Predicting implementation: comparing validated measures of intention and assessing the role of motivation when designing behavioral interventions.
Predicting implementation: comparing validated measures of intention and assessing the role of motivation when designing behavioral interventions.
复制标题
DOI：
10.1186/s43058-020-00050-4
复制
发表时间：
2020
影响因子：
--
通讯作者：
Mandell DS
中科院分区：
文献类型：
--
作者：
Fishman J;Lushin V;Mandell DS
行为意图（捕捉一个人执行行为的动机水平）被认为是影响循证实践（EBP）使用的因果和近端机制。实施研究以不同的方式测量了意图，而且不清楚哪一种最具预测性。有些人通常使用“基于证据的实践”，而另一些人则使用特定的EBP。关于条目条目是否应该用“我打算”、“我将”或“你有多大可能”来表达，以及单个条目是否足够，也存在尚未解决的争论。本研究使用每个词干来指代特定的EBP或“基于证据的实践”，比较了这些常用测量方法预测未来EBP实施的能力。预测效度对因果模型检验和制定有效的实施策略具有重要意义。一项纵向研究招募了70名教师，跟踪他们对两种ebp的使用情况，并比较了测量教师意向的六个不同项目的预测效度。衡量标准的不同之处是，一个项目是指具体的EBP，还是指一般的“基于证据的实践”，以及该项目是否以三种方式之一来表达：“我打算”、“我将”或“你有多大可能”。对于每个项目，线性回归估计了未来行为解释的方差。我们还通过使用不同的系统将项目相互关联并估计EBP实施中的解释方差，比较了单个项目与项目总数的预测效度。根据EBP和意图的测量方式，可解释的实施方差范围从3.5到29.0%。涉及特定EBP的措施，而不是一般的“基于证据的实践”，在实施中占更多的差异（例如，29.0%对8.6%，11.3%对3.5%）。预测的有效性取决于词干的措辞是“我打算”、“我将”还是“你有多大可能”。观察到的意图和EBP使用之间的关联强度将取决于如何测量意图。如果一个项目涉及特定的EBP，而不是一般的EBP，那么这种关联要强得多。为了预测实现，结果支持使用两个或三个指向特定EBP的意图项的集合。一种由单个项目组成的更实用的意图衡量方法也可以预测执行情况。如前所述，这种关系也将根据EBP而变化，这对因果模型测试和实施策略的设计有直接的影响。
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 “evidence-based 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. 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 inter-correlating the items using different stems and estimating the explained variance in EBP implementation. 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.” The observed strength of the association between intentions and EBP use will depend on how intention is measured. The association was much stronger if an item referred to a specific EBP, rather than EBP in general. To predict implementation, the results support using an aggregate of two or three intention items that refer to the specific EBP. An even more pragmatic measure of intention consisting of a single item can also predict implementation. As discussed, the relationship will also vary depending on the EBP, which has direct implications for causal model testing and the design of implementation strategies.