“I get by with a little help from my friends”: Adolescent peer friendship networks and self-harm

By Holly Crudgington.

What do you think of when you hear the word ‘school’? The word might have many connotations, depending on who you ask. Context matters. Personally, it brings back some fond and some difficult memories of being a teenager at a public secondary school in the UK.

It’s been over 10 years since I was at secondary school, but I still remember vividly how it felt to be part of a peer group and the influence this had on my behaviour and wellbeing. I was very attuned to how peer-friendships developed, and I worried about what my peers thought of me and where I fitted within the school. Cliques of peers formed friendships based on similar interests (e.g., music taste) and attributes (e.g., gender), and there was a hierarchy of popular people. I’m lucky to have a twin sister, and having a sister be part of the same peer group at school made it an easier environment to adapt to. However, the peer-friendships I developed also played a huge part in how I learnt to cope and deal with emotions entering older adolescence and adulthood.  

Adolescence can be a turbulent time of behavioural, emotional, and social development. Evidence suggests that many adult mental health problems first emerge before the age of 25 [1] and self-harm (an umbrella term that refers to intentional self-poisoning or self-injury, irrespective of suicidal intent) is a considerable public health challenge in young people [2,3]. Prevalence estimates suggest that 16-18% of adolescents have self-harmed at least once in their lifetime, although estimates vary depending on the definition of self-harm used and the sample [4-6]. Given that self-harm peaks in adolescence, a time when social interactions with peers are salient, could peer-friendship networks play a role in its development and maintenance?

The social influence of peers during adolescence is pivotal. Peers can affect adolescent health behaviour such as substance use, sexual behaviour, risk-taking and suicidal behaviour [7-10]. A key risk factor for the transition between suicidal thinking and attempts in young people is being exposed to self-harm among friends [11]. Likewise, adolescents who engage in self-harm are more likely to have friends who self-harm and self-harm by best friends and the wider friendship group can predict subsequent self-harm in young people [12].

Social networks may also facilitate the transmission of behaviour. Behaviours have the potential to be ‘contagious’ and transmit through a network via socialisation (i.e., an individual is influenced by others), selection (i.e., individuals choose to befriend peers like them), or both. For example, there is evidence that a peers’ behaviour (e.g., smoking) predicts changes in similar peers’ behaviour over time (e.g., similar peers start to smoke), known as ‘direct socialisation’. It is called ‘direct’ because a friends’ behaviour is predictive of a young persons’ engagement in the same behaviour. However, for self-harm, it may be more complex. One of the only longitudinal studies to examine socialisation of self-harm found that self-harming behaviour can transmit through a social network via ‘indirect socialisation’ in adolescent high school networks [13]. The study found that friends depressive symptoms predicted changes in girls’ and boys’ self-harm over time, and impulsivity predicted changes in boys’ self-harm [13]. This is ‘indirect socialisation’ because a friends’ behaviour may have influenced a related behaviour in a young person. 

It is increasingly being recognised that social determinants, like your social circle, are key determinants of health and behaviour. However, within the UK, not much is known about the characteristics or structures of peer friendship networks of adolescents that self-harm, and if and how self-harm might be socialised through peer-friendships networks.

My PhD research

I am a first-year PhD student at the Centre for Society and Mental Health (CSMH), at King’s College London. I’m funded by the Economic and Social Research Council (ESRC) and part of the London Interdisciplinary Social Science Doctoral Training Partnership (LISS-DTP). My PhD project is focussed on adolescent self-harm and the influence of gender and peer-friendship networks.

I will use data from the Risk, Resilience, Ethnicity, and Adolescent Mental Health (REACH) study. REACH is an accelerated cohort study of around 4000 adolescents from 12 mainstream secondary schools in two ethnically and socially diverse inner-London boroughs. At baseline, three school-based cohorts have been constructed: school year 7 (ages 11-12), school year 8 (ages 12-13), and school year 9 (ages 13-14). Each cohort has been followed at one- and two-year time intervals which covers five years in two years (school years 7-11). Pupils at the schools have been completing self-reported measures on mental health, risk, and protective factors, including questions about self-harm. Within REACH, sample weights were added to the data and the weights are calculated using 2016/2017 data from the National Pupil Database. ‘Weighting’ is essentially a way of addressing bias for sample selection and to make the data more reflective of the target population. Sample weights made little difference to the estimates within REACH as the cohorts are highly representative of the target population and there were high participation rates.

Recent findings from REACH highlight that the weighted prevalence of mental health problems for the adolescents at baseline was 18.6%, and mental health problems were more common among girls compared with boys [14]. 18.6% is higher than the national average in England (14%) [15] and suggests adolescent mental health problems are common in inner-city London. Among girls (vs boys), the risk of self-harm was around 40% higher.

Across each time point, adolescents within REACH have nominated up to five friends within their year group at their respective school. By linking these nominations together, we obtain separate peer-friendship networks for each year group at each school. In a friendship network, a ‘node’ is the individual pupil (or participant) and an ‘edge’ is the relational tie that is analysed between two (or more) nodes that can be directed (e.g., I nominate you as a friend, but that person might not necessarily nominate me – Figure 1). Data of this kind lends itself to Social Network Analysis (SNA), something I intend to use in my PhD.

Figure 1. A directed graph with 6 nodes. A blue circle represents an individual pupil within a school (node). An arrow (edge) represents a directed friendship nomination e.g., indicating who nominated who as a friend.

SNA is a method that can investigate social structures and patterns of relations among people using networks and graph theory [16]. With the REACH network data, there is so much to explore. For example, we can look at group-level features such as how cohesive/dense a network is as well as individual-level features such as how central a node is within a group, or who is the most popular node, and how this might relate to self-harm. Using the longitudinal network data, it may be possible to explore if self-harm can transmit through a network overtime via socialisation (i.e., an individual is influenced by others), selection (i.e., individuals choose to befriend peers like them), or both.

SNA is an interesting methodology, that I look forward to learning more about. I think the method can provide a unique insight into adolescent self-harm and the influence of peer-friendship networks. However, a crucial element of REACH is its localised approach to mental health, in that it focuses on two inner south London boroughs. It will be important to keep this context in mind when analysing the data and utilising the voices and expertise of the REACH young people when interpreting the results. Context matters.

If you are interested in learning more about the REACH study, or the Centre for Society and Mental Health, use the links below:


  1. Kim-Cohen, J., Caspi, A., Moffitt, T. E., Harrington, H., Milne, B. J., & Poulton, R. (2003). Prior juvenile diagnoses in adults with mental disorder: developmental follow-back of a prospective-longitudinal cohort. Archives of general psychiatry, 60(7), 709-717. (link)
  2. Carroll, R., Metcalfe, C., & Gunnell, D. (2014). Hospital presenting self-harm and risk of fatal and non-fatal repetition: systematic review and meta-analysis. PloS one, 9(2), e89944. (link)
  3. Patton, G. C., Coffey, C., Sawyer, S. M., Viner, R. M., Haller, D. M., Bose, K., … & Mathers, C. D. (2009). Global patterns of mortality in young people: a systematic analysis of population health data. The lancet, 374(9693), 881-892. (link)
  4. Madge, N., Hewitt, A., Hawton, K., Wilde, E. J. D., Corcoran, P., Fekete, S., … & Ystgaard, M. (2008). Deliberate self‐harm within an international community sample of young people: comparative findings from the Child & Adolescent Self‐harm in Europe (CASE) Study. Journal of child Psychology and Psychiatry, 49(6), 667-677. (link)
  5. Klonsky ED, Victor SE, Saffer BY. (2014). Nonsuicidal Self-Injury: What We Know, and What We Need to Know. Canadian Journal of Psychiatry. 59:565–8.  (link)
  6. Muehlenkamp, J. J., Claes, L., Havertape, L., & Plener, P. L. (2012). International prevalence of adolescent non-suicidal self-injury and deliberate self-harm. Child and adolescent psychiatry and mental health, 6(1), 1-9. (link)
  7. Jarvi, S., Jackson, B., Swenson, L., & Crawford, H. (2013). The impact of social contagion on non-suicidal self-injury: A review of the literature. Archives of Suicide Research, 17(1), 1-19. (link)
  8. Potard, C., Courtois, R., & Rusch, E. (2008). The influence of peers on risky sexual behaviour during adolescence. The European Journal of Contraception & Reproductive Health Care, 13(3), 264-270. (link)
  9. Leung, R. K., Toumbourou, J. W., & Hemphill, S. A. (2014). The effect of peer influence and selection processes on adolescent alcohol use: a systematic review of longitudinal studies. Health psychology review, 8(4), 426-457. (link)
  10. Blakemore, S. J. (2018). Avoiding social risk in adolescence. Current directions in psychological science, 27(2), 116-122. (link)
  11. Mars, B., Heron, J., Klonsky, E. D., Moran, P., O’Connor, R. C., Tilling, K., … & Gunnell, D. (2019). What distinguishes adolescents with suicidal thoughts from those who have attempted suicide? A population‐based birth cohort study. Journal of child psychology and psychiatry, 60(1), 91-99. (link)
  12. You, J., Lin, M. P., Fu, K., & Leung, F. (2013). The best friend and friendship group influence on adolescent nonsuicidal self-injury. Journal of Abnormal Child Psychology, 41(6), 993-1004. (link)
  13. Giletta M, Burk WJ, Scholte RHJ, Engels RCME, Prinstein MJ. Direct and Indirect Peer Socialization of Adolescent Nonsuicidal Self-Injury. J Res Adolesc. 2013;23:450–63. (link)
  14. Knowles, G., Gayer-Anderson, C., Beards, S., Blakey, R., Davis, S., Lowis, K., … & Schools Working Group. (2021). Mental distress among young people in inner cities: the Resilience, Ethnicity and AdolesCent Mental Health (REACH) study. J Epidemiol Community Health, 75(6), 515-522. (link)
  15. Sadler, K., Vizard, T., Ford, T., Marchesell, F., Pearce, N., Mandalia, D., … & McManus, S. (2018). Mental health of children and young people in England, 2017. NHS Digital: Office for National Statistics.
  16. Wasserman, S., & Faust, K. (1994). Social Network Analysis: Methods and Applications (Structural Analysis in the Social Sciences). Cambridge: Cambridge University Press.

Holly Crudgington (@hollycrudge) is a PhD student at the Centre for Society and Mental Health, (@kcsamh) King’s College London. Email: