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We describe a new Bayesian estimation algorithm for fitting a binary treatment, ordered outcome selection model in a potential outcomes framework. We show how recent advances in simulation methods, namely data augmentation, the Gibbs sampler and the Metropolis-Hastings algorithm can be used to fit this model efficiently, and also introduce a reparameterization to help accelerate the convergence of our posterior simulator. Conventional “treatment effects” such as the Average Treatment Effect (ATE), the effect of treatment on the treated (TT) and the Local Average Treatment Effect (LATE) are adapted for this specific model, and Bayesian strategies for calculating these treatment effects are introduced. Finally, we review how one can potentially learn (or at least bound) the non-identified cross-regime correlation parameter and use this learning to calculate (or bound) parameters of interest beyond mean treatment effects.

Longer length of stay (LOS) in residential alcohol and other drug treatment has been associated with more favourable outcomes, but the optimal duration has yet to be determined for reliable change indices. Optimal durations are likely to be a function of participant and problem characteristics. The purpose of this paper is to determine whether LOS in a residential therapeutic community for alcohol and other drug treatment community independently predicts reliable change across a range of psychological recovery and well-being measures.

In total, 380 clients from Australian Salvation Army residential alcohol and other drug treatment facilities were assessed at intake and three months post-discharge using the Addiction Severity Index 5th ed., The Depression, Anxiety and Stress Scale, The Recovery Assessment Scale, the Mental Health Continuum-Short Form and The Life Engagement Test.

The findings confirm LOS as an independent predictor of reliable change on measures of well-being and client perceived assessment of recovery. The mean LOS that differentiated reliable change from no improvement was 37.37 days.

The finding of LOS as a predictor of reliable change and the identification of an estimated time requirement may be useful for residential drug treatment providers in modifying treatment durations.

We explore the effect of selective schooling, where students are assigned to different schools by ability, on adult health, well-being and labour market outcomes. We exploit the 1960s transition from a selective to a non-selective secondary schooling system in England and Wales. The introductio3n of mixed-ability schools decreased average school quality and peer ability for high-ability pupils, while it increased them for low-ability pupils. We therefore distinguish between two treatment effects: that of high-quality school attendance for high-ability pupils and that of lower-quality school attendance for low-ability pupils, with mixed-ability schools as the alternative. We address selection bias by balancing individual pre-treatment characteristics via entropy balancing, followed by ordinary least squares (OLS) regression. Selective schooling does not affect long-term health and well-being, while it marginally raises hourly wages, compared to a mixed-ability system, and school aspirations for high-ability pupils. Cognitive and non-cognitive abilities measured prior to secondary school are significantly and positively associated with all adult outcomes.

Lechner and Miquel (2001) approached the causal analysis of sequences of interventions from a potential outcome perspective based on selection-on-observables-type assumptions (sequential conditional independence assumptions). Lechner (2004) proposed matching estimators for this framework. However, many practical issues that might have substantial consequences for the interpretation of the results have not been thoroughly investigated so far. This chapter discusses some of these practical issues. The discussion is related to estimates based on an artificial data set for which the true values of the parameters are known and that shares many features of data that could be used for an empirical dynamic matching analysis.

Substance abuse is a major public health concern, with over millions of people suffering from it worldwide. Although there is an abundance of treatment options, many of these rehabilitative trajectories are subject to “drop-out”. In addition, “drop-out” is a significant risk factor for relapse. There is an urgent demand for effective treatment, which would enable patients to reduce abuse and prevent relapse. Takiwasi is an addiction treatment centre that combines traditional Amazonian plant medicine with conventional western medicine and psychotherapy. The purpose of this paper is to explore whether socio-demographics factors, such as education level and occupation, psychiatric comorbidities and primary drug use, are associated with treatment non-completion of Ayahuasca (AYA)-assisted addiction therapy.

Data on the first treatment episode of 121 patients were collected from the patient database from the years 2012 to 2017. To determine whether there is an association between the variables of interest and treatment non-completion, a χ² analysis and a logistic regression analysis were performed.

Of the 121 patients analysed, 48.2 per cent completed their treatment, whilst 51.8 per cent did not. Students compared to those who are employed showed significantly higher odds for treatment non-completion (p=0.006; OR=3.7; 95% CI=1.5–9.6). Other variables in the multivariable analysis showed no significant relationship with treatment non-completion. While several limitations restricted the study, the findings suggest that the AYA-assisted treatment in Takiwasi may benefit from additional support for patients who are students. Moreover, it is advised to conduct more long-term follow-up of patients in order to gain better insight into the outcome of treatment at an AYA-assisted treatment centre.

It appears that AYA-assisted therapy in a therapeutic community is a feasible type of treatment for addiction, for which further studies should elucidate the role of motivation in relation to socio-demographic factors and type of addiction in the risk of treatment non-completion.

172 adult male prisoners were assessed before and after intervention in a UK prison‐based therapeutic community using psychometric measures of psychological well‐being and offence‐related risk. All mean scores changed significantly in the expected direction. For men tested after 12 months or more, concurrent changes occurred in both domains. Significant relationships were also found between parole board assessments of risk reduction and psychometric changes. The study suggests that interventions with offenders can target offence‐related risk and mental health as clinically compatible treatment targets. Interventions with offenders may need to focus on improvements in mental health to enhance participants' readiness to address risk.

In the previous chapter, the reader will have become familiar with the idea of screening for traumatic experiences within organisations as a way to identify those who may benefit most from interventions and support. In this chapter, I present an overview of the trauma therapy literature in the first instance and then explore some of the debates regarding specific trauma-informed treatments versus general therapeutic approaches. The multicultural competency literature is discussed, and the multicultural orientation approach of cultural humility, cultural opportunity and cultural comfort is highlighted in a practice context. This chapter concludes with a case study vignette that brings it all together with a clinical example of what trauma-informed therapy through a multicultural lens might look like. As such I operationalise choice, collaboration , trust and transparency, and cultural principles from the trauma-informed care literature. Although applied here to specific trauma-informed organisations, some of the methods and processes that I unpack can be used in non-specific organisations where social/case managers are employed and wish to operationalise choice and collaboration in a structured way.

Research suggests that homework compliance within cognitive behavioral therapy is associated with treatment adherence and positive treatment outcomes through generalization of learned skills. The purpose of this paper is to determine whether there were differences in aggression and substance use between participants who did and did not complete therapy homework assignments.

Secondary analyses were conducted using data from Easton et al.’s (2017) randomized controlled trial of substance abuse domestic violence (SADV) treatment among substance dependent intimate partner violence (IPV) offenders. Analyses of covariance were conducted in order to determine whether homework completion had a significant effect on aggression and substance use. Correlational analyses were conducted to determine the association between quality of homework and outcomes.

Participants (n=63) who completed at least two homework assignments had fewer days of alcohol use during treatment compared to those who did not complete any assignments, p=0.03. There was not a difference in the number of days participants engaged in violence based on homework completion. Analyses indicated that those who displayed aggression proximal to alcohol use during treatment completed significantly fewer homework assignments compared to those who did not display aggression proximal to alcohol use (p=0.04).

This research was limited to a sample of male substance using offenders of IPV within the US additional research utilizing a larger sample size in order to investigate differences in homework completion across treatment groups is needed. Further analysis of the barriers to and predictors of homework compliance among this population is recommended.

This research highlights the need for incorporation of homework and further exploration of methods and treatment modalities to ensure homework compliance among substance using male offenders of IPV.

Education researchers have been urged to utilize causal inference methods to estimate the policy effect more rigorously. While randomized controlled trials (RCTs) are the gold standard for assessing causality, RCTs are infeasible in some educational settings, particularly when ethical concerns or high cost are involved. Quasi-experimental research designs are the best alternative approach to study educational topics not amenable to RCTs, as they mimic experimental conditions and use statistical techniques to reduce bias from variables omitted in the empirical models. In this chapter, we introduce and discuss the core concepts, applicability, and limitations of three quasi-experimental methods in higher education research (i.e., difference-in-differences, instrumental variables, and regression discontinuity). By introducing each of these techniques, we aim to expand the higher education researcher's toolbox and encourage the use of these quasi-experimental methods to evaluate educational interventions.

This study aims to investigate outcomes of multisystemic therapy (MST) using the Youth Level of Service/Case Management Inventory (YLS/CMI) – part I.

This study, using a pre-post design, included a sample of 2,123 Norwegian youths (mean age = 14.7, SD = 1.34). The MST team supervisors assessed the YLS/CMI risk factors in addition to five behavioral treatment goals (Lives at home, Attends school/work, No violence/threats, Law-abiding and Drug-free) before and after treatment. In addition, data included responses from parent interviews six months post treatment.

Significant correlations were found between the total and dynamic YLS/CMI change scores and the additive index of behavioral treatment goals. In addition, the YLS/CMI change scores predicted the five treatment goals at the termination of treatment and at six-month follow-up.

The results indicate that the YLS/CMI is a valuable assessment tool for predicting the achievement of MST behavioral goals in adolescents with serious problem behavior.

This study provides an evaluation of the YLS/CMI in a Norwegian context and adds support for continued use of the YLS/CMI in MST.

This paper provides new insights about the YLS/CMI inventory as a tool for examining treatment change in MST. Results show that the YLS/CMI captures relevant risk factors in the youths’ environment.