Gender Differences in the Validity of the Substance Abuse Subtle Screening Inventory—3 (SASSI-3) With a Criminal Justice Population

Pérez, Deanna M.; Wish, Eric D.

doi:10.1177/0306624x10362662

Cited by 4 publications

(2 citation statements)

References 28 publications

(29 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Convergent validity was also demonstrated with a variety of other indexes, including the Michigan Alcohol Screening Test (MAST), the Minnesota Multiphasic Personality Invertory-2 (MMPI-2), and the Millon Clinical Multiaxial Inventory-II (MCMI-II; Lazowski et al, 1998). In addition, SASSI showed higher accuracy (89%) in detecting women with substance dependence than in detecting men (59%; Perez & Wish, 2011). Additional dichotomous questions in the survey asked about respondents' use of either alcohol or other drugs in the year before being incarcerated.…”

Section: Methodsmentioning

confidence: 92%

Differences Among Incarcerated Women With Assaultive Offenses

Kubiak

Kim

Fedock

et al. 2013

J Interpers Violence

View full text Add to dashboard Cite

A majority of the existing research on women's use of violence focuses on intimate partner violence, often excluding other types of violence for which women may be incarcerated. The current study expands this area of research by assessing between and within-group differences among a randomly selected group of incarcerated women (n = 543). Comparisons between violent and nonviolent offense types among women found few differences, but significant differences among women with an assaultive offense, based on the presence or absence of a self-reported uncaught violence, were found. Differences in women with isolated (i.e., single incident of violence perpetration through a review of formal and self-report data) and patterned uses of violence were present in relation to issues of mental health, substance abuse, criminogenic risk, and expressions of anger and personality factors. These findings have important implications for intervention as well as future research.

show abstract

Section: Methodsmentioning

confidence: 92%

Differences Among Incarcerated Women With Assaultive Offenses

Kubiak

Kim

Fedock

et al. 2013

J Interpers Violence

View full text Add to dashboard Cite

show abstract

“…Though the type of tool used is at the discretion of the facility, there are concerns with making informed decisions given the differing psychometrics, focus, and target population of many assessment tools [26]. There have been recommendations promoting the use of standard assessment tools such as the SASSI and ASAM [27,28], but these tools have not proven to have comparable effectiveness [29][30][31][32][33][34]. Given this evidence, it may be worth examining alternative standard guidelines for using assessment tools which may aid in ensuring patients receive equitable and timely services [35].…”

Section: Discussionmentioning

confidence: 99%

Assessing public behavioral health services data: a mixed method analysis

Vaughn

Maxey

Keen

et al. 2020

Subst Abuse Treat Prev Policy

View full text Add to dashboard Cite

Background Measuring behavioral health treatment accessibility requires timely, comprehensive and accurate data collection. Existing public sources of data have inconsistent metrics, delayed times to publication and do not measure all factors related to accessibility. This study seeks to capture this additional information and determine its importance for informing accessibility and care coordination. Methods The 2018 National Survey for Substance Abuse and Treatment Services (N-SSATS) data were used to identify behavioral health facilities in Indiana and gather baseline information. A telephone survey was administered to facilities with questions parallel to the N-SSATS and additional questions regarding capacity and patient intake. Quantitative analysis includes chi-square tests. A standard qualitative analysis was used for theming answers to open-ended questions. Results About 20% of behavioral health facilities responded to the study survey, and non-response bias was identified by geographic region. Among respondents, statistically significant differences were found in several questions asked in both the study survey and N-SSATS. Data gathered from the additional questions revealed many facilities to have wait times to intake longer than 2 weeks, inconsistency in intake assessment tools used, limited capacity for walk-ins and numerous requirements for engaging in treatment. Conclusion Despite the low response rate to this study survey, results demonstrate that multiple factors not currently captured in public data sources can influence coordination of care. The questions included in this study survey could serve as a framework for routinely gathering these data and can facilitate efforts for successful coordination of care and clinical decision-making.

show abstract