Table 5.

Stages of the Q-methodology study (Phase 2a)³⁸

Stage	Summary of how this will be implemented in this study
1. Selecting the Q-set (sample of card statements)	The statements used in a Q-study can be generated through a number of diverse sources. In this study, the Q-set will be created from the emerging initial programme theories and potential contexts, mechanisms and outcomes identified from the literature reviewed in Phase 1a. Q-sets can contain between 30–80 statements.43 Examples of statements may include: Professionals decide what is best for the stroke survivor, flexibility and freedom to decide what works best for me, understanding the person and their needs, being able to get support from a wide range of local and community organisations.
2. Select the P-set (sample of participants)	This stage involves the selection of participants who are considered to be ‘information rich’ (or key informants) and likely to hold a range of viewpoints, and in this case, have insights and experiences relevant to the developing programme theories. In this case, stroke survivors (n=20), multidisciplinary community-rehabilitation practitioners (n=20) and team managers (n=8) will be recruited to participate in the Q-methodology study.
3. The Q-sorting process (ranking of the cards by participants) and brief follow-up interview	In this stage, participants will be asked to rank the ‘importance’ of the statements according to a condition of instruction, which in this case is in response to the question ‘what is important to making supported self-management work for you?’ Participants will be asked to sort the cards into piles of agree, disagree and neutral and then to rank them in order of importance on a bell-shaped Q-grid from most to least important. A short follow-up interview is conducted with all participants to invite them to explain the position of their cards. In this study, it is intended that these explanations will help to identify the importance of specific components or structures involved in supporting self-management but also to provide insights into how contexts, mechanisms and outcomes link together.
4. Factor analysis and interpretation	Once the cards/statements have been sorted by participants, correlation and factor analysis is performed using a statistical programme such as Ken-Q. The factor analysis identifies groups of participants who have rank ordered the statements in a similar fashion and share similar perspectives.43 A description of these shared views are then presented for qualitative interpretation, in this case, shared views on what is important for making supported self-management in stroke work and views on the most important and least important statements in each ‘factor’. This interpretation tells the story.