I suggest you think about whether the model should be used rather than can it be used. You do not give any information about the subject of the model or the purpose of the study so I can only answer very generally. The R^2 says you can control or predict 0.2% of the variance in the outcome. Is that a significant change in this field or application? Let's say you are predicting a cost on the order of $100000 with a variance of $10000. The model tells you about $20 of that variance. I cannot think of a field where that sort of change would be considered worth trying to control but maybe there is one.
Generally, before worrying too much about "is this result true", it can be helpful to think about "does it matter if it is true". With such a small effect, I would guess that it is not a practically significant result but only you can make that judgement.
By the way, I would avoid saying a coefficient is significant without stating at what level. The traditional p < 0.05 threshold for significance has no justification beyond popularity and is, in my opinion, often far too generous.