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We read with great interest the report by Lee et al. [1], “Who is more likely to adopt and comply with the electronic patient-reported outcome measure (ePROM) mobile application? A real-world study with cancer patients undergoing active treatment,” in which the authors identified factors influencing ePROM adoption and compliance in the real world. Real-world studies, such as the current study, are a valuable addition to previous ePROM studies in clinical research settings. However, there is room for discussion on how the associations revealed in this study should be acted upon.
Regarding ePROM adoption, the authors reported that “patients who had greater expectations regarding the ease of use and usefulness of the ePROM app were more likely to adopt the app than those who did not” [1]. Based on this result, they highlighted the importance of giving app users technical training [1]. Though this strategy has some merit, rapidly advancing aging population is likely to impede its effectiveness. Population aging not only is an issue in the Republic of Korea where the survey was conducted, but also is becoming a challenge worldwide [2]. Age is the factor driving the digital divide [3], indicating that simply giving the elderly technical training may not overcome any hesitancy to use an ePROM app. We propose that this issue can be addressed by employing informal support, where family members help the patient enter ePROM responses into the app. It is crucial that older adults have support from their families or others to conquer any initial fears or uncertainties about using new technologies [4]. Moreover, it is important that older people continue to use it, as this will benefit their digital skills [5], and we believe that family support will be invaluable from this perspective as well.
References
Lee M, Kang D, Kim S et al (2022) Who is more likely to adopt and comply with the electronic patient-reported outcome measure (ePROM) mobile application? A real-world study with cancer patients undergoing active treatment. Support Care Cancer 30(1):659–668. https://doi.org/10.1007/s00520-021-06473-6
Beard JR, Officer A, de Carvalho IA et al (2016) The World report on ageing and health: a policy framework for healthy ageing. Lancet 387(10033):2145–2154. https://doi.org/10.1016/S0140-6736(15)00516-4
Jun W (2021) A study on cause analysis of digital divide among older people in Korea. Int J Environ Res Public Health 18(16):8586. https://doi.org/10.3390/ijerph18168586
Tsai HS, Shillair R, Cotten SR (2017) Social support and “playing around”: an examination of how older adults acquire digital literacy with tablet computers. J Appl Gerontol 36(1):29–55. https://doi.org/10.1177/0733464815609440
Bottiroli S, Cavallini E, Dunlosky J, Vecchi T, Hertzog C (2017) Self-guided strategy-adaption training for older adults: transfer effects to everyday tasks. Arch Gerontol Geriatr 72:91–98. https://doi.org/10.1016/j.archger.2017.05.015
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MT drafted the first version of the letter. YI and UH provided additional input. All authors read and approved the final manuscript.
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Tsubaki, M., Ito, Y. & Haniuda, Y. Further thoughts on how the electronic patient-reported outcome measure (ePROM) can be implemented in the real world. Support Care Cancer 31, 58 (2023). https://doi.org/10.1007/s00520-022-07545-x
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DOI: https://doi.org/10.1007/s00520-022-07545-x