Published on in Vol 21, No 7 (2019): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12212, first published .
Computerized Quality of Life Assessment: A Randomized Experiment to Determine the Impact of Individualized Feedback on Assessment Experience

Computerized Quality of Life Assessment: A Randomized Experiment to Determine the Impact of Individualized Feedback on Assessment Experience

Computerized Quality of Life Assessment: A Randomized Experiment to Determine the Impact of Individualized Feedback on Assessment Experience

Journals

  1. van der Meulen M, Zamanipoor Najafabadi A, Lobatto D, Andela C, Vliet Vlieland T, Pereira A, van Furth W, Biermasz N. SF-12 or SF-36 in pituitary disease? Toward concise and comprehensive patient-reported outcomes measurements. Endocrine 2020;70(1):123 View
  2. 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
  3. Hou J, Li Q, Yu M, Li F, Tang Y, Long Y, Alike Y, Zhang Y, Ali M, Zhang C, Li W, Yang R. Validation of a Mobile Version of the American Shoulder and Elbow Surgeons Standardized Shoulder Assessment Form: An Observational Randomized Crossover Trial. JMIR mHealth and uHealth 2020;8(7):e16758 View
  4. Finkelstein F, Cimini M, Finkelstein S, Kliger A. Computerized adaptive technology for the assessment of HRQOL of PD and CKD patients. Peritoneal Dialysis International: Journal of the International Society for Peritoneal Dialysis 2021;41(5):509 View
  5. Pfob A, Mehrara B, Nelson J, Wilkins E, Pusic A, Sidey-Gibbons C. Machine learning to predict individual patient-reported outcomes at 2-year follow-up for women undergoing cancer-related mastectomy and breast reconstruction (INSPiRED-001). The Breast 2021;60:111 View
  6. Butler S, Sculley D, Santos D, Fellas A, Gironès X, Singh-Grewal D, Coda A. Effectiveness of eHealth and mHealth Interventions Supporting Children and Young People Living With Juvenile Idiopathic Arthritis: Systematic Review and Meta-analysis. Journal of Medical Internet Research 2022;24(2):e30457 View
  7. de Ligt K, de Rooij B, Hedayati E, Karsten M, Smaardijk V, Velting M, Saunders C, Travado L, Cardoso F, Lopez E, Carney N, Wengström Y, Ives A, Velikova G, Sousa Fialho M, Seidler Y, Stamm T, Koppert L, van de Poll-Franse L. International development of a patient-centered core outcome set for assessing health-related quality of life in metastatic breast cancer patients. Breast Cancer Research and Treatment 2023;198(2):265 View
  8. Aiyegbusi O, Roydhouse J, Rivera S, Kamudoni P, Schache P, Wilson R, Stephens R, Calvert M. Key considerations to reduce or address respondent burden in patient-reported outcome (PRO) data collection. Nature Communications 2022;13(1) View
  9. Albers E, Fraterman I, Walraven I, Wilthagen E, Schagen S, van der Ploeg I, Wouters M, van de Poll-Franse L, de Ligt K. Visualization formats of patient-reported outcome measures in clinical practice: a systematic review about preferences and interpretation accuracy. Journal of Patient-Reported Outcomes 2022;6(1) View
  10. Mnoyan A, Zhukov S, Morozov A, Bagdasarov A, Petrukhina E, Stepanenko V. Objective criteria for the quality of life of patients who underwent surgery (literature review). Bulletin of the Medical Institute "REAVIZ" (REHABILITATION, DOCTOR AND HEALTH) 2024;13(6):103 View