I am trying to find out the treatment effect using propensity score matching. I have a query on the choice of covariates required for determining the propensity scores. As mentioned in the previous literature, I understood that only the background variables are to be included which is not affected by treatment. In the pscore command in stata, I have incorporated such controls but none of them are significant. In this case, will this approach work?

Also, I have another query regarding the balancing property. According to the pscore command, the results show that the final number of blocks is 5. However, the detailed output only shows two blocks - 5 and 4

Code:
**************************************************** 
Algorithm to estimate the propensity score 
**************************************************** 


The treatment is dumtui

  (firstnm) |
     dumtui |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |         40        7.29        7.29
          1 |        509       92.71      100.00
------------+-----------------------------------
      Total |        549      100.00



Estimation of the propensity score 

Iteration 0:   log likelihood = -143.27483
Iteration 1:   log likelihood = -140.05137
Iteration 2:   log likelihood = -140.01568
Iteration 3:   log likelihood = -140.01567

Probit regression                                 Number of obs   =        549
                                                  LR chi2(7)      =       6.52
                                                  Prob > chi2     =     0.4807
Log likelihood = -140.01567                       Pseudo R2       =     0.0227

------------------------------------------------------------------------------
      dumtui |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
  logfeediff |  -.4351585   .3457078    -1.26   0.208    -1.112733    .2424163
     meaninc |   .0000241    .000032     0.75   0.452    -.0000386    .0000868
     engdiff |   .7431845   .4173667     1.78   0.075    -.0748392    1.561208
    profdiff |    .020041   .5687919     0.04   0.972    -1.094771    1.134853
     govprop |  -.0285287   .5192992    -0.05   0.956    -1.046337    .9892791
   propunemp |  -.2523839   .6641851    -0.38   0.704    -1.554163    1.049395
propmaleat~d |   .0205683   .5769323     0.04   0.972    -1.110198    1.151335
       _cons |   4.965179   2.654825     1.87   0.061     -.238183    10.16854
------------------------------------------------------------------------------



Note: the common support option has been selected
The region of common support is [.79588694, .99533472]



Description of the estimated propensity score 
in region of common support 

                 Estimated propensity score
-------------------------------------------------------------
      Percentiles      Smallest
 1%     .8346569       .7958869
 5%     .8778466       .8202823
10%     .8917124       .8244704       Obs                 549
25%      .910725        .830139       Sum of Wgt.         549

50%     .9283149                      Mean           .9271435
                        Largest       Std. Dev.      .0288954
75%     .9503249       .9760316
90%     .9618948       .9777905       Variance       .0008349
95%     .9658854       .9830645       Skewness      -.8160764
99%     .9709594       .9953347       Kurtosis       4.133895



****************************************************** 
Step 1: Identification of the optimal number of blocks 
Use option detail if you want more detailed output 
****************************************************** 


The final number of blocks is 5

This number of blocks ensures that the mean propensity score
is not different for treated and controls in each blocks



********************************************************** 
Step 2: Test of balancing property of the propensity score 
Use option detail if you want more detailed output 
********************************************************** 


The balancing property is satisfied 


This table shows the inferior bound, the number of treated
and the number of controls for each block 

  Inferior |
  of block |   (firstnm) dumtui
of pscore  |         0          1 |     Total
-----------+----------------------+----------
        .6 |         0          1 |         1 
        .8 |        40        508 |       548 
-----------+----------------------+----------
     Total |        40        509 |       549 
Note: the common support option has been selected


******************************************* 
End of the algorithm to estimate the pscore 
*******************************************

It would be a great help if I could get some clarifications on whether my procedure is correct.