Background
Methods
Overarching methodological approach
Knowledge synthesis
Study design
Eligibility criteria
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▪ Participants (P): Any type of stakeholder involved in creating or testing a strategy for PPI in the science or practice of scaling up. Stakeholder refers to “individual or group who is responsible for or affected by health- and healthcare-related decisions that can be informed by research evidence” [31, 32]. We will include the following nine types of stakeholders: (1) patients and the public (e.g., patients, their informal caregivers, their families, patient and consumer advocacy organizations, and local, national, or global citizens), (2) providers (e.g., individuals and organizations that provide care to patients and populations such as nurses, physicians, pharmacists, mental health counselors, and community-based workers), (3) purchasers (e.g., employers, governments, and other individuals or entities responsible for underwriting the cost of care), (4) payers (e.g., payers who pay or reimburse costs of health-related interventions such as insurers, individuals with deductibles, and others responsible for reimbursement for health-related\ interventions), (5) policy makers (e.g., policymaking entities such as governments and professional associations), (6) product makers (e.g., drug and device manufacturers), (7) investigators (e.g., researchers, postdoctoral fellows, and research coordinators), (8) the press (e.g., publishers and news media), and (9) trainees (e.g., university or college students) [31‐34]. This includes organizations that provide guidance for promoting PPI in the science and practice of scaling up in HSS.
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▪ Intervention (I): Any strategy proposed for involving patients and/or the public (alone) or multiple stakeholders (including patients and/or the public) in research or practical initiatives related to the steps of the scaling-up process in HSS. We will consider the four levels of PPI [13, 14]: (1) information (i.e., patient or the public receives information but has no role in contributing); (2) consultation (i.e., patients or the public provide their views, thoughts, feedback, opinions, or experiences but without a commitment to act on them; (3) collaboration (i.e., patients or the public are engaged to influence the scaling-up initiative, including commenting, advising, ranking, voting, prioritizing, and reaching consensus, but without direct control over decisions; and (4) coproduction (i.e., patients or the public are equal members of the research team and participate in all steps of the scaling-up initiative).
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▪ Comparator (C): We will consider for inclusion both studies with comparison group and studies without.
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▪ Outcomes (O): We will consider a wide range of metrics related to PPI. We will use the following taxonomy: process metrics and outcome metrics [35]. The process metrics form four domains: (1) direct process metrics (e.g., agenda setting and time allocation, roles in decision making, and control over the meeting minutes); (2) surrogate process metrics (e.g., formal power, organizational commitment to involvement, and equality of participation); (3) preconditions for involvement metrics (e.g., literacy of patient and public participants, resources provided, and presence or quality of training); and (4) aggregate process metrics (e.g., respect, transparency of the decision-making process, and level or ladder of participation). The outcome metrics form three domains: (1) internal outcomes as measured by impact on involved patient or public participants (e.g., knowledge, satisfaction, and trust), on services provided (e.g., efficiency and cost-effectiveness of services, number of complaints about services, and services quality and safety), and on organization or system (e.g., funding and resources availability, staff views on PPI, and presence of racism in system); (2) external outcomes as measured by influence on the broader public (e.g., awareness or knowledge of health issues, support of the organization or system, and PPI as part of social change outside the organization), and on population health (e.g., population health status and level of health inequalities); and (3) aggregate outcomes (e.g., overall cost-effectiveness of PPI).
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▪ Setting (S): Any context related to HSS. The World Health Organization defines health as “a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity” [36].
Literature search
Study selection
Data extraction
Risk of bias
Data analysis
Consultation with the steering committee
Delphi study
Study design
Participants
Data collection
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○ Round 1: We will collect participants’ sociodemographic information (e.g., country, sex, areas of expertise, primary occupational role). For each PPI strategy included in the preliminary list, we will ask participants to (1) rate how relevant the strategy is to engaging women, men, or other sex/gender categories; (2) rate how relevant the strategy is to each of the scaling-up steps; (3) determine how relevant the strategy is to various contexts (e.g., low-, middle-, or high-income countries; primary, secondary, or tertiary care); and (4) suggest any other PPI strategies required in scaling-up initiatives in HSS. Responses will be collated and discussed by our steering committee, and a list of strategies will be drawn up for scoring in the following round.
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○ Round 2: Participants will be asked to individually score each PPI strategy for its overall relevance to the largest range of sex/gender categories, scaling up steps and contexts. In addition, they will be invited to provide a brief justification or cite a relevant study to support their scores. Finally, there will be an opportunity to add any further PPI strategy that respondents feel should be considered. We will collate results and calculate the median score and percentage of agreement.
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○ Round 3: We will send a checklist to participants who completed the second round in which the median results from the third round are listed alongside the participant’s own score. Participants will be invited to reconsider the relevance of the PPI strategies and confirm or revise their score in the light of the participants’ opinions.
Data analysis
Build collaboration network
Discussion
Acknowledgements
Last name, First name | Country | Sex | Type of stakeholder | Email |
---|---|---|---|---|
Beaumont, Martin | Canada | Male | Policy maker |
martin.beaumont@chudequebec.ca
|
Beleno, Ron | Canada | Male | Patient instructor |
ron@rb33.com
|
Ben Charif, Ali | Comoros, Canada | Male | Trainee, investigator |
ali.bencharif@gmail.com
|
Bierman, Arlene | USA | Female | Policy maker |
arlene.bierman@ahrq.hhs.gov
|
Blais, Johanne | Canada | Female | Provider |
blaisj2@videotron.ca
|
Fancott, Carol | Canada | Female | Decision maker, investigator |
carol.fancott@cfhi-fcass.ca
|
Geiger, Friedemann | Germany | Male | Provider, investigator | f.geiger@uksh.de |
Gogovor, Amédé | Togo, Canada | Male | Trainee, investigator |
amede.gogovor@gmail.com
|
Guay-Bélanger, Sabrina | Canada | Female | Investigator |
sabrina.guay-belanger.ciussscn@ssss.gouv.qc.ca
|
Kastner, Kathy | Canada | Female | Patient instructor |
kathyk@bestendings.com
|
Légaré, France | Canada | Female | Provider, investigator |
france.legare@mfa.ulaval.ca
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McLean, Robert | Canada, South Africa | Male | Policy maker, investigator |
rmclean@idrc.ca
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Milat, Andrew J | Australia | Male | Policy maker, investigator |
andrew.milat@health.nsw.gov.au
|
Paquette, Jean-Sébastien | Canada | Male | Provider, investigator |
jspaquette.lab@gmail.com
|
Plourde, Karine V. | Canada | Female | Investigator |
karine.plourde2.ciussscn@ssss.gouv.qc.ca
|
Rivest, Francois | Canada | Male | Investigator |
francois.rivest@canada.ca
|
Straus, Sharon | Canada | Female | Provider, investigator |
sharon.straus@utoronto.ca
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Thibodeau, Guy | Canada | Male | Decision maker |
guy.thibodeau.ciussscn@ssss.gouv.qc.ca
|
Wolfenden, Luke | Australia | Male | Investigator |
luke.wolfenden@hnehealth.nsw.gov.au
|
Zomahoun, Hervé Tchala Vignon | Benin, Canada | Male | Investigator | herve.zomahoun.ciussscn@ssss.gouv.qc.ca |