Techniques For Unlearning Old Behaviors: Self-Monitoring

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Self-Monitoring involves learning to pay careful and systematic attention to your problem behaviors and habits, and to the stimuli that trigger them into action. There are two types of self-monitoring we can distinguish: qualitative monitoring, and quantitative monitoring. Qualitative monitoring involves paying attention to the quality of things that are happening (how they make you feel, what they look like, etc.). Quantitative monitoring, on the other hand, involves counting things. Though both kinds of monitoring are important, self-monitoring works best when you approach it in a primarily quantified way: deciding what behaviors and habits you will monitor, figuring out a reasonable way to count or measure the occurrence of each behavior or habit, and then actually counting the occurrence of each and every behavior using your measurement system. When self-monitoring is approached in this formal quantitative style, you gain, sometimes for the first time ever, accurate measurements of how you are actually behaving, and how commonly various triggering stimuli occur that set your bad habits or behaviors in motion. You may have previously had a vague idea of the extent of your problem, but now you have an accurate measurement which you can use as a baseline against which to measure progress. You can, of course, self-monitor in a less quantitative way, but doing so fails to give you a much more accurate picture of your problem than you previously had, and so is generally not worth the effort.

You need to have a system in place to self-monitor well. Your system should describe what you will monitor (behaviors, triggers), how often you will monitor, and how you will record your observations. Let’s say that you want to monitor your smoking habit. The obvious measurement that has meaning for your smoking habit is how many cigarettes you smoke in a given day, so you might decide to record every time you smoke a cigarette. You might also want to record triggering events that lead to your smoking. Recording this data doesn’t have to be complicated. You can simply write down an entry in a small notebook you carry with you every time you light up. As you record the cigarette lighting event, you might also jot down your sense of what led you to light up at that moment. Your record might look like this:

Smoking Log

Date

Time

Triggers

Nov 28

9:28 am

Nervous feeling, thought lighting up would help.

Nov 28

10:05 am

Coffee break!

Though recording an event every time it happens is best from an accuracy point of view, it is not always practical to do so. You can alternatively decide to count events regularly after some amount of time has past (every three hours, say), or in the evening when you get home from work. You can set an alarm to remind you to make your recordings.

Sometimes the behaviors you want to count occur too rapidly to make recording in real time practical, and too commonly to make retrospective recording accurate. Say, for instance, you were interested in counting the number of times you said “um” during a speech you were making. It would be difficult to give the speech if you were stopping every moment to make a record, and too difficult to keep a good count for retrospective recording as well. In this sort of case, make a recording of your speech, and then listen to it later on, recording the “um’s” as you listen.

Its easy to count events, but sometimes you want to capture more data than just that an event happened. You might want to record how intensely you were feeling the need to have a cigarette prior to lighting up, as well as the fact that you did light up, for example. When this is the case, you need to decide on a scale for measuring the intensity of your smoking urge before you start monitoring, and then use that scale consistently throughout the recording period.

The final part of a self-monitoring effort involves making sense out of your data. It is hard to make sense out of a list of rows in your logbook. Patterns in your observations will be much more easy to pick out if you represent them in the form of a graph. One kind of useful graph for representing simple data counts is called a Histogram. To make a histogram, simply sum up the number of times you smoked on each day, and then draw a bar that many units off the horizontal axis of your graph over a column representing each day.

Graphs can be constructed by hand on graph paper, or in an automated fashion inside spreadsheet programs like Microsoft Excel or OpenOffice.org’s free Calc program.

Another type of tracking site that can be used to create new habits/behaviors is HabitForge. The free-to-use site allows people to set a goal for a behavior/habit and have assistance in tracking whether they are meeting that each day for 21 days (the time research has shown it takes to form a habit).  Users will receive a customized daily email asking how they did and can click “yes” or “no” daily. Succeed for 21 days, and the new action will be easier to make into a habit. Skip a day and the clock starts over at day one.

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