Determining an appropriate sample size is vital in drawing realistic conclusions from research findings. Although there are several widely adopted rules of thumb to calculate sample size, researchers ...remain unclear about which one to consider when determining sample size in their respective studies. ‘How large should the sample be?’ is one the most frequently asked questions in survey research. The objective of this editorial is three-fold. First, we discuss the factors that influence sample size decisions. Second, we review existing rules of thumb related to the calculation of sample size. Third, we present the guidelines to perform power analysis using the G*Power programme. There is, however, a caveat: we urge researchers not to blindly follow these rules. Such rules or guidelines should be understood in their specific contexts and under the conditions in which they were prescribed. We hope that this editorial does not only provide researchers a fundamental understanding of sample size and its associated issues, but also facilitates their consideration of sample size determination in their own studies.
Long COVID (LC) refers to persistent symptoms after acute COVID-19 infection, which may endure for months or years. LC affects millions of people globally, with substantial impacts on quality of ...life, employment, and social participation. Ensuring access to effective, patient-centered care for LC demands evidence, grounded in inclusive representation of those affected by the condition. Yet survey studies frequently under-represent people with the most disabling disease presentations and racially and socio-economically marginalized groups. We aimed to describe a patient-engaged approach to developing a survey to inform public LC healthcare, and to assess its implementation in terms of enabling participation by diverse LC patients in Brazil.
Survey development was iterative, achieved through an interdisciplinary collaboration among researchers including people living with LC, and grounded in three guiding principles: (1) evidence-based; (2) inclusive, intersectional, and patient-centered understanding of chronic illness and research participation; and (3) sensitivity to the context of healthcare access.
The product of our collaboration was a longitudinal survey using a questionnaire assessing: LC symptoms; their clinical and functional evolution; and impacts on quality of life, household income, health service access, utilization, and out-of-pocket expenses. We illustrate how we operationalized our three principles through survey content, instrument design, and administration. 651 participants with diverse LC symptoms, demography, and socio-economic status completed the survey. We successfully included participants experiencing disabling symptoms, Black and mixed race participants, and those with lower education and income.
By centering patient experience, our novel, principles-based approach succeeded in promoting equity, diversity, and inclusion in LC survey research. These principles guiding patient-engaged collaboration have broad transferability. We encourage survey researchers working on chronic illness and in other contexts of marginalization and inequality to adopt them.
PDF
