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Targeted and universal intervention

Targeted and universal intervention. Leon Feinstein 18-July-2006. Five questions. How well can we identify those children at risk of adult social exclusion? Which measures are most predictive? What difference does it make? What are the implications for the delivery of services?

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Targeted and universal intervention

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  1. Targeted and universal intervention Leon Feinstein 18-July-2006

  2. Five questions • How well can we identify those children at risk of adult social exclusion? • Which measures are most predictive? • What difference does it make? • What are the implications for the delivery of services? • What are the implications for the targeting of interventions?

  3. E.g. Relationship of G1 maternal interest at G2 age 7 and G2-G3 parenting at G2 age 33

  4. Relative cognitive shifts, 7 -11, by SES, 1958 Cohort Source: Feinstein, L. ‘Schools and Educational Attainment’, Oxford Review of Economic Policy, (in press)

  5. Skills and capabilities; Probability of being in workless household with children at age 30 Source: Feinstein, L. and Bynner, J. (Dec 2003), ‘The benefits of assets in childhood as protection against adult social exclusion: the relative effects of financial, human, social and psychological assets’, Note to HM Treasury.

  6. Conceptual model for family influences on child development

  7. Some cost-benefit notation • C(T+) = The social cost of the outcome (T=truth) • P(T+) = The unconditional probability of the outcome • P(D+)= The level of targeting of the intervention • C(D+)= The cost of the intervention • f= the effectiveness of the intervention; 0 ≤ f ≤ 1.

  8. True and false positives P(TP) = P(D+ | T+) = A / (A+C) P(FP) = P(D+ | T-) = B / (B+D)

  9. Costs and benefits • C(T-, D+) = The cost of a positive decision and hence intervention for those who would not experience the outcome (deadweight +stigmatisation costs) • C(T+, D-) = The cost of a negative decision and hence failure to intervene for those who would experience the outcome • B(T+, D+) = The net benefit of a positive decision and intervention for those who would experience the outcome (net of intervention and stigmatisation costs) • B(T-, D-) = The net benefit of a negative decision and absence of intervention for those who would not experience the outcome.

  10. B(T+, D+) = P(D+, T+) * f * C(T+) – P(D+, T+) * C(D+) = P(TP) * P(T+) {f * C(T+) –C(D+) }

  11. C(T-, D+) = P(D-, T+) * C(D+) = P(FP) * P(T-) * C(D+) Hence cost effectiveness requires: P(TP) > P(T-) * C(D+) P(FP) P(T+) { f * C(T+) –C(D+) }

  12. ROC Curves: Allowing the allocation threshold to vary

  13. Optimal point on the ROC curve S* = P(T-) * B(T-, D-) + C(T-, D+) P(T+) B(T+, D+) + C(T+, D-)

  14. 2. Estimating P(TP) and P(FP)

  15. Predicting teenage parenthood, by age

  16. Predicting adult depression, by age

  17. Predicting teenage parenthood, by domain

  18. Predicting adult depression, by domain

  19. Predicting other outcomes from age 10 measures, 1970 Cohort

  20. Predicting other outcomes, P(TP), 1970

  21. 3. Preliminary discussion • Targeting depends on identification • Identification capabilities are very strong • So targeted intervention is possible, but: • Ethical issues • Stigmatisation • Need effective and appropriate intervention • Facilitated community engagement crucial • People move in and out of risk • Progressive universalism is essential • Role of schools and GPs?

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