Solutions to the Problem of Diminished Social Interaction

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Evolutionary Psychology
www.epjournal.net – 2008. 6(4): 637-651
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Original Article
Solutions to the Problem of Diminished Social Interaction
Peter K. Jonason, Department of Psychology, New Mexico State University, Las Cruces, New Mexico, USA.
Email: [email protected] (corresponding author)
Gregory D. Webster, Department of Psychology, University of Florida, Gainesville, Florida, USA.
A. Elizabeth Lindsey, Department of Communication Studies, New Mexico State University, Las Cruces,
New Mexico, USA.
Abstract: Social animals, like humans, need to interact with others, but this is not always
possible. When genuine social interaction is lacking, individuals may seek out or use
sources of interaction that co-opt agency detection mechanisms vis-à-vis the human voice
and images of people, called social snacking. Study 1 (N = 240) found that ratings of how
alone participants felt were correlated with frequency of talking to themselves and using
the TV for company. Study 2 (N = 66) was a daily diary study where loneliness was
correlated with both Study 1 behaviors and singing to oneself. These solutions essentially
trick the person's brain into feeling like they are socially interacting, thus, appeasing the
relative dependence humans have on social interaction. Social snacking may satisfy one’s
need for social interaction because humans are unlikely to be able to differentiate between
virtual and real people because this distinction did not exist in ancestral environments.
Keywords: agency detection, social snacking, evolutionary psychology, loneliness
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Introduction

Limited social contact is problematic to any social species. When people lack social
contact they have psychological and health dysfunctions (Bowlby, 1988; Hazan and
Shaver, 1994; Perlman and Peplau, 1984). These dysfunctions often manifest themselves in
the form of depression, grief, anxiety, and loneliness (Baumeister and Tice, 1990; Leary,
1990). People have a fundamental need for affiliation that stems from the benefits of group
living (Baumeister and Leary, 1995). Being lonely and alone appears to have both
biological and social components (Gruter and Masters, 1986) and both cause psychological
discomfort (Jones, Freeman, and Goswick, 1981) like ostracism (Williams, 2007).

Solving loneliness
What does one do when they feel alone or lonely? Individuals may attempt to buffer
themselves from these feelings by seeking out activities and interaction partners that
remind them of social connections, or what is being called “social snacking” (Gardner,
Pickett, and Knowles, 2005; Twenge et al., 2007). For instance, looking at memorabilia
that conjures up memories of loved ones makes aged people feel less lonely (Sherman,
1991). Furthermore, the degree to which individuals anthropomorphize their pets is a
function of how lonely they are (Epley, Waytz, Akalis, and Cacioppo, 2008). Individuals
seek out reminders that they have social lives when not immersed in them at that time.
Social snacking is one solution to the problems created by the relative dependence on
maintaining social bonds that people have. However, traditional work on social snacking
has not provided good evolutionary accounts of why social snacking might work. The
current study examines the associations between social snacking and rates of diminished
social interaction from an evolutionary perspective.
From an evolutionary perspective, social snacking might work because it activates
agency detection mechanisms (for review see, Barrett, 2005). In a world where there are
numerous stimuli, agency detection mechanisms allow one to focus on certain features as
heuristics in processing. For instance, hearing rustling in the bushes may activate predator-
detection mechanisms that cause a flight response whether or not the rustling is actually
caused by a predator. In the case of social snacking, features like the human face and voice
may provide the appropriate cues that activate these agency detection mechanisms that tell
individuals they are not alone.
For social snacking to function through cues to agency, types of social snacking
should be characterized by cues to agency. Individuals give their pets personalities and
think of their pets as people when they are lonely, thus creating cues to agency (Epley et
al., 2008). We investigate two other types of social snacking. Talking to oneself and
watching TV offer cues to agency but have rarely been studied as either social snacking or
from an evolutionary perspective. Talking to oneself and watching TV may co-opt (for a
review see, Buss, Haselton, Shackelford, Bleske, and Wakefield, 1998) the mechanisms
that correspond to genuine social interaction because it shares some of the same features as
genuine social interaction: human agents talking. This co-option likely mimics enough of
the features of genuine social interaction that individuals’ need for social interaction is
appeased, perhaps to a lesser degree than the genuine article (Rosengren and Windhal,
1972). It likely works because evolved psychological mechanisms have difficulty
differentiating between types of entities people did not reliably encounter in ancestral times
(Kanazawa, 2002).
Most research on talking to oneself and watching TV has utilized proximate
models. Research suggests that self-talk can (1) decrease anxiety (Conroy and Metzler,
2004; Gould, Finch, and Jackson, 1993; Page, Sime, and Nordell, 1999), (2) increase goal
attainment (Green, Hall, and Erickson, 1995; Hardy, Gammage, and Hall, 2001; Johnson,
Hrycaiko, Johnson, and Halas, 2004; Van Raalte, Cornelius, Brewer, and Hatten, 2000), (3)
increase self-esteem and decrease depression (Philpot and Bamburg, 1996; Philpot,
Holliman, and Madonna, 1995), (4) enhance self-knowledge and is related to self-
consciousness (Schneider, 2002), and (5) be useful in treating social maladjustment
(Calvete and Cardenoso, 2002). This research, in sum, suggests that talking to oneself may
be a solution that people use to deal with their problems.
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Solving loneliness
Research in mass media and communication has also come from more proximate
theoretical positions. Individuals may use media, such as TV, as a means, in part
(Rosengren and Windahl, 1972), to deal with their lack of social contacts (Giles, 2002;
Rubin, 1981, 1983; Rubin, Perse, and Powell, 1985; Nordenstreng, 1970). Some people
may use the TV as a means by which they can escape from the troubles of their day-to-day
life (McQuail, Blumler, and Brown, 1972) and much more (for review see, McQuail,
1972). People develop parasocial or virtual relationships with TV characters. For instance,
individuals who are lonelier will form parasocial relationships with news broadcasters
(Rubin, Perse, and Powell, 1985). Social facilitation occurs on well–learned tasks when
participants did these tasks in the “presence” of their favorite TV characters (Gardner and
Knowles, 2008). While it may be true that individuals have become disengaged from real
life by watching too much TV (Putman, 2000), individuals who watch more TV reported
more satisfaction with their social lives than those who did not watch as much of certain
genre of programming; people fail to distinguish between real friends and parasocial
friends (Kanazawa, 2002). This suggests that people lump real friends and parasocial
friends together when considering their social network.
The current studies capitalize on the adaptionist paradigm to reframe the emerging
discipline of social snacking. Study 1 is a single-shot, correlational study, whereas Study 2
is based on longitudinal data. Both studies focus on how social isolation is correlated with
rates of social snacking. Social snacking tends to be characterized by cues to agency and
thus, we conceptualize social snacking as working through agency detection mechanisms.
Study 1
In Study 1, we examine the correlations between self-talk, turning the TV on for
company along with one measure of social isolation: rates of being alone. This is an initial
study to examine the relationship between social isolation and potential measures of social
snacking. We predict that rates of self-talk and TV for company will be positively
correlated with rates of being alone.
Methods
Participants
Two hundred forty undergraduates (49% female) ranging in age from 18 to 65
years (M = 20, SD = 7.8) enrolled in psychology and communication classes at a large
public university in the Northeastern U.S. received extra credit for their voluntary
participation.

Measures

Participant’s frequency of being alone was measured with four items (1 = not at all;
5 = very much). Two items asked participants how frequently they were alone and how
alone they were. Two more questions asked how much participants agreed with the
statements: I am often alone and I am frequently by myself. These items were averaged to
create an index of the frequency of being alone (Cronbach ? = .91; M = 2.28, SD = 1.64).

Participant’s use of self-talk was a five-item measure (1 = not at all; 5 = very
much). Participants were asked how much they did the following: (1) I speak to myself out
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Solving loneliness
loud, (2) I talk to myself, (3) I talk to myself out loud, (4) I speak to myself, and (5) I put
my thoughts into words. These items were averaged to create an index of the amount of
self-talk (? = .82; M = 2.70, SD = .96).

TV use was a four-item measure (1 = not at all; 5 = very much). Participants were
asked how much they did the following: (1) I turn the TV on when I get home, (2) I often
have the TV on, (3) even if I am not watching it, the TV is on at my home, and (4) I do not
always watch the TV when it is on. These items were averaged to create an index of TV-
usage (? = .74; M = 3.04, SD = 1.01).
Results

Rates of aloneness were correlated with self-talk (r(233) = .17, p < .05) and TV use
(r(234) = .24, p < .01). Self-talk and TV usage (r(234) = .23, p < .01) were also correlated.
No other significant relationships or differences were found. Women were marginally more
likely to talk to themselves than men (t(232) = -1.77, p < .08).

Discussion

Being alone appears to be correlated with rates of self-talk and using the TV for
company. Results confirmed our contention that when alone, individuals seek out
replacements for social interaction that mimic genuine social interaction.
Study 2
In Study 1 we considered how rates of being alone related to TV usage and talking
to oneself. Next we will address both rates of being alone and rates of loneliness in a daily
diary study. This study addresses three questions. First, what were the relationships
between daily measures and trait-level measures of loneliness? Second, what were the
relationships between daily aloneness and other daily measures? Third, did these within-
person relationships vary as a function of trait-level characteristics such as participant sex,
loneliness (Russell, 1996), and people’s tendency to form “friendships” with TV characters
or parasocial interaction (Rubin, Perse, and Powell, 1985)? We also expand our
examination to include another type of social snacking: singing to oneself.
In Study 1, we found that women were slightly more likely to use self-talk than
men. This finding is consistent with prior work that suggests that women feel a need to
maintain more closely bonded relationships than men (Buhrke and Fuqua, 1987). If women
feel they need to maintain more intimate social connections, then they may be more likely
to social snack than men. In the past, such a sex difference has been seen in research that
makes the distinction between positive and negative self-talk (Tamres, Janicki, and
Helgeson, 2002); women appear to use negative self-talk more than men. We predict sex
differences in self-talk in general and in negative self-talk, such that women will use
negative and general self-talk more than men.


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Solving loneliness
Methods

Participants

Sixty-six students (76% female) ranging in age from 19 to 47 years (M = 23.88, SD
= 5.70) enrolled in communication classes at a large public university in the Southwestern
U.S. received extra credit their voluntary participation.

Procedure

A daily diary measure was distributed to the participants. This packet contained an
informed consent and the measures to be discussed below. All but the Loneliness Scale and
Parasocial Interaction Scale were included in the daily diary portion. Participants reported
their responses to the daily diary items across four days. At the end of the four days
participants turned in the packet and were thanked and debriefed.

Trait measures

The UCLA Loneliness Scale (Russell, 1996) was used to measure loneliness. This
scale was only presented once to the participants before they completed the daily diary
measures as discussed below (? = .92).
Parasocial
interaction
(? = .88) was measured using a modified version of Rubin,
Perse, and Powell’s (1985) measure by making the items not specific to news-viewing but
TV viewing in general. For instance, participants were asked how much they agreed with
statements such as: “I see my favorite TV personality as a natural, down-to-earth person”
and “I miss seeing my favorite TV personality when he or she is not on TV.”

Daily measures

All daily items were averaged into their respective measures to create daily mean
scores. Daily aloneness (test-rest reliability = .76) was measured using two items: “I have
been alone a lot today” and “I felt very alone today.” Daily TV use for company (test-rest
reliability = .82) was also measured using two items: “The TV was on today although I did
not really watch it” and “I turned the television on today mostly to just keep me company.”
Daily self-singing (test-rest reliability = .83) was measured using three items such as:
“Today I sang to myself” and “I found myself singing to myself today.”

Three types of daily self-talk were measured with four items each: general, positive,
and negative. General self-talk (test-rest reliability = .79) was measured using items such as
“I spoke to myself at least once out loud today” and “I talked to myself today.” Positive
self-talk
(test-rest reliability = .85) was measured with items such as, “When I talked to
myself out loud today, I praised myself” and “When I talked to myself out loud today, I
congratulated myself.” In contrast, negative self-talk (test-rest reliability = .86) was
measured with items such as, “When I talked to myself out loud today, I chastised myself”
and “When I talked to myself out loud today, I criticized myself.” Descriptive statistics are
reported in Table 1.





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Solving loneliness
Table 1. Descriptive statistics
Mean
(SD)
1. Average amount of self-talk
2.78 (0.89)
2. Average amount of self-sing
1.92 (0.93)
3. Average amount of positive self-talk
2.56 (0.83)
4. Average amount of negative self-talk
2.27 (0.84)
5. Average amount of putting the TV on for company
2.35 (0.94)
6. Average amount of being alone
4.17 (3.27)
7. UCLA loneliness
2.02 (0.48)
8. Parasocial interaction
2.79 (0.65)
Note. Participants reported frequency (1 = not at all; 5 = very much)
Results
Our questions of interest regarding daily (within-person) relationships took three
forms. First, what were the relationships between daily measures and trait-level measures
of loneliness? Second, what were the relationships between daily aloneness and other daily
measures? Third, did these within-person relationships vary as a function of trait-level
characteristics such as participant sex, loneliness, and parasocial interaction? To answer
these questions, we first report bivariate correlations in Table 2.

Table 2. Correlation among trait variables and daily diary variables summed across four days
1
2
3
4
5
6
7
8
1. Daily TV for company
--

2. Daily self-talk
.44**
--

3. Parasocial interaction1
.06
-.07
--

4. Daily positive self-talk
.18
.46**
.12
--
5. Daily negative self-talk
.45**
.44**
.12
.17
--
6. UCL
A Loneliness1
.26*
.29*
.02
-.22
.34**
--
7. Daily aloneness
.27*
.31*
.06
-.23
.29*
.46**
--
8. Daily self-sing
.25*
.55**
.01
.37*
.47**
.25*
.25*
--
* p < .
05, ** p < .01
1 Trai

t variable
Next we conducted a series of multilevel random coefficient models (Raudenbush
and Bryk, 2002) using the program Hierarchical Linear Modeling (HLM6; Raudenbush,
Bryk, Cheong, and Congdon, 2004). In these analyses, daily observations were treated as
nested within participants. In the terminology of multilevel modeling, daily measures were
the level-1 units of analysis, and individuals were the level-2 units of analysis. These
analyses were conducted following guidelines offered by Nezlek (2001). All state-level
predictors were group-mean-centered, and all trait-level predictors were grand-mean-
centered, except for participant sex, which was coded –1 (women) and 1 (men).




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Solving loneliness
The first set of analyses consisted of what are called “totally unconditional” models,
that is, analyses in which there are no predictors are either level 1 or level 2. Such analyses
provide estimates of means as well as within- and between-person variance estimates.
These models are presented below:
yti = ?0i + eti,
?0i = ?00 + r0i.
In these models, y is a dependent measure, taken t times (or days) for i individuals. The
within-person variance is eti, and the between person variance is r0i. The estimated mean for
each of i persons is ?0i, and the grand mean for the sample is ?00 (the between-person mean
of the within-person means across time). The results of these analyses are summarized in
Table 3. As can be seen from these variance estimates, there was a roughly equivalent
amount of variance at the within- and between-person in all measures, suggesting that
modeling both levels could be fruitful.

Table 3. Variance decomposition for Daily Measures
Variance
decomposition
Variable Between
Within %
Between
Daily alone amount
0.40
0.50
44.4
TV for company
0.61
0.53
53.5
Self-sing 0.86
0.68
55.7
Self-talk 0.61
0.66
48.0
Positive Self-talk
0.59
0.41
58.7
Negative Self-talk
0.59
0.39
60.1

Relationships between Mean Daily Measures and Trait Measures

Relationships between mean daily measures and trait loneliness and parasocial
interaction were examined with a series of models that were unconditional at level 1 (the
day level) and included traits as predictors at level 2 (the person level). In essence, these
analyses estimated a mean for each person (averaging across four days) and then estimated
relationships between these means and the trait measures. For example, to examine
relationships between mean daily aloneness and trait loneliness, the following model was
estimated:
Daily alonenessti = ?0i + eti,
?0i = ?00 + ?01(Trait loneliness)i + r0i.
In these models, the estimated daily aloneness means for each of i persons is ?0i, and ?00 is
the grand mean of the sample for the average person (when trait loneliness is zero). The
random coefficient of interest here is ?01, which describes the relationship between the
mean of each i person’s daily aloneness scores and her or his trait loneliness scores. As
shown in Table 4, trait loneliness was significantly positively related to the mean of each
daily measure except for positive self-talk. This suggests that chronically lonely people
report more social snacking than those who are less chronically lonely. In contrast to
loneliness, trait parasocial interaction was unassociated with the mean daily measures.
Lastly, a significant sex difference was observed in one variable: Men reported more self-
talk (M = 3.09) than women (M = 2.66; ?01 = 0.21, t(64) = 2.21, p < .05, r = .27).
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Table 4. Daily Measures as a Function of Loneliness
Variable
?01
t(64)
r
Daily alone amount
0.88
4.81**
.52
TV for company
0.52
2.19*
.26
Self-sing 0.48
2.02*
.24
Self-talk 0.53
2.44*
.29
Positive Self-talk
–0.36
–1.52
–.19
Negative Self-talk
0.64
3.17**
.37
*p < .05. **p < .01.

Relationships between Daily aloneness and Other Daily Measures.
We next examined the within-person relationships between daily aloneness and
other daily measures. For example, the within-person relationship between daily aloneness
and self-talk was examined with the following model:
Daily alonenessti = ?0i + ?1i(Daily self-talk)ti + eti.
The test of whether this relationship was significantly different from zero (across all
participants) was conducted at level 2 (the between-person level). These tests concerned the
?10 coefficient from the following model:
?0i = ?00 + r0i,
?1i = ?10 + r1i.
The random coefficient of interest here is ?10, which describes the mean of the within-
person slopes across all participants. As can be seen in Table 5, daily aloneness was
significantly positively related to every daily social snacking behavior except negative self-
talk. This result suggests that the within- and between-person relationships between
loneliness and social snacking behaviors are similar, which need not necessarily be the
case, because these levels of analysis are mathematically independent.

Trait Moderation of Within-Person Relationships.
The following model examined sex differences in the within-person relationship
between daily aloneness and daily self-talk:
Daily alonenessti = ?0i + ?1i(Daily self-talk)ti + eti,
?0i = ?00 + ?01(Sex)i + r0i,
?1i = ?10 + ?11(Sex)i + r1i.
Participant sex moderated the relationship between daily aloneness and daily self-talk (?11
= –0.13, t(64) = –2.07, p < .05, r = –.25; Figure 1a), such that women exhibited a
significantly positive relationship (?10 = 0.29, t(64) = 3.58, p < .01, r = .41), whereas men
exhibited no such relationship (?10 = 0.04, t(64) = 0.44, p = .66, r = .05).







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Table 5. Daily aloneness as a Function of Other Daily Measures
Variable
?01
t(65)
r
TV for company
0.36
4.64**
.50
Self-sing 0.14
1.97*
.24
Self-talk 0.22
3.35**
.38
Positive Self-talk
0.15
2.20*
.26
Negative Self-talk
0.04
0.42
.05
*p ? .05. **p < .01.

The following model examined the extent to which individual differences in
parasocial interaction moderated the within-person relationship between daily aloneness
and self-singing:
Daily alonenessti = ?0i + ?1i(Daily self-singing)ti + eti,
?0i = ?00 + ?01(Parasocial interaction)i + r0i,
?1i = ?10 + ?11(Parasocial interaction)i + r1i.
Individual differences in parasocial interaction moderated the relationship between daily
aloneness and daily self-singing (?11 = 0.21, t(64) = 2.16, p < .05, r = .26; Figure 1b), such
that people with high (+1 SD) parasocial interaction scores had a significantly positive
relationship (?10 = 0.29, t(64) = 2.83, p < .01, r = .33), whereas people with low (–1 SD)
parasocial interaction scores had no such relationship (?10 = 0.02, t(64) = 0.28, p = .78, r =
.03).
The following model examined the extent to which individual differences in trait
loneliness moderated the within-person relationship between daily aloneness and positive
self-talking:
Daily alonenessti = ?0i + ?1i(Daily positive self-talk)ti + eti,
?0i = ?00 + ?01(Trait loneliness)i + r0i,
?1i = ?10 + ?11(Trait loneliness)i + r1i.
Individual differences in loneliness moderated the relationship between daily aloneness and
daily positive self-talking (?11 = 0.26, t(64) = 2.18, p < .05, r = .26; Figure 1c), such that
people with high (+1 SD) loneliness scores had a significantly positive relationship (?10 =
0.25, t(64) = 3.50, p < .01, r = .40), whereas people with low (–1 SD) loneliness scores had
no such relationship (?10 = -0.002, t(64) = –.02, p = .98, r = –.002).
The following model examined the extent to which individual differences in
loneliness moderated the within-person relationship between daily aloneness and watching
television for company:
Daily alonenessti = ?0i + ?1i(Daily television for company)ti + eti,
?0i = ?00 + ?01(Trait loneliness)i + r0i,
?1i = ?10 + ?11(Trait loneliness)i + r1i.
Individual differences in loneliness also moderated the relationship between daily
aloneness and daily television for company (?11 = 0.42, t(64) = 3.04, p < .01, r = .36;
Figure 1d), such that people with high loneliness scores had a significantly positive
relationship (?10 = 0.55, t(64) = 5.67, p < .01, r = .58), whereas people with low loneliness
scores had no significant relationship (?10 = 0.15, t(64) = 1.58, p = .12, r = .19).
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We have assumed that trait- and state-level measures of social isolation were
measuring slightly different phenomena. Some researchers, however, have argued that
aloneness and loneliness are not orthogonal, but instead highly related. For instance,
Marcoen, Goossens, and Caes, (1987) argued that aloneness is a state but also
simultaneously a trait. If these authors are correct, our results could be driven to some
degree by multicollinearity between daily aloneness and loneliness. To insure that
multicollinearity was not problematic in our study, we examined it, finding that it had little
impact (Tolerance = .79, VIF = 1.27; see, Cohen, Cohen, West, and Aiken, 2003).

Figure 1.
Daily aloneness as functions of (a) daily self-talk and participant sex, (b) self-
singing and trait interaction, (c) positive self-talk and trait loneliness, and (d) TV for
company and trait loneliness.

a

Self-talk x participant sex
b
Self-singing x parasocial interaction
3
3

s

s
2.42
2.33
2.38
2.31

2.17
2.11
2
2
1.66
1.65
Daily alonenes
Daily alonenes

W omen
-1 SD parasocial
Men
+1 SD parasocial
1

1
-1 SD
+1 SD
-1 SD
+1 SD

Daily self-talk
Daily self-singing

c
Positive self-talk x UCLA loneliness
d
T V for company x UCLA loneliness
3

3.09
2.75
3

s

2.26
ess
n
e
n

2
o

2
al
1.92
1.82
1.65
1.64
i
l
y

Daily alonenes

a
D

1.50
-1 SD loneliness
-1 SD loneliness

+1 SD loneliness
+1 SD loneliness
1
1

-1 SD
+1 SD
-1 SD
+1 SD
Daily positive self-talk
Daily TV for company
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