Social Relationships, Leisure Activity, and Health in Older Ad.docx
Collegiate Pursuit of Happiness Final
1. I. Introduction
One of the greatest challenges in life is finding happiness. Whether it is happiness in
romance, happiness in your career, or simply happiness with yourself, the answer always seems
to be just out of reach. Yet, that has never stopped humans from seeking content and bliss. For
many young adults, these answers are found in the daily experiences with friends and family.
Positive social interactions, immersion in organizations and communities, and the intimate
relationships formed from these experiences are all important in regards to satisfying the
happiness needs of college students. Therefore, the purpose of this study is to examine the
fundamental factors that we believe affect the happiness of college students. How does a
student’s involvement, whether in Greek life or with extracurricular activities, play a vital role in
their happiness? Does the social support college students experience affect their self-esteem and,
subsequently, happiness? Is a student’s happiness determined by the stress of their romantic
relationship status and the problems associated with it? By examining these overarching factors,
we hope to shed some light and enable us to understand the relationship between the defining
aspects of the college experience and a student’s happiness level.
II. Literature Review
The framework of this study comes from two established Communication Studies
theories: Social Penetration Theory (SPT) and Uncertainty Reduction Theory (URT). SPT
revolves around the idea that an individual’s self-disclosure leads to deeper and more meaningful
relationships (Altman & Taylor, 1973). These relationships are looked at on a reward-cost scale,
meaning that if the interaction is seen as intimate and satisfying then the relationship itself is
worth maintaining. This reward/cost structure impacts the involvement, effort, and emotional
investment a person puts into a relationship, which also correlates with their happiness levels. It
2. is important to utilize SPT in our study because it relates to how involvement levels as well as
investment in surrounding relationships give shape to a student’s happiness. Furthermore, SPT
explains the value of social support in a student’s happiness because individuals depend on deep,
intimate relationships to enhance their self-esteem. URT helps explain the negative effects on
happiness, particularly when people feel uncertain about the future of their relationships (Berger
& Calabrese, 1975). It specifically applies to loneliness because it signifies uncertainty with
those around you when you do not know what to expect out of a relationship, and therefore feel
alone. Hence, both theories give structure to how we will analyze the variables at hand.
Researchers have been attempting to understand the reasons behind happiness for years.
The difficult part of this type of research revolves around the fact that the definition of happiness
keeps evolving. People constantly find new ways of defining what it means to be happy and,
subsequently, the reasons behind it change. For instance, Watson (1930) looked at what makes
people happy and who amongst the general population is happiest. The study found that the
happiest people tended to be those who were popular (or felt popular), married (vs unmarried),
and have stable friends. While some might call a study done in the 30’s outdated, it does set a
good foundation for what people seek when trying to make themselves happier, and what trends
exist in American society when it comes to being happy. Hence, these factors can be examined in
today’s college students to determine if these dated assumptions are still vital indicators of
happiness.
One of these proposed indicators of happiness amongst college students is that of
involvement. Those who engage in extracurricular activities on a regular basis correlate with
greater levels of satisfaction. One study suggested that extraverts who participate in serious,
constructive leisure activities such as social and physical events tend to have higher happiness
3. levels (Lu & Argyle, 1994; Lu & Hu, 2005). Another study extended on that finding by showing
how happiness is not affected by age, and those who had higher social participation were also the
individuals who were more involved (Cooper, 2011). Other findings also found correlation
between larger and more diverse social networks and higher happiness levels (Chen, 2012). In
other words, engaging in more diverse social activities can lead to an improved social standing,
and with this comes a happier and healthier lifestyle.
Because social life can incorporate many different elements, it is important to narrow the
study down to specifics. For example, engaging in social activities in college comes in many
forms, but one primary way is through Greek life membership. Previous studies showed that
Greek students illustrated higher levels of involvement in organizations and interaction with
fellow students (Pike & Askew, 1990). As previously exhibited, higher levels of involvement
indicate higher levels of happiness. This in turn leads to our desire to study whether or not being
involved in Greek life will specifically increase a student’s happiness. Those associated with
Greek membership may also display greater gains in interpersonal skills than those who did not
identify as a member of the Greek community (Hunt & Rentz, 1994). This can be attributed to
the cultural and organizational structure of fraternity/sorority, which seems to correlate with
more social development and construction of close relationships as well (Asel, Seifert &
Pascarella, 2009).
Sociability can have a few different factors involved, so we decided to narrow the focus.
We argue that having a higher social standing means having a strong social support system. The
rationale behind this is that social support can be seen as a fundamental factor in the happiness of
college students, especially in terms of their self-esteem. Previous studies propose that
subjective happiness is mainly marked by self-esteem, personal control, optimism, and
4. extraversion (Myers & Diener, 1995). When a person experiences lower levels of these factors, it
their sense of loneliness increases and happiness decreases. However, just because an individual
may experience high social support does not necessarily mean they are not lonely (Denny &
Steiner, 2009).
The effects of loneliness have not been extensively touched upon in the social sciences, at
least with concern to happiness. In other words, there is a need for research to understand how
much loneliness impacts an individual’s happiness level. While previous studies have found
support for the idea that increased social capital tends to increase happiness, to assume that social
support and loneliness are exact opposites of each other is not a solid assumption (Cooper, 2011;
Chen, 2012). Denny & Steiner (2009) point out an inconsistency between athletes’ self-esteem
and level of social support. Even though athletes in universities experience high amounts of
social support, a lowering in self-esteem, and therefore increase in loneliness, can render the
effects of that null. Thus, we aim to examine the specific effect loneliness has on happiness
levels and whether it carries far more significance than previously thought.
Differing levels of loneliness are associated with the quality of relationships present in a
college student’s day-to-day life. These relationships range from that of a child-parent to
friendship to that of a romantic partner. It has been suggested that a good relationship with
parents increases happiness, while having a low amount of friendships signified lower happiness
(Uusitalo-Malmivaara & Lehto, 2013). During emerging adulthood, most individuals attempt to
maintain and establish romantic relationships (Arnett, 2000). This suggests that the romantic
status of college students play a vital role in shaping their experience, especially in terms of
happiness. Findings in previous research suggest that friendship quality does not buffer the
impact of romantic relationships conflict on happiness (Demir, 2010). Thus, romantic
5. relationships, compared to friendships, play a more important role in happiness of emerging
adults. In addition, we believe that the main contributing factor to a student’s happiness is the
level of stress associated with a relationship status. URT helps support this assumption by
illustrating that the uncertainty of finding a romantic partner in college may relate to a negative
impact on the happiness of an individual.
Before moving into the methodological aspect of the study, it is important to note the
issue with measuring happiness. All the previous studies utilized different criteria and methods
of measuring individual content, whether they are objective scales, or subjective reports. While
the implications can be treated similarly, there has been surprising contradictions between the
two. For example, a study concerning objective satisfaction levels of Japanese cities was
compared to a more subjective means of measuring happiness, and it was found that the two
studies gave almost countering results (Kuroki, 2013). Instead of the cities having relatively
similar outputs for each measure, the subjective satisfaction levels of previously reported “happy
cities” were found to actually be the worst, and the same true in the other direction. This is not
the primary concern with our study, but it is possible that there could be varying differences in
subjective and objective happiness. We feel it is prudent to include it in the model as a control.
Given that, we expect the following relationships concerning objective happiness:
H1: People who are more involved in organizations on campus will have higher
happiness scores.
H2: Those involved in Greek life will exhibit higher levels of happiness than those who
are not involved.
H3: Individuals who have more social support will exhibit higher happiness levels.
H4: Those who have lower “loneliness” scores will exhibit higher happiness levels.
6. H5: Those who experience less stress with their current relationship status will have
higher happiness levels.
III. Methodology
The data for this study comes from a survey issued to University of San Diego
undergraduate students in November of 2013. The survey was constructed and distributed
through Qualtrics, and used a convenience sampling technique. A total of 471 responses were
received, and 348 of the surveys were completed fully. From this survey, the 348 responses to
nine questions for each participant was used to create the variables for the regression equation.
The first question asked the gender of the individual, coded as 1 for male, 0 for female.
Second, respondents were asked to indicate their relationship status. This was coded as 1=single,
2=casually dating/hooking up, 3=in a relationship but not exclusive, and 4=in a committed
relationship (monogamous relationship). Each of these were separated into dummy variables, i.e.
1 if single and 0 if not, 1 if hooking up and 0 if not, etc. After this, a question asked how much
stress their current relationship, or lack of relationship, caused in their life. This was coded
through a scale of 1=none, 2=little, 3=some, and 4=a lot.
For involvement, a simple scale was used that asked individuals to think of all the clubs
and organizations they were involved in, and how many times they went to the meetings and
events throughout the semester. The options were coded as 1=never, 2=once a semester, 3=a few
times a semester, 4=once or twice a month, 5=once a week, 6=a few times a week, 7=every day,
and 8=more than once a day. This was used as an increasing scale, so a higher number would
signify a higher amount of involvement. Related to involvement, association with Greek life was
measured through a question asking if the individual belonged to a sorority or fraternity, and
7. coded as 1=yes, 0=no. This was treated as a dummy variable in the regression equation to test for
its effects.
For social support, respondents were presented with an alternate version of the
Multidimensional Scale of Perceived Social Support, in which ten statements were presented,
versus twelve as in the original scale (Zimet, et al, 1988). The questions asked about the social
support they received from friends and family, and were asked to respond using a 7-point Likert
scale ranging from Strongly Disagree (1) to Strongly Agree (7). The responses to each question
were added together and divided by the total number of questions, to give an average level of
social support, which is used in the equation.
Loneliness was measured using a UCLA scale created by Russell, Peplau, and Ferguson
(1978). This scale contained fourteen statements, versus the twenty found in the original
iteration. These statements declared attitudes such as “I have nobody to talk to” and “I cannot
tolerate being alone.” Respondents used a 4-point scale, coded as 1=I have never felt this way,
2=I rarely feel this way, 3=I sometimes feel this way, and 4=I often feel this way. Positive
statements were reverse coded, and all the answers were averaged to create a loneliness variable,
measuring the overall loneliness level of the individual.
Happiness was split into two parts: Objective and Subjective. Subjective happiness was
measured through a single question, asking how happy, satisfied, or pleased the individual was
with their life over the past month. They were then presented with a 6-point scale, ranging from
1=extremely happy, could not have been more satisfied or pleased, to 6=very dissatisfied,
unhappy most of the time. This was reverse coded in order to get an increasing measure of
subjective happiness, and treated as an independent variable.
8. Finally, objective happiness was measured through the use of the Center for
Epidemiological Studies Depression Scale, which has 12 statements pertaining to feelings of
depression possibly held in the past week (Radloff & Teri, 1986). This scale consisted of
statements such as “I was bothered by things that usually don’t bother me” and “I felt
depressed”. Responses were coded using a 4-point scale, with 1=rarely or none of the time (less
than 1 day), 2=some of a little of the time (1-2 days), 3=occasionally or a moderate amount of
time (3-4 days), 4=most or all of the time (5-7 days). All negative statements were reverse coded
to transform the scale into the opposite of depression, or happiness, for the sake of this survey.
The answers to each statement were averaged, and used as a measure of overall objective
happiness. This was treated as our dependent variable.
IV. Results
Table 1: Variable Description
Variable Description
Obj_Happiness Measures total objective happiness level felt in the past week
(Reverse depression scale)
Male Dummy variable; 1 if male, 0 if female
Involvement Measures total involvement level (range: least involved (1) to most
involved (8)
Greek Dummy variable; 1 if in a sorority of fraternity, 0 if not
Social Measures overall social support (Multidimensional scale)
Loneliness Measures overall feelings of aloneness (Loneliness scale)
Single Dummy variable; 1 if single, 0 if not
9. Hookup Dummy variable; 1 if casually dating/hooking up, 0 if not
Nonexclusive Dummy variable; 1 if in non-exclusive relationship, 0 if not
Rel_status Dummy variable; 1 if in monogamous relationship, 0 if not
(reference variable, not included in equation)
Rel_stress Measures overall stress felt about relationship status (1=none, 4=a
lot)
Subj_Happiness Measure subjective happiness level in past month (Self-reported
happiness; 1=very unhappy, 6=very happy)
The table above provides an explanation of each variable used in the regression model.
Objective happiness was the dependent variable, and it was regressed against all other variables
(except Rel_status) using the Ordinary Least Squares technique. The equation is specified as
such:
Obj_Happiness= Β0+ Β1XMale+ Β2XInvolvement+ Β3XGreek+ Β4XSocial+
Β5XLoneliness+ Β6XSingle+ Β7XHookup+ Β8XNonexclusive+ Β9XRel_stress+
Β10XSubj_Happiness
As stated in the hypothesis, Involvement, Greek, and Social are expected to have a
positive relation with Obj_happiness, and Loneliness and Rel_stress are expected to have a
negative relation. Male, Single, Hookup, Nonexclusive, and Subj_happiness are not
hypothesized in any direction, but are included as both controls and to see if they have any
additional significant influences themselves.
Table 2: Descriptive Statistics
10. Mean Std. Dev. Min Max
Obj_happiness 3.275 0.516 1.583 4
Male 0.225 0.418 0 1
Involvement 4.763 1.693 1 8
Greek 0.324 0.469 0 1
Social 5.917 1.000 2.3 7
Loneliness 1.896 0.559 1.071 3.643
Single 0.474 0.500 0 1
Hookup 0.145 0.352 0 1
Nonexclusive 0.040 0.197 0 1
Rel_status 0.341 0.475 0 1
Rel_stress 2.069 0.838 1 4
Subj_happiness 4.295 1.127 1 6
Table 2 shows the descriptive statistics for the variables used in the equation. The data
consists of 22.5% (78) males and 77.5% (268) females. Overall, the mean objective happiness
score was 3.275 out of 4, whereas the mean subjective happiness rating was 4.295 out of 6,
which is fairly comparable. This indicates that the total population is objectively happier (or less
depressed) than they report they are. For males, 80.77% (63) reported a subjective happiness
score of 4 or higher, with a slightly lower percentage, 75.37% (202) of females reporting the
same. This data suggest that males feel slightly happier than females do, on average. On the
same note, males had a higher percentage in the 1 category, 2.56% (2), whereas women only had
1.49% (4) reporting as such.
12. [0.025]
Subj_happiness
0.123***
[0.021]
R-squared 0.513
Adjusted R-squared 0.498
Prob(F-stat) 0.000
Observations 368
*p<0.10, **p<0.05, ***p<0.01
Table 3 shows the output for the specified model. Male, involvement, loneliness,
relationship stress and subjective happiness levels have significant relationships, with male at the
5% level and the rest at the 1% level. Overall, the model has an R-squared of 0.513, suggesting
that this model can explain about 51% of the variance in the dependent variable, objective
happiness. Given this model, a few of the hypothesis are supported, while the rest are not:
H1: People who are more involved in organizations on campus will have higher
happiness scores.
H2: Those involved in Greek life will exhibit higher levels of happiness than those who
are not involved.
Due to both the involvement variable and Greek life variable being insignificant, this model
suggests that there is no relationship between level of involvement or participation in Greek life
and objective happiness. This means that people with higher values in these categories do not
have significantly different happiness levels than those who do not, and therefore does not
support the first two hypotheses.
H3: Individuals who have more social support will exhibit higher happiness levels.
13. H4: Those who have lower “loneliness” scores will exhibit higher happiness levels.
For the social variable, the equation states that a 1 unit increase in social support will signify a
0.081 unit increase in objective happiness, ceteris paribus. The model also states that those who
have a 1 unit increase in “loneliness” will experience a 0.360 decrease in objective happiness,
ceteris paribus. This supports our hypotheses that increased social support and decreased
loneliness will have positive relationships on objective happiness.
H5: Those who experience less stress with their current relationship status will have
higher happiness levels.
For the final hypothesized variable, the equation states that a 1 unit increase in relationship stress
will also have a 0.089 decrease in objective happiness, ceteris paribus. This supports the
hypothesis that stress concerning their relationship status is negatively correlated with an
individual’s objective happiness.
Discussion
This study was created in order to understand how much the social aspects of college life
affect the everyday happiness of undergraduate students. This centered on the following five
(shortened) hypothesis: 1) Involved people would be happier; 2) Greek life would have happier
members; 3) High social support indicates high happiness; 4) Those who are less lonely will
have higher happiness; and 5) Less stress with relationship status is correlated with happier
individuals. In the end, the first two ended up not having significant relationships, and the last
three were supported by the regression model. While the variables concerning involvement,
Greek, and relationship stress have interesting implications, we are going to focus on social
support, loneliness, and other significant finds that we did not hypothesize.
14. First off, it is not surprising that involvement and Greek life ended up being insignificant.
Previous research showed that hobbies (which could be lumped in with involvement) had little
consequence on an individual’s happiness (Watson, 1930). Granted, this research is quite dated,
but even the research done by Cooper, et al (2011), found that the types of involvement that were
most influential were things like religious service attendance. An argument could be made that it
is not necessarily the attendance or participation that leads to the increased happiness, but rather
the opportunities to allow for increased social capital, which was proposed in other studies
concerning happiness (Chen, 2012; Uusitalo-Malmivaara & Lehto, 2013). This doesn’t seem too
likely though, since our correlation table, included in this discussion’s index, showed that these
two variables barely correlate.
In other words, if our social support variable is significant, and involvement is not, then it
seems logical that there is nothing inherently happy about being involved if you are getting little
to no social support from it. The same conclusion can be reached about Greek life and
relationships. The amount of pull the social demands of college creates on an individual can lead
to a lot of stress in how ones feels about the relationships they have, or lack of one. For example,
if an individual becomes involved, Greek life or not, and doesn’t feel accepted, liked, or
supported by those around him, then it would be irrational to say he is happy. Still, there is a
significant emphasis put on becoming involved and trying as many things as possible, with little
guidance on how to actually belong to these groups. As for involvement, as a student, many
people are suggested and downright pressured to join fraternities and organizations, that it “will
be good for them”. Yet, if our research is accurate, this does not necessarily lead to happiness,
nor does it lead to automatic social support, which leads to an interesting conundrum.
15. An interesting conclusion reached was that, apparently, social support and loneliness, two
seemingly opposite variables, are not a related as one would think. According to the correlation
table, while these two have a correlation value of .5609, it wasn’t high enough to be a concern
(on that note, there wasn’t any real concern for multicollinearity, since all simple correlation
values were less than 0.8). This was supported by previous research, which found that athletes
may have high social support, but if their self-esteem is was low, then this was a moot point
(Denny & Steiner, 2009). This could have large implications for social scientists seeking to
explain depression and suicide in individuals who are seemingly popular and well liked.
According to our study, loneliness ended up having the largest impact of the
hypothesized variables, with a negative 0.36 drop in happiness with ever unit increase in
loneliness. This dwarfs the effects of every other variable, which barely makes it to the 0.1 mark
(excluding subjective happiness). If Denny & Steiner’s assumption is true, and loneliness and
sociability aren’t perfect substitutions of another, than an individual could score extremely high
on the social support scale, and still suffer from extreme loneliness. In fact, a one unit increase in
loneliness would almost negate a uniform increase in every other significant variable, showing
how important that variable is to happiness. Due to its low correlation with every other variable,
it’s no wonder a common statement made by the loved ones of a recent suicide victim is a lack of
understanding when the individual was so well liked. Hence, we believe this to be one of the
most important findings of the study, mainly due to the implications it has for friends worried
about people they know.
On a similar vein, it is interesting to see the significance of two non-hypothesized
variables. Both male and subjective happiness had outputs at an extremely significant level, even
though we did not expect them to be so. In a revisit to the literature, many of the studies did also
16. found that being male had a significant positive effect on happiness, even though one wouldn’t
expect it (Cooper, et al, 2011; Chen, 2012). Myers and Diener (1995) suggested that this is likely
due to women being about twice as vulnerable to depression and anxiety, and therefore will
identify as less happy. But, looking at our output, the effect it has is not that large; it only will
increase happiness by 0.92 units, which is practically nothing since the variable only takes two
values. The more interesting of the two is the subjective happiness variable.
It was mentioned earlier in the literature review that there is some disjoint between how
happiness is measured, whether through objective types of research, like scales, or more
subjective means, like self-reports. Different studies use different means, which is why our study
incorporated both, to see the relationship between the two if any. This mainly stemmed from the
findings in Kuroki’s (2013) study, in which the objective happiness scale used to measure
satisfaction in various cities gave almost completely opposite results to the more subjective
reports gathered. The difference here was that there was not a paradoxical relationship as
concluded in the other study; instead, there was a positive relationship between subjective and
objective happiness. Of course, it is not clear what direction this relationship is: does feeling
happier actually make you happier, or does actually being happier make you say you’re happy?
It’s a confusing process, much like anything concerning happiness, but an important one at that.
It would be very educational to test to see if making someone feel happier actually increases their
overall objective happiness levels. This could be a good avenue of research for future studies.
At this point, it would be appropriate to address some of the short-comings of the study,
as all studies have them. First off, the data collection was done through convenience sampling
techniques, opening up the possibility for error, especially since this was done mainly in the
Communication department. To say this data is completely representative of the university
17. population would be a stretch. Secondly is our measurement of happiness. Because the survey
did not use a specific happiness measurement scale, we had to reverse code a depression scale.
Now, while the definition of depression is basically the exact opposite of happiness, it is still a
proxy, and therefore always open to scrutinizing. The bias this may put on our data may not be
large, but if the assumption the women are more prone to depression is true, it is still a
possibility. Related to that, there is existing debate on what a better measure of happiness is:
objective scales or subjective reports. While we did choose objective for this, one could easily
switch it around and see what the effects are on the other variable.
In the end, what this study helps shows is that there is no single factor that explains
happiness, and that it is comprised of multiple different determinants. Given that, and the limited
power of our equation, there is something to be said about the importance of social support and
feelings of aloneness, and its effects on happiness. We hope further studies take this, and try to
discover the best ways to mitigate the varying effects this has on happiness, so that universities
and society in general can help make sure its youth is as happy as can be.
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