@article {138,
	title = {Development of an item bank for the assessment of depression in persons with mental illnesses and physical diseases using Rasch analysis},
	journal = {Rehabilitation Psychology},
	volume = {54},
	number = {2},
	year = {2009},
	note = {Forkmann, ThomasBoecker, MarenNorra, ChristineEberle, NicoleKircher, TiloSchauerte, PatrickMischke, KarlWesthofen, MartinGauggel, SiegfriedWirtz, MarkusResearch Support, Non-U.S. Gov{\textquoteright}tUnited StatesRehabilitation psychologyRehabil Psychol. 2009 May;54(2):186-97.},
	month = {May},
	pages = {186-97},
	edition = {2009/05/28},
	abstract = {OBJECTIVE: The calibration of item banks provides the basis for computerized adaptive testing that ensures high diagnostic precision and minimizes participants{\textquoteright} test burden. The present study aimed at developing a new item bank that allows for assessing depression in persons with mental and persons with somatic diseases. METHOD: The sample consisted of 161 participants treated for a depressive syndrome, and 206 participants with somatic illnesses (103 cardiologic, 103 otorhinolaryngologic; overall mean age = 44.1 years, SD =14.0; 44.7\% women) to allow for validation of the item bank in both groups. Persons answered a pool of 182 depression items on a 5-point Likert scale. RESULTS: Evaluation of Rasch model fit (infit < 1.3), differential item functioning, dimensionality, local independence, item spread, item and person separation (>2.0), and reliability (>.80) resulted in a bank of 79 items with good psychometric properties. CONCLUSIONS: The bank provides items with a wide range of content coverage and may serve as a sound basis for computerized adaptive testing applications. It might also be useful for researchers who wish to develop new fixed-length scales for the assessment of depression in specific rehabilitation settings.},
	keywords = {Adaptation, Psychological, Adult, Aged, Depressive Disorder/*diagnosis/psychology, Diagnosis, Computer-Assisted, Female, Heart Diseases/*psychology, Humans, Male, Mental Disorders/*psychology, Middle Aged, Models, Statistical, Otorhinolaryngologic Diseases/*psychology, Personality Assessment/statistics \& numerical data, Personality Inventory/*statistics \& numerical data, Psychometrics/statistics \& numerical data, Questionnaires, Reproducibility of Results, Sick Role},
	isbn = {0090-5550 (Print)0090-5550 (Linking)},
	author = {Forkmann, T. and Boecker, M. and Norra, C. and Eberle, N. and Kircher, T. and Schauerte, P. and Mischke, K. and Westhofen, M. and Gauggel, S. and Wirtz, M.}
}
@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.}
}
