Conducting breast cancer research during a pandemic isolation time

Objective: Aiming at the assistance of women with breast cancer, quality of life indicators can help in clinical practice, guide therapeutic intervention strategies, and evaluate the success of intervention after surgery and cancer treatment, in addition to defining parameters for actions. This perspective study is about the quality of life of patients treated for breast cancer at the Institution. However, as soon as the pandemic started, the need to readapt the way of filling out the questionnaires to an online model emerged. Our objective is to share the facilities and difficulties of online model research. Methods: Through the selection of patients for research that aimed to analyze the quality of life of patients with breast cancer, they were contacted by their registered e-mails in the institution system. Each patient received an explanation of the project through e-mail and the Free and Informed Consent Term (TCLE). After agreement, the survey link of the REDCap system directing the selected instrument to be filled in was sent. The analysis included a general questionnaire composed of demographic and clinical aspects (collected by electronic medical record data) and specific questionnaires. Results: In all, 477 e-mails were sent, 52 patients signed the TCLE (but 2 did not answer the research), 36 answered the questionnaires completely, and 14 incompletely. A total of 12 e-mails were returned (wrong e-mail address). Conclusion: During the pandemic period, new tools were incorporated in order to obtain data and maintain research. Moving to an online way brought the chance to keep studies, giving new possibilities to answer research remotely, but difficulties were added to this new kind of research. E-mail data, lack of explanation face-to-face, and the number of complete responses mainly in long questionnaires were some of the most tricky parts of this new way of study. Online strategy is a real option, but the success of the process depends on many variables.