Unveiling the Nexus Between Digital Monitoring and Experiences of Intimate Partner Violence in Romantic Relationships

Abstract

Using survey data from a sample of 378 women who live in the United States and self-identify as either Black or Latinx, this study explores predictors of women’s digital monitoring practices in intimate relationships in the context of intimate partner violence (IPV). We use literature about surveillance, monitoring, and IPV to frame our study. Our results show three significant instances that influence the odds of monitoring a romantic partner: (1) past experiences with digital abuse, (2) past experiences with offline psychological abuse, and (3) age, with younger women having increased odds of engaging in digital monitoring compared to older women. Although relationship satisfaction was negatively associated with digital monitoring, it was not a predictor variable. This suggests that casual surveillance behaviors are highly ambiguous and not necessarily indicative of a poor relationship. In fact, for women with past abuse experiences, digital monitoring may function as a coping mechanism that brings personal reassurance.

Keywords

social media electronic surveillance digital monitoring intimate partner violence romantic relationships

This study examines the predictors of digital monitoring in the context of intimate partner violence (IPV), looking at what demographic factors and what types of IPV experiences increase the odds of women engaging in digital monitoring in their romantic relationships. By digital monitoring, we refer to a range of surveillance activities enacted through technology with the goal of gaining awareness of a partner’s offline and/or online behaviors (Tokunaga, 2011). Examples of digital monitoring include checking a partner’s social media accounts, reviewing their browsing history, and looking through messages on their phone (Marshall et al., 2013; Van Ouytsel et al., 2019). Research on technology and social and personal relationships suggests that digital monitoring is becoming increasingly popular (Hermida & Hernández-Santaolalla, 2020; Hernández-Santaolalla & Hermida, 2020; Hertlein & van Dyck, 2020; Ramirez & Lane, 2019; Tokunaga, 2016), with some studies estimating that about one-third of U.S. adults have looked through their partner’s phone without that person’s knowledge (Kaspersky, 2021; Vogels & Anderson, 2020).

Digital monitoring is typically understood as a soft or casual surveillance practice (Lyon, 2022; Tokunaga, 2016) and is not considered abusive to the same extent as online sexual harassment (Schokkenbroek et al., 2023), coercive control (Harris & Woodlock, 2021), or cyber dating abuse (Caridade et al., 2019; Marganski & Melander, 2018). While a growing body of scholarship has investigated factors contributing to digital monitoring behaviors (Fox & Moreland, 2015; Fox & Warber, 2014; Tokunaga, 2016), the role of IPV experiences in one’s relationship history remains underexplored in the literature. Similarly, studies on cyber dating abuse and coercive control have examined the role of technology in perpetuating abuse in romantic relationships (Dragiewicz et al., 2019; Woodlock et al., 2020) and women’s strategies for responding to and managing technological risk in these contexts (Dragiewicz et al., 2021; Freed et al., 2018), but less is known about how these experiences may inform survivors’ own digital surveillance practices toward their partners, particularly among women of color. Studying digital monitoring in the context of IPV is important because for survivors of IPV, technology can be a tool to resist abuse (Rogers et al., 2023), increase their digital safety, and cope in the aftermath of violence (Douglas et al., 2019; Havard & Lefevre, 2020). We believe the link between digital monitoring and IPV warrants further investigation, and our study intervenes at this junction by examining whether Black and Latinx women’s past experiences of abuse (physical, psychological, or digital) shape their digital monitoring practices in romantic relationships. We speculate that women who have experienced various forms of IPV may turn to digital monitoring as a form of coping or an unhealthy relational maintenance strategy.

We focus on the digital monitoring practices of women, and specifically Black and Latinx women, for several reasons. First, Black and Latinx women are among the highest social media users (Auxier & Anderson, 2021), yet women of color are often overlooked in scholarship on communication and technology. Next, in the context of electronic surveillance, research indicates that women experience more jealousy and relationship stress because of social media than men and may therefore be more likely than men to look through their partner’s phone or engage in digital monitoring behaviors (Arikewuyo et al., 2021). Here, studies show that Hispanic women are more likely than White and Black women to engage in online snooping (Vogels & Anderson, 2020). Finally, beyond informing digital praxis, issues of race and sex also matter because of their relevance for IPV victimization. Studies show that Black and Latinx women are high-risk populations for IPV (Littleton & DiLillo, 2021; Mattson & Rodriguez, 1999). Indeed, while one in four women in the United States are victims of IPV, 45% of Black women (Bent-Goodley et al., 2023) and 55% of Latinas (Murdaugh et al., 2004) report experiencing IPV. Altogether, these perspectives make women of color a relevant study group to examine the interplay between digital monitoring and IPV in intimate relationships.

Literature review

Surveillance, monitoring, and intimate relationships

The concept of surveillance refers to practices of “watching over,” whether in-person or through electronic means (Lyon, 2022). Because those doing the “watching over” typically exert some form of power and control over the watched, surveillance is tied to power imbalances, invasion of privacy, loss of autonomy, and even authoritarianism (Lyon, 2007). Surveillance has important social and psychological impacts. Manokha (2018) notes that awareness of modern surveillance technologies and the presence of large audiences on social media can lead to a chilling effect whereby people engage in self-restraint or self-censorship in their online sharing practices. This is especially true when people fear surveillance by government authorities. Here, self-censorship can negatively affect things such as social mobilization, freedom of expression, labor rights, and other individual freedoms (Manokha, 2018, p. 232). Knowing that one is being watched can also lead to anxiety, stress, and other negative psychological harms (Bhatia, 2021). In the context of corporate surveillance, Bright et al. (2021) found that privacy concerns associated with online surveillance led to erosion of trust, increased privacy behaviors, and generally negatively influenced people’s social media engagement.

Digital monitoring is closely related to surveillance in that both practices involve observation, but while the practice of surveillance stresses issues of “power, politics, and resistance,” monitoring is a softer form of observation that involves periodic data collection or regularly checking in on someone (Lyon, 2022, p. 5). In the workplace, for example, monitoring may refer to checking in on employees to ensure their work is satisfactory (Lyon, 2022). In the context of social and intimate relationships, the practice of monitoring is associated with horizontal surveillance or peer-to-peer scrutiny (Hermida & Hernández-Santaolalla, 2020; Marwick, 2012) with the goal of seeking information to reduce uncertainty. When individuals do not trust their partners or have a history of betrayal in their romantic relationships, they may turn to surveillance strategies as a coping mechanism (Fox & Warber, 2014; Tokunaga, 2011). Existing scholarship on digital monitoring finds this is a highly ambiguous practice, with both positive and negative connotations. At best, digital monitoring is a way to casually check in on friends and family (Marwick, 2012; Tokunaga, 2011); at worst, the practice can result in privacy violations and digitally abusive behaviors (Hermida & Hernández-Santaolalla, 2020).

In the context of intimate relationships, monitoring is typically not described in positive terms (Dindia, 2003; Hernández-Santaolalla & Hermida, 2020); in fact, Tokunaga (2016) argues that the practice should be seen as a sign of negative relationship interactions and an indication of decreasing relationship satisfaction. Similarly to the social and psychological impacts of surveillance in general, digital monitoring in romantic relationships can have negative psychological consequences for both parties, including emotional distress and dissatisfaction, all of which ultimately undermine relationship satisfaction (Elphinston & Noller, 2011; Lukacs & Quan-Haase, 2015). When individuals engage in intimate partner surveillance, it is often an attempt to protect themselves from perceived threats or to confirm suspicions of romantic infidelity or betrayal (Fox & Warber, 2014; Tokunaga, 2016). Digital monitoring is therefore associated with a desire to maintain control and security (Fox & Moreland, 2015; Guerrero et al., 2005). By turning to digital monitoring, individuals are trying to alleviate their own insecurities and relational uncertainties. Given the role of digital monitoring in coping with relational uncertainties, we propose to examine how this practice may be connected to women’s IPV experiences. Specifically, we explore whether different IPV experiences increase the odds of engaging in digital monitoring.

Digital monitoring: benefits and coping strategies

Although most studies on digital monitoring present the practice as unhealthy, some studies have described digital monitoring in positive terms. For example, research shows that engaging in online surveillance behaviors can serve as a way to demonstrate one’s interest and commitment to a romantic relationship (Ruggieri et al., 2021). Among teenagers, sharing passwords and social media accounts is seen as a form of trust and an acceptable relational maintenance practice (Van Ouytsel et al., 2016). Digital monitoring in the form of location-sharing through applications like Life360 or Find My iPhone has been described as a positive form of surveillance because it offers a sense of safety and reassurance and can be helpful in coordinating household tasks like running errands (Griggio et al., 2019; Mavoa et al., 2023). Companies even market their applications directly to couples, with the Life360 website stating that, “with Life360, couples can rest assured that their partner is safe and protected,” highlighting the importance of digital togetherness via alerts and seamless location updates (Life360, 2024). In the context of IPV, scholarship shows that victims of IPV can also use technology to resist abuse (Rogers et al., 2023). Types of actions taken by survivors include blocking contacts on social media or mobile phones (Douglas et al., 2019; Havard & Lefevre, 2020), making changes to devices, cloud storage providers, or security settings (Douglas et al., 2019; Havard & Lefevre, 2020), monitoring children’s phones for new apps or devices after contact visits, or disconnecting from social media altogether (Douglas et al., 2019).

These actions align with other coping strategies IPV survivors employ. Coping strategies include a wide range of thoughts, emotions, and behaviors used to manage difficult situations (Waldrop & Resick, 2004). IPV survivors, for example, may turn to cognitive coping strategies like positive self-talk (Waldrop & Resick, 2004) or cognitive restructuring (Griffing et al., 2006) to seek reassurance in the face of long-standing insecurities and fears from past instances of IPV. Although not currently addressed in the literature, given the power of technology to work as a tool to resist abuse and the role of cognitive and emotional coping mechanisms to process IPV, we stipulate that digitally monitoring a partner in response to past or current abuse experiences may function as a coping strategy for survivors. In the following sections, we review types of IPV and demographic facts that could shape digital monitoring practices.

The continuum of violence

Various terms, including digital coercive control, cyber dating violence, and cyber dating abuse, have been used to account for the myriad ways new technologies enable abusive partners to harass, stalk, and control their victims with greater ease, using new methods and channels (Dodge, 2023; Dragiewicz et al., 2019; Woodlock et al., 2020). Examples of digitally intrusive or harmful behaviors include requiring a partner to share passwords, monitoring social media and email activity, clandestine audio and visual recordings, accessing accounts without permission, and geo-location stalking, among others (Dragiewicz et al., 2019; Freed et al., 2018; Woodlock, 2017). Digital abuse can also be sexual in nature, such as pressuring someone to send intimate photos or videos and engaging in the nonconsensual sharing of intimate or sexual images (Gjika, 2023; Henry et al., 2019).

When enacted in the context of an intimate relationship, digitally abusive behavior among adults is theorized as a subset of IPV, which includes physical, sexual, financial, and psychological abuse (World Health Organization, 2024). When discussing IPV, it is important to note that due to the interconnectedness of digital and physical experiences, victims of IPV tend to be subjected to more than one form of abuse (Marganski & Melander, 2018; Rogers et al., 2023; Schokkenbroek et al., 2023) in what is referred to as a continuum of violence (Dunn, 2021). Indeed, literature demonstrates that technology-facilitated abuse often happens alongside and simultaneously with other types of abuse in intimate relationships, including psychological, physical, and sexual aggression, and that experiencing digital abuse significantly increases the odds of in-person victimization (Marganski & Melander, 2018; Rogers et al., 2023). To fully understand how IPV may tie into monitoring, it is therefore crucial to consider the range of violent incidents victims experience both online and in-person.

Predictors of digital monitoring: demographic factors

Studies on digital monitoring in romantic relationships have noted important differences across three demographic points: sex, age, and race. First, research shows that because women experience more jealousy and uncertainty in romantic relationships than men, they are more likely than men to engage in digital surveillance practices, especially as a coping mechanism in the face of relational uncertainty (Arikewuyo et al., 2021; Smoker & March, 2017). Sex is thus a significant predictor of digital monitoring in intimate relationships.

Second, where age is concerned, studies have examined the digital monitoring practices of youth because this age group has grown up in technology-rich environments and being fully immersed in social media may make them more prone to engage in electronic surveillance (Hertlein & van Dyck, 2020; Ruggieri et al., 2021). Studies found that monitoring and aggression practices are common in adolescent and young adult dating relationships among both sexes (Reed, Tolman, & Ward, 2016; Reed, Tolman, Ward, & Safyer, 2016; Ruggieri et al., 2021). Research in this area often focuses on more intrusive forms of violence, such as cyber dating abuse or online sexual harassment (Gjika, 2023; Schokkenbroek et al., 2023), yet findings from these studies help situate digital monitoring as a practice of control amid a larger trend of using technology as a form of power and violence in romantic relationships. For example, in their extensive review of scholarship on technology-enabled threats and abuse in young people’s romantic relationships, Caridade et al. (2019) found that while perpetration rates vary greatly, studies on cyber psychological abuse consistently report high perpetration rates ranging from 34% to 64% among youth.

At the intersection of age and sex, research shows that adolescent and college-aged women express strong support for digital monitoring behaviors like password sharing, reading a partner’s private social media conversations, or even logging into a partner’s account to view their online activity (Montero-Fernández et al., 2023). This suggests that young women are more likely than other groups to engage in digital monitoring and find the practice acceptable. Finally, in terms of racial and ethnic differences, various studies have noted that digital monitoring behaviors are particularly prevalent among younger women of color, as they are often among the most active social media users (Vogels & Anderson, 2020).

Current study

Based on the literature outlined above, we developed a research question and four hypotheses. First, to explore broadly how past experiences with abuse (digital and/or other) shape women’s digital surveillance practices, we propose the following research question:

RQ1: What factors influence the odds of women monitoring their romantic partners?

Next, based on theories about violence against women and recent scholarship on IPV, we developed the following four hypotheses in relation to digital monitoring:

H1: Past experiences with digital violence will positively influence the odds of engaging in digital monitoring.

H2: Past experiences with offline violence (a) physical and (b) psychological will positively influence the odds of engaging digital monitoring.

H3: Relationship satisfaction will negatively influence the odds of engaging in digital monitoring.

H4: Age will negatively influence the odds of engaging in digital monitoring.

Methods

Data collection and procedure

To examine the factors that shape Black and Latinx women’s digital monitoring practices in intimate relationships, we conducted a survey through Prolific, an online crowdsourcing platform that has a pool of vetted and diverse individuals who are readily available to participate in research studies (www.prolific.co). Prolific is known for its partnerships with academics, and the studies have shown that research conducted through Prolific produces higher-quality data than surveys distributed on competing platforms such as CloudResearch or MTurk (Peer et al., 2022).

Participants were asked a set of questions about their social media usage and experiences with IPV in both online and offline contexts. They were also asked whether they had ever monitored a romantic partner using a smartphone or social media application. Finally, the questionnaire included standard demographic questions (e.g., age, sex, race, political affiliation). Participation in the survey was anonymous. Survey completion time ranged from 4 to 48 min (M = 14). In accordance with Prolific’s ethical rewards principle, which recommends paying participants $12.00 per hour, we used the average completion time as our pricing guideline and compensated participants $3.80 for taking the survey (www.prolific.co). The study was approved by an Institutional Review Board, included an informed consent form, and followed guidelines for the ethical treatment of research participants.

Participants

We recruited 415 women who live in the United States and self-identify as either Black or Latinx. After removing participants who timed out of the survey and incomplete survey answers, we were left with a final sample of 378 women. Of those, 200 identified as Black or African American, and 178 identified as Latinx or Hispanic. Participants ranged in age from 18 to 75 (M = 33.45, SD = 11.63). In terms of political partisanship, 265 participants identified as Democrats (70%), 80 as Independents (21%), and 33 as Republicans (9%). Our sample was diverse in other ways too. For instance, our study included participants from a range of sexual orientations: 268 (71%) participants identified as heterosexual, 72 (19%) as bisexual, 18 (5%) as lesbian, 15 (4%) as pansexual, and five (1%) as asexual. Participants also came from different communities with 29 (8%) identifying as living in a rural area, 78 (20%) in a small city or town, 170 (44%) in a suburb near a large city, and 110 (28%) in a large city.

Data analysis

We conducted a logistic regression in Stata 18.0 with digital monitoring as our outcome variable and the following seven variables as the predictor variables: digital abuse, psychological harm, physical harm, relationship satisfaction, age, political affiliation, and community.

Measurements

Table 1 shows an overview of all scales, including scale statistics. Table 2 shows a correlation matrix of the study variables.

Table 1.

Scales and Scale Statistics.

Variable	Number of items	Example item	Reference	α	M	SD	Min	Max
Digital Abuse Scale	12	Told you who you can or can’t be friends with on social media.	Love is Respect (2023)National DomesticViolence Hotline (2023)	0.90	4.47	6.78	0	35
		Tracked your activities on social media.
		Stolen or insisted on being given your account passwords.
		Insulted or humiliated you in social media posts, including posting unflattering photos or videos.
		Posted or sent photos of another person to make you jealous.
		Purposefully ignored your social media communications.
		Intentionally made you feel guilty or bad about something through social media statements.
		Sent excessive messages to monitor where you are and with whom.
		Sent you unwanted explicit photos or videos through social media.
		Created a fake social media profile in your name and image.
		Blocked you or unfollowed you to taunt you or make you feel bad.
		Pressured you to send explicit photos or videos.
Privacy Protection Behaviors Scale	5	Use two-or three-factor authentication on your accounts.	Sindermann et al. (2021).	0.73	11.87	4.32	0	20
		Remove location services or geotags from social media apps.
		Review someone’s social media profile before adding them.
		Adjust ad preferences to minimize targeted advertisements.
		Stay up to date on data breaches and data leaks.
Relationship Satisfaction Scale	8	My partner meets my needs.	Hendrick (1988)	0.95	20.91	7.72	0	32
		I am generally satisfied with my relationship.
		The relationship has met my original expectations.
		I feel that things are going well with my partner.
		How often do you wish you hadn’t gotten into this relationship?How often do you feel that things are not going well in your relationship?
		How often do you experience problems in your relationship?How often do you have second thoughts about your relationship?

Table 2.

Correlation Matrix (N = 378).

	1.	2.	3.	4.	5.	6.	7.	8.	9.
1. Monitoring	-
2. Digital Abuse	.26***	-
3. Physical Harm	.20***	.35***	-
4. Psychological Harm	.29***	.40***	.50***	-
5. Digital Privacy	–.13**	.06	–.01	.05	-
6. Relationship Satisfaction	–.13*	–.29***	–.17***	–.26***	–.00	-
7. Age	–.17**	–.09	.07	.02	–.03	–.07	-
8. Political Affiliation	.02	–.02	–.05	–.06	–.06	.00	–.03	-
9. Community	.09	.03	–.02	.04	.03	.07	–.04	.02	-

p < .05; **p < .01; ***p < .001.

Digital monitoring

Digital monitoring was measured using a binary variable, coded as 0 for women who have never monitored a romantic partner and as 1 for women who have done so. The survey question was broad and asked women if they had ever used social media or smartphone applications to monitor a romantic partner’s activities or behaviors. This phrasing allowed us to capture both past and ongoing digital monitoring. A total of 191 participants, or about 49% of our sample, had monitored their romantic partner at one point in time (M = .49, SD = .50).

Digital abuse scale

Digital abuse was measured by a 12-item scale (based on data from the National Domestic Violence Hotline (2023) and Love Is Respect (2023)) which asked respondents: “How often has a romantic partner done the following?” Participants were then asked to indicate how often they had experienced certain forms of digital violence by a romantic partner on a 5-point scale which ranged from 0 = never to 4 = 10 or more times (e.g., “Told you who you can or can’t be friends with on social media”). In selecting items to include in the scale, theoretical conceptualizations of digital violence guided our operational definition. This was a crucial part of ensuring content validity and making sure that the scale captured the meaning of digital violence. Participants’ scores were summed to indicate their digital abuse score, and higher scores indicate more experiences with digital abuse; we also report the observed range within the sample (Min = 0, Max = 35, M = 4.47, SD = 6.78). Internal consistency for the scale was high, with a Cronbach’s alpha of 0.90. Overall, 233 participants or about 60% of our sample had experienced at least one instance of digital abuse from a romantic partner.

Relationship satisfaction scale

Using an 8-item variation of Hendrick’s (1988) relationship satisfaction scale, relationship satisfaction was assessed by asking participants to rate on a 5-point Likert-type scale how happy they were in their current or most recent relationship; we also report the observed range within the sample (Min = 0, Max = 32, M = 20.91, SD = 7.72). Some items were measured on a scale which ranged from strongly disagree = 0 to strongly agree = 4 (e.g., I feel that things are going well with my partner); while others were formulated in a question format that ranged from 0 = never to 4 = all the time. Where appropriate, items were reverse coded and then all five items were summed so that higher scores indicated a higher relationship satisfaction. Internal consistency was high with a Cronbach’s alpha of 0.95.

Psychological harm

Psychological harm was measured using a binary variable, coded as 0 for women who have never experienced psychological harm from their partner and as 1 for women who have experienced psychological harm from a romantic partner. The question asked respondents if their romantic partner had ever “yelled, insulted, or threatened” them. In our study, 184 participants, or about 48% of the sample, had experienced psychological harm (M = .48, SD = .50).

Physical harm

Physical harm was measured using a binary variable, coded as 0 for women who have never experienced physical harm at the hands of a romantic partner and as 1 for women who have. The question asked respondents if they had ever been “pushed, slapped, or hit” by a romantic partner. In our study, 87 participants or 22.48% of the sample had experienced physical harm from a romantic partner (M = .22, SD = .42).

Participant age

Respondents were asked to type in their age using a numerical value. Only women aged 18 and above were allowed to participate in the study. Age ranged from 18 to 75 (M = 33.37, SD = 11.65)

Political affiliation

Political affiliation was measured using a continuous scale where respondents indicated their political leaning from strong Republican to strong Democrat, with higher scores indicating participants self-identified as more democratic leaning (Min = 0, Max = 6, M = 4.34, SD = 1.45). As a whole, our sample leaned democratic.

Community

Community was measured using a continuous variable ranging from rural area (0) to large city (3) (M = 1.93, SD = 0.88). A total of 280 participants, or about 72% of our sample, lived in either a large city or a suburb near a large city.

Findings

Our research question asked what factors influence the odds of women engaging in digital monitoring of their romantic partners. The final logistic regression model for this study included seven predictors and was statistically significant: χ² (7, N = 378) = 57.68, p < .001 and explained 11.04% of the variance (Nagelkerke R² ). Results indicate three significant instances that influence the odds of engaging in digital monitoring: (1) past experiences with digital abuse (p < .05), (2) past experiences with offline psychological abuse (p < .01), and (3) age (p < .01).

Specifically, we found that the odds of engaging in digital monitoring increased by 5% for each additional increase in the digital abuse scale, meaning that women who experienced multiple instances of digital abuse from a romantic partner had higher odds of turning to digital monitoring than women with no or little digital abuse experience. Significantly, we also found that the odds of engaging in digital monitoring increased by 87% for women who had experienced psychological abuse compared to women who had no such experience. Finally, we found that age decreased the odds of engaging in digital monitoring; for each additional year of age, the odds of engaging in digital monitoring decreased by 3%.

We developed several hypotheses around past experiences with IPV and digital monitoring. In regard to H1, we found that past experiences with digital violence were a significant predictor variable in our model (p < .05), and that the odds of engaging in digital monitoring increased by 5% for each additional increase in the digital abuse scale, thereby proving support for H1.

H2 stipulated that past experiences with offline domestic violence (physical and psychological) will be positively associated with digital monitoring. Although both past experiences with physical abuse and past experiences with offline psychological abuse were positively associated with digital monitoring, only psychological harm was a significant predictor in our model (p < .01). For women who had experienced psychological harm, the odds of engaging in digital monitoring increased by 87% compared to women with no such abuse experience. As such, we found partial support for H2.

Next, H3 proposed that relationship satisfaction will negatively influence the odds of engaging digital monitoring. Results from the logistic regression model show a negative, but not significant, relationship between relationship satisfaction and digital monitoring. Therefore, H3 was not supported.

H4 stipulated that age would negatively influence the odds of engaging in digital monitoring, meaning that younger women would have higher odds than older women of engaging in digital monitoring. Age was a significant predictor in our model (p < .01), and we found that for each additional year of age, the odds of monitoring decreased by 3%.

The remaining demographic variables, political affiliation, and community were not significant in our model. Findings from the logistic regression are presented in Table 3.

Table 3.

Regression Analysis for Digital Monitoring.

DV = Monitoring of a Romantic Partner (N = 378)
Predictors	Odds Ratio	B	p	Lower CI	Upper CI
Digital Abuse Scale	1.05	0.05	0.012 *	1.01	1.09
Physical Harm	1.22	0.17	0.591	0.64	2.30
Psychological Harm	2.54	0.94	0.001 ***	1.48	4.36
Digital Privacy Scale	0.92	–0.07	0.002 **	0.89	0.97
Relationship Satisfaction	0.98	–0.02	0.330	0.96	1.02
Age	0.97	–0.03	0.003 **	0.95	0.99
Political Affiliation	1.03	0.02	0.764	0.88	1.20
Community	1.23	0.20	0.115	0.95	1.58

p < .05; **p < .01; ***p < .001 indicates significance of Bold.

Discussion

This study examined the circumstances under which Black and Latinx women, a high-risk population for IPV (Littleton & DiLillo, 2021), experience increased odds of engaging in digital monitoring behaviors in their romantic relationships. Digital monitoring is a casual form of surveillance (Lyon, 2022; Tokunaga, 2011), and while still intrusive, it does not rise to the level of harm associated with digital stalking or online harassment (Arikewuyo et al., 2021; Kaspersky, 2021; Schokkenbroek et al., 2023; Vogels & Anderson, 2020). This distinction is crucial to the interpretation of our research findings. In line with past research on digital monitoring in social and personal contexts, we stipulate that women who engage in digital monitoring are not perpetrators of digital abuse, but individuals who turn to technology in response to relational uncertainties and fears (Fox & Moreland, 2015; Guerrero et al., 2005; Hermida & Hernández-Santaolalla, 2020; Hertlein & van Dyck, 2020; Ramirez & Lane, 2019; Tokunaga, 2016). Rather than functioning as a tool for coercion or violence, digital monitoring may thus be a coping or reassurance mechanism. That digital monitoring is a primarily a casual form of surveillance is supported by the fact that relationship satisfaction is not a predictor of digital monitoring. In other words, the digital monitoring practices employed by the women in our study were not harmful or severe enough to cause the type of damage that would lead participants to report poor levels of relationship satisfaction. We discuss the relevance and implications of our findings in greater detail below.

Monitoring in the IPV context

Our most prominent finding is that past experiences with digital abuse as well as past experiences with offline psychological abuse are significant predictors of digital monitoring in intimate relationships. We theorize that experiences with psychological abuse (both online and offline) may contribute to some women more proactively managing their relational uncertainties through technology and that digital monitoring is a type of mental or psychological coping strategy (Griffing et al., 2006; Waldrop & Resick, 2004).

As previous research indicates, the goal of digital surveillance is to reduce uncertainty and gain awareness of someone’s behaviors and actions (Tokunaga, 2011; Van Ouytsel et al., 2019). Digital monitoring, such as checking on a partner’s whereabouts or latest online actions, although often described as an unhealthy and negative practice (Fox & Moreland, 2015; Guerrero et al., 2005; Tokunaga, 2016), may in some instances help victims of IPV confirm insecurities in a current relationship or provide much-needed reassurance that helps them feel better about a new romantic relationship. IPV victims, who have experienced lying, denial, and gaslighting by perpetrators, may find themselves unable to trust in their own knowing abilities (March et al., 2025) as abuse often causes heightened levels of anxiety, stress, and uncertainty. Consequently, surveilling romantic partners online may be one strategy survivors use to manage or reduce uncertainty in their relationships. Digital monitoring can be a way to obtain some much-needed reassurance by checking their partner’s social media accounts, smartphones, or location for hard data.

Relatedly, electronic monitoring may also emerge as a form of safety work by survivors, where casual surveillance is an attempt at assessing or managing threats of violence posed by their abusers (Dragiewicz et al., 2021). Some studies on IPV victimization and the uses of technology to resist abuse also suggest survivors may be monitoring social media and mobile communications as a way to gather evidence against their abuser, which can help with custody, protection orders, leaving, and so on (Freed et al., 2018; Henry & Powell, 2016). In such a scenario, women with experiences of digital and emotional abuse may turn to digital monitoring as a way to regain control and strengthen their IPV case.

When contextualizing our findings, it should be noted that both digital abuse and psychological abuse are conceptually similar to each other in that they are designed to cause mental and emotional harm to victims (Harris & Woodlock, 2021). For instance, the psychological harm question in our survey asked women if their romantic partner had ever yelled, insulted, or threatened them, while the digital abuse scale asked women questions about their partner’s controlling online behaviors, such as telling them who they can or can’t be friends with on social media. Consequently, it is possible that both the digital abuse scale and the offline psychological abuse measure tapped into the same type of abuse and trauma experiences. Indeed, research shows that women who experience offline IPV also often experience online aggression and intimidation as part of a continuous cycle of violence (Dunn, 2021; Marganski & Melander, 2018; Woodlock et al., 2020). As such, one can conceptualize digital abuse as psychological or verbal abuse perpetrated through technology. These conceptual similarities may explain why both variables, collectively, predict digital monitoring in intimate relationships.

Surprisingly, past experiences with physical abuse were not a significant predictor in our model. Given the intertwined nature of most forms of IPV (Dunn, 2021; Marganski & Melander, 2018; Woodlock et al., 2020), we expected all types of IPV experiences to hang together and be significant predictors of digital monitoring. There are several possible explanations for why past experiences with physical abuse were not a predictor of digital monitoring. Women who have experienced extensive physical abuse from a romantic partner may be especially fearful of their abuser (Dragiewicz et al., 2021; Van Hightower et al., 2000). This may lead them to adopt social withdrawal or other avoidance-related coping mechanisms (Griffing et al., 2006) instead of digital monitoring. In addition, the power imbalance of a relationship that involves physical violence may cause women to be more vigilant about their online presence or even stay off the internet altogether in the hopes of avoiding further aggression from their partner (Frolo, 2021; Güçlü et al., 2017; Waldrop & Resick, 2004). If women are worried about the possible ramifications of getting caught engaging in digital monitoring, they may find it safer to avoid using technology to check in on their partner.

The fact that younger women are more likely than older women to engage in digital monitoring practices in their intimate relationships lends support to recent studies which show that about one-third of adults in partnered relationships have monitored their significant other without that individual’s consent (Kaspersky, 2021; Vogels & Anderson, 2020) and that this trend is particularly common among younger social media users (Caridade et al., 2019; Cava et al., 2020; Hertlein & van Dyck, 2020; Montero-Fernández et al., 2023; Ruggieri et al., 2021; Schokkenbroek et al., 2023). The presence of this result in our study on the experiences of Black and Latinx women also suggests that the rise of casual surveillance practices in romantic relationships is a trend across various ethnic and racial groups. That younger women have increased odds of engaging in digital monitoring indicates that this type of coping mechanism or relational uncertainty management strategy may be more popular among certain age cohorts. Since younger women have grown up in a technology-saturated world (Hertlein & van Dyck, 2020; Montero-Fernández et al., 2023), the act of monitoring a romantic partner’s online activities may seem like a helpful and intuitive cognitive coping strategy. In a time where casual surveillance behaviors are becoming increasingly common, digitally monitoring a romantic partner may be seen as a natural extension of other forms of social or peer-to-peer surveillance (Marwick, 2012; Paik et al., 2022).

Limitations and conclusion

Focusing on the experiences of Black and Latinx women, this study examined what factors shape digital monitoring practices in romantic relationships, unpacking the complex relationship between digital monitoring, IPV (online and offline), privacy protection behaviors, and relationship satisfaction. Overall, we found that women who scored higher on the digital abuse scale, women who experienced psychological harm in the past, women who scored lower on the privacy protection behaviors scale, and younger women had increased odds of engaging in digital monitoring practices in their intimate relationships. By stepping outside of the all-White samples often employed in academic research, we expanded the breadth and richness of current studies on the intersections of monitoring, digital privacy, and technology-facilitated abuse.

Although this study makes important contributions to scholarship on technology and intimate partner surveillance among women of color, it is not without limitations. Past research on technology-facilitated abuse in intimate relationships tells us that sex is an important distinguishing factor in relation to digital monitoring and digital abuse behaviors (Ellyson et al., 2021; Reed et al., 2017). By focusing exclusively on women, we were not able to draw conclusions across identify differences in the experiences of male and nonbinary individuals. Relatedly, by centering the experiences of adult Black and Latinx women, many of our participants shared similar demographic characteristics (e.g., political affiliation, education, community), which restricted our ability to draw additional comparative demographic insights from the data. Future studies on digital monitoring and its ties to IPV may want to sample an even more diverse spectrum of voices, including individuals from different gender identities, ethnicities, and socio-economic backgrounds, to provide a more comprehensive understanding of this phenomenon.

Another limitation of our study is our choice of measures. By utilizing only single measures for physical abuse and psychological violence, we were not able to discern nuances within these categories of IPV. In addition, since our questions about IPV and digital monitoring were phrased using “have you ever,” we cannot with certainty establish the temporal sequence of these behaviors. It is possible that for some participants, these behaviors happened in the past and that they were still ongoing for others. Future research should consider making these distinctions to better understand the relationship between different forms of IPV and digital monitoring and how these behaviors are causally linked.

Finally, future studies may want to further examine the ambiguous nature of digital monitoring as a response mechanism to relational uncertainties and past IPV experiences. Such research would be valuable in articulating the threshold between helpful and harmful monitoring behaviors in our increasingly technology-dependent society.

Footnotes

ORCID iDs

Caley Hewitt

Fanny A. Ramirez

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Author biographies

Caley Hewitt is a PhD student at the Manship School of Mass Communication at Louisiana State University. Her research examines the intersections of gender, technology, and politics.

Fanny A. Ramirez (PhD, Rutgers University) is an assistant professor at Louisiana State University, where she holds a joint appointment with the Manship School of Mass Communication and LSU’s interdisciplinary Center for Computation and Technology. Her research examines the role of information communication technologies in society with a focus on issues of privacy, discrimination, and race and gender inequality.

Anna Gjika (PhD, The CUNY Graduate Center) is an assistant professor of Sociology at the State University of New York at New Paltz. Her research explores the intersections of gender, violence, and technology and sociolegal responses to gender-based violence.

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