Mental health implementation science: integrating lived experience expertise

Organizational complexities involved with the EBP implementation process attempt to explain the level of success or failure of implementation, as measured by fidelity outcomes. The LAPIS mission is to foster collaboration and expertise in health policy and health systems within an international context. Visit the Library to explore our collection of https://www.nationalacademies.org/read/26809/chapter/5 UW-coauthored implementation science publications and to find examples of key implementation science concepts in action. To learn more about how different fields leverage implementation science. For those new to implementation science, we suggest starting with What is implementation science?

Case Studies of Successful Implementation in Real-World Settings

Emerging research on the Beliefs and Attitudes for Successful Implementation in Schools (BASIS; Lyon et al., 2019a) implementation strategy, designed to target implementer motivation and enhance the effects of training and coaching, points to the potential malleability of implementer perceptions and beliefs. Implementer motivation, perceptions, and engagement in PD and coaching for new initiatives has continued to be an important area of focus (Holmes et al., 2021) in addition to interest in the effects of teacher stress and burnout on classroom practice and teacher and student outcomes (Herman et al., 2020). Although little research has explicitly attended to equity in coaching, it will be important to explore practical, systems issues such as how to ensure that under-resourced school systems can access effective, tailored, and multi-level (as needed) internal and external coaching models. It may also be the case that internal and external coaches can work together in tiered coaching models to build internal coaches’ capacity for longer term workforce sustainability within the school system (Frazier et al., 2019; Ouellette et al., 2024). Trade-offs between costs and funding sources needed, coach capacity or bandwidth, and diversity of training and expertise have been repeatedly pointed out as important considerations for school systems (Flannery et al., 2018; Giordano et al., 2020).

Fig. 2. Levels of change.

In multiple survey-based studies, the majority of patients with MH diagnoses reported interest in MH apps; however, rates of actual use are considerably lower than reported interest (Beard et al. 2019; Lipschitz et al. 2019, 2020; Torous et al. 2014). Recipients can include individuals seeking MH apps outside of a healthcare setting, patients within a healthcare system, and providers recommending apps to their patients. MH apps may help level the playing field by offering access to care for those with economic, geographic, or stigma-related barriers to receiving in-person treatment (Bakker et al. 2016). To be included, sources had to include information relevant to behavioral health app implementation as defined by i-PARIHS domains (features of the innovation, recipients, context, facilitation, and/or measurement of successful implementation). Implementation science involves the “study of methods to promote the systematic uptake of research findings and other evidence-based practices” (Bauer et al. 2015; Eccles and Mittman 2006). The review is guided by the integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) framework and discusses the role of the innovation, its recipients, context, and facilitation in influencing successful implementation of MH apps.

• The methods used in this study draw on frameworks from implementation science and methodological approaches in rapid qualitative analysis.
• While some studies have used vignette-based approaches 18, 50, in general measurement in implementation research is impeded by the complexity of defining and operationalizing major domains of implementation science.
• In follow-up conversations with panel members, nearly all highlighted measure length as a key issue with current implementation measures, raising concerns related to respondent fatigue, assessor fatigue and artificial inflation of internal consistency.
• Our objectives were to develop consensus on best practices for implementation measurement and identify strengths and opportunities in current practice.

While contends that adaptation to change requires organizations to explore new approaches to replace traditional and out-dated practices, capabilities, and knowledge bases. Fidelity refers to the adherence to established program protocols and requirements , and failure to implement with fidelity can compromise the intended effectiveness of the original intervention . Notwithstanding a highly supportive policy environment, strong support from service administrators, and an enthusiastic staff response to training, application of the training and support tools was weaker than anticipated.

In this paper, we sought to reflect on the decade that has passed since Owens and colleagues (2014) articulated an agenda for implementation science in school mental health. Within the context of school mental health, research to date focuses primarily on describing the processes through which schools make de-implementation decisions. In health care more broadly, there has been growing interest in de-implementation, but this work is still in its infancy, focused on identifying existing frameworks (Nilsen et al., 2020), characterizing and developing de-implementation strategies (Ingvarsson et al., 2022; McKay et al., 2018), and defining outcomes (Prusaczyk et al., 2020).

Beyond these more structural barriers to use lies a lack of knowledge regarding app effectiveness. For those with limited data plans, the decision to download an app may mean sacrificing other functionalities on their phone and can therefore be a considerable barrier to use; lack of Wi-Fi access and service disruptions are additional obstacles (Lattie et al. 2020). Providers’ values, beliefs, and motivation are also critical to consider; providers must believe that an app will significantly benefit their patient for them to recommend one (Jacob et al. 2020).

Walker and colleagues (this issue) take on the task of determining where systems should invest in EBP implementation by applying a Geographic Information Systems approach in Washington State. Zimmerman and colleagues (this issue) note that implementation is too often driven by a trial and error approach, and demonstrate that participatory system dynamics modeling can be a powerful tool to improve the implementation planning process. The special issue includes a number of manuscripts that focus on emergent methodologies that are relevant to studying system-level implementation across the four EPIS phases. The special issue concludes with a commentary written by leaders of a large public behavioral health system highlighting their perspectives on system-level implementation and needed areas for research inquiry.