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Community Coaltions |
All of these simple everyday examples involve baselines. Sometimes people may call them other names: reference points, adaptation levels, anchors, or norms, for example. But whatever we call them, we all have them and we all use them. In a way, they are essential for all of us in making judgments about people and things. Without baselines, it would be much harder to navigate our way through the world.
Most everyday baselines are casual and informal. We may not even notice them; we certainly don't measure them. In making decisions about community actions, and about public policies in general, however, we sometimes take baselines a lot more seriously. For example, every month, the Consumer Price Index is released by the Bureau of Labor Statistics. The numerical value of that index, which tells us whether the cost of living is going up or down, relies on a baseline. Likewise, many other indices, including stock indices (e.g., the Dow Jones), local quality of life indicators, etcetera, rely on baseline measures.
Interpretations against a baseline are the way most policy decisions get made. If a new law has raised the penalties for drunk driving, has drunk driving decreased? What kinds of activities will draw visitors to local parks, based on data we already have on park use? Good decisions in these cases and countless examples more will depend on good collection and utilization of baseline data. Comparison to a baseline is the standard against which policy success is judged.
Experts generally consider determining baseline measures of behavior to be the first phase in any sort of behavior modification program, followed by implementation of the program and finally a follow-up phase in which the results are measured and analyzed.
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Example: An anti-gang project for urban high school students Some indicators that you might want to consider using as your baseline measures could be rates of:
If one of the things your group is planning is an after-school discussion group, then the first indicator would probably be a good one for you to use as a baseline measure, because it should give you a good idea of the numbers of students who might be likely to participate in an after-school activity. |
Next, find measurements on those indicators.
Once you've chosen indicators, decide exactly what you're going to measure, and for how long. For example, will you measure violent gang-related incidents on school property during the school year? Will you measure the number of alcohol-related automobile fatalities over a four-week period? It's possible that someone else has already measured these things if so, then you'll just need to verify (and, if necessary, update) the information. Otherwise, you or someone else will need to go out there and measure them. See Chapter 3, Section 4: Collecting Information about the Problem for more information on how to gather the specifics you'll need.
Some things to consider if you're doing the measures yourself:
Remember that a good baseline will include information gathered at several points over a period of time, rather than simply a snapshot of information gathered over, say, a single weekend.
Let's say that you now have data for your baseline measure, as well as data collected at a handful of different times afterwards. How do you make sense of this information? First, you should know a bit about the different types of baseline data patterns.
When you present your baseline measures in graph form, you can learn a lot about how bad a problem is in your community and whether now is a good time to introduce any sort of intervention to change it.
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Example: Baseline data patterns
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Stable baselines
With a stable baseline, there's no evidence of upward or downward trends; things may fluctuate a little over time but for the most part the data points fall into a pretty tight range.
A stable baseline is the best basis for starting your project. If rates of whatever it is you're measuring have stayed pretty stable over a long period of time before you start, you can be more certain that changes after your intervention begins are really a result of your efforts.
Ascending and descending baselines
As you might guess from the names, an ascending baseline means that whatever is being measured has steadily increased over time, and a descending baseline means it has decreased.
Unstable or variable baselines
When the data points range all over the place and there are no clear trends, you have an unstable or variable baseline. With a variable baseline, it's usually not a good idea to introduce any sort of intervention, because the variations in the baseline make it too hard to tell whether any changes will be a direct result of the intervention.
When you have a more complex baseline, you need to give some serious consideration whether the health problem is increasing or decreasing.
Say, for example, that the baseline measure you're graphing stands for the rate of teen smoking in your county. If the baseline is descending, indicating that fewer and fewer teens are smoking, then you may want to hold off on conducting any sort of intervention. However, if the baseline is ascending, showing that teen smoking is on the rise, then conducting some sort of intervention is probably the right thing to do. It may not be as easy to tell what the effect of your intervention is as it would be with a stable baseline, but knowing that the problem is increasing is plenty of reason to take action!
Decide which problem(s) to address
Based on the data, decide what problem(s) should most be addressed by your group or coalition. What looks like it most needs to be dealt with? Is it something you can reasonably expect to be able to change? See Chapter 3, Section 5: Analyzing Community Problems for some ideas on how to do this.
Identify primary targets of the intervention
This means deciding who your intervention will be aimed at a given group of people? An institution? Decide how their behavior helps produce and maintain the problem. Figure out what your research results suggest about relationships between the problem (s) and the behaviors of the targeted group.
Develop an action plan
For more help designing an action plan, see Chapter 8, Section 5: Developing an Action Plan and Section 7: Identifying Action Steps in Bringing About Community and Systems Change.
Begin your intervention
Get going! With the knowledge you've gained from checking your baseline measures, you will have a much better chance of making real changes in your community, and you can use those measures to monitor your success.
Using your baseline measures to figure out how prevalent any problems and positive tendencies are in your community can be very effective in helping you to monitor how the effect your efforts are having. By giving you one way to measure the success of your programs, baseline measures can be enormously helpful to your efforts.
Resources
Centers for Disease Control (1987). Guidelines for AIDS Prevention Program Operations [Online].
Cooper, J.O., Heron, T.E., and Heward, W.L. (1987). Applied behavior analysis. New York: Macmillan Publishing Company.
Martin, G. and Pear, J. (1992). Behavior modification: What it is and how to do it. Eaglewood Cliffs, N.J.: Prentice-Hall.
Sulzer-Azaroff, B. and Mayer, G. R. (1986). Achieving educational excellence using behavioral strategies. New York: CBS College Publishing.
Sundel, M. and Sundel, S. S. (1975). Behavior modification in the human services: A systematic introduction to concepts and applications. New York: John Wiley & Sons.
Tyler Norris Associates, Redefining Progress, and Sustainable Seattle. (1997). The community indicators handbook: Measuring progress toward healthy and sustainable communities. Boulder, CO: Tyler Norris Associates.
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