I am having trouble with a Structural Equation Model.

As you can see in the attached picture, my main outcome variable (F4) is a latent variable. When I run the model, all of the paths are significant in the hypothesized direction, but the Chi-square is very high (almost 10,000) and other fit indexes are low.

However, if I create a satisfaction 'observed' variable first in SPSS (by adding the scores together of x1, x2, and x3 - the cronbach's alpha is .921 (answers on a Likert scale)), then run the model again, the model is fit much better - chi-square is 16.754 at a .005 probability level, NFI at .996, CFI .997, etc.

Is there something I can do to improve the full model which uses the latent variable? I can provide more information.

Thank you.