Patient engagement in health implementation research: A logic model

Abstract Introduction Growing evidence supports patient engagement (PE) in health implementation research to improve the quality, relevance and uptake of research. However, more guidance is needed to plan and operationalize PE before and throughout the research process. The aim of the study was to develop a logic model illustrating the causal links between context, resources, activities, outcomes and impact of PE in an implementation research programme. Methods The Patient Engagement in Health Implementation Research Logic Model (hereafter the Logic Model) was developed using a descriptive qualitative design with a participatory approach, in the context of the PriCARE programme. This programme aims to implement and evaluate case management for individuals who frequently use healthcare services in primary care clinics across five Canadian provinces. Participant observation of team meetings was performed by all team members involved in the programme and in‐depth interviews were conducted by two external research assistants with team members (n = 22). A deductive thematic analysis using components of logic models as coding categories was conducted. Data were pooled in the first version of the Logic Model, which was refined in research team meetings with patient partners. The final version was validated by all team members. Results The Logic Model highlights the importance of integrating PE into the project before its commencement, with appropriate support in terms of funding and time allocation. The governance structure and leadership of both principal investigators and patient partners have significant effects on PE activities and outcomes. As an empirical and standardized illustration that facilitates a shared understanding, the Logic Model provides guidance for maximizing the impact of patient partnership in various contexts for research, patients, providers and health care. Conclusion The Logic Model will help academic researchers, decision makers and patient partners plan, operationalize, and assess PE in implementation research for optimal outcomes. Patient or Public Contribution Patient partners from the PriCARE research programme contributed to developing the research objectives and designing, developing and validating data collection tools, producing data, developing and validating the Logic Model and reviewing the manuscript.


| INTRODUCTION
Literature on patient engagement (PE) in research has increased exponentially in the last decade. The many benefits of having patients as partners in research (hereafter patient partners) are well documented. PE can improve the quality of research 1-4 by co-designing the study's protocols, choosing relevant outcomes, 5 improving processes and ethical practises, 2,4 as well as validating research instruments. 4

PE
can also increase study enrolment. 5 Academic researchers who involve patients in research recognize patients' experience as expertise. 4 Based on patients' priority and holistic needs assessment, 6 this strategy can improve the relevance and uptake of research. 1,6,7 PE is more effective when patients with lived experience are meaningfully involved as research team members. 8 Involving patients in key aspects of implementation research can also facilitate and enhance implementation processes, 9 which can improve outcomes for both the research process and patient healthcare. 2 Patients' perspectives can produce innovative solutions that improve the health and well-being of the population. 7,10 PE has positive impacts on researchers and patient partners such as enhanced skills, and increased self-confidence, social support, learnings and satisfaction. 2,4,7 Many tools and frameworks have been proposed to assess PE in implementation research. [11][12][13] In a systematic review that includes 65 frameworks, Greenhalgh et al. 14 classified them into five categories: power-focused; priority-setting; study-focused; reportfocused and partnership-focused. In another systematic review that included 14 models and frameworks, Chudyk et al. 15 organised elements underlying PE in health service research into six categories: principles; foundational components; context; actions; levels and outcomes. For academic researchers and patient partners, these PE frameworks are useful to identify the essential components of their programme, but do not necessarily provide the 'recipe' linking, in operational terms, the principles, strategies, outcomes and impacts. 16 Logic models aim to provide a systematic way to visualize the interaction between the rationale of an intervention, planned activities, required resources and expected outcomes, 17 and offer an interesting means to advance our knowledge about this 'recipe'.
Logic models can support the reporting and standardization of PE in research 18  This study focused on the engagement of patient partners deployed in the PriCARE research programme, which is detailed elsewhere. 21,22 PriCARE implemented and evaluated a case management intervention for individuals that frequently use healthcare services in primary care clinics across five Canadian provinces: New Brunswick, Newfoundland, Labrador, Nova Scotia, Quebec, and Saskatchewan.
One to two patient partners were recruited in each participating province to work closely with the provincial research team. Each province circulated a posting to different networks where interested patient partners could apply and then meet with the local principal investigator and coordinator. In addition to taking an active part in the various steps of the research process, from the proposal stage to knowledge transfer activities, the patient partners participated in both the central decision-making committee as well as a 'community of practice' to foster their engagement in various stages of the research programme and ensure that their priorities were considered.

| Design
A descriptive qualitative design 23 was conducted with a participatory approach 24 involving patient partners and academic researchers of BISSON ET AL. | 1855 the PriCARE programme. As some of the academic researchers were also healthcare providers, the perspective of this category of participant was included.

| Sampling and participants
All the PriCARE team members were invited to participate in this study using purposeful sampling. 25 Twenty-two members agreed to participate including principal investigators (n = 5); co-investigators (n = 2); research coordinators and assistants (n = 8); one postdoctoral researcher; patient partners (n = 7) from four out of the five participating Canadian provinces. All participants discussed the aim of the current study during Steering Committee meetings and patient partners' Community of Practice meetings. amongst team members to support PE; team members' expectations of PE when they joined the research programme; potential activities, events or incidents related to PE and the contribution that team members would like to make in the future. Sociodemographic data (gender, age, location, first language, time of involvement in the PriCARE programme) were also collected so that the participants could be described. Since the 'context' component of the logic model was well described in the Canadian Institutes of Health Research SPOR UNITS document, 3 it was not explored during the interviews.

| Data collection
('SPOR' is the Canadian Institutes for Health Research Strategy for Patient-Oriented Research, which has formed funding partnerships with provinces and territories, philanthropic organisations, academic institutions and health charities. SPOR funds 10 SUPPORT Units across Canada to provide specialized services to researchers, patients, clinicians, policy makers and SPOR-funded entities to conduct patient-oriented research). Interviews with academic team members were digitally recorded and transcribed verbatim. To preserve the confidentiality of the patient partners, the two external assistants produced a deidentified summary of their interviews that was validated at a meeting in which the patient partners reviewed and approved the summary.

| Analysis
Data were analyzed using a deductive thematic analysis approach 26 where the themes corresponded to the categories of a classic logic model (i.e., resources, activities, outputs, outcomes, impact). All data were categorized under these themes using NVivo 12 software by research coordinators and assistants involved in the PriCARE programme with expertise in qualitative research. Data about resources, activities, output, outcomes and impact were pooled 26,27 and included in a first version of the Logic Model. Team meetings with a principal investigator, a co-principal investigator, a coordinator, a research assistant and a patient partner helped to refine the Logic Model. It was then presented to all participants during Steering Committee meetings and patient partners' Community of Practice meetings where comments were incorporated. A new version of the Logic Model was then shared with everyone by email for review and final validation following an iterative and participative process. 28 Table 1

| Activities
Both patient partners and academic researchers were involved in all research activities from project inception to knowledge translation.
Since PE was integrated into the governance structure of the research programme, ongoing activities related to PE support such as  The data collection methods used in the current study (participant observation, in-depth interviews and dyadic approach) have also helped fill the gap concerning the need for more systematic data collection 30 and the need to assess PE from the perspective of both patient partners and academic researchers. 11

| Limitations
A limitation of this study is that patient partners and academic research team members acting as study participants and contributing to their own data analysis could potentially cause bias due to social desirability and the risk of self-censorship. However, external research assistants hired to collect data mitigate this limitation. The participatory approach and the active role of participants in data analysis and interpretation provide some strengths because of their familiarity with the research programme. Furthermore, the team members are also involved in many other projects involving PE and bring external perspectives as well. Lastly, the Logic Model does not include challenges in the PriCARE programme regarding PE, but they have been documented elsewhere by Danish et al. 29 and Beland et al. 31

| CONCLUSION
The Patient Engagement in Health Implementation Research Logic Model will help academic researchers, healthcare providers, decision makers and patient partners involved or interested in PE in implementation research to plan and operationalize the resources and activities to achieve desired outcomes.