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Qualitative Study Design

Phenomenology

iconPurpose

Used to describe the lived experience of individuals.


 

iconDefinition

  • Now called Descriptive Phenomenology, this study design is one of the most commonly used methodologies in qualitative research within the social and health sciences.
  • Used to describe how human beings experience a certain phenomenon. The researcher asks, “What is this experience like?’, ‘What does this experience mean?’ or ‘How does this ‘lived experience’ present itself to the participant?’
  • Attempts to set aside biases and preconceived assumptions about human experiences, feelings, and responses to a particular situation.
  • Experience may involve perception, thought, memory, imagination, and emotion or feeling.
  • Usually (but not always) involves a small sample of participants (approx. 10-15).
  • Analysis includes an attempt to identify themes or, if possible, make generalizations in relation to how a particular phenomenon is perceived or experienced.

iconMethods

Methods used include:

  • participant observation
  • in-depth interviews with open-ended questions
  • conversations and focus workshops. 

Researchers may also examine written records of experiences such as diaries, journals, art, poetry and music.


 

strengths Strengths

Descriptive phenomenology is a powerful way to understand subjective experience and to gain insights around people’s actions and motivations, cutting through long-held assumptions and challenging conventional wisdom.  It may contribute to the development of new theories, changes in policies, or changes in responses.


 

limitations Limitations

  • Does not suit all health research questions.  For example, an evaluation of a health service may be better carried out by means of a descriptive qualitative design, where highly structured questions aim to garner participant’s views, rather than their lived experience.
  • Participants may not be able to express themselves articulately enough due to language barriers, cognition, age, or other factors.
  • Gathering data and data analysis may be time consuming and laborious.
  • Results require interpretation without researcher bias.
  • Does not produce easily generalisable data.

 

iconExample questions

  • How do cancer patients cope with a terminal diagnosis?
  • What is it like to survive a plane crash?
  • What are the experiences of long-term carers of family members with a serious illness or disability?
  • What is it like to be trapped in a natural disaster, such as a flood or earthquake? 

 

iconReferences