Predicting implementation: comparing validated measures of intention and assessing the role of motivation when designing
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(2020) 1:81
Implementation Science Communications
RESEARCH
Open Access
Predicting implementation: comparing validated measures of intention and assessing the role of motivation when designing behavioral interventions Jessica Fishman1,2,3* , Viktor Lushin1 and David S. Mandell1,3
Abstract Background: Behavioral intention (which captures one’s level of motivation to perform a behavior) is considered a causal and proximal mechanism influencing the use of evidence-based practice (EBP). Implementation studies have measured intention differently, and it is unclear which is most predictive. Some use items referring to “evidencebased practice” in general, whereas others refer to a specific EBP. There are also unresolved debates about whether item stems should be worded “I intend to,” “I will,” or “How likely are you to” and if a single-item measure can suffice. Using each stem to refer to either a specific EBP or to “evidence-based practice,” this study compares the ability of these commonly used measures to predict future EBP implementation. The predictive validity is important for causal model testing and the development of effective implementation strategies. Methods: A longitudinal study enrolled 70 teachers to track their use of two EBPs and compare the predictive validity of six different items measuring teachers’ intention. The measures differ by whether an item refers to a specific EBP, or to “evidence-based practices” in general, and whether the stem is worded in one of the three ways: “I intend to,” “I will,” or “How likely are you to.” For each item, linear regressions estimated the variance in future behavior explained. We also compared the predictive validity of a single item versus an aggregate of items by intercorrelating the items using different stems and estimating the explained variance in EBP implementation. Results: Depending on the EBP and how intention was measured, the explained variance in implementation ranged from 3.5 to 29.0%. Measures that referred to a specific EBP, rather than “evidence-based practices” in general, accounted for more variance in implementation (e.g., 29.0% vs. 8.6%, and 11.3% vs. 3.5%). The predictive validity varied depending on whether stems were worded “I intend to,” “I will,” or “How likely are you to.” (Continued on next page)
* Correspondence: [email protected] 1 Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA 2 Annenberg School, University of Pennsylvania, Philadelphia, USA Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creati
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