on evaluating health adaptation for a changing climate.

In this video, we illustrate evaluation best practices

for describing health adaptation work using our real world scenarios.

Describing the program is the second step in the CDC evaluation framework.

In this step, we describe clearly what our program does and depict visually

with a logic model the outcomes we expect to achieve as a result of our activities.

In step two, stakeholders use a participatory process to create a logic model,

which visualizes how a health adaptation is expected to work.

We know that health adaptations are complicated by time, scale, and complexity,

creating logic models to describe them as equally complicated.

For example, simple logic models may suggest linearity and causality where it does not exist.

Similarly, depicting complicated relationships, or influential factors

or conditions using logic models can be challenging.

Overcoming challenges and illustrating complex health adaptation cause

for following useful design practices, such as using diverse design elements,

integrating context, and making assumptions explicit.

We can convey complicated adaptations in a number of ways, like placing time

or scale boundaries in and around our model.

Using different types of lines and arrows allows us to show relationships

and the strength of those relationships.

A bolder or more solid line can convey a stronger relationship,

or hypothesize relationship between the items in the boxes.

Varying shades of color and different shapes or symbols can convey different categories

or intensities of connections or relationships.

It is also important to integrate context into the model.

The context of an adaptation is critical in enabling

or hindering activities, outputs, and outcomes.

We can improve our evaluation by incorporating this information by, for instance,

including projected climate data, or vulnerability indices

in our logic model if they are relevant.

Finally, we can be very explicit in noting any assumptions we have

between the boxes or nodes in our logic model.

This will lead to insights about how our stakeholders expect the adaptation to work.

Let's now check in with our practitioners to see how they are using these practices

to describe their health adaptations, the second step of the evaluation framework.

If you would like to revisit our practitioners' evaluation journeys so far,

please refer back to the previous videos in this series.

To describe the new city greening project,

Cassandra's logic model uses two of our design principles.

She is color coding her outcomes and using rainfall projections

to illustrate the project's potential impacts.

By color coding according to different projection scenarios,

Cassandra is able to show stakeholders the different impacts they might expect

to see with the greening project.

Further, this helps her explain how all outcomes in the logic model, especially health outcomes,

may be affected by different rainfall levels.

These design principles also help demonstrate the point

at which greening may not effectively manage stormwater.

For instance, if the city begins experiencing higher rainfall levels,

then city officials may need to revisit decisions about the usefulness

of greening for stormwater management.

Instead, they may decide that resources should be redirected towards more sweeping efforts,

such as installing larger pipes to better manage the volume of stormwater.

Meanwhile, at her state health department,

Elaine continues her evaluation work on wildfire preparedness.

She is using shapes and design elements

to describe how the multitude program crosses different scales.

Because her program includes three major interventions; outreach, training,

and resource assistance, Elaine updates her larger model

to show how the interventions fit together.

She then breaks it into three intervention specific logic models.

To better describe each specific intervention, Elaine uses different shapes

to create a separate, smaller logic model, depicting how each intervention intends

to achieve its specific outcomes.

This nested approach provides a clearer picture of how the program is expected to work.

This design also allows Elaine to show how data from different interventions can feed

into the same outcome category, such as knowledge increase or behavior change.

Now let's check in with Jackson at the county health department

to see how his training evaluation plan is progressing.

After engaging a few additional stakeholders,

Jackson and the work group conduct a logic modeling session to map

out how they expect their home health aide intervention to unfold.

They start by writing down all the activities and intended outcomes on sticky notes

and placing them on the whiteboard to show how they think the program will work.

Jackson then engages his group in a discussion about assumptions.

For example, conducting trainings won't automatically lead to an increase in knowledge.

Underlying factors often hold our logic model pieces together.

The group works to identify underlying assumptions between two key outcomes;

home health aides' increase in knowledge, and the adoption of a new behavior,

such as identifying symptoms of heat related illness.

As the group begins examining the various parts of the logic model

and generating their assumptions, they ask themselves,

to what extent are these assumptions valid?

Following one of the design principles, Jackson suggests making these assumptions explicit

in the logic model by using dashed lines to show the areas of uncertainty.

To further capture the discussion, he adds notes to make their assumptions explicit

and places them at the bottom of the financial logic model.

Clearly noting this information will help the group decide on an appropriate set of standards

and indicators later on in the evaluation process.

Using the best practices described in this video can allow you to tackle common challenges faced

by practitioners in step two of the evaluation framework.

CDC provides many useful resources on describing programs.

For more information, please visit our climate and health evaluation webpage.

In the following video, our three practitioners will begin step three of the evaluation cycle,

focusing the evaluation design for their health adaptation work.