A longitudinal twin study of victimisation and loneliness from childhood to young adulthood

Abstract

The present study used a longitudinal and discordant twin design to explore in depth the developmental associations between victimisation and loneliness from mid-childhood to young adulthood. The data were drawn from the Environmental Risk (E-Risk) Longitudinal Twin Study, a birth cohort of 2,232 individuals born in England and Wales during 1994–1995. Diverse forms of victimisation were considered, differing across context, perpetrator and timing of exposure. The results indicated that exposure to different forms of victimisation was associated with loneliness in a dose-response manner. In childhood, bullying victimisation was uniquely associated with loneliness, over and above concurrent psychopathology, social isolation and genetic risk. Moreover, childhood bullying victimisation continued to predict loneliness in young adulthood, even in the absence of ongoing victimisation. Within-twin pair analyses further indicated that this longitudinal association was explained by genetic confounds. In adolescence, varied forms of victimisation were correlated with young adult loneliness, with maltreatment, neglect and cybervictimisation remaining robust to controls for genetic confounds. These findings indicate that vulnerability to loneliness in victimised young people varies according to the specific form of victimisation in question, and also to the developmental period in which it was experienced.

Introduction

A large body of evidence confirms that children and adolescents who are exposed to victimisation face increased risk of diverse negative outcomes by early adulthood, including psychopathology (Bowes, 2015; Jaffee, 2017; Norman, Byambaa, De et al, 2012; Schaefer, Moffitt, Arseneault et al, 2018), lower educational and career attainment (Brown & Taylor, 2008; Currie & Widom, 2010), and risk markers for inflammatory disease (Baldwin, Arseneault, Caspi et al, 2014; Copeland, Wolke, Lereya et al, 2014; Rasmussen, Moffitt, Eugen-Olsen et al, 2019). Another potentially important outcome is loneliness, a form of psychological distress associated with perceived shortcomings in one’s social relationships (Peplau & Perlman, 1982). Loneliness is particularly common among adolescents and young adults (Luhmann & Hawkley, 2016). However, individuals vary in their susceptibility to feeling lonely, and there is evidence that this vulnerability could be shaped by adverse peer experiences earlier in life, such as being the victim of violence (Matthews, Danese, Caspi et al, 2019).

According to an evolutionary model of loneliness, humans are motivated to seek social connection as it confers a sense of safety (Cacioppo, Hawkley, Ernst et al, 2006). Being subjected to victimisation is a sign that one’s safety has been compromised, and this could in turn elicit a feeling that one’s network of social connections is deficient and not fulfilling the functions desired of it. It is therefore plausible that feelings of loneliness could increase subsequent to a victimisation exposure. If robust associations between victimisation and loneliness can be established, this could inform future research questions about a potential mediating role of loneliness in the associations between youth victimisation and later outcomes.

Differential effects of victimisation on loneliness

Much of the research on childhood victimisation and loneliness has focused on bullying (Pavri, 2015). Notably, bullying is a very specific form of victimisation, the distinct features of which could have important implications (Arseneault, 2018). First, bullying takes place between peers of a similar age. Given the important role of peer acceptance in shaping children’s sense of belonging (Qualter, Vanhalst, Harris et al, 2015), being bullied by peers could therefore have particularly strong implications for loneliness compared to other forms of victimisation. Second, bullying is characterised by an imbalance of power in favour of the perpetrator. Thus, children who become victims of bullying are often characterised by certain pre-existing disadvantages that make it harder to defend themselves. This highlights the importance of controlling for vulnerabilities that frequently co-occur with both bullying and loneliness, such as depression and anxiety, to test whether loneliness in bullied individuals occurs only in the context of these other problems, or whether an association exists even in their absence.

In the adolescent literature, there has been an increasing focus on internet or ‘cyber’ victimisation, due to the growing ubiquity of digital technology in everyday life, particularly among younger generations. This form of victimisation has its own distinct characteristics in comparison to offline forms: it takes place away from any physical location, the identity of the perpetrator may not be known, and it can continue even if the victims remove themselves from the situation (Przybylsi & Bowes, 2017). As a relatively new phenomenon, conceptual and methodological approaches to cybervictimisation have varied widely, and consequently, so too have estimates of its prevalence and effects on mental health (Nixon, 2014). Nonetheless, there is evidence that cybervictimisation is associated with greater loneliness and other emotional problems in young people (Olenik-Shemesh, Heiman & Eden, 2012; Varghese & Pistole, 2017).

Beyond bullying and cybervictimisation, other forms of victimisation may also play a role in the emergence of loneliness. For instance, emotional maltreatment may disrupt the formation of secure attachments, negatively shaping individuals’ perceptions of their relationships with others (Tailieu, Brownridge, Sareen & Afifi, 2016). Being physically harmed by an adult could elevate vigilance for threat, resulting in low trust, avoidant behaviours and difficult social encounters (McCrory, Gerin & Viding, 2017). Victims of sexual assault may feel unable to disclose their experiences, due to perceived stigma or an expectation that they will not be believed (Sable, Danis, Mauzy & Gallagher, 2006). All such possibilities could be reflected in elevated feelings of loneliness. Moreover, exposure to multiple forms of victimisation (‘polyvictimisation’) could have a dose-response association with loneliness, as has been observed for other mental and physical health outcomes (Felitti, Anda, Nordenberg et al, 1998). This highlights the value of measurement approaches that capture diverse forms of victimisation that vary in terms of the nature of the exposure (e.g. physical, emotional, sexual), the perpetrator (e.g. family members, peers, strangers), the context (e.g. home, school, online), and the severity (Fisher, Caspi, Moffitt et al, 2015).

Temporal priority and genetic confounding

The directionality of the associations between victimisation and loneliness is not straightforward. Although loneliness could be an outcome of victimisation, an alternative hypothesis is that lonely children are seen by perpetrators as easy targets: traits such as shyness and low confidence could make it harder for them to defend themselves, and thus make them more likely to be singled out (Acquah, Topalli, Wilson, Junttila & Niemi, 2015; Pavri, 2015). Moreover, negatives stereotypes attached to the concept of loneliness could lead to lonely children being ill-treated by their peers (Rotenberg & Kmill, 1992). If this were the case, associations between childhood victimisation and feelings of loneliness later in development could simply reflect the continuity of pre-existing loneliness in childhood. Alternatively, victimisation and loneliness may predict one another in a bidirectional manner. In addition, the timing of the exposure during development may play a role in shaping the associations between victimisation and loneliness: certain types of victimisation may exert distinct effects when experienced in childhood versus adolescence (Logan-Greene, Nurius, Hooven & Thompson, 2015; Troop-Gordon, 2017). These considerations necessitate longitudinal study designs, with repeated measures spanning multiple developmental stages, to disentangle the temporal priority of associations and test the possibility of ‘critical periods’ for victimisation exposure.

Another issue that bears consideration is that associations between victimisation and loneliness could be confounded by genetic risk. Behavioural genetics research shows that variation in most psychological traits is partially explained by genetic differences; that is, individuals carrying certain genetic variants are more likely to have the trait than others (Plomin, DeFries, Knopik & Neiderhiser, 2016). Moreover, the genetic influences on one trait often overlap with other traits, meaning that a correlation between two phenotypes could be driven by an underlying genetic correlation. The heritability of loneliness (that is, the proportion of variance accounted for by genetic influences) is approximately 40–50% (Goossens, van Roekel, Verhagen et al, 2015; Matthews, Danese, Wertz et al, 2016). Victimisation, though ostensibly an environmental exposure, also does not happen at random and there may be heritable traits that increase the risk of a person becoming a victim (Ball, Arseneault, Taylor et al, 2008; Beaver, Boutwell, Barnes & Cooper, 2009; Beckley, Caspi, Arseneault et al, 2018). To the extent that the same genetic influences that place individuals at risk of victimisation also contribute to loneliness, the association between these phenomena may be confounded. This can be ruled out by comparing outcomes in monozygotic twin pairs who are matched for their genomes but discordant in their exposure to victimisation. This method has allowed the robustness of the association between victimisation and mental health to be stringently tested (Schaefer et al, 2018; Jaffee, Caspi, Moffitt & Taylor, 2004; Pingault, O’Reilly, Shoeler et al, 2018).

Aim of study

In the present study, we used a developmental cohort of twins to explore the associations between victimisation and loneliness between adolescence and young adulthood. Multiple forms of victimisation were considered, spanning different contexts, perpetrators, levels of severity, and developmental periods. As well as investigating the independent effects of different form of victimisation, we tested for a cumulative effect of experiencing multiple forms of victimisation. We also exploited both cross-sectional and longitudinal associations to test the directionality of effects. Furthermore, the robustness of associations was tested, first by controlling for concomitant psychopathology, and second by examining within-twin pair discordance in victimisation to control for unmeasured familial sources of confounding.

Methods

Participants

Participants were members of the Environmental Risk (E-Risk) Longitudinal Twin Study, which tracks the development of a birth cohort of 2,232 British children. The sample was drawn from a larger birth register of twins born in England and Wales in 1994–1995 (Trouton, Spinath & Plomin, 2002). Full details about the sample are reported elsewhere (Moffitt and E-Risk Study Team, 2002). Briefly, the E-Risk sample was constructed in 1999–2000, when 1,116 families (93% of those eligible) with same-sex 5-year-old twins participated in home-visit assessments. This sample comprised 56% monozygotic (MZ) and 44% dizygotic (DZ) twin pairs; sex was evenly distributed within zygosity (49% male). 90% of participants were of white ethnicity.

Families were recruited to represent the UK population with newborns in the 1990s, to ensure adequate numbers of children in disadvantaged homes and to avoid an excess of twins born to well-educated women using assisted reproduction. The study sample represents the full range of socioeconomic conditions in Great Britain, as reflected in the families’ distribution on a neighbourhood-level socioeconomic index (ACORN [A Classification of Residential Neighbourhoods], developed by CACI Inc. for commercial use) (Odgers, Caspi, Bates, Sampson & Moffitt, 2012; Odgers, Caspi, Russell et al, 2012). Specifically, E-Risk families’ ACORN distribution matches that of households nation-wide: 25.6% of E-Risk families live in “wealthy achiever” neighbourhoods compared to 25.3% nationwide; 5.3% vs. 11.6% live in “urban prosperity” neighbourhoods; 29.6% vs. 26.9% live in “comfortably off” neighbourhoods; 13.4% vs. 13.9% live in “moderate means” neighbourhoods, and 26.1% vs. 20.7% live in “hard-pressed” neighbourhoods. E-Risk underrepresents “urban prosperity” neighbourhoods because such houses are likely to be childless.

Follow-up home visits were conducted when the children were aged 7 (98% participation), 10 (96%), 12 (96%), and at 18 years (93%). There were 2,066 children who participated in the E-Risk assessments at age 18, and the proportions of MZ (56%) and male same-sex (47%) twins were almost identical to those found in the original sample at age 5. The average age of the twins at the time of the assessment was 18.4 years (SD = 0.36); all interviews were conducted after their 18th birthday. There were no differences between those who did and did not take part at age 18 in terms of socioeconomic status (SES) assessed when the cohort was initially defined (χ² = 0.86, p = .65), age-5 IQ scores (t = 0.98, p = .33), or age-5 emotional or behavioural problems (t = 0.40, p = .69 and t = 0.41, p = .68, respectively).

Home visits at ages 5, 7, 10, and 12 years included assessments with participants as well as their mother (or primary caretaker). The home visit at age 18 included interviews only with the participants. The Joint South London and Maudsley and the Institute of Psychiatry Research Ethics Committee approved each phase of the study. Parents gave informed consent and twins gave assent between 5–12 years and then informed consent at age 18.

Measures

Victimisation

Childhood victimisation was assessed repeatedly when participants were 5, 7, 10, and 12 years old, including physical/sexual abuse, emotional abuse and neglect, physical neglect, and bullying by peers. Exposures were coded from 12-year dossiers for each child that comprised information from home-visit staff, mothers, children, family doctors, and child-protection interventions. Each exposure across childhood was coded for severity or frequency on a 3-point scale (Table 1).

Table 1:

Associations between childhood victimisation and childhood loneliness (age 5–12).

		N (%)	Unstandardised regression coefficent (95% CI)
Physical/sexual abuse
	Minor	344 (15.41)	.09 (−.03, .20)
	Severe	128 (5.73)	.23 (.01, .47)
Physical neglect
	Minor	158 (7.08)	.23 (.02, .43)
	Severe	44 (1.97)	.08 (−.23, .40)
Emotional abuse/neglect
	Moderate	195 (8.74)	.24 (.06, .42)
	Severe	68 (3.05)	.49 (.17, .80)
Bullying victimisation
	Occasional	788 (35.59)	.24 (.17, .31)
	Frequent	197 (8.90)	.83 (.63, 1.03)

N = Number, CI = Confidence interval. All associations adjusted for sex and socioeconomic status. Associations shown in bold are significant using the Benjamini-Hochberg procedure with a false discovery rate of .05.

Adolescent victimization was assessed at age 18, when participants were interviewed about experiences between ages 12 and 18 using the Juvenile Victimization Questionnaire (Finkelhor, Hamby, Turner & Ormrod, 2011), adapted as a clinical interview. Age 12 is a salient age for our participants because it is when British children leave primary school and enter secondary school. The study assessed seven forms of victimization: maltreatment, neglect, sexual victimization, family violence, peer/sibling victimization, cybervictimisation, and crime victimization. Like childhood victimization, exposure to each form of victimisation was coded for severity on a 3-point scale (Table 2).

Table 2:

Associations between adolescent victimisation (age 12–18) and young adult loneliness (age 18).

			Unstandardised regression coefficient (95% CI)
		N (%)	Adjusted for sex and socioeconomic status	Adjusted additionally for childhood loneliness (age 12)	Adjusted additionally for childhood victimisation (age 5–12)
Maltreatment
	Moderate	213 (10.32)	1.49 (1.15, 1.84)	1.40 (1.07, 1.74)	1.39 (1.06, 1.72)
	Severe	67 (3.25)	1.85 (1.30, 2.40	1.67 (1.10, 2.24)	1.63 (1.04, 2.22)
Neglect
	Moderate	80 (3.88)	1.12 (.62, 1.62)	.88 (.36, 1.41)	.84 (.32, 1.37)
	Severe	46 (2.23)	2.04 (1.34, 2.74)	1.61 (.91, 2.31)	1.55 (.83, 2.26)
Sexual victimisation
	Moderate	198 (9.62)	.66 (.35, .96)	.55 (.26, .84)	.53 (.24, .83)
	Severe	53 (2.57)	2.41 (1.78, 3.03)	1.95 (1.28, 2.63)	1.90 (1.22, 2.58)
Family victimisation
	Moderate	136 (6.60)	.40 (.05, .75)	.47 (.12, .81)	.45 (.11, .79)
	Severe	250 (12.12)	.65 (.37, .92)	.55 (.28, .83)	.51 (.24, .79)
Peer victimisation
	Moderate	870 (42.13)	.62 (.45, .80)	.58 (.41, .75)	.57 (.40, .75)
	Severe	323 (15.64)	1.34 (1.07, 1.62)	1.22 (.95, 1.49)	1.20 (.93, 1.47)
Crime victimisation
	Moderate	670 (32.43)	.62 (.43, .82)	.56 (.37, 0.75)	.55 (.36, .74)
	Severe	398 (19.26)	.99 (.72, 1.25)	.89 (.63, 1.14)	.86 (.60, 1.12)
Cybervictimisation
	Moderate	286 (13.86)	1.15 (.86, 1.44)	1.08 (.80, 1.37)	1.07 (.79, 1.35)
	Severe	133 (6.45)	1.01 (.62, 1.39)	.89 (.51, 1.27)	.86 (.49, 1.24)

N = Number, CI = Confidence interval. All analyses are adjusted for sex and socioeconomic status. Associations shown in bold are significant using the Benjamini-Hochberg procedure with a false discovery rate of .05.

Polyvictimisation refers to the experience of multiple victimizations of different types, and it is a more powerful predictor of adverse outcomes than any particular exposure (Finkelhor, Ormrod & Turner, 2007). A 3-level measure of polyvictimisation was derived for both childhood and adolescence, based on the number of different forms of severe victimisation present: none (0), one (1), and two or more (2).

Detailed descriptions of the victimisation assessments have been published previously (Danese, Moffitt, Arseneault, et al, 2017; Fisher et al, 2015), and are provided in the Supplementary Materials.

Loneliness

A measure of loneliness in childhood was derived using three items from the Children’s Depression Inventory (CDI; Kovacs, 1992), completed when participants were aged 12. Each item was presented as a set of three statements, and participants were instructed to select the statement that described them best: (1) “I do not feel alone”, “I feel alone many times” or “I feel alone all the time”; (2) “I have plenty of friends,” “I have some friends but I wish I had more” or “I do not have any friends”; and (3) “Nobody really loves me”, “I am not sure if anybody loves me”, “I am sure that somebody loves me”. Although drawn from an instrument designed to assess depression, these particular items are very similar in content to items used in the Children’s Loneliness Scale (CLS), which is considered the gold standard for assessing loneliness in children (Maes, Van den Noortgate, Vanhalst, Beyers & Goossens, 2017). Items were coded 0 to 2 and summed to produce a scale from 0–6 (M = .48; SD =.86, α = .48).

Loneliness in adulthood was assessed at age 18 using four items from the UCLA Loneliness Scale, Version 3 (Russell, 1996): “How often do you feel that you lack companionship?”, “How often do you feel left out?”, “How often do you feel isolated from others?” and “How often do you feel alone?” A very similar short form of the UCLA scale has previously been developed for use in large-scale surveys, and correlates strongly with the full 20-item version (Hughes, Waite, Hawkley & Cacioppo, 2004). The scale was administered as part of a computer-based self-complete questionnaire. The items were rated “hardly ever” (0), “some of the time” (1) or “often” (2). Items were summed to produce a total loneliness score from 0–8 (M = 1.57, SD = 1.94, α = .83). The correlation between loneliness measured at age 12 and at age 18 was r = .25.

Covariates

Because the items used in the age-12 loneliness measure originated from a scale used to measure depression, and because loneliness and depression are highly correlated in general (Matthews et al, 2016), the remaining items of the CDI were summed to produce a depressive symptom scale, which was entered as a covariate with childhood loneliness to account for the shared variance between them. Symptoms of anxiety at age 12 were assessed using the Multidimensional Anxiety Scale for Children (March, 1997). At age 18, symptoms of depression and anxiety were assessed via a structured clinical interview based on DSM-IV criteria (American Psychiatric Association, 1994). All analyses were adjusted for sex and for family socioeconomic status, measured via a standardized composite of income, education and occupation.

Data analysis

All analyses were conducted in Stata Version 15 (StataCorp, 2017). First, in order to ascertain whether the number of victimisation exposures was associated with loneliness in a dose-response manner, we tested associations between polyvictimisation and loneliness. These associations were examined in childhood (age 5–12 victimisation and age-12 loneliness), in adolescence (age 12–18 victimisation and age-18 loneliness), and from childhood to young adulthood (age 5–12 victimisation and age-18 loneliness). We also tested for a graded association between re-victimisation (exposure in both childhood and adolescence) and loneliness in young adulthood.

Second, we tested childhood associations between individual forms of victimisation across ages 5 to 12 and loneliness at age 12. Due to the high co-occurrence between loneliness and depression and anxiety (Matthews et al, 2019), we further controlled for childhood symptoms of these mental health problems. Third, to test whether discordance in victimisation within twin pairs was associated with differences in loneliness, we applied fixed-effects models to the data, thus controlling for familial confounds. We then repeated this analysis using MZ twin pairs only, thereby controlling completely for genetic variation between twins in a pair.

Third, we tested associations between adolescent victimisation across ages 12 to 18 and loneliness at age 18. To investigate whether these associations were explained by pre-existing loneliness, we first tested whether childhood loneliness was associated with greater risk of adolescent victimisation, and then included childhood loneliness as a covariate in the associations between adolescent victimisation and young adult loneliness. Next, to determine whether these associations were explained by the continuity of victimisation originating earlier in life, we tested a further model additionally controlling for prior exposure to any severe victimisation in childhood. Further, we conducted sensitivity analyses, in which age-18 depression and anxiety were controlled for. We then applied fixed-effects models to the data, first in the whole sample and then in MZ twins only, to test whether the significant associations were independent of shared environmental and genetic confounds.

Fourth, we tested longitudinal associations between childhood victimisation and age-18 loneliness. In order to test whether victimisation predicted increases in loneliness over time, we then added age-12 loneliness as a covariate after the initial bivariate associations were estimated. Next, to test whether childhood victimisation continued to predict loneliness regardless of whether victimisation was still ongoing, we controlled for exposure to any victimisation during adolescence. Significant associations were further subjected to controls for age-18 depression and anxiety. We also used fixed-effects models to control for the effects of unmeasured familial confounds.

Participants in this study were pairs of same-sex twins, and therefore each family contained data for two individuals, resulting in non-independent observations. To correct for this, we used tests based on the Huber-White or sandwich variance (Williams, 2000), which adjusts the estimated standard errors to account for the dependence in the data.

Post-hoc analyses

We conducted two additional sets of analyses to address questions arising from the main results. First, we entered childhood social isolation between ages 5 to 12 as a covariate with childhood bullying, to test whether the association between bullying and loneliness was explained by victimised children being isolated by their peers. The childhood social isolation scale was based on mothers’ and teachers’ reports of children’s peer rejection and social withdrawal, using items drawn from the Children’s Behaviour Checklist and Teacher Report Form (Achenbach, 1991a, 1991b). Full details of the measure are published elsewhere (Matthews, Danese, Wertz, et al, 2015). This analysis was initially conducted with loneliness at age 12 as the dependent variable, and this was then repeated for loneliness at age 18. Second, we entered problematic technology use at age 18 as a covariate with adolescent cybervictimisation, to test whether the association between this form of victimisation and age-18 loneliness was explained by excessive time spent online. Problematic technology use was measured using an adapted version of the Compulsive Internet Use Scale (Meerkerk, Van Den Eijnden, Vermulst & Garretsen, 2009).

A breakdown of the research questions and variables used in each analysis is provided in Supplementary Table S1.

Results

Cumulative and enduring effects of polyvictimisation

Individuals who were exposed to one form of severe victimisation were lonelier on average than those not exposed, and individuals exposed to multiple forms of severe victimisation were more lonely compared to those exposed to just one form, or none at all (Figure 1). This pattern was observed in childhood (B = .54; 95% CI = .31, .77), in adolescence (B = 1.25; 95% CI = .98, 1.53), and from childhood to adolescence (B = .73, 95% CI = .31, 1.15). Furthermore, individuals who were exposed to severe victimisation in both childhood and adolescence were lonelier at age 18 than individuals who were victimised in just one of these time periods, or never (B = 1.14; 95% CI = .83, 1.45).

Figure 1.

Mean (z-scored) levels of loneliness according to the number of forms of victimisation experienced. * p < .05 *** p < .001

Associations between victimisation and loneliness in childhood

In bivariate regression models, multiple forms of victimisation between 5–12 years were associated with loneliness at age 12 (Table 1). However, when concurrent depression and anxiety at age 12 were controlled for, only bullying remained independently associated with loneliness (occasional bullying: B = .11; 95% CI = .05, .17; frequent bullying: B = .24; 95% CI = .09, .39). When social isolation between 5–12 years was controlled for in a post-hoc analysis, childhood bullying remained associated with loneliness at age 12 (occasional: B = .18, 95% CI = .11, .26; frequent B = .67; 95% CI = .46, .87).

A fixed effect model using the whole sample (MZ and DZ twins together) revealed that bullying victimisation was associated with within-family differences in loneliness, indicating an association independent of shared environmental influences (occasional bullying: B = .25; 95% CI = .12, .38; frequent bullying: B = .76; 95% CI = .47, 1.05). When the sample was restricted to MZ twins only, thereby holding genetic influences constant also, the association remained significant (occasional: B = .19; 95% CI = .01, .37; frequent: B = .71; 95% CI = .30, 1.12). Thus, among genetically-identical twin pairs discordant for bullying victimisation, the twins who were bullied were lonelier on average than their non-bullied co-twins. Within-family analyses could not be conducted for physical neglect or emotional abuse/neglect due to low discordance for these exposures among MZ twins (Supplementary Table S2).

Associations between adolescent victimisation and loneliness in young adulthood

All forms of adolescent victimisation were associated with greater feelings of loneliness at age 18 (Table 2). The strongest associations were for severe maltreatment, sexual victimisation and neglect. Adolescent victimisation was also predicted by childhood loneliness (Table 3). Nonetheless, all associations between adolescent victimisation and age-18 loneliness remained significant after controlling for childhood loneliness, and for prior victimisation in childhood (Table 2). These associations were also robust to controls for the concurrent presence of any other form of severe victimisation, and for depression and anxiety symptoms, with the exception of family victimisation and moderate sexual victimisation which became non-significant (Table 4).

Table 3:

Associations between childhood loneliness (age 12) and adolescent victimisation (age 12–18)

	N (%)	RR (95% CI)
		Adjusted for sex and socioeconomic status	Adjusted additionally for childhood victimisation (age 5–12)
Maltreatment
Moderate	213 (10.32)	1.42 (1.21, 1.65)	1.35 (1.15, 1.58)
Severe	67 (3.25)	1.62 (1.31, 2.01)	1.39 (1.12, 1.72)
Neglect
Moderate	80 (3.88)	1.59 (1.29, 1.97)	1.46 (1.17, 1.83)
Severe	46 (2.23)	1.98 (1.58, 2.49)	1.76 (1.38, 2.23)
Sexual victimisation
Moderate	198 (9.62)	1.36 (1.18, 1.57)	1.31 (1.13, 1.52)
Severe	53 (2.57)	2.05 (1.63, 2.57)	1.81 (1.43, 2.30)
Family victimisation
Moderate	136 (6.60)	.92 (.73, 1.15)	.88 (.70, 1.11)
Severe	250 (12.12)	1.26 (1.11, 1.44)	1.17 (1.02, 1.34)
Peer victimisation
Moderate	870 (42.13)	1.23 (1.09, 1.38)	1.19 (1.06, 1.35)
Severe	323 (15.64)	1.54 (1.32, 1.79)	1.44 (1.24, 1.68)
Crime victimisation
Moderate	670 (32.43)	1.18 (1.04, 1.34)	1.14 (1.00, 1.30)
Severe	398 (19.26)	1.36 (1.18, 1.56)	1.26 (1.09, 1.46)
Cybervictimisation
Moderate	286 (13.86)	1.37 (1.21, 1.55)	1.32 (1.16, 1.50)
Severe	133 (6.45)	1.39 (1.14, 1.69)	1.31 (1.08, 1.59)

N = Number, CI = Confidence interval. RR = Relative risk ratio. All associations adjusted for sex and socioeconomic status. Associations shown in bold are significant using the Benjamini-Hochberg procedure with a false discovery rate of .05.

Table 4:

Associations between adolescent victimisation (age 12–18) and young adult loneliness (age 18), adjusting for confounds

		Association with loneliness B (95% CI)		Within-family fixed effect B (95% CI)
		Adjusted for other forms of victimisation (age 12–18)	Adjusted for depression and anxiety (age 18)	Whole sample (MZ and DZ twins)	MZ twins only
Maltreatment
	Moderate	1.18 (.82, 1.53)	.92 (.63, 1.21)	.99 (.61, 1.36)	1.07 (.55, 1.59)
	Severe	1.21 (.65, 1.76)	.91 (.43, 1.39)	1.22 (.38, 2.06)	.73 (−.27, 1.74)
Neglect
	Moderate	.66 (.14, 1.17)	.49 (.03, .94)	.47 (−.14, 1.09)	.14 (−.66, .93)
	Severe	1.23 (.55, 1.91)	.83 (.22, 1.44)	1.37 (.37, 2.37)	1.47 (.20, 2.74)
Sexual victimisation
	Moderate	.29 (−.02, .59)	−.06 (−.34, .23)	.06 (−.31, .43)	.08 (−.42, .58)
	Severe	1.66 (1.02, 2.31)	1.41 (.90, 1.91)	.99 (.20, 1.79)	.98 (−.01, 1.97)
Family victimisation
	Moderate	.25 (−.09, .59)	.10 (−.22, .42)	.30 (−.22, .82)	.29 (−.39, .97)
	Severe	.22 (−.06, .50)	.05 (−.20, .30)	.43 (.04, .82)	−.01 (−.56, .53)
Peer victimisation
	Moderate	.48 (.30, .65)	.28 (.11, .44)	.35 (.13, .58)	.21 (−.07, .49)
	Severe	.99 (.70, 1.27)	.61 (.35, .87)	.58 (.20, .95)	.42 (−.03, .86)
Crime victimisation
	Moderate	.44 (.25, .63)	.33 (.15, .51)	.30 (.04, .55)	.23 (−.12, .57)
	Severe	.47 (.21, .73)	.31 (.06, .55)	.60 (.23, .96)	.34 (−.11, .79)
Cybervictimisation
	Moderate	.84 (.55, 1.12)	.54 (.27, .81)	.72 (.36, 1.08)	.95 (.50, 1.40)
	Severe	.50 (.12, .88)	.32 (−.02, .66)	.77 (.29, 1.25)	.57 (.03, 1.11)

B = Unstandardised regression coefficient. CI = Confidence interval. MZ = monozygotic. DZ = dizygotic. All analyses are adjusted for sex and socioeconomic status. Associations shown in bold are significant using the Benjamini-Hochberg procedure with a false discovery rate of .05.

In the whole sample, the within-family fixed effect was significant for all forms of victimisation, indicating that victimisation was associated with differences in loneliness independently of shared environmental influences (Table 4). However, when the sample was restricted to MZ twins, only maltreatment, neglect and cybervictimisation remained significantly associated with loneliness. This indicates that associations between the other forms of adolescent victimisation and loneliness are largely explained by familial influences, both genetic and environmental.

As a post-hoc analysis, the association between cybervictimisation and loneliness was tested while controlling for problematic technology use, to test whether the association was explained by excessive time spent online. The inclusion of this covariate did not substantively attenuate the association (moderate: B = .93; 95% CI = .65, 1.21; severe: B = .85; 95% CI = .46, 1.23).

Longitudinal associations between childhood victimisation and age-18 loneliness

Of the four forms of childhood victimisation examined, severe physical/sexual abuse and occasional and frequent bullying up to age 12 predicted feelings of loneliness at age 18 (Table 5). The strongest effect was for frequent bullying victimisation. These associations were not explained by pre-existing loneliness in childhood. After controlling for ongoing victimisation during adolescence, only bullying remained significantly associated with loneliness. This association was robust to controls for depression and anxiety at age 18 (occasional bullying: B = .28; 95% CI = .11, .46; frequent bullying: B = .82; 95% CI = .49, 1.14), and for childhood social isolation (occasional: B = .41, 95% CI = .21, .60; frequent: .90; 95% CI = .50, 1.31).

Table 5:

Associations between childhood victimisation (age 5–12) and young adult loneliness (age 18).

		Association with loneliness B (95% CI)
		Adjusted for sex and socioeconomic status	Adjusted additionally for childhood loneliness	Adjusted additionally for adolescent victimisation
Physical/sexual abuse
	Minor	.08 (−.17, .33)	.06 (−.19, .30)	−.06 (−.31, .18)
	Severe	.60 (.14, 1.06)	.50 (.07, .92)	.22 (−.19, .62)
Physical neglect
	Minor	.21 (−.19, .61)	.10 (−.29, .48)	.05 (−.31, .41)
	Severe	.47 (−.29, 1.23)	.41 (−.37, 1.19)	.16 (−.61, .94)
Emotional abuse/neglect
	Moderate	.03 (−.33, .38)	−.08 (−.43, .27)	−.15 (−.49, .19)
	Severe	.42 (−.21, 1.05)	.18 (−.42, .78)	−.12 (−.66, .43)
Bullying victimisation
	Occasional	.47 (.29, .66)	.36 (.18, .55)	.27 (.09, .45)
	Frequent	1.13 (.75, 1.51)	.73 (.36, 1.10)	.51 (.15, .88)

B = Unstandardised regression coefficient. N = Number, CI = Confidence interval. All analyses are adjusted for sex and socioeconomic status. Associations shown in bold are significant using the Benjamini-Hochberg procedure with a false discovery rate of .05.

In fixed effect models, frequent childhood bullying victimisation predicted within-twin pair differences in age-18 loneliness in the whole sample (B = 0.56; 95% CI = .02, 1.10), indicating an association independent of family-wide environmental influences. However, this effect became non-significant when the sample was restricted to MZ twins (B = −.36; 95% CI = −1.05, .33), indicating genetic mediation of the remaining association between childhood bullying victimisation and age-18 loneliness.

Discussion

This study builds on the existing literature by using a longitudinal twin study design to advance hypotheses about the developmental associations between victimisation and loneliness in young people. Diverse forms of victimisation in childhood and adolescence were shown to co-occur with elevated feelings of loneliness, and the graded effects observed for polyvictimisation suggest a cumulative association, with higher levels of loneliness being reported in the presence of multiple forms of victimisation. Moreover, lonely children were at increased risk of experiencing new instances of victimisation during adolescence, over and above prior victimisation exposures. However, to the extent that victimised children and adolescents felt lonely as adults, this was partly explained by the presence of co-occurring mental health problems, and by genetic influences that simultaneously contribute to risk for victimisation and for loneliness.

Of the four forms of childhood victimisation investigated in this study, bullying was the most common, and emerged as the strongest correlate of loneliness at age 12. It was the only form of victimisation to be associated with loneliness irrespective of concurrent psychopathology, and was also independent of familial confounding. In late childhood and early adolescence, feelings of loneliness are related strongly to an unfulfilled need to be accepted by peers (Qualter et al, 2015). Bullying by peers constitutes a clear frustration of this need. Indeed, social exclusion is itself a common relational bullying tactic (Wolke, Woods, Bloomfield & Karstadt, 2000). This may partly explain why bullying was more strongly associated with loneliness compared to other forms of victimisation. However, social isolation did not fully explain this association, suggesting that bullying could have implications for loneliness over and above relegating children to the periphery of the peer group.

Loneliness is generally conceptualised as arising from a perceived incongruence between an individual’s desired and actual social relationships (Peplau & Perlman, 1982). For bullied children in school or other group settings, being acutely aware of the disparity between their own troubled peer relationships and the relatively positive and normative relationships enjoyed by their contemporaries in the same environment could elicit an acute sense of injustice and a perception of oneself as an outsider. Feeling that one has no one to turn to for support could further compound feelings of isolation and helplessness, as victims often believe that reporting the bullying (for example, to a teacher) is not a viable option (Berguno, Leroux, McAinsh & Shaikh, 2004). Other potential mechanisms through which bullying could increase vulnerability to loneliness include diminished self-esteem, social anxiety, and elevated sensitivity to social rejection (Iffland, Sansen, Catani & Neuner, 2014; Pavri, 2015; Zimmer-Gembeck, Trevaskis, Nesdale & Downey, 2014).

Bullying was also the only form of childhood victimisation that foreshadowed greater feelings of loneliness in adulthood, even when victimisation was no longer ongoing. However, the within-family analyses did not support a causal pathway from childhood bullying to adult loneliness, instead pointing to common familial influences underlying the two, including genetic differences. Thus, although bullying is associated with loneliness in childhood via environmental pathways, the more long-term association between childhood bullying and young adult loneliness is largely mediated by genetic mechanisms. This finding mirrors other research on discordant twins, showing that while bullying predicts mental health problems longitudinally, the environmental component of this association, though present at baseline, diminishes over time, with genetic influences largely explaining outcomes after 5 years (Singham, Viding, Schoeler et al, 2017). One possibility is that children initially feel lonely as a result of being bullied and genetic influence shape the recovery trajectory, whereby only those children with a genetic vulnerability continue to feel lonely over time.

Children exposed to physical abuse and emotional abuse/neglect were lonelier at age 12 only if they also exhibited symptoms of depression and anxiety. As loneliness frequently co-occurs with these mental health problems, this constitutes a subgroup of substantial size. Nonetheless, it indicates that children exposed to this form of victimisation do not report loneliness in the absence of emotional problems. Previous research in this cohort has also shown that neither parental antisocial behaviour nor witnessing domestic violence in early childhood were associated with feelings of loneliness in adulthood (Matthews et al, 2019). Thus, certain experiences in the childhood home environment which have powerful implications for emotional and behavioural development appear to be less applicable to this particular outcome. Instead, victimisation within the family home seems to be more relevant for loneliness if experienced later in development: maltreatment and neglect during adolescence emerged as significant correlates of young adult loneliness, independently of covariates, whereas physical abuse during childhood only predicted loneliness if victimisation was ongoing during adolescence. Childhood maltreatment may nonetheless interact with loneliness to affect other outcomes: for example, previous findings in this cohort show that the association between loneliness and sleep impairments is exacerbated among individuals with a history of physical maltreatment (Matthews et al, 2017).

Cybervictimisation co-occurs with offline victimisation more often than not, with the latter accounting for a larger proportion of variance in mental health problems such as depression and anxiety (Przybylsi & Bowes, 2017). Despite this, both peer and cybervictimisation in adolescence were independently associated with young adult loneliness. However, of the two, only cybervictimisation survived controls for familial confounds. It is unclear what distinct features of cybervictimisation may differentiate it from ‘traditional’ peer victimisation in this way. It was hypothesised that cybervictimisation could be a proxy for compulsive or problematic internet use, which has been shown to be associated with loneliness (Nowland, Necka & Cacioppo, 2018; Matthews et al, 2019) and could increase the probability of encountering hostile communications online. However, problematic technology use did not explain the association in this sample, indicating that the experience of this type of victimisation merits further exploration. Meanwhile, the finding that an environmental effect for peer victimisation was only detected in childhood and not in adolescence suggests again that the effects of victimisation on loneliness may vary according to the developmental stage in which it is experienced.

That some of the significant associations between victimisation and loneliness were explained by genetic mechanisms raises the question of which heritable traits could underlie these associations. Depression and anxiety, which were included as covariates in this study as they are known correlates of both victimisation and loneliness, may partly account for the heritable component of these phenotypes (Arseneault, Bowes & Shakoor, 2010; Matthews et al, 2016). However, most associations survived controls for these confounds. Attachment styles or social cognitive skills may be plausible candidates that merit investigation. Furthermore, analysis of genome-wide data and polygenic risk scores may offer promise in future research of disentangling the genetic overlap between victimisation and loneliness.

Limitations

Our findings should be considered in light of some limitations. It should be noted that although data on bullying were collected prospectively, the upper limit of the reporting period (age 12) coincided with the assessment of childhood loneliness. The association between these measures is therefore based partly on cross-sectional data and does not convey information about its direction. The longitudinal associations from childhood bullying to adult loneliness, and from childhood loneliness to adolescent peer victimisation, are suggestive of a bidirectional association. However, bullying and peer victimisation are not synonymous terms; bullying being a specific form of peer victimisation that is repeated and involves a power imbalance in favour of the perpetrator (Arseneault, 2018). Testing for a reciprocal association between bullying and loneliness would require repeated measures of both constructs using consistent measures.

It was not possible to examine physical abuse and sexual abuse separately in childhood, due to small group sizes for sexual abuse (minor: N = 17; severe: N = 16). The issue of power also applies to discordant twin analyses, as the level of discordance within twin pairs, particularly for childhood victimisation, is low (Jaffee, 2017). For example, there were no MZ pairs in this sample who were discordant for severe childhood physical neglect (Supplementary Table S2). In the case of adolescent victimisation, there was greater discordance for most forms of victimisation (Supplementary Table S3). Nonetheless, the halving of sample size when restricting analyses only to MZ twins has further implications for the precision of model estimates (Boardman & Fletcher, 2015).

The internal consistency of the childhood loneliness measure was modest. One potential explanation for this is that loneliness is a multidimensional construct (Hawkley, Browne & Cacioppo, 2005), and each of the items maps onto a specific manifestation of loneliness: lack of friends, not being loved, and the internal state of feeling ‘alone’. The three would not always co-occur within the same individual, as they apply to different domains of life (e.g. school and peer group versus home and family). Nonetheless, each one fits conceptually to the definition of loneliness as a perception that one’s relationships with others are deficient in some way.

By definition, all participants in this sample had a sibling of the same age and sex (and, in more than half of cases, the same genome). The extent to which this could be protective against loneliness is not clear. Conversely, there may be unique aspects of being a twin that could contribute to loneliness, such as being treated as a pair rather than as individuals with separate identities, or being left out by peers due to an assumption that twins can rely on each other for company. The experience of loneliness may therefore be different in some respects for twins compared to singletons or non-twin sibling pairs. However, the number of individuals in this sample who reported feelings of loneliness ‘some of the time’ or ‘often’ at age 18 are in line with those found in other studies of adolescents and young adults in the UK general population (Office for National Statistics, 2018).

Implications

While these data do not support a causal effect of childhood bullying on loneliness that endures into the adult years, this does not mean that victims should be considered ‘out of the woods’ if the bullying ceases. To the contrary, if being a victim of bullying partially reflects a genetic vulnerability to loneliness, an implication of this is that victims remain at risk of becoming lonely later in life even if they are no longer being victimised. Early adulthood is a peak age for loneliness (Luhmann & Hawkley, 2016), and individuals with a history of bullying victimisation in childhood may require particular support during the transition from adolescence to adult life. Moreover, bullying should remain a concern for long-term outcomes more generally, as it has been shown to predict mental health and psychosocial problems well into mid-life (Takizawa, Maughan & Arseneault, 2014). The findings of the present study do not detract from the importance of interventions to reduce bullying and support victims in order to prevent adverse outcomes later in life.

Additionally, the findings highlight that abuse and neglect, though extensively studied as childhood risk factors, could have particular implications for loneliness when they are experienced in adolescence rather than in childhood. Even though adolescents increasingly spend more time outside of the family home, thereby exposing them to a more diverse range of environmental risks, victimisation within the family home appears to be particularly important for loneliness at this stage of life. Conversely, while peer victimisation has strong implications for mental health in adolescence (Troop-Gordon, 2017), it appears to be most relevant to loneliness when experienced in childhood. This highlights that the experience of loneliness, and its antecedents, are dynamic across development (Qualter et al, 2015), and that strategies to support victimised and lonely individuals should reflect this.