Background: Individual trajectories of drug use and drug-related problems are highly heterogeneous. There is no standard taxonomy of these trajectories, but one could be developed by defining natural categories based on changes in symptoms of substance-use disorders over time.
Methods: Our study was conducted in a community sample in Baltimore, Maryland. At baseline, all participants were using opioids and/or cocaine, but none were in treatment. Drug use and symptomatology were assessed again at 12 months (N = 115).
Results: We defined Quitters as participants who had not used for at least 30 days at follow-up (17%). For the remaining participants, we performed longitudinal cluster analysis on DSM symptom-counts, identifying three trajectory clusters: newly or persistently Symptomatic (40%) participants, Chippers (21.5%) with few symptoms, and Converted Chippers (21.5%) with improved symptom counts. Logistic regression showed that profiles of Quitters did not resemble Chippers, but instead resembled Symptomatic participants, having high probability of disorderly home neighborhood, nonwhite race, and negative mood. Quitters tended to have two protective factors: initiating opioid-agonist treatment during the study (r = 0.25, CL95 0.02-0.48) and lack of polydrug use (r = 0.25, CL95 0.004-0.49). Converted Chippers tended to be white, with orderly home neighborhoods and less negative mood (r 0.24 to 0.31, CL95 0.01-0.54).
Conclusions: Changes in DSM symptomology provided a meaningful measure of individual trajectories. Quitters shared psychosocial characteristics with Symptomatic participants, but not with participants who continued to use with few symptoms. This suggests that Quitters abstained out of necessity, not because their problems were less severe.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6587183 | PMC |
http://dx.doi.org/10.1016/j.addbeh.2019.04.030 | DOI Listing |
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