Interdisciplinary and multidisciplinary working in data analysis Nick Emmel, Kahryn Hughes, and...

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Interdisciplinary and Interdisciplinary and multidisciplinary multidisciplinary working in data analysis working in data analysis Nick Emmel, Kahryn Nick Emmel, Kahryn Hughes, and Joanne Hughes, and Joanne Greenhalgh Greenhalgh University of Leeds University of Leeds

Transcript of Interdisciplinary and multidisciplinary working in data analysis Nick Emmel, Kahryn Hughes, and...

Page 1: Interdisciplinary and multidisciplinary working in data analysis Nick Emmel, Kahryn Hughes, and Joanne Greenhalgh University of Leeds.

Interdisciplinary and Interdisciplinary and multidisciplinary working multidisciplinary working

in data analysisin data analysis

Nick Emmel, Kahryn Nick Emmel, Kahryn Hughes, and Joanne Hughes, and Joanne

GreenhalghGreenhalgh

University of LeedsUniversity of Leeds

Page 2: Interdisciplinary and multidisciplinary working in data analysis Nick Emmel, Kahryn Hughes, and Joanne Greenhalgh University of Leeds.

ContentContent

• Our research and methodological Our research and methodological approachapproach

• Complexity in interdisciplinary and Complexity in interdisciplinary and multidisciplinary approaches in the multidisciplinary approaches in the researchresearch

• How we do interdisciplinary and How we do interdisciplinary and multidisciplinary researchmultidisciplinary research

• The outputs from these research activitiesThe outputs from these research activities

Page 3: Interdisciplinary and multidisciplinary working in data analysis Nick Emmel, Kahryn Hughes, and Joanne Greenhalgh University of Leeds.

DEFINING

Analysis Dimensions of social exclusion Methodological contributions from the 'extra-excluded'

FINDING DEVELOPING

Dissemination Access and retention strategies for existing and new programmes to address health and social care with the socially excluded

An iterative methodological strategy

Identification Who are the 'extra-excluded'?

Development Methods to recruit the 'extra-excluded’

Commentary How do the 'extra-excluded' interpret their exclusion and are the recruitment strategies appropriate / effective?

Methodological Evaluation of the utility of methods for recruiting the 'extra-excluded'?

Page 4: Interdisciplinary and multidisciplinary working in data analysis Nick Emmel, Kahryn Hughes, and Joanne Greenhalgh University of Leeds.

Critical reflexivityCritical reflexivity

• Two research sitesTwo research sites::– the locality in which we do the research (a low-the locality in which we do the research (a low-

income urban community) income urban community) – and ‘the team’ of qualitative researchersand ‘the team’ of qualitative researchers

• Strategies for enhancing reflexivityStrategies for enhancing reflexivity::– Tape recording team meetingsTape recording team meetings– demonstrating data analysis techniques to team demonstrating data analysis techniques to team – Writing memos to each otherWriting memos to each other– Mapping thematic findingsMapping thematic findings

Page 5: Interdisciplinary and multidisciplinary working in data analysis Nick Emmel, Kahryn Hughes, and Joanne Greenhalgh University of Leeds.

Definitions of multidisciplinary Definitions of multidisciplinary and interdisciplinary workingand interdisciplinary working• Multidisciplinary workingMultidisciplinary working: :

working in parallel to answer a working in parallel to answer a common research question but common research question but maintaining our own maintaining our own epistemological positions.epistemological positions.

• Inter-disciplinary workingInter-disciplinary working::we attempt to combine, negotiate we attempt to combine, negotiate and reconcile different and reconcile different epistemological positions. epistemological positions.

Page 6: Interdisciplinary and multidisciplinary working in data analysis Nick Emmel, Kahryn Hughes, and Joanne Greenhalgh University of Leeds.

A schematic of messy interdisciplinary and multidisciplinary working showing the trajectory of each researcher and outputs

Complexity and innovation

Page 7: Interdisciplinary and multidisciplinary working in data analysis Nick Emmel, Kahryn Hughes, and Joanne Greenhalgh University of Leeds.

Complexity: two types—Complexity: two types—uncertainty uncertainty

• Environmental uncertaintyEnvironmental uncertainty::exploratory nature of our research questions to exploratory nature of our research questions to identify and get hold of the socially excluded.identify and get hold of the socially excluded.

• Task uncertaintyTask uncertainty: : team members with different expertise “each team members with different expertise “each of whom has information relevant to the of whom has information relevant to the solution of a particular problem but none of solution of a particular problem but none of whom knows enough to act in isolation” whom knows enough to act in isolation” (Watts, 2005:4).(Watts, 2005:4).

Page 8: Interdisciplinary and multidisciplinary working in data analysis Nick Emmel, Kahryn Hughes, and Joanne Greenhalgh University of Leeds.

Interdisciplinary (combined) or Interdisciplinary (combined) or multidisciplinary (separate) working in the multidisciplinary (separate) working in the researchresearch• team meetings (combined) team meetings (combined)

• iterative strategy (combined)iterative strategy (combined)

• gathering the data (combined and gathering the data (combined and separate)separate)

• reframing the data in the context of the reframing the data in the context of the methodologies developed (e.g., access methodologies developed (e.g., access case methodology) and producing case methodology) and producing substantive theorisations of the data substantive theorisations of the data (combined and separate) (current stage).(combined and separate) (current stage).

Page 9: Interdisciplinary and multidisciplinary working in data analysis Nick Emmel, Kahryn Hughes, and Joanne Greenhalgh University of Leeds.

An example of the mappingAn example of the mapping

Page 10: Interdisciplinary and multidisciplinary working in data analysis Nick Emmel, Kahryn Hughes, and Joanne Greenhalgh University of Leeds.

Interdisciplinary and Interdisciplinary and multidisciplinary working: multidisciplinary working: practicepractice

• Externalising internal strategies for making sense of dataExternalising internal strategies for making sense of data

• Integration: enabling integration of different data analyses Integration: enabling integration of different data analyses in producing explanationsin producing explanations

• Innovation: combining expertise brings the data into Innovation: combining expertise brings the data into broader fields of visibilitybroader fields of visibility

• Addressing complexity: these ways of working enable us to Addressing complexity: these ways of working enable us to address issues of task and environmental uncertaintyaddress issues of task and environmental uncertainty

Page 11: Interdisciplinary and multidisciplinary working in data analysis Nick Emmel, Kahryn Hughes, and Joanne Greenhalgh University of Leeds.

Interdisciplinary and Interdisciplinary and multidisciplinary working—some multidisciplinary working—some observationsobservations• Make analyses of large data-sets more manageable and Make analyses of large data-sets more manageable and

creativecreative• Bring multiple epistemologies to bear on our research Bring multiple epistemologies to bear on our research

questionsquestions• Address environmental and task uncertainties Address environmental and task uncertainties • Innovation is encouraged because analyses are triangulated Innovation is encouraged because analyses are triangulated

through interdisciplinary and multidisciplinary workingthrough interdisciplinary and multidisciplinary working• Supports innovation in terms of the production of conceptual Supports innovation in terms of the production of conceptual

and methodological outputs that can be disseminatedand methodological outputs that can be disseminated• While the research process is necessarily messy, it is While the research process is necessarily messy, it is

nevertheless closely managed through these strategies of nevertheless closely managed through these strategies of reflexivityreflexivity

• How the research field is constituted through multiple How the research field is constituted through multiple epistemological interests of the research team remains epistemological interests of the research team remains available for analyses throughout studyavailable for analyses throughout study

• Outputs belong to each team memberOutputs belong to each team member