Jasper Faber

Chapter 2 44 design eHealth as a tool to respond to these needs. While doing so, professionals are advised to establish a trustful relationship with the target group, which could be achieved through personal contact and/or through trusted doctors or other key persons (Stuber et al., 2020). In addition, future research endeavors should take into account the challenges related to recruiting and researching vulnerable populations and take the appropriate methodological strategies to minimize the impact of those challenges. This could help improve the accessibility and affordability of eHealth innovations and thereby help equalizing inequalities in healthcare. 2.4.4 Strengths and limitations This study addressed the ever-increasing gap in health disparities by giving voice to a target group that is frequently overlooked in health research. Traditional approaches have received criticism as they, when executed irresponsibly, bring forth mistrust, feelings of stigmatization, and anxiety (Bastida et al., 2010). CBPR has gained increasing attention in addressing ethical challenges in health research, as it encourages equity and shared decision making and increases community involvement (Israel, 2013). By taking this approach, we ensured that our participants felt comfortable, safe, and especially involved during the research activities. The resulting insights directly carry our participants’ voices and are, therefore, a meaningful contribution to responsible digital health. While frequently people with a low SEP are expected to adapt their attitudes toward the intervention, we aim to have a more complete idea of how we should design interventions to be adapted to them. Although our study provides an in-depth insight into the attitudes of people living in a low-SEP neighborhood, the results are not generalizable toward all low-SEP contexts. First, we aimed at limiting possible feelings of stigmatization by sampling on neighborhood SEP. This would make it difficult to relate the findings directly to other studies that select participants on individual measures of SEP (e.g., education, income and, occupation). Yet, this different selection criterion allowed us to target a group that would otherwise have been excluded. For example, the questionnaire demographics indicate a relatively high percentage of participants who attained a follow-up education. In traditional studies, this part of the sample would have been seen as high-SEP and therefore excluded from the study. Socioeconomic determinants and barriers leading to disparities in health behavior are complex (Artiga & Hinton, 2018; van Wijk et al., 2019). Capturing them merely based on individual determinants is therefore problematic and has accumulated critique over the years (Braveman et al., 2005). Instead, our focus on neighborhood SEP takes into account other factors that have proven to have a

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