Well, if the data doesn't support the original hypothesis, I guess we could just close our eyes, cross our fingers, and hope the next assessment magically aligns with what we want to see. Or we could, you know, use that brain thing and go with D.
Personally, I'm leaning towards B. Why not just cover all our bases and design an intervention to address every possible function? After all, the behavior is the real problem, not the hypothesis.
Option C is a bit concerning, as continuing to conduct the assessment until the data matches the original hypothesis seems like a recipe for confirmation bias. Better to be open-minded and go with D.
I'm torn between B and D. While a comprehensive intervention package might work, it seems more prudent to adjust the hypothesis to align with the actual functional assessment findings.
Option D is clearly the correct answer. If the functional assessment data doesn't support the original hypothesis, it's time to revise the hypothesis based on the new information gathered.
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