Logic model

Logic models are hypothesized descriptions of the chain of causes and effects leading to an outcome of interest (e.g. prevalence of cardiovascular diseases, annual traffic collision, etc.).

[4][5] Domains of application are various, e.g. waste management,[6] poultry inspection,[7] business education,[8] heart disease and stroke prevention.

Citing Funnell and Rogers's account (2011),[12] Joy A. Frechtling's (2015) encyclopedia article[2] traces logic model underpinnings to the 1950s.

By making clear the intended outcomes and the causal pathways leading to them, a program logic model provides the basis upon which planners and evaluators can develop a measurement plan and adequate instruments.

In addition, the pathways of numerous outcomes are still largely misunderstood due their complexity, their unpredictability and lack of scientific / practical evidences.

The intervention mapping approach of Bartholomew et al.[11] makes an extensive use of the logic model through the whole life-cycle of a health promotion program.

The Progressive Outcomes Scale Logic Model (POSLM) approach was developed by Quisha Brown in response to the racial wealth gap [exacerbated by the COVID-19 pandemic] to aid organizations in the immediate need to add a racial equity focus when developing program logic models.

The POSLM approach makes use of the logic model with a strong focus on tracking progressive improvement towards racial disparity outcomes.

These KPIs are specific to the racial disparity issues which the population served identifies with (i.e. low reading, financial literacy, unemployment, etc).

This helps to ensure that the logic model remains focused on improving the real-time needs of people to remove racial barriers.