title: A conceptual model for understanding effective coalitions involved in health promotion programming.
abstract: Funding agencies are increasingly focused on community coalitions as effective entities for promoting public health programs. Yet, there has been no conceptual model for understanding how effective coalition infrastructure works to facilitate a learning environment, wherein coalition members and leaders receive ongoing training and technical assistance needed to accomplish their external programming goals. This article presents a conceptual model for measuring the internal effectiveness of coalitions [Internal Coalition Outcome Hierarchy (ICOH)]. The ICOH model served as the basis for development of the evaluation instrument, Internal Coalition Effectiveness, which measures internal coalition effectiveness based on achievement of organizational outcomes at each of the model's seven hierarchical levels. The ICOH conceptual model has broad application for public health nurses who are frequently called on to serve as evaluators for community coalitions engaged in health programming. The model has implications for evaluators to use in teaching coalition members and leaders about their internal strengths and areas for improvement, so that coalitions can develop more effective internal structures and thereby promote long-term sustainability.
authors.affiliation: University of Nebraska Medical Center, College of Nursing, Omaha, NE 68198-5330, USA. mecramer@unmc.edu
authors.forename: Mary E
authors.initials: ME
authors.lastname: Cramer
authors.forename: Jan R
authors.initials: JR
authors.lastname: Atwood
authors.forename: Julie A
authors.initials: JA
authors.lastname: Stoner
mesh_terms: D003256:Community Participation; D003299:Cooperative Behavior; D006265:Health Care Coalitions / Q000458:organization & administration*; D006290:Health Planning Technical Assistance / Q000458:organization & administration*; D006293:Health Promotion / Q000458:organization & administration*; D006801:Humans; D017146:Models, Organizational