Qualitative findings
Seventeen young women between 18-25 years old were interviewed. [Table 1].
![](data:image/png;base64,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)
Survey information on socioeconomic classification was not taken
All participants, except one, had experienced IPVA in at least one relationship. None were currently in an abusive relationship. Just over half (13/17) had experienced DVA in their family of origin and the same proportion (13/17) had experienced both DV in their family of origin and IPVA. All 17 young people had experienced at least one type of maltreatment prior to their abusive intimate relationship. Maltreatment included: experiencing domestic violence and abuse within the family (physical, sexual, emotional, controlling, financial), being aware of DV within the family, sexual abuse or grooming by adults (not parents) or peers, neglect by family, or severe bullying by peers. More than half of the participants were recruited through frontline services and had a long and complex history of negative life events and had attempted help-seeking over the life course and prior to their IPVA.
For brevity in this article all forms of abuse and victimisation that is not IPVA will be defined under the umbrella term ‘maltreatment’.
The interview data showed that most participants had experienced multiple forms of victimization. The majority of participants’ accounts were dominated by narratives of not being heard or believed when they attempted to talk about their experiences of maltreatment or home-life and how negative labelling and disbelief by family, peers, community and society caused intense feelings of loneliness and isolation. Feeling lonely and isolated led to more vulnerability to further maltreatment, including abusive intimate relationships. Participants accounts also showed ways to ameliorate the impact of loneliness and support their wellbeing. Building on these findings two main themes were developed from the data: 1) Isolation and Loneliness with the subtheme of being Silenced through Labelling; and Disbelief and 2) Ways out of Loneliness: Finding a Voice with subthemes of Grandmother; Finding Good Friends and Taking Control; and Education and Achievement.
The first section will describe findings on how help-seeking was responded to at all ecological levels by participants family, peers, community and society; and how it impacted on the participants’, well-being, identity and consequent help-seeking behaviours. The second section gives findings on what helped alleviate the impact at the different ecological levels. The findings can most easily be visualised as a loop as shown in Figure I (Figure I: Loop of Loneliness).
Relationship Level (family, partner)
Loneliness can be a possible consequence of the shame young people exposed to childhood violence often feel, which can then increase the risk of poor mental and physical health 41. Feeling alone, loneliness, isolated or an outsider was mentioned by all but one of the participants across the range of socio-economic groups and backgrounds. The young women who had been multi-victimised had usually experienced early years maltreatment. As a result, loneliness often started in the earliest years due to family abuse, neglect and witnessing DVA. Similarly, those who had come from the most disadvantaged backgrounds, where family addictions and mental illness were common, were also more likely to mention feeling lonely from a young age. However, being able to name the feeling they had when they were young was not always easy for young women, and expressions of loneliness were implicit as well as explicit:
I was quiet, I was timid and I was like wanting to please my parents, please everyone around me…I think when it happens like that especially when you’ve been in a hard… when you feel unwanted as a child (Maya 19)
Being Silenced through Labelling
Most of the young women in the current study described being negatively labelled throughout their lives and the consequences this had on their help-seeking behaviour. For example, young women commonly described how trying to tell others in the family about their abuse was met with disbelief and subsequently being identified as somehow ‘wrong’ within the family and their truth discredited. Labelling theory is concerned with the self-fulfilling effects of labelling and who it is that bestows the labelling - the social process by which the labelling is applied and its effect 42. Consequently, the labels the family applied to the young women effectively blocked any further attempts at disclosure:
Sometimes [I talked to] my brother but that was hard because sometimes he'd use it against me…Saying that I lied. That I’m a liar and I lied about it. (Maya 19).
Being labelled as ‘the black sheep’ in her family impacted on Lorraine’s help-seeking: ‘It’s like if my own family don’t believe me and they know me better than anyone else, why would anyone else believe me?’
Outside of the family, Ellie described her perpetrator using labelling to take charge of the narrative around assault, effectively de-railing her help-seeking and leaving her more isolated:
he [man who sexually assaulted her when she was aged 12/13] basically told his girlfriend that he’d cheated on her with me doing what he did and then I came out of this a homewrecker so then I couldn’t tell people what had actually happened, I didn’t really tell anyone. (Ellie 25)
Being silenced through negative labelling at a young age reinforced the feelings of loneliness and isolation. A social process that continued at the next ecological level.
Relationship and Community Level Response (Peers, Teachers, Schools, Church)
Outside of the home, the most important community level contact was schools. Participants often described acting out their distress or trauma from maltreatment, alongside more actively seeking help, whilst in school.
As reported in the literature 43,44 teachers can be an important source of help and validation. However, most participants’ accounts of school responses to their behaviour were negative. Being negatively labelled within school was an interactional process creating a negative feedback loop; young women were labelled as ‘bad’ by peers, which was then reinforced by teachers (or the other way around) causing more ‘bad behaviour’. Participants described being bullied by peers and punished by the institution until the ‘bad’ label became a self-fulfilling prophecy.
I didn’t drop out, I got booted out…Basically, I had issues with being bullied, because of who my parents were and what they’ve done… you know, “Your mum didn’t want you, you're a smack baby,” the usual. Which then progressed into my hair being cut, my blazer being set alight, whilst I was wearing it. (Gemma 21)
The experience of being silenced through labelling happened more and to greater extremes for participants with disabilities, those from ethnic minority or socioeconomically disadvantaged backgrounds, or who were neurodiverse. Intersectionality compounded the experiences of being labelled. Jackie clearly understood in retrospect the negative feedback loop in respect of institutional expectations around her educational abilities. At the time she felt highly visible, labelled and at the same time unheard because of her ethnicity, physical and learning disabilities:
Being a black girl in an all-white school with disabilities, I had all the hallmarks to being bullied... It was blatant. If someone is calling you the ‘N’ word in the middle of the playground…the teachers said nothing. The teachers thought because I was in a lower grade at school that I would fail school. Which I did fail school because nobody was there to support me. (Jackie 25)
Eleanor’s neurodiversity was mislabelled at primary school:
The only thing that carried me through was in primary school I’d been taken out of my year for a year because my head teacher said I was retarded. Yes, and I had to have one-to-one lessons to learn to read, write, do maths. What happened is I went from a retard…[to top of the class] (Eleanor 19)
Within school, some participants were referred to the school counsellor due to their acting out distress - labelled as behavioural problems. However, all accounts of school counselling services were negative. Ellie remembered her experiences being nullified, ‘I told her about being sexually abused when I was 12, she told me that that was just boys experimenting and exploring’. Again, this response effectively silences the participant through invalidating their experiences of abuse and trauma.
Being silenced through denial was a persistent theme in our data. Participants’ school and peer level responses to their signs of trauma led to more loneliness. The feeling of being outcast or stigmatised by peers and teachers was clearly articulated by participants. Nina described the vicious circle of behaviour and response, culminating in entrenched isolation:
I was bruised, I was scratched, bitten, everything, fag butts [by abuser], that’s the reason why I did not take my clothes off in school. All the other girls did. I was standing there going, “Oh my God, it must only be me then.” Then you feel even more outcast and the school don’t want to be involved with you, and the kids don’t really want to be involved with you, because you’re different. Then, you’re isolated again there, where you’re not supposed to be.
Feelings of isolation and loneliness were also due to the responses participants had received when they tried to seek help from services. Participants from the more advantaged backgrounds had less multi-victimisation and their accounts of loneliness and outsider feelings tended to be linked to mental health problems. This was exacerbated due to their mental health problems being denied by professionals, including school counsellors, but especially when peers invalidated mental ill health experiences:
It did really, really, hurt to not be believed [about aural and visual hallucinations] . It really, really, did, but I just ended up becoming a bit more solitary after that. (Nive 24)
However, those who had felt most isolated tended to be from more disadvantaged backgrounds, often these feelings of being alone had carried on into adulthood, sometimes with a strong sense of self-reliance learned through adversity. When asked if she had received any good support in her life, Gemma responded: ‘Not really. They all seem to fade away… I learnt to not rely on anybody but yourself ‘
Community Level Response (Children’s Social Care, Police, Health Services)
The young women who had been recruited through frontline support organisations were more likely to have had early contact with social services. Descriptions of contact with social workers tended to be negative and the services provided were felt to be inconsistent. As found in previous research 45,46 young people had often not felt heard or that their needs and wishes had been taken in to account. However, individual social workers were appreciated if they helped out the wider family.
Police were often involved with families when DVA and other maltreatment was present. Again, individual officers were praised. However, the police response generally reflected the accepted knowledge of the time, that only physical violence counted as abuse, as Leah described:
Mum had to keep going to the police [about abusive ex-husband] The police did absolutely fuck all. They basically said, ‘until he physically hurts somebody, we're not doing anything’. So, you just felt like, "Well, what are you meant to do?" There's literally no one to help (Leah 24)
The sense of isolation and loneliness was increased when there was misalignment of services. Young women offered group therapy for their maltreatment described situations where the treatments left them confused:
At CAMHS [Child and Adolescent Mental Health Services] The whole family went to that, so a lot of shouting. It didn't help much. I didn't really know what the place was for. I was a troubled girl. (Soraya 22)
Cumulative Loneliness (life-course aspect of ecological model
When reflecting on their lives and making connections between past experiences and their own experiences of being with an abusive partner, participants linked entrenched feelings of loneliness with how easy it had been to end up in an abusive relationship:
when I went home to my mum [from care], I got into a relationship with Jaeden quite quickly, who is my daughter's dad. I still didn't know where my head was with things, really, and felt a lot of loneliness. I was trying to find a place of belonging, I guess, and I jumped into my relationship quite quickly, and then fell pregnant. (Soraya 22)
Participants identified how loneliness had increased their vulnerability to further abuse and victimisation:
the whole [grooming] stuff I think was, again, being lonely. Because, obviously, I got back with ex time, and time, and time, and time, again for the fact of being lonely. And then I got in with [older girls, grooming] because I thought, “Friends,” like. (Nicky 19)
Ways out of Loneliness: Finding a Voice
Indications as to the positive factors or turning points in their lives were given in the young peoples’ descriptions surrounding ways out of being silenced and loneliness, primarily through being properly seen, heard and supported.
Relationship Level
Where ‘Nan’ could often be an important figure, a loving, consistent and – above all – safe person and place within difficult childhoods:
my nan was my universe, so I lived with my nan… And I felt safe, for some years I felt really safe. (Nina 23)
My Nan was like my guardian angel, and she’d be there for me, no matter what… before she got unwell, she didn’t like the first stepdad at all. I would always go to my Nan and talk to her about it and she believed me (Bec 22)
These findings align with evidence that having just one loving and consistent relationship with an adult can have a buffering effect on young people who have been maltreated 21,47. For the above young women, the grandparent was described as on their side and able to see the maltreatment within the family. Whilst all of these ‘nans’ had died when the participants were teenagers, a bereavement still felt keenly, their importance in providing a corrective foundation in chaotic lives was clear.
- Finding Good Friends and Taking Control
For those with friendships, the most helpful were considered the ones where there was open communication and full support when needed, especially in a crisis.
Escaping the home and school situation to further education and real, empathetic friends who truly heard worked as a revelation:
it was the first time that somebody had taken me feeling… by the way I felt. Like it was a real problem. It's just because I had never had genuine friends like that.. I met people at uni and within a year, I was able to tell them so much stuff that I could never have told, or had never told, anyone else. (Leah 24)
Having just one friend who came from a similar background and/or shared a similar experience can make a substantial difference:
There’s one friend that has stuck through me, through in and out, and that’s X. She’d give the world for my kids, same as I would hers. (Gemma 21)
Church had been a source of friendship and support outside of her dysfunctional family for Chloe:
[I was] a bit lost. But I had my church friends. I never really felt a part of my family. I always felt different and detached from them. It was like watching someone else's home life, rather than mine, if that makes sense. I always used to wish that I was going to grow up and find out I was adopted, but that's not going to happen.
Simply getting older and having more control over their lives, including financially, buffered the effects of early maltreatment. Leah had taken her experiences in her family and used them to achieve the independent life she wanted:
I think I just had this absolute, utter determination to get myself the life I wanted. A good job, enough money that I would never be in a position where a man could hold my money.
Over the life-course, with age and experience, participants described accepting and even welcoming what had once been stigmatising and isolating, for example:
I was just always made to feel like an outsider, like something was always a bit weird about me. Which I still get, from people, now, but I embrace it now. (Lily 22)
At the cultural level, changing perceptions of mental illness and identity politics in the last decade are likely to be reflected in how participants’ talk about themselves.
Community Level
Education has the potential to be an extremely positive factor in ameliorating the impact of DV and abuse in the home – both at the time and investing in the futures of vulnerable children and adolescents:
My little like safe haven- you know, wondering what the hell was going on at home. I came out with seven ‘A’s and nothing below a B. So, it worked, I suppose. (Laughter) (Lorraine 22)
A combination of academic achievement and good foster care had enabled Chloe to begin to fulfil her potential:
school was alright, actually. I was a straight-A student. I excelled really well, academically. [when I went into foster care] I wasn't that smelly little girl in the corner, wearing the same clothes every day. So it got better. But then I just threw myself into my studies, so I didn't really care
Achievements that may seem minor to others can and do have an impact on participants feelings of self-worth and ability to envisage another future. Tutors who are prepared to put in the extra effort and support for young people who have been labelled ‘difficult’ are extremely important in this future. This was particularly true for those from disadvantaged backgrounds, such as Gemma:
I’ve fought tooth and nail to be able to get onto my child-minding course. But I was told repeatedly four times over the space of two years because of my past and trouble I’ve been in as a child I wouldn’t be able to work with kids. So I was slowly dropping out of college, but luckily enough I managed to scrape through by the skin of my teeth because my tutor understood me, she understood my point. She helped me go through the assessment for my learning disabilities that the other schools hadn’t listened to.
Teachers hold a unique position to be a consistent, observant and supportive adult outside of the family unit. Participants described responding positively to being seen and heard by teachers and trust was very important in the teacher/pupil relationship where trust within the family and elsewhere had been broken; in Chloe’s case she had felt able to disclose about the neglect and abuse in her home due to addictions, and being raped by her half-brother, ‘my tutor was amazing. She was the one that I told…She was just really nice. She was so sweet’
Finally, there were descriptions of positive police responses to help seeking behaviour, of being heard and taken seriously, such as Chloe’s, ‘the police got involved, and that's when they actually started- "Right, we need to start paying attention to what she's saying, rather than a young girl lashing out’. (Chloe 23)
Positive descriptions of interactions with the police increased over the life-course of the participants’ accounts, which was likely the result of changing police policy around domestic abuse, reflecting the shifting societal/cultural knowledge influenced by activism, research and journalism within the sector.
Quantitative findings
2127 women and 1145 men were included in our analysis. Characteristics of these participants, and how they compare with the original ALSPAC cohort are described in Supplementary Table 1. Study cohort members were less likely than those of the full ALSPAC cohort to have mothers who had already borne children, who had a degree, or be in high social class positions (based on highest social class of the mother and father); they were also less likely to be part of single parent households, or be a Person of Colour, but were more likely to report not being 100% heterosexual. For all of the above variables, they were less likely to have missing data.
Child maltreatment was associated with a 2-fold higher chance of both female and male 14 year-olds reporting that school was a place they felt lonely (OR for women: 2.06, 95% CI 1.37 to 3.11; OR for men 2.36, 95% CI 1.16 to 4.80) (Table 2). In males, there was also an association between child maltreatment and loneliness within peer group (feeling that your friends did not understand you, at age 13); OR 3.35, 95% CI 1.40 to 8.00. This association was not seen in females. In females, there was weak evidence of an association between child maltreatment and overall loneliness in the past two weeks at age 13 (OR 1.67, 95% CI 0.96 to 2.93); this association was not seen in males. Adjustment for covariates did not alter these associations.
Child maltreatment was associated with an increased risk of IPVA in both females and males (Table 3). Loneliness at school at age 14 was associated with IPVA in females (OR 1.63, 95% CI 1.13 to 2.35) and males (OR 1.84, 95% CI 0.92 to 3.71). ORs for the associations of loneliness within peer group and overall in the past two weeks with IPVA were positive for females, but with very wide confidence intervals, but there was no evidence of associations between these measures of loneliness and higher risk of IPVA in males.
There was some evidence that loneliness at school mediated a small proportion of the association between child maltreatment and IPVA in females and males (shown by the direct effects being smaller than the total effects in Table 4), but the direct effect was still very similar to the total effect (e.g. 1.60 for the total effect, 1.56 after accounting for loneliness at school at age 14), suggesting the vast majority of the association between child maltreatment and IPVA is not mediated through loneliness at school. For the other measures of loneliness, total and direct effects were very similar, suggesting these are not important mediators of the association between child maltreatment and IPVA.
Table 2
Associations between child maltreatment and loneliness during adolescence. N=2127 females and 1145 males, using imputed data
|
Odds ratio for the association between child maltreatment and loneliness during adolescence (95% confidence interval)
|
|
Females
|
Males
|
|
Loneliness at school at age 14
|
Loneliness within peer group at age 13
|
Overall loneliness at age 13
|
Loneliness at school at age 14
|
Loneliness within peer group at age 13
|
Overall loneliness at age 13
|
Maltreatment* between 0-12 years (unadjusted)
|
2.06 (1.37 to 3.11)
P=0.001
|
0.95 (0.46 to 1.96)
P=0.88
|
1.67 (0.96 to 2.93)
P=0.07
|
2.36 (1.16 to 4.80)
P=0.02
|
3.35 (1.40 to 8.00)
P=0.007
|
1.56 (0.68 to 3.56)
P=0.29
|
Maltreatment* between 0-12 years (adjusted**)
|
2.25 (1.48 to 3.41)
P<0.001
|
0.91 (0.44 to 1.90)
P=0.81
|
1.64 (0.93 to 2.90)
P=0.09
|
2.40 (1.17 to 4.93)
P=0.02
|
3.74 (1.16 to 8.98)
P=0.003
|
1.44 (0.63 to 3.31)
P=0.39
|
*Maltreatment = emotional abuse, emotional neglect, physical abuse, sexual abuse, domestic violence (violence between ‘parents’), bullying
**Adjusted models include the following covariates for females: maternal age at delivery, maternal parity at delivery, maternal education, whether the child lives in a single parent household. For males, the same set of covariates was used apart from single parent household, which could not be included due to perfect prediction in one or more of the imputed datasets
Table 3
Associations of maltreatment and loneliness with IPVA (2127 females, 1145 males, imputed data)
|
Odds ratio for the association of child maltreatment or loneliness in adolescence with IPVA in young adult relationships between 18-21 years old (95% confidence interval)
|
|
Females (unadjusted)
|
Females (adjusted**)
|
Males (unadjusted**)
|
Males (adjusted**)
|
Child maltreatment* 0-12 years
|
1.29 (1.03 to 1.60)
P=0.02
|
1.28 (1.02 to 1.59)
P=0.03
|
1.39 (1.02 to 1.90)
P=0.04
|
1.38 (1.01 to 1.90)
P=0.05
|
|
|
|
|
|
Loneliness at school at age 14
|
1.63 (1.13 to 2.35)
P=0.01
|
1.65 (1.14 to 2.38)
P=0.01
|
1.85(0.92 to 3.71)
P=0.08
|
1.76 (0.87 to 3.55)
P=0.11
|
Loneliness within peer group at age 13
|
1.43 (0.70 to 2.93)
P=0.32
|
1.42 (0.69 to 2.91)
P=0.34
|
0.81 (0.33 to 1.97)
P=0.64
|
0.83 (0.34 to 2.02)
P=0.68
|
Overall loneliness at age 13
|
1.39 (0.83 to 2.31)
P=0.21
|
1.40 (0.83 to 2.34)
P=0.20
|
1.08 (0.44 to 2.62)
P=0.87
|
1.03 (0.42 to 2.52)
P=0.96
|
*Maltreatment = emotional abuse, emotional neglect, physical abuse, sexual abuse, domestic violence (violence between ‘parents’), bullying
**Adjusted models include the following covariates for females: maternal age at delivery, maternal parity at delivery, maternal education, whether the child lives in a single parent household. For males, the same set of covariates was used apart from single parent household, which could not be included due to perfect prediction in one or more of the imputed datasets
Table 4
Mediation of association between maltreatment and IPVA, by loneliness (2127 females, 1145 males, imputed data*)
|
Odds ratio for the association of child maltreatment with IPVA in young adult relationships between 18-21 years old; before (total effect) and after (direct effects) accounting for mediation by loneliness (95% confidence interval)
|
|
Females (adjusted***)
|
Males (adjusted***)
|
Total effect of child maltreatment** on IPVA
|
1.60 (1.29 to 2.00)
P=0.02
|
1.90 (1.39 to 2.60)
P=0.04
|
Direct effects; i.e. the association between child maltreatment* and IPVA after accounting for****:
|
|
|
Loneliness at school at age 14
|
1.56 (1.25 to 1.94)
P=0.04
|
1.87 (1.36 to 2.56)
P=0.05
|
Loneliness within peer group at age 13
|
1.26 (1.05 to 1.52)
P=0.02
|
1.93 (1.41 to 2.65)
P=0.03
|
Overall loneliness at age 13
|
1.60 (1.27 to 1.99)
P=0.03
|
1.91 (1.40 to 2.61)
P=0.04
|
All three loneliness measures
|
1.57 (1.26 to 1.96)
P=0.04
|
1.89 (1.37 to 2.59)
P=0.05
|
*Pooled beta coefficients and standard errors were derived across imputed datasets using Rubin’s rules. Mean p-values across the imputed datasets are reported.
**Maltreatment = emotional abuse, emotional neglect, physical abuse, sexual abuse, domestic violence (violence between ‘parents’), bullying
*** Adjusted models include the following covariates for females: maternal age at delivery, maternal parity at delivery, maternal education, whether the child lives in a single parent household. For males, the same set of covariates was used apart from single parent household, which could not be included due to perfect prediction in one or more of the imputed datasets
****The ‘natural direct effect’.