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To HIIT or Not to HIIT – Decision-Making Among Individuals With Type 2 Diabetes (T2D)

Project Description

Objective

The study aims to explore the decision-making processes of individuals with type 2 diabetes (T2D) as they navigate the ongoing choice of whether to participate in high-intensity interval training (HIIT) as part of a diabetes self-management programme (DSMP).

Research Questions

  • What is at stake for individuals when deciding whether to commit to HIIT?
  • Which mechanisms influence their continuous decisions to attend or skip sessions?
  • What concerns and perceived benefits shape the decision-making process?
  • How do healthcare professionals, peers, and family members influence participants' decisions?

Study Design

This is a qualitative study embedded within the LIVING study at a trial site where HIIT is offered as part of the DSMP.

Participants

Participants are recruited from the LIVING study.

Sample

  • ~4 non-HIIT participants
  • ~6 HIIT participants

Data Collection

Semi-structured interviews

  • Non-participants: Interviewed once after their decision
  • Participants: Interviewed three times
    • After initial decision
    • After completion of the intervention
    • One year after completion of the intervention

Diaries

  • Participants complete short diaries for each HIIT session
  • Captures factors influencing attendance and reflections on participation

Observations

  • Participant observations conducted during HIIT sessions
  • Focus on engagement and interaction

Analytical Approach

Thematic Analysis

  • Data will be coded and analysed using thematic analysis
  • Focus on identifying patterns and central themes across data sources

Theoretical Framework

  • Focus on understanding behaviour related to physical activity initiation and maintenance

Folder and File Structure

The repository is organized as follows:

  • analysis/
    Research-book, reflections etc.

  • doc/
    Interview guides, diaries, protocols, and analytic notes


Data Management and Analysis

  • Transcription will be done using GoodTape
  • All data analysis are conducted N-vivo
  • Data will be stored using Midt-x

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