?? What's the same? The real part of the pole tells you whether the system is stable. Any pole in the right-hand side of the diagram tells you that it'll be unstable. More specifically the magnitude of the real part of the pole gives you the exponential envelope which accompanies the sinusoidal response.
Why is there a need to express the transfer function in terms of complex roots? If you want to do so then you're unnecessarily complicating the problem. But I'll give it a shot. First express the TF in terms of http://www.swarthmore.edu/NatSci/echeeve1/Ref/LPSA/PartialFraction/PartialFraction.html" .
\frac{1}{(s-a-jb)(s-a+jb)} = \frac{-j\frac{1}{2b}}{s-a-jb} + \frac{j\frac{1}{2b}}{s-a+jb}.
Taking the inverse laplace transform of both sides, we apply the formal definition of it, resulting in a http://en.wikipedia.org/wiki/Inverse_Laplace_transform" .
Since we know the roots (or singularities) are at a\pm jb, we can evaluate the line integral by applying Cauchy's residue theorem ie. for example inverse Laplace transform the first term:
L^{-1} \left( \frac{-j\frac{1}{2b}}{s-a-jb} \right) = -j\frac{1}{2b} \cdot \frac{1}{j2\pi} \oint_c e^{st} \frac{1}{s-a-jb} ds = -j\frac{1}{2b} \cdot \frac{1}{j2\pi} \cdot j2\pi Res(e^{st}F(s),a+jb)
\text{Res}(F(s)e^{st},a+jb) = e^{(a+jb)t}.
Using this result, we plug this back into the expression above:
L^{-1} \left( \frac{-j\frac{1}{2b}}{s-a-jb} \right) = -\frac{1}{2b} e^{t(a+jb)}.
Applying the same procedure for the other partial fraction term gives the following result:
-j\frac{1}{2b}e^{t(a+jb)} + j\frac{1}{2b}e^{t(a-jb)} = -\frac{1}{b}e^{at} \frac{1}{j2} (e^{jbt}-e^{-jbt}) = -\frac{1}{b}e^{at}\sin(bt)
All the above was done using the fundamental definition of the Laplace inverse transform.
Now you should be able to see from the above that the time-domain form of the response is stable only if a<0, since otherwise the e^(at) term grows exponentially. If the poles are strictly imaginary ie. s=jw, then e^(at)=1 where a=0 and you have a marginally stable where the system responses oscillates, which is consistent with what the textbook says.
Hope this helps.