Dataset Information

Two Pathways to Self-Harm in Adolescence.

ABSTRACT:

Objective

The behavioral and emotional profiles underlying adolescent self-harm, and its developmental risk factors, are relatively unknown. We aimed to identify subgroups of young people who self-harm (YPSH) and longitudinal risk factors leading to self-harm.

Method

Participants were from the Millennium Cohort Study (N = 10,827). A clustering algorithm was used to identify subgroups who self-harmed with different behavioral and emotional profiles at age 14 years. We then traced the profiles back in time (ages 5-14 years) and used feature selection analyses to identify concurrent correlates and longitudinal risk factors of self-harming behavior.

Results

There were 2 distinct subgroups at age 14 years: a smaller group (n = 379) who reported a long history of psychopathology, and a second, much larger group (n = 905) without. Notably, both groups could be predicted almost a decade before the reported self-harm. They were similarly characterized by sleep problems and low self-esteem, but there was developmental differentiation. From an early age, the first group had poorer emotion regulation, were bullied, and their caregivers faced emotional challenges. The second group showed less consistency in early childhood, but later reported more willingness to take risks and less security with peers/family.

Conclusion

Our results uncover 2 distinct pathways to self-harm: a "psychopathology" pathway, associated with early and persistent emotional difficulties and bullying; and an "adolescent risky behavior" pathway, whereby risk taking and external challenges emerge later into adolescence and are associated with self-harm. At least one of these pathways has a long developmental history, providing an extended window for interventions as well as potential improvements in the identification of children at risk, biopsychosocial causes, and treatment or prevention of self-harm.

SUBMITTER: Uh S

PROVIDER: S-EPMC8661039 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:AimsSuicidal acts may cluster in time and space and lead to community concerns about further imitative suicidal episodes. Although suicide clusters have been researched in previous studies, less is known about the clustering of non-fatal suicidal behaviour (self-harm). Furthermore, most previous studies used crude temporal and spatial information, e.g., numbers aggregated by month and residence area, for cluster detection analysis. This study aimed to (i) identify space-time clusters of self-harm and suicide using daily incidence data and exact address and (ii) investigate the characteristics of cluster-related suicidal acts.MethodsData on emergency department presentations for self-harm and suicide deaths in Taipei City and New Taipei City, Taiwan, were used in this study. In all-age and age-specific analyses, self-harm and suicide clusters were identified using space-time permutation scan statistics. A cut-off of 0.10 for the p value was used to identify possible clusters. Logistic regression was used to investigate the characteristics associated with cluster-related episodes.ResultsA total of 5,291 self-harm episodes and 1,406 suicides in Taipei City (2004-2006) and 20,531 self-harm episodes and 2,329 suicides in New Taipei City (2012-2016) were included in the analysis. In the two cities, two self-harm clusters (n [number of self-harm episodes or suicide deaths in the cluster] = 4 and 8 in Taipei City), four suicide clusters (n = 3 in Taipei City and n = 4, 11 and 4 in New Taipei City) and two self-harm and suicide combined clusters (n = 4 in Taipei City and n = 8 in New Taipei City) were identified. Space-time clusters of self-harm, suicide, and self-harm and suicide combined accounted for 0.05%, 0.59%, and 0.08% of the respective groups of suicidal acts. Cluster-related episodes of self-harm and suicide were more likely to be male (adjusted odds ratio [aOR] = 2.22, 95% confidence interval [CI] 1.26, 3.89) and young people aged 10-29 years (aOR = 2.72, 95% CI 1.43, 5.21) than their cluster-unrelated counterparts.ConclusionsSpace-time clusters of self-harm, suicide, and self-harm and suicide combined accounted for a relatively small proportion of suicidal acts and were associated with some sex/age characteristics. Focusing on suicide deaths alone may underestimate the size of some clusters and/or lead to some clusters being overlooked. Future research could consider combining self-harm and suicide data and use social connection information to investigate possible clusters of suicidal acts.