Triangulating visual and verbal data to enhance research interviews with people with learning disabilities

Background: People with learning disabilities often use visual data such as photographs and graffiti walls to express themselves, and recently there has been a rise in research methods that include visual data collection. Visual data can be collected during interviews with people with disabilities by using communication tools such as Talking Mats.

Aim: To explore the benefits of triangulating visual and verbal data collected through interviewing people with learning disabilities.

Method: A new multimethod approach was used involving the collection and analysis of visual and verbal data. Six participants with mild-to-moderate learning disabilities were interviewed about their sleep issues using the Talking Mats tool, which involves the placement of picture cards and symbols to express feelings or opinions, and through questions about their experience of sleep issues, to which they responded verbally and non-verbally. Data were interpreted using triangulation and compared with a Likert-type scoring system.

Findings: The triangulation of visual and verbal data provided the researchers with a greater understanding of participants’ experiences and perceptions about sleep issues than simply summing responses to Talking Mats using a Likert-type scale.

Conclusion: The use of a multimethod approach to data collection gives visual and verbal data equal status and provides a greater depth of understanding of the findings than either data set would provide in isolation. Consequently, this can increase the credibility and confirmability of research findings and enhance insight into the phenomena under investigation.