Background: Globally, pre-eclampsia and eclampsia are major contributors to maternal and perinatal mortality; of which the vast majority of deaths occur in less developed countries. In addition, a disproportionate number of morbidities and mortalities occur due to delayed access to health services. The Community Level Interventions for Pre-eclampsia (CLIP) Trial aims to task-shift to community health workers the identification and emergency management of pre-eclampsia and eclampsia to improve access and timely care. Literature revealed paucity of published feasibility assessments prior to initiating large-scale community-based interventions. Arguably, well-conducted feasibility studies can provide valuable information about the potential success of clinical trials prior to implementation. Failure to fully understand the study context risks the effective implementation of the intervention and limits the likelihood of post-trial scale-up. Therefore, it was imperative to conduct community-level feasibility assessments for a trial of this magnitude. Methods: A mixed methods design guided by normalization process theory was used for this study in Nigeria, Mozambique, Pakistan, and India to explore enabling and impeding factors for the CLIP Trial implementation. Qualitative data were collected through participant observation, document review, focus group discussion and in-depth interviews with diverse groups of community members, key informants at community level, healthcare providers, and policy makers. Quantitative data were collected through health facility assessments, self-administered community health worker surveys, and household demographic and health surveillance. Results: Refer to CLIP Trial feasibility publications in the current and/or forthcoming supplement. Conclusions: Feasibility assessments for community level interventions, particularly those involving task-shifting across diverse regions, require an appropriate theoretical framework and careful selection of research methods. The use of qualitative and quantitative methods increased the data richness to better understand the community contexts.
- Community-based interventions
- Feasibility study