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Think of a particular difficulty and its resolution (for which there is not yet an NLP pattern). Usually these will be nominalizations (“difficulty,” “resolution”), and your modeling task will be to denominalize it into the processing that the person goes through, to find out “How, specifically?” the person does it. If you model a nominalized experience, it will typically be at a sufficiently general level that your model will be applicable to a wider range of people than if you model a simpler and more specific skill. However, usually as the level of generalization increases, so does the complexity of the process you will need to model.
You can model the problem and its resolution separately—or alternately for contrast—and then model a process that will make the transition from one to the other (more on this later). This is how Connirae and I modeled the Grief, Guilt, Shame, and Forgiveness patterns.
Remember that your model can only be as good as the experiences that you choose to model. When modeling grief, for example, we passed over people who said (often with a sigh, and shallow breathing) that they now felt “OK” about the lost person. Instead we chose people who felt (and behaved) joyously when thinking of the lost person. If we had modeled the former, we would have modeled a less-than-optimal solution. However, for practice in learning how to model, modeling a less-than-optimal example can be just as useful.
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