“It's complicated.” A systematic review of associations between social network site and..., Transcriptions of Media & Society

Download “It's complicated.” A systematic review of associations between social network site and... and more Transcriptions Media & Society in PDF only on Docsity! lable at ScienceDirect Computers in Human Behavior 75 (2017) 684e703Contents lists avaiComputers in Human Behavior journal homepage: www.elsevier .com/locate/comphumbehReview“It's complicated.” A systematic review of associations between social network site use and romantic relationships Holly M. Rus, Jitske Tiemensma* Psychological Sciences, University of California, Merced, CA, USAa r t i c l e i n f o Article history: Received 9 March 2016 Received in revised form 2 March 2017 Accepted 5 June 2017 Available online 6 June 2017 Keywords: Social network sites Social media Romantic relationships Emerging adults Gender differences* Corresponding author. University of California, Science, 5200 North Lake Road, Merced, CA 95343, U E-mail addresses: hrus@ucmerced.edu (H.M. Rus) (J. Tiemensma). http://dx.doi.org/10.1016/j.chb.2017.06.004 0747-5632/© 2017 Elsevier Ltd. All rights reserved.a b s t r a c t Social network site (SNS) use may have important implications for romantic relationships. This sys- tematic literature review aims to (a) identify theory-based approaches for studying associations between SNS use and romantic relationships, (b) identify key romantic relationship constructs measured in relation to SNS use, (c) synthesize the mechanisms by which SNS use may influence and be influenced by romantic relationships, and (d) discuss improved methods for guiding future research. Twenty-six peer- reviewed articles published in English from 2000 to 2015 that include measures of a romantic rela- tionship construct as an outcome or predictor of SNS-related behavior for someone in a romantic rela- tionship comprise this review. Studies are categorized as focusing on individual characteristics, relationship characteristics, or behavioral actions. Overall, findings indicate underdevelopment of SNS- related theory, and suggest that SNS behaviors may both influence and be influenced by individual and relationship characteristics such as adult attachment style, SNS-induced jealousy, relationship satisfaction and commitment, and partner identity overlap. Gender appears to influence associations between SNS use and relationship constructs, particularly in relation to interpreting ambiguous infor- mation about a partner. Further, SNSs may serve a maintenance function within romantic relationships. Directions for future research include assessing multiple SNSs in diverse samples and standardizing measurement of SNS behaviors. © 2017 Elsevier Ltd. All rights reserved.Contents 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 685 1.1. Social network sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 685 1.2. Romantic relationships in the age of social network sites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 685 1.3. Review objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 686 2. Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 686 2.1. Search strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 686 3. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 686 3.1. Theoretical support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 686 3.1.1. Attachment theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 686 3.1.2. Investment Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 687 3.1.3. Dependence power . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 687 3.1.4. Self-expansion theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 692 3.1.5. Relational Maintenance Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 692 3.1.6. Uncertainty Reduction Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 693 3.1.7. Theory of Planned Behavior . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 693 3.1.8. Synthesis and evaluation of theoretical framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 693Merced, SSHA, Psychological SA. , jtiemensma@ucmerced.edu H.M. Rus, J. Tiemensma / Computers in Human Behavior 75 (2017) 684e703 6853.2. Individual characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 693 3.2.1. Jealousy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 693 3.2.2. Attachment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 694 3.2.3. Synthesis and evaluation of studies examining individual characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 694 3.3. Relationship characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 695 3.3.1. Satisfaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 695 3.3.2. Commitment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 695 3.3.3. Partner identity overlap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 695 3.3.4. Synthesis and evaluation of studies examining relationship characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 695 3.4. Behavioral actions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 697 3.4.1. Maintenance and monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 697 3.4.2. Infidelity and divorce . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 698 3.4.3. Synthesis and evaluation of studies examining behavioral actions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 698 4. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 698 4.1. Theory-based approaches for identifying associations between SNS use and romantic relationships . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 699 4.2. Key romantic relationship constructs measured in relation to SNS use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 699 4.3. Synthesis of mechanisms by which SNS use is associated with romantic relationships . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 699 4.3.1. The role of gender . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 699 4.4. SNS use and romantic relationships across ages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 700 4.5. Improved methods for guiding future research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 700 5. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 701 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7021. Introduction Social media is changing the landscape for interpersonal communication. Platforms such as Facebook and Twitter attract hundreds of millions of daily users (Duggan, Ellison, Lampe, Lenhart, & Madden, 2015) and continue to inspire behavioral research in various areas. Studies have ranged in interest from predicting use from personality (Correa, Hinsley, & De Zuniga, 2010), to social media as a health information context (Moorhead et al., 2013), to assessing the general impact of social media use on well-being and mental health (Best, Manktelow, & Taylor, 2014; Pantic, 2014). Although social media is more commonly used to maintain friendships (Ellison, Steinfield, & Lampe, 2007; Houser, Fleuriet, & Estrada, 2012), it also plays an important role in romantic relationships (Smith&Duggan, 2013). Several affordances of social network sites (SNSs) (e.g., high visibility within and con- stant access to one's social network, including romantic alterna- tives) may have important implications for romantic relationships. This article provides a systematic review of research concerning associations between SNS use and romantic relationships as well as provides suggestions for future research directions. 1.1. Social network sites The terms “social media” and “social network site” are often interchangeably used; however, distinction is necessary for framing review of this literature. Social media is a blanket term for defining Internet applications that allow for the exchange of user-generated content (Kaplan & Haenlein, 2010). This term describes a variety of communication forms including blogs, message boards, videos sharing platforms (e.g., YouTube), and SNSs. Social network sites are a type of social media that may best be defined as web-based services that allow for maintenance of social relationships within one's publicly visible social network (Ellison, 2007). Given the global popularity of SNSs, recent research focusing on computer- mediated communication most commonly focuses on SNS use rather than social media use in general. Recent reports suggest that SNS use transcends major demographic variables including gender, age, race/ethnicity, and socio-economic status, with over 65% of adult Internet users from each major category reporting use(Duggan et al., 2015). To date, Facebook remains the most popular SNS, with over 1 billion worldwide users (fb.com, 2015) and 71% of online adults naming it as their preferred platform (Duggan et al., 2015). Accordingly, the vast majority of SNS research is specific to Facebook use. 1.2. Romantic relationships in the age of social network sites Romantic relationships can be defined as relationships based on emotional and physical attraction that could potentially lead to long-term intimate relationships (World Health Organization). During early adulthood, romantic relationships have important individual and societal implications for promoting personal well- being and providing a framework for future relationships (Feldman, Gowen, & Fisher, 1998; Fox & Anderegg, 2014). The Internet plays an increasingly important role in romantic re- lationships. Recent years have shown a two-fold increase in the number of couples who met online (Madden & Lenhart, 2006; Sprecher, 2011). Following trend, Hall (2014) found that close to 35% of all couples married between 2005 and 2012 initiated their relationship online. Although not the primary function, SNSs are a common online location for meeting a partner (Hall, 2014), and appear to play a role in all phases of romantic relationships including initiation, escalation, maintenance, dissolution, and even post-dissolution ex-partner monitoring (Smith & Duggan, 2013). A landmark study (reviewed below) by Muise, Christofides and Desmarais (2009) found that general Facebook use predicted romantic jealousy. Since then, research has evolved in considering the complex associations between SNS use, individual differences, and romantic relationship constructs such as attachment style, satisfaction, commitment, partner identity overlap, relationship maintenance strategies, and infidelity. Although use is expanding to different age demographics, 18- to 24-year-olds remain the primary SNS audience (Duggan et al., 2015). Defined as emerging adulthood (Arnett, 2000), this distinct developmental period encompasses a time of identity exploration relevant to romantic relationships. In particular, young people in this age range are more likely to participate in transitory relation- ships of short duration (Shulman & Connolly, 2013). Given that the majority of SNS use research has been conducted on emerging Table 1 Literature synthesis for associations between social network site use and romantic relationship constructs. Authors Sample Study Aim and Design Theoretical Framework Measures/Stimuli Findings Individual Characteristics Jealousy McAndrew and Shah (2013) n ¼ 40; 60% female; age range 18 e23; RS ¼ 100% current Cross-sectional survey exploring if FB activity and gender predict FB jealousy. NA - FB use: number of daily logins and time spent on the site on an average day - FB Jealousy Scale (Muise et al., 2009). Females more prone to FB jealousy. Males more likely to accurately predict females' FB jealousy. Muise et al. (2009) n ¼ 308; 75% female; Mage ¼ 18.7; RS ¼ 50.5% seriously dating 1 person, 33.6% single, 8.3% casually dating, 3.7% in open relationship, 3% cohabitating, 0.7% married, 0.3% divorced or separated Cross-sectional survey exploring if FB activity and gender predict FB jealousy. NA - FB use: mean minutes per day - FB Jealousy Scale* Trait jealousy, female gender, and time spent on FB significantly predicted FB jealousy. Fleuriet et al. (2014) y n ¼ 82; 53% female; Mage ¼ 20.38; RS ¼ 47% single Experimental design testing the effect of nonverbal FB message characteristics and sender attractiveness on emotional reactions of message recipient's partner. Attachment Theory (Bartholomew & Horowitz, 1991) - FB message with combination of (un) attractive photo and ambiguous text - Sixteen negative emotions (including jealousy) selected from Richins' (1997) cluster of emotion descriptors Females experienced more negative emotion across conditions. Regardless of gender, the attractive sender photo and winking emoticon message predicted more negative emotion than other nonverbal cues. Preoccupied attachment was positively associated with negative emotion, while dismissive attachment was negatively associated with negative emotion. Hudson et al. (2015) Study 1 n ¼ 83; 50% female; Mage ¼ 19.94; RS ¼ 42% current Cross-sectional survey with open- ended response section exploring if user gender and type of emoticon predict emotional reaction to message on partner's FB wall. NA - Open-ended response about emotional reaction The majority of participants would confront partner. Males had higher jealousy with wink face emoticon, while females had higher jealousy with no emoticon. Hudson et al. (2015)y Study 2 n ¼ 111; 54% female; Mage ¼ 19.87; RS ¼ 50.5% current Experimental design testing the effect of a wink face emoticon and no emoticon on FB jealousy of message recipient's partner. NA - FB message with wink face or no emoticon - FB Jealousy Scale Females showed higher jealousy than males. No effect for emoticon condition. Hudson et al. (2015)y Study 3 n ¼ 177; 53% female; Mage ¼ 20.20; RS ¼ 46.9% current Experimental design testing the effect of no emoticon, a wink face emoticon, and a smiling face emoticon on FB jealousy of message recipient's partner. NA - FB message with no emoticon, wink face, or smiling face emoticon - FB Jealousy Scale Females showed higher jealousy than males. No effect for emoticon condition. Muscanell et al. (2013) y n ¼ 226; 70% female; Mage ¼ 19; 86% White; RS ¼ 100% current Experimental design testing the effect of partner's FB photo privacy settings and number of dyadic FB photos on negative emotion. NA - FB photo privacy settings (public, friends only, private) - Dyadic FB photos - Single item Likert ratings of jealousy, anger, disgust, and hurt Females showed more jealousy, hurt, and anger than males. More negative emotions were observed when partner did not have dyadic photos and when photos were set to private. Muise et al. (2014) y Study 1 n ¼ 160; 48% female; Mage ¼ 19.16; 85.4% White; RS ¼ 51.9% seriously dating 1 person, 34.4% single, 10% casually dating, 3.8% in open relationship Experimental design testing the effect of familiarity with the individual appearing with one's partner in an ambiguous photo on the partner's FB wall on partner monitoring, and FB jealousy. NA - Ambiguous photo of partner and member of the opposite sex of varying familiarity (unknown, mutual friend, cousin) - 9 Items adapted from Multidimensional Jealousy Scale (Pfeiffer & Wong, 1989) - Partner monitoring: time spent viewing FB profile in seconds Females more jealous in general, especially when viewing photo of partner with unknown ormutual friend. Amount of time females spend searching FB profiles corresponded to amount of jealousy; inversely related for males. Muise et al. (2014) Study 2 n ¼ 108 heterosexual couples; Mage ¼ 21.05; 40% European, MRL ¼ 19.78, SD¼ Cross-sectional survey exploring if FB jealousy, gender, and attachment style predict partner monitoring. Attachment Theory (Collins & Read, 1990) - FB Jealousy Scale - Multidimensional Jealousy Scale - ECR-Short Form (Wei et al., 2007) - FB use: minuets per day - Partner surveillance: minutes per day viewing partner's FB profile Females spend more time monitoring partner's FB activity in response to jealousy. Higher attachment anxiety increased partner monitoring for females, not males. Trait jealousy was significantly associated with monitoring. H .M .Rus,J.Tiem ensm a / Com puters in H um an Behavior 75 (2017) 684 e 703 688 Utz and Beukeboom (2011) n ¼ 194; 71% female; Mage ¼ 22; RS ¼ 76% current; MRL ¼ 24.98 Cross-sectional survey exploring if relationship satisfaction, trait jealousy, SNS use, need for popularity, monitoring behavior, and self-esteem predict SNS jealousy and happiness. NA - Relationship satisfaction (1 item) - Trait jealousy (1 item) - FB Jealousy Scale - SNS use: frequency of logging in (6 points: several times per day - several times per month) - Need for Popularity Scale (Santor, Messervey, & Kusumaker, 2000) - SNS monitoring behavior: items from SNS Jealousy scale - RSE (Rosenberg, 1979) - SNS happiness scale (5 items)* - SNS Jealousy Scale (adapted FB jealousy scale) In general, participants reported more happiness than jealousy in response to partner's online behavior; however, those with low self- esteem experienced more jealousy than those with high self-esteem. Monitoring behavior predicted jealousy. Utz et al. (2015) n ¼ 77; 76% female; Mage ¼ 22; 31 Scottish, 24 English, 3 from outside Europe, remaining from other European countries Cross-sectional, within-subjects survey comparing if FB and Snapchat use predict user jealousy. NA - FB and Snapchat use: frequency of logging in (6 points: several times per day - several times per month); number of snaps sent in a week - FB Jealousy Scale (modified for Snapchat) Jealousy was higher with Snapchat, especially when partner communicated with ex-partner or unknown member of opposite sex. Attachment Style Emery et al. (2014) Study 1 n ¼ 217; 56.7% female; Mage ¼ 30.71; RS ¼ 100% current; MRL ¼ 62.76 Cross-sectional survey exploring if attachment style predicts desired vs actual FB relationship visibility. Attachment Theory (Collins & Read, 1990) - ECR-Short Form - Perception of relationship quality (3 items) - Perceived independence from partner (2 items) - Desired FB relationship visibility - Dyadic FB relationship display - FB use: (8 points: rarelyd > 2 h per day) Anxious attachment predicted desire for higher visibility, while avoidant attachment predicted low desired and actual visibility. Belief that others perceived low quality relationship motivated low visibility in avoidantly, and high visibility in anxiously attached people. Emery et al. (2014) y Study 2 n ¼ 586; 53.9% female;Mage ¼ 31.4; RS ¼ 100% current; MRL ¼ 76.44 Experimental design testing the effect of priming attachment style on desired FB relationship visibility Attachment Theory (Collins & Read, 1990) - ECR-Short Form - Desired FB relationship visibility - FB use: (8 points: rarelyd > 2 h per day) Priming for avoidance predicted lower desired visibility than priming for anxiety or a control prime. Emery et al. (2014) Study 3 n ¼ 108 heterosexual dating couples;Mage ¼ 21.05; MRL ¼ 19.78 Repeated measures cross-sectional survey exploring if attachment style and daily insecurity predict FB relationship visibility Attachment Theory (Collins & Read, 1990) - ECR-Short Form - Daily feelings of insecurity about partner (1 item) - Dyadic FB relationship display - Posting relationship-relevant information on FB - FB use: minutes per day (0-600 range) Avoidant attachment predicted less visible relationship for self and partner. Anxious attachment not associated with visibility. Daily insecurity predicted increased relationship disclosure for self but not partner. Fox and Warber (2014) n ¼ 328 42% female; Mage ¼ 20.68; 81.7% White; RS ¼ 61% current Cross-sectional survey exploring if attachment style and relationship uncertainty predict partner surveillance. - Attachment Theory (Bartholomew & Horowitz, 1991) Uncertainty Reduction Theory (Knobloch & Solomon, 1999) - Bartholomew and Horowitz (1991) Attachment Measure - Knobloch & Solomon (1999) Rela- tional Uncertainty Scale - Partner surveillance: ISS (Tokunaga, 2011) Fearful and Preoccupied individuals had highest levels of relationship uncertainty and partner surveillance. Marshall et al. (2013) Study 1 n ¼ 255; 79% female; Mage male ¼ 21.44, Mage female ¼ 22.53; 66% North American; RS ¼ 100% current: 69% exclusively dating; MRLmale ¼ 20.23, MRLfemale ¼ 22.82 Repeated measures design exploring if attachment style predicts FB jealousy and partner surveillance. Attachment Theory (Collins & Read, 1990) - ECR-R (Fraley et al., 2000) - FB Jealousy Scale - Partner surveillance: frequency of looking at partner's FB profile (5 points: never e very often) Anxious attachment was positively associated, and avoidance attachment was negatively associated with FB jealousy and surveillance. Anxious association partially mediated by lower trust. Marshall et al. (2013) Study 2 n ¼ 108 heterosexual dating couples; Mage male ¼ 26.93, Mage female ¼ 25.36; 49% European; RS ¼ 100% current: 32% exclusively dating, 37% cohabitating, 20% married, 11% engaged; MRL¼ 28.62 Repeated measures cross-sectional survey exploring if attachment style and daily FB jealousy predict partner surveillance. Attachment Theory (Collins & Read, 1990) - ECR-R - FB Jealousy Scale - Partner surveillance: number of times checked partner's profile each day (6 points: 0e5 þ times) Anxious attachment was positively associated, and avoidance attachment was negatively associated with FB jealousy and surveillance. Anxious association was partially mediated by daily jealousy. (continued on next page) H .M .Rus,J.Tiem ensm a / Com puters in H um an Behavior 75 (2017) 684 e 703 689 Table 1 (continued ) Authors Sample Study Aim and Design Theoretical Framework Measures/Stimuli Findings Relationship Characteristics Satisfaction Hand et al. (2013) n ¼ 233; 60.5% female; Mage ¼ 20.82; RS ¼ 100% current: 80.3% exclusively dating; MLR ¼ 22.52 Cross-sectional survey exploring if time spent on FB predicts intimacy and relationship satisfaction. NA - FB use: respondent use and perceived partner use on weekdays and weekends - DAS (Spanier, 1976) - RAS (Hendrick, 1988) - PAIR Inventory (Schaefer & Olson, 1981) Intimacy mediated the relationship between perceived partner FB use and relationship satisfaction such that higher intimacy buffered the negative relationship between perceived partner SNS use and relationship satisfaction. Papp et al. (2012) n ¼ 59 heterosexual couples; majority currently attending school; RS ¼ 0% married; MRL ¼ 19.6 Cross-sectional survey exploring if dyadic profile display and gender predicts relationship satisfaction. NA - Dyadic FB profile photo and FB status - Disagreement over FB relationship status - Conflict Subscale of Conflict Tactics Scale (Straus, 1979) - CSI (Funk & Rogge, 2007) Males' display of partnered status and females' inclusion of partner in profile photo linked to greater relationship satisfaction. Disagreement over status display linked to lower satisfaction in females. Saslow et al. (2013) Study 1 n ¼ 115; 61% female; Mage ¼ 36.62; RS ¼ 100% married; MRL ¼ 117.96; 75% European American Cross-sectional survey exploring if relationship satisfaction predicts dyadic profile display in married individuals. NA - Dyadic FB profile photo - 2 items averaged from PRQC (Fletcher, Simpson, & Thomas, 2000) Higher relationship satisfaction predicted greater likelihood of respondent posting dyadic profile photo. Gender did not moderate this association. Saslow et al. (2013) Study 2 n ¼ 148; 74% female; Mage ¼ 31.85; RS ¼ 100% married; MRL ¼ 78.12; 74% European American Repeated measures cross-sectional survey exploring if relationship satisfaction predicts dyadic profile display. NA - Dyadic FB profile photo at baseline, 4, and 12 months - 2 items averaged from PRQC - Hazan and Shaver (1987) attachment style descriptions Relationship satisfaction predicted tendency to post dyadic photos; however, tendency to post dyadic photos did not change over time. Gender and attachment style unaffiliated with positing dyadic photos. Saslow et al. (2013) Study 3 n ¼ 108 heterosexual couples; Mage ¼ 21.05; 40% European; MRL ¼ 19.78, SD ¼ 15.49 Cross-sectional survey exploring if relationship satisfaction predicts dyadic profile display. NA - 5 items from Investment Model Scale (Rusbult et al., 1998) measuring relationship satisfaction - ECR-Short Form - Presence of relationship-relevant posts on FB - Presence of dyadic profile photo - FB use: minuets per day Higher relationship satisfaction predicted greater likelihood of respondent and partner posting dyadic profile photo. Participants more likely to post relationship-relevant information on days when satisfaction was higher. Elphinston and Noller (2011) n ¼ 342; 57% female; Mage ¼ 19.75; 100% Australian; RS ¼ 100% current: 86.9% dating, 13.3% married or cohabitating; MRL ¼ 16.44; Cross-sectional survey exploring if FB intrusion predicts relationship satisfaction, jealousy, and partner surveillance. Investment Model Theory (Rusbult, 1980) - FB Intrusion Questionnaire* - 5 items from Investment Model Scale measuring relationship satisfaction - Short-Form Multidimensional Jealousy Scale (cognitive jealousy and surveillance behaviors; Elphinston, Feeney, & Noller, 2011) - FB use: hours per week Jealousy and surveillance fully mediated negative relationship between FB intrusion and relationship satisfaction. Commitment Dibble and Drouin (2014) n ¼ 374; 61% female; Mage ¼ 20.50; 55.7% Asian; RS ¼ 54% current Cross-sectional survey exploring if gender, commitment, and investment in current relationship predicts communication with “back burners” Investment Model Theory (Rusbult, 1980) - Commitment subscale from Investment Model Scale - Number of back burners in contact list - Nature of communication with back burner (romantic vs. platonic) Males have more back burners than females. Quality of alternative partners positively related to number of romantic and platonic back burners; however, total number of back burners unrelated to commitment or investment in current partner. Drouin et al. (2014) n ¼ 148; 74% female; Mage ¼ 20.59; 84% White; RS ¼ 100% current: 7% married, 28% live with partner; MRL ¼ 29 Cross-sectional survey exploring if commitment, jealousy, and attachment style predict FB solicitation behaviors. Investment Model Theory (Rusbult, 1980) Attachment Theory (Collins & Read, 1990) - Commitment subscale from Investment Model Scale - FB Jealousy Scale - FB friend solicitation behavior - Number of friends and romantic alternatives on FB Commitment negatively related to solicitation when in a relationship. FB jealousy mediated relationship between attachment anxiety and solicitation behaviors. H .M .Rus,J.Tiem ensm a / Com puters in H um an Behavior 75 (2017) 684 e 703 690 2 Negative emotion was measured as the likelihood of experiencing 16 negative emotions (including jealousy) from Richins' (1997) scale. H.M. Rus, J. Tiemensma / Computers in Human Behavior 75 (2017) 684e703 6933.1.6. Uncertainty Reduction Theory Uncertainty Reduction Theory (Berger & Calabrese, 1975) states that partners use communicative behaviors to reduce uncertainty about their relationship. Knobloch and Solomon (1999) identified four distinct types of relational uncertainty: (a) behavioral uncer- tainty, referring to boundaries between acceptable and unaccept- able behaviors within the relationship; (b) mutuality uncertainty, referring to uncertainty about the reciprocity of feelings between partners; (c) future uncertainty, referring to uncertainty about the long-term future of the relationship; and (d) definitional uncer- tainty, referring to uncertainty about how the relationship is explained to third parties. Fox and Warber (2014) used this framework to assess if relationship uncertainty was associated with partner surveillance on Facebook. As hypothesized, high levels of relationship uncertainty predicted surveillance. Similarly, Stewart et al. (2014) found that specific types of uncertainty predicted both monitoring and relationship maintenance behaviors. 3.1.7. Theory of Planned Behavior The Theory of Planned Behavior (Ajzen, 1991) is a decision- making model with many behavioral applications. It posits that an individual's intention to behave is influenced by attitudes about the specific behavior, subjective norms surrounding the behavior (i.e., perceived social pressure to perform the behavior), and one's perceived behavioral control (i.e., perception over control of per- forming the behavior) (Ajzen, 1991). Darvell, Walsh, and White (2011) applied the framework to partner monitoring behavior among Facebook users, and found that more favorable attitudes towards monitoring and greater perceived social pressure to monitor predicted higher intentions to monitor, which in turn predicted behavior. 3.1.8. Synthesis and evaluation of theoretical framework Despite their apparent utility in understanding some SNS be- haviors, these applied theories do not yet account for affordances specific to SNSs. Prominent characteristics such as the permanence and public visibility of information shared on SNSs have not been incorporated into theoretical models of use. Similarly, models are yet to consider how frequency of contact (e.g., several times a day versus once a month) with specific types of information may in- fluence associations. Moving forward, accounting for such affor- dances will advance the development of unique theory appropriate to SNS use. 3.2. Individual characteristics The following individual characteristics related to relationships were examined among active SNS users of varying romantic rela- tionship status: jealousy and attachment style. The studies are presented in order by complexity of associations from least to most. 3.2.1. Jealousy Romantic jealousy is a complex emotion aroused by a partner's suspected or actual infidelity (Bringle & Buunk, 1991; Shackelford, LeBlanc, & Drass, 2000), which results in the experience of nega- tive emotions such as sadness, anger, and fear (Parrott & Smith, 1993). Affordances of SNSs (e.g., public relationship display and ability to observe a partner's communication with potential rivals) have inspired the belief that a type of romantic jealousy specific to SNS use may exist. Muise et al. (2009) developed the now widely used Facebook Jealousy Scale: a measure of romantic jealousy eli- cited by specific Facebook behaviors (e.g., “becoming jealous after seeing that your partner has received awall message from someone of the opposite sex”). The scale has been adapted to accommodate other SNSs, and serves as the primary measure of romantic jealousyin relation to SNS use (see Table 1 for exceptions included in this review). Only three studies (Muise et al., 2009, 2014; Study 2; Utz& Beukeboom, 2011) measured trait jealousy, indicating the greater interest indand perhaps importance ofdconsidering the influence of context-specific romantic jealousy. Two studies examined the influence of general SNS activity on feelings of jealousy. McAndrew and Shah (2013) found that females were more prone to Facebook-invoked jealousy than males; how- ever, males were better able to predict the gender differences in jealousy. In particular, females seemed unaware that their male partners would experience less jealousy than they would over behaviors such as communication with same-sex rivals. In devel- oping the Facebook Jealousy Scale, Muise et al. (2009) found that females were more jealous overall; however, spending more time on Facebook predicted higher jealousy even when controlling for individual, personality, and relationship factors. Several studies experimentally manipulated Facebook message content to assess its effect on jealousy. Fleuriet et al. (2014) found that females showed more negative emotion2 when hypothetically presented with finding an ambiguous message accompanied by different nonverbal cues on their partner's Facebook wall (i.e., written in all capital letters, followed by awinking emoticon, !!!, or a photo of an unknown (un)attractive member of the opposite sex). The attractive photo message predicted the most negative emotion across gender compared to the unattractive, text only, or all capital letter message while the winking emoticon predicted significantly more negative emotion than all scenarios except for the attractive photo. In a series of three studies, Hudson et al. (2015) also manipulated nonverbal cues (i.e., no emoticon, smiling emoticon, andwinking emoticon) accompanying an ambiguousmessage from a member of the opposite sex. Females showed higher jealousy overall. Type of emoticon only appeared to affect jealousy for males when it was winking and for females, when it was absent. In addition to what users post on each other's profiles, how partners display their relationships and grant access to information on their own profiles may also influence jealousy. Muscanell, Guadagno, Rice, and Murphy (2013) found that females reported more jealousy than males when imagining that their partner had posted a photo with a member of the opposite sex. However, jealousy differed depending on the photo's privacy settings and the number of dyadic photos of the couple. In particular, stringent privacy settings (viewable only to the user) predicted the highest jealousy across gender, while females were more jealous than males when the privacy settings were set to all Facebook friends or all Facebook users. Absence of dyadic photos predicted highest jealousy. Keeping track of what is being posted where and by whom might also provoke jealousy in romantic relationships. In a series of studies, Muise et al. (2014) found that males and females differed in partner monitoring after experiencing varying levels of potential threat to their relationship. Females spent more time searching Facebook (the subjectivemeasure of jealousy) after viewing a photo of their hypothetical partner with an attractive member of the opposite sex, particularly when the photo included an unknown or mutual friend (compared to a cousin). Males reported more jeal- ousy with the mutual friend and showed a search pattern opposite of their experienced jealousy (i.e., the least amount of searching in themutual friend condition). Using daily diary method, a follow-up study found that Facebook-related jealousy was associated with attachment anxiety, such that higher anxiety increased partner monitoring in females but not in males. H.M. Rus, J. Tiemensma / Computers in Human Behavior 75 (2017) 684e703694Although common, jealousy might not be the only emotion experienced by romantic partners using SNSs. Utz and Beukeboom (2011) found that participants were more likely to experience relationship happiness than SNS-related jealousy but that self- esteem moderated the relationship between SNS use and SNS jealousy such that those with lower self-esteem experienced more jealousy. In the same study, monitoring behavior and need for popularity predicted SNS jealousy, but different types of SNS use and relationship satisfaction did not. In one of the few studies comparing SNS platforms, Utz, Muscanell, and Khalid (2015) found that Snapchat may elicit more jealousy than Facebook. A within-subjects design directly compared the same behaviors conducted via the self-destructing message app and the flagship social network website. Regardless of gender, participants reported more overall jealousy when using Snapchat, particularly when one's partner added or messaged a previous partner or unknown person of the opposite sex. 3.2.2. Attachment Adult attachment is an individual characteristic that influences thoughts, emotions, and behaviors in romantic relationships (Collins& Allard, 2001). Several studies examined attachment as an underlying mechanism predicting SNS behaviors. Emery et al. (2014) found that anxious attachment predicted desire for higher relationship visibility (i.e., display of dyadic profile photos and relationship statuses on Facebook) while avoidant attachment predicted low desired and actual visibility. In addition, the belief that others perceived a low quality relationship motivated low visibility in avoidant, and high visibility in anxious individuals. A follow-up study found that priming for avoidance predicted lower desired visibility than priming for anxiety or a control condition. A third study used daily diaries to show that avoidant attachment predicted less relationship visibility for the respondent and the partner, while anxious attachment (respondent's or partner's) was not associated with visibility. Three recent studies looked at the relationship between attachment style and partner surveillance. Fox and Warber (2014) found that attachment predicted relationship uncertainty and (ex-)partner surveillance such that preoccupied and fearful in- dividuals reported the highest levels of each. Marshall et al. (2013) found that anxious attachment was positively associated, and avoidant attachment negatively associated with Facebook jealousy and surveillance, but that lower partner trust partially mediated the anxious association. A follow-up study found that anxious attachment was positively associated, and avoidant attachment negatively associated with Facebook jealousy and surveillance; however, daily jealousy partially mediated the anxious association. 3.2.3. Synthesis and evaluation of studies examining individual characteristics Jealousy has received the most attention regarding SNS use and romantic relationships. Access to ambiguous and otherwise un- available information has been cited as a potential source for SNS- induced jealousy (e.g., Muise et al., 2009), suggesting that the affordances of SNSs may enable this specific form of relationship conflict. Several studies showed evidence of this, specifically in relation to nonverbal message characteristics (Fleuriet et al., 2014; Hudson et al., 2015) and photos of one's partner with a member of the opposite sex (Muise et al., 2014; Muscanell et al., 2013). Social networking site-induced jealousy may also be influenced by indi- vidual characteristics such as gender, trait jealousy, attachment style, and self-esteem (McAndrew& Shah, 2013; Muise et al., 2009, 2014; Utz & Beukeboom, 2011) as well as by behaviors such as partner monitoring (Utz & Beukeboom, 2011) and even platform- specific features (Utz et al., 2015).Studies assessing associations among SNS use and jealousy used a variety of samples and methods, some of which may have strengthened studies or limited conclusions. McAndrew and Shah (2013), Hudson et al. (2015), and Fleuriet et al. (2014) each included fewer than 100 participants; however, Fleuriet et al. (2014) utilized an experimental design to assess the ef- fect of nonverbal message characteristics on jealousy. Similarly, Hudson et al. (2015) studies 1 and 2, Muscanell et al. (2013), and Muise et al. (2014) study 1 each used experimental design, making for stronger causal conclusions. Samples being primarily female (>70%) may have influenced the findings of Muise et al. (2009), Muscanell et al. (2013), Utz and Beukeboom (2011), and Utz et al. (2015). Future research should strive to include large, diverse samples, and incorporate sound methodology. Given that the majority of studies used the Facebook Jealousy Scale (Muise et al, 2009) validating this scale and establishing it as a standard measure should hold primacy. Doing such will facilitate more meaningful cross-study comparison and research synthesis. Adult attachment motivates offline relationship behaviors (Collins & Allard, 2001), potentially accounting for its associations with relationship display (Emery et al., 2014), jealousy (Marshall et al., 2013; Muise et al., 2014) and partner surveillance (Fox & Warber, 2014). Avoidant attachment appeared to be associated with SNS behaviors reflective of a dislike for closeness such as reduced relationship visibility (Emery et al., 2014) and lower jeal- ousy (Marshall et al., 2013). Anxious attachment was associated with SNS behaviors reflective of fear of abandonment such as higher relationship visibility (Emery et al., 2014) and more partner surveillance (Marshall et al., 2013). Both Emery et al. (2014) studies 1 and 2 and Marshall et al. (2013) study 2 included adult partici- pants recruited from outside a university setting (mean ages, 30.71, 31.4, and 26.14, respectively). However, associations among attachment style and SNS use appear similar to those found in the undergraduate, emerging adult sample (mean age¼ 20.68) used by Fox and Warber (2014). Thus, associations may generalize to different age groups. Studies examining adult attachment benefitted from several methodological features, including large sample size (in partic- ular, Emery et al. (2014) study 1), inclusion of dating couples (Emery et al., 2014 study 2; Marshall et al., 2013 study 2), and use of validated measures (Emery et al., 2014; Fox & Warber, 2014; Marshall et al., 2013). Given that most studies included the Ex- periences in Close Relationships-Revised (ECR-R; Fraley, Waller, & Brennan, 2000) or ECR-Short Form (Wei, Russell, Mallinckrodt, & Vogel, 2007), these measures should perhaps become standardized when measuring adult attachment in this context. Studies that have directly examined the individual character- istics of jealousy and adult attachment style as potential mecha- nisms of association show a logical link between online and offline behaviors. With the exception of SNS-induced jealousy, the iden- tified associations suggest that SNSs enable behaviors in a new context that likely otherwise already exist. For example, anxiously attached individuals now have Facebook to display and reinforce their relationship status when expressing their fear of abandon- ment previously relied on other means. The shift in accessibility to one's partner provided by SNSs perhaps marks a more significant change in how romantic jealousy will play out. Many studies indicate that it is the unprecedented access to informationdin particular, ambiguous informationdabout one's partner that may invoke jealousy. Given the wide adoption of SNSs, monitoring the perhaps contemporary evolution of jealousy will become important. H.M. Rus, J. Tiemensma / Computers in Human Behavior 75 (2017) 684e703 6953.3. Relationship characteristics The following relationship characteristics were examined among active SNS users of varying romantic relationship status: relationship satisfaction, commitment, and partner identity over- lap. The studies are presented in order by complexity of associa- tions from least to most. 3.3.1. Satisfaction Relationship satisfaction reflects an evaluation of feelings, thoughts, and behaviors associated with a romantic relationship (Hendrick, 1988). Several studies looked at the connection between SNS use and relationship satisfaction. Hand, Thomas, Buboltz, Deemer, and Buyanjargal (2013) found that partner intimacy mediated the negative relationship between perceived partner Facebook use and relationship satisfaction, suggesting that higher intimacy may buffer the negative influence of perceptions of one's partner using Facebook. Several studies considered the influence of dyadic relationship display on satisfaction. Papp, Danielewicz, and Cayemberg (2012) found that females' inclusion of their partner in profile photos and males’ display of partnered status (e.g., Facebook status of “in a relationship”) were linked to greater satisfaction, but that disagreement over dyadic status display was linked to lower satisfaction in females but not males. Similarly, Saslow et al. (2013, studies 1 and 2) found that regardless of gender, higher satisfaction predicted greater likelihood of married individuals posting dyadic profile photos both cross-sectionally and over a one year period. In a follow-up study, dating couples showed the same pattern and were particularly likely to post relationship-relevant information on days when satisfactionwas higher; however, an effect for gender was not tested. Elphinston and Noller (2011) developed a measure of Facebook Intrusion (i.e., excessive attachment to the website to the point of daily life and relationship disruption) to predict satisfaction along with jealousy and partner surveillance. Time spent on Facebook was not associated with satisfaction; however, jealousy and sur- veillance fully mediated the negative association between Face- book Intrusion and satisfaction, suggesting that excessive attachment to the site may only negatively influence romantic re- lationships through romantic jealousy. 3.3.2. Commitment Commitment can be defined as feelings of psychological attachment to one's partner (Rusbult et al., 1998). Evaluations of one's own as well as a partner's level of commitment have been identified as influential features of relationship dynamics (Cloven& Roloff, 1993; Samp & Solomon, 2001). Several studies considered relationship commitment as a predictor for various SNS behaviors. Dibble and Drouin (2014) found no significant differences in number of “back burners” (defined as potential relationship alter- natives of romantic and/or sexual pursuit) based on current rela- tionship status (single vs. coupled), however males had more back burners than females. Total number of back burners was unrelated to commitment or investment in current partner; however, perceived quality of alternative partners was positively related to the number of romantic and platonic back burners. Drouin et al. (2014) found that commitment was negatively related to Facebook solicitation behaviors (defined as sending or accepting a friend request from a romantic interest) while currently in a relationship, but not when single. Further, Facebook jealousy mediated the relationship between attachment anxiety and solic- itation behavior such that higher jealousy predicted more solici- tation behavior while in a relationship for anxiously attached individuals.Using dependence power, (Cloven & Roloff, 1993), Samp and Palevitz (2014) found that those low in dependence power (i.e., respondents who perceived that they were more dependent on their partners) were more likely to perceive a hypothetical part- ner's transgression (viewing an ambiguous message on their partner's Facebook wall) as a threat as well as to use indirect Facebook partner monitoring behaviors after the threat. Alterna- tively, those high in dependence power (i.e., the partner was more dependent on the respondent) showed greater likelihood of con- fronting the partner face-to-face after the threat. 3.3.3. Partner identity overlap Close relationships often lead to partners incorporating each other's interests into their own identities (Aron & Aron, 1986). Two studies examined identity incorporation as a predictor of Facebook profile similarity. Using the Inclusion of Self in Others Scale (IOS; Aron et al., 1992) as a measure of partner identity incorporation, Carpenter and Spottswood (2013) found that incorporation was unrelated to general Facebook use or to the number of mutual friends between partners; however, greater incorporation pre- dicted greater likelihood of displaying and tagging one's partner in dyadic photos. Similarly, Casta~neda et al. (2015) used the IOS scale along with the Investment Model Scale (Rusbult et al., 1998) as a measure of commitment and satisfaction to predict Facebook pro- file overlap. Again, greater identity incorporation predicted more profile overlap, in this case supported by higher commitment and relationship investment. 3.3.4. Synthesis and evaluation of studies examining relationship characteristics It appears that characteristics of the relationship (i.e., levels of satisfaction and commitment) may both influence, and be influ- enced by specific SNS behaviors. For example, relationship satis- faction may be both an indicator and consequence of how partners choose to display their relationship within an SNS (Papp et al., 2012; Saslow et al., 2013). Similarly, likelihood of contacting romantic alternatives via SNSs appears to be linked to commitment to one's current partner (Drouin et al., 2014), while commitment may also determine how threatening partners perceive certain SNS behaviors to be (Samp & Palevitz, 2014). Additional relationship characteristics and SNS behaviors such as intimacy (Hand et al., 2013), jealousy, and partner surveillance (Elphinston & Noller, 2011) may further influence associations among these constructs. Partner identity incorporation may influence relationship display and SNS profile overlap, which may also reflect commitment and relationship investment (Carpenter& Spottswood, 2013; Caste~neda et al., 2015). Studies including adults recruited from outside of a university setting suggest that certain associations related to relationship satisfaction and SNS use may be age-specific. Saslow et al. (2013) studies 1 and 2 included married adult participants (mean age ¼ 36.62, 31.85, respectively), and found that regardless of gender, greater relationship satisfaction predicted higher frequency of posting dyadic profile photos. The lack of gender differences seen in these older participants in relationships of longer duration (married for mean of 117.96 months) suggests that the influence of gender may be limited to a certain age range (i.e., in comparison to Papp et al. (2012) finding that dyadic display differently predicted relationship satisfaction for male and female emerging adults). Members within a social network, regardless of gender, are likely aware that other members of their network have been married for ten years, therefore dyadic relationship display may not be as important for perceptions of social network maintenance in an older demographic, making it less important to relationship satisfaction. H.M. Rus, J. Tiemensma / Computers in Human Behavior 75 (2017) 684e703698relational certainty. Similarly, Stewart et al. (2014) found that monitoring was not related to satisfaction; however, more moni- toring was used when partners perceived mutual and definitional uncertainty, and that partners used more assurances and openness to maintain the relationship in the absence of future and defini- tional uncertainty.3.4.2. Infidelity and divorce Research concerning online infidelity suggests that partners share high consensus about what constitutes unacceptable behavior (Helsper & Whitty, 2010). However, very limited research has empirically assessed the association between SNS use and such extreme relationship outcomes. To date, only two studies have examined the connection between SNS use, infidelity, and romantic relationship termination. Clayton et al. (2013) found that Facebook- related conflict (e.g., arguing with a partner over excessive Face- book use) mediated the relationship between Facebook use and negative relationship outcomes (i.e., infidelity, breakup, and divorce) but only for those who had been in relationships for three years or less. Clayton (2014) found that Twitter-related conflict mediated the relationship between Twitter use and negative rela- tionship outcomes; however, length of relationship was not significant.3.4.3. Synthesis and evaluation of studies examining behavioral actions Social network sites appear to serve a function for maintaining romantic relationships. Maintenance behaviorsdboth routine and strategicdperformed via Facebook appear to be related to rela- tionship satisfaction (Dainton, 2013). Partner monitoring as a maintenance behavior may result from and motivate feelings of jealousy, trust, and relationship uncertainty (Billedo et al., 2015; Darvell et al., 2011; Stewart et al., 2014). Constant access to one's partner seems to be both a beneficial and potentially harmful affordance of SNSs. In romantic relationships, infidelity and divorce constitute the extreme in terms of potential negative outcomes. Despite the considerable amount of research on possible sources of relationship conflict, limited work has directly assessed how SNS use may contribute to such dramatic consequences. Cross-platform studies on Facebook and Twitter (Clayton, 2014; Clayton et al., 2013) sug- gest that partners’ disagreement over SNS use may determine its role in infidelity and divorce more so than SNS use in general. Both Clayton (2014) and Clayton et al. (2013) included adult participants recruited outside of a university setting (mean age 29 and 33, respectively). Assessing this age demographic was appropriate considering the constructs of interest (i.e., infidelity and divorce). However, given that associations were linked to SNS-related part- ner conflict (presumably something not age dependent), similarTable 3 Measurement methods for partner monitoring/surveillance. Authors Measurement Billedo et al. (2015) Interpersonal Elect Darvell et al. (2011) Frequency of check Elphinston and Noller (2011) Items from Multidi Fox and Warber (2014) Interpersonal Elect Marshall et al. (2013) Study 1 Frequency of lookin Study 2 Number of times ch Muise et al. (2014) Study 1 Seconds spent view Study 2 Minutes/day viewin Stewart et al. (2014) Items from the FB J Utz and Beukeboom (2011) Items from the FB J Note. FB ¼ Facebook. Studies not included either did not measure partner monassociations may exist within an emerging adult demographic as well. Future work should expand inquiry into this younger sample to better assess if the influence of SNS-related conflict transcends age. A considerable strength of studies examining relationship maintenance and partner monitoring was use of theoretical frameworks. With one exception (Darvell et al., 2011), all studies used Relational Maintenance Theory (Canary & Stafford, 1992), suggesting that this theory may be appropriately applicable to online behavior. Although studies assessing maintenance and monitoring included large (>180) sample sizes, the majority had an overrepresentation of females (>69%). In addition, although measuring the same general constructs (maintenance and moni- toring), studies used a wide variety of measures (see Tables 1 and 2), with very little overlap or even consensus on defining moni- toring behavior (see Table 3). Given the unprecedented capacity for partner monitoring that SNSs enabledand the potential detri- mental consequences of this behaviordstandardizing definition and measurement of partner monitoring is crucial for future research. Studies examining infidelity and divorce provide valuable insight into the role of SNSs in such extreme relationship outcomes. Both Clayton (2014) and Clayton et al. (2013) included homogenous samples (likely due to participants being recruited from the au- thor's own SNS networks); however, the simple cross-sectional survey design highlighted the importance of SNS-related partner conflict. To date, no other studies have looked at such extreme relationship outcomes and SNS use, something that is of consid- erable interest given the potential interpersonal, emotional, and even financial consequences of romantic relationship termination. As with both individual characteristics and relationship char- acteristics, behavioral actions appear to have a complicated asso- ciation with SNS use and romantic relationship constructs. Similar to behavior related to adult attachment style, commitment, and satisfaction, SNSs appear to provide a context allowing otherwise existing behaviors to play out (e.g., partner monitoring). However, given the ease of monitoring that SNSs facilitate, doing such could be seen as a behavior allowed or created by the context, similar to SNS-induced jealousy. Greater access to potential alternative part- ners granted by SNSs may also encourage infidelity; however, as with many other behaviors and associations, SNSs appear to be a vehicle for enabling such behavior rather than a source of cause.4. Discussion The global adoption of SNSs has led many to question the as- sociation between use and romantic relationships. This review serves as a guide for synthesizing the current state of knowledge while remaining cognizant of the highly interrelated nature ofronic Surveillance Scale for SNSs (Tokunaga, 2011) ing partner's FB profile in past week on 7 pt scale: neverdat every login mensional Jealousy Scale (Pfeiffer & Wong, 1989) ronic Surveillance Scale for SNSs (Tokunaga, 2011) g at partner's FB profile on 5 pt scale: neverdvery often eck partner's FB profile each day on 6 pt scale: 0d5þ ing a FB profile g partner's FB profile ealousy Scale (Muise et al., 2009) ealousy Scale (Muise et al., 2009) itoring/surveillance, or did not report how it was measured. H.M. Rus, J. Tiemensma / Computers in Human Behavior 75 (2017) 684e703 699many observed constructs and the continual development of theory-guided investigation. Due to the current state of the litera- ture, the majority of included studies focused on emerging adult, university students. Characteristics definitive of this developmental period and demographic likely influence associations among SNS use and romantic relationships. However, discrepancies and simi- larities between slightly older adult samples were highlighted where possible. This article aimed to provide a systematic review of research concerning associations between SNS use and romantic relationships as well as provide suggestions for future research directions. Each specific aim is addressed below.4.1. Theory-based approaches for identifying associations between SNS use and romantic relationships Several theories were used in examining the association be- tween SNS use and romantic relationships. Relational Maintenance Theory (Canary & Stafford, 1992) guided investigation of the function of social media for communication and surveillance among long-distance and geographically close romantic partners, and showed that partners do employ common offline behaviors online. (Billedo, Kerkhof, & Finkenauer, 2015; Dainton, 2013; Stewart et al., 2014). Carpenter and Spottswood (2013) and Casta~neda et al. (2015) used Self-Expansion Theory (Aron & Aron, 1986) to show that overlap in partner identity predicted overlap in Facebook profiles. Darvell et al. (2011) used the Theory of Plan- ned Behavior (Ajzen, 1991) to predict partner monitoring behavior on Facebook, and found that attitudes and social norms influenced intentions, which predicted behavior. Rusbult's (1980) Investment Model was used to predict SNS communication with romantic al- ternatives (Dibble & Drouin, 2014; Drouin et al., 2014), and showed that commitment may differently relate to communication depending on relationship status and communication method. Attachment Theory (Bartholomew & Horowitz, 1991; Collins & Read, 1990) was used to predict relationship display (Emery et al., 2014), partner surveillance (Fox & Warber, 2014; Marshall et al., 2013) and jealousy (Fleuriet et al., 2014), and showed that attach- ment predicted SNS behaviors characteristic of the style. Uncer- tainty Reduction Theory (Berger & Calabrese, 1975; Knobloch & Solomon, 1999) was used in predicting both partner surveillance (Fox & Warber, 2014) and relationship maintenance behaviors (Stewart et al., 2014). Samp and Palevitz (2014) used dependence power (Cloven & Roloff, 1993) to show that perceived relationship dynamics may influence both threat perception and behavioral reaction to partner's SNS behavior. Use of these theories reflects the multifaceted nature of SNS research and shows the utility in examining certain behaviors from multiple perspectives. As the field moves forward, theory will have to remain flexible in accounting for the ever-evolving nature of computer-mediated communication.4.2. Key romantic relationship constructs measured in relation to SNS use Constructs of interest varied between studies. However, inter- related, but distinct enough themes allowed for categorization of studies into three key areas. Studies focusing on individual char- acteristics included constructs of romantic jealousy and adult attachment style. Studies addressing relationship characteristics focused on relationship satisfaction, commitment, and partner identity overlap. Finally, studies assessing behavioral actions looked at SNS use for relationship maintenance and partner monitoring, as well as associations between SNS use, infidelity, and divorce.4.3. Synthesis of mechanisms by which SNS use is associated with romantic relationships Synthesis of the literature on SNS use and romantic relation- shipsmakes it clear that associations cannot be easily dichotomized as beneficial or harmful. Rather, the influence of interrelated con- structs appears to depend on many factors. Studies focusing on romantic jealousy showed that access to ambiguous or otherwise unavailable information about a partner may lead to SNS-induced jealousy (McAndrew & Shah, 2013; Muise et al., 2009; Muscanell et al., 2013; Utz & Beukeboom, 2011; Utz et al., 2015). Affordances specific to SNS communica- tion such as photos and emoticons may be particularly prob- lematic (Fleuriet et al., 2014; Hudson et al., 2015; Muise et al., 2014). Studies focusing on adult attachment style showed that users may express characteristics of certain styles in online be- haviors such as relationship display and partner monitoring (Emery et al., 2014; Fox & Warber, 2014; Marshall et al., 2013). Relationship satisfaction and commitment appear to both influ- ence and be influenced by specific SNS behaviors such as con- tacting romantic alternatives and perceiving a partner's SNS behavior as threatening (Dibble & Drouin, 2014; Drouin et al., 2014; Elphinston & Noller, 2011; Hand et al., 2013; Papp et al., 2012; Samp & Palevitz, 2014; Saslow et al., 2013 study 3). Part- ner identity incorporation may influence display on SNS profile, which may also reflect commitment and relationship investment (Carpenter & Spottswood, 2013; Caste~neda et al., 2015). Social network sites appear to serve both maintenance and monitoring functions in romantic relationships, which may be related to levels of satisfaction (Billedo et al., 2015; Dainton, 2013; Darvell et al., 2011; Stewart et al., 2014). Conflict over use by a partner may be linked to SNS's role in infidelity and divorce (Clayton, 2014; Clayton et al., 2013). Given the breadth of topics covered and the lack of standardized measures, comprehensive synthesis and conclusion is difficult. However, distinction can be drawn between studies identifying behaviors or characteristics enabled by SNSs (i.e., behaviors perhaps enacted differently on an SNS, but behaviors that do not require an SNS to exist) and behaviors created by SNSs. Social network sites appear to enable or enhance behaviors related to adult attachment style, relationship satisfaction, commitment, partner identity overlap, and relationship maintenance. Partner surveillance and SNS-induced jealousy have arguably been created by SNSs as they otherwise would not exist without this context (or at least not to the same extent in the case of partner surveillance). As previously described, associations among all constructs, characteristics, and behaviors appear to be dynamic and highly interrelated, with causal pathways yet to be identified. Moving forward, highlighting the difference between how SNSs have simply provided a new context for existing behaviors and how SNSs have inspired new behaviors can provide key insight into how SNSs may shape romantic relationships. 4.3.1. The role of gender Transcendent of study topic or domain, one theme emerged as central to many findings. Gender appears to be highly intertwined in the dynamic interplay between SNS use and romantic re- lationships. Trends may be related to the social function that SNSs may serve particularly for females. Because females spend more time maintaining social relationships (Eagly &Wood, 1999; Eagly, 1987), it is plausible that females may be more susceptible than males to feeling threatened by the affordances of SNSs (e.g., high visibility and constant access to one's social network). For example, Muscanell et al. (2013) found that females were more jealous when a potential threat to their relationship was visible to H.M. Rus, J. Tiemensma / Computers in Human Behavior 75 (2017) 684e703700all members of their social network compared to when their partner attempted to keep it hidden, implying that exposure of the threat might be perceived as worse than the threat itself. In contrast, Utz et al. (2015) found that their small (n ¼ 77) and predominantly female (76%) sample experienced more jealousy on Snapchat, a muchmore private form of SNS, when compared to Facebook, especially when their partner directly communicated with a member of the opposite sex. Perceptions surrounding Snapchat's affordances (i.e., its intended use as a much more private form of communication) might account for these findings. That is, users feel more jealousy knowing that their partner is directly communicating with a potential rival versus communi- cating in a more public sphere. Ambiguity of threat also seems to play a role in how males and females experience jealousy. Hudson et al. (2015) found that males were more jealous than females when reading an ambiguous message containing a winking emoticonda recognized signal of flirtation (Walthier & D'Addario, 2001)dwhile females were most jealous in the absence of an emoticon. Similarly, Muise et al. (2014) found that males reported more jealousy when viewing an ambiguous photo of their partner with a mutual friend of the opposite sex while females reported beingmost jealous in response to an unknown member of the opposite sex. Offline research in- dicates that females may have a stronger reaction to cues of emotional infidelity while males react more strongly to sexual in- fidelity (Buss & Schmitt, 1993; Buunk & Dijkstra, 2004)da differ- ence that may translate to online behavior. In addition to jealousy, gender also appears to influence satis- faction. This again may reflect the social function that SNSs may serve for females. For example, Papp et al. (2012) found gender differences in satisfaction based on type of dyadic display (photo versus status). Specifically, on Facebook dyadic relationship display in a photo is much more obvious than in a relationship status (i.e., the photo is the prominent feature of the user's profile page and appears in any place that the user makes a post, while the rela- tionship status is only visible on the user's profile page and even then may require searching to find). That higher relationship satisfactionwas linked to dyadic photo display for females might in part reflect a function of social network maintenance. That is, satisfaction with the relationship may be tied to high visibility within females' social networks. Similarly, disagreement over dyadic status display reduced satisfaction for females. The authors did not report if the disagreement concerned the user's or their partner's status, however the fact that any disagreement reduced satisfaction for females may reflect perceived damage to social network maintenance. That is, male partners may not have pro- vided the relationship visibility that females wanted within their social network, which reduced relationship satisfaction. It is also possible that couples with lower relationship satisfaction are more likely to disagree over dyadic relationship displays given that causal directionality cannot be determined from this study. Saslow et al. (2013) found no gender differences in satisfaction in emerging adults (study 3) or in married adults (studies 1 and 2). For emerging adults, this may have been due to only dyadic profile photos being considered compared to both dyadic photos and dyadic statuses in Papp et al. (2012). For married adults, this may reflect different perceptions of social network maintenance in an older demographic. In sum, gender appears to be related to SNS use and romantic relationships in ways that could reflect the different social function of SNSs for males and females. Considering the heavy adoption of SNSs by females (Duggan et al., 2015), future research should consider gender as a potential underlying mechanism driving apparent associations.4.4. SNS use and romantic relationships across ages Few studies have considered SNS use and romantic relationships outside of a university setting. Clayton (2014), Clayton et al. (2013), Emery et al. (2014) studies 1 and 2, Marshall et al. (2013) study 2, and Saslow et al. (2013) studies 1 and 2, eachmeasured associations in young adults (mean age
25), and suggest that some associa- tions may transcend specific developmental periods. Studies on attachment (Emery et al., 2014 studies 1 and 2; Marshall et al., 2013 study 2) indicate that certain attachment styles (e.g., avoidant, anxious) may be similarly affiliated with SNS behaviors (e.g., part- ner monitoring, relationship display) in both emerging adults and young adult populations. Saslow et al. (2013) studies 1 and 2 highlight how gender might differently relate to relationship satisfaction and SNS relationship display based on age and marital status. Finally, Clayton (2014) and Clayton et al. (2013) emphasize the need to study how SNS-related partner conflict might influence infidelity and divorce in younger, emerging adult samples. 4.5. Improved methods for guiding future research Several limitations became apparent during review of this literature. The majority of research was conducted on Facebook, making cross-platform comparison challenging. However, the few studies that did include different SNSs (Clayton, 2014; Dibble & Drouin, 2014; Utz & Beukeboom, 2011; Utz et al., 2015) suggested that there may be important SNS platform-specific affordances associated with romantic relationships. As research in this area continues to grow along with the popularity of SNS use, focus will likely broaden and allow for cross-platform comparisons. There was an over-representation of cross-sectional survey research, making for weaker conclusions about the relationships of interest. As such, it becomes more difficult to distinguish between potential explanatory factors such as relationship status, gender, age, and cultural influences on SNS use and romantic relationships. Considering the apparently complicated interplay among many relationship constructs and SNS behaviors, mixed methods and experimental work on specific associations would be appropriate. With few exceptions, the samples were relatively homogenous in terms of race/ethnicity, gender, age, sexual orientation, and relationship status. The majority of samples included Caucasian, female undergraduates, some of whom were single, and many of whom were in heterosexual romantic relationships of short dura- tion. It is possible that many of the identified associations between SNS use and romantic relationships are an artifact of this stage of lifedemerging adulthooddwhen romantic relationships are less established and more transient (Arnett, 2000). Twenty-year-olds may be more likely than older individuals to experience romantic jealousy regardless of the source. Similarly, SNSs may serve an entirely different purpose for older individuals in long-term romantic relationships (e.g., the lack of gender differences in rela- tionship satisfaction based on dyadic display seen in Saslow et al., 2013 studies 1 and 2). As such, 35- to 50-year-olds are the fastest growing group of SNS adopters (Duggan et al., 2015), highlighting the importance of studying broader age groups. However, emerging adulthood is an essential time for establishing and testing models of romantic relationships that may have long-term consequences (Fox & Anderegg, 2014), and 18- to 24-year-olds remain the prime demographic of SNS users (Duggan et al., 2015). Therefore, studying associations between SNS use and romantic relationships in this population will continue to be important. Several studies noted that homosexual participants were excluded because of the different implications SNSs may carry for romantic relationships in a marginalized social group. For example, relationship displaymay be differently related to satisfaction due to