Mobile Social Media in Social Internations FINAL PAPER
1. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 2
An Applied Behavior Analysis: Reducing Mobile Social Media Application Use in the
Presence of Others
By: Kelsey Harris
Elon University
Senior Psychology Seminar 2013
2. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 3
Abstract
This study used applied behavior analysis to change a participant’s use of mobile
social media applications while in the presence of other people. The participant was
in fact the researcher. During baseline, the participant recorded data without
making any changes to the normal daily routine. The intervention involved placing
the cellular device out of sight during social interactions, as well as having to place a
$1 bill into a plastic bag for every time the social media application was accessed.
The intervention immediately decreased the number of times mobile social media
was used during social interactions with others. The results suggest that mobile
social media application use can be decreased while in the presence of others, and
maintained over a significant period of time.
3. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 4
An Applied Behavior Analysis: Reducing Mobile Social Media Application Use in the
Presence of Others
Technology has become a huge role in the lives of people today. So much, that
researchers have wondered if technology has negatively impacted communication
skills and interpersonal skills (Reich, Espinzoa & Subrahmanyam, 2012). With the
recent advancements of the Internet and cell phone use, mobile technology has
entered into a completely different realm of every day life. The rise of mobile
applications within the past decade has allowed an instant gratification for Internet
and social media users.
First, there is a need to differentiate the role of the Internet into its various
uses. Internet usage can include solitary, non-social activities such as browsing,
video games, and video streaming, but can also include social interactions through
instant messaging, e-mail, social networks, and video chat. While the choice is based
on individual preferences, there is evidence that online solitary activities are
harmful in building social relations with others (Baym, Zhang, & Lin, 2004).
Social Media
Sixty-five percent of adults in 2011 used social networking sites on the
Internet, a 35% increase compared to 2008. Today, Facebook, Twitter, and
Instagram are three of the most used social media applications by populations
4. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 5
(Wang, Tchernev, & Solloway, 2012). While all three share some similarities, they
also share many key differences.
Facebook is recognized as an online yearbook for people all over the world,
known to bring old friends back together after life changes force them apart. As one
of the most used social networks among college campuses, Facebook has become a
universal outlet for identify exploration. However, Facebook use has been
negatively correlated with initiating or starting an interpersonal relationship
(Jenkins-Guarnieri, Wright, & Hudiburgh, 2012).
College-aged individuals are faced with many challenges – adapting to new
environments, new friends, academic responsibilities, identity development, and
future career planning. While some students thrive in high-pressure environments,
others may fall victim to depression and anxious thoughts about themselves.
Facebook has been used excessively as a means for social support, mainly among
college students with depressive or anxious thoughts (Koc & Gulyagci, 2013).
Facebook use is also negatively related to college student engagement, or the real-
world effort to participate in the world to actively reach goals. Research such as this
has prompted professors and educational personnel to discover ways to infuse
Facebook and other social network sites positively into the classroom (Junco, 2012).
Twitter is another medium of social media that is specifically designed for
short bursts of information, in 140 characters or less. Many news outlets, including
CNN, NY Times, ESPN, and USATODAY, have taken to Twitter to reach the masses at
a faster rate. While researchers believe that Twitter has allowed its users to take an
even closer look into the lives of others (even celebrities), many believe that this
5. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 6
multidimensional level has created another false “world” that Twitter users fall into
(Murthy, 2012).
While there has been significantly less research done on Twitter and
Instagram as opposed to Facebook, there are implications that both mediums have
the same effect on users, as does Facebook. Instagram provides a medium for users
to share millions of pictures instantly with friends, family members, and strangers
alike. The application seemingly has people capturing every moment with their cell
phones, making every moment count (Hochman & Scwarts, 2012).
Internet addiction is a phenomenon urging concern with the growing
number of Internet and social media users. While there is no consensus on a
singular operational definition of Internet addiction, there are several factors that
have been identified to be components. The six indicators include salience, mood
change, tolerance, withdrawal symptoms, conflict, and relapse/reinstatement.
Salience is among one of the first stages when the Internet becomes one of the most
central parts of a person’s day. Mood change then accompanies use or disuse of the
activity, followed by tolerance and withdrawal symptoms. The person will
continually need higher doses of Internet usage to satisfy their addiction, and if
these high doses are not met, withdrawal symptoms occur. Conflict, both
interpersonal and intrapersonal, follows next and threatens their offline social life
(family, friends, peers, etc.). The last step, relapse/reinstatement, involves the
person referring back to their addictive behaviors, even after short periods of
restraint (Smahel, Brown, & Blinka, 2012). Wang et al. (2012) researched social
media as a vessel that fulfills our emotional, cognitive, social, and habitual needs on
6. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 7
a daily basis. While data suggests that social media is gratifying all-around,
researchers found that heavy social media use can actually lead to increasing needs
that become harder and harder to gratify. State of mind, individuality, amount of
use, and reasons for using social media are important factors relating to the
gratifications and personal needs looking to be fulfilled.
Cell Phone Applications and Presence
Social media mobile applications such as Facebook, Instagram, and Twitter
are now a part of a billion dollar industry for cell phones, and continuing to grow at
a rapid pace. From 2009 to 2010, the number of mobile application Facebook users
increased by 112%, while the number of mobile application Twitter users increased
by 347% (Anderson, n.d.).
The ever-impeding presence of cell phones has combined both the virtual
space and the physical, present world. This has led to cell phones being used
frequently during face-to-face social interactions, such as at the dinner table or
social outings, because individuals tend to think of other people and happenings
outside of their present context. Before the cell phone, it could be said physical
conversations had a higher quality, as the virtual world was less likely to interfere
with the present (Pszybylski & Weinstein, 2012). In some countries, loud cell phone
conversations in public areas have become such a nuisance that mobile technology
is banned from a respective area (i.e. movie theaters, plays, etc.). Some countries
such as France, China, Russia, and Israel permit the use of jammers, devices that
block mobile phone signals in a particular area (Srivastava, 2010). Przybylski and
Weinstein (2012) found that just the presence of cell phones can decrease the
7. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 8
feelings of closeness and trust during a face-to-face conversation, and decreases it
even more during meaningful, intimate conversations. The researchers contribute
this effect to the virtual world “colliding” with the present world. Meanwhile, in
2004, college students indicated that only 27% of online interaction took place
while in the presence of other people. This number has greatly increased in the past
decade (Baym et al., 2004).
In order to keep up with the newest technologies, society has to keep
updating its social norms surrounding the technological advances. Humphreys
(2005), in his observations of public places, noticed that people who are alone tend
to use their cell phones as a way to deflect their feelings of vulnerability and to look
occupied. Meanwhile, people who are with others in a public place may also feel this
same vulnerability if their friend leaves the table, or engages in conversation with
someone else that the original friend does not know. The latter phenomenon has
become known as cross talk (Humphreys, 2005).
In another aspect, public areas such as subways, trains, and buses pose
situations where a majority of the individuals are alone. In today’s society, it has
become the norm for people to be on their cell phones, read newspapers/books, or
listen to music to occupy their time and vulnerability. This false sense of busyness
has deterred seemingly random conversations with strangers (Banjo, Hu, & Sundar,
2008). Among these public places, cell phones are also seen as distractions in the
workplace, classroom, drivers, and among pedestrians. The risk of pedestrian
accidents greatly increases when crossing the street while simultaneously using
8. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 9
mobile Internet applications. This type of multitasking causes the pedestrian to pay
less cognitive attention to their surroundings (Byington & Schwebel, 2013).
Some gender differences have also been discovered in this area. Women
specifically use cell phones as a way to deflect unwanted attention from possible
suitors or strangers, more often then men (Srivastava, 2010). Kimbrough,
Guadagno, Muscanell, & Dill (2013) discovered that women are using social media
networks at a higher rate than men, and even used text-based cell phone
communication at a higher rate as well. Interestingly enough, both the men and
women in the study still acted within their gender roles regardless of the situation.
Women tended to use social media and text-based communication to maintain
relationships, while men tended to use it as a means to an end (Kimbrough et al.,
2013).
Interpersonal Development
Internet and cell phone usage has been found to serve several different
purposes in the lives of adolescents today. In 2012, seventy-five percent of 12-17
year-olds owned cell phones, indicating the large number of adolescents with their
own mobile device (Pea et al., 2012). Because adolescence is a key phase of the
developmental process, many researchers have focused on this age range and their
connection with Internet technology.
Reich et al. (2012) explored high school students’ Internet usage and found
that adolescents seem to use networking sites to supplement their offline
friendships and may, in fact, support emotional intimacy. Online networks also
allow people to widen their social contacts far greater than just in face-to-face
9. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 10
contexts (Reich et al., 2012). While there is a known risk that social networks
increase interactions between strangers, research shows that a majority of teens are
actually proactive in their online safety.
Past research has also been done to explore the effects of high media use and
its developmental consequences on children. The younger children are exposed to
high media use (TV, cell phone, computer, social media), the higher the risk of being
less content in relation to friendships, relationships with parents, and feelings of
sadness/unhappiness (Rideout, Foehr, & Roberts, 2010). However, researchers do
recognize that the younger generation also feels a higher need for online social
interaction compared to older populations. Adolescents and college-aged people
may find that Internet interaction has a higher value than their parents or
grandparents might believe, and in turn incorporate the Internet into their social
lives more often than others (Wang et al., 2012).
However, while there are positive implications of Internet usage on
relationships, online communication and face-to-face communication cannot be
substituted for one another. Face-to-face communication is still an integral
component of social and emotional development. Having a high and frequent
amount of face-to-face communication is positively related to greater social success,
more feelings of normalcy, and more sleep among girls aged 8-18 (Pea et al., 2012).
This study is suggestive of the positive effects of face-to-face communication among
young adults, but does not establish true cause and effect.
Geographical context also plays a role in the frequency of face-to-face
communication as a medium. Baym et al. (2004) examined social relationships
10. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 11
among college students, and found that 74% of local relationships are maintained
face-to-face, while long distance relationships are only 41% likely to use face-to-face
communication. Overall, lack of nonverbal cues, lack of emotional information, and
lack of physical interaction are all attributed to the weak “quality” of communication
from online mediums (Lee, Leung, Lo, & Xiong, 2011).
Applied Behavior Analysis
In this present study, the researcher took on the perspective of a behavior
analyst to explore the effects of mobile social media usage while with others in close
proximity. The researcher aimed to decrease the amount of social media usage
while in the presence of others, and ultimately maintain the change even after the
study. According to Chance (1998), behavior analysis can be defined as the study of
the functional relations between behavior and environmental events. Behavior
analysts focus on behavior change, and search for ways to evoke this change by
observing and manipulating the antecedents and consequences related to the
behavior. The term “antecedent” refers to the situations that happen before the
behavior occurs, while “consequence” refers to what happens after the behavior.
When performing applied behavior analysis, it is important to build a theory
around a data-based approach rather than theory testing. Behavior analysts
concentrate solely on the actual, observable behavior involved, and not the complex
issue underneath. Rather than looking at psychological reasons behind a behavior,
the data systematically provides behavior analysts with a process for treatment
(Bailey & Burch, 2009).
11. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 12
Given the recent boom in mobile social media applications, this present study
explored one participant’s use of mobile applications while in the presence of others
as the target behavior. The researcher aimed to discover the antecedents and
consequences related to the particular behavior, and if the behavior could be
modified and decreased. This study can hopefully shed light on the younger
generations constant usage of mobile phone technology and reiterate the
importance of being in the “current” moment of conversations with others.
Method
Participants
One 21-year-old female undergraduate student participated in the applied
behavior analysis out of general interest in the topic. The participant recorded her
own behavior and implemented her own intervention. The participant is in fact the
researcher.
Apparatus
The participant recorded whether or not she initiated the mobile Facebook,
Instagram, or Twitter applications during a social interaction. Social interactions
were defined as contact with one or more other person in a social context for longer
than one minute. The recording system involved the participant marking an I (yes,
used social media) or X (did not use social media) in the Notes application located
on the IPhone, as shown in Figure 1. At the end of the day, the number of “yes”
tallies was divided by the total number of social interactions, giving a percentage for
each day of testing. A Ziploc bag, dollar bills, and Hershey’s with Almond bars were
also materials used during the intervention phase. The Ziploc bag served as a
12. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 13
container for the dollar bills, which were a punishment during the intervention
phase. The Hershey’s with Almond bars were used as a reward and positive
reinforcement during intervention.
Procedure
Applied behavior analysis and modification were used solely for this
research. One participant tracked her own use of social media on cell phone
applications while in the company of others, for a 14-day period to serve as baseline
data. Every social interaction had to involve one or more other person. Social media
use was measured as the act of clicking or starting up either the Facebook,
Instagram, or Twitter application on her cell phone during the social interaction. It
is also important to note that if another person walked up and joined the
group/social interaction, it was then counted as another separate interaction than
the previous one. Example: An individual social interaction would be sitting at lunch
with two other friends. If another friend joins the group a few minutes later, it
would then be counted as two separate interactions (one before the friend joined,
one after they joined).
The intervention phase began once the baseline data collection period ended
after fourteen days. The stimulus control involved keeping the IPhone out of sight
during the social interaction, either by placing the device in a book-bag or a purse.
To positively reinforce the intervention, if the percentage of ‘YES’ interactions fell
below 30% three days in a row, the participant was allowed to have a Hershey’s
with Almond bar. As a punishment for every ‘YES’ interaction at the end of the day,
13. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 14
the participant had to place a $1 bill into a Ziploc bag and not touch it until the
conclusion of the study.
Results
Figure 2 shows the percentage of social interactions where mobile social
media applications were opened and accessed by the participant. The baseline
phase lasted a total of 14 days, while the intervention phase lasted 44 days. The
intervention phase is defined by keeping the cell phone out of sight during social
interactions with others. The dotted line in Figure 2 signifies the end of baseline
collection and the beginning of the intervention phase.
The two phases depicted two different patterns of data, seen through various
descriptive statistics in Table 1. During the baseline phase, the mobile social media
applications were accessed in an average of 67% of all social interactions, while in
the intervention phase the applications were opened in only an average of 24% of
social interactions. Baseline data collection also has a median of 75%, while the
intervention data has a median of 24%. Lastly, the mode of the baseline data
collection is 100%, while the mode of the intervention phase is 0%. The descriptive
statistics in Table 1 highlight the decrease between phases in mobile social media
use while in the presence of others.
However, there were also significant outliers that stood out in both the
baseline and intervention phase in Figure 2. During baseline, the first five days
showed a consistent percentage on or above 50. Days 6, 7, and 8 then dropped
below 50%, and returned back to 50% and above from days 9 to 14. The beginning
of the intervention phase showed an immediate and dramatic decrease in
14. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 15
percentage (100% day 14; 33% days 15 and 16). Throughout intervention, the
percentages consistently stayed on or below 50% except for days 27 and 35.
Discussion
Results indicated that the intervention successfully decreased the number of
times mobile social media was accessed during a social interaction, as expected. On
average, the intervention produced a 43% decrease compared to baseline.
The participant noticed that the actual act of keeping the cell phone out of
sight during social interactions was not tough. Rather, remembering to keep the
phone out of sight was the hardest part of conducting the intervention. Because the
cell phone is such an integral part of the participant’s life, it became a conscious act
to not automatically reach for it. Also mentioned during the intervention, the dollar
bills as a punishment effectively deterred the participant from wanting to commit
the target behavior, while the Hershey’s with Almonds bars created a valued
reward.
When assessing the contingency of the target behavior with antecedents and
consequences, the participant noted that the occurrence of the behavior was related
to the characteristics of her companions in the social context, lulls and pauses in
conversation, social contexts revolved around eating/sitting down, and when her
companions also proceeded to look at their cell phones. Humphreys’ (2005)
research concerning cell phones and social norms is supported in this study, as the
pauses in conversation indicate the vulnerability of the companions to maintain
constant conversation and feel ‘awkward’ when it is not accomplished. Meanwhile,
groupthink is a psychological phenomenon that describes the participant’s need to
15. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 16
conform with the group, as her companions also pull out their cell phones during
the social interaction (Choi & Kim, 1999). Social contexts revolved around
eating/sitting down were a perceived antecedent of the target behavior, but not an
absolute requirement. Sitting down during a social interaction creates an
environment of rest: a slight pause during a busy day of running from place to place.
During these restful periods, social interactions often last longer, and are therefore
more likely to have an increased chance at having a pause or lull in conversation
(Humphreys, 2005).
Consequences that occurred after the target behavior include feelings of guilt
and instant gratification from checking the social media applications. Instant
gratification can be most likely attributed to early signs of Internet addiction, which
may soon become the norm among the younger generation. Internet addiction
involves feelings of withdrawal and satisfaction from all aspects of the Internet,
including mobile applications (Smahel, Brown, & Blinka, 2012). The participant also
observed that the instant gratification was stronger if a post was made on social
media the day of – causing the participant to want to check the application more
often for ‘tweets, replies, or likes’. Invariably, the mobile application use seemed to
decrease the perceived meaning of the current conversation taking place in present
time; the cell phone “collided” with the real world (Przybylski & Weinstein, 2012).
There are two notable strengths within this applied behavior analysis: the
study only focused on only one participant for an extended amount of time, and the
intervention was successful in changing behavior. Focusing on one participant
allowed the study to be in depth and personal, as it was easier for the intervention
16. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 17
to inevitably be successful in changing the behavior. However, one important
limitation to mention is the study’s generalizability across participants. Because the
intervention was personal to the participant due to the value of money and
Hershey’s with Almonds bars, the intervention may not hold the same weight with
other participants. While the overall concept of the study and change in behavior is
generalizable, the intervention may not be.
It is interesting to also note that reactivity most likely played a part in the
immediate and dramatic decrease during the first days of the intervention phase.
Reactivity occurs when participants change their behavior once they are aware that
they are being observed (Chance, 1998). In this study, the participant and
researcher are one and the same, thus leaving room for an even bigger reactivity
influence.
Future research studies surrounding mobile application use should focus on
the variety of companion characteristics. Companion characteristics could vary
according to age, strength of relationship/friendship, as well as family members
versus peers. In this study, the researcher noticed that the amount of social media
activity was significantly lower when the companions were older in age, family
members, and/or had a stronger relationship to the participant. This variability will
help determine if changes in relationship influence the use of mobile social media in
the presence of others.
17. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 18
References
Anderson, D. (n.d.). “How mobile devices are impacting social media”. T-Mobile USA.
Bailey, J., & Burch, M. (2009). How to think like a behavior analyst. Understanding
the science that can change your life (pp. 3-33). New York, NY: Routledge
Taylor & Francis Group.
Banjo, O., Hu, Yifeng., & Sundar, S. (2008). Cell phone usage and social interaction
with proximate others: Ringing in a theoretical model. The Open
Communication Journal, 2, 127-135.
Baym, N., Zhang, Y., & Lin, M. (2004). Social interactions across media: Interpersonal
communication on the internet, telephone and face-to-face. New Media &
Society, 6 (3), 299-318. doi: 10/1177/1461444804041438
Byington, K., & Schwebel, D. (2013). Effects of mobile internet use on college student
pedestrian injury risk. Accident Analysis and Prevention, 51, 78-83.
Chance, P. (1998). Chapter 1 – The ABC’s of applied behavior analysis: First course in
applied behavior analysis (pp. 1-41). Long Grove, IL: Waveland Press, Inc.
Choi, J. & Kim, M. (1999). The organizational application of groupthink and its
limitations in organizations. Journal of Applied Psychology, 84(2), 297-306.
Hochman, N., & Schwartz, R. (2012). Visualizing instagram: Tracing cultural visual
rhythms. Social Media Visualization: AAAI Technical Report WS-12-03.
18. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 19
Humphreys, L. (2005). Cellphones in public: Social interactions in a wireless era.
New Media Society, 7(6), 810-833. doi: 10.1177/1461444805058164
Jenkins-Guarnieri, M., Wright, S., & Hudiburgh, L. (2012). The relationships among
attachment style, personality traits, interpersonal competency, and facebook
use. Journal of Applied Developmental Psychology, 33, 294-301.
Junco, R. (2012). The relationship between frequency of facebook use, participation
in facebook activities, and student engagement. Computers & Education, 58,
162-171. doi: 10.1016/j.compedu.2011.08.004
Kimbrough, A., Guadagno, R., Muscanell, N., & Dill, J. (2013). Gender differences in
mediated communication: Women connect more than do men. Computers in
Human Behavior, 29, 896-900.
Koc, M., & Gulyagci, S. (2013). Facebook addiction among turkish college students:
The role of psychological health, demographic, and usage characteristics.
Cyberpsychology, Behavior, and Social Networking, 16(4), 279-284.
doi: 10.1089/cyber.2012.0249
Lee, P., Leung, L., Lo, V., & Xiong, C. (2011). Internet communication versus face-to
face interaction in quality of life. Social Indicators Research.
doi: 10.1007/s11205-010-9618-3
Murthy, D. (2012). Towards a sociological understanding of social media: Theorizing
twitter. Sociology, 46(6), 1059-1073. doi: 10.1177/0038038511422553
Pea, M., Nass, C., Meheula, L., Rance, M., Kumar, A., Bamford, H., . . . Zhou, M. (2012).
Media use, face-to-face communication, media multitasking, and social well
19. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 20
being among 8- to 12 year-old girls. Developmental Psychology, 48(2), 327
336. doi: 10.1037/a0027030
Przybylski, A., & Weinstein, N. (2012). Can you connect with me now? How the
presence of mobile communication technology influences face-to-face
conversation quality. Journal of Social and Personal Relationships, 1-10.
doi: 10.1177/0265407512453827
Reich, S. Espinoza, G., & Subrahmanyam, K. (2012). Friends, iming, and hang out
face-to-face: Overlap in adolescents’ online and offline social networks.
Developmental Psychology, 48(2), 356-368. doi: 10/1037/a0026980
Rideout, V., Foehr, U., & Roberts, D. (2010) Generation M2: Media in the lives of
8-18 year olds. Retrieved from Kaiser Family Foundation website:
http://www.kff.org/entmedia/mh012010pkg.cfm
Smahel, D., Blinka, L., & Brown, B. (2012). Associations between online friendship
and internet addiction among adolescents and emerging adults.
Developmental Psychology, 48(2), 381-388. doi: 10/1037/a0027025
Srivastava, L. (2010). Mobile phones and the evolution of social behaviour.
Behaviour & Information Technology, 24 (2), 111-129.
doi: 10/1080/01449290512331321910
Wang, Z., Tchernev, J., & Solloway, T. (2012). A dynamic longitudinal examination of
social media use, needs, and gratifications among college students. Computers
in Human Behavior, 28, 1829-1839.
http://dw.doi.org/10/1016/j.chb.2012.05.001
20. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 21
Table 1
Descriptive Statistics
Baseline Intervention
Average 67% 24%
Median 75% 24%
Mode 100% 0%
21. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 22
Figure 1. Snapshot of the recording system used in the Notes application on the
participant’s IPhone. The “1” signifies an interaction where the mobile social media
application was accessed, where an “X” represents an interaction where social
media was not accessed.
22. MOBILE SOCIAL MEDIA IN SOCIAL INTERACTIONS 23
Figure 2. This graph shows the percentage of interactions where social media applications were opened. The dotted line
signifies the end of baseline collection and beginning of the intervention phase.
0
10
20
30
40
50
60
70
80
90
100
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44
PercentageofInteraconswith
SocialMediaUse
Day
Baseline Interven on