Factors influencing cardiovascular disease screening uptake and implementation strategies to enhance cardiovascular disease screening uptake in Singapore adults: a multi-method study protocol.
Ngoc Huong Lien Ha, Gigi Toh, Mary Ng, Jumana Hashim, Yen-Ting Tina Chen, Shao Chuen Tong, Joyce Tan, Zi Xuen Wong, Pei Fen Sam, Shir Gi Toh, Jun Hui Tan, Ke Xin Eh, Wei Lin Ng, Adelene Ong, Zhen En Ang
Abstract
Open AccessIntroduction: The prevalence of cardiovascular diseases (CVD) and CVD risk factors such as Type 2 Diabetes Mellitus (T2DM), hypertension and hypercholesterolemia has increased steadily worldwide. Population health screening is a common effort that promotes early detection, better prognosis and reduces disease burden. However, despite nationwide efforts, screening uptake for CVD risk factors in Singapore has remained moderately low (60.2%). Profiles of individuals who do not screen remain largely unknown, making them harder to reach via mainstream screening efforts. Existing literature has yet to organise factors systematically influencing CVD screening uptake, making it difficult to select a set of robust strategies to promote CVD screening uptake. This study aims to identify determinants of screening uptake for T2DM, hypertension and hypercholesterolemia in eligible adults residing in Western Singapore, and develop an implementation strategy toolkit to enhance screening uptake in this population. Methods: Prospective, theory-informed, two-phased, multi-method study design. Phase 1: rapid umbrella review, document review and qualitative interviews (n = 20-40) to examine existing evidence about behavioural factors influencing CVD risk factors and strategies implemented to increase uptake. Phase 2: identified determinants mapped onto strategies, its feasibility and acceptability. Strategies ranked high will be specified to clarify who will implement them, what actions are required and how they will be implemented in specific settings. The strategies are organised into an actionable toolkit, where the Implementation Research Logic Model technique will be adopted to articulate the interrelationships between determinants, hypothesised causal mechanisms and strategies. Both phases will be guided by established implementation science frameworks and co-design approach. Clinical Trial Registration: identifier [CRD42024566701].