Abstract
The application of web-based and remotely administered surveys is becoming increasingly popular due to the fact that it offers numerous advantages over traditional paper-based or computer-based surveys completed in the presence of the researcher. However, it is unclear whether complex preference elicitation tasks administered online in highly vulnerable patient populations are also feasible. This commentary discusses opportunities and challenges of conducting quantitative patient preference studies in lung cancer patients using web-based modes of data collection. We refer to our recent experience in the context of the Patient Preference in Benefit-Risk Assessments during the Drug Life Cycle (PREFER) project. Among the main advantages were the possibility of reaching a wider and geogra-phically distant population in a shorter timeframe while reducing the financial costs of testing, the greater flexibility offered and the reduced burden on the patients. Some limitations were also identified and should be the object of further research, including the potential lack of inclusiveness of the research, the lack of control over who is completing the survey, a poor comprehension of the study material, and ultimately a lower level of engagement with the study. Despite these limitations, experience from the PREFER project suggests that online quantitative methods for data collection may provide a valuable method to explore preferences in vulnerable patient populations beyond the COVID-19 pandemic.
Original language | English |
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Pages (from-to) | 2509-2517 |
Number of pages | 9 |
Journal | Patient Preference and Adherence |
Volume | 15 |
DOIs |
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Publication status | Published - 15 Nov 2021 |
Bibliographical note
Funding Information:This contribution is part of the PREFER project. The Patient Preferences in Benefit-Risk Assessments during the Drug Life Cycle (PREFER) project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 115966. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation program and EFPIA.
Publisher Copyright:
© 2021 Oliveri et al.