Facebook Tells Me So: Applying the Theory of Planned Behavior to Understand Partner-Monitoring Behavior on Facebook

Abstract

The social networking site (SNS) Facebook is becoming increasingly recognized as a medium through which individuals can investigate and monitor others' activities. However, little is known about whether Facebook monitoring behavior occurs within romantic relationships and, accordingly, the psychological predictors of this behavior. The present study employed an extended theory of planned behavior (TPB) framework including self-esteem, partner trust, and demographic characteristics, to predict frequent Facebook partner-monitoring. Facebook users (N=244) in romantic relationships completed measures assessing the standard TPB constructs (attitude, subjective norm, and perceived behavioral control), additional predictor variables (self-esteem and partner trust), and demographic characteristics (age, gender, relationship length, daily Facebook logins, and time spent per login). One week later, participants reported their level of Facebook partner-monitoring during the previous week. Regression analyses supported the standard TPB constructs of attitude and subjective norm in predicting intentions to engage in frequent Facebook partner-monitoring, with intention, in turn, predicting behavior. Partner trust, but not self-esteem, significantly predicted frequent Facebook partner-monitoring intentions. Of the demographic characteristics, daily Facebook logins significantly predicted both intention and behavior and, unexpectedly, relationship length directly affected behavior. Overall, the current study revealed that frequent Facebook partner-monitoring is influenced by attitudinal, normative, and relational factors and, potentially, increased visits to Facebook. These findings provide a new understanding of an individual's use of the world's leading SNS to monitor their partner's activities and provide a foundation for future studies to investigate the potential negative implications this activity may have for those in romantic relationships.

Introduction

Facebook, the world's most popular online social networking site (SNS), is used by over 500 million individuals. Its mission is to “Give people the power to share and make the world more open and connected.”¹ Accordingly, Facebook promotes widespread sharing and access to others' information, including photographs, personal details, relayed thoughts, and conversations between other users. By design, Facebook facilitates surveillance as members can track the beliefs, actions, and interests of the larger group to which they belong,² providing a medium where monitoring, investigation, and even stalking behavior are considered acceptable use of the network.³ Despite increasing recognition that Facebook encourages such behaviors,⁴ the notion of using Facebook to monitor a partner's activities remains largely unexplored.

However, one study investigating Facebook use revealed that students (the majority of users) commonly used the site to check on their partners by searching their partner's profile for evidence of unfaithfulness, such as inappropriate messages or photos.⁵ More recently, Muise et al. (2009) found that increased Facebook use within student couples predicted jealousy-related feelings and behaviors, such as regularly checking a partner's profile and being suspicious of their online activities.⁶ In their study, participants reported that Facebook turns people into “nosey Parkers” and creates an urge to investigate a partner's profile that is too great to resist. Although potentially beneficial, the openness of Facebook, coupled with such checking and monitoring behavior, may offer a gateway for potentially problematic partner-monitoring to occur.

To investigate Facebook partner-monitoring, the present study adopts a well-validated decision-making model, the theory of planned behavior (TPB).⁷ The TPB posits that intentions are the most proximal determinant of behavior. Intention is influenced by three constructs: attitudes, an individual's positive or negative evaluation of performing a behavior; subjective norms, an individual's perceived social pressure to perform the behavior; and perceived behavioral control (PBC), an individual's perception of control over performing the behavior (also posited to directly predict behavior). The TPB has been applied to various behaviors, including those involving Internet use^8–11 and, specifically, SNS engagement.^12,13 A meta-analysis revealed that, on average, the model accounted for 39 percent and 27 percent of the variance in intention and behavior, respectively.¹⁴ Research also indicates that including additional variables may improve the predictive ability of the model.^7,14 This study explores the effects of two constructs known to affect individuals' behavior in romantic relationships, self-esteem and trust, and also examines the impact of demographic factors identified as influencing Internet and Facebook-specific behaviors.

Self-esteem

Self-esteem reflects an overall evaluation of how one perceives and feels about themselves.¹⁵ Within relationships, individuals with high self-esteem are thought to have greater confidence in their partner¹⁶ and feel more secure in their relationship.¹⁷ Conversely, low self-esteem has been linked with suspicion and jealousy in romantic associations.^18,19 Individuals with low self-esteem, then, may be more suspicious of their partner and more likely monitor their partner's Facebook activities. Although a previous study⁶ revealed that self-esteem did not predict Facebook-related jealousy, research is yet to investigative the role of self-esteem in relation to SNS monitoring-specific behavior.

Trust

Trust can be conceptualized as an individual's orientation toward the social world, which motivates daily behavior.²⁰ More specifically, partner trust refers to an individual's confidence in their romantic partner and/or their relationship.²¹ A previous study revealed that partner trust significantly predicted Facebook-related jealousy, such as feeling suspicious about a partner's Facebook activities and checking their Facebook profile.⁶ Since partner distrust is believed to encourage surveillance behaviors such as spying on a partner,²² individuals with low partner trust may be more likely to engage in frequent Facebook partner-monitoring.

Demographic factors

Various demographic factors may also contribute to Facebook partner-monitoring behavior. For instance, younger users spend more time on Facebook,²³ and females⁶ are more likely than males to use SNSs for relational purposes²⁴ and to monitor their partner's text messages and emails.²⁵ One study revealed an association between the desire to investigate others on Facebook and the frequency of visits to the site,²³ whereas another indicated that increased Facebook use may lead to increased surveillance of a partner's profile.⁶ Research also demonstrates that individuals frequently use Facebook to learn more about, and “get to know,” new acquaintances.^3–5 Thus, this study explores whether age, gender, Facebook use, and relationship length influence frequent Facebook partner-monitoring.

The present study

The present study examined the psychological determinants of Facebook partner-monitoring by applying an extended TPB to predict frequent Facebook partner-monitoring intentions and subsequent behavior. It was hypothesized that attitude, subjective norm, and PBC would predict intention to engage in frequent Facebook partner-monitoring (Hypothesis 1), and that intention and PBC would predict frequent Facebook partner-monitoring in the following week (Hypothesis 2). Based on previous research investigating the role of self-esteem and partner trust on couples' Facebook experiences,⁶ in an exploratory manner, self-esteem and partner trust were incorporated into the TPB to gauge whether they influenced intention (Hypothesis 3). Additionally, consistent with prior studies examining the impact of various demographic factors on both general and relational partners' use of Facebook and other SNSs,^{3–6,23–25} in an exploratory manner, the influence of the demographic variables of age, gender, relationship length, daily Facebook logins, and time spent per login was examined (Hypothesis 4).

Method

Participants

Participants (n=244; 190 female and 54 male) were required to be at least 18 years old, Facebook users, and in romantic relationships with partners who used Facebook. Participants were aged 18 to 47 years (M=21.80, SD=5.51) and were predominantly university students (89 percent). A majority of participants (n=171; 68 percent) completed the follow-up questionnaire 1 week later.

Design

The study employed a prospective design with two waves of data collection, 1 week apart. Before collecting data, a pilot study was conducted on 21 partnered Facebook users (16 female and 5 male, aged 21 to 35 years [M=23.19, SD=3.07]) to assist in defining and operationalising the target behavior. The main questionnaire assessed the standard TPB items, self-esteem and partner trust, and demographic characteristics. The second questionnaire assessed participants' self-reported level of Facebook partner-monitoring during the previous week.

Measures

Target behavior

Given that pilot study participants reported, on average, checking on their partner's activities between “never” to “once or twice weekly,” the target behavior of frequent Facebook partner-monitoring was defined in the main study as “using Facebook to check on your partner's activities at least 3 times a week.” To measure “check on your partner's activities,” descriptions obtained from the pilot study (e.g., checking your partner's profile, checking who your partner is in contact with, scanning your partner's wall posts and photos) were used. Additionally, participants were asked to think of all possible Facebook applications and features they might use to check on a partner's activities. At follow-up, approximately one-third (36 percent) of participants reported engaging in frequent Facebook partner-monitoring during the previous week (i.e., at least 3 times a week).

Main questionnaire

All TPB items in the main questionnaire were standard measures.⁷ Most items were positively worded, with some items negatively worded to reduce response bias. All items were scored on Likert scales, with the exception of attitude scored using sematic differential scales, and the demographic factors of age and gender.

TPB variables

Intention

Three items assessed intention to perform the target behavior (e.g., “I intend to use Facebook to check on my partner's activities at least three times in the next week”; 1, strongly disagree to 7, strongly agree).

Attitude

Attitude was assessed by four 7-point semantic differential scales (e.g., “For me, using Facebook to check on my partner's activities at least three times in the next week would be”; 1, good to 7, bad).

Subjective norm

Subjective norm was measured using four items (e.g., “Most people who are important to me would approve me using Facebook to check on my partner's activities at least three times in the next week”; 1, strongly disagree to 7, strongly agree).

Perceived behavioral control

Three items comprised the PBC measure (e.g., “If I wanted to I would use Facebook to check on my partner's activities at least 3 times in the next week”; 1, strongly disagree to 7, strongly agree). Due to low scale reliability, only the highest loading item reflecting the self-efficacy component of PBC (stated above) was used to measure PBC.

Additional variables: demographics, self-esteem, and partner trust

Demographics

Participants indicated their age, gender, length of their current relationship (1 [less than 1 month] to 6 [more than 5 years]), the number of times they logged onto Facebook each day (1 [not every day] to 6 [Facebook is continuously open on my computer throughout the day]), and the time spent per Facebook login (1 [5–10 minutes] to 5 [over an hour]).

Self-esteem

The well-validated 10-item Rosenberg Self-Esteem Scale¹⁵ assessed self-esteem (e.g., “I feel that I'm a person of worth”; 1, strongly agree to 4, strongly disagree).

Partner trust

Partner trust was measured by the 20-item partner trust subscale of the Trust Inventory,²⁶ previously reported as possessing excellent internal consistency, α=0.92²⁶ (e.g., “My partner makes me feel safe”; 1, strongly agree to 5, strongly disagree).

Follow-up questionnaire

One week after completing the main questionnaire, participants indicated how often in the past week they had used Facebook to check on their partner's activities (1, [never] to 7 [every time I logged on]).

Procedure

Ethics approval was obtained from the University's Ethics Committee. All data were collected online. One week after completing the main questionnaire, participants were e-mailed a link to the followup questionnaire. To protect anonymity, participants registered a unique code to match their main and followup questionnaire responses.

Results

Descriptive analysis of the data

The means, standard deviations, bivariate correlations, and reliabilities of the TPB and additional variables are shown in Table 1. Subjective norm was the strongest correlate of intention, with intention the strongest correlate of behavior. All scales possessed at least moderate reliability.

Table 1.

Means, Standard Deviations, Bivariate Correlations, and Reliabilities for Attitude, Subjective Norm, Perceived Behavioral Control, Self-Esteem, Partner Trust, Intention, Behavior (Frequent Facebook Partner-Monitoring), and Demographic Variables

Variable	M	SD	1	2	3	4	5	6	7	8	9	10	11	12
1. Attitude	3.21	0.51	(0.75)	0.65^**	0.32^**	−0.04	−0.25^**	0.70^**	0.43^**	−0.07	0.00	−0.20^**	0.15^*	0.15^*
2. Subjective Norm	3.89	1.42		(0.78)	0.41^**	−0.15^*	−0.32^**	0.76^**	0.47^**	−0.18^**	0.03	−0.23^**	0.31^**	0.15^*
3. PBC	5.06	1.73			–	0.05	−0.17^**	0.34^**	0.31^**	−0.01	−0.10	−0.15^*	0.17^**	−0.01
4. Self-Esteem	3.04	0.51				(0.90)	0.36^**	−0.11	−0.03	0.22^**	−0.15^*	0.09	0.04	−0.04
5. Partner Trust	3.90	0.68					(0.93)	−0.41^**	−0.27^**	0.11	−0.02	0.32^**	−0.18^**	0.01
6. Intention	3.40	1.81						(0.85)	0.64^**	−0.14^*	0.02	−0.24^**	0.35^**	0.16^*
7. Behavior	2.43	1.49							–	−0.13	0.00	−0.28^**	0.42^**	0.06
8. Age	21.82	5.56								–	−0.18^**	0.40^**	−0.14^*	−0.12
9. Gender^a	–	–									–	0.11	0.10	0.07
10. Rel-length^a	–	–										–	−0.14^*	−0.08
11. FB login/day^a	–	–											–	0.17^**
12. Time/FB login^a	–	–												–

Note: Mean scores in the present study are based on 7-point scales (1–7), except for self-esteem (1–4) and partner trust (1–5). Figures in parentheses on the diagonal are alpha coefficients.

Cronbach's alpha not computed for PBC, behavior, or age; single-item measures

Mean, SD, and Cronbach's alpha not computed; dichotomous or categorical measures.

p<0.05. ^**p<0.01.

PBC, perceived behavioral control; Rel-length, Relationship length; FB login/day, Facebook logins per day; Time/FB login, Time spent per login.

The sample's demographic characteristics and self-reported behavior are shown in Table 2. Given the relatively low number of participants who completed the follow-up questionnaire, multivariate analysis of variance analyses (MANOVAs) were conducted to identify whether differences existed between those who did and did not complete both questionnaires. MANOVA results indicated that there were no significant differences on any of the demographic and TPB variables (standard and additional) for participants who completed the first questionnaire only versus those who completed both.

Table 2.

Demographic Characteristics as Percentages of the Total Sample (n=244)

Characteristic	Percent (n)
Age
18–22	75.5 (184)
23–27	13.9 (34)
28–32	3.6 (9)
33–37	2.4 (6)
38–42	2.8 (7)
43–47	1.8 (4)
Gender
Male	21.7 (53)
Female	78.3 (191)
Relationship length
<1 month	9 (22)
Several months	13.5 (33)
6–12 months	22.7 (53)
1–2 years	17.6 (43)
2–5 years	27.9 (68)
>5 years	10.2 (25)
Facebook logins per day
Not every day	12.3 (30)
1–2 times	29.1 (71)
2–3 times	24.6 (60)
>5 times	16.8 (41)
>10 times	6.6 (16)
Facebook stays open on my computer	10.7 (26)
Time spent per login
5–10 minutes	29.1 (71)
10–20 minutes	40.2 (98)
Approximately ½ hour	20.5 (50)
>½ hour	5.7 (14)
>1 hour	4.5 (11)
Level of partner-monitoring in previous week (at follow-up)
Never	17.6 (43)
1–2 times	26.2 (64)
>3 times	12.7 (31)
>5 times	2.9 (7)
Daily	2.5 (6)
>once daily	2 (5)
With every login	2.5 (6)

Regression analysis predicting behavioral intentions

A hierarchical multiple regression was conducted to predict intention to engage in frequent Facebook partner-monitoring (Table 2). The step 1 demographic variables of age, gender, relationship length, daily Facebook logins, and time spent per login significantly accounted for 17 percent of the variance in intention, F(5, 238)=9.92, p<0.001. At step 2, the TPB variables, attitude, subjective norm, and PBC, significantly increased the proportion of variance by a further 49 percent, F(3, 235)=111.86, p<0.001. At step 3, self-esteem and partner trust significantly accounted for an additional 2 percent of the variance, F(2, 233)=7.94, p<0.001. The final model accounted for 68 percent of the variance and, of the significant predictors, subjective norm had the largest beta weight, followed by attitude, partner trust, and daily Facebook logins. Therefore, in partial support of Hypothesis 1, attitude and subjective norm, but not PBC, significantly predicted intentions to engage in frequent Facebook partner-monitoring. Additionally, partner trust emerged as a significant predictor of intentions (Hypothesis 3), as did the demographic variable of daily Facebook logins (Hypothesis 4).

Regression analysis predicting behavior

A hierarchical multiple regression was conducted to predict frequent Facebook partner-monitoring (Table 3). The step 1 demographic variables of age, gender, relationship length, daily Facebook logins, and time spent per login significantly accounted for 24 percent of the variance in behavior, F(5, 156)=9.78, p<0.001. At step 2, the TPB variables, intention and PBC, significantly accounted for a further 23 percent of the variance, F(2, 154)=33.40, p<0.001. At step 3, attitude and subjective norm did not significantly improve the prediction of behavior, F(2, 152)=0.38, p=0.69, nor did self-esteem and partner trust at step 4, F(2, 150)=0.78, p=0.46. The final model accounted for 48 percent of the variance and, of the significant predictors, intention had the largest beta weight, followed by daily Facebook logins, and relationship length. Therefore, in partial support of Hypothesis 2, intention, but not PBC, significantly predicted frequent Facebook partner-monitoring. Also, the demographic variables of daily Facebook logins and relationship length were significant behavioral predictors (Hypothesis 4) (Table 4).

Table 3.

Hierarchical Multiple Regression Analysis Including Demographics, Self-Esteem, and Partner Trust in Predicting Intentions to Engage in Frequent Facebook Partner-Monitoring

Variable	B	β	R²	ΔR²
Step 1
Age	0.00	0.00	0.17^***	0.17^***
Gender	−0.05	−0.01
Relationship length	0.00	0.00
FB logins per day	0.10	0.08^*
Time per FB session	0.07	0.04
Step 2
Attitude	0.50	0.33^***	0.66^***	0.49^***
Subjective norm	0.58	0.46^***
PBC	0.01	0.01
Step 3
Self-esteem	−0.01	−0.00	0.68^***	0.02^***
Partner trust	−0.43	−0.16^**

Note: Weights provided are those revealed in the final step of the analysis.

p<0.05; ^**p<0.01; ^***p<0.001.

FB, Facebook.

Table 4.

Hierarchical Multiple Regression Analysis Including Demographics, Self-Esteem, and Partner-Trust in Predicting Frequent Facebook Partner-Monitoring

Variable	B	β	R²	ΔR²
Step 1
Age	0.01	0.03	0.24^***	0.24^***
Gender	−0.03	−0.01
Relationship length	−0.18	−0.18^*
FB logins per day	0.22	0.21^**
Time per FB session	−0.07	−0.05
Step 2
Intention	0.49	0.62^***	0.47^***	0.23^***
PBC	0.03	0.03
Step 3
Attitude	−0.09	−0.07	0.47	0.00
Subjective norm	−0.03	−0.03
Step 4
Self-esteem	0.17	0.06	0.48	0.01
Partner trust	0.09	0.04

Note: Weights provided are those revealed in the final step of the analysis.

p<0.05; ^**p<0.01; ^***p<0.001.

Discussion

The present study examined the application of an extended TPB to measure frequent Facebook partner-monitoring. Providing partial support for Hypothesis 1, attitude and subjective norm significantly predicted intention to engage in frequent Facebook partner-monitoring. Therefore, individuals with more favorable attitudes towards frequent Facebook partner-monitoring and who perceived greater social pressure to do so were more likely to intend to engage in this behavior. In partial support of Hypothesis 2, intentions significantly predicted frequent Facebook partner-monitoring behavior at followup. Despite expectations, PBC did not significantly predict intentions or behavior; however, these findings support the argument that the effect of PBC declines as an individual's volitional control increases.⁷ Similarly, previous studies have found that PBC did not emerge as a predictor of SNS intentions¹² or behavior¹³; therefore, it may be that individuals perceive they have high volitional control over varying SNS behaviors. Specifically, current findings suggest that individuals can use Facebook to monitor their partner's activities at will, perhaps due to the ease of accessing information about one's partner throughout the network.

For Hypothesis 3, partner trust emerged as a significant predictor of intentions, suggesting that the less an individual trusts their partner, the greater their intention to engage in frequent Facebook partner-monitoring. Self-esteem, however, was not a significant predictor of intentions. These findings are consistent with Muise et al.,⁶ who demonstrated support for the role of trust, but not self-esteem, in couples' jealousy-related behaviors on Facebook. Arguably, the influence of an individual's self-esteem within a relationship may be better captured by more narrowly defined constructs reflecting relationship confidence, rather than global measures like the Rosenberg Self-Esteem Scale.¹⁵

For Hypothesis 4, age, gender, and time spent per login were not significant predictors; however, daily Facebook logins predicted both intention (although only a fairly weak predictive ability) and behavior and, unexpectedly, relationship length directly affected behavior. The findings regarding daily Facebook logins suggest that the more often an individual visits Facebook, the greater their intention to engage in, and subsequent engagement in, frequent Facebook partner-monitoring. This finding is consistent with previous research revealing an association between the desire to use Facebook for surveillance purposes and the frequency of visits to the site.²³ However, such an effect may be bi-directional whereby daily login is a precursor to monitoring but also the intent to monitor prompts the visits made to Facebook. Further research is needed to better understand the potential bi-directional process between Facebook logins and partner-monitoring behavior. Finally, the finding that relationship length directly affected behavior implies that the shorter the duration of, or the less developed, an individual's relationship, the more likely people are to spontaneously monitor their partner.

Interestingly, trust was positively associated (correlated) with relationship length and negatively related to Facebook logins. Given these findings, it may be that trust increases over the duration of a relationship, affecting frequency of Facebook logins and partner-monitoring behavior. Future research may unpack further the processes influencing these relationships.

Although it is unclear the extent to which Facebook partner-monitoring is problematic, it is possible that frequent engagement in this behavior could lead to excessive Facebook use and relationships difficulties. Interventions that aim to prevent or reduce problematic partner-monitoring could emphasize that important others (e.g., Facebook friends and partners) would disapprove of frequent Facebook partner-monitoring (subjective norm), reinforce the costs (e.g., discovering unwarranted, undesirable information about a partner) associated with frequent Facebook partner-monitoring (attitudes), and incorporate trust-building strategies between partners.

To the authors' knowledge, this study is the first to investigate explicitly the concept, and underlying determinants, of Facebook partner-monitoring from a sound theoretical basis. This study also adds to the limited body of research applying the TPB to SNS settings in general,^12,13 and is the first to test the validity of an extended TPB in the context of Facebook monitoring specifically. Results of the current study also provide new support for the inclusion of partner trust as a significant predictor in the TPB in the context of examining close relationships. Further strengths of the study include its prospective design and the sampling of individuals most likely to use Facebook. A primary limitation of the study, however, concerns the absence of a clear definition of this new behavior. Given the numerous ways in which Facebook might be used to monitor a partner's activities, participants were asked to consider examples beyond those provided; therefore, current findings account for individuals' varying interpretations of what partner-monitoring denotes. Further limitations include the predominantly female student sample and the lower response rate to the follow-up questionnaire. The use of only one item to measure PBC (due to low scale reliability) is also a limitation; it may be beneficial to include a more comprehensive assessment of an individual's level of perceived control over performing monitoring behaviors. Future research is needed to obtain a clearer definition of Facebook partner-monitoring, perhaps by employing a qualitative approach, and to investigate the potentially negative impact that frequent Facebook partner-monitoring could have on the development and maintenance of romantic relationships.

Overall, this study provides initial support for the utility of the TPB in predicting frequent Facebook partner-monitoring in that attitude and subjective norm predicted intention, and intention predicted behavior. The study also demonstrated the influence of partner trust, the frequency of daily Facebook visits, and the length of an individual's relationship, on Facebook partner-monitoring. This preliminary investigation provides insight into what is becoming an increasingly popular aspect of Facebook use for relational partners, prompting future research to examine the impact that Facebook partner-monitoring might have on people's intimate relationships.

Footnotes

Disclosure Statement

No competing financial interests exist.

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