Analyzing and graphing the data you get from your behavior program is essential as it tells you whether or not your hypothesis and/or approaches are correct.  As a general rule of thumb you will want to review data on a monthly basis to see how the behavioral change is going; this is also necessary because if the programming is failing to have the desired effect, you can further investigate as to why this is occurring (staff aren't following the plan, any number of environmental variable changes that weren't present when the plan was written, or even that the program itself just does not work.  Below you will see some common examples of how data is graphed (graphing isn't always necessary, but it does make it easier to get an impression of what is going on and other people on the team are usually impressed with a good graph). 

Frequency Analysis

Frequency analysis is the most common type of analysis done by clinicians over the course of a BSP.  From this you can see whether or not the behavior is decreasing due to the approaches put in place.  You can also track replacement behavior frequency (doing this on the same graph can give you a great visual reference as to how the person is responding to the plan.  At the end of the plan duration (usually 12 months in most case) you can complete a percent change analysis to see how the identified behavior(s) changed over the course of the 12 months.  In order to do this you will need to know the percent change formula, which is - new value - old value / old value x 100.  Example of an annual behavior summary with percent change analysis available below.

Cyclical Data and Behavioral Manifestation Graphing

Cyclical data analysis is something that I came up with as a way to view a person's mental health cycles (Bipolar, Seasonal Affective, etc.) in comparison to their problematic behavior frequency (I'm sure I'm not the first to think of this, I've just never come across it before).  The two graphs below are examples of what the cyclical topography and behavioral frequency looks like when laid one on top of the other.  The graph on the left shows a "typical" cycle i.e. consistent changes in mania and depression, and the graph on the left shows a "rapid" cycle, i.e. does not follow the typical, consistent course of a bipolar D/O.  The rapid cycling frequency graph is also different from the typical cycle as it only accounts for certain days of the month instead of each month separately.  As you can see the rapid cycling graph only has data points for every five days, this is because usually rapid cycling changes occur multiple times within a month. 

Trial Data (A-B, A-B-B-A, A-B-A-B)

When doing 1:1 work with a client and testing out interventions to assess their effectiveness, utilizing this type of data tracking will show you the client's response once the intervention is presented.  The schedules I have below are not the only possible schedules that can be used when testing specific interventions with a client; they're just the ones I typically use. 

Blank Frequency Analysis.xlsx Blank Frequency Analysis.xlsx
Size : 22.019 Kb
Type : xlsx
Blank Trial Data Tracking Format.xlsx Blank Trial Data Tracking Format.xlsx
Size : 27.151 Kb
Type : xlsx
Blank Cyclical Analysis.xlsx Blank Cyclical Analysis.xlsx
Size : 31.865 Kb
Type : xlsx
Example Annual Behavioral Summary.docx Example Annual Behavioral Summary.docx
Size : 58.721 Kb
Type : docx

The files to the left are Excel documents that are setup so you can replicate the above graphs. 

 

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