The goal of this study was to more fully understand readiness for treatment in a pre-treatment sample of 446 substance abusers. Structural Equation Modeling (SEM) was used to: (1) examine the relationships between readiness factors identified in the Pre-Treatment Readiness Scale; and (2) identify the effects of predisposing, illness, and inhibiting determinants on the factors. As with in-treatment samples, Problem Recognition was found to influence Treatment Readiness, although through a different intervening factor, Desire for Change rather than Desire for Help. A fourth factor, Treatment Reluctance, was also influenced by the Desire for Change factor. Fixed characteristics such as age and gender had minimal influences on readiness factors, as did inhibiting characteristics that reflected recent functioning. Illness characteristics including drug severity and perceived treatment barriers had a more robust influence on readiness factors. This study provides an increased understanding of readiness for treatment among pre-treatment substance abusers and also supported the construct validity of the Pre-Treatment Readiness Scale.
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http://dx.doi.org/10.1300/J465v28n01_03 | DOI Listing |
Expert Opin Ther Pat
January 2025
Department of Pharmaceutical and Biomedical Sciences, Rudolph H. Raabe College of Pharmacy, Ohio Northern University, Ada, OH, USA.
Introduction: Opioids have served as a cornerstone in pain management for decades. However, the emergence of increasingly potent synthetic analogs brings forth a range of side effects, including respiratory depression, tolerance, dependence, constipation, and, more importantly, the development of severe and debilitating opioid use disorder (OUD). Search for therapeutics to mitigate OUD has been challenging and this has called for novel approaches that include design of small molecules targeting neuronal circuits involved in addiction (opioid, dopamine, serotonin, norepinephrine, and glutamate receptors, etc.
View Article and Find Full Text PDFJ Viral Hepat
February 2025
Statistics, Modelling and Economics Department, UK Health Security Agency, London, UK.
Chronic hepatitis C virus (HCV) infection is associated with significant morbidity, mortality and health economic burden. Over 90% of HCV cases in England occur in people who inject drugs (PWID). Current treatments for HCV are effective but do not protect against reinfection.
View Article and Find Full Text PDFJMIR Form Res
January 2025
Center on Substance Use and Health, San Francisco Department of Public Health, San Francisco, CA, United States.
Background: Despite increasing fatal stimulant poisoning in the United States, little is understood about the mechanism of death. The psychological autopsy (PA) has long been used to distinguish the manner of death in equivocal cases, including opioid overdose, but has not been used to explicitly explore stimulant mortality.
Objective: We aimed to develop and implement a large PA study to identify antecedents of fatal stimulant poisoning, seeking to maximize data gathering and ethical interactions during the collateral interviews.
Sci Rep
January 2025
Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, No. 38, Italia Ave., Ghods St, Keshavarz Boulevard, Tehran, Iran.
Substance Use Disorder (SUD) is a medical condition where an individual compulsively misuses drugs or alcohol despite knowing the negative consequences. The anterior cingulate cortex (ACC) has been implicated in various types of SUDs, including nicotine, heroin, and alcohol use disorders. Our research aimed to investigate the effects of deep brain stimulation (DBS) in the ACC as a potential therapeutic approach for morphine use disorder.
View Article and Find Full Text PDFSubstance abuse research depends on precise and sensitive assessments of reinforcer efficacy in animal models. However, conventional methods often lack theoretical rigor and specificity to support these assessments. To address these gaps, the Modular Maximization Theory (MMT) is introduced as a comprehensive framework for understanding instrumental behavior.
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