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The Interplay of Personality and Addiction in Predicting Sobriety:

The Interplay of Personality and Addiction in Predicting Sobriety: A Longitudinal Study of Health Care Professionals Daniel Angres, M.D.¹ &Stephanie Bologeorges, B.A.¹ ¹ Resurrection Behavioral Health-Addiction Services. Measures

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The Interplay of Personality and Addiction in Predicting Sobriety:

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  1. The Interplay of Personality and Addiction in Predicting Sobriety: A Longitudinal Study of Health Care Professionals Daniel Angres, M.D.¹ &Stephanie Bologeorges, B.A.¹ ¹ Resurrection Behavioral Health-Addiction Services • Measures • Longitudinal Sobriety Outcome: Post-treatment sobriety outcome was measured by tracking the relapse behavior of patients through the 2 year period following discharge. Patients were followed with random urine-monitoring at an average of twice a month during this interval, and also participated in weekly AfterCare groups. Classification was made into one of two groups: 1. remaining sober or completely abstinent with no reports of use and no positive urine screens 2. relapsed to substance use based on positive urine screens and corroborating follow-up reports by post-discharge treatment coordinators • Temperament and Character Inventory-Revised: The TCI-R is a 240 item self-report questionnaire consisting of 5-point Likert scale items. The measure yields four temperament dimensions (Novelty Seeking, Harm Avoidance, Reward Dependence, and Persistence) and three dimensions of character (Self-Directedness, Cooperativeness, and Self-Transcendence). Reliability and validity of the instrument have been established (Cloninger et al., 1993). • Millon Clinical Multiaxial Inventory: The MCMI-III is a 175 item self-report questionnaire comprised of true-false items designed to identify clinical states, DSM-IV Axis I and II disorders, and clinical syndromes including drug and alcohol dependence. Raw scores are adjusted to base rate scores for analyses. Per the manual, a base rate score >85 is conservatively indicative of a clinical PD. Reliability and validity are established (Millon, 1997). Table: Binary Logistic Regression Predicting Sobriety Outcome from Gender, Antisocial, and Alcohol Dependence • Introduction • It is estimated that at some point during their career, 10-15% of all health care professionals will misuse drugs or alcohol (Baldissari, 2007). Research has also indicated the rate of addiction in this population is near to or higher than that of the general population (Berge et al., 2009), which has a lifetime prevalence of 10.3% (Compton et al., 2007). • Results from the National Epidemiologic Survey on Alcohol and Related Conditions found that individuals with any substance use disorder were 2.2 times more likely to have a comorbid personality disorder (PD) when adjusted for demographic variables and other psychiatric conditions (Compton et al., 2007). • The rates of specific comorbid PDs with addictions have been varied in the research literature, although multiple studies have identified the Cluster B PDs (specifically Antisocial) as most prevalent across various types of substance abusers (e.g. Hesse et al., 2007). • Treatment for individuals with addictions and comorbid PDs is not without considerable difficulty; the presence of a comorbid PD has been associated with failure to complete treatment, poorer treatment outcomes, and a higher propensity for relapse (e.g. Nielsen et al., 2007). Health care professionals with addiction face unique challenges in treatment (e.g. licensing and return to work issues) and considerations must be made with regard to this population. It has been noted that the intellect inherent to this population has been associated with exceptional rationalization, denial, and resistance, which perpetuate treatment difficulties (Berge et al., 2009). • While addicted health care professionals have received attention in the clinical literature, there is a paucity of empirical research that examines the interplay of personality variables with the clinical treatment for addiction in this population and its subsequent impact on outcome. With the role of health care professionals in maintaining public health, it is critically important to understand potential underlying factors of addiction, such ass personality, that may predict both substance abuse and treatment outcome. • Aims of the Present Investigation • To investigate if personality variables differentiate sobriety outcomes among health care professionals in addictions treatment over a two year follow-up interval • To narrow the deficit in the extant literature by integrating personality and addiction factors with treatment outcomes for health care professionals, of which longitudinal data is lacking • Discussion • The two year sobriety outcome rate for the sample of health professionals was 73.3%, which is both highly favorable and is consistent with prior findings on physicians (e.g. DuPont, 2009). This is the first longitudinal outcome study to date to integrate a range of health care professionals and multiple drugs of choice. • Factors independently predictive of relapse were female gender, alcohol as drug of choice, and higher scores on the MCMI-III consistent with Antisocial PD. These indicators are useful tools by which treatment providers can better identify patients needing more specialized care integrating personality dysregulation with addiction. • That female gender was predictive of relapse extends prior findings of physicians, wherein females have reportedly less spousal and workplace support (McGovern et al., 2003). Female physicians have also been found more likely to be alcohol dependent, which links the independent factors of gender and drug of choice in present findings. • Alcohol was the most prominent substance in relapse, meaning the workplace was generally spared safety issues (e.g. diversion of substances and job impairment). • Elevated Antisocial personality scores in the relapse group are consistent with those suggested by prior literature and also extend prior findings to longitudinal outcome. • Interestingly, results investigating the interplay of these factors did not find significant multivariate differences across outcome groups, revealing the heterogeneity of personality among addicts and alcoholics, particularly those of such a high functioning population. The need to individualize and tailor treatment is emphasized. • Results • At the end of the two-year interval, 85 of the 116 health care professionals had maintained complete abstinence from all addictive substances, yielding an overall success rate of 73.3%. • Success rates by professional group are shown in the • table to the right. A 4x2 Pearson Chi Square analysis • found no significant differences between health care • professional group and outcome: χ²(3) = 3.83, p > .05. • The sample prevalence of PDs was 35.3% (n = 41). • No significant association was found between having • any PD and outcome status (p > .05). • Univariate analyses were performed using Pearson’s Chi Square tests for categorical variables and independent sample t-tests for continuous variables to determine variables that differentiated relapsed from sober individuals. The following factors were associated with relapse: • Gender- Women were more likely than men to have relapsed; χ²(1) = 5.30, p < .05 • Alcohol Dependence- Higher scores on the MCMI-III scale were associated with relapse. A significant mean difference of 10.84 was yielded between the sober (M = 58.29) and relapse (M = 69.13) groups; t (65.44) = -2.00, p = .05 • Antisocial Personality- Higher MCMI-III scores on this scale were associated with relapse. A significant mean difference of 9.88 was yielded between the sober (M = 48.61) and relapse (M = 58.48) groups; t (66.80) = -2.146, p = .035. • Binary logistic regression was used to identify the multivariate contribution of all explanary variables significant in univariate analyses. The dependent variable in the model was the two-year sobriety outcome status (sober = 0, relapsed = 1). The table titled: Binary Logistic Regression Predicting Sobriety Outcome from Gender, Antisocial, and Alcohol Dependence presents the regression coefficients, standard error terms, the Wald Chi Square tests of the unique contribution of each predictor holding the effects of the other predictors constant, the significance value, and the model predicted odds of relapse for the overall binary logistic regression model predicting sobriety outcome. Gender was coded in binary, with male as the reference code. The overall regression equation is therefore: • ln (Odds) = -1.545 + .013 Alcohol Dependence + .006 Antisocial - .969 Gender. • Methods • Participants • A clinical sample of health care professionals (N = 116) were patients at a tailored intensive substance abuse hospital day-treatment program with associated supervised independent living in a therapeutic community. Participants were 68.1% male and 31.9% female. Inclusion criteria for admission required medical stabilization, a diagnosis of current alcohol or drug dependence, and occupation as a health care professional. The mean age of the sample was 43.5 years, with no significant difference in age between gender. Professional breakdown of the sample included 56 physicians, 28 nurses, 21 pharmacists, and 11 other health care professionals (dentists, optometrists, physician’s assistants, and advanced medical students) • Procedure • Participants completed a tailored professional’s treatment program with respect to personality. The program was abstinence-based, 12-step oriented, and tailored in duration ranging from 6-10 weeks. Within one week of admission, participants completed the TCI-R and the MCMI-III self-report instruments. Two-year sobriety status was obtained through self-disclosure in a facilitated 2-year AfterCare program consisting of weekly caduceus groups, as well as through reports by post-discharge coordinators. Status was biologically confirmed through urine monitoring. References Baldissari, M. R. (2007). Impaired healthcare professional. Critical Care Medicine, 35 (2): s106-s116. Berge, K., Seppala, M., Schipper, A. (2009). Chemical Dependency and the Physician. Mayo Clinical Proceedings, 84(7): 625-631. Cloninger, C., Svrakic, D., & Przybeck, T. (1993). A psychobiological model of temperament and character. Archives of General Psychiatry, 50: 975-990. Compton. W., Thomas, Y., Stinson, F., Grant, B. (2007). Prevalence, Correlates, Disability, and Comorbidity of DSM-IV Drug Abuse and Dependence in the U.S.: Results from the National Epidemiologic Survey on Alcohol and Related Conditions. Archives of General Psychiatry, 64: 566-576. DuPont, R., McLellan, A., White, W., Merlo, L., Gold, M. (2009). Setting the standard for recovery: Physicians’ Health Programs. Journal of Substance Abuse Treatment, 36 (2): 159-171. Hesse, M., Nielsen, P., Rojskjaelr, R. (2007). Stability and Change in MCMI II Personality Disorder Scores in Treated Alcohol Dependent Subjects: Relationship to Post-treatment Abstinence. Int’l Journal of Mental Health Addiction, 5: 254-262. McGovern, M., Angres, D., Shaw, M., Rawal, P. (2003). Gender of Physicians with Substance Use Disorders: Clinical Characteristics, Treatment Utilization, and Post-treatment Functioning. Substance Use and Misuse, 38 (7): 993-1001. Millon, T. (1997). MCMI-III manual. Minneapolis, MN: National Computer Systems. Nielsen, P., Rojskjaer, S., Hesse, M. (2007). Personality-Guided Treatment for Alcohol Dependence: A Quasi-Randomized Experiment. The American Journal on Addictions, 16: 357-364.

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