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Computers in Human Behavior 65 (2016) 232e240

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Computers in Human Behavior

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Social media use, community participation and psychological well-being among individuals with serious mental illnesses

Eugene Brusilovskiy a, *, Greg Townley b, Gretchen Snethen a, Mark S. Salzer a

a Department of Rehabilitation Sciences, Temple University, United States b Department of Psychology, Portland State University, United States

a r t i c l e i n f o

Article history: Received 9 March 2016 Received in revised form 22 August 2016 Accepted 24 August 2016 Available online 30 August 2016

Keywords: Social media Community participation Civic engagement Psychosocial outcomes Serious mental illnesses

* Corresponding author. Department of Rehabilitat sity, 1700 N. Broad St., Suite 313C, Philadelphia, PA 19

E-mail address: [email protected] (E. Brusilov

http://dx.doi.org/10.1016/j.chb.2016.08.036 0747-5632/© 2016 Elsevier Ltd. All rights reserved.

a b s t r a c t

Background: Little research exists on social media (e.g., Facebook, Twitter, etc.) use among individuals with serious mental illnesses (SMI). One particular question of interest is the extent to which online social media use is associated with these individuals' community participation, civic engagement and psychosocial outcomes. Methods: Two-hundred and thirty-two individuals with SMI receiving services at 18 mental health or- ganizations throughout the continental U.S. completed questionnaires on their community participation, civic engagement, quality of life, loneliness, and psychiatric symptoms. They were also asked which social media sites they used; the duration, frequency and importance of, and reasons for, social media use; and the number of contacts they had on social media. Results: Approximately a third of the sample reported having at least one social media account. Greater frequency, intensity and longevity of social media were associated with higher levels of community participation, and greater intensity of social media use was positively associated with civic engagement. For instance, those who used social media at least 30 min a day had 16.4 more days of participation and voting rates that were higher by 17.4%. Social media use was not found to be significantly associated with loneliness, psychiatric symptoms or quality of life. Discussion and implications: Greater social media use appears to be associated with greater community engagement without negative repercussions on loneliness, symptoms, or quality of life. Interventions that support social media use among individuals with SMI could have important community integration benefits.

© 2016 Elsevier Ltd. All rights reserved.

1. Introduction

Studies examining computer use among individuals with serious mental illnesses (SMI) e conditions which include major depression, bipolar disorder and schizophrenia-spectrum disor- ders, and which have resulted in a substantial and persistent interference with the ability to participate in major life activities e began more than a decade ago with findings that these individuals use computers (Salzer, Simiriglia, & Solomon, 2003) and have at- titudes towards computers that are similar to those of other groups (Salzer & Burks, 2003). Reasons for Internet use among persons with SMI vary, ranging from obtaining news to online shopping to

ion Sciences, Temple Univer- 121, USA. skiy).

checking the weather, with some even using it to take online courses or make phone calls (Cook et al., 2005). Many go online to receive information about mental health issues and medication (e.g., Cook et al., 2005; Berger, Wagner, & Baker, 2005; Schrank, Sibitz, Unger, & Amering, 2010), and some have participated in the growing number of online interventions targeting the various needs of this population, such as parenting skills (e.g., Kaplan, Solomon, Salzer, & Brusilovskiy, 2014), peer support (e.g., Kaplan, Solomon, Brusilovskiy, Cousonis, & Salzer, 2011), and psychother- apy (e.g., Barak, Hen, Boniel-Nissim, & Shapira, 2008).

Individuals with SMI also use the Internet to access various social media platforms. Even though there is relatively sparse data on social media use and its health-related correlates among in- dividuals with SMI, according to the Pew Research Center (2014), 74% of all U.S. adults have at least one social media account. There are seemingly widespread concerns, and some evidence, that in the general population, greater use of social media may undermine

E. Brusilovskiy et al. / Computers in Human Behavior 65 (2016) 232e240 233

subjective well-being (e.g., Kross et al., 2013), enhance loneliness and depression (e.g., O'Keeffe & Clarke-Pearson, 2011; Yao & Zhong, 2014), and monopolize time that would otherwise be devoted to face-to-face interaction with others and to participation in mean- ingful community activities. However, while some evidence does point to a relationship between social media use and more clinical symptoms of certain psychiatric disorders, at least in some in- dividuals (e.g., Rosen, Whaling, Rab, Carrier, & Cheever, 2013; Sidani et al., 2016), numerous empirical studies have found that the relationship between social media use and various health- related factors appears to be positive in the general population. A lot of people use social media because they enjoy it and find it useful (e.g., Lin & Lu, 2011). Social media appears to have positive effects on the maintenance of offline relationships (Burke, Marlow, & Lento, 2010; Ellison, Steinfield, & Lampe, 2007) and the devel- opment and cultivation of loose relationships (Steinfield, Ellison, & Lampe, 2008; Shaw & Gant, 2002; Subrahmanyam, Reich, Waechter, & Espinoza, 2008; Kietzmann, Hermkens, McCarthy, & Silvestre, 2011) e that is, relationships that are not necessarily central to an individual's life but which nonetheless provide sup- port to promote a sense of belonging and social inclusion (e.g., Granovetter, 1973; Townley, Miller, & Kloos, 2013). Plausibly as a result of this, using social media is associated with lower levels of loneliness (e.g., Ryan & Xenos, 2011; Shaw & Gant, 2002; Burke et al., 2010), enhanced self-esteem (Barker, 2009; Shaw & Gant, 2002; Steinfield et al., 2008), and more frequent participation in the local community, institutions and spaces (Hampton, Sessions, Her, Rainie, 2009), including greater opportunities to identify available resources within the community (Kietzmann et al., 2011).

However, there is some literature which suggests that Internet and social media use in the SMI population may be lower than in the general population (e.g., Martini et al., 2013; Miller, Stewart, Schrimsher, Peeples, & Buckley, 2015). The reasons and motiva- tion for social media use may also be different, with individuals with SMI often using this technology to connect to peers with similar conditions or to seek out information on their symptoms and treatment from professionals (e.g., Birnbaum, Rizvi, Correll, & Kane, 2015; Schrank et al., 2010). However, social interactions of individuals with SMI may be facilitated or enhanced online and in particular, on social media, because these individuals tend to have diminished social networks and limited availability of social sup- port outside of mental health providers and family members (Highton-Williamson, Priebe & Giacco, 2015). This could be because online relationships do not require verbal communication or im- mediate responses, which may be more difficult due to the symp- toms of mental illnesses; because social media interactions can often be anonymous; or because stigma and fear associated with mental illnesses might be less pronounced online than in face-to- face communication, enabling persons with SMI to interact with individuals from other social groups (Highton-Williamson, Priebe & Giacco, 2015; Naslund, Grande, Aschbrenner, & Elwyn, 2014).

Some apparent benefits of social media use, and the positive associations of social media use with various health-related out- comes in the SMI population, are also described in several empirical studies. For instance, in a study of 80 individuals with schizo- phrenia, 47% of participants reported having a social media account and 27% reported using social media daily, with many users indi- cating that social media helped them with interacting and social- izing with their friends and family members (Miller et al., 2015). In another study of 140 young adults with SMI, it was reported that 93.4% of the sample used social media (Gowen, Deschaine, Gruttadara, & Markey, 2012). Ninety-four percent of these re- spondents believed social media use helped them feel less isolated, and that some of the most enjoyable features of social media included communicating with other users (usually via private

message or public posts), making new friends, and having shared interests. The study also presented desired features and topics to be included in a social networking site for young adults with mental illness, including independent living skills, strategies to overcome social isolation, and resources on transitioning to adulthood. Another study examining the use of social media for peer support among persons with SMI analyzed comments posted to 19 YouTube videos uploaded by individuals who identified as having schizo- phrenia, schizoaffective disorder, or bipolar disorder and who talked about their experiences with mental illness in the videos (Naslund et al., 2014). The authors reported four themes related to peer support: minimizing isolation and offering hope; finding support through peer exchange; sharing strategies for coping; and lessons from shared experiences of using medication and seeking mental health services. A study examining pathways to care for youth with SMI reported that nearly three-quarters of the surveyed youths supported the idea of receiving help or advice from mental health professionals via social media (Birnbaum et al., 2015). Furthermore, peer-led interventions have utilized social media to supplement mental health services and have been found to be associated with greater socialization and social connectedness (Alvarez-Jimenez et al., 2014).

Some studies also discuss the association between social media and psychiatric symptoms in the SMI population. For instance, in a sample of youths with schizotypal personality disorder, greater chat room participation was correlated with more psychiatric symptoms (Mittal, Tessner, & Walker, 2007). In semistructured interviews conducted with an Austrian sample of 26 individuals with schizophrenia or schizoaffective disorder, some individuals also indicated that certain online activities, such as reading infor- mation on illness, would increase their symptoms; however, this didn't seem to be the case for the majority of the study participants (Schrank et al., 2010).

One understudied area is the extent to which social media use of individuals with SMI is related to their community participation, including their involvement in recreational, social, vocational, civic and other areas of community life. Among people with SMI, greater community participation is associated with better psychosocial outcomes, such as perceived recovery and quality of life (e.g., Burns-Lynch, Brusilovskiy, & Salzer, in press; Salzer, Baron, Menkir, & Breen, 2014). Numerous other studies have also discussed the psychosocial well-being and recovery-related benefits of working (e.g., Eklund & Hansson, 2001; Provencher, L., Gregg, Mead, & Mueser, 2002), attending school (e.g., Cook & Solomon, 1993), having social relationships (e.g., Yanos, Rosenfield, & Horwitz, 2001), and being actively involved in leisurely and recreational activities (e.g., Iwasaki, Coyle, & Shank, 2010) in this population. While some new literature suggests that social media can promote community integration of individuals with SMI (Snethen & Zook, 2016), and a handful of case reports have documented the posi- tive effects of social media use on social interactions that have eventually led to substantially greater community participation in these individuals (Daley et al., 2005; Veretilo & Billick, 2012), there is a lack of larger empirical studies to assess these relationships.

The goal of this study is to extend our knowledge about the relationship between social media use and various psychosocial outcomes and community engagement among individuals with SMI. Specifically, the current study uses data from a national sample to test two hypotheses based on the aforementioned research results:

H1. Higher levels of social media use will be associated with better psychosocial outcomes, specifically lower levels of loneliness and psychiatric symptoms, and better quality of life.

H2. Higher levels of social media use will be associated with

E. Brusilovskiy et al. / Computers in Human Behavior 65 (2016) 232e240234

greater community participation and civic engagement.

Results of this study will be of value to those who are interested in gaining a better understanding of how individuals with SMI engage with social media and the extent to which social media may be associated with different health-related variables.

2. Methods

2.1. Participants and procedures

Participants in this study were 232 individuals receiving pub- licly funded mental health services at 18 mental health organiza- tions from 13 states who were recruited to take part in a larger study examining factors affecting community participation. An attempt was made to maximize geographic diversity and levels of urbanicity, as defined by the 2013 United States Department of Agricultural (USDA) Rural-Urban Continuum Codes (RUCCs) (USDA, 2016) by reaching out to potential organizations via email cam- paigns, listserv announcements, and targeted outreach, especially to agencies in less urban settings. Organizations interested in participating contacted the research team for more information. Those agencies that agreed to participate distributed flyers to po- tential eligible participants across their various programs.

Individuals interested in the study from each agency contacted a research assistant to be screened using the following inclusion criteria: 1) adults aged 18e64, 2) with a self-reported diagnosis of schizophrenia-spectrum (295.XX) or major affective (296.XX) dis- order 3) resulting in a substantial interference with or limitation in their ability to participate in any major life activities such as work, school, recreation, social activities, religious activities, family re- lationships, or caring for themselves, 4) that was in the past 12 months, 5) who were eligible for Medicaid or a state-equivalent publicly funded benefit program, and 6) willing to provide their home address for the larger study. Individuals who had a legal guardian or couldn't provide informed consent were excluded (see Fig. 1). After going through the informed consent process, partici- pants were asked to complete an hour-long telephone survey, which asked them, among other things, about their perceptions of

Fig. 1. Participant recru

their communities, their health and functioning, psychiatric symptoms, their psychosocial well-being, community participa- tion, civic engagement, and social media use. Individuals were paid $20 for their time. Between 1 and 31 individuals were recruited from each of the mental health 18 organizations. Even though the sampling methodology used in this study may have limitations when it comes to generalizability, we chose this approach because using a probability sample when recruiting from multiple agencies would have entailed significant logistical barriers, such as sub- stantial agency staff time and effort, which in turn would have limited our ability to recruit a sufficiently large sample. Therefore, in order to obtain a sufficiently large sample, we opted for a non- probability sample. The study received Institutional Review Board approval from the lead author's university.

2.2. Measures

2.2.1. Social media use Participants were asked which social media platforms they used

and which one they used most often. Social media were defined for the participant as online social networking sites such as Facebook, Twitter, LinkedIn, and others. In addition, they were asked to specify the frequency of their social media use (with categories ranging between several times a day and never), intensity of use on an average day (with categories ranging between less than 15 min and more than 2 h), and for how long they have been using social media (with longevity categories ranging between less than 6 months and more than 2 years). Lastly, we also asked individuals questions about the importance of social media use and reasons for social media use (e.g., to see what their contacts are up to; to share things about themselves; to feel less lonely, etc.), as well as the total number of contacts they had on all social media platforms they used. The social media items appear to have face validity and were developed by the authors after carefully reviewing the existing questionnaires on social media use. Some of the items e particu- larly on frequency, number of contacts, and reasons for social media use e were modified from similar questions used in other studies (Ryan & Xenos, 2011; Kross et al., 2013; Pew Research Center, 2014).

itment flow chart.

E. Brusilovskiy et al. / Computers in Human Behavior 65 (2016) 232e240 235

2.2.2. Loneliness A four item version of the UCLA Loneliness Scale (Russell,

Peplau, & Ferguson, 1978) was included in the survey. Each of the four items was rated on a 4-point scale, with higher values indic- ative of greater loneliness. Items asked about how often individuals felt left out and isolated from others, and how often they felt that there are people that really understand them or that they can talk to. A composite score was created as the average of the 4 items. The original UCLA Loneliness Scale demonstrates good validity and reliability (e.g., Russell, 1996; Russell, Peplau, & Cutrona, 1980).

2.2.3. Quality of life Quality of life was measured with the first item of Lehman's

(1988) Quality of Life (QOL) Interview. The item asks respondents to rate how they feel about their life in general on a 7-point Likert- type scale (1 ¼ terrible; 7 ¼ delighted). Published studies have used this item as an indicator of overall quality of life (e.g., Evensen et al., 2012).

2.2.4. Psychological distress Psychological distress was assessed with the 25 item version of

the Hopkins Symptoms Checklist (HSCL-25), a widely used instru- ment that measures distress resulting from a wide range of symptoms (Derogatis, Lipman, Rickels, Uhlenhuth, & Covi, 1974). Numerous studies have been carried out with different populations to demonstrate the reliability and validity of this measure (e.g., Veijola et al., 2003; Lee, Kaaya, Mbwambo, Smith-Fawzi, & Lesha- bari, 2008). Each of the questions asks the respondents to indicate how much they were bothered or distressed by a particular symptom, and is rated on a four-point Likert scale, where 1 is ‘not at all’ and 4 is ‘extremely’. The composite HSCL-25 score was computed by averaging the scores on the 25 items, with lower scores indicative of fewer symptoms. Scores higher than 1.75 are indicative of psychiatric caseness, or a substantial level of psychi- atric distress. (Hesbacher, Rickels, Morris, Newman, & Rosenfeld, 1980; Winokur, Winokur, Rickels, & Cox, 1984).

2.2.5. Community participation In this study, we used the modified, 22-item version of the

Temple University Community Participation (TUCP) Scale (Salzer, Brusilovskiy, Prvu-Bettger, & Kottsieper, 2014). The TUCP inquires about the number of days of participation in the past 30 days in 22 different areas (shopping, work, religious activities, visiting a family or friend, etc.) without a staff person and was found to have good reliability and validity (Salzer, Brusilovskiy, et al., 2014; Salzer, Kottsieper, & Brusilovskiy, 2015; Burns-Lynch, Brusilovskiy, & Salzer, in press). For the current study, we calculated two partici- pation constructs. They are 1) the total number of days of partici- pation, computed as the sum of participation days across all 22 items, with possible scores on this construct ranging between 0 and 660 (30 days x 22 participation areas), and 2) the total number of different areas in which a person participated at least once in the past 30 days. Possible scores on this second construct range be- tween 0 and 22. Unlike the “days of participation” construct that measures the total amount of participation, this construct measures variety of participation.

2.2.6. Civic engagement We asked three yes/no questions about participants' civic

engagement. These questions were: 1) “Did you vote in your most recent local or municipal election?”; 2) “Have you picketed or protested in your community in the last year?”; and 3) “Have you donated money in your community in the last year?”. These items are not combined into a scale in this study; each of these items is used separately to measure a different aspect of civic engagement,

and has face validity. Similar items have been used in past studies assessing civic engagement (e.g., Brusilovskiy & Salzer, 2012; Flanagan & Bundick, 2011).

2.3. Analyses

In order to provide a descriptive picture of social media use among participants of our study, proportions of individuals using the various social media platforms, as well as the tabulations of the reasons for, and importance, frequency, intensity and longevity of, social media use were calculated. Independent samples t-tests and chi-square tests were conducted to address both hypotheses, comparing the psychosocial, community participation and civic engagement variables of individuals who have 1) high vs. low fre- quency of social media use (i.e., use at least weekly vs. use less than weekly or have no social media account), 2) high vs. low intensity of social media use (i.e., use at least 30 min per day vs. use less than 30 min a day or have no social media account), and 3) high vs. low longevity of social media use (i.e., have used for at least six months vs. have used for less than six months or have no social media ac- count). Given the lack of research in this area for this population, decisions regarding these high and low cut-offs were data driven and in service of creating distinct groups that could be compared in the analyses that follow.

3. Results

3.1. Sample description

A number of demographic, employment and diagnostic vari- ables are presented in Table 1. The table presents this information for the entire 232-person sample, and also separately for the 77 individuals who had at least one social media account and the 155 individuals without a social media account. Over 60% of the sample lived in urban counties (RUCC 1 or 2), while the rest lived in sub- urban or rural counties. 61.3% of the participants were female and the rest were male; more than two-thirds were white and about a quarter were black; and approximately a third were married or had a significant other. Less than a fifth of the sample were employed at the time of the survey. 70.0% of the sample had scores of 1.75 or higher on the Hopkins Symptoms Checklist, indicating psychiatric caseness. Of all the variables presented in the table, individuals who had at least one social media account differed from those who did not have one only in education, with substantially greater pro- portions of individuals with a social media account having more than a high school education. Individuals who had at least one social media account were also significantly younger than those who did not (mean age was 42.4 (SD ¼ 11.4) and 48.3 (SD ¼ 10.9) years, respectively; t(142) ¼ 3.76, Cohen's d ¼ 0.53, p < 0.001); the average age of the entire sample was 46.4 (SD ¼ 11.4) years. Means, standard deviations, and zero-order correlations of the key study variables are included in Table 2.

3.2. Social media use e descriptive statistics

As mentioned above, a total of 77 participants (33.2%) reported having at least one social media account, while 155 did not. Of the 77 who had an account, 75 (97.4%) used Facebook, 20 (26.0%) used Twitter, 20 (26.0%) used Googleþ, 16 (20.8%) used Pinterest, 12 (15.6%) used LinkedIn, 11 (14.3%) used Instagram, 8 (10.4%) used MySpace, 7 (9.1%) used MeetUp, 7 (9.1%) used SnapChat, and 5 (6.5%) used Reddit. When asked which site was used most often, 71 (92.2%) said Facebook, 3 (3.9%) said Googleþ, 2 (2.6%) e Twitter, and 1 (1.3%) e MeetUp. The majority of those who had a social media account said that it was important (n ¼ 19, 24.7%) or very

Table 1 Demographics, education, employment and diagnosis by social media use.

Whole sample (N ¼ 232)

1 þ social media Account (N ¼ 77)

No social media Account (N ¼ 155)

Chi-square tests

N % N % N % c 2 DF P-Value

Urban 140 60.34% 42 54.55% 98 63.23% 1.62 1 0.20 Female Gender 141 61.30% 51 66.23% 90 58.82% 1.19 1 0.28

Race White 158 68.10% 58 75.32% 100 64.52% 2.77 1 0.10 Black 56 24.24% 15 19.74% 41 26.45% 1.25 1 0.26 Native American 9 3.90% 2 2.63% 7 4.52% 0.48 1 0.49 Pacific Islander 1 0.43% 0 0.00% 1 0.65% 0.49 1 0.48 Asian 3 1.30% 2 2.63% 1 0.65% 1.57 1 0.21 Other Race 10 4.35% 1 1.32% 9 5.84% 2.51 1 0.11

Hispanic/Latino Ethnicity 16 6.93% 4 5.26% 12 7.74% 0.49 1 0.49 Married or Has Significant Other 73 31.60% 28 36.84% 45 29.03% 1.44 1 0.23

Education Less than High School 53 22.94% 11 14.47% 42 27.10% 15.96 2 <0.001 High School or Equivalent 78 33.77% 18 23.68% 60 38.71% More than High School 100 43.29% 47 61.84% 53 34.19%

Working for Pay 42 18.26% 19 25.33% 23 14.84% 3.73 1 0.06

Diagnosis Depression 91 39.22% 33 42.86% 58 37.42% 0.64 1 0.42 Bipolar 122 52.59% 42 54.55% 80 51.61% 0.18 1 0.67 Schizophrenia 60 25.86% 14 18.18% 46 29.68% 3.54 1 0.06 Schizoaffective Disorder 45 19.40% 18 23.38% 27 17.42% 1.17 1 0.28 Additional Diagnosis 11 4.74% 2 2.60% 9 5.81% 1.17 1 0.28

HSCL-25 Scores Above 1.75 161 70.00% 54 71.05% 107 69.48% 0.06 1 0.81

Table 2 Descriptive statistics and zero-order correlations (N ¼ 232).

Mean SD 1 2 3 4 5 6 7 8 9 10 11

1. Frequency of Social Media Use (At Least Weekly) 0.29 0.45 e 2. Intensity of Social Media Use (At Least 30 Minutes a Day) 0.20 0.40 0.71*** e 3. Longevity of Social Media Use (At Least 6 Months) 0.31 0.47 0.88*** 0.71*** e 4. TU Scale - Total number of participation days 53.06 40.99 0.16* 0.16* 0.14* (0.71) 5. TU Scale - Total number of participation areas 7.60 3.50 0.14* 0.12 0.16* 0.66*** e 6. Quality of Life Item 1 - How do you feel about your life in general? 4.32 1.61 �0.02 �0.05 �0.03 0.25*** 0.28*** e 7. HSCL-25 Scale Score 2.15 0.65 �0.04 0.00 �0.04 �0.19** �0.25*** �0.52*** (0.94) 8. UCLA Index Score 2.51 0.71 �0.10 0.00 �0.07 �0.23*** �0.27*** �0.46*** 0.53*** (0.69) 9. Voted in your most recent local or municipal election 0.33 0.47 0.07 0.15* 0.03 0.13* 0.18** 0.06 �0.09 �0.11 e 10. Picketed or protested in your community in the last year 0.04 0.20 0.10 0.16* 0.08 0.23*** 0.19** 0.13 �0.10 �0.17* 0.21** e 11. Donated money in your community in the last year 0.31 0.46 0.09 0.06 0.07 0.17* 0.17* 0.10 �0.15* �0.04 0.04 0.09 e

Notes: * < 0.05. ** < 0.01. *** < 0.001. Standardized Cronbach's alphas are shown in the diagonal where applicable.

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important (n ¼ 31, 40.3%) to them, whereas 16 (20.8%) said it was of little importance and 11 (14.3%) said it was unimportant. The average number of contacts e friends, followers, etc. e that the participants had on social media was 171.4 (SD ¼ 252.6), with the median being 100 contacts. Table 3 presents the frequency, in- tensity and longevity of social media use. Approximately 29%, 20% and 31% of the entire 232 person sample reported having high frequency, intensity and longevity of social media use, respectively. It is noteworthy that out of the 77 individuals who had at least one social media account, nearly two-thirds used social media at least once a day, nearly 60% spent at least 30 min a day on it, and only 3 individuals reported using it for less than 6 months.

Table 4 shows that in the entire sample, the average age was significantly lower among individuals who had greater frequency, intensity and longevity of social media use.

The reasons for social media use varied greatly among

participants. Slightly over half (n ¼ 41, 53.2%) of the 77 person sample said that they use social media to share things about themselves a least once a week. On the other hand, 62 participants (80.5%) reported using social media at least once a week to see what their contacts are doing or to look at their photos and other posts, while 46 (62.2%) use it to learn more about people they meet or know in real life. 44 (59.5%) use it at least weekly to keep up with the news, and nearly half of the sample (n ¼ 35, 47.9%) re- ported using it to keep up with the current social trends. Many indicated that they use social media at least weekly to feel less lonely (n ¼ 47, 63.5%) or because there was nothing better to do (n ¼ 56, 74.7%). Most of the sample used it less than weekly for professional reasons (n ¼ 54, 77.1%), to meet new people (n ¼ 49, 70.0%), or to learn about things going on in the community, such as new businesses or social, cultural, religious or political events (n ¼ 42, 59.2%).

Table 3 Frequency, intensity and longevity of social media use.

N %

How often do you use social media? High Frequency 67 28.88% Several times a day 37 15.95% About once a day 15 6.47% 3e5 days a week 6 2.59% 1e2 days a week 9 3.88%

Low Frequency 165 71.12% Every few weeks 6 2.59% Less often 4 1.72% No social media account 155 66.81%

How much time per day do you spend on social media? High Intensity 46 19.83% More than 2 h 20 8.62% Between 1 and 2 h 17 7.33% Between 30 min and 1 h 9 3.88%

Low Intensity 186 80.17% Between 15 and 30 min 17 7.33% Less than 15 min 14 6.03% No social media account 155 66.81%

For how long have you been using social media? High Longevity 73 31.47% More than two years 62 26.72% Between a year and two years 6 2.59% Between 6 months and a year 5 2.16%

Low Longevity 158 68.10% Less than 6 months 3 1.29% No social media account 155 66.81%

E. Brusilovskiy et al. / Computers in Human Behavior 65 (2016) 232e240 237

3.3. Psychosocial outcomes and levels of community participation and civic engagement

As reported in Table 2, in the entire 232-person sample, the average scores were 2.50 (SD ¼ 0.71) out of 4 on the UCLA Lone- liness Measure, 4.32 (1.61) out of 7 on the Quality of Life item, and 2.15 (0.65) out of 4 on the Hopkins Symptoms Checklist. The average number of days of participation was 53.06 (SD ¼ 40.99) days out of a potential 660 days, and the average number of participation areas was 7.60 (SD ¼ 3.50) out of a potential 22 areas. For the civic engagement items, 77 individuals (33.62%) voted in the most recent local or municipal election, 10 (4.3%) picketed or protested in their communities in the last year, and 72 (31.0%) donated money in their community in the last year. None of the psychosocial outcomes, participation or civic engagement variables were associated with any of the demographic characteristics.

3.4. Social media use and psychosocial outcomes, participation, and civic engagement

Table 5 presents the associations between social media use and psychosocial outcomes and community participation. Loneliness,

Table 4 Average age by social media use.

Mean S

Frequency of Use At Least Weekly 42.0 1 Less than Weekly or No Social Media Account 48.1 1

Intensity of Use At Least 30 Mins/Day 41.2 1 Less than 30 Mins/Day or No Social Media Account 47.6 1

Longevity of Use At Least 6 Months 42.2 1 Less than 6 Months/No Social Media Account 48.3 1

quality of life and psychiatric symptoms were not found to be associated with frequency, intensity or longevity of social media use. Compared with individuals who do not have social media ac- counts or who use them less than weekly, participants who use their accounts at least once a week reported a higher number of community participation days and participation areas. Greater in- tensity of social media use was associated with higher number of participation days; and greater longevity of social media use was positively associated with both the number of participation days and the number of participation areas. The associations between social media use and civic engagement are shown in Table 6. Fre- quency and longevity of social media use were not associated with any of the civic engagement variables; however, those who re- ported using social media at least 30 min a day were significantly more likely to have voted in the most recent municipal election and picketed or protested in the community in the past year.

4. Discussion

The results from this study extend research on the relationship between social media use and psychosocial outcomes, community participation, and civic engagement among individuals with SMI. Overall, as expected, greater frequency, intensity, and longevity of social media use was not associated with loneliness, symptoms, or quality of life. Greater intensity and longevity of social media use was positively correlated with more days of community partici- pation. And higher intensity of use was associated with greater civic engagement. The findings suggest that contrary to some specula- tion, social media use may not be harmful and does not appear to be negatively associated with psychosocial well-being. On the con- trary, substantial proportions of our sample said that they use social media at least weekly to feel less lonely, to keep in touch with friends and family, or to learn more about people they know in real life. Social media use may make individuals feel closer to people who are important to them and may help with the development of new relationships. This is consistent with how individuals use so- cial media in the general population (Ellison et al., 2007). One broad motivation for social media usage is the opportunity to cultivate and share one's identity (Nadkarni & Hofmann, 2012), and in this study, more than half of participants used social media to share information about themselves. Positive associations between social media use and community participation and civic engagement may be due to the fact that individuals find out about e or are invited to e various community events and activities on social media. How- ever, it should be noted that a relatively small proportion (40.8%) of our sample used social media to learn about events going on in their communities.

Knowing the different reasons for why individuals with SMI use social media has practical benefits for service providers, as they may be able to think of creative ways in which clients can utilize

D T-test

t DF P-Value Cohen's d

1.6 3.68 111 <0.001 0.54 0.9

2.1 3.26 63 0.002 0.56 0.9

1.6 3.75 126 <0.001 0.54 0.8

Table 5 Association between social media use with psychosocial outcomes, community participation and civic engagement.

Frequency of social media use Less than weekly At least weekly Test statistics

N ¼ 165 N ¼ 67 Mean SD Mean SD t DF P-Value Cohen's d

UCLA Loneliness Index 2.55 0.69 2.39 0.73 1.53 116 0.13 0.23 Quality of Life 4.35 1.63 4.27 1.59 0.31 122 0.76 0.05 HSCL-25 Scale Score 2.16 0.67 2.11 0.60 0.55 132.3 0.58 0.08 TU Scale - Total number of participation days 48.8 38.2 63.5 45.8 �2.31 105.3 0.02 0.35 TU Scale - Total number of participation areas 7.29 3.37 8.36 3.72 �2.03 112.4 0.04 0.30 Intensity of social media use Less than 30 Mins/

Day 30 þ Minutes/Day Test statistics

N ¼ 186 N ¼ 46 Mean SD Mean SD t DF P-Value Cohen's d

UCLA Loneliness Index 2.51 0.69 2.50 0.77 0.05 64.35 0.96 0.01 Quality of Life 4.37 1.64 4.15 1.52 0.85 73.22 0.40 0.14 HSCL-25 Scale Score 2.15 0.65 2.16 0.65 �0.05 69.11 0.96 0.02 TU Scale - Total number of participation days 49.8 37.9 66.2 49.8 �2.08 58.6 0.04 0.37 TU Scale - Total number of participation areas 7.39 3.31 8.43 4.11 �1.59 60.34 0.12 0.28 Longevity of social media use 6 Months or less 6 þ Months Test statistics

N ¼ 159 N ¼ 73 Mean SD Mean SD t DF P-Value Cohen's d

UCLA Loneliness Index 2.54 0.69 2.43 0.74 1.00 130.8 0.32 0.15 Quality of Life 4.36 1.64 4.25 1.56 0.48 143.3 0.63 0.07 HSCL-25 Scale Score 2.17 0.66 2.11 0.63 0.68 144.6 0.50 0.09 TU Scale - Total number of participation days 49.1 38.7 61.6 44.7 �2.06 123.6 0.04 0.30 TU Scale - Total number of participation areas 7.23 3.34 8.41 3.73 �2.32 127.2 0.02 0.33

Table 6 Association between social media use with civic engagement.

Frequency of social media use Less than weekly At least weekly Test statistics

N ¼ 165 N ¼ 67 N % N % c 2 DF P-Value

Voted in most recent municipal election 52 31.5 25 39.1 1.77 1 0.28 Picketed or protested in your community in the past year? 5 3.0 5 7.5 2.27 1 0.13 Donated money in your community in the past year? 47 28.5 25 37.3 1.74 1 0.19

Intensity of social media use Less than 30 Mins/ Day

30 þ Minutes/Day Test statistics

N ¼ 186 N ¼ 46 N % N % c 2 DF P-Value

Voted in most recent municipal election 56 30.3 21 47.7 4.85 1 0.03 Picketed or protested in your community in the past year? 5 2.7 5 10.9 5.98 1 0.01 Donated money in your community in the past year? 55 29.6 17 37.0 0.94 1 0.33

Longevity of social media use 6 Months or less 6 þ Months Test statistics N ¼ 159 N ¼ 73 N % N % c 2 DF P-Value

Voted in most recent municipal election 52 32.7 25 35.7 0.20 1 0.66 Picketed or protested in your community in the past year? 5 3.1 5 6.9 1.66 1 0.20 Donated money in your community in the past year? 46 28.9 26 35.6 1.04 1 0.31

E. Brusilovskiy et al. / Computers in Human Behavior 65 (2016) 232e240238

social media for enhancing social support, community participa- tion, and potentially even labor force participation. In particular, people may be encouraged to use social media to search for com- munity events that might be of interest to them, or to look for employment or educational opportunities listed on social media sites. Further, social media may be an appropriate platform for delivering interventions that target social support or community participation, especially for younger individuals with SMI who are more likely to be social media users.

The study is also among the first to examine the general patterns

of social media use in this population. The findings suggest that approximately a third of the participants in our sample have at least one social media account, and nearly two-thirds of these in- dividuals indicated that having a social media account is either important or very important. Furthermore, 87% of social media account holders use it at least weekly, 60% use it for at least 30 min a day, and the vast majority (96%) have had a social media account for at least two years.

Even though the study does not aim to estimate the prevalence of social media use in the SMI population, we found that 33.2% of

E. Brusilovskiy et al. / Computers in Human Behavior 65 (2016) 232e240 239

our sample are social media users. We note that this number is substantially lower than corresponding estimates in the most recent study of the general population (74%; Pew Research Center, 2014) and a study of social media use among young adults with SMI (93.4%; Gowen et al., 2012). These discrepancies are likely due to several factors. First, the individuals in our study are recipients of publicly funded mental health services, indicating income levels which are substantially lower than those of the general population. Second, when compared with the sample in the Gowen et al. (2012) study, the individuals in our study were substantially older. Similar to the Cook et al. (2005) study, Gowen et al. (2012) also adminis- tered their survey online, thereby precluding any individuals who do not currently use the Internet from participating and resulting in a potentially biased estimate of social media use.

The finding that younger participants were more likely to use social media was not surprising; however, this may indicate that young adults with SMI may be accustomed to social media and desire it as a complement to treatment. In addition to finding increased social media use among younger participants, we also found that individuals with more education were more likely to use social media. This may be due to the fact that those who received more education may have had greater exposure to computers and the Internet while getting their degrees and may be more comfortable with social media use. These individuals may also have more resources that allow them to afford regular access to social media.

Even though our sample might not be representative of all in- dividuals with SMI in terms of how much they use social media, we do not have any reason to believe that this will have an impact on the relationship between social media use, community participa- tion, civic engagement and psychosocial outcomes. Future studies should attempt to utilize probability sampling to determine whether findings are substantially different from those reported here. Future research should also examine the psychometric properties of the items assessing social media use that were developed for and used in this study.

The study has a number of limitations that are worth noting. First, while it includes individuals from a wide range of geographic areas and a variety of mental health organizations throughout the United States, our sample may not necessarily be representative of the overall population of individuals with SMI. Second, this is a correlational study, and causal relationships linking greater social media use to higher levels of community participation and civic engagement should not be inferred. In fact, it could be that greater community participation and civic engagement lead to greater social media use. Third, even though the social media measures that are used in this study appear to have face validity, readers should keep in mind that other psychometric properties of our measures have not yet been examined. Future studies should assess whether these social media items are reliable and valid. Finally, the survey questionnaire used in this study did not include any ques- tions about potentially negative effects and perceived risks of social media use, which are described by Naslund et al. (2014). A separate study conducting a thorough examination of these adverse effects is needed.

5. Conclusion

This study represents one of the first attempts to examine social media use among individuals with SMI and its association, or lack thereof, with psychosocial variables, participation, and civic engagement. Given the value that participants in our study placed upon social media use, as well as its positive relationship with community participation and civic engagement, it is important to consider future interventions aimed at enhancing social media use

among individuals with SMI as a means to boost community participation and civic engagement without creating loneliness and distress or diminished quality of life.

Acknowledgements

The contents of this paper were developed with the assistance of a grant from the National Institute on Disability, Independent Living and Rehabilitation Research (NIDILRR; Grant # 90RT5021- 02-00; Salzer, PI). However, the contents do not necessarily represent the policy of the U.S. Department of Health and Human Services, and endorsement by the Federal government should not be assumed. Thanks to the community mental health organizations who partnered with us for this study and to the research staff (Alyssa Balletta, Christopher Green, Katie Pizziketti, Stephany Wilson, Jared Pryor, Natasha Roseboom and Andrea Bilger) who made this work possible.

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