ABSTRACT
While discussions of evidence-based practices are a predominant trend in the USA, mental health policy can not yet be characterised as data-driven. However, over the past decade, there have been increases in the translation of such research into mental health policy at the federal, state and local levels. Part of that progress has come from a greater understanding by researchers of the kind of information that policy makers can use and from a greater trust among policy makers in the relevance, accuracy and utility of empirical data.
There are three classes of empirical data that appear to have particular salience for mental health policy making in the USA at present. The first class is the randomised clinical trial (RCT). These data mimic the research that drives the introduction of new medications through the Federal Drug Administration, albeit no such federal authority exists for identifying and certifying effective psychosocial interventions. Generally speaking, the accepted criterion for credibility of data from RCTs has been the presence of multiple studies completed by different research groups in different locales. Examples of treatment approaches whose dissemination and implementation have been enhanced through the publication of multiple and diverse RCTs include assertive community treatment (ACT) (Drake et al, 2000; Mueser et al, 2003) and multisystemic treatment (MST) (Henggeler et al, 1997). Generally, these studies begin as academic research, often with federal funding from the National Institute of Mental Health (NIMH), the National Institute on Alcohol Abuse and Alcoholism (NIAAA), the National Institute on Drug Abuse (NIDA) or the Substance Abuse and Mental Health Service Administration (SAMHSA). The results of the RCTs are generally published in widely read research journals, and those publications are used essentially to ‘advertise’ the availability of a treatment that works. Following such
