Article type
Year
Abstract
Background:
A logic model has been described as “a graphical summary of the pathways from intervention or individual intervention components to anticipated outcomes” (Anderson 2011). Rehfuess and colleagues (2017) also suggest that logic models can offer a common language for communication between the research team and stakeholders.
Objectives:
To develop and use a logic model as a ‘scaffolding’ framework to synthesise qualitative evidence on experiences of residents, families and staff on the impact of robotic companion animals (robopets) on health and wellbeing.
Methods:
We developed a logic model which would be flexible, with scope to develop as the data emerged. The model was informed by our knowledge of the literature from background reading and by our previous reviews in care-home research.We used a framework based synthesis approach with the logic model providing the structure for data extraction. Two reviewers extracted data from the 14 included qualitative papers.
Results:
We piloted data extraction using two papers to assess the suitability of the framework and to ensure consistency of extraction. Post data-extraction discussion between reviewers identified where data did and did not support the components of the model, as well as finding ‘new’ components. Therefore, we revised the model and shared it with the wider team and members of the Expert Advisory Group (a care-home manager, a care-home owner and a vet).The purpose of these meetings was to draw on their perspectives and tacit knowledge, and explore whether the revised model made sense, and if it helped their understanding of the potential impact of robopets. Feedback suggested that the second model resonated with the researchers and practitioners.
Conclusions:
Advantages of the logic model framework synthesis were efficiency and flexibility. Having an initial framework to code the data enabled us to work within tight time constraints; and, although we had identified a priori components, there was scope for components to emerge de novo. The logic model also offered a visual tool which facilitated communication and mutual understanding of how robopets may impact health and wellbeing in care homes.
Patient or healthcare consumer involvement:
Representatives from care home settings and animal welfare were involved as members of the Expert Advisory Group.
A logic model has been described as “a graphical summary of the pathways from intervention or individual intervention components to anticipated outcomes” (Anderson 2011). Rehfuess and colleagues (2017) also suggest that logic models can offer a common language for communication between the research team and stakeholders.
Objectives:
To develop and use a logic model as a ‘scaffolding’ framework to synthesise qualitative evidence on experiences of residents, families and staff on the impact of robotic companion animals (robopets) on health and wellbeing.
Methods:
We developed a logic model which would be flexible, with scope to develop as the data emerged. The model was informed by our knowledge of the literature from background reading and by our previous reviews in care-home research.We used a framework based synthesis approach with the logic model providing the structure for data extraction. Two reviewers extracted data from the 14 included qualitative papers.
Results:
We piloted data extraction using two papers to assess the suitability of the framework and to ensure consistency of extraction. Post data-extraction discussion between reviewers identified where data did and did not support the components of the model, as well as finding ‘new’ components. Therefore, we revised the model and shared it with the wider team and members of the Expert Advisory Group (a care-home manager, a care-home owner and a vet).The purpose of these meetings was to draw on their perspectives and tacit knowledge, and explore whether the revised model made sense, and if it helped their understanding of the potential impact of robopets. Feedback suggested that the second model resonated with the researchers and practitioners.
Conclusions:
Advantages of the logic model framework synthesis were efficiency and flexibility. Having an initial framework to code the data enabled us to work within tight time constraints; and, although we had identified a priori components, there was scope for components to emerge de novo. The logic model also offered a visual tool which facilitated communication and mutual understanding of how robopets may impact health and wellbeing in care homes.
Patient or healthcare consumer involvement:
Representatives from care home settings and animal welfare were involved as members of the Expert Advisory Group.