Measuring mental health outcomes with pre-post designs.
The pre-post design has been the workhorse of outcome evaluations for many years. Using data from a study of 984 treated children (ages 5 to 17 years), this article argues that there are two structural problems with the pre-post evaluation of outcome: (1) excessively large intervals of uncertainty for individual outcomes and (2) paradoxical inconsistencies in the evaluation of groups. These problems can be solved by designs with three or more repeated measures analyzed with longitudinal multilevel analytic models.
Lambert
E W
EW
Center for Mental Health Policy, Vanderbilt University, Nashville 37212, USA. Warren.Lambert@Vanderbilt.edu
Doucette
A
A
Bickman
L
L
D000293:Adolescent; D002648:Child; D003156:Community Mental Health Services / Q000592:standards*; D005260:Female; D006801:Humans; D008297:Male; D015233:Models, Statistical; D009010:Monte Carlo Method; D009657:North Carolina; D017063:Outcome Assessment, Health Care / Q000379:methods*; D015397:Program Evaluation / Q000379:methods* / Q000706:statistics & numerical data; D011569:Psychiatric Status Rating Scales / Q000706:statistics & numerical data; D012107:Research Design