Add loadings to improve fit
Adding more item/factor relationships will always improve your model fit because more parameters are always going to fit the data more precisely. However, when adding loadings, you want to be sure they are justifiable by theory. A good place to start is with loadings that were strong in an EFA with the same number of factors (on a separate dataset, of course!) - you can consider whether those suggested item/factor relationships might be justified by theory. If they are supported by your theory, you can add them to your CFA.
This exercise is part of the course
Factor Analysis in R
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Add some plausible item/factor loadings to the syntax
theory_syn_add <- "
AGE: A1, A2, A3, A4, A5
CON: C1, C2, C3, C4, C5
EXT: E1, E2, E3, E4, E5, ___
NEU: N1, N2, N3, N4, N5, ___
OPE: O1, O2, O3, O4, O5
"