Master’s Thesis, 30 ECTS
The Program for Master of Science in Psychology, 300 ECTS Autumn 2018
Supervisor: Jeong Jin Yu
EXAMINING FACEBOOK USE,
SELF-COMPASSION AND ITS INTERACTIONS
WITH SUBJECTIVE WELL-BEING
First of all, I would like to thank my supervisor, Jeong Jin Yu, for guidance, help, and patience. I would also like to thank all the students who participated in this study and Elin who suffered through my breakdowns.
Abstract
The use of social network services (SNS) has exponentially grown especially among younger generations. Facebook (FB) use today constitutes a part of many university students’ everyday life. At the same time, research interest for self-compassion has grown tremendously. High self-compassion is associated with high subjective well-being (SWB), while high FB use has shown association with lower SWB. The effect of interaction between FB use and self-compassion in predicting SWB has thus far not been tested. This study examined if FB use correlated with SWB, if compassion correlated with SWB, and if the level of self-compassion had a moderating effect between FB use and SWB. A survey containing measures of frequency and duration of FB use, Self-Compassion Scale - Short Form, Positive and Negative Affect Schedule, and Satisfaction With Life Scale was administered to Swedish university students (N = 231, M age = 24.84, SD = 5.9). A hierarchal regression analysis was
used to test if FB use and self-compassion interacted to predict SWB. The regression analysis showed that only self-compassion significantly predicted SWB. This study suggests that frequency and duration of FB use might not be enough to predict SWB. Future research could benefit from mapping more precisely what kind of FB use is beneficial or non-beneficial for user well-being. Also, future research could benefit from considering type of FB use in interaction with the level of self-compassion in predicting SWB.
Keywords: Social network services, Facebook, subjective well-being, self-compassion Abstrakt
Användandet av sociala medier (SNS) har växt kraftigt bland yngre generationer. Facebook (FB) användande utgör idag en del av många universitetsstudenters vardagliga liv. Samtidigt har forskningsintresset kring self-compassion vuxit. Hög self-compassion är associerat med högt subjektivt välbefinnande (SWB) medan högt FB-användande har visat associationer med lägre SWB. Effekten av interaktion mellan FB-användande och self-compassion för att predicera SWB har ej tidigare studerats. Denna studie undersökte korrelation mellan FB-användande och SWB, korrelation mellan compassion och SWB, samt om self-compassion hade en modererande effekt mellan FB-användande och SWB. En enkät innehållande mätning av frekvens och duration av FB-användande, Self-Compassion Scale - Short Form, Positive and Negative Affect Schedule och Satisfaction With Life Scale administrerades till svenska universitetsstudenter (N = 231, M age = 24.84, SD = 5.9). Hierarkisk
regressionsanalys användes för att undersöka om interaktion mellan FB-användande och self-compassion kunde predicera SWB. Regressionsanalysen visade att endast self-self-compassion signifikant kunde predicera SWB. Resultatet föreslår att frekvens och duration av FB-användande möjligtvis inte är tillräckligt för att predicera SWB. Framtida studier kan med fördel mer utförligt undersöka vilken typ av FB-användande som har fördelaktig eller icke-fördelaktig effekt på SWB, samt ta hänsyn till typ av FB-användande och nivå av self-compassion i interaktion för att predicera SWB.
The amount of Facebook users worldwide kept increasing in 2018 (Facebook, 2018). Meanwhile, the research interest for self-compassion has grown during the last years (Neff et al., 2017). While both Facebook use and self-compassion has been linked to well-being (Verduyn et al., 2015; Zessin et al., 2015), potential interactions between Facebook use and self-compassion regarding effects on well-being has thus far not been examined. The purpose of this study consisted of three parts; to examine if Facebook use correlated with subjective well-being, if level of self-compassion correlated with subjective well-being and if level of self-compassion had a moderating effect between Facebook use and subjective well-being among Swedish university students. The following introduction aims to briefly present theses different constructs.
Social network sites (SNS). An SNS has been defined as an on-line communication site allowing users to have identifiable profiles. Through these profiles users can create content and consume content created by other users. Interactions between on-site contacts is also openly displayed for other users (Ellison & Boyd, 2013).
Out of the broad selection of existing SNS, Facebook (FB) has the highest number of active users (Statista, 2018). FB use has increased among college students, and constitutes a part of many college students’ everyday lives (Thompson & Lougheed, 2012). FB was founded in 2004 and has a mission of giving people the power to connect, build community, and bring the world closer together. As for the second quarter of 2018, the site has over 2.23 billion users worldwide (Facebook, 2018). A mapping of the Internet use of the Swedish population showed that 74% of all Swedes were connected to FB in 2017, and that more than half of the Internet users (53%) logged on to FB daily. In the age group 16-25, 93% of Swedish Internet users connected to FB sometime during 2017 (svenskarnaochinternet, 2018). Seemingly, FB has grown to include a majority of the Swedish population, allowing users to constantly be connected. An increasing body of research on the field has shown that university students’ FB use can lead to addiction (Ryan, Chester, Reece, & Xenos, 2014) and that use of FB and other SNS come with both potential risks and benefits regarding user well-being. Given the widespread use of FB and other SNS, understanding their possible impact on user well-being is of great value.
SNS use is more popular among younger generations than it is in older generations (Hayes, van Stolk-Cooke, & Muench, 2015). Older generations have earlier not had the access to these massive networks, or other technical social instruments. Older generations tend to show greater skepticism than younger generations regarding the value of technology in their daily life (Smith, 2014). Because of this, the conditions for social contact have changed over the last decade. Examining how these changes effect SNS user well-being will help to understand the impact of the development of the Internet and SNS on younger generations. On average, Swedish university students start their studies at 24 years of age, which is late in comparison with other countries (ekonomifakta, 2018). However, Swedish university students still represent a young generation, and the age group is notably active on FB (svenskarnaochinternet, 2018). Of all registered students on Swedish universities in 2017, 60.5% where female (Statistiska Centralbyrån, 2018).
Self-compassion. The research interest in self-compassion has recently grown tremendously, with over 650 published articles on the topic between 2016 and 2017 (Neff et al., 2017). Compassion is described as being moved by others’ suffering and being open and aware of others’ pain without avoiding it, so that feelings of kindness and need to ease others’ suffering emerge. Self-compassion can be explained as directing the same attitudes towards oneself in time of suffering, which creates adaptive ways for individuals to handle setback (Neff, 2003). The construct consists of three components; self-kindness vs. self-judgment,
common humanity vs. isolation, and mindfulness vs. over-identification. Self-kindness describes being gentle and understanding towards oneself in moments of suffering. Common humanity describes the understanding that suffering and personal inadequacy is an inevitable part of the human experience. Lastly, mindfulness describes finding a balanced approach to one’s own suffering. This means observing suffering with openness and putting one’s own situation into a larger perspective, without suppressing the negative experiences (Neff, 2018). Self-compassion has shown to correlate with both negative and positive affective states (Lopez, Sanderman, Ranchor, & Schroevers,2018). Neff (2003) suggests that self-compassion might influence positive affect through positive affect responses such as experiences of understanding and kindness. Similarly, Dundas, Svendsen, Wiker, Granli, and Schanche (2015) suggest that compassion is related to lower experiences of depression through decreases in self-judgment.
Well-being. Psychological research on well-being has been divided into two fields; psychological well-being and subjective well-being. Psychological well-being is a broad construct that aims to measure human experiences of autonomy, personal growth, and purpose in life (Ryff, 1989). Due to the broad nature of the construct of psychological well-being, this study will focus on the concept of subjective well-being (SWB). SWB describes how a person evaluates his or her life in aspects of cognitions and emotions. SWB can be further divided into cognitive and affective components. Cognitive well-being is also called life satisfaction and measures one’s cognitive evaluation of life. Affective well-being measures the presence of positive affect and the absence of negative affect (Diener, 1984). Satisfaction with life and experience of positive affect have been shown to correlate at about .50 in undergraduate university students (Staw & Barsade, 1993). Higher levels of SWB have been linked to higher socioeconomic status and higher psychological, interpersonal, and physical functioning (Lyubomirsky, King, & Diener, 2005). People with high SWB have shown to self-report greater health (Røysamb, Tambs, Reichborn-Kjennerud, Neale, & Harris, 2003) and are less likely to engage in unhealthy activities like drug or alcohol abuse (Lusczynska & Tekozel, 2002). People high in SWB are less likely to suffer from work disability connected to psychiatric conditions and even suicide (Koivumaa-Honkanen et al., 2004). High positive affect at the age of 18 has been shown to correlate with higher salary, higher work autonomy and higher ratings of occupational fulfillment at a follow-up 8 years later (Roberts, Caspi, & Moffitt, 2003). SWB among college students has also shown to correlate negatively with long-term unemployment after graduation (Lyubomirsky et al., 2005). People who show high levels of SWB tend to be more open towards others and their well-being has been associated with relationship closeness. High SWB among college students has even shown to correlate with marriage satisfaction later on in life (Stones & Kozma, 1986). Taken together, SWB in general has a great impact on individuals’ physical and mental health. SWB among college students involves possible benefits in big life domains such as future careers and relationships. Because of this, understanding and promoting high well-being both in general and among college students are of great importance.
Interpersonal-connection-behavior theory. In an extensive review on existing literature on SNS and well-being, Clark, Algoe, and Green (2018) developed the interpersonal-connection-behavior theory. The theory aims to explain the mixed results that previous research has shown regarding SNS use and its impact on well-being. Clark and colleagues (2018) suggest that SNS increases the well-being of their users when helping them to develop and maintain meaningful social connections. On the other hand, when these sites do not help users build and maintain meaningful connections, users’ well-being is decreased mainly due to social
comparison and isolation. The theory builds on previous research that links FB use with loneliness (Song et al., 2014). Research states that use of SNS could satisfy users social needs without actually contributing with interpersonal resources, leading to lower social recourses (Green et al., 2005). The interpersonal-connection-behavior theory also links SNS use with potential social comparison, resulting in lowered well-being. Previous research supports this idea, both in correlational (Chou & Edge, 2012) and experimental studies (Haferkamp & Krämer, 2011). At the same time, the theory builds the idea of positive outcomes of active SNS use on previous research that links FB use to increased connection and social support (Liu & Yu, 2013) mainly through active use (Teppers, Luyckx, Klimstra & Goossens, 2014). While the theory suggests that active use of SNS predicts higher levels of well-being while passive use predicts lower levels of well-being, it acknowledges the existence of individual differences (Clark et al., 2018). One possible candidate for such individual differences in the association between SNS usage and SWB is self-compassion. In other words, one possibility is that the relationship between SNS use and well-being may be moderated by the level of self-compassion. Many psychological traits could possibly moderate the association between SNS and SWB. However, since Self-compassion has shown strong relations with well-being (Zessin et al., 2015) and the research interest for compassion is growing, examining self-compassion as a possible moderator could both be of relevance and help extend current knowledge. Since self-compassion includes seeing suffering as common to all of humanity, practicing self-kindness, and avoiding over-identification (Neff, 2003), it is possible that high self-compassion may relieve negative effects of SNS use on SWB. Thus, the interpersonal-connection-behavior theory (Clark et al., 2018) may provide a theoretical baseline for the examination of possible interactions between SNS use and levels of self-compassion in predicting SWB. The remainder of this introduction aims to explain how self-compassion and SNS use might interact to predict SWB. It also aims to explain why understanding their possible interaction in predicting well-being is beneficial.
Self-compassion and subjective well-being
A relatively large body of research has examined the impact of self-compassion on well-being. A meta-analysis by Zessin and colleagues (2015) indicated a strong positive association between self-compassion and well-being. Their study also reviewed experimental studies aiming at manipulating state of self-compassion, which indicated a causal effect from self-compassion on well-being. The analysis showed a stronger relationship between cognitive and psychological well-being and compassion than between affective well-being and self-compassion. The authors argue that self-compassion leads to cognitive acceptance of negative feelings rather than replacement of such, which could impact its effect on affective well-being. However, more research is needed to clarify the differences in the relation between self-compassion and different forms of well-being (Zessin et al., 2015). Neff (2003) suggests that self-compassion may predict positive affect by stimulating positive feelings such as acceptance and understanding towards oneself. Self-compassion may also predict lower negative affect as a result of lowered self-judgment (Dundas et al., 2015). Also, Neely, Schallert, Mohammed, Roberts, and Chen (2009) suggest that self-compassion leads to greater life satisfaction through helping individuals hold a positive attitude towards oneself and avoiding judgment towards personal limitations.
In another meta-analysis of 14 studies, McBeth and Gumley (2014) examined the relationship between self-compassion and psychopathology, primarily regarding anxiety, stress, and depression. The analysis showed a strong inverse relationship between self-compassion and psychopathology such that high self-compassion was associated with less mental health
problems. In the same vein, Booker and Dunsmore (2018) showed that college students with higher self-rated self-compassion reported higher affective and cognitive well-being. Similarly, Akin (2010) showed that high self-compassion correlated with low levels of loneliness among college students. In summary, a growing body of research has found high self-compassion to predict high subjective well-being and low levels of psychopathology.
SNS and subjective well-being
In the existing literature on SNS, use that promotes social connection and exchange with others has been classified as active use (Clark et al., 2018). Examples of SNS use viewed as active include commenting on posts or creating contents. SNS use that does not include direct exchange or does not promote social connection has been classified as passive use. This, for example, includes passively viewing posts and passively browsing other users’ content (Verduyn et al., 2015). It has also been suggested that FB users spend about 50% more time passively browsing than using the site in an active way (Verduyn et al., 2015). SNS profiles allow users to carefully manage their personal impressions (Chou & Edge, 2012). Research shows that users often create idealized profiles by uploading their best pictures (Manago, Graham, Greenfield, & Salimkhan, 2008) and by mostly sharing positive life events (Denti et al., 2012). Similarly, a Swedish study showed that only 38% of Swedish FB users used the platform to share negative events or emotions. Exposure to this type of self-presentation from others may lead to the perception that others live better lives, resulting in increased upward self-comparison, which has proven to have a negative effect on well-being (Denti et al., 2012). FB use have also been suggested to correlate positively with loneliness (Song et al., 2014).
To some extent, previous research suggests positive effects from FB use on well-being. Liu and Yu (2013) suggested that FB use may induce well-being among students, partially as a way of learning social skills through online contacts. A longitudinal study by Burk and Kraut (2016) controlled for participants’ self-rated well-being and server logged SNS use over a period of three months. The result showed that personalized communication from close friends was connected with increases in well-being. Passively browsing, only giving or receiving likes, or even receiving messages from weak friendship ties, however, did not lead to increased well-being. Indeed, many other studies have linked passive SNS use to decreased well-well-being. For example, passive FB use has shown to predict declines in the affective component of subjective well-being both in experimental studies and in daily life (Verduyn et al., 2015). Studies that have measured the effects of passive SNS use on cognitive well-being over time has also shown decreases in life satisfaction (Krasnova, Wenninger, Widjaja, & Buxmann, 2013; Kross et al., 2013). In summary, FB and SNS use has been linked positively or negatively to user well-being. Active use has been linked to increased subjective well-being and passive use has been linked to decreased subjective well-being. However, given that FB users seem to predominantly use the site in a passive way (Verduyn et al., 2015), higher FB use may be linked to lower subjective well-being.
SNS and self-compassion
To my knowledge, no previous studies examining the relationship between SNS use and self-compassion have been conducted. However, previous research on each construct can be used to find commonalities, differences, and links between the two. SNS use and self-compassion have both been shown to affect well-being among college students; passive FB use has been shown to correlate with lower subjective well-being (Burk & Kraut 2016) and high levels of self-compassion have been shown to correlate with higher subjective well-being
(Zessin et al., 2015). Because self-compassion can be of help when confronted with perceived suffering and shortcomings (e.g., Neff, 2003) and help lowering depressive symptoms (McBeth & Gumley, 2014), it is possible that self-compassion could have a buffering effect against the negative effects from SNS use on well-being. One possibility, in the context of this study, is that the level of self-compassion can exert a moderating effect on the impact of SNS use on SWB among college students. This effect could manifest, if university students with high levels of self-compassion show higher levels of SWB despite high levels of SNS use. In contrast, students with high levels of SNS use and low levels of self-compassion would exhibit low SWB. If self-compassion shows a moderating effect on the relation between SNS use and subjective well-being, this could help refine the interpersonal-connection behavior theory by bringing understanding of how the construct of self-compassion fits with the theoretical framework. Further knowledge on the relations between self-compassion, SNS use, and SWB could also help guiding future interventions for promoting well-being.
Current study
With the massive growth of SNS, FB use has become a substantial part of university student’s everyday lives. Research has started to bring understanding of how this form of networking may affect user well-being. However, further knowledge of how FB use affects SWB is needed. The current study aims to examine the relationships between FB use and SWB, as well as self-compassion and its relation to subjective well-being. Of particular note, the present study is intended as a first step towards understanding how SNS use and self-compassion may interact with each other in predicting SWB among Swedish university students. Examining self-compassion as a possible moderator of the effect between FB use and SWB among university students may bring understanding of how self-compassion can be integrated to the interpersonal-connection-behavior theory. While the theory is a new contribution to the research of SNS use and its effects on well-being, it thus far lacks specificity about how individual differences impact this relation (Clark et al., 2018). Therefore, this study may make an interesting contribution in filling this void. This study may also bring further knowledge useful in the development of both SNS and self-compassion interventions in ways that may promote subjective well-being.
In this study, SNS use will be limited to use of FB, mainly since FB is the biggest and most widely used SNS in Sweden (svenskarnaochinternet, 2018). Many other SNS exist, but due to the limited time and resources available for the study, this limitation in the data collection is needed. Only frequency and duration of FB use will be measured in this study and more time spent on FB is likely to lead to a bigger negative impact on SWB (Verduyn et al., 2015). The construct of well-being will in this study be limited to self-rating of SWB. This limitation has been made because subjective well-being builds on self-evaluations of one’s life, while psychological well-being focuses on the abstract concept of fulfilling human potential and finding meaning with life (Zessin et al., 2015). While the interpersonal-connection-behavior theory claims that SNS use predict decreased well-being through increased isolation and self-comparison (Clark et al., 2018), this study will test the direct impact of SNS use on subjective well-being, with self-compassion as a moderator.
Hypothesis
1. The first hypothesis was that high Facebook use would predict low subjective well-being.
2. The second hypothesis was that high self-compassion would predict high subjective well-being.
3. The third hypothesis was that self-compassion would moderate the association between Facebook use and subjective well-being. Specifically, high Facebook use and low self-compassion would predict low subjective well-being, whereas high Facebook use and high self-compassion would predict high subjective well-being.
Figure 1 shows the hypothesized model. Figure 1. Hypothesized model.
Methods
Design
Correlation analyses were conducted between the study variables. Hierarchal
regression analysis was made to examine interaction between FB use and self-compassion in predicting the dependent variables of SWB measured. All data analyses were carried out with IBM SPSS Statistics 24 (IBM Corporation, Armonk, New York).
Participants
The participants in this study consisted of students from Umeå, Lund, and Örebro Universities. Participants were recruited by contacting student councilors by e-mail, who in their turn posted the questionnaires to students on their respective online learning management systems or by student e-mails. Participants were enrolled in various university programs. A total of 231 students answered the questionnaire. Table 1 shows descriptive statistics for the study participants.
Table 1. Descriptive data for all participants
n % M SD MIN MAX RANGE
Sex 231
Male 55 23.8
Female 173 74.9
Other 3 1.3
Age 228 24.84 5.9 19 68 49
Note: n= total of participants, M = mean, SD = standard deviation.
Instruments
The questionnaire used in the study consisted of the self-rating questionnaires: Self-Compassion Scale – Short Form (SCS-SF; Raes, Pommier, Neff, & Van Gucht, 2011), Positive Affect Negative Affect Schedule (PANAS; Watson, Clark & Tellegen 1988), and Satisfaction With Life Scale (SWLS; Diener, Emmons, Larsen & Griffin, 1985). These three instruments where used to measure components of SWB. Existing translated Swedish versions were used. The questionnaire also included questions regarding frequency and duration of FB use and demographic variables such as sex, age, and university program enrollment.
Self-Compassion Scale – Short Form - SCS-SF. The SCS-SF (Raes et al., 2011) is a self-rating questionnaire including of 12 items measuring level of self-compassion. The questionnaire aims to measure each of the dimensions in self-compassion; common humanity vs. isolation, mindfulness vs. over-identification, and self-kindness vs. self-judgement. For example, one item aiming to measure self-kindness is the following; “I try to be understanding and patient towards those aspects of my personality I don’t like”. The SCS-SF answers consist of a 5-point Likert scale, ranging from 1 (almost never) to 5 (almost always). A high mean score indicates a high level of self-compassion. The SCS-SF can be used as a time-efficient alternative to the full version (Raes et al., 2011). The SCS-SF has shown good internal consistency for non-clinical samples and good test-retest reliability. The scale has also shown
good factor validity and convergent validity, and the instrument is recommended for measuring self-compassion in clinical and research setting (see Castillho, Pinto-Gouveia, & Duarte, 2015 for details). For this sample, Cronbach’s alpha was .81.
Positive and Negative Affect Schedule - PANAS. The PANAS (Watson et al., 1988) is a 20-item scale that aims to measure experiences of positive and negative affect (10 positive and 10 negative, e.g., “indicate the extent you have felt this way over the past month - strong”) on a 5-point Likert scale ranging from 1 (very slightly or not at all) to 5 (extremely). Positive Affect reflects to what extent one feels active and enthusiastic. While low positive affect is characterized by sadness and lack of energy, high positive affect is characterized by high energy and engagement. Negative Affect reflects subjective distress and lower engagement and is not connected with feelings of pleasure. Low negative affect is characterized by a state of tranquility, while high negative affect is characterized by a variety of unpleasant moods. The scales have shown to have high internal consistency, convergent and discriminant validity, and show high test-retest reliability (Watson et al., 1988). Cronbach’s alpha for this study was .85 for Positive Affect and .84 for Negative Affect.
Satisfaction With Life Scale - SWLS. The SWLS (Diener et al., 1985) is a widely used measure of cognitive well-being. The instrument was developed to measure life satisfaction as a whole, and allows the respondent to evaluate life satisfaction by subjective references and criteria (Pavot & Diener, 2009). The questionnaire is a self-rating of life satisfaction, and consists of five items (e.g., “I am satisfied with my life”) with answers on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). Subjective ideas and references of one’s life satisfaction are measured, but circumstances like current mood or events are shown to generally have a small impact. Instead, individuals often tend to use similar information (e.g., relationships and life achievements) when rating life satisfaction (Emerson, Guhn, & Gadermann, 2017). The SWLS has shown high internal consistency and test-retest stability. The SWLS has also proven discriminant validity from emotional well-being measurements, and is recommended for use together with emotional well-being scales in order to capture the broad construct of subjective well-being (Pavot & Diener, 2009). For this sample, Cronbach’s alpha was .82.
Facebook use. Information was collected through self-ratings of frequency and duration of one’s Facebook use over the last month (e.g., “during the past month, how many times would you estimate that you’ve visited Facebook?”). Both frequency and duration had answers on Likert scales ranging from 1 to 7. For example, answers for frequency range from 1 (never) to 7 (more than 10 times/day). Questions and response options measuring FB use can be found in appendix 1.
Procedure
Data was collected through an online questionnaire created with Google Forms. All information and the questionnaires were given in Swedish. All data was collected during a period of two weeks in October 2018. Participants answered the questionnaire that took about 5-10 minutes to complete. No compensation for participation was given.
Ethical considerations
included in the online questionnaire. The collected data could not be used to determine any one participant’s identity.
Results
Descriptive data for the study variables are presented in Table 2. Table 2. Results of the instruments reported in means and std. deviations
Variables M SD MIN MAX RANGE
SWLS 4.72 1.15 2.20 7 4.80 PA 3.37 .63 1.7 4.80 3.10 NA 2.51 .69 1 4.60 3.60 SCS-SF 2.96 .65 1.58 4.58 3 Facebook use 3.5 .94 1 7 6
Note: SCS-SF = Self-Compassion Scale Short Form, SWLS = Satisfaction With Life Scale, PA = PANAS Positive Affect, NA = PANAS Negative Affect.
Table 3 shows correlations between the study variables. Table 3. Correlation between key measures
Variables 1 2 3 4 5 1.SWLS - 2.PA .46** - 3.NA -.38** -.29** - 4.SCS-SF .51** .45** -.48** - 5.FB -.09 .01 .12 -.06 -
Note: SCS-SF = Self-Compassion Scale Short Form, SWLS = Satisfaction With Life Scale, PA = PANAS Positive Affect, NA = PANAS Negative Affect.
*p < .05. **p < .01. ***p < .001.
Self-compassion had a significant positive correlation with satisfaction with life and positive affect on the p < .01. level. Self-compassion had a significant negative correlation with negative affect on the p < .01. level. Although the expectation was that both FB use and self-compassion would be significantly correlated with all measures of SWB, FB use did not significantly correlate with any of the measures of SWB.
A hierarchal regression analysis was made to examine for interaction between FB use and self-compassion in predicting the dependent variables of SWB measured. Tables 4, 5 and 6 show results for the hierarchal regression analyses. Table 4 shows the analysis for the dependent variable satisfaction with life, Table 5 for negative affect and Table 6 for positive affect. To avoid multicollinearity, centered variables for FB use and self-compassion was created before the hierarchal regression analysis were made (Aiken & West, 1991). FB use and self-compassion were entered in the first step of the analysis, followed by the interaction of FB use and self-compassion in the second step of the analysis.
Predictors β B SE ΔR² Total R² Step 1 Facebook use -.06 -.08 .07 Self-Compassion .51*** .89*** .10 .26*** Step 2 Facebook use -.06 -.08 .07 Self-compassion .51*** .90*** .10 Facebook use X Self Compassion -.00 .01 .10 0 .26***
Note: β = standardized coefficient beta, B = unstandardized B, SE = standard error, ΔR² = R²
change.
*p < .05. **p < .01. ***p < .001.
The overall model predicting satisfaction with life was significant (F(3, 227) = 27.2, p < .001). The model accounted for 26% of the variance in satisfaction with life. Only self-compassion significantly positively predicted satisfaction with life.
5. Summary of regression analysis on variables predicting negative affect
Predictors β B SE ΔR² Total R² Step 1 Facebook use -.09 -.07 .04 Self-Compassion -.48*** -.51*** .06 .24*** Step 2 Facebook use .09 .07 .04 Self-compassion -.48*** -.51*** .06 Facebook use X Self Compassion -.01 .01 .06 0 .24***
Note: Note: β = standardized coefficient beta, B = unstandardized B, SE = standard error, ΔR²
= R² change.
The overall model predicting negative affect was significant (F(3, 227) = 24.26, p < .001). The model accounted for 24% of the variance in negative affect. Only self-compassion significantly negatively predicted negative affect.
6. Summary of regression analysis on variables predicting positive affect
Predictors β B SE ΔR² Total R² Step 1 Facebook use .04 .03 .07 Self-Compassion .46*** .44*** .10 .21*** Step 2 Facebook use .03 .02 Self-compassion .46*** .45*** Facebook use X Self Compassion -.04 -.04 .10 .21***
Note: Note: β = standardized coefficient beta, B = unstandardized B, SE = standard error, ΔR²
= R² change.
*p < .05. **p < .01. ***p < .001.
The overall model predicting positive affect was significant (F(3, 227) = 19.92, p < .001). The model accounted for 21% of the variance in positive affect. Only self-compassion significantly positively predicted positive affect.
The hierarchal regression analyses showed that level of self-compassion significantly predicted all measures of SWB, whereas FB use did not significantly predict any of the measures of SWB. Entering the interaction between FB use and self-compassion did not significantly change R² for any of the measures of SWB.
Discussion
The ever-increasing use of SNS comes with potential risks, for example by generating upward social-comparison which may have a negative impact on SWB (Denti et al., 2012). At the same time, the interest of self-compassion in psychological research has also grown tremendously (Neff et al., 2017). A large body of research has suggested that self-compassion has positive effects on individuals’ SWB, for example by evoking feelings of acceptance and understanding towards oneself (Neff, 2003). While both SNS use and self-compassion have received increasing attention in psychological research, no previous studies have examined the potential interaction of the constructs. Thus, this study was conducted in an attempt to contribute to an understanding of how FB use and self-compassion may interact in predicting SWB. The main purpose of this study was to test if self-compassion had a moderating effect in the relation between FB use and SWB.
The first hypothesis was that high FB use would predict low SWB. The result did not show a significant association between FB use and any of the measured components of SWB (i.e., satisfaction with life, positive affect, and negative affect). The lack of a significant relation between FB use and SWB is not in line with previous research suggesting that FB use predicts declines in affective components of SWB (Verduyn et al., 2015) and life satisfaction (Krasnova et al., 2013; Kross et al., 2013). Existing research (e. g., Burk & Kraut, 2016) and the interpersonal-connection-behavior theory (Clark et al., 2018) suggest that communication with close relationship ties through FB leads to increased SWB. In this study, active or passive use of FB was not measured. It is possible that users spend more time actively using FB and this might explain the absence of significant association between FB use and SWB in this study. It is also possible that passive FB use is more widespread among users even in this sample. However, potential positive effects from active use might be stronger than the negative effects from passive use, and could therefore hide a potential link between SWB and FB use when type of use is not controlled for, even if passive use is more common. Further research would be needed to control for type of FB use to gain greater insight into this issue.
The second hypothesis was that high self-compassion would predict high SWB. Self-compassion significantly predicted all parts of SWB measured. The present findings that self-compassion is positively associated with positive affect and negatively with negative effect are in line with previous research (e.g., Lopez et al., 2018). Self-compassion has been suggested to predict positive affect by stimulating positive feelings towards oneself such as acceptance and understanding (Neff, 2003). The relation between self-compassion and negative affect may be a result of lowered self-judgement (Dundas et al., 2015). Holding a positive attitude towards oneself and avoiding judgement towards personal limitations could also lead to greater life satisfaction (Neely et al., 2009).
The third hypothesis was that FB use and self-compassion would interact to predict SWB. Specifically, high FB use and low self-compassion would predict low SWB, whereas high FB use and high self-compassion would lower the negative effect of high FB use on SWB and predict higher levels of SWB. However, the results documented that self-compassion did not serve as a moderator between FB use and SWB. Since a number of previous studies have suggested that FB use correlates with changes in SWB (e.g., Kross et al., 2013; Verduyn et al., 2016), examining self-compassion as a potential moderator should still be of interest for future studies. The absence of significant interaction between FB use and self-compassion in predicting SWB in this study might simply be due to limitations to the current study.
Several limitations to the study could be addressed. First of all, the sample size in this study was relatively small, and the participants consisted of university students which means that the result may not be generalized onto other groups. Secondly, the data represent considerably more female than male participants. A majority of Swedish university students
are females (Statistiska Centralbyrån, 2018), but the data sample of this study is more unevenly distributed than the Swedish university student population. A bigger population, representing other groups than university students and with a more even distribution between the sexes, might lead to a different result. The collection of longitudinal data might also provide different results with causal relations. Thirdly, one limitation of the study was that only Facebook use was measured. There are a vast number of SNS available, and it is possible that participants use other SNS more than they use FB. Also, only frequency and duration of Facebook use were measured in the present study, without type of use or exposure of different types of content. Finally, all data in this study were based on self-rated questionnaires, and other ways of collecting data (e.g., peer ratings, FB use measured by server logs, observations) would substantially increase reliability of the findings.
Future research would benefit from examining whether self-compassion has a moderating role on the relationship between FB use and SWB, together with type of FB use. In order to do this, future studies could also benefit from more thoroughly examining what kind of FB use is beneficial and non-beneficial for users. For example, Burk and Kraut (2016) suggest that only personalized communication from close relationship ties led to increases in well-being. On the other hand, other authors have suggested positive effects on well-being from other types of use. For example, Liu and Yu (2013) suggest that FB use can help build stronger real-life connections by helping individuals practice social skills through online contacts. In other words, further knowledge of how different FB interactions effect SWB is needed. Simply dichotomizing FB use into passive or active use might, however, not be enough to capture the complex reality. It is likely that user response to different FB content is highly individual, and that a qualitative approach to future research in the field could contribute to an improved knowledge about FB use and its association with SBW.
Improved knowledge of FB use and its association with SWB could be of help when developing practical implications, such as guidelines for how to use FB in ways that promote well-being. Given the widespread use of FB and other SNS, such interventions could be of great importance. The result from his study could guide such interventions by suggesting that simply spending more time on FB does not necessarily lead to lower SWB. The result of this study suggests a strong link between self-compassion and SWB, which could further stress the usefulness of interventions aimed at increasing individuals’ level of self-compassion.
Even though this study failed to show any significant results regarding a moderating effect of self-compassion on the relation between FB use and SWB, it can provide important guidance for future research. The results in this study suggests that general FB use may not be significantly associated with components of SWB. This insight may be seen as an indirect support to the idea of the interpersonal-connection-behavior theory, claiming that different types of FB use leads to different effects on user well-being. Future studies could take guidance from this result by carefully measuring type of FB use when examining effects on SWB. This study also extends previous research, suggesting that self-compassion is strongly connected to SWB including experiences of positive affect, negative affect, and satisfaction with life among Swedish university students.
Reference list
Aiken, L.S., & West, S.G. (1991). Multiple Regression: Testing and Interpreting Interactions. London: Sage Publications.
Akin, A. (2010) Self-compassion and Loneliness. International Online Journal of Educational Sciences, 2, 702-718. Retrieved from
https://www.researchgate.net/profile/Ahmet_Akin4/publication/49591624_Self- compassion_and_Loneliness/links/53e37d490cf23a7ff74952ef/Self-compassion-and-Loneliness.pdf
Booker, J. A., & Dunsmore, J. C. (2018). Testing direct and indirect ties of self-compassion with subjective well-being. Journal of Happiness Studies: An interdisciplinary Forum in Subjective Well-being. Retrieved on from https://rdcu.be/bcl7b
Burke, M., & Kraut, R. E. (2016). The relationship between Facebook use and well‐ being depends on Communication Type and Tie Strength. Journal of Computer-Mediated Communication, 21, 265-281. doi:10.1111/jcc4.12162
Castilho, P., Pinto‐ Gouveia, J., & Duarte, J. (2015). Evaluating the multifactor structure of the long and short versions of the self‐ compassion scale in a clinical sample. Journal of Clinical Psychology, 71, 856-870. doi:10.1002/jclp.22187
Chou, H. G., & Edge, N. (2012). 'They are happier and having better lives than I am': The impact of using Facebook on perceptions of others' lives. Cyberpsychology, Behavior, and Social Networking, 15, 117-120. doi:10.1089/cyber.2011.0324
Clark, J. L., Algoe, S. B., & Green, M. C. (2018). Social network sites and well-being: The role of social connection. Current Directions in Psychological Science, 27, 32-37. doi:10.1177/0963721417730833
Denti, L., Barbopuolos, I., Nilsson, I., Thulin, M., Wendeblad, M., Andén, L., & C.,
Davidsson, E. (2012). Sweden’s largest Facebook study. Gothenburg Research Institute. Retrieved from http://hdl.handle.net/2077/28893
Diener, E. (1984). Subjective well-being. Psychological Bulletin, 95, 542–575. doi:10.1037/0033-2909.95.3.542
Diener, E., Emmons, R. A., Larsen, R. J., & Griffin, S. (1985). The Satisfaction With Life Scale. Journal of Personality Assessment, 49, 71-75. doi: 10.1207/s15327752jpa4901_13 Dundas, I., Svendsen, J. L., Wiker, A. S., Granli, K. V., & Schanche, E. (2016).
Self-compassion and depressive symptoms in a Norwegian student sample. Nordic Psychology, 68, 58–72. doi:10.1080/19012276.2015.1071203
Ellison, N. B., & Boyd, D. M. (2013). Sociality through social network sites. The Oxford hand-book of Internet studies, 151–172. Oxford, England: Oxford University Press. Retrieved from
http://www.oxfordhandbooks.com/view/10.1093/oxfordhb/9780199589074.001.0001/oxf ordhb-9780199589074-e-8
Emerson, S. D., Guhn, M., & Gadermann, A. M. (2017). Measurement invariance of the Satisfaction with Life Scale: Reviewing three decades of research. Quality of Life Research: An International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation, 26, 2251-2264. doi:10.1007/s11136-017-1
Facebook. (2018). Facebook Reports Second Quarter 2018 Results. Retrieved from https://investor.fb.com/investor-news/press-release-details/2018/Facebook-Reports-Second-Quarter-2018-Results/default.aspx
Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7, 117-140. doi:10.1177/001872675400700202
Green, M. C., Hilken, J., Friedman, H., Grossman, K., Gasiewskj, J., Adler, R., & Sabini, J. (2005). Communication via instant messenger: Short-and long-term effects. Journal of Applied Social Psychology, 35, 445-462. doi:10.1111/j.1559-1816.2005.tb02130.x
Haferkamp, N., & Krämer, N. C. (2011). Social comparison 2.0: Examining the effects of online profiles on social- networking sites. Cyberpsychology, Behavior, and Social Networking, 14, 309–314. doi:10.1089/cyber.2010.0120
Hayes, M., van Stolk-Cooke, K., & Muench, F. (2015). Understanding Facebook use and the psychological affects of use across generations. Computers in Human Behavior, 49, 507– 511. doi:10.1016/j.chb.2015.03.040
Koivumaa-Honkanen, H., Koskenvuo, M., Honkanen, R. J., Viinamaki, H., Heikkilae, K., & Kaprio, J. (2004). Life dissatisfaction and subsequent work disability in an 11-year follow-up. Psychological Medicine, 34, 221–228. doi:10.1017/S0033291703001089
Krasnova, H., Wenninger, H., Widjaja, T., & Buxmann, P. (2013). Envy on Facebook: A hidden threat to users’ life satisfaction? Retrieved from
https://boris.unibe.ch/id/eprint/47080
Kross, E., Verduyn, P., Demiralp, E., Park, J., Lee, D. S., Lin, N., & Ybarra, O. (2013). Facebook use predicts declines in subjective well-being in young adults. Plos ONE, 8. Retrieved from
http://search.ebscohost.com.proxy.ub.umu.se/login.aspx?direct=true&db=psyh&AN=2013 -30399-001&site=ehost-live&scope=site
Liu, C.Y., & Yu, C.P. (2013). Can Facebook use induce well-being? Cyberpsychology, Behaviour, and Social Networking, 16, 674-678. doi:10.1089/cyber.2012.0301 López, A., Sanderman, R., Ranchor, A. V., & Schroevers, M. J. (2018). Compassion for
others and self-compassion: Levels, correlates, and relationship with psychological well-being. Mindfulness, 9, 325–331. doi: 10.1007/s12671-017-0777-z
Lyubomirsky, S., King, L., & Diener, E. (2005). The benefits of frequent positive affect: Does happiness lead to success? Psychological Bulletin, 13, 803–855. doi:10.1037/0033-2909.131.6.803.
MacBeth, A., & Gumley, A. (2012). Exploring compassion: A meta-analysis of the association between self-compassion and psychopathology. Clinical Psychology Review, 32, 545-552. doi:10.1016/j.cpr.2012.06.003
Manago, A. M., Graham, M. B., Greenfield, P. M., & Salimkhan, G. (2008).
Self-presentation and gender on MySpace. Journal of Applied Developmental Psychology, 29, 446-458. doi:10.1016/j.appdev.2008.07.001
Metler, S. J., & Busseri, M. A. (2017). Further evaluation of the tripartite structure of subjective well‐ being: Evidence from longitudinal and experimental studies. Journal of Personality, 85, 192-206. doi:10.1111/jopy.12233
Neff. (2018) Self compassion. Retrieved 2018-09-15 from http://self-compassion.org
Neff, K. D., Long, P., Knox, M. C., Davidson, O., Kuchar, A., Costigan, A., … Breines J. G. (2018) The forest and the trees: Examining the association of self-compassion and its positive and negative components with psychological functioning, Self and
Identity, 17, 627-645. doi:10.1080/15298868.2018.1436587
Neely, M. E., Schallert, D. L., Mohammed, S. S., Roberts, R. M., & Chen, Y.-J. (2009). Self-kindness when facing stress: The role of self-compassion, goal regulation, and support in college students’ well-being. Motivation and Emotion, 33, 88–97. doi:10.1007/s11031-008-9119-8
Ekonomifakta.se, Svenskt näringsliv. (2018). Examensålder. Retrieved from
Pavot, W., & Diener, E. (2009). Assessing Well-Being: The Collected Works of Ed Diener. Dordrecht: Springer.
Raes, F., Pommier, E., Neff, K. D., & Van Gucht, D. (2011). Construction and factorial validation of a short form of the Self-Compassion Scale. Clinical Psychology and Psychotherapy, 18, 250-255. doi:10.1002/cpp.702
Roberts, B. W., Caspi, A., & Moffitt, T. E. (2003). Work experiences and personality
development in young adulthood. Journal of Personality and Social Psychology, 84, 582– 593.doi:10.1037/0022-3514.84.3.582
Ryan, T., Chester, A., Reece, J., & Xenos, S. (2014). The uses and abuses of Facebook: A review of Facebook addiction. Journal of Behavioral Addictions, 3, 133-148.
doi:10.1556/JBA.3.2014.016
Ryff, C. D. (1989). Happiness is everything, or is it? Explorations on the meaning of
psychological well-being. Journal of Personality and Social Psychology, 57, 1069–1081. doi:10.1037/0022-3514.57.6.1069
Røysamb, E., Tambs, K., Reichborn-Kjennerud, T., Neale, M. C., & Harris, J. R. (2003). Happiness and health: Environmental and genetic contributions to the relationship between subjective well-being, perceived health, and somatic illness. Journal of Personality and Social Psychology, 85, 1136–1146. doi:10.1037/0022-3514.85.6.1136 Smith, A. (2014). Older adults and technology use. Pew Internet & American Life Project.
Retrieved from http://www.pewinternet.org/2014/04/03/ older-adults-and-technology-use/ Song, H., Zmyslinski-Seelig, A., Kim, J., Drent, A., Victor, A., Omori, K., & Allen, M.
(2014). Does Facebook make you lonely?: A meta analysis. Computers in Human Behavior, 36, 446–452. doi:10.1016/j.chb.2014.04.011
Statista. (2018). Most famous social network sites worldwide as of July 2018, ranked by number of active users (in millions). Retrieved from
https://www.statista.com/statistics/272014/global-social-networks-ranked-by-number-of-users/
Statistiska Centralbyrån. (2018) Universitet och högskolor. Studenter och examinerade på grundnivå och avancerad nivå 2016/1. Retrieved from
https://www.scb.se/publikation/35252
Staw, B. M., & Barsade, S. G. (1993). Affect and managerial performance: A test of the sadder-but-wiser vs. happier-and-smarter hypothesis. Administrative Science Quarterly, 38, 304–331. doi:10.2307/2393415
Stones, M. J., & Kozma, A. (1986). “Happy are they who are happy . . .” A test between two causal models of relationships between happiness and its correlates. Experimental Aging Research, 12, 23–29.doi:10.1080/03610738608259431
Svenskarna och internet. (2018). Svenskarna och internet 2017. En årlig studie av svenska folkets internetvanor. Retrieved from
https://2017.svenskarnaochinternet.se/kommunikation-och-sociala-plattformar/facebook/ Thompson, S. H., & Lougheed, E. (2012). Frazzled by Facebook? An exploratory study of
gender differences in social network communication among undergraduate men and women. College Student Journal, 46, 88–99. Retrieved from
http://search.ebscohost.com.proxy.ub.umu.se/login.aspx?direct=true&db=psyh&AN=2012 -18560-011&site=ehost-live&scope=site
Teppers, E., Luyckx, K. A., Klimstra, T., & Goossens, L. (2014). Loneliness and Facebook motives in adoles- cence: A longitudinal inquiry into directionality of effect. Journal of Adolescence, 37, 691–699. doi:10.1016/j.ado lescence.2013.11.003
Toplu-Demirtaş, E., Kemer, G., Pope, A. L., & Moe, J. L. (2018). Self-compassion matters: The relationships between perceived social support, self-compassion, and subjective
well-being among LGB individuals in Turkey. Journal of Counseling Psychology, 65, 372-382. doi:10.1037/cou0000261
Verduyn, P., Lee, D. S., Park, J., Shablack, H., Orvell, A., Bayer, J., & Kross, E. (2015). Passive Facebook usage undermines affective well-being: Experimental and longitudinal evidence. Journal of Experimental Psychology: General, 144, 480-488.
doi:10.1037/xge0000057
Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063–1070. doi:10.1037/0022-3514.54.6.1063
Zessin, U., Dickhäuser, O., & Garbade, S. (2015). The relationship between self‐ compassion and well‐ being: A meta‐ analysis. Applied Psychology: Health and Well-Being, 7, 340-364. doi:10.1111/aphw.12051
Appendix 1
Questions and answer alternatives used for measures of frequency and duration of FB use. The questions and answer alternatives were given to participants in Swedish but has here been translated to English.
During the past month, how many times would you estimate that you have visited Facebook?
1) Never 2) 1-3 times/month 3) 1-2 times/week 4) 3-6 times/week 5) 1-4 times/day 6) 5-10 times/day
7) More than 10 times/day
During the past month, how much time would you estimate that you have spent on each single Facebook visit?
1) 1-5 minutes 2) 5-10 minutes 3) 11-20 minutes 4) 21-30 minutes 5) 31-45 minutes 6) 46-60 minutes 7) More than 60 minutes
