Measures for Predictors of Innovation Adoption

• Published in: Administration and policy in mental health and mental health services research Vol. 42; no. 5; pp. 545 - 573
• Main Authors: Chor, Ka Ho Brian, Wisdom, Jennifer P., Olin, Su-Chin Serene, Hoagwood, Kimberly E., Horwitz, Sarah M.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.09.2015; Springer Nature B.V
• Subjects: Child & adolescent psychiatry; Clinical Psychology; Collaboration; Corporate culture; Decision making; Diffusion of Innovation; Evidence based; Evidence-Based Practice; Health Administration; Health Informatics; Health promotion; Health services; Health Services Research; Humans; Innovations; Measurement; Medicine; Medicine & Public Health; Mental health; Original Paper; Policy making; Primary care; Psychiatry; Public Health; Quality; Researchers; Science; Social networks; Synthesis; Technological change; Technology Acceptance Model; Wisdom; New York; United States > US; Measure; Innovation; Organization; Evidence-based treatments and practices; Adoption
• ISSN: 0894-587X; 1573-3289
• DOI: 10.1007/s10488-014-0551-7

Building on a narrative synthesis of adoption theories by Wisdom et al. ( 2013 ), this review identifies 118 measures associated with the 27 adoption predictors in the synthesis. The distribution of measures is uneven across the predictors and predictors vary in modifiability. Multiple dimensions and definitions of predictors further complicate measurement efforts. For state policymakers and researchers, more effective and integrated measurement can advance the adoption of complex innovations such as evidence-based practices.