1. Long-term continuity in antisocial behaviour and associated mental health problems—conferring resilience to high-risk individuals
Dr Maria M. Ttofi
Friday, July 5, 2019
Epanodos Conference, Athens

2. Structure of the Presentation
Long-term continuity in antisocial behaviour
Confounded relationship? Causal inferences?
Policy implications?
Accumulation of adverse childhood experiences: Links with mental health and offending
Additive effects
What does this mean?
Practical issues relating to risk assessment?
Protective factors interrupting the continuity from youth aggression to adult crime

3. Antisocial behaviour and crime is expensive
Data from the UK
Cumulative costs of public services used through to adulthood (≈28) by 10-year olds with varying levels of antisocial behaviour (Scott et al., 2001)
11.000’ 30,00; 105,000

4. Multi-Problem Children
ODD
Drug use
Bullying
“… one of the principal challenges of a risk-focused approach is that it resulted in the proliferation of separate problem-specific programs, funded by independent agencies supporting work in each risk area, and disseminated through different publication venues …. rather than emphasizing the identification of shared risk, protective, and promotive factors” (Guerra & Bradshaw, 2008)

5. PART A:
Continuity in Antisocial Behaviour: Co-current and long-term effects of school bullying

6. Part of normal development?
Or does it have detrimental effects?

7. Indications from previous research…
Short-term effects:
depressive symptomatology (Bosworth et al, 1999; Van der Wal et al, 2003)
increased risk for suicidal ideation and self-injurious behaviour (Kaltiala-Heino et al, 1999)
eating disorders (Kaltiala-Heino et al, 2000)
Long-term effects:
later offending (Farrington, 1993; Sourander et al, 2006; Losel, 2008)
bullied children: difficulties in trust/intimacy in opposite-sex and friendly relationships in adulthood (Gilmartin, 1987; Dietz, 1994)

8. Systematic Review Extensive searches in 19 electronic databases
63 relevant journals
‘grey literature’ (ETHOS, ProQuest)
Screening and coding of 661 reports
ed the principal investigators of a large number of prospective longitudinal studies (received results from 24 separate research teams)

9. Instructions to Lead Investigators of Longitudinal Studies:
The strength of the relationship between bullying and later outcomes
The strength of this relationship after controlling for earlier risk factors (not a confounded relationship)
Particular strength
We contacted investigators of major longitudinal surveys
Highlighted that all findings are important irrespective of statistical significance

10. Meta-analysis
Meta-analysis: bring together and ‘re-analyse’ data from existing studies
Helps researchers avoid a ‘vote-counting’ approach
Effect size = measure of association between two variables

11. Measure of Effect Size (Odds Ratio)
OR = 3 => Bullies are 3 time more likely to have committed crime in adult life

12. (4 meta-analyses: Ttofi et al., 2011a; 2012; 2016; 2011b)

13. Note: statistically significant difference for victims and bully-victims only
Valdebenito, Ttofi, Eisner, 2017 meta-analysis (35 studies)

15. Policy Implications
Bullies and victims are more likely to face adverse problems in adult life
These children face multiple adverse childhood experiences
Long-term continuity: mechanisms set in motion?
How can we interrupt this continuity from bullying to later adverse outcomes?
Need to intervene early and support all children involved
Implementation of effective anti-bullying and other early prevention/mental health programmes

16. PART B:
Additive effects of multiple adverse childhood experiences (ACE): Results from the Cambridge Study in Delinquent Development

17. ACEs and Offending (Craig, Piquero, Farrington, Ttofi 2017)
ACEs: Prevalence
ACEs and Offending

18. Managing ACEs ACEs important and should be addressed early in life
which are ‘more important’?
Practical issues relating to risk assessment
Always additive effects?
What ‘combination’ of ACEs and from which domains most predictive?
Vulnerability and resilience? Interaction between risk and protective factors

19. Reising, Ttofi, Farrington, Piquero (2019)

20. Mental Health and Crime
Jolliffe et al. (2017) systematic review of offending trajectories
55 longitudinal studies; 14 analysed data based on offending trajectories
Individuals in different trajectories differ in ‘degree’ of risk rather than ‘kind’ of risk
Additive effects of risk factors
Above results may explain varied levels of mental health in our meta-analytic review
‘Simplistic model’: varied antecedents of depression
Developing partnerships across domains to address increased ACEs

21. Protective factors against youth aggression and adult crime
Part C:
Protective factors against youth aggression and adult crime
Vulnerable
Invincible

22. IQ as a protective factor against offending
cohort
No parental incarceration
Attribute Absent (Low IQ)
Higher Proportion of Offenders
Attribute Present (High IQ)
Higher Proportion of Non-Offenders
Long-term parental incarceration

23. Τtofi et al., 2016 meta-analysis; JCJ

26. Implications for policy & practice
Attention should be paid to the cognitive/academic development of high-risk individuals, potentially via intellectual enrichment and other individual and school programs (Farrington, Ttofi, & Lösel, 2016).
A small fraction of high-risk individuals are responsible for the majority of offences committed (Blumstein, Cohen, Roth, & Visher, 1986; Piquero, Farrington, & Blumstein, 2003)
best to address not only the deficits but also the strengths of these high-risk youth rather than targeting the wider population of youth.

27. What next?
What is known: prevalence of offending within the protective and non-protective categories
What is unknown: exact protective mechanisms that link intelligence to resilience (Masten et al., 1990; Rutter, 1987)?
Interaction processes of intelligence with school performance (Lynam et al., 1993), self-control (McGloin, Pratt, & Maahs, 2003), and motivation to change (Salekin et al., 2010)

28. Protective Stabilizing Effect, conferring stability despite increasing risk (graphs: Ttofi et al., 2016; JCJ)

29. Protective enhancing effect, allowing children to ‘engage’ with stress such that their competence is augmented

30. Protective-reactive, when the attribute generally confers advantages but less so when stress levels are high than low

33. Gaffney. , H. , Farrington, D. P. , Espelage, D. L. , Ttofi, M. M
Gaffney*, H., Farrington, D.P., Espelage, D.L., Ttofi, M.M. (2019). Are cyberbullying intervention and prevention programs effective? A systematic and meta-analytical review. Aggression and Violent Behavior, 45, 134 – 153.
Gaffney, H., Ttofi, M.M., & Farrington, D.P. (2019). Evaluating the effectiveness of school-bullying prevention programs: An updated meta-analytical review. Aggression and Violent Behavior, 45, 111 – 133.
Reising*, K., Ttofi, M. M., Farrington, D. P., & Piquero, A. R. (2019). Depression and anxiety outcomes of offending trajectories: A systematic review of prospective longitudinal studies. Journal of Criminal Justice, 62, 3-15.
Craig, J. M., Piquero, A. R., Farrington, D. P., & Ttofi, M. M. (2017). A little early risk goes a long bad way: Adverse childhood experiences and life-course offending in the Cambridge study. Journal of Criminal Justice, 53,
Valdebenito, S., Ttofi, M. M., Eisner, M., & Gaffney, H. (2017). Weapon carrying in and out of school among pure bullies, pure victims and bully-victims: A systematic review and meta-analysis of cross-sectional and longitudinal studies. Aggression and Violent Behavior, 33,
Ttofi, M.M., Farrington, D.P., Piquero, A.R., & DeLisi, M. (2016). Editorial. Protective factors against offending and violence: Results from prospective longitudinal studies. Journal of Criminal Justice, 45, 1 – 3.
Ttofi, M.M., Farrington, D.P., Piquero, A.R., Lösel, F., DeLisi, M., & Murray, J. (2016). Intelligence as a protective factor against offending: A meta-analytic review of prospective longitudinal studies. Journal of Criminal Justice, 45, 4 – 18.
Ttofi, M. M., Farrington, D. P., Lösel, F., Crago, R. V., & Theodorakis, N. (2016). School bullying and drug use later in life: A meta- analytic investigation. School Psychology Quarterly, 31, 1, 8 – 27.
Ttofi, M. M. (2015). Adolescent bullying linked to depression in early adulthood: Evidence supports early intervention. British Medical Journal, 350, h2694.
Ttofi, M.M., Bowes, L., Farrington, D.P., & Lösel, F. (2014). Protective factors that interrupt the continuity from school bullying to later internalizing and externalizing problems: A systematic review of prospective longitudinal studies. Journal of School Violence, 13, 5 – 38.
Ttofi, M.M., Farrington, D.P., & Lösel, F. (2014). Interrupting the continuity from school bullying to later internalizing and externalizing problems: Findings from cross-national comparative studies. Journal of School Violence, 13, 1 – 4.
Ttofi, M.M., Farrington, D.P., & Lösel, F. (2012). School bullying as a predictor of violence later in life: A systematic review and meta- analysis of prospective longitudinal studies. Aggression and Violent Behaviour, 17, 405 – 418.
Ttofi, M.M., Farrington, D.P., & Lösel, F. (2011). Editorial: Health consequences of school bullying. Journal of Aggression, Conflict and Peace Research, 3 (2), 60 – 62.
Ttofi, M.M., Farrington, D.P., Lösel, F., & Loeber, R. (2011). Do the victims of school bullies tend to become depressed later in life? A systematic review and meta-analysis of longitudinal studies. Journal of Aggression, Conflict and Peace Research, 3 (2), 63 – 73.
Ttofi, M.M., Farrington, D.P., Lösel, F., & Loeber, R. (2011). The predictive efficiency of school bullying versus later offending: A systematic/meta-analytic review of longitudinal studies. Criminal Behaviour and Mental Health, 21, 80 – 89.
* PhD student

34. Maria M. Ttofi: mt394@cam.ac.uk
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Maria M. Ttofi: