Examining Recidivism in a Prostitution Diversion Program.

Street-based sex work is criminalized throughout much of the U.S. Diversion programs have shown mixed results. This study examined the effect a quasi-experimental intervention (prostitution diversion program, n = 149) had on prostitution rearrest compared with a waitlist control group (n = 77) among N = 226 individuals arrested for prostitution in Baltimore. In both groups, n = 64 (28.32%) were rearrested for prostitution over 30 months. Tests of differences compared groups with a significant difference in gender only. A Cox proportional hazard model examined differences in survival time (to recidivist prostitution arrest) between individuals in the control and intervention groups at 6, 12, 18, 24, and 30 months. Results indicate that participation in the intervention did not have a significant effect on decreasing prostitution arrests over time. History of prior prostitution arrest was a significant predictor (hazard ration [HR] = 1.12, p = .02) of rearrest.Lack of program success suggests that barriers to exiting prostitution are substantial, despite availability of supportive services, and that diversion programs may not be the best intervention strategy for all sex workers. Future research should identify motivators for exiting and how to reduce exiting barriers.

Item Responses in Quantity-Frequency Questionnaires: Implications for Data Generalizability.

Alcohol consumption is an important predictor of a variety of negative outcomes. There is an extensive literature that examines the differences in the estimated level of alcohol consumption between types of assessments (e.g., quantity-frequency [QF] questionnaires, daily diaries). However, it is typically assumed that all QF-based measures are nearly identical in their assessment of the volume of alcohol consumption in a population. Using timeline follow-back data and constructing common QF consumption measures, we examined differences among survey instruments to assess alcohol consumption and heavy drinking. Using three data sets, including clinical to community samples, we demonstrate how scale-specific item characteristics (i.e., number of response options and ranges of consumption assessed by each option) can substantially affect the estimated mean level of consumption and estimated prevalence of binge drinking. Our analyses suggest that problems can be mitigated by employing more resolved measures of quantity and frequency in consumption questionnaires.

Toward more efficient diagnostic criteria sets and rules: The use of optimization approaches in addiction science.

Psychiatric diagnostic systems, such as The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), use expert consensus to determine diagnostic criteria sets and rules (DCSRs), rather than exploiting empirical techniques to arrive at optimal solutions (OS). Our project utilizes complete enumeration (i.e., generating all possible subsets of item combinations A and B with all possible thresholds, T) to evaluate all possible DCSRs given a set of relevant diagnostic data. This method yields the entire population distribution of diagnostic classifications (i.e., diagnosis of the disorder versus no diagnosis) produced by a set of dichotomous predictors (i.e., diagnostic criteria). Once unique sets are enumerated, optimization on some predefined correlate or predictor will maximally separate diagnostic groups on one or more, disorder-specific "outcome" criteria. We used this approach to illustrate how to create a common Substance Use Disorder (SUD) DCSR that is applicable to multiple substances. We demonstrate the utility of this approach with respect to alcohol use disorder and Cannabis Use Disorder (CUD) using DSM-5 criteria as input variables. The optimal SUD solution with a moderate or above severity grading included four criteria (i.e. 1) having a strong urge or craving for the substance (CR), 2) failure to fulfill major role obligations at work school or home (FF), 3) continued use of the substance despite social or interpersonal problems caused by the substance use (SI) and 4) physically hazardous use (HU)) with a diagnostic threshold of two. The derived DCSR was validated with known correlates of SUD and performed as well as DSM-5. Our findings illustrate the value of using an empirical approach to what is typically a subjective process of choosing criteria and algorithms that is prone to bias. The optimization of diagnostic criteria can reduce criteria set sizes, resulting in decreased research, clinician, and patient burden.

Deriving alternative criteria sets for alcohol use disorders using statistical optimization: Results from the National Survey on Drug Use and Health.

Much of the foundation of clinical practice, psychiatric epidemiology, and research into the etiology, course, prevention, and treatment of alcohol use disorder (AUD) rests on psychiatric diagnosis. However, existing research has failed to adequately exploit empirical techniques and existing databases to derive criteria considered optimal with respect to predicting external correlates. The current project adopts a novel approach to deriving new diagnostic criteria sets and rules for AUD. Utilizing the 2010 (N = 24,120) and 2013 (N = 23,627) National Survey on Drug Use and Health (NSDUH; Substance Abuse and Mental Health Services Administration [SAMHSA], 2011, 2014) data sets, we performed a statistical optimization procedure, using complete enumeration, on participants 21 or older who had consumed at least 1 alcoholic beverage in the past year. The goal was to maximize the distance (based on Cohen's d) between mean levels of the optimization criteria (i.e., consumption and functional impairment) in those with an AUD diagnosis versus those without. In contrast with current convention, AUD is derived transparently using a data-driven approach. The best solution included 9 criteria with a diagnostic threshold of 3, while the second-best solution comprised 5 criteria with a threshold of 2. External validation demonstrated both solutions perform similarly, suggesting it is appropriate to use either, depending on the goal of the diagnosis. Overall, statistical optimization approaches can yield highly efficient criteria sets and rules, although multiple, near equivalently performing solutions can be generated. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Sexual Orientation Self-Concept Ambiguity: Scale Adaptation and Validation.

The current article describes the adaptation of a measure of sexual orientation self-concept ambiguity (SSA) from an existing measure of general self-concept clarity. Latent "trait" scores of SSA reflect the extent to which a person's beliefs about their own sexual orientation are perceived as inconsistent, unreliable, or incongruent. Sexual minority and heterosexual women ( n = 348), ages 18 to 30, completed a cross-sectional survey. Categorical confirmatory factor analysis guided the selection of items to form a 10-item, self-report measure of SSA. In the current report, we also examine (a) reliability of the 10-item scale score, (b) measurement invariance based on respondents' sexual identity status and age group, and (c) correlations with preexisting surveys that purport to measure similar constructs and theoretical correlates. Evidence for internal reliability, measurement invariance (based on respondent sex), and convergent validity was also investigated in an independent, validation sample. The lowest SSA scores were reported by women who self-ascribed an exclusively heterosexual or exclusively lesbian/gay sexual identity, whereas those who reported a bisexual, mostly lesbian/gay, or mostly heterosexual identity, reported relatively higher SSA scores.