Background. A 10-question screening scale of psychological distress and a six-question short-form scale embedded within the 10-question scale were developed for the redesigned US National Health Interview Survey (NHIS). Methods. Initial pilot questions were administered in a US national mail survey (N fl 1401). A reduced set of questions was subsequently administered in a US national telephone survey (N fl 1574). The 10-question and six-question scales, which we refer to as the K10 and K6, were constructed from the reduced set of questions based on Item Response Theory models. The scales were subsequently validated in a two-stage clinical reappraisal survey (N fl 1000 telephone screening interviews in the first stage followed by N fl 153 face-to-face clinical interviews in the second stage that oversampled first-stage respondents who screened positive for emotional problems) in a local convenience sample. The second-stage sample was administered the screening scales along with the Structured Clinical Interview for DSM-IV (SCID). The K6 was subsequently included in the 1997 (N fl 36116) and 1998 (N fl 32440) US National Health Interview Survey, while the K10 was included in the 1997 (N fl 10641) Australian National Survey of Mental Health and Well-Being. Results. Both the K10 and K6 have good precision in the 90th‐99th percentile range of the population distribution (standard errors of standardized scores in the range 0‐20‐0‐25) as well as consistent psychometric properties across major sociodemographic subsamples. The scales strongly discriminate between community cases and non-cases of DSM-IV}SCID disorders, with areas under the Receiver Operating Characteristic (ROC) curve of 0‐87‐0‐88 for disorders having Global Assessment of Functioning (GAF) scores of 0‐70 and 0‐95‐0‐96 for disorders having GAF scores of 0‐50. Conclusions. The brevity, strong psychometric properties, and ability to discriminate DSM-IV cases from non-cases make the K10 and K6 attractive for use in general-purpose health surveys. The scales are already being used in annual government health surveys in the US and Canada as well as in the WHO World Mental Health Surveys. Routine inclusion of either the K10 or K6 in clinical studies would create an important, and heretofore missing, crosswalk between community and clinical epidemiology.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/F141675CCD0E08C0FB98E01C006B4E0D/S0033291702006074a.pdf/div-class-title-short-screening-scales-to-monitor-population-prevalences-and-trends-in-non-specific-psychological-distress-div.pdf

Short screening scales to monitor population prevalences and trends in non-specific psychological distress.

A primary goal of scale development is to create a valid measure of an underlying construct. We discuss theoretical principles, practical issues, and pragmatic decisions to help developers maximize the construct validity of scales and subscales. First, it is essential to begin with a clear conceptualization of the target construct. Moreover, the content of the initial item pool should be overinclusive and item wording needs careful attention. Next, the item pool should be tested, along with variables that assess closely related constructs, on a heterogeneous sample representing the entire range of the target population. Finally, in selecting scale items, the goal is unidimensionality rather than internal consistency ; this means that virtually all interitem correlations should be moderate in magnitude. Factor analysis can play a crucial role in ensuring the unidimensionality and discriminant validity of scales.

/pdf/constructing-validity-basic-issues-in-objective-scale-336bh0ucpv.pdf

Constructing validity: Basic issues in objective scale development

Contents: Preface. Part I: R. Barr, Society and Literacy. S.B. Heath, The Sense of Being Literate: Historical and Cross-Cultural Features. P. Foster, A. Purves, Literacy and Society with Particular Reference to the Non-Western World. R.L. Venezky, The Development of Literacy in the Industrialized Nations of the West. J.T. Guthrie, V. Greaney, Literacy Acts. R-M. Weber, Linguistic Diversity and Reading in American Society. J.S. Chall, J.R. Squire, The Publishing Industry and Textbooks. P. Shannon, Politics, Policy, and Reading Research. Part II: M.L. Kamil, Task and Format Variables in Reading Research. A. Graesser, J.M. Golding, D.L. Long, Narrative Representation and Comprehension. S. Bovair, D.E. Kieras, Toward a Model of Acquiring Procedures from Text. C.A. Weaver, III, W. Kintsch, Expository Text. R.J. Tierney, T. Shanahan, Research on the Reading-Writing Relationship: Interactions, Transactions, and Outcomes. R. Calfee, E. Hiebert, Classroom Assessment of Reading. D. Reinking, L. Bridwell-Bowles, Computers in Reading and Writing. R. Waller, Typography and Discourse. Part III: P.B. Mosenthal, Constructs of Reader Process. L.C. Ehri, Development of the Ability to Read Words. K.E. Stanovich, Word Recognition: Changing Perspectives. R. Beach, S. Hynds, Research on Response to Literature. T.P. McNamara, D.L. Miller, J.D. Bransford, Mental Models and Reading Comprehension. M. Daneman, Individual Differences in Reading Skills. K.K. Wixson, M.Y. Lipson, Perspectives on Reading Disability Research. F.R. Vellutino, M.B. Denckla, Cognitive and Neuropsychological Foundations of Word Identification in Poor and Normally Developing Readers. S.G. Paris, B.A. Wasik, J.C. Turner, The Development of Strategic Readers. M. Hegarty, P.A. Carpenter, M.A. Just, Diagrams in the Comprehension of Scientific Texts. L. Mikulecky, R. Drew, Basic Literacy Skills in the Workplace. R.C. Anderson, W.E. Nagy, Word Meanings. Part IV: P.D. Pearson, Literacy and Schooling. E. Sulzby, W. Teale, Emergent Literacy. C. Juel, Beginning Reading. I. Beck, M. McKeown, Conditions of Vocabulary Acquisition. P.D. Pearson, L. Fielding, Comprehension Instruction. L.R. Roehler, G.G. Duffy, Teachers' Instructional Actions. R. Barr, R. Dreeben, Grouping Students for Reading Instruction. J.V. Hoffman, Teacher and School Effects in Learning to Read. D.E. Alvermann, D.W. Moore, Secondary School Reading. P. Johnston, R. Allington, Remediation. Epilogue: P.B. Mosenthal, M.L. Kamil, Understanding Progress in Reading Research.

Handbook of Reading Research

Structural equation modeling (SEM) is a multivariate statistical framework that is used to model complex relationships between directly observed and indirectly observed (latent) variables. SEM is a general framework that involves simultaneously solving systems of linear equations and encompasses other techniques such as regression, factor analysis, path analysis, and latent growth curve modeling. Recently, SEM has gained popularity in the analysis of complex genetic traits because it can be used to better analyze the relationships between correlated variables (traits), to model genes as latent variables as a function of multiple observed genetic variants, and to assess the association between multiple genetic variants and multiple correlated phenotypes of interest. Though the general SEM framework only allows for the analysis of independent observations, recent work has extended SEM for the analysis of data on general pedigrees. Here, we review the theory of SEM for both unrelated and family data, describe the available software for SEM, and provide examples of SEM analysis.

Structural Equation Modeling

Background Public Law 102-321 established a block grant for adults with "serious mental illness" (SMI) and required the Substance Abuse and Mental Health Services Administration (SAMHSA) to develop a method to estimate the prevalence of SMI. Methods Three SMI screening scales were developed for possible use in the SAMHSA National Household Survey on Drug Abuse: the Composite International Diagnostic Interview Short-Form (CIDI-SF) scale, the K10/K6 nonspecific distress scales, and the World Health Organization Disability Assessment Schedule (WHO-DAS). An enriched convenience sample of 155 respondents was administered all screening scales followed by the 12-month Structured Clinical Interview for DSM-IV and the Global Assessment of Functioning (GAF). We defined SMI as any 12-month DSM-IV disorder, other than a substance use disorder, with a GAF score of less than 60. Results All screening scales were significantly related to SMI. However, neither the CIDI-SF nor the WHO-DAS improved prediction significantly over the K10 or K6 scales. The area under the receiver operating characteristic curve of SMI was 0.854 for K10 and 0.865 for K6. The most efficient screening scale, K6, had a sensitivity (SE) of 0.36 (0.08) and a specificity of 0.96 (0.02) in predicting SMI. Conclusions The brevity and accuracy of the K6 and K10 scales make them attractive screens for SMI. Routine inclusion of either scale in clinical studies would create an important, and heretofore missing, crosswalk between community and clinical epidemiology.

https://jamanetwork.com/journals/jamapsychiatry/articlepdf/207204/YOA20567.pdf

Screening for Serious Mental Illness in the General Population

Background Concepts, Models, and Features Ability and Item Parameter Estimation Assessment of Model-Data Fit The Ability Scale Item and Test Information and Efficiency Functions Test Construction Identification of Potentially Biased Test Items Test Score Equating Computerized Adaptive Testing Future Directions of Item Response Theory

Fundamentals of Item Response Theory

Fundamentals of Item Response Theory.

Item response theory has become an essential component in the toolkit of every researcher in the behavioral sciences. It provides a powerful means to study individual responses to a variety of stimuli, and the methodology has been extended and developed to cover many different models of interaction. This volume presents a wide-ranging handbook to item response theory - and its applications to educational and psychological testing. It will serve as both an introduction to the subject and also as a comprehensive reference volume for practitioners and researchers. It is organized into six major sections: the nominal categories model, models for response time or multiple attempts on items, models for multiple abilities or cognitive components, nonparametric models, models for nonmonotone items, and models with special assumptions. Each chapter in the book has been written by an expert of that particular topic, and the chapters have been carefully edited to ensure that a uniform style of notation and presentation is used throughout. As a result, all researchers whose work uses item response theory will find this an indispensable companion to their work and it will be the subject's reference volume for many years to come.

Handbook of Modern Item Response Theory

Item Response Theory

1 Some Background to Item Response Theory.- 2 Assumptions of Item Response Theory.- 3 Item Response Models.- 4 Ability Scales.- 5 Estimation of Ability.- 6 Information Function and Its Application.- 7 Estimation of Item and Ability Parameters.- 8 Approaches for Addressing Model-Data Fit.- 9 Examples of Model-Data Fit Studies.- 10 Test Equating.- 11 Construction of Tests.- 12 Item Banking.- 13 Miscellaneous Applications.- 14 Practical Considerations in Using IRT Models.- References.- Author Index.

Ronald K. Hambleton

Papers

Fundamentals of Item Response Theory

Fundamentals of Item Response Theory.

Handbook of Modern Item Response Theory

Item Response Theory

Item Response Theory: Principles and Applications