Abstract
BackgroundThe gateway hypothesis (and particularly the prediction of developmental stages in drug abuse) has been a subject of protracted debate since the 1970s. Extensive research has gone into this subject, but has yielded contradictory findings. We propose an algorithm for detecting both association and causation relationships given a discrete sequence of events, which we believe will be useful in addressing the validity of the gateway hypothesis.To assess the gateway hypothesis, we developed the GatewayNet algorithm, a refinement of sequential rule mining called initiation rule mining. After a brief mathematical definition, we describe how to perform initiation rule mining and how to infer causal relationships from its rules (“gateway rules”).We tested GatewayNet against data for which relationships were known. After constructing a transaction database using a first-order Markov chain, we mined it to produce a gateway network. We then discuss various incarnations of the gateway network.We then evaluated the performance of GatewayNet on urine drug screening data collected from the emergency department at LSU Health Sciences Center in Shreveport. A de-identified database of urine drug screenings ordered by the department between August 1998 and June 2011 was collected and then restricted to patients having at least one screening succeeding their first positive drug screening result.ResultsIn the synthetic data, a chain of gateway rules was found in the network which demonstrated causation. We did not find any evidence of gateway rules in the empirical data, but we were able to isolate two documented transitions into benzodiazepine use.ConclusionsWe conclude that GatewayNet may show promise not only for substance use data, but other data involving sequences of events. We also express future goals for GatewayNet, including optimizing it for speed.
Highlights
The gateway hypothesis has been a subject of protracted debate since the 1970s
Implementation To better understand the extent to which the Gateway Hypothesis manifests itself in drug use trends, we developed GatewayNet, an algorithm that constructs a directed, weighted graph of drug initiation events derived from a form of association rule mining
initiation rule mining (IRM) shows promise to demystify the Gateway Hypothesis, but it may be useful in the prediction of any event
Summary
The gateway hypothesis (and the prediction of developmental stages in drug abuse) has been a subject of protracted debate since the 1970s. A de-identified database of urine drug screenings ordered by the department between August 1998 and June 2011 was collected and restricted to patients having at least one screening succeeding their first positive drug screening result. Full list of author information is available at the end of the article progression from tobacco and alcohol to cannabis, to LSD, amphetamines, or heroin She posits that this association is bidirectional and that a similar sequence will occur for regression in drug use [1]. At the height of the crack cocaine epidemic, Kandel and Yamaguchi reformed their model to account for its sudden appearance and found that a) cocaine precedes crack cocaine, and b) models using cocaine or crack cocaine exclusively had a poorer fit than those containing both [3]
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