Mixed Methods Research Designs

Convergent Parallel Design

• Used to obtain different but complementary data on a topic.
• Purpose: To combine the strengths of each type of data.
• Data Collection: Both quantitative and qualitative data are collected simultaneously.
• Study Components:
  • Cross-sectional data (survey).
  • Focus group data.
  • In-depth interviews.
• Timing: All data collected concurrently.
• Analysis: Results of each data type are brought together for analysis.
• Example: A local community health center conducting a healthcare needs study using multiple data types.

Explanatory Sequential Design

• Description: A two-phased study.
• Phase 1: Collection of quantitative data to address the study's questions.
• Phase 2: Collection of qualitative data to explain or build on the initial quantitative results.
• Example Study: Retention of older healthcare workers (Hodgkin et al., 2017).
• Background:
  • Staff shortages exist in the Australian health sector.
  • A large number of baby boomers are approaching retirement.
  • Exploring barriers and incentives for retaining older workers is critical.
• Overall Research Question: What are the organizational and social factors that impact on the retirement intentions of healthcare workers aged 55 years and over?
• Phase 1 Details:
  • Participants: n = 299
  • Data Collection: Survey.
  • Measures:
    • Demographic variables.
    • Retirement intentions.
    • Effort-reward imbalance measure.
    • General health measure.
• Phase 2 Details:
  • Participants: n = 17
  • Data Collection: In-depth interviews.
  • Focus: Exploring both retention and retirement intentions to explain quantitative findings.

Exploratory Sequential Design

• Description: Begins with and prioritizes qualitative data.
• Process: Results of the first (qualitative) stage are used to develop the second (quantitative) stage.
• Premise: Exploration of an issue or concept is required first.
• Usefulness: Developing theories or concepts when measures or instruments are not available.
• Example Study: Dellemain, Hodgkin & Warburton, 2017 – development of a practice theory for rural case management.
• Rationale: Limited research exists on the impact of rurality on case management, particularly in the Australian context.
• Design: Qualitative dominant, sequential, exploratory mixed-method design.
• Aim: To develop community-based rural case management practice theory.

Embedded Design

• Description: A mixed-method approach used to enhance understanding when a single dataset is insufficient.
• Function: Different types of data provide a supportive secondary role to offset limitations.
• Example Study: Workflow and work patterns in Australian residential aged care facilities (Hodgkin, Warburton & Savy, 2012).
• Research Focus: Accurately reporting and documenting activities undertaken by the healthcare workforce (e.g., division 1 nurse, division 2 nurse, allied health practitioner, ward clerk).
• Quantitative Data Collection: Structured observation technique over a two-hour period to document each role and the time taken for each activity.
• Qualitative Data Collection: Structured interviews with key personnel.
• Purpose of Qualitative Data: To provide crucial contextual data to explain factors such as:
  • Staff shortages for particular roles.
  • Qualifications held by staff in particular roles.
  • How the layout of the facility affected a task.