CBTI programs are very efficient in that they save time, reduce human error, are cost effective, and are objective/reliable, yet limited in that they are not always used by adequately trained evaluators or are not integrated with multiple sources of data.
[1] The program was used to evaluate MMPI[2] data from hospital patients and generated a list of 110 possible descriptive statements which corresponded to particular scale elevations.
Actuarial assessment programs are based on statistical or actuarial prediction (e.g., statistical analyses, linear regression equations and Bayesian rules), which is empirically based while automated assessment programs consist of a series of if-then statements derived by expert clinicians[8] and informed by published research and clinical experience.
The use of CBTIs is found in a variety of psychological domains (e.g., clinical interviewing and problem rating), but is most commonly utilized in personality and neuropsychological assessments.
[9] However, many validity studies are flawed due to small samples,[11] criterion contamination, the Barnum effect, inadequate input data to generate powerful statistical prediction rules,[7] unreliability of measures and the practice of generalizing across testing situations and populations without considering potential moderators.
CBTI programs arguably have many benefits over traditional hand-scored assessments and clinician interpretations which may contribute to their popularity.
[18] Additionally, CBTIs may promote exceedingly cavalier attitudes towards clinical assessment and interpretation, and as they are increasingly available to inadequately trained evaluators, the potential for misuse is high.
[3] Lastly, there is a call for the more effective integration of clinical and computer-based prediction methods, beginning with a partnership between clinicians and researchers in the development of CBTI programs.