@article {147,
	title = {Computerized adaptive measurement of depression: A simulation study},
	journal = {BMC Psychiatry},
	volume = {4},
	number = {1},
	year = {2004},
	pages = {13-23},
	abstract = {Background: Efficient, accurate instruments for measuring depression are increasingly importantin clinical practice. We developed a computerized adaptive version of the Beck DepressionInventory (BDI). We examined its efficiency and its usefulness in identifying Major DepressiveEpisodes (MDE) and in measuring depression severity.Methods: Subjects were 744 participants in research studies in which each subject completed boththe BDI and the SCID. In addition, 285 patients completed the Hamilton Depression Rating Scale.Results: The adaptive BDI had an AUC as an indicator of a SCID diagnosis of MDE of 88\%,equivalent to the full BDI. The adaptive BDI asked fewer questions than the full BDI (5.6 versus 21items). The adaptive latent depression score correlated r = .92 with the BDI total score and thelatent depression score correlated more highly with the Hamilton (r = .74) than the BDI total scoredid (r = .70).Conclusions: Adaptive testing for depression may provide greatly increased efficiency withoutloss of accuracy in identifying MDE or in measuring depression severity.},
	keywords = {*Computer Simulation, Adult, Algorithms, Area Under Curve, Comparative Study, Depressive Disorder/*diagnosis/epidemiology/psychology, Diagnosis, Computer-Assisted/*methods/statistics \& numerical data, Factor Analysis, Statistical, Female, Humans, Internet, Male, Mass Screening/methods, Patient Selection, Personality Inventory/*statistics \& numerical data, Pilot Projects, Prevalence, Psychiatric Status Rating Scales/*statistics \& numerical data, Psychometrics, Research Support, Non-U.S. Gov{\textquoteright}t, Research Support, U.S. Gov{\textquoteright}t, P.H.S., Severity of Illness Index, Software},
	author = {Gardner, W. and Shear, K. and Kelleher, K. J. and Pajer, K. A. and Mammen, O. and Buysse, D. and Frank, E.}
}
@article {146,
	title = {Multidimensional adaptive testing for mental health problems in primary care},
	journal = {Medical Care},
	volume = {40},
	number = {9},
	year = {2002},
	note = {Gardner, WilliamKelleher, Kelly JPajer, Kathleen AMCJ-177022/PHS HHS/MH30915/MH/NIMH NIH HHS/MH50629/MH/NIMH NIH HHS/Med Care. 2002 Sep;40(9):812-23.},
	month = {Sep},
	pages = {812-23},
	edition = {2002/09/10},
	abstract = {OBJECTIVES: Efficient and accurate instruments for assessing child psychopathology are increasingly important in clinical practice and research. For example, screening in primary care settings can identify children and adolescents with disorders that may otherwise go undetected. However, primary care offices are notorious for the brevity of visits and screening must not burden patients or staff with long questionnaires. One solution is to shorten assessment instruments, but dropping questions typically makes an instrument less accurate. An alternative is adaptive testing, in which a computer selects the items to be asked of a patient based on the patient{\textquoteright}s previous responses. This research used a simulation to test a child mental health screen based on this technology. RESEARCH DESIGN: Using half of a large sample of data, a computerized version was developed of the Pediatric Symptom Checklist (PSC), a parental-report psychosocial problem screen. With the unused data, a simulation was conducted to determine whether the Adaptive PSC can reproduce the results of the full PSC with greater efficiency. SUBJECTS: PSCs were completed by parents on 21,150 children seen in a national sample of primary care practices. RESULTS: Four latent psychosocial problem dimensions were identified through factor analysis: internalizing problems, externalizing problems, attention problems, and school problems. A simulated adaptive test measuring these traits asked an average of 11.6 questions per patient, and asked five or fewer questions for 49\% of the sample. There was high agreement between the adaptive test and the full (35-item) PSC: only 1.3\% of screening decisions were discordant (kappa = 0.93). This agreement was higher than that obtained using a comparable length (12-item) short-form PSC (3.2\% of decisions discordant; kappa = 0.84). CONCLUSIONS: Multidimensional adaptive testing may be an accurate and efficient technology for screening for mental health problems in primary care settings.},
	keywords = {Adolescent, Child, Child Behavior Disorders/*diagnosis, Child Health Services/*organization \& administration, Factor Analysis, Statistical, Female, Humans, Linear Models, Male, Mass Screening/*methods, Parents, Primary Health Care/*organization \& administration},
	isbn = {0025-7079 (Print)0025-7079 (Linking)},
	author = {Gardner, W. and Kelleher, K. J. and Pajer, K. A.}
}
