Happiness-Suicide Paradox and Boredom

1Running Head: HAPPINESS-SUICIDE PARADOX AND BOREDOM

Because Nothing Ever Happens Here: A Look At Boredom and the Happiness-Suicide Paradox

Lindsey M. Lockridge

University of Alabama


Because Nothing Ever Happens Here: A Look At Boredom and the Happiness-Suicide Paradox

“We’re running down the streets in our underwear, because nothing ever happens here.”

What at first seems like a silly song written by Icelandic electropop band FM Belfast turns out to

be a rather interesting insight into a curious problem known as the Happiness-Suicide Paradox –

a theory which states that happier countries have higher suicide rates. Not surprisingly, Iceland –

along with its northern neighbors Sweden, Denmark, and Norway – ranks among the top ten

happiest countries, according to a meta-analysis conducted by psychologist Adrian White. White

(2006) analyzed data from UNESCO, the CIA, the New Economics Foundation, the WHO, the

Veenhoven Database, the Latinbarometer, the Afrobarometer, and the UNHDR to create the

first-ever “world map of happiness,” ranking Denmark, Iceland, and Sweden 1st, 4th, and 7th,

respectively. Data from the 2012 Prosperity Index, combining factors such as economy,

governance, education, health, and personal freedom, shows a similar trend, with Norway,

Denmark, and Sweden taking 1st, 2nd, and 3rd, and Iceland dragged down to 15th only by its poor

economy.

On the other hand, despite high levels of happiness and life satisfaction, a number of

studies have shown that these same countries also have relatively high suicide rates – the

paradox at the focal point of this paper, but one that still remains poorly understood. The

question stands: why? Theories have been tossed around from seasonal affective disorder due to

dark winters in Scandinavia to differing attitudes about suicide. Until recently, the happiness-

suicide paradox has been examined only as a comparison of various countries, but the Federal

Reserve Bank of San Francisco narrowed the scope to a single nation – the United States – and

found the pattern to be the same (Daly, Oswald, Wilson, & Wu, 2010). Combining a variety of

factors such as life evaluation, work environment, and healthy behaviors, the Gallup-Healthways


Well-Being Index created a happiness map similar to the Prosperity Index on Legatum’s website,

but focused on the United States. According to the poll, Western and Midwestern states had the

highest wellbeing scores while the South had the lowest, which has remained fairly consistent

over the past four years (2011). This could be attributed to a difference in region, but the Federal

Reserve Bank of San Francisco adjusted its average life satisfaction and suicide risk scores for

differences in details like age, income, employment, etc., and the correlation persisted (Daly et

al., 2010).

Few studies have looked at the factors underlying this phenomenon. The research thus far

has simply sought to establish its existence; however, the goal of this paper is to delve deeper

and search for a possible explanation.

First of all, several theories about the happiness-suicide paradox have mentioned the

possibility of relative happiness. One of the first studies conducted on this idea interviewed

lottery winners, accidental paraplegics, and people who had neither won a lottery nor were

paralyzed and discovered that the lottery winners found less pleasure in everyday activities after

winning, and that they eventually became habituated to the happiness derived from winning so

that they were no happier than control subjects (Brickman, Coates, & Janoff-Bulman, 1978).

This sprung future research on adaptation theory – the theory that earlier events serve as

reference for how later events are judged – and it has been held consistently as true. Bowling,

Beehr, Wagner, and Libkuman (2005) describe this in terms of a pay raise: a person who has

worked for years without a raise experiences greater happiness even when given a small raise,

and then adjusts his expectations. It can also be seen between individuals, such as when someone

used to large raises is less happy with a 2% raise than a person who receives the same raise, but

has never before received one (Bowling et al., 2005).


With that being said, one can infer that those who are well off take their state for granted.

In a country such as Denmark, which scores high on education, income, and health, people

become content and require a greater change in circumstances to feel a higher level of happiness,

as opposed to people in countries that have lower scores in those areas. The opposite is assumed

to be true: those who are happy react more intensely to a negative situation than do those in the

same situation who are less happy. In the context of the happiness-suicide paradox, people in

happy countries and states will react more strongly to a negative stimulus and thus be more prone

to suicidal tendencies.

Studies have also illustrated that humans compare themselves to those by which they are

surrounded. Hagerty (2000) examined the incomes of natural American communities, in which

individuals earning less than the maximum income of the area and surrounded by many others

earning more money felt less happiness than those surrounded by more people earning a similar

income. It might not be a stretch, then, to think that the same can be said about happiness.

Additionally, according to the United States Census, the states with the largest

concentrations of Scandinavian Americans are those scoring among the highest on the happiness

scale, such as Utah, Minnesota, and the Dakotas. This makes one wonder if there is some genetic

factor to the paradox, but the presence of Australia in the Prosperity Index’s rankings throws a

wrench in the idea. Needless to say, it might be an interesting direction for future research.

Returning to FM Belfast’s insight from the beginning of this paper, perhaps the paradox

can be attributed to “nothing ever happening.” A study conducted on youth in rural Australia

found a positive correlation in leisure boredom and heightened risk of suicide (Patterson & Pegg,

1999). In fact, in another Australian study that investigated adolescents in northern Queensland,

Bones, Cheers, and Hill (1993) reported that despite appearing to have access to recreation


facilities and living in luxurious environments, teenagers responded that there “is not much to

do” and “it’s a boring place.” That data coincides with the happiness-suicide paradox in that the

2012 Prosperity Index has ranked Australia as one of the happiest countries – 4th, to be exact –

but also has high suicide rates.

In several past studies, boredom has been linked to negative affect, including depression,

thought to be derived from a lack of purpose or meaning in life (Fahlman, Mercer, Gaskovski,

Eastwood, & Eastwood, 2009). However, boredom and depression may not be synonymous.

Maltsberger (2000) described an example of a patient who attempted suicide twice, but did not

consider himself depressed, and his psychiatrist did not consider diagnosing him as such.

In another (but similar) vein, Manolito Gallegos (2011) wrote a paper on Schopenhauer’s

theory that happiness only exists as a lack of suffering, and not something that exists positively.

Gallegos reinforced the idea that happiness cannot exist without suffering, defined as being any

sort of pain including that derived from striving toward a goal, and one “cannot get past boredom

without reintroducing [certain forms of suffering]” (Gallegos, 2011). One can draw the

conclusion, then, that people in places with greater self-satisfaction would have less for which to

strive (a form of suffering) and thus be prone to boredom, and that feeling happy is only tangible

in the presence of its opposite. To put it simply, people who are consistently happy may be numb

to that happiness and will resort to suicide not because of hopelessness or sadness, but because

there is nothing else to do.

In fact, as brought up in Fahlman et al.’s (2009) paper, boredom derives from a lack of

fulfillment, so people who do not experience suffering may not be as fulfilled. Baumeister,

Bratslavsky, Finkenauer, and Vohs (2001) examined the theory that bad is stronger than good,

finding that it holds true in almost all possible cases. People are more likely to remember


negative events, more likely to pay attention to negative traits, more likely to remember criticism

over compliment, etc. (Baumeister et al., 2001). If it is the negative that form more lasting

memories and make stronger impressions, then the lack of such must leave a life feeling empty.

The current study will look at the idea that humans need bad events to happen – if not to them,

then in close proximity – in order to be interested in life.

Two studies will be conducted. Study 1 will be a basic examination, similar to that of

Patterson and Pegg (1999), of American states and their leisure activities. The hypothesis is that

states with higher rates of suicide will report fewer positive leisure activities (such as recreational

sports) and higher rates of leisure boredom. Study 2 will involve a life simulator to evaluate

several hypotheses: 1) people with good lives will report less happiness than people with bad

lives when a good event happens, 2) people with bad lives will report a smaller change in

happiness than people with good lives when a bad event happens, 3) people with good lives will

report decreasing interest when neither good nor bad events happen, and 4) people with good

lives will report the greatest increase in interest when a bad event happens either to them or to

another person. If the hypotheses are true as predicted, then it will provide some evidence to

believe that the happiness-suicide paradox results from boredom rather than happy people feeling

sadness more intensely, as previously thought.

Method

Study 1

Design

Study 1 will be a mail survey in which participants fill out information about recreational

activities in their respective areas. No variable will be manipulated, as the survey will be used


only to look for a trend in suicide rates and recreational activities based on state. The questions

will include what types of activities one has available and one’s own opinion of the activities.

Participants

Surveys will be sent to inhabitants of all states to gather as representative a sample as

possible. No incentive or compensation will be rewarded.

Materials/Measures

The survey will include basic demographics, such as age, gender, race, region (South,

Northeast, Midwest, and West), and state of residence, and ask questions regarding recreational

facilities in the area. Questions will ask for information about what types of activities are

available, what types of activities the participant regularly engages in, how enjoyable the

activities are, how accessible they are, and how interesting or fulfilling one finds living in that

particular area.

Procedure

A survey will be sent out to every American address and given a 3-month deadline to

complete and return it. All surveys will be sealed in an envelope with stamps and empty

envelope to encourage a higher return rate. A consent form and information sheet stating that the

prime interest of the study is to compare the recreational activities available to people in different

states will be on top, and the questions will begin with demographic information, followed by

most general factual information (such as nearby recreational activities and facilities) and ending

with the participant’s evaluation of the activities available to him based on a 1 – 5 numerical

scale with 1 being not at all interesting and 5 being very interesting. Contact information in case

the participant has any questions or concerns will be available on the final page.

Results


The data will be collected and analyzed using a Pearsons correlation for recreational

activity and suicide rate (data from the Federal Reserve Bank of San Francisco [2010]), and

interest and suicide rate. Then it will be analyzed using a one-way ANOVA for region. The

results from the Pearsons correlation will demonstrate that there is a negative relationship

between suicide rate and amount of recreational activity, as well as a negative relationship

between suicide rate and interest. People reporting more recreational activity and interest should

come from areas with lower suicide rates. Secondly, the ANOVA should reveal that there is a

significant difference in interest per region and that the West and Midwest should have the

lowest interest scores in order to follow the hypothesis that suicide in happy areas is contributed

to boredom.

Study 2

Design

Study 2 will examine a simulated life (good or bad) with the potential for four conditions

(good event, bad event, no event, and bad event happening to neighbor) in a between-subjects 2

x 4 factorial design. Each participant will be randomly assigned to either a good or a bad

simulated life, and then will be assigned one of the four event conditions. The dependent

variables will be how interested in and how happy the participant is with his simulated life,

which will be gathered from a series of questionnaires administered periodically throughout the

course of the experiment.

Participants

Approximately 120 participants will be recruited from a convenience sample from a large

southeastern university. All participants will be enrolled in the university and will mostly be


between the ages of 18 and 22. Participants will be recruited from the psychology subject pool

and will participate in order to fulfill a research credit requirement.

Materials/Measures

Survey. A university-wide survey will be sent out to establish an average ranking for a

selection of 10 good events and 10 bad events. The questionnaire will simply ask participants to

rank a total of 20 events (10 good and 10 bad ranked separately) for what they consider to be the

best thing to happen to a person and what they consider to be the worst thing to happen to a

person. Good events will be events such as having a child, getting married, receiving a

promotion, and winning the lottery while the bad events will include losing a job, getting a

divorce, losing one’s house, and the sudden death of a loved one. The data will be collected and

averaged to determine the single-best and single-worst event to happen to a person to be used in

the simulator for the actual experiment.

Pretest. All recruited participants will be given a pretest to determine what they consider

to be a good or a bad life. The top answers for both will be collected and used to create the good

life and bad life simulations. The participants will also be required to fill out basic demographic

information such as age, race, and gender.

Life simulation. Studies have shown that video games are widely popular in the United

States, with around 40% of the adult population playing them (Slagle, 2006). Simulation games

are particularly useful as learning tools and provide true-to-life experiences (Sitzmann, 2011).

Additionally, games like the Sims are addicting because they allow for the player to synthesize

her own version of real life with the game’s version of real life (Nutt & Railton, 2010). With

these studies in mind, the current study will implement a life simulator similar to the popular PC


game the Sims in order to simulate a good or a bad life for each participant. Each life will have

one of the four conditions randomly programmed into it.

Progress log. Each participant will be asked to fill out a short daily log about his or her

experience with the game. The questions will be basic and will focus primarily on how happy

with and how interested the participant is in his simulated life.

Post-test. A post-test will be administered to determine the overall satisfaction each

participant had with his or her simulated life, but will also be used to look for any potential

distress the participant might have felt with certain events. Another several questions will be

asked to determine how invested the participant was in his or her character.

Procedure

Each participant will be asked to fill out the pretest to determine the components of the

good and bad lives used for the experiment. After the data has been collected, a default good life

and a default bad life will be created. All “good” lives will have the same starting components

and all “bad” lives will have the same starting components. Each participant will then be

introduced to the program by an experimenter who will go over the consent form and

information sheet and will then explain the controls of the game. The experimenter will explain

that the purpose is to determine how people create their own simulated lives so as to avoid

demand characteristics. Participants will be randomly assigned to one of the two default life

settings. Each participant will create his or her own character (customize appearance and name)

and will be asked to come in to the lab three times a week for an hour a day to play. At the end of

each session, each participant will fill out a daily log that tracks his happiness and interest in his

simulated life.


After two weeks, each participant will encounter randomly one of three events. In the

case of the fourth situation, nothing will happen and so will serve as a control. Those in the good

event condition will experience the event determined to be most good as decided by the

university-wide survey, those in the bad event condition will experience the event determined to

be most bad as decided by the university-wide survey, and those in the proximal bad event will

not experience the event directly. Participants in this condition, however, will hear about the bad

event happening to his or her neighbor.

After another week, the experiment will end and participants will be given a final post-

test to ensure that they did not experience any distress or negative emotions. The post-test will

also be used to evaluate the participant’s overall satisfaction with his simulated life and how

invested he was in his character. An experimenter will then debrief the participant, answer any

questions and address any concerns, and then the participant will be thanked.

Results

The data collected will be analyzed using a between subjects ANOVA. How invested a

participant was in his or her simulated life will also be factored in. The results from this analysis

will demonstrate a main effect for the event condition. If the results follow the hypotheses, then

1) participants in the good life condition will report less happiness than people with the bad life

condition when a good event happens, 2) participants in the bad life condition will report a

smaller change in happiness than people with good life condition when a bad event happens, 3)

participants in the good life condition will report decreasing interest when neither good nor bad

events happen, and 4) participants in the good life condition will report the greatest increase in

interest when a bad event happens either to them or to another person.

Discussion


In the case of study 1, if the hypothesis holds true that areas with less recreational

activities have higher rates of suicide, then improvement can be made in those areas to focus on

creating new recreational activities, as suggested by Patterson and Pegg (1999). Regions such as

the West and Midwest will show a lower rate of interesting recreational activities, which will

negatively correlate with suicide rate. However, due to data being collected by mail survey,

results may not be as representative as expected as it is highly possible that not all surveys will

be completed and returned. With study 2, if the hypotheses hold true, then it opens the door to

future research on the happiness-suicide paradox and boredom. This suggests that despite living

a good, healthy life, one can still fell unsatisfied without negative things. This follows

Schopenhauer’s theory that happiness cannot exist without suffering (Gallegos, 2011). In the

case of the person living a good life with neither good nor bad events happening, it is expected

that his interest will slowly decrease over time, as he has nothing to strive for. However, if a

person in a good life experiences a good event, his happiness will not increase very much, just as

a person in a bad life who experiences a bad event will not have much of a change in happiness,

as proposed by Bowling et al. (2005). This information may help to improve therapy for

depression, such as placing depressed patients among others who have similar life satisfaction

rather than with happier individuals.

Study 2 is not without drawbacks, however, and one of the biggest is that the participants

may come from various backgrounds and thus view good and bad events differently, even after

being evaluated with the pretest. On the other hand, if the experiment proves successful, future

research can be directed to an evaluation on a nationwide level to determine any differences in

how people handle good and bad events based on state/region.


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Happiness-Suicide Paradox and Boredom