity: Measuring stress and satisfaction in the workplace. Jour-
nal of Organizational Behavior Management, 8, 141-157.
Watson, D., Carey, L. A., & Carey, G. (1988a). Positive and negative
affectivity and their relation to anxiety and depressive disorders.
Journal of Abnormal Psychology, 97, 346-353.
Watson, D., Clark, L., & Tellegen, A. (1988b). Development and vali-
dation of brief measures of positive and negative affect: The PANAS
scales. Journal of Personality and Social Psychology, 54, 1063-1070.
Zöller, M. E., & Archer, T. (2009). Predicting stress in male and female
psychiatric patients and healthy volunteers. Social Behavior and
Personality, 37, 1081-1094. doi:10.2224/sbp.2009.37.8.1081
Zöller, M. E., Karlsson, E., & Archer, T. (2009). Self-rated affect
among adults presenting psychiatric diagnosis. Individual Differ-
ences Research, 7, 14-28.