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

Research Instruments, Questionnaires, and Tools (576) Depression and Mood Disorders; Suicide Prevention (1363)

Published on in Vol 19, No 9 (2017): September

Computerized Adaptive Testing Provides Reliable and Efficient Depression Measurement Using the CES-D Scale

Computerized Adaptive Testing Provides Reliable and Efficient Depression Measurement Using the CES-D Scale

Computerized Adaptive Testing Provides Reliable and Efficient Depression Measurement Using the CES-D Scale

Authors of this article:

Bao Sheng Loe1 Author Orcid Image ;   David Stillwell2 Author Orcid Image ;   Chris Gibbons2, 3 Author Orcid Image
Article Authors Cited by (17) Tweetations (6) Metrics

Journals

  1. Tian X, Dai B. Developing a Computerized Adaptive Test to Assess Stress in Chinese College Students. Frontiers in Psychology 2020;11 View
  2. Sidey-Gibbons C, Brooks H, Gellatly J, Small N, Lovell K, Bee P, Solari A. Assessing mental health service user and carer involvement in physical health care planning: The development and validation of a new patient-reported experience measure. PLOS ONE 2019;14(2):e0206507 View
  3. Sanderson S, Loe B, Freeman M, Gabriel C, Stevenson D, Gibbons C, Chitty L, Lewis C. Development of the Knowledge of Genome Sequencing (KOGS) questionnaire. Patient Education and Counseling 2018;101(11):1966 View
  4. Geerards D, van den Berg L, Pusic A, Hoogbergen M, Klassen A, van der Hulst R, Sidey-Gibbons C. Deriving an overall appearance domain score by applying bifactor IRT analysis to the BODY-Q appearance scales. Quality of Life Research 2020;29(4):1065 View
  5. Amtmann D, Bamer A, Liljenquist K, Cowan P, Salem R, Turk D, Jensen M. The Concerns About Pain (CAP) Scale: A Patient-Reported Outcome Measure of Pain Catastrophizing. The Journal of Pain 2020;21(11-12):1198 View
  6. Glasgow R, Kwan B, Matlock D. Realizing the full potential of precision health: The need to include patient-reported health behavior, mental health, social determinants, and patient preferences data. Journal of Clinical and Translational Science 2018;2(3):183 View
  7. Harrison C, Loe B, Lis P, Sidey-Gibbons C. Maximizing the Potential of Patient-Reported Assessments by Using the Open-Source Concerto Platform With Computerized Adaptive Testing and Machine Learning. Journal of Medical Internet Research 2020;22(10):e20950 View
  8. Geerards D, Klassen A, Hoogbergen M, van der Hulst R, van den Berg L, Pusic A, Gibbons C. Streamlining the Assessment of Patient-Reported Outcomes in Weight Loss and Body Contouring Patients: Applying Computerized Adaptive Testing to the BODY-Q. Plastic & Reconstructive Surgery 2019;143(5):946e View
  9. Zhou L, Parmanto B. Development and Validation of a Comprehensive Well-Being Scale for People in the University Environment (Pitt Wellness Scale) Using a Crowdsourcing Approach: Cross-Sectional Study. Journal of Medical Internet Research 2020;22(4):e15075 View
  10. Chung K, Park J, Joung D, Jhung K. Response Time as an Implicit Self-Schema Indicator for Depression Among Undergraduate Students: Preliminary Findings From a Mobile App–Based Depression Assessment. JMIR mHealth and uHealth 2019;7(9):e14657 View
  11. 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
  12. Xu C, Christensen J, Haykal T, Asaad M, Sidey-Gibbons C, Schaverien M. Measurement Properties of the Lymphedema Life Impact Scale. Lymphatic Research and Biology 2022;20(4):425 View
  13. Xu C, Schaverien M, Christensen J, Sidey-Gibbons C. Efficient and precise Ultra-QuickDASH scale measuring lymphedema impact developed using computerized adaptive testing. Quality of Life Research 2022;31(3):917 View
  14. Xu C, Smith G, Chen Y, Checka C, Giordano S, Kaiser K, Lowenstein L, Ma H, Mendoza T, Peterson S, Shih Y, Shete S, Tang C, Volk R, Sidey-Gibbons C, Jayadevappa R. Short-form adaptive measure of financial toxicity from the Economic Strain and Resilience in Cancer (ENRICh) study: Derivation using modern psychometric techniques. PLOS ONE 2022;17(8):e0272804 View
  15. Liou G, Bonner C, Tay L. A psychometric view of technology-based assessments. International Journal of Testing 2022;22(3-4):216 View
  16. Giordano A, Testa S, Bassi M, Cilia S, Bertolotto A, Quartuccio M, Pietrolongo E, Falautano M, Grobberio M, Niccolai C, Allegri B, Viterbo R, Confalonieri P, Giovannetti A, Cocco E, Grasso M, Lugaresi A, Ferriani E, Nocentini U, Zaffaroni M, De Livera A, Jelinek G, Solari A, Rosato R. Applying multidimensional computerized adaptive testing to the MSQOL-54: a simulation study. Health and Quality of Life Outcomes 2023;21(1) View
  17. Kraska J, Bell K, Costello S. Graded Response Model Analysis and Computer Adaptive Test Simulation of the Depression Anxiety Stress Scale 21: Evaluation and Validation Study. Journal of Medical Internet Research 2023;25:e45334 View