نظارت بر پیشرفت مشتری و بازخورد در بهداشت روانی بر اساس مدرسه

Research in children’s mental health has suggested that emotional and behavioral problems in are inextricably tied to academic difficulties. However, evidence-based programs implemented in school-based mental health tend to focus primarily on treatment practices, with less explicit emphasis on components of evidence-based assessment (EBA), such as progress monitoring and feedback. The current paper describes two studies that incorporated standardized assessment and progress monitoring/feedback into school-based mental health programs. Barriers to implementation are identified, recommendations for clinicians implementing EBA in the school setting are provided, and examples of mental health and academic indicators are discussed.

Emotional and behavioral problems represent significant barriers to student academic success (Adelman and Taylor, 2000 and Shriver and Kramer, 1997). Unfortunately, the majority of youth experiencing mental health problems do not receive indicated interventions (Merikangas et al., 2011). Given that children and adolescents spend more time in school than any other setting outside of the home (Hofferth & Sandberg, 2001), providing mental health care in the education sector has the potential to enhance the likelihood that students will receive services (Lyon, Ludwig, Vander Stoep, Gudmundsen, & McCauley, 2013). This stands in contrast to other service sectors, such as community mental health settings, where access is largely parent-mediated and a variety of barriers to care have been identified, particularly for youth from historically underserved ethnic and economic minority groups (Cauce et al., 2002 and Yeh et al., 2003). Indeed, of the youth who receive mental health services, 70% to 80% receive them in the school context (Farmer et al., 2003), and research has documented that youth from ethnic and cultural minority backgrounds are just as likely to access school services as their Caucasian counterparts (Kataoka et al., 2007 and Lyon et al., 2013). Beyond their accessibility, school-based mental health (SBMH) programs allow for early screening, assessment, and intervention, as well as more opportunities for direct behavioral observation than traditional clinic settings (Owens & Murphy, 2004). It is for many of these reasons that the national emphasis on SBMH has continued to grow (Franken, 2013 and Protect our Children, our Communities by Reducing Gun Violence, 2013). Nevertheless, academic goals and mental health services lack a common language or unified system for tracking and communicating meaningful student progress across teachers, administrators, and service providers, resulting in inadequate alignment between the two (Center for Mental Health in Schools, 2011). Indeed, recent research has suggested that mental health–school integration may be enhanced through the implementation of data-driven processes in which outcomes relevant to emotional, behavioral, and academic functioning are routinely monitored (Lyon et al., 2013 and Prodente et al., 2002). The recent, growing emphasis on evidence-based assessment (EBA) tools and processes in mental health provides an opportunity to maximize or improve mental health/school integration. EBA can be defined as “assessment methods and processes that are based on empirical evidence in terms of both their reliability and validity as well as their clinical usefulness for prescribed populations and purposes” (Mash & Hunsley, 2005, p. 364). Indeed, there is increasing evidence to suggest that components of EBA—such as monitoring and feedback—may represent stand-alone and worthwhile quality improvement targets for youth mental health services (Bickman et al., 2011). Nevertheless, in schools, EBA-relevant data remain underutilized, in part because the infrastructure for supporting their collection and use are underdeveloped (Lyon et al., 2013 and Weist and Paternite, 2006). In particular, when combined with practice monitoring—recording interventions in tandem with progress indicators—progress monitoring and feedback provide an opportunity for evaluating real-time response to intervention and making as-needed adjustments. Unfortunately, few approaches to accomplishing these goals in SBMH have been articulated. EBA Principles and Evidence Notably, the definition of EBA provided above includes both methods and processes for care. When referencing methods, EBA includes (a) standardized assessment tools, which have empirical support for their reliability, validity, and clinical utility ( Jensen-Doss & Hawley, 2010), and (b) idiographic assessment approaches, defined as quantitative variables that have been individually selected or tailored to maximize their relevance for a particular individual ( Haynes, Mumma, & Pinson, 2009). Idiographic targets may include approaches to goal-based outcome assessment, including Goal Attainment Scaling ( Cytrynbaum et al., 1979 and Michalak and Holtforth, 2006) and, more recently, “top problems” assessments ( Weisz et al., 2011 and Weisz et al., 2011). In contrast, EBA processes may include (a) initial assessment for the purposes of problem identification/diagnosis, and treatment planning, (b) progress monitoring (a.k.a., routine outcomes monitoring; Carlier et al., 2012) over the course of intervention, and/or (c) feedback to clinicians or clients about the results of initial or ongoing assessments (e.g., reporting on progress that has been achieved). Feedback to clinicians is a central component of measurement-based care, while client feedback supports alignment and shared decision making with service recipients. Figure 1 provides an overview of and organizing structure for the method and process components of EBA. Although progress monitoring and feedback are included as discrete processes, it should be noted that monitoring without feedback is unlikely to lead to service quality improvements ( Lambert et al., 2003). The primary focus of the current paper will be on describing school-based EBA processes, particularly approaches to progress monitoring and feedback over the course of an intervention in SMH, but will also address key EBA methods for use in schools in the context of monitoring. Although the constructs discussed have broad applicability across populations, they are specifically relevant to mental health service delivery in the education sector. Full-size image (36 K) Figure 1. Overview of evidence-based assessment methods and processes. Figure options Progress monitoring is typically conceptualized as influencing client outcomes through feedback and its impact on clinician behavior. Feedback Intervention Theory (FIT; Kluger, & DeNisi, 1996) posits that behavior is regulated by comparisons of feedback to hierarchically organized goals. Feedback loops to clinicians have the effect of refocusing attention on new or different goals and levels of the goal hierarchy, thereby producing cognitive dissonance and behavior change among professionals (Riemer, Rosof-Williams, & Bickman, 2005). As clinicians receive information about client symptoms or functioning (e.g., high distress) that is inconsistent with their goal states (i.e., recovery from a mental health problem), FIT suggests that their dissonance will motivate them to change their behavior in some way to better facilitate client improvement (e.g., applying a new or different intervention technique or engaging in additional information gathering). Use of repeated standardized assessment tools to track mental health outcomes and provide feedback to providers has been associated with youth and adult client improvements and reductions in premature service discontinuation (e.g., Bickman et al., 2011, Lambert et al., 2003, Lambert, 2010 and Lambert, 2011), and may enhance communication between therapists and clients (Carlier et al., 2012). Nevertheless, despite these benefits, less is known about idiographic progress indicators and their influence on clinician behavior. In addition, research has consistently found that community-based clinicians are relatively unlikely to use EBA tools, and even less likely to engage in EBA processes such as incorporating them into their treatment decisions (Garland et al., 2003, Hatfield and Ogles, 2004 and Palmiter, 2004).