Introduction
Implementation of research findings in the real-world mostly depends on the dynamic, multidimensional, multi-level interplay between context, intervention and implementation strategies (Powell et al., 2025: Pfadenhauer, 2017). Many factors are determined without theoretical support; and even where contextual analyses are conducted, the findings are rarely used to inform subsequent project phases such as implementation, strategy and choices. There is no single method to study contexts are explained, the range of measurement tools, including micro and macro-level factors, are limited, and reporting guidelines or standards for reporting (Pinnock et al., 2017; Pinnock et al., 2017) are ambiguous regarding how contextual analysis to report (Rogers et al., 2020; McHugh et al., 2020). In probing more deeply into the context to discover hidden processes, it needs fewer resources than traditional methods. Such types of initiative are useful for contextual analyses, which are rarely well-resourced (Haines et al., 2021; Conte et al., 2019; Haines et al., 2021). Thus, it needs to understand that, to achieve the quality and success that execution research promises, we need to break open the “black box” of contextual analysis (Mielke et al., 2022).
A persistent crisis is undermining the value of scholarly inquiry: research outcomes frequently fail to address practical, real-world issues. These disconnect stems largely from an over-reliance on static, decontextualized methodologies. Approaches that prove effective in one situation rarely yield identical results in another, as circumstances are inherently dynamic and evolving. By the time traditional research is disseminated, the original problem has often transformed, rendering findings obsolete or irrelevant.
Several factors contribute to this challenge i) Context Dependency: The co-production of knowledge is profoundly shaped by local social, cultural, and situational requirements, which vary widely across groups and settings; ii)Changing Situations: Real-world problems are fluid; as one source aptly notes, "sometimes there just isn't a fixed solution"; iii) Failure of Generalization: Academic incentives often prioritize narrow, specialized studies over broad, adaptable solutions to complex, large-scale challenges; iv) Poor Implementation: Interventions falter when introduced into new environments without meaningful adaptation to local contexts; v) Methodological Limitations: Traditional methods like RCTs often "strip away" context to achieve internal validity, paradoxically rendering their findings difficult to apply in practice.