Blocked Goals, Persistent Action: Implementation Intentions Engender Tenacious Goal Striving

Research on goal attainment has demonstrated that people are more likely to reach their goals when they form implementation intentions. Three experiments tested whether implementation intentions lead to tenacious goal striving following blockage of an initial attempt to reach the goal. In all three experiments some participants were instructed to form an implementation intention and other participants were not. Subsequently, the initial goal-directed attempt of all participants was unexpectedly blocked. Experiment 1 found that implementation intentions resulted in more attempts to realize one’s goal. Experiment 2 showed that when participants formed an implementation intention their repeated attempt was acted out as intensely as their first, blocked attempt. Experiment 3 found that implementation intentions still allow people to seize an alternative, more onerous means to realize their intention. These results imply that implementation intention conserve self-regulatory strength. After goal blockage, the remaining strength can be used to continue goal-directed action

Meaningful change definitions: sample size planning for experimental intervention research

Experimental tests of interventions need to have sufficient sample size to constitute a robust test of the intervention’s effectiveness with reasonable precision and power. To estimate the required sample size adequately, researchers are required to specify an effect size. But what effect size should be used to plan the required sample size? Various inroads into selecting the a priori effect size have been suggested in the literature—including using conventions, prior research, and theoretical or practical importance. In this paper, we first discuss problems with some of the proposed methods of selecting the effect size for study planning. We then lay out a method for intervention researchers that provides a way out of many of these problems. The proposed method requires setting a meaningful change definition, it is specifically suited for applied researchers interested in planning tests of intervention effectiveness. We provide a hands-on walk through of the method and provide easy-to-use R functions to implement i

Meaningful change definitions:sample size planning for experimental intervention research

Experimental tests of interventions need to have sufficient sample size to constitute a robust test of the intervention’s effectiveness with reasonable precision and power. To estimate the required sample size adequately, researchers are required to specify an effect size. But what effect size should be used to plan the required sample size? Various inroads into selecting the a priori effect size have been suggested in the literature—including using conventions, prior research, and theoretical or practical importance. In this paper, we first discuss problems with some of the proposed methods of selecting the effect size for study planning. We then lay out a method for intervention researchers that provides a way out of many of these problems. The proposed method requires setting a meaningful change definition, it is specifically suited for applied researchers interested in planning tests of intervention effectiveness. We provide a hands-on walk through of the method and provide easy-to-use R functions to implement i

Changing energy-related behavior: An Intervention Mapping approach

This paper's objective is to apply Intervention Mapping, a planning process for the systematic development of theory- and evidence-based health promotion interventions, to the development of interventions to promote energy conservation behavior. Intervention Mapping (IM) consists of six steps: needs assessment, program objectives, methods and applications, program development, planning for program implementation, and planning for program evaluation. Examples from the energy conservation field are provided to illustrate the activities associated with these steps. It is concluded that applying IM in the energy conservation field may help the development of effective behavior change interventions, and thus develop a domain specific knowledge-base for effective intervention design.Energy-related behavior Behavior change Intervention Mapping