Research methods in clinical psychology: An introduction for students and practitioners Chris Barker

1
Research methods in clinical psychologyAn
introduction for students and practitionersChris
Barker, Nancy Pistrang, and Robert Elliott

• CHAPTER 12
• Analysis, interpretation and dissemination

2
Overview

• Interpretation
• What is the strength and significance of the
  findings?
• What are their scientific and professional
  implications?
• Dissemination
• Making the findings known

3
Qualitative analysis overview

• Analysis is an inductive process
• Many different approaches
• vary in depth of interpretation / inference
• method should fit research questions and the data
• Generic processes / general principles
• Within-case and cross-case analysis

4
Frequently used approaches

• Grounded theory
• Interpretative phenomenological analysis (IPA)
• Discourse analysis
• Content analysis

5
Preliminaries to data analysis

• Transcriptions
• different conventions
• anonymity
• Immersion in the data

6
Generic processes in analysis

• identifying meaning
• categorising
• integrating
• Note cyclical, not linear

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Identifying meaning

• identifying and labelling ideas
• line-by-line (microanalysis)
• meaning units
• codes (labels) in vivo v. abstract
• implicit v. explicit meaning

8
Categorising

• themes or categories
• method of constant comparison
• saturation

9
Integrating

• linking themes / categories
• conceptual framework or hierarchical structure

10
Computer packages for qualitative analysis

• Good for sorting and searching, linking
  categories
• e.g., ATLAS-ti, NUDIST

11
Writing up the results

• Different models
• conventions for different genres of qualitative
  research
• what best captures the essence of the data?
• be guided by the research questions
• Narrative account
• tell a story
• describe the phenomenon
• illustrate with examples
• Table of themes/ tree diagrams

12
Good practice in qualitative analysis

• guidelines for evaluating qualitative research,
  e.g.
• credibility checks
• have the research questions been answered?
• is the analysis coherent and integrated?
• Elliott et al. (1999) Willig (2001) Yardley
  (2000)

13
Quantitative approaches

• Measures of strength and significance of the
  findings

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Statistical conclusion validity

• Was the study sensitive enough?
• Large enough sample?
• Error minimised in measurement and design?
• Do the variables covary?
• Were the statistical methods appropriate?
• If so, how strongly?
• Significance
• (Shadish, Cook Campbell, 2002)

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Significance of the findings

• Statistical significance
• Effect sizes
• Clinical significance

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Statistical significance

• p-value (alpha level) of statistic
• e.g., ?2 (1) 4.7, p 0.03
• null hypothesis testing framework
• currently controversial
• replace with confidence intervals?
• value dependent on sample size

17
Effect size

• measure of magnitude
• independent of sample size
• depends on statistical test
• often classified into small, medium and large
  (see Cohen)

18
Effect sizes Meta-analysis

• Pioneered by Smith Glass (1977)
• Aggregates several studies, using effect sizes
• Advantages
• Quantitative effect size index
• Can also examine study variables (e.g.,
  investigator allegiance)
• However GIGO (garbage in, garbage out)!

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Clinical significance

• Measure of meaningfulness
• do patients actually improve?
• endstate functioning
• Jacobson and Truax (1991)
• reliable change
• clinical significance cut-offs
• Number needed to treat
• used in evidence-based medicine

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External validity

• Can the findings be generalised across
• persons
• settings
• times?
• Replication
• Literal
• Operational
• Constructive

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How research is used and interpreted

• Dissemination
• research as a public activity
• feedback to staff and managers
• feedback to participants
• Publication
• Research utilisation
• does research affect policy?
• models of research utilisation (Weiss, 1986)
• Political issues