Background Calls have been made for greater application of the decision sciences to investigate and improve use of research evidence in mental health policy and practice. This article proposes a novel method, “decision sampling,” to improve the study of decision-making and research evidence use in policy and programmatic innovation. An illustrative case study applies the decision sampling framework to investigate the decisions made by mid-level administrators when developing system-wide interventions to identify and treat the trauma of children entering foster care. Methods Decision sampling grounds qualitative inquiry in decision analysis to elicit information about the decision-making process. Our case study engaged mid-level managers in public sector agencies (n = 32) from 12 states, anchoring responses on a recent index decision regarding universal trauma screening for children entering foster care. Qualitative semi-structured interviews inquired on questions aligned with key components of decision analysis, systematically collecting information on the index decisions, choices considered, information synthesized, expertise accessed, and ultimately the values expressed when selecting among available alternatives. Results Findings resulted in identification of a case-specific decision set, gaps in available evidence across the decision set, and an understanding of the values that guided decision-making. Specifically, respondents described 14 inter-related decision points summarized in five domains for adoption of universal trauma screening protocols, including (1) reach of the screening protocol, (2) content of the screening tool, (3) threshold for referral, (4) resources for screening startup and sustainment, and (5) system capacity to respond to identified needs. Respondents engaged a continuum of information that ranged from anecdote to research evidence, synthesizing multiple types of knowledge with their expertise. Policy, clinical, and delivery system experts were consulted to help address gaps in available information, prioritize specific information, and assess “fit to context.” The role of values was revealed as participants evaluated potential trade-offs and selected among policy alternatives. Conclusions The decision sampling framework is a novel methodological approach to investigate the decision-making process and ultimately aims to inform the development of future dissemination and implementation strategies by identifying the evidence gaps and values expressed by the decision-makers, themselves.
A family's journey in understanding their child's behaviors in relation to Autism Spectrum Disorders (ASD) frequently begins with screening. This study aimed to characterize the interpretive processes that unfold for parents. We employed longitudinal interviews with 19 families engaged in a community-based multi-stage screening protocol. Parents participated in 1-6 interviews dependent upon children's length of engagement in the screening protocol; data were analyzed through modified grounded theory. Parents who moved towards understanding their child's behaviors as ASD expressed (1) sensitization to ASD symptoms, (2) differentiation from other developmental conditions, and (3) use of the ASD diagnosis to explain the etiology of concerning behaviors. Identifying interpretive processes involved during ASD screening provides new opportunities for shared decision-making.
Background To “model and simulate change” is an accepted strategy to support implementation at scale. Much like a power analysis can inform decisions about study design, simulation models offer an analytic strategy to synthesize evidence that informs decisions regarding implementation of evidence-based interventions. However, simulation modeling is under-utilized in implementation science. To realize the potential of simulation modeling as an implementation strategy, additional methods are required to assist stakeholders to use models to examine underlying assumptions, consider alternative strategies, and anticipate downstream consequences of implementation. To this end, we propose Rapid-cycle Systems Modeling (RCSM)—a form of group modeling designed to promote engagement with evidence to support implementation. To demonstrate its utility, we provide an illustrative case study with mid-level administrators developing system-wide interventions that aim to identify and treat trauma among children entering foster care. Methods RCSM is an iterative method that includes three steps per cycle: (1) identify and prioritize stakeholder questions, (2) develop or refine a simulation model, and (3) engage in dialogue regarding model relevance, insights, and utility for implementation. For the case study, 31 key informants were engaged in step 1, a prior simulation model was adapted for step 2, and six member-checking group interviews (n = 16) were conducted for step 3. Results Step 1 engaged qualitative methods to identify and prioritize stakeholder questions, specifically identifying a set of inter-related decisions to promote implementing trauma-informed screening. In step 2, the research team created a presentation to communicate key findings from the simulation model that addressed decisions about programmatic reach, optimal screening thresholds to balance demand for treatment with supply, capacity to start-up and sustain screening, and availability of downstream capacity to provide treatment for those with indicated need. In step 3, member-checking group interviews with stakeholders documented the relevance of the model results to implementation decisions, insight regarding opportunities to improve system performance, and potential to inform conversations regarding anticipated implications of implementation choices. Conclusions By embedding simulation modeling in a process of stakeholder engagement, RCSM offers guidance to realize the potential of modeling not only as an analytic strategy, but also as an implementation strategy.
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