Hello, I'm working on a study where the goal is to determine the effect of a treatment. Everyone received the treatment, and I have a pre treatment measurement and a post treatment measurement for each person. I have calculated the change between pre and post (specifically, Post minus pre), and am using this as a dependent variable in a regression model. I also have a couple of demographic variables in the model. See code and results below.

Code:
reg change female age

      Source |       SS           df       MS      Number of obs   =        35
-------------+----------------------------------   F(2, 32)        =      5.19
       Model |  2232.18795         2  1116.09397   Prob > F        =    0.0112
    Residual |  6881.38348        32  215.043234   R-squared       =    0.2449
-------------+----------------------------------   Adj R-squared   =    0.1977
       Total |  9113.57143        34  268.046218   Root MSE        =    14.664

------------------------------------------------------------------------------
      change |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      female |  -16.27532   5.262576    -3.09   0.004    -26.99483   -5.555801
         age |  -.4479529   .2852654    -1.57   0.126    -1.029019    .1331137
       _cons |   48.06454   20.07094     2.39   0.023     7.181372    88.94772
------------------------------------------------------------------------------

.

Questions:
1. How to interpret the value of _cons (48.06) ? In a model without the covariates I thought it was the average of the change scores, but with the covariates present the value changed. Can one conclude there is a statistically significant treatment effect here since p=0.023?
2. How to interpret the coefficient for female (-16.28)? is it saying that the treatment was not as effective for females? what does the number actually represent?

thank you in advance for any comments!