An updated protocol for a systematic review of implementation-related measures

Cara C. Lewis, Kayne D. Mettert, Caitlin N. Dorsey, Ruben G. Martinez, Bryan J. Weiner, Elspeth Nolen, Cameo Stanick, Heather Halko, Byron J. Powell

Implementation science is the study of strategies used to integrate evidence-based practices into real-world settings (Eccles and Mittman, Implement Sci. 1(1):1, 2006). Central to the identification of replicable, feasible, and effective implementation strategies is the ability to assess the impact of contextual constructs and intervention characteristics that may influence implementation, but several measurement issues make this work quite difficult. For instance, it is unclear which constructs have no measures and which measures have any evidence of psychometric properties like reliability and validity. As part of a larger set of studies to advance implementation science measurement (Lewis et al., Implement Sci. 10:102, 2015), we will complete systematic reviews of measures that map onto the Consolidated Framework for Implementation Research (Damschroder et al., Implement Sci. 4:50, 2009) and the Implementation Outcomes Framework (Proctor et al., Adm Policy Ment Health. 38(2):65-76, 2011), the protocol for which is described in this manuscript. Our primary databases will be PubMed and Embase. Our search strings will be comprised of five levels: (1) the outcome or construct term; (2) terms for measure; (3) terms for evidence-based practice; (4) terms for implementation; and (5) terms for mental health. Two trained research specialists will independently review all titles and abstracts followed by full-text review for inclusion. The research specialists will then conduct measure-forward searches using the "cited by" function to identify all published empirical studies using each measure. The measure and associated publications will be compiled in a packet for data extraction. Data relevant to our Psychometric and Pragmatic Evidence Rating Scale (PAPERS) will be independently extracted and then rated using a worst score counts methodology reflecting "poor" to "excellent" evidence. We will build a centralized, accessible, searchable repository through which researchers, practitioners, and other stakeholders can identify psychometrically and pragmatically strong measures of implementation contexts, processes, and outcomes. By facilitating the employment of psychometrically and pragmatically strong measures identified through this systematic review, the repository would enhance the cumulativeness, reproducibility, and applicability of research findings in the rapidly growing field of implementation science.