title: Analysing narrative data using McCormack's Lenses.
abstract: OBJECTIVE
  In health and social care research, pure naturalistic enquiry often seeks to understand personal experiences, and adopts data collection methods that can generate vast amounts of rich, thick text. This article demonstrates the way in which the author used a particular approach to analyse the complex narrative data arising from her MPhil research into experiences of lesbian parents in the healthcare system.
  
  
  BACKGROUND
  Narrative data is often cumbersome, prolific and chaotic, and it can be difficult to manage such data effectively while remaining sympathetic to the original meaning of the storyteller. Guidance exists on what narrative analysis should achieve, but finding ways of interpreting and demonstrating meaning in different types of stories can be challenging.
  
  
  METHODS
  The data discussed here arose from six unstructured interviews with ten lesbian parents from across the UK, collected in 2003-04 during the author's MPhil studies.
  
  
  METHODS
  The use of McCormack's Lenses to analyse narrative data supported the philosophical underpinnings of Heideggerian phenomenology which provided the framework for the research endeavour.
  
  
  CONCLUSIONS
  Locating the analysis method that best suits the methodology, purpose and data is not always easy. Naturalistic or qualitative researchers may need to make extra effort to explain the philosophical and practical aspects of their work, and while it can be tempting to select an adequate analysis approach, seeking out the framework which best fits the data will enhance the credibility of the findings
  
  
  CONCLUSIONS
  McCormack's Lenses provides a flexible framework for the analysis of complex narrative data. It enables the researcher to take core themes and stories of experience in the original story and reveal these to the reader with openness. As well as remaining true to the original story, the framework enables the researcher to demonstrate that the reported findings are situated in the original data.
authors.affiliation: Faculty of Society and Health, Bucks New University, Uxbridge, UK. lesley.dibley@bucks.ac.uk
authors.forename: Lesley
authors.initials: L
authors.lastname: Dibley
mesh_terms: D003627:Data Interpretation, Statistical; D005260:Female; D018452:Homosexuality, Female; D006801:Humans; D033262:Narration; D010290:Parents; D006113:United Kingdom