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Webinar 6 development of a longitudinal qualitative database

Leveraging Data to Make Better Decisions - An Overview of Databases

  • Webinar Series

Webinar 6:Development of a Longitudinal Qualitative Database

Mary Crea-Arsenio MSc.

Andrea Baumann RN, PhD

Mabel Hunsberger RN, PhD

Nursing Health Services Research Unit (NHSRU)

McMaster University

Date: Monday March 18, 2013

Time: Noon- 1:00PM (EST)


Leveraging Data to Make Better Decisions - An Overview of Databases

  • Webinar Series


  • Types of Research

  • Types of Data

  • Qualitative Longitudinal Research (QLR)

  • Use of QLR in Policy Research

  • Development of a Qualitative Longitudinal Database

Types of data

Leveraging Data to Make Better Decisions - An Overview of Databases

  • Webinar Series

Types of Data

Primary data

  • collected to answer a specific research question.

    Secondary data

  • collected by some other user.

Source: Wunsch, Harrison, & Rowan (2005).

What is qualitative research
What is Qualitative Research? Databases

“Qualitative research seeks to identify, map and explore the multiple perspectives held by individuals and groups within their social setting.”

Source: Molloy, Woodfield & Bacon, 2007

What is quantitative research
What is Quantitative Research? Databases

“Quantitative research is a formal, objective, systematic process in which numerical data are used to obtain information about the world.”

Source: Burns & Grove, 2005.

Cross sectional
Cross-Sectional Databases

  • Data collected on a sample of the population at a single point in time

  • Used to examine relationships between variables of interest

Source: Barratt & Kirwan, 2009

What is longitudinal research
What is Longitudinal Research? Databases

  • Data are collected over time

  • Participants are the same or are comparable

  • Analysis includes comparison of data between or within points in time

  • Quantitative or qualitative

Source: Ruspini, 1999

Qualitative Longitudinal Databases

Provides an in-depth understanding of how and why change occurs.

Quantitative longitudinal

Measures the extent of change and identifies prevalence of factors that affect change.

Source: Molloy, Woodfield & Bacon, 2007

Longitudinal research quantitative versus qualitative
Longitudinal Research: DatabasesQuantitative versus Qualitative

Source: Molloy, Woodfield & Bacon, 2007

Advantages of longitudinal research
Advantages of Longitudinal Research Databases

  • Examines change over time

  • Allows for exploration of topics with a developmental aspect (e.g. processes related to aging, career trajectories)

  • Includes changing context

Qualitative longitudinal research qlr
Qualitative Longitudinal Research (QLR) Databases

  • Provides information on people’s perspectives and how and why these are perceived to have changed over time

  • Explores changes over time and processes associated with these changes

  • Detailed accounts of people’s experience of particular situations

Source:Farrall, 2007; MacMillan, 2011; Molloy, Woodfield & Bacon, 2007

Key principles of qlr
Key Principles of QLR Databases

Temporal element

  • annual waves of data collection


  • what changes from year to year and the processes associated with that change

    Relational account

  • how change is related to political and economic contexts

    Role of multiple factors in complex systems

Source: MacMillan, 2011

Why use qlr in policy research
Why Use QLR in Policy Research? Databases

  • Produces in-depth knowledge about the individuals or groups within particular policy contexts.

  • Can be used to evaluate policy interventions because it is flexible and based on real-time developments

Source: Neale & Morton, 2012.

Why use qlr in policy research1
Why use QLR in Policy Research? Databases

Examines experiences and perceptions of those affected by a policy decision over time

e.g. realistic evaluation model emphasizes how and why policies work, and in what contexts (Pawson and Tilley, 1997).

Source: Molloy, Woodfield & Bacon, 2002.

Advantages of qlr
Advantages of QLR Databases

  • In-depth analysis of phenomenon

  • Participants can reflect on responses provided in earlier interviews

  • Ability to link micro to macro- understanding change in relation to larger contexts (e.g. political, economic).

Source: Farrall, 2007.

Disadvantages Databases

  • Maintaining sample over time

  • Amount of data generated longitudinally

  • Analysis is complex and takes time

Ethical considerations
Ethical Considerations Databases

  • Confidentiality

  • Repeated informed consent

  • Storing data

Qlr research designs
QLR Research Designs Databases

  • In-depth interviews

    • fixed time intervals, same people, led by same research team

  • Retracing respondents from an earlier study

  • A long term follow-up of a particular group

Developing a qualitative longitudinal database

Developing a Qualitative Longitudinal Database Databases

Providing an example

Nursing graduate guarantee 2007 2012
Nursing Graduate Guarantee 2007-2012 Databases

  • Ontario policy initiative launched in 2007

  • Incentive funding for employers

    • hire new graduate nurses

    • temporary full-time supernumerary positions

    • six months

  • Evaluated annually

Source: Baumann, Hunsberger, Crea-Arsenio, & Idriss-Wheeler, 2012.

Policy evaluation
Policy Evaluation Databases

Research question:

What is the impact of the NGG on full-time employment of new graduate nurses?

Sample Databases

  • Examined employer perceptions of NGG over time

  • Sampled repeatedly at one year intervals over five years (2007-2012)

  • Semi-structured interview guide

  • Annual focus groups

Applying principles of qlr
Applying Principles of QLR Databases


Interview guide
Interview Guide Databases

  • Developed in 2007 to evaluate employers perceptions of NGG

  • Questions added as new ideas emerge from data each year

  • Questions guided by unique context of each year

Coding data
Coding Data Databases

  • Open coding: line-by-line coding independently by two researchers

  • Compared across researchers to establish common themes

  • Coding structure entered into database and used as base for following year’s analysis

  • New themes emerge each year

Coding challenges
Coding Challenges Databases

  • Data collection can be difficult at the outset because hard to know what data will be significant over time

  • Data may seem preliminary because data collection is on-going

  • Evidence of change may take years to emerge

Source: Neale, 2011.

How qlr data can inform policy
How QLR Data Can Inform Policy? Databases

  • How do stakeholder perceptions change over time?

  • What contextual factors impact stakeholders perceptions? How do they impact perceptions?

  • What changes are significant for policy-makers?

  • How can policy influence stakeholder behaviours and attitudes?

Data analysis
Data Analysis Databases

  • Analyze cross-sectional data after each wave of data collection

    • Longitudinal analysis of each case (creating employer profiles)

    • Longitudinal analysis across cases to examine change over waves of data collection

Use of software
Use of Software Databases

  • QSR N-vivo qualitative software allows researchers to develop database of interview data

  • Able to hold large amounts of data

  • Can append new data annually

Challenges of using software
Challenges of Using Software Databases

  • Does not analyze data; stores data

  • Longitudinal data cleaning can be time consuming

  • Meaning of codes may change over time

  • Expensive

Employer qualitative database an example of qlr research
Employer Qualitative Database- DatabasesAn Example of QLR Research

Five years of interview data including 196 organizations participating in 38 focus groups:

  • Examine changes in employer perceptions of hiring new graduates over time

  • Evaluate change in ability to offer full-time employment to new graduate nurses over time

  • Describe employer perceptions of changing political and economic contexts

New member nurse ft employment source baumann et al 2012
New Member Nurse FT Employment Databases(Source: Baumann et al., 2012)

Source: Baumann, Hunsberger, Crea-Arsenio & Idriss-Wheeler, 2012.

Understanding the change over time
Understanding the Change Over Time Databases

  • Decrease in FT employment in 2010 was a result of a number of factors related to employer participation in NGG

  • Interview findings provided context for change and allowed researchers to examine the factors associated with this change

Factors affecting full time
Factors Affecting Full-Time Databases

  • Economic downturn impacted number of FT positions available for new graduates

  • High participation in early years of initiative limited employers ability to hire as many new graduates in 2010.

  • Number of new graduates hired in 2010 would have been even less had the NGG funding not been available.

Source: Baumann, Hunsberger, & Crea-Arsenio & Idriss-Wheeler, 2011.

Context for policy
Context for Policy Databases

  • Qualitative database allowed for:

    • an examination of employer perspectives over time

    • an understanding of change in employer hiring practices

  • Provided evidence for policy-makers to continue to invest in new graduate nurses

Conclusions Databases

  • Developing qualitative databases can provide researchers with detailed information about perceptions and experiences over time

  • Qualitative databases can be used to enhance quantitative databases

  • Databases allow opportunity for secondary analysis of qualitative data

References Databases

Barratt, H. & Kirwan, M. (2009). Design, Application, Strengths & Weaknesses of Cross-Sectional Studies. HealthKnowledge. Avaialable:


Burns, N. & Grove, S.K. (2005) The Practice of Nursing Research: Conduct, Critique, and Utilization (5th Ed.). St. Louis, Elsevier Saunders.

Baumann, A., Hunsberger, M.,Crea-Arsenio, M. & Idriss-Wheeler, D. (2012). Health Human Resource Series Number 35. Employment integration of nursing graduates: Evaluation of a provincial policy strategy. Hamilton, Ontario: Nursing Health Services Research Unit, McMaster University.

Baumann, A., Hunsberger, M., &Crea-Arsenio, M. (2011). Health Human Resource Series Number 29. Employment integration of nursing graduates: Evaluation of a provincial policy strategy. Hamilton, Ontario: Nursing Health Services Research Unit, McMaster University.

References Databases

Farrall, S. (2007). What is qualitative longitudinal research? Papers in Social Research Methods Qualitative Series no 11. London School of Economics and Political Science Methodology Institute .

Molloy, D., Woodfield, K. & Bacon, J. (2007). Longitudinal qualitative research approaches in evaluation studies. Department for Work and Pensions Working Paper No. 7, London: HMSO.

Ruspini, E. (1999). Longitudinal research and the analysis of social change. Quality and Quantity, 33, 219–227.

MacMillan, R. (2011). Seeing things differently? The promise of qualitative longitudinal research on the third sector. Third Sector Research Centre Working Paper 56.

Neale, B. and Morton. S (2012) Creating Impact through QL research. Timescapes Methods Guide Series, No 20.

Wunsch, H., Harrison, D., Rowan, K. (2005). Health Services Research in critical care using administrative data. Journal of Critical Care, 20, 264-269.

Contact information
Contact Information Databases

Andrea Baumann, PhD

Scientific Director

Nursing Health Services Research Unit

McMaster University

Michael DeGroote Centre for Learning

MDCL 3500

(905) 525-9140 ext. 22581

[email protected]