Influence of Psychiatric and Personality Disorders on Smoking Cessation Among Individuals in Opiate Dependence Treatment

Abstract

Objective We aimed to evaluate how psychiatric and personality disorders influence smoking cessation goals and attempts among people with opiate dependence who smoke. This information could aid the development of more effective cessation interventions for these individuals. Methods Participants (N=116) were recruited from two methadone clinics, completed the Millon Clinical Multiaxial Inventory–III, and were asked about their smoking behavior and quitting goals. We used the Least Absolute Shrinkage and Selection Operator (LASSO) method, a technique commonly used for studies with small sample sizes and large number of predictors, to develop models predicting having a smoking cessation goal, among those currently smoking daily, and ever making a quit attempt, among those who ever smoked. Results Almost all participants reported ever smoking (n = 115, 99%); 70% (n = 80) had made a serious quit attempt in the past; 89% (n = 103) reported current daily smoking; and, 59% (n = 61) had a goal of quitting smoking and staying off cigarettes. Almost all (n = 112, 97%) had clinically significant characteristics of a psychiatric or personality disorder. White race, anxiety, and a negativistic personality facet (expressively resentful) were negative predictors of having a cessation goal. Overall narcissistic personality pattern and a dependent personality facet (interpersonally submissive) were positive predictors of having a cessation goal. Somatoform disorder, overall borderline personality pattern, and a depressive personality facet (cognitively fatalistic) were negative predictors of ever making a quit attempt. Individual histrionic (gregarious self-image), antisocial (acting out mechanism), paranoid (expressively defensive), and sadistic (pernicious representations) personality disorder facets were positive predictors of ever making a quit attempt. Each model provided good discrimination for having a smoking cessation goal or not (C-statistic of .76, 95% CI[0.66, 0.85]) and ever making a quit attempt or not (C-statistic of .79, 95% CI[0.70, 0.88]). Conclusions Compared to existing treatments, smoking cessation treatments that can be tailored to address the individual needs of people with specific psychiatric disorders or personality disorder traits may better help those in opiate dependence treatment to set a cessation goal, attempt to quit, and eventually quit smoking.

Association Patterns of Antisocial Personality Disorder across Substance Use Disorders

“…Notably, the “Attempts to Quit” criterion was the only one that was negatively associated with ASPD, suggesting that the absence of ASPD, or decreased ASPD symptomology, allows individuals to make more attempts to terminate their substance use. However, there are different views on whether the presence of ASPD supports or hinders SUD treatment seeking behavior and abstinence [33–35]. Further, the different associations of ASPD with criteria for individual SUDs supports our decision to analyze each separately rather than creating a composite SUD variable for analysis.…”

Telehealth Mindfulness-Oriented Recovery Enhancement vs Usual Care in Individuals With Opioid Use Disorder and Pain

“…Physical pain, emotional distress, and reward deficiency, which affect the majority of people receiving MT, are thought to contribute to continued opioid and other drug use and MT dropout . Studies of people receiving MT indicate that 80% to 88% experienced pain in the last week, and pain is negatively associated with MT retention .…”

“…Physical pain, emotional distress, and reward deficiency, which affect the majority of people receiving MT, 6,7 are thought to contribute to continued opioid and other drug use and MT dropout. 8,9 Studies of people receiving MT indicate that 80% to 88% experienced pain in the last week, 6 and pain is negatively associated with MT retention. 9,10 Also, individuals with pain who receive MT report lower treatment satisfaction than those without pain and are more likely to believe their methadone dosage is too low.…”

Prediction model of emergency mortality risk in patients with acute upper gastrointestinal bleeding: a retrospective study

“…Nevertheless, our new model outperformed PERS in both the original AUC and corrected AUC. Nomograms are graphical depictions of individual-level prognosis predictions and have been shown to be more accurate than conventional models for predicting prognosis (Balachandran et al, 2015;Cooperman et al, 2016;Huang et al, 2016;Touijer & Scardino, 2009). We established a nomogram based on five predictors including four clinical patient characteristics, which can be readily obtained in clinical settings, and one medical intervention that can be used for the better management of patients.…”