University of Twente Student Theses

Login

Identifying Patient-Reported Outcome Measures that Assess Physical Symptoms for Childhood Cancer Survivors and Exploring Barriers and Facilitators for Clinical Implementation

Vriens, Maartje (2022) Identifying Patient-Reported Outcome Measures that Assess Physical Symptoms for Childhood Cancer Survivors and Exploring Barriers and Facilitators for Clinical Implementation.

[img] PDF
2MB
Abstract:Improved survival rates for childhood cancer are accompanied by a majority of those survivors suffering from long-term physical symptoms, as a result of their previously received treatments. Patient-reported outcome measures (PROMs) have the potential to measure those symptoms in cancer survivors more accurately than merely physician assessment. The implementation of PROMs in daily clinical practice has appeared to be challenging. This study focused on (1) identifying validated PROMs that can measure physical symptoms of childhood cancer survivors, and (2) exploring barriers and facilitators that can apply to childhood cancer survivors and their doctors in implementing and using digital PROMs in daily clinical practice. Eventually, no validated questionnaire is available that can measure all physical symptoms in childhood cancer survivors. Future efforts are needed to establish a questionnaire for childhood cancer survivors, which can be done by combining validated instruments directed at other patient groups, or by creating a new questionnaire specifically focusing on the physical symptoms of childhood cancer survivors. In addition, the created overview with barriers and facilitators can be used as an indication of what factors can impede or facilitate childhood cancer survivors in completing PROMs.
Item Type:Essay (Master)
Clients:
Princess Máxima Centre, Utrecht, Netherlands
Faculty:BMS: Behavioural, Management and Social Sciences
Subject:77 psychology
Programme:Psychology MSc (66604)
Link to this item:https://purl.utwente.nl/essays/90810
Export this item as:BibTeX
EndNote
HTML Citation
Reference Manager

 

Repository Staff Only: item control page