Mental Model Mapping for Behavioral Program Design

Behavioral instruments are vital to improve intervention efficacy; and mental mapping seems to be a prerequisite to profile decision strategies that affect interventions.
Published in Social Sciences
Mental Model Mapping for Behavioral Program Design

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The 'Why' Question: In specific socioeconomic development programs, achieving perpetual program efficiency requires a better diagnosis of the individual’s truthful problems in the design stage to employ behaviorally informed interventions. Essentially, the causes of these problems are rooted in the individual’s mental model; behavioral design, in this context, can lead to better-diagnosed solutions using insights from the mental mapping of the target group. Findings from recent studies further suggest that incorporating a behavioral approach into research design can significantly improve a program’s effectiveness; and mental mapping seems to be a prerequisite of profiling decision strategies that affect interventions.

Mental Model Mapping: Successful programs are more likely to rely on a deep understanding of the target group and a policymaker’s mental models (or cognitive maps) and the corresponding decision mechanism. A mental model basically explains an individual’s reasoning, inferring, and decision-making process that influences the anticipated outcomes. For example, an individual with a bias for the present, who likes immediate benefits from consumption, may choose non-healthy food that comes from his or her family’s and/or peers’ food habits. In some cases, less socially inclusive groups with essentially lower social trust have adopted a lower contribution rule for facilitating public concerns and charitable giving. In the case of developing economies, community preference and social learning influence the end user’s mental model to adopt new technologies. These problems have long been studied by mainstream behavioral economics; however, there is the potential scope of mapping mental models to identify individual-level behavioral research problems.

Including behavioral aspects, mental modeling seems an essential tool for related fields of decision analysis, e.g., risk and uncertainty, choice architecture, strategic management, marketing, online auction, machine learning, and system dynamics. Like any individual, professionals and policymakers could also be affected by their cognitive biases such as mindset, training, and social and economic contexts which certainly affect their designed policies and programs. Analyses of mental models, of course, can help reduce the biases of internal deliberations. Either for individuals or professional groups, model profiling is now considered an important prerequisite to designing an effective behavioral model.

Behavioral Program Design: Behavioral design, by concept, is a better-diagnosed cognitive insights-based solution that provides valuable leads to the higher design efficacy of policies and subsequent programs. The central argument for behavioral design has twofold issues: i) improved design–based on the mental model, and ii) effective and long-term intervention with internal and external validation.

As behavioral design deals with an individual’s thinking process and choice patterns, analysis of the respective mental model is of particular importance. We can generalize this process into four consecutive steps: (1) problem identification and causality analysis, (2) mapping the target group’s mental model, (3) supportive behavioral strategies employed based on the type of the mental model, and (4) program evaluation which detects the behavioral design (effectiveness evaluation & redesign), determining whether it is more effective as a whole (see Fig. 1). The use of behavioral insights in the early stage of any policy-relevant program design would be more effective sooner rather than later.

Fig. 1: Mental Model-based Behavioral Program Design Process

Most notably, the inclusion of behavioral interventions makes the programs more efficient at minimum cost than launching additional programs, which is not uncommon in both developed and developing countries. We can use endorsed findings from behavioral design to other potential aspects of socio-economic concerns, where common traditional tools are found less functional, continuously and considerably so.

Policy Implications: It can be argued that a mental-model based behavioral program design approach has three strategic policy implications. First, governments, especially of developing and less developed countries can set a rule of employing mental modeling and a behavioral design approach for facilitating public policies and socio-economic development programs as deemed appropriate. Interdisciplinary research considering the views of sociologists and political scientists together with the insights from traditional and behavioral economics are of particular importance. These, in turn, can generate widespread impacts and returns in the long run. Also, insights from psychological anthropology can further improve the behavioral design because it can reveal the complex interactions of human behavior and culture.

Second, policymakers, development professionals, and researchers are systematically affected by their cognitive biases. Obviously, they are more prone to make mistakes because of their subjective beliefs in analyzing existing information in hand and program evaluation. As effective policies and programs depend substantially on a rigorous understanding of their underlying mental models, neutralization measures and information updating are required for bias-free policy and program design.

Third, funding organizations can insist that receiving governments and institutions incorporate behavioral design where the earlier program’s outreach and effectiveness were evidently low. Corresponding authorities for particular programs can assign a behavioral policy designer if these interventions are found effective in the pilot stage. However, capacity building inputs should be considered initially, especially for developing and less developed countries. To do so, collaborative efforts of policymakers, funding organizations, industry partners, academia, and think tanks are essential for spreading this approach as a component of research design. These would be a potential corrective measure for the case of analysis paralysis.

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