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‘Dark logic’: theorising the harmful consequences of public health interventions
  1. Chris Bonell1,
  2. Farah Jamal1,
  3. G J Melendez-Torres2,
  4. Steven Cummins3
  1. 1Department of Childhood, Families and Health, Institute of Education, University of London, London, UK
  2. 2Department of Social Policy and Intervention, Centre for Evidence-Based Intervention, University of Oxford, Oxford, UK
  3. 3Department of Social & Environmental Health Research, London School of Hygiene & Tropical Medicine, London, UK
  1. Correspondence to Professor Chris Bonell, Department of Childhood, Families and Health, Institute of Education, University of London, 18 Woburn Square, London WC1H 0NR, UK; c.bonell{at}


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.


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