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Poster Numbers 39 to 45 – Methods: Poster No: 41
Analysis in qualitative longitudinal research: possibilities, benefits and challenges
  1. Emma Carduff,
  2. Murray Scott and
  3. Kendall Marilyn
  1. University of Edinburgh, Scotland, UK

Abstract

Background Qualitative longitudinal research (QLR) generates rich data which would seem ideal for exploring the dynamic experiences of patients towards the end of life, yet most studies in palliative care are cross-sectional.

Aim Taking a case study from a QL project I will highlight the rich analytical possibilities which result from QLR compared to a snapshot approach, while reflecting on the challenges and how they can be overcome.

Methods The project adopted a qualitative longitudinal design, employing indepth interviews with 16 participants with metastatic colorectal cancer who had advanced disease but were expected to survive a year. Narrative and thematic analyses were employed to capture the major issues and themes at each time point and longitudinal analysis was conducted to explore how the participants' experiences evolved over time.

Key findings Thematic analysis at each time point allows the researcher to synthesise the experiences of the group as they approach the end of their lives. Although useful for informing practice, thematic techniques may neglect the nuances of the individual experience. Narrative techniques allow the researcher to maintain the participant's story rather than fragmenting it, thus better capturing the individual experience. Longitudinal analysis further enhances this interrogation as it follows changes over time. Managing the immense volume of data that is generated in QLR can be challenging so the use of a carefully designed strategy for the analysis, and a qualitative research computer package (such as NVivo) can confront some of the complexities.

Conclusions The range of analytical possibilities available in QLR means that with careful planning and reflexive practice the benefits outweigh the challenges. The findings can inform us about how the participant's experience changes in real time which is not possible with cross-sectional analysis. Such research can help model patient-centred healthcare which is responsive to dynamic needs.

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