Introduction

Romantic partners often rely on technology to initiate and maintain their intimate relationship (Boyle & O’Sullivan, 2016; Papp et al., 2012; Pew Research Center, 2016), but using technology can open opportunities for intimate partner cyberstalking (IPC; Marcum et al., 2017; Smoker & March, 2017). Many young adults experience instability in romantic partnerships (Arnett, 2015) and engage in computer-mediated communication in their intimate relationships (Boyle & O’Sullivan, 2016), which could increase their risk for IPC. College-student studies have found estimates up to 36% for victimization and 67% for perpetration of various IPC behaviors (Lyndon et al., 2011; Shorey et al., 2015).

IPC is not well-understood. Definitions and measurement vary (Finn, 2004; Maple et al., 2012; Marcum et al., 2017; Reyns et al., 2012; Shorey et al., 2015; Smoker & March, 2017; United States Department of Justice, 2000), and the behaviors that are considered to be IPC are unclear because the technologies used to cyberstalk are debated (Bahm, 2003). IPC generally involves the use of the Internet and other information and communication technologies to repeatedly monitor, threaten, and/or harass a current, former, or potential romantic partner, causing them fear or concern for their safety (Bocij & McFarlane, 2002; Finn, 2004; Maple et al., 2012; Smoker & March, 2017; United States Department of Justice, 2000). Distress and alarm are also included as responses in some cyberstalking definitions (Maple et al., 2012; Worsley et al., 2017). Some college-student studies have only focused on Internet-based IPC behaviors (Acquadro Maran & Begotti, 2019; Marcum et al., 2017), and it is argued that stalking with technology beyond the Internet should not be termed “cyberstalking” (Bahm, 2003). According to Bahm (2003), the term “cyber” typically pertains to the Internet and may be expanded to include computer technology, but it does not encompass all forms of technology that may be used to stalk. Conversely, others have been more lenient with the term “cyber,” and when defining cyberstalking, they have considered a wide variety of electronics that are used to stalk, such as text messaging, cameras, and location devices (e.g., Shorey et al., 2015; Smoker & March, 2017). Studies among college students and social media users have included various technologies, such as phones, texting, and tracking applications, when assessing IPC behaviors (Shorey et al., 2015; Smoker & March, 2017), thus accepting a broader definition of IPC. Similarly in a small qualitative study, college students described multiple technologies, including the Internet and other electronics, that have been used to perpetrate psychological aggression and to harass a romantic partner (Melander, 2010). However, young adults’ understanding of the technology-facilitated behaviors involved in IPC remain unclear due to a lack of research investigating their perspectives of which behaviors should and should not be considered IPC.

Severity of Intimate Partner Cyberstalking

There is a lack of literature about IPC severity and its measurement. Among studies including community and college-based samples, severe forms of general cyberstalking and other unwanted pursuits have involved media platforms for verbal communication (e.g., video, phone; Barnes & Biros, 2007); monitoring and threatening acts using a cell phone, cameras, spyware, social media, email, and GPS (Dardis & Gidycz, 2017); and violation behaviors (e.g., done without consent; Cupach & Spitzberg, 2000). Severe pursuits and intrusions have occurred less frequently among college students than minor behaviors (Cupach & Spitzberg, 2000; Dardis & Gidycz, 2017), as they have been perceived as more threatening, violating, annoying, and upsetting (Cupach & Spitzberg, 2000). There is no consensus regarding the measurement of severity, but methods have included an assessment of the stalker’s actions and threats and an analysis of victim advocates’ case notes (Barnes & Biros, 2007); a factor analysis of pursuit behaviors that resulted in severe and minor factors (Dardis & Gidycz, 2017); the extent participants felt or would feel annoyed, upset, threatened, and their privacy violated by the behaviors (Cupach & Spitzberg, 2000); duration (Purcell et al., 2004); and experiencing multiple forms of stalking each at a high frequency (Mechanic et al., 2000). More research is necessary to clarify IPC severity and its measurement.

General Stalking Severity and Psychological and Social Health States

Given the dearth of literature about IPC severity, the associations between IPC severity and adverse health states are unclear. Among studies that combined both in-person and electronic stalking and included community-based samples of adults, victims of stalking for longer than two weeks have been more likely to relocate their residence, change their phone number, reduce social outings, and experience greater psychological morbidity compared to those who reported stalking for two weeks or less (Purcell et al., 2004). Battered women who were relentlessly stalked by an intimate partner have reported greater depression and post-traumatic stress compared to women who were infrequently stalked (Mechanic et al., 2000). Victims of severe IPC may experience similar adverse psychological and social health states.

The Present Study

It is important to understand young adults’ perceptions of and experiences with IPC to effectively address this problem among the population. We defined IPC as the use of the Internet and other information and communication technologies to repeatedly monitor, threaten, and/or harass a current or former romantic partner, causing them to feel afraid, threatened, harassed, and/or distressed (Bocij & McFarlane, 2002; Finn, 2004; Maple et al., 2012; Smoker & March, 2017; Worsley et al., 2017). We defined intimate partner according to the Centers for Disease Control and Prevention’s uniform definition:

An intimate partner is a person with whom one has a close personal relationship that may be characterized by the partners’ emotional connectedness, regular contact, ongoing physical contact and sexual behavior, identity as a couple, and familiarity and knowledge about each other’s lives. The relationship need not involve all of these dimensions. Intimate partner relationships include current or former: spouses (married spouses, common-law spouses, civil union spouses, domestic partners), boyfriends/girlfriends, dating partners, ongoing sexual partners. (Breiding et al., 2015, p. 11)

The study was conducted in two phases. In Phase 1, we examined young adults’ perceptions of which technology-facilitated behaviors they considered to be IPC and the severity of these behaviors. To our knowledge, there is no validated tool to assess IPC experiences in a hierarchy of increasing severity. Therefore, the severity perceptions from Phase 1 were used to operationalize severity experienced in the next phase. In Phase 2, we investigated the association between perceived severity of behaviors and victimization frequency among young adults. Also, we examined perceived severity of IPC victimization experienced and its association with depressive symptoms and social isolation. Associations between demographics and perceived severity of IPC experienced were explored. We hypothesized:

H1

As the perceived severity of IPC behaviors increases, the frequency of victimization decreases.

H2

When the perceived severity of IPC victimization experienced increases, young adults are more likely to report depressive symptoms and greater social isolation.

Methods

Sampling and Recruitment

Phase 1 included a convenience sample of 104 undergraduate and graduate students at a mid-Atlantic university. Eligible participants were ages 18–25, currently and/or previously had an intimate partner (examples that were provided to participants include spouses, boyfriends/girlfriends, dating partners, and ongoing sexual partners), and were proficient in English. We recruited participants through classroom visits to four public health courses and a recruitment email. Because fewer students ages 23–25 volunteered to participate when using this strategy, we sent a recruitment email to the public health graduate student listserv to increase recruitment of these ages.

Phase 2 included a convenience sample of 181 Amazon Mechanical Turk (MTurk) workers (Amazon Mechanical Turk, 2018). MTurk is a useful and reliable tool for data collection (Buhrmester et al., 2011; Goodman et al., 2013; Mason & Suri, 2012). Previous researchers have found similar results and psychometrics between MTurk and college-student samples in areas such as health literacy, decision-making, and personality (Buhrmester et al., 2011; Goodman et al., 2013; Nguyen et al., 2016; Paolacci et al., 2010). Eligible participants in this study were ages 18–25, located in the United States, currently and/or previously had an intimate partner, had high-quality performance statistics on MTurk (i.e., requestors approved ≥ 98% of their tasks; they completed and were approved for ≥ 500 tasks; Nguyen et al., 2016), and were victims of IPC. These victims were a subset of individuals who responded to a larger, broader survey (N = 469) that was advertised as a study examining the use of computer-based technology among intimate partners and associated health states. Therefore, they were deemed eligible for this study based on their responses to cyberstalking victimization questions that were included in the broader survey (see Methods for the cyberstalking victimization measure). Information about the study and the survey link were posted on the MTurk website. Interested participants were asked to take the survey alone in a quiet, private area. To ensure the quality of our MTurk data, we checked the dataset for suspicious and discordant responses, and none were found.

Compared to the Phase 1 sample, more participants in Phase 2 were ages 23–25, male, employed (p < 0.025 after Bonferroni adjustment), Non-Hispanic White, not attending school, earning $20,000 or more, and married (p < 0.017 after Bonferroni adjustment; see Table 1 in Results for sample characteristics).

Procedure

Phase 1 participants completed a 25-min survey online and received a $10 electronic gift card for Target. Phase 2 participants completed a 15-min survey online and were paid $3.50. After both surveys, we provided links to information about technology-facilitated stalking (National Network to End Domestic Violence, 2017; The National Center for Victims of Crime, 2011) and to resources that assist victims. These resources were offered by the university (Phase 1 only) and the National Center for Victims of Crime (The National Center for Victims of Crime, 2011). Participants provided informed consent online immediately before beginning both surveys. The university’s Institutional Review Board approved both phases.

Measures

Perceptions of IPC Behaviors

We asked Phase 1 participants, “Intimate partner cyberstalking involves the use of the Internet and other information and communication technologies to repeatedly monitor, threaten, and/or harass a current, former, or potential romantic partner. Do you think any of the following behaviors are cyberstalking?” Twenty technology-facilitated behaviors were provided, including 18 items from the Controlling Partners Inventory (CPI, α = 0.90 among college students; content and face validity were established by field experts; Burke et al., 2011; α = 0.84 in Phase 1) and two items that we added to increase the scope of IPC behaviors measured (i.e., checking text message and Internet search histories). We depersonalized the items from the CPI (e.g., “Using a webcam to monitor a partner’s activities”). Items that addressed Facebook were generalized to any social networking site (see Table 2). Responses included 0 = “No” and 1 = “Yes.” The cyberstalking definition provided to participants did not include the victim’s reactions to the behaviors because we wanted to focus purely on the occurrence and minimize any bias from the participants’ emotions.

IPC Perceived Severity Weights

Using a Q-sort (Barbosa et al., 1998; Stephenson, 1935, 1953), Phase 1 participants categorized these same 20 behaviors into boxes according to their beliefs about the severity of the behaviors. Seven boxes were provided, ranging from “1-Most Mild” to “7-Most Severe.” Weights for each behavior were calculated by averaging the Q-sort scores. Participants also provided open-ended responses regarding why they sorted particular behaviors as “1-Most Mild” and “7-Most Severe.”

IPC Victimization

In Phase 2, the same 20 behaviors were utilized, but they were personalized and included the CPI-Partner subscale (α = 0.86 in Phase 2; e.g., “Partner used a webcam to monitor my activities;” Burke et al., 2011). Participants answered if they ever experienced the behaviors in their current or most recent (if single) intimate relationship. Seven options were provided, including the CPI’s original five categories from 0 = “Never” to 4 = “4 or more times” (shortened to “4 + times”). We added 5 = “I do not use this technology” and 6 = “My partner does not use this technology.” The “5 s” and “6 s” were recoded as “not applicable” (< 4% for all behaviors). Valid responses were 0–4.

Participants who answered at least “1 time” to any behavior were asked if the behavior made them feel afraid, threatened, harassed, and/or distressed. Five responses were provided, from 0 = “Not at all” to 4 = “Extremely.” The data were recoded as, 0 = “No” (“Not at all”) and 1 = “Yes” (“A little bit” to “Extremely”). Following studies that defined or measured cyberstalking as more than one incident (Acquadro Maran & Begotti, 2019; Maple et al., 2012; Reyns et al., 2012) that threatened and/or harassed victims and evoked fear and/or distress (Bocij & McFarlane, 2002; Finn, 2004; Maple et al., 2012; Worsley et al., 2017), participants were categorized as victims if they experienced any of the 20 behaviors repeatedly (i.e., one behavior at least twice or multiple behaviors at least one time each), which made them feel afraid, threatened, harassed, and/or distressed.

IPC Perceived Severity Experienced

The perceived severity weights from Phase 1 were applied to the IPC victimization data collected in Phase 2. A severity score was calculated by averaging the weighted items that each participant experienced. The score ranged from 1 to 7, with higher scores indicating greater perceived severity experienced.

Depressive Symptoms

We used a short form of the Center for Epidemiologic Studies Depression Scale (CESD-10; Andresen et al., 1994) to measure depressive symptoms, which included 10 items with established convergent validity among older adults (Andresen et al., 1994) and α = 0.72 among college students (Oppong Asante & Andoh-Arthur, 2015; α = 0.89 in Phase 2; e.g., “During the past week…I felt depressed.”). The four response options ranged from 0 = “Rarely or none of the time (less than 1 day)” to 3 = “Most or all of the time (5–7 days).” Positively worded items were reverse coded so that higher scores for all items represented greater depressive symptoms. A total scale score was calculated by adding the items (range 0–30). Using the recommended reliable and validated cut-off score for depressive symptoms (Andresen et al., 1994), the variable was coded as 0 = “No depressive symptoms” (score of 0–9) and 1 = “Depressive symptoms” (score ≥ 10). We used a binary variable because we wanted to distinguish between the presence of depressive symptoms and normal “downs” that may not be indicative of depressive symptoms.

Social Isolation

We used the Friendship Scale (Hawthorne, 2006) to measure social isolation, which included six items with established concurrent validity and α = 0.83 among older adults (Hawthorne, 2006; α = 0.90 in Phase 2; e.g., “During the past four weeks…I felt isolated from other people.”). The five response options ranged from 0 = “Not at all” to 4 = “Almost always.” Positively worded items were reverse coded so that higher scores for all items signified greater social isolation. A total scale score was calculated by adding the items (range 0–24). To our knowledge, there is no validated cut-off score for social isolation, so it was used as a continuous variable.

Demographics

The demographic variables are summarized in Table 1. Originally, gender included a “transgender” response and sexual orientation included an “unsure” response. These responses were recoded as missing and not included in the analyses because the frequencies were small (transgender, n = 2, 1.9% for Phase 1 and n = 1, 0.6% for Phase 2; unsure, n = 4, 3.8% for Phase 1 and n = 0, 0.0% for Phase 2).

Statistical Analyses

All quantitative analyses were conducted with SPSS v25. Descriptive statistics were calculated for all variables. A z-test with Bonferroni adjustment was used to explore differences in demographic proportions between our two samples. Independent t-tests and ANOVA with Bonferroni post-hoc tests were used to explore bivariate associations between demographics (categorical independent variables, IV) and IPC perceived severity experienced (continuous dependent variable, DV). The association between IPC perceived severity weights (continuous IV) and IPC victimization frequency (continuous DV) was assessed with Pearson correlation and linear regression. Cases consisted of the IPC behaviors, and victimization frequency included the number of participants who experienced the behaviors at least twice. Because heteroskedasticity was present, a heteroskedasticity-consistent standard error estimator was applied to the regression (Hayes & Cai, 2007). The association between IPC perceived severity experienced (continuous IV) and depressive symptoms (binary DV) was examined with point-biserial correlation and logistic regression that controlled for age, gender, highest level of education, income, sexual orientation, relationship status, and hours/day in the virtual presence of others (i.e., in a social setting via technology, such as a cell phone call, video chat, or online messaging). The association between IPC perceived severity experienced (continuous IV) and social isolation (continuous DV) was assessed with Pearson correlation and linear regression with the same control variables. Significance for analyses with Bonferroni adjustment was p < 0.025 for two pairwise comparisons and p < 0.017 for three pairwise comparisons. Otherwise, significance was p < 0.05 and 95% confidence intervals for odds ratios not including one. Assumptions for analyses were satisfied except when noted.

Thematic analysis was conducted using NVivo 12 to identify themes from Phase 1 participants’ open-ended responses regarding why they rated IPC behaviors as the mildest or the most severe. Themes were determined for the mildest and most severe behaviors separately. We followed qualitative analytic steps provided by Braun and Clarke (Braun & Clarke, 2006). Driven by the data, codes were generated across all IPC behaviors and grouped into emergent themes. Themes were reviewed, refined, and defined. Two coders were used, and the inter-rater reliability was 92% agreement. Differences in coding were discussed until consensus was reached. Furthermore, we determined the percentage of participants that provided responses for each theme.

Missing Data

Nonresponse missing data in Phase 1 included age (3.8%), race/ethnicity (1.0%), annual income (1.9%), parental income (1.0%), and perceptions of IPC behaviors (1.0% for two behaviors). Nonresponse missing data in Phase 2 included race/ethnicity (2.2%), relationship length (0.6%), virtual presence (0.6%), depressive symptoms (3.3%), and social isolation (5.0%). Using chi-square tests, nonresponse missing data for social isolation and virtual presence were associated with gender and relationship status, respectively (p < 0.05). No other associations were found for unanswered missing data. Because missing data for some variables may be explained by observed data, as noted, we assumed missing at random and used multiple imputation to handle nonresponse missing data for Phase 2. Age, gender, race/ethnicity, highest level of education, income, sexual orientation, relationship status, relationship length, and virtual presence were used as predictors to impute social isolation, depressive symptoms, and demographic variables with missing data. Forty imputations were generated (Graham et al., 2007) and averaged to create the final imputed value. Data that were provided and recoded as missing or not applicable, as noted above (i.e., responses for transgender, unsure of sexual orientation, and not using the technology included in the IPC victimization items), were not imputed. Unanswered missing data for Phase 1 were not imputed because these data were only used for descriptive analyses.

Results

Descriptive Statistics and Demographic Differences with IPC Perceived Severity Experienced

Table 1 includes descriptive statistics for Phase 1 and Phase 2. Among Phase 2 participants, the mean scores for IPC perceived severity experienced and social isolation were 3.46 (SD = 0.61) and 9.90 (SD = 5.99), respectively. Over half of these MTurk workers indicated depressive symptoms (n = 106, 58.6%). Male MTurk workers experienced greater perceived severity of IPC victimization compared to females (p < 0.05, Cohen’s d = 0.33; see Table 1). However, Levene’s test for equality of variances was significant (p < 0.05), so these results were based on equal variances not assumed. No other demographics were significantly associated with IPC perceived severity experienced.

Table 1 Participant characteristics and associations with intimate partner cyberstalking (IPC) perceived severity experienced
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Perceived Severity Weights, Perceptions of IPC Behaviors, and Prevalence of Victimization

Monitoring a partner with a hidden camera received the most severe weight in Phase 1 and was the least common behavior experienced at least twice in Phase 2 (see Table 2). The majority of Phase 1 participants thought each technology-facilitated behavior was cyberstalking (see Table 2).

Table 2 Perceived severity weights, perceptions of intimate partner cyberstalking (IPC) behaviors, and prevalence of behaviors experienced at least twice (2 +)
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Themes Describing the Mildest and Most Severe Behaviors

In general, the majority of themes that emerged for the mildest and most severe behaviors related to the dynamics of the romantic relationship, the harm done to the victim, and perceived social norms among young adults. We identified seven themes from Phase 1 participants’ qualitative responses that described the mildest behaviors (see Table 3). Students believed that checking behaviors, monitoring location, and excessive/threatening communication were the mildest forms of cyberstalking because (1) they were considered harmless but unhealthy (i.e., they do not directly hurt the partner but may be inappropriate behavior in the relationship); (2) they may be justified by positive intentions (e.g., young adults may check on their partner to ensure they are safe or they may excessively call them because they are more attentive); (3) respondents indicated a distinction between public and private information (e.g., a partner may choose to make certain information public on social media or partners may share a computer); (4) these behaviors were considered common/normal among young adults in untrusting (i.e., does not trust partner to be faithful) and serious/committed relationships and in this social media era; (5) partners may consent to these behaviors; (6) excessive and threatening texts/calls/emails can be ignored or blocked on phones and computers; and (7) the actions were not considered serious to those who have perpetrated the behaviors.

Table 3 Themes describing the mildest cyberstalking behaviors
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We identified seven themes from Phase 1 participants’ qualitative responses that described the most severe behaviors (see Table 4). Students considered checking, location monitoring, surveillance, threatening, and inappropriate behaviors as the most severe forms of cyberstalking because (1) they invade the partner’s privacy; (2) they can impact the partner’s physical, mental, social, academic, and economic health; (3) they are conducted to intentionally harm the partner; (4) partners may not consent to these behaviors; (5) they involve illegal activity; (6) they may be a precursor to other forms of abuse, such as physical or sexual abuse; (7) and they may involve technology, particularly email, that is not commonly used among young adults other than for work or school. For both mild and severe behaviors, some participants commented that the victim’s perceptions of the behaviors are subjective.

Table 4 Themes describing the most severe cyberstalking behaviors
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Hypothesis 1

Supporting Hypothesis 1 (as the perceived severity of IPC behaviors increases, the frequency of victimization decreases), the perceived severity weights from Phase 1 were negatively correlated with victimization frequency in Phase 2 (r =  − 0.72, p < 0.001). As the perceived severity weights increased by one unit, victimization frequency decreased by approximately 11 participants (p < 0.001; see Table 5).

Table 5 Linear regression analyses with intimate partner cyberstalking (IPC) perceived severity weights, victimization frequency, perceived severity experienced, and social isolation
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Hypothesis 2

The results support Hypothesis 2 (when the perceived severity of IPC victimization experienced increases, young adults are more likely to report depressive symptoms and greater social isolation). The perceived severity of IPC victimization experienced among Phase 2 participants was positively correlated with depressive symptoms (rpb = 0.26, p < 0.001) and social isolation (r = 0.36, p < 0.001). After controlling for demographics (i.e., age, gender, highest level of education, income, sexual orientation, relationship status, and hours/day in the virtual presence of others), Phase 2 participants were more likely to indicate depressive symptoms and greater social isolation when the perceived severity of IPC victimization experienced increased by one unit (p < 0.001, see Tables 5 and 6).

Table 6 Logistic regression analysis with intimate partner cyberstalking (IPC) perceived severity experienced and depressive symptoms
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Discussion

The young adults in this study thought IPC involved various technology-facilitated behaviors. Their perceptions support a broad definition of IPC and are consistent with studies that assessed IPC with technologies besides the Internet (Shorey et al., 2015; Smoker & March, 2017). These results suggest that IPC is perceived to be a complex issue that cannot be measured with one technology or behavior. Their perceptions may be influenced by advancements in technology, which enable individuals to quickly and easily monitor and harass their partners via multiple devices and applications (Melander, 2010). Young adults’ perceptions of IPC may continue to evolve as new technologies are developed.

Consistent with the cyberstalking literature (Barnes & Biros, 2007), threatening cell phone calls (i.e., verbal communication) received a slightly higher perceived severity weight than threatening texts and emails (i.e., text communication). Threatening behaviors and monitoring partners via cameras and spyware received the highest perceived severity weights, which were similar to severe cyber pursuit behaviors (Dardis & Gidycz, 2017). Additionally, our results support literature indicating that violation-related intrusion behaviors (e.g., done without consent) are the most severe (Cupach & Spitzberg, 2000). Based on the themes that were generated, behaviors are perceived to be more severe when the perpetrator’s intentions are harmful, the victim’s health is negatively impacted, and their privacy is violated. These results are consistent with literature assessing severity based on the extent participants felt or would feel annoyed, upset, threatened, and their privacy violated by the behaviors (Cupach & Spitzberg, 2000).

According to a previous study, female college students were more likely to be victims of technological dating abuse compared to males (Burke et al., 2011). However, when severity is taken into account, we found that males experienced greater perceived severity of IPC than females. Our results are consistent with another study examining severe cyber psychological abuse among college students in romantic relationships (Leisring & Giumetti, 2014). Given the limited literature investigating IPC severity, this gender-severity relationship deserves further exploration in order to clarify high-risk groups that need attention when developing and implementing IPC prevention strategies. Research that has consistently identified a particular gender or genders (e.g., female, male, transgender, non-binary, etc.) that has/have experienced greater IPC severity compared to other genders could provide insight into which gender groups require targeted prevention programs.

As hypothesized (H1), the perceived severity weights increased as victimization frequency decreased. Therefore, behaviors that were perceived to be more severe were less common. Similarly, severe in-person and cyber pursuits and intrusions among college students have occurred less frequently than minor behaviors (Cupach & Spitzberg, 2000; Dardis & Gidycz, 2017). According to the themes that emerged, mild behaviors may be more frequent because they can be justified by positive intentions and are considered harmless, consensual, and normal among partners. Severe behaviors may be less frequent because they are damaging, illegal, not consensual, and may include uncommonly used technology.

As hypothesized (H2), participants were more likely to experience depressive symptoms and greater social isolation when the perceived severity of IPC victimization increased. These results support findings from stalking studies (Mechanic et al., 2000; Purcell et al., 2004). Victims of greater severity may experience lower mood, increased helplessness, and less control over the situation, which could be associated with their depressive symptoms (Worsley et al., 2017). They may also be more likely to experience social isolation due to a lack of interest in socializing when feeling disheartened and anxious about the situation and distrusting others after the incident (Worsley et al., 2017). Additionally, they may curtail their use of social media and other technology (Worsley et al., 2017), or their partner may control their network of friends (Melander, 2010).

Strengths and Limitations

This study was the first, to our knowledge, to (1) have young adults identify IPC from a list of potential behaviors; (2) measure perceived IPC severity via a Q-sort; and (3) apply severity perceptions to understand the relationships between IPC severity experienced and health states. Also, we included a larger sample size than traditional Q-sorts (Brown, 1980; Dziopa & Ahern, 2011). However, the study utilized two different samples, which were demographically disparate. Both phases were cross-sectional, and the results can only suggest associations, not causality. The questions assessing depressive symptoms and social isolation were not asked as direct outcomes of IPC, so it is uncertain whether they resulted from IPC. Furthermore, it is unclear if the victims experienced in-person stalking or other forms of intimate partner abuse in addition to IPC. Although a next step for our analysis could be to explore social isolation as a mediator in the pathway between IPC perceived severity experienced and depressive symptoms or to investigate depressive symptoms as a mediator in the pathway between IPC perceived severity experienced and social isolation, the overlapping timeframes of the depressive symptoms and social isolation measures, their bidirectional relationship (Cacioppo & Hawkley, 2009; Elmer & Stadtfeld, 2020), and a lack of theoretically-sound instrumental variables limited the opportunity to appropriately explore these mediation relationships. Because data were self-reported, there may be social desirability bias present. The resulting odds ratio from the logistic regression analysis with depressive symptoms had a rather large confidence interval, indicating increased uncertainty of this estimate. A larger sample may be needed. The low sample sizes for some demographic groups limited the power to detect significant differences when exploring associations between these demographic variables and IPC perceived severity experienced, further supporting the need for a larger sample. Both phases included convenience samples and cannot be generalized to all young adults ages 18–25 who have ever had an intimate partner. Because students in Phase 1 were recruited from public health classes, they may be more health-conscious than other young adults. Additionally, the MTurk workers in Phase 2 may be more susceptible to IPC because they work virtually and may be more tech-savvy.

Implications and Future Direction

The results from this study enhance our understanding of young adults’ perceptions of IPC behaviors and the severity of these behaviors. We captured their thoughts about severity quantitatively and qualitatively, which enabled us to contextualize IPC perceived severity. Future research should utilize mixed-method approaches to further explain the dynamics surrounding IPC risk and prevention. Based on young adults’ perceptions of IPC behaviors, future research should include a variety of technology-facilitated behaviors in their measurement of IPC and utilize a standardized definition of IPC that incorporates multiple technologies. Furthermore, their perceptions of severity inform potential methods for assessing severity in future studies. Young adults’ thoughts about IPC behaviors and severity can inform prevention strategies to address IPC among this population.

The results from this study increase our knowledge of psychological and social health states associated with IPC perceived severity. Future research should continue to investigate the epidemiology surrounding IPC severity, such as further exploration of prevalence estimates, risk factors, and high-risk groups. Additionally, more research is necessary to comprehend mediators and moderators in the relationships between IPC severity and adverse health states. Once we gain a better understanding of the epidemiology of severity and associated mechanisms, the results can be used to develop effective policies and programs to prevent IPC among young adults.