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Which adolescents develop persistent substance dependence in adulthood? Using population-representative longitudinal data to inform universal risk assessment

  • M. H. Meier (a1), W. Hall (a2) (a3), A. Caspi (a4) (a5) (a6), D. W. Belsky (a7) (a8), M. Cerdá (a9), H. L. Harrington (a4) (a5), R. Houts (a4) (a5), R. Poulton (a10) and T. E. Moffitt (a4) (a5) (a6)...

Abstract

Background

To our knowledge, there are no universal screening tools for substance dependence that (1) were developed using a population-based sample, (2) estimate total risk briefly and inexpensively by incorporating a relatively small number of well-established risk factors, and (3) aggregate risk factors using a simple algorithm. We created a universal screening tool that incorporates these features to identify adolescents at risk for persistent substance dependence in adulthood.

Method

Participants were members of a representative cohort of 1037 individuals born in Dunedin, New Zealand in 1972–1973 and followed prospectively to age 38 years, with 95% retention. We assessed a small set of childhood and adolescent risk factors: family history of substance dependence, childhood psychopathology (conduct disorder, depression), early exposure to substances, frequent substance use in adolescence, sex, and childhood socioeconomic status. We defined the outcome (persistent substance dependence in adulthood) as dependence on one or more of alcohol, tobacco, cannabis, or hard drugs at ⩾3 assessment ages: 21, 26, 32, and 38 years.

Results

A cumulative risk index, a simple sum of nine childhood and adolescent risk factors, predicted persistent substance dependence in adulthood with considerable accuracy (AUC = 0.80).

Conclusions

A cumulative risk score can accurately predict which adolescents in the general population will develop persistent substance dependence in adulthood.

Copyright

Corresponding author

*Address for correspondence: M. H. Meier, PhD., Department of Psychology, Arizona State University, PO Box 871104, Tempe, AZ 85287-1104, USA. (Email: madeline.meier@asu.edu)

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