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
11. Chiu A, Hoxha I, Jensen C, Saucke M, Pitt S. Medical Maximizing Preferences and Beliefs About Cancer Among US Adults. JAMA Network Open 2024;7(6):e2417098 View
12. Geurts Y, Peters F, Feldman E, Roodhart J, Richir M, Dekker J, Beets G, Cnossen J, Bottenberg P, Intven M, Verheij M, de Ligt K, Walraven I. Using a modified Delphi procedure to select a PRO-CTCAE-based subset for patient-reported symptomatic toxicity monitoring in rectal cancer patients. Quality of Life Research 2024;33(11):3013 View
13. Lázaro E, Moscardó V. Qualitative Health-Related Quality of Life and Natural Language Processing: Characteristics, Implications, and Challenges. Healthcare 2024;12(19):2008 View
14. Perry L, Mossman B, Garcia S, Kircher S, Dunn A, Alonzi S, Easwar S, Hoerger M. Personality Feedback With Tailored Self‐Care Recommendations Improves Self‐Efficacy for Cancer Management: A Randomized Controlled Trial. Psycho-Oncology 2024;33(11) View