This paper is in the following e-collection/theme issue:

Research Instruments, Questionnaires, and Tools (576) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (832) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (1515) Diagnostic Tools in Mental Health (242)

Published on in Vol 16, No 9 (2014): September

Applying Computer Adaptive Testing to Optimize Online Assessment of Suicidal Behavior: A Simulation Study

Applying Computer Adaptive Testing to Optimize Online Assessment of Suicidal Behavior: A Simulation Study

Applying Computer Adaptive Testing to Optimize Online Assessment of Suicidal Behavior: A Simulation Study

Authors of this article:

Derek Paul De Beurs1, 2 Author Orcid Image ;   Anton LM de Vries3 Author Orcid Image ;   Marieke H de Groot1 Author Orcid Image ;   Jos de Keijser4 Author Orcid Image ;   Ad JFM Kerkhof1, 2 Author Orcid Image
Article Authors Cited by (48) Tweetations (8) Metrics

Journals

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  2. De Beurs D, Fried E, Wetherall K, Cleare S, O’ Connor D, Ferguson E, O'Carroll R, O’ Connor R. Exploring the psychology of suicidal ideation: A theory driven network analysis. Behaviour Research and Therapy 2019;120:103419 View
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  5. Magnée T, de Beurs D, Terluin B, Verhaak P. Applying Computerized Adaptive Testing to the Four-Dimensional Symptom Questionnaire (4DSQ): A Simulation Study. JMIR Mental Health 2017;4(1):e7 View
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  7. Forkmann T, Teismann T, Stenzel J, Glaesmer H, de Beurs D. Defeat and entrapment: more than meets the eye? Applying network analysis to estimate dimensions of highly correlated constructs. BMC Medical Research Methodology 2018;18(1) View
  8. de Beurs D, Bosmans J, de Groot M, de Keijser J, van Duijn E, de Winter R, Kerkhof A. Training mental health professionals in suicide practice guideline adherence: Cost-effectiveness analysis alongside a randomized controlled trial. Journal of Affective Disorders 2015;186:203 View
  9. Delgado-Gomez D, Baca-Garcia E, Aguado D, Courtet P, Lopez-Castroman J. Computerized Adaptive Test vs. decision trees: Development of a support decision system to identify suicidal behavior. Journal of Affective Disorders 2016;206:204 View
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  11. Chien T, Lin W. Improving Inpatient Surveys: Web-Based Computer Adaptive Testing Accessed via Mobile Phone QR Codes. JMIR Medical Informatics 2016;4(1):e8 View
  12. Chien T, Lin W. Simulation study of activities of daily living functions using online computerized adaptive testing. BMC Medical Informatics and Decision Making 2016;16(1) View
  13. Chien T, Shao Y, Kuo S. Development of a Microsoft Excel tool for one-parameter Rasch model of continuous items: an application to a safety attitude survey. BMC Medical Research Methodology 2017;17(1) View
  14. de Beurs D, Fokkema M, de Groot M, de Keijser J, Kerkhof A. Longitudinal measurement invariance of the Beck Scale for Suicide Ideation. Psychiatry Research 2015;225(3):368 View
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  19. Djaja N, Janda M, Olsen C, Whiteman D, Chien T. Estimating Skin Cancer Risk: Evaluating Mobile Computer-Adaptive Testing. Journal of Medical Internet Research 2016;18(1):e22 View
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  21. Kliem S, Lohmann A, Mößle T, Brähler E. German Beck Scale for Suicide Ideation (BSS): psychometric properties from a representative population survey. BMC Psychiatry 2017;17(1) View
  22. de Beurs D, Fokkema M, O’Connor R. Optimizing the assessment of suicidal behavior: The application of curtailment techniques. Journal of Affective Disorders 2016;196:218 View
  23. Franco-Martín M, Muñoz-Sánchez J, Sainz-de-Abajo B, Castillo-Sánchez G, Hamrioui S, de la Torre-Díez I. A Systematic Literature Review of Technologies for Suicidal Behavior Prevention. Journal of Medical Systems 2018;42(4) View
  24. Weiner S, Hoppe J, Finkelman M. Techniques to Shorten a Screening Tool for Emergency Department Patients. Western Journal of Emergency Medicine 2019;20(5) View
  25. Spangenberg L, Teismann T, Forkmann T, Rath D, Schönfelder A, Paashaus L, Juckel G, Stengler K, Glaesmer H. Psychometrische Eigenschaften und Faktorstruktur der deutschen Version der Beck-Suizidgedanken-Skala (BSS): Validierung an einer Stichprobe psychiatrischer Patienten. PPmP - Psychotherapie · Psychosomatik · Medizinische Psychologie 2020;70(09/10):405 View
  26. Rassy J, Bardon C, Dargis L, Côté L, Corthésy-Blondin L, Mörch C, Labelle R. Information and Communication Technology Use in Suicide Prevention: Scoping Review. Journal of Medical Internet Research 2021;23(5):e25288 View
  27. Boudreaux E, Rundensteiner E, Liu F, Wang B, Larkin C, Agu E, Ghosh S, Semeter J, Simon G, Davis-Martin R. Applying Machine Learning Approaches to Suicide Prediction Using Healthcare Data: Overview and Future Directions. Frontiers in Psychiatry 2021;12 View
  28. Kurisu K, Hashimoto M, Ishizawa T, Shibayama O, Inada S, Fujisawa D, Inoguchi H, Shimoda H, Inoue S, Ogawa A, Akechi T, Shimizu K, Uchitomi Y, Matsuyama Y, Yoshiuchi K. Development of computer adaptive testing for measuring depression in patients with cancer. Scientific Reports 2022;12(1) View
  29. Yang T, Chien T, Lai F. Web-Based Skin Cancer Assessment and Classification Using Machine Learning and Mobile Computerized Adaptive Testing in a Rasch Model: Development Study. JMIR Medical Informatics 2022;10(3):e33006 View
  30. Abal F, Sánchez González J, Lozzia G, Attorresi H. Escala de Desesperanza de Beck (BHS): ventajas de una administración adaptativa. Revista Iberoamericana de Psicología 2020;14(1):71 View
  31. Podlogar M, Gutierrez P, Osman A. Optimizing the Beck Scale for Suicide Ideation: An Item Response Theory Approach Among U.S. Military Personnel. Assessment 2023;30(4):1321 View
  32. Harris K, Wang L, Mu G, Lu Y, So C, Zhang W, Ma J, Liu K, Wang W, Zhang M, Ho R, Arias S. Measuring the suicidal mind: The ‘open source’ Suicidality Scale, for adolescents and adults. PLOS ONE 2023;18(2):e0282009 View
  33. Demir C, French B. Applicability and Efficiency of a Computerized Adaptive Test for the Washington Assessment of the Risks and Needs of Students. Assessment 2023;30(1):238 View
  34. Burn A, Ford T, Stochl J, Jones P, Perez J, Anderson J. Developing a Web-Based App to Assess Mental Health Difficulties in Secondary School Pupils: Qualitative User-Centered Design Study. JMIR Formative Research 2022;6(1):e30565 View
  35. Morales-Vives F, Ferrando P, Dueñas J. Should suicidal ideation be regarded as a dimension, a unipolar trait or a mixture? A model-based analysis at the score level. Current Psychology 2023;42(25):21397 View
  36. Rosen A, Moore T, Calkins M, Gur R, Gur R. Effects of Skip-Logic on the Validity of Dimensional Clinical Scores: A Simulation Study. Psychopathology 2019;52(6):358 View
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  39. Colledani D, Robusto E, Anselmi P. Shortening and Personalizing Psychodiagnostic Assessments with Decision Tree-Machine Learning Classifiers: An Application Example Based on the Patient Health Questionnaire-9. International Journal of Mental Health and Addiction 2024 View
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Books/Policy Documents

  1. de Winter R, de Beurs D. Behandeling van suïcidaal gedrag in de praktijk van de GGZ. View
  2. Sunderland M, Batterham P, Calear A, Carragher N. The Cambridge Handbook of Clinical Assessment and Diagnosis. View
  3. Davies R. Handbook of Research in Educational Communications and Technology. View
  4. Masoner H, ElBassiouny A. The Wiley Encyclopedia of Personality and Individual Differences. View
  5. Masoner H, ElBassiouny A. The Wiley Encyclopedia of Personality and Individual Differences. View
  6. de Winter R, Meijer C, de Groot M. Suicide Risk Assessment and Prevention. View
  7. de Winter R, Meijer C, de Groot M. Suicide Risk Assessment and Prevention. View