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Home / 1R01 DA025163 | Researching the Social Dynamics of a Loyal Methamphetamine Market

1R01 DA025163 | Researching the Social Dynamics of a Loyal Methamphetamine Market

2009-2014 | Researching the Social Dynamics of a Local Methamphetamine Market

The National Institute on Drug Abuse, National Institutes of Health (1R01 DA025163)

Principal Investigator: Lee D. Hoffer


Directly or indirectly, all illicit drug users engage the illicit drug economy. Understanding the roles that different individuals play in the market is critical for prevention, treatment, and law enforcement—yet no systematic theory exists to describe the dynamics of local drug markets.

The objective of this project is to develop and systematically field-test agent-based methodology that dynamically represents consumer, dealer, and health behaviors associated with the methamphetamine market in [Cuyahoga (Cleveland) and neighboring Summit Counties.] This approach will give researchers and policy makers an entirely new perspective for observing outcomes of interactive behaviors, as well as the opportunity to do experiments not possible in the real world. To program dynamic social simulations, we will characterize roles, motives, behaviors, and interactions of market participants utilizing ethnographic decision-tree modeling (EDM). To validate and extend EDM data, we will collect quantitative measures of participants’ daily behaviors, drug consumption, costs, and interactions using Ecological Momentary Assessment (EMA). We will integrate these descriptive methods through a three-wave panel study (N=204). We will use the collected data to set simulation parameters and evaluate simulation output. Applying Complexity Theory (discussed in Background), we will then develop an agent-based model (ABM), which will incorporate: (1) descriptive data (provided by the ethnography) on agent behaviors, relationships, and interactions (i.e., the market structures), and (2) quantitative measures (provided by the EMA and panel survey) to accurately inform the settings and distributions of the simulation parameters.

The product of this study will be simulation-based computer laboratory offering policy makers and researchers an entirely novel analytic framework and research tool for: (1) dynamically observing how illicit drug markets operate, (2) experimenting with agent behaviors, market parameters, and conditions, and 3) evaluating “what if” policy scenarios intended to influence market outcomes. The specific aims of this project are to:

  1. Conduct ethnographic research on the methamphetamine market in [Cuyahoga (Cleveland) and neighboring Summit Counties] enhanced by ethnographic decision-tree modeling (EDM) to facilitate Agent-Based Model (ABM) development.
  2. Enrich (and validate) this descriptive data using Ecological Momentary Assessment (EMA), collecting self-report data on daily drug consumption, production, sales, decisions, strategies etc.
  3. Inform (and validate) simulation metrics and parameters, as well as simulation output using a panel survey of N=204 active methamphetamine users.
  4. Construct a computer lab of ABM simulations reproducing how the local methamphetamine market operates integrating both social (i.e., health) and economic behaviors.
  5. Experiment with the ABM simulations to:
    • Understand further how the market operates and functions.
    • Evaluate market parameters, components, and distributions (e.g., retail drug price, number of customers, supply).
    • Create and test policy-based intervention scenarios (e.g. enforcement, treatment, and outreach) intended to impact outcomes.
    • Model risk behaviors (e.g., needle sharing, trading drugs for sex) influencing the spread of HIV.

The potential utility of the proposed project is far reaching because of the project’s systematic combination of ethnography’s rich descriptive detail offered combined with ABM’s power to aggregate socially complex behaviors. The methods developed in this project will provide a theoretically informed interdisciplinary.

Page last modified: July 19, 2017