‘Dark logic’: theorising the harmful consequences of public health interventions

TLDR

Public health programmes can inflict serious harms, yet the assessment of such adverse effects remains largely neglected. This paper argues for evaluating potential harms and their underlying mechanisms in public health interventions and proposes a new process for developing “dark logic models” to guide such evaluations. The authors examine current evaluation protocols for addressing harmful outcomes and mechanisms, and outline a process that includes theorising agency‑structure interactions, building comparative understanding across similar interventions, and consulting local actors to identify how mechanisms may be derailed. The authors conclude that theorising dark logic models is essential to prevent the replication of harms in public health interventions.

Abstract

Although it might be assumed that most public health programmes involving social or behavioural rather than clinical interventions are unlikely to be iatrogenic, it is well established that they can sometimes cause serious harms. However, the assessment of adverse effects remains a neglected topic in evaluations of public health interventions. In this paper, we first argue for the importance of evaluations of public health interventions not only aiming to examine potential harms but also the mechanisms that might underlie these harms so that they might be avoided in the future. Second, we examine empirically whether protocols for the evaluation of public health interventions do examine harmful outcomes and underlying mechanisms and, if so, how. Third, we suggest a new process by which evaluators might develop 'dark logic models' to guide the evaluation of potential harms and underlying mechanisms, which includes: theorisation of agency-structure interactions; building comparative understanding across similar interventions via reciprocal and refutational translation; and consultation with local actors to identify how mechanisms might be derailed, leading to harmful consequences. We refer to the evaluation of a youth work intervention which unexpectedly appeared to increase the rate of teenage pregnancy it was aiming to reduce, and apply our proposed process retrospectively to see how this might have strengthened the evaluation. We conclude that the theorisation of dark logic models is critical to prevent replication of harms. It is not intended to replace but rather to inform empirical evaluation.