title: Instrumentation issues in implementation science.
abstract: BACKGROUND
  Like many new fields, implementation science has become vulnerable to instrumentation issues that potentially threaten the strength of the developing knowledge base. For instance, many implementation studies report findings based on instruments that do not have established psychometric properties. This article aims to review six pressing instrumentation issues, discuss the impact of these issues on the field, and provide practical recommendations.
  
  
  CONCLUSIONS
  This debate centers on the impact of the following instrumentation issues: use of frameworks, theories, and models; role of psychometric properties; use of 'home-grown' and adapted instruments; choosing the most appropriate evaluation method and approach; practicality; and need for decision-making tools. Practical recommendations include: use of consensus definitions for key implementation constructs; reporting standards (e.g., regarding psychometrics, instrument adaptation); when to use multiple forms of observation and mixed methods; and accessing instrument repositories and decision aid tools.
  
  
  CONCLUSIONS
  This debate provides an overview of six key instrumentation issues and offers several courses of action to limit the impact of these issues on the field. With careful attention to these issues, the field of implementation science can potentially move forward at the rapid pace that is respectfully demanded by community stakeholders.
authors.affiliation: Department of Psychology, Virginia Commonwealth University, 806 West Franklin St,, Richmond 23220, VA, USA. martinezrg@vcu.edu.
authors.forename: Ruben G
authors.initials: RG
authors.lastname: Martinez
authors.forename: Cara C
authors.initials: CC
authors.lastname: Lewis
authors.forename: Bryan J
authors.initials: BJ
authors.lastname: Weiner
mesh_terms: D006284:Health Plan Implementation / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D016730:Program Development / Q000379:methods* / Q000706:statistics & numerical data; D011594:Psychometrics / Q000379:methods; D015203:Reproducibility of Results; D012107:Research Design