Psychometric network analysis is an alternative theoretically-driven analytic approach that has the potential to conceptualize
cognitive impairment in
Alzheimer's disease differently than was previously assumed and consequently detect unknown treatment effects. Based on individual participant data, extracted from three double-blind, randomized placebo-controlled clinical trials, psychometric networks were computed on observed
Alzheimer's Disease Assessment Scale Cognitive Subscale scores at baseline (N=1,554) and on predicted change scores at 24 weeks of follow-up for participants who received
donepezil (N=797) or placebo (N=484). A novel conceptualization of
cognitive impairment in
Alzheimer's disease was displayed through the baseline network, that had 90% (n=27) positive statistically significant (p<0.05) associations, and a most central aspect of ideational praxis. Following 24 weeks, treatment effects emerged via the differences between the change score networks. The
donepezil network had more statistically significant (p<0.05) positive associations and a higher global strength (n=15; S=1.22; p=0.03), than the placebo network (n=8; S=0.57). This suggests that for those who were treated with
donepezil compared with placebo, cognition is a more unified construct. The main aspects of change in
cognitive impairment were comprehension of spoken language for the
donepezil network and spoken language ability for the placebo network. Comprehension of spoken language apears to be most sensitive to
psychopharmaceutical interventions and should therefore be closely monitored. Overall, our psychometric network analysis presents a new conceptualization of
cognitive impairment in
Alzheimer's disease, points to previously unknown treatment effects and highlights well-defined aspects of cognitive impairment that may translate into future treatment targets.