Introduction
This document was prepared as a resource for researchers
attending the meeting "Assessing the Impact of Childhood Interventions
on Subsequent Drug Abuse" organized by the National Institute on
Drug Abuse with co-sponsorship by the National Institute of Mental Health.
Little is known about how mental health treatments for childhood psychopathologies
influence the subsequent risk of drug abuse. This meeting is intended
to stimulate the development of research in this important area. In
planning for the meeting, NIDA staff and extramural researchers recognized
the need to incorporate a systematic consideration of methodological
challenges affecting this line of research. This portion of the program
will identify resources and strategies for measuring substance abuse
and related risk factors and for addressing followup, design, and analysis
problems. This document is provided as a supplement to the methodological
presentations.
This annotated bibliography samples and documents some
of the latest developments in research methods that are relevant to
the study of childhood mental health intervention and drug abuse prevention.
Our collection covers general topics in research methods, such as research
design, sampling strategies and measurement issues, and statistical
analysis. It also includes work that specifically addresses methodological
concerns that drug abuse prevention researchers often have, such as:
the use of self report measures in drug use; issues of selection bias
and the use of statistical adjustments in observational studies; selection
of covariates; the handling of subject attrition and missing data; and
power calculation.
This annotated bibliography emphasizes statistical analyses.
This is in response to the increasing need for more sophisticated research
designs and analyses in the field of prevention, and also to reflect
the recent rapid growth of applied statistical techniques. In addition
to traditional analysis that researchers are familiar with, we include
techniques that are more recently developed, such as hierarchical linear
modeling, growth curve modeling, survival analysis, structural equation
modeling and latent transition analysis.
Knowing that the end-users of our work will be researchers
who have varying sophistication in methodological training, we try to
include work that assumes different levels of statistical understanding.
Finally, we want to point out that this bibliography is far from a comprehensive
survey of methodological advances. Rather it is compiled to be an introductory
guide for prevention researchers, aiming at providing the necessary
leads that facilitate researchers' search for useful methodological
references.
Chi-Ming Kam
Linda M. Collins
The Methodology Center
Pennsylvania State University
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