“The
Future of Longitudinal Studies:
What we know; What we don’t know; What we need to
know”
Biology
And Biomedical Studies
Chaired by Joseph Campos, University of California, Berkeley
Saturday, March 22, 2003
Carolyn
Tucker Halpern
"Putting Biology In A Developmental Systems Model"
University of North Carolina
There is an increased interest in implementing Developmental
Systems models in empirical research. The core philosophy of this
approach is that sequences and outcomes of development are probabilistically
determined by the coactional operations of biological, psychological,
and social/contextual factors and events. Without such an approach,
cross-level co-actions and bi-directional relationships are missed;
however empirical application is difficult.
Project attempting to apply Developmental Systems approach: “HIV:
Pathways and Prevention”
Uses data from National Longitudinal Study of Adolescent Health
(Add Health)
Add Health has three waves of data collected to date; respondents
in 7th-12 grades at Wave I:
Wave I: Approx. 20,000 subjects
Wave II: Approx. 15,0000 subjects
Wave III: Approx. 15,0000 subjects
Add Health was designed to assess the health status of adolescents
and explore the causes of their health-related behaviors, focusing
on the effects of the multiple contexts or environments (both social
and physical) in which they live. Biomarkers were added at Wave
III.
“HIV: Pathways and Prevention” integrates person- and
variable-centered approaches to investigate adolescent risk taking.
Adolescents clustered according to drug and sexual risk taking profiles
over time. Use repeated measures from multiple levels of developmental
system to predict cluster membership and transitions to lower or
higher risk clusters. DNA collected for siblings at Wave III allows
for examination of how the same genotype may be associated with
different risk taking trajectories over time, based on differential
coaction with other factors and experiences, and conversely, how
different genotypes may be associated with similar risk trajectories.
Issues in implementing Developmental Systems models:
Practical Issues:
-
Complex models require a large sample size to avoid empty cells
and have adequate statistical power
-
Problem may be exacerbated when using biological measures that
may have low population prevalence
-
Ethical issues regarding biomarker collection and storage
-
Longitudinal design compounds these issues
Institutional/Disciplinary
-
Lack of availability of centers that facilitate long-term inter-disciplinary
collaborations
-
Do we need to re-educate ourselves in order to collaborate across
disciplines?
-
Is such re-education a luxury available primarily to more senior
investigators?
-
If we emphasize transdisciplinary training, do we run the risk
of turning out future scientists who are “vapid eclecticists?”
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