title: Classification and prevalence of spin in abstracts of non-randomized studies evaluating an intervention.
abstract: BACKGROUND
  Spin represents specific reporting strategies, either intentional or unintentional, to convince the reader that the beneficial effect of the experimental intervention in terms of efficacy and safety is greater than that shown by the results. The objectives of this study were to 1) develop a classification of spin specific to non-randomized studies assessing an intervention and 2) estimate the prevalence of spin in abstracts of reports of such studies.
  
  
  METHODS
  In a first step, we developed a specific classification of spin for non-randomized studies by a literature review and pilot study. In a second step, 2 researchers trained in the field of methodology evaluated the prevalence of spin in the abstract of all non-randomized studies assessing an intervention published in the BioMed Central Medical Series journals between January 1, 2011 and December 31, 2013. All disagreements were resolved by consensus. We also determined whether the level of spin in abstract conclusions was high (spin reported without uncertainty or recommendations for further trials), moderate (spin reported with some uncertainty or recommendations for further trials) or low (spin reported with uncertainty and recommendations for further trials).
  
  
  RESULTS
  Among the 128 assessed articles assessed, 107 (84%) had at least one example of spin in their abstract. The most prevalent strategy of spin was the use of causal language, identified in 68 (53%) abstracts. Other frequent strategies were linguistic spin, inadequate implications for clinical practice, and lack of focus on harm, identified in 33 (26%), 25 (20%), and 34 (27%) abstracts respectively. Abstract conclusions of 61 (48%) articles featured a high level of spin.
  
  
  CONCLUSIONS
  Abstract of reports of non-randomized studies assessing an intervention frequently includes spin. Efforts to reduce the prevalence of spin in abstract for such studies are needed.
authors.affiliation: METHODS Team, Centre of Research in Epidemiology and Statistics Sorbonne Paris Cité (CRESS), UMR 1153, INSERM, Paris, France. clement.lazarus@aphp.fr.|Paris Descartes University, Sorbonne Paris Cité, Faculté de Médecine de Paris, Paris, France. clement.lazarus@aphp.fr.|Centre d'Épidémiologie Clinique, Hôpital Hôtel Dieu, Assistance Publique des Hôpitaux de Paris, 1, place du Parvis Notre-Dame, 75181, Paris, France. clement.lazarus@aphp.fr.
authors.forename: Clément
authors.initials: C
authors.lastname: Lazarus
authors.affiliation: METHODS Team, Centre of Research in Epidemiology and Statistics Sorbonne Paris Cité (CRESS), UMR 1153, INSERM, Paris, France. romana.haneef@aphp.fr.|Paris Descartes University, Sorbonne Paris Cité, Faculté de Médecine de Paris, Paris, France. romana.haneef@aphp.fr.
authors.forename: Romana
authors.initials: R
authors.lastname: Haneef
authors.affiliation: METHODS Team, Centre of Research in Epidemiology and Statistics Sorbonne Paris Cité (CRESS), UMR 1153, INSERM, Paris, France. philippe.ravaud@aphp.fr.|Paris Descartes University, Sorbonne Paris Cité, Faculté de Médecine de Paris, Paris, France. philippe.ravaud@aphp.fr.|Centre d'Épidémiologie Clinique, Hôpital Hôtel Dieu, Assistance Publique des Hôpitaux de Paris, 1, place du Parvis Notre-Dame, 75181, Paris, France. philippe.ravaud@aphp.fr.|French Cochrane Center, Paris, France. philippe.ravaud@aphp.fr.|Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA. philippe.ravaud@aphp.fr.
authors.forename: Philippe
authors.initials: P
authors.lastname: Ravaud
authors.affiliation: METHODS Team, Centre of Research in Epidemiology and Statistics Sorbonne Paris Cité (CRESS), UMR 1153, INSERM, Paris, France. isabelle.boutron@htd.aphp.fr.|Paris Descartes University, Sorbonne Paris Cité, Faculté de Médecine de Paris, Paris, France. isabelle.boutron@htd.aphp.fr.|Centre d'Épidémiologie Clinique, Hôpital Hôtel Dieu, Assistance Publique des Hôpitaux de Paris, 1, place du Parvis Notre-Dame, 75181, Paris, France. isabelle.boutron@htd.aphp.fr.|French Cochrane Center, Paris, France. isabelle.boutron@htd.aphp.fr.
authors.forename: Isabelle
authors.initials: I
authors.lastname: Boutron
mesh_terms: D000043:Abstracting and Indexing / Q000379:methods*; D015982:Bias; D006801:Humans; D012107:Research Design