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Background: Patient and public involvement (PPI), also called patient engagement, patient partnership, or consumer involvement, holds potential to change approaches and outcomes in research and healthcare. All research teams have complex power dynamics, including those with patient/public members. We present our perceptions and understandings of power arising from our own experiences on health research teams. We suggest ways for members of health research teams to move forward in efforts to minimize power discrepancies.
Main Body: As an international group of patients, caregivers, and research allies, we have experienced power dynamics within PPI collaborations and believe they must be challenged to achieve more equitable partnerships. We explore four themes relating to power in no order of importance: (1) The unstable and changing nature of power in PPI. Patient/public partners' abilities and capacities to engage equally depend on the working environment and on their economic, cultural, social and symbolic (including health) capitals; (2) Power between and amongst patients/public partners. Layers of power exist between and amongst patient/public partners and their networks, which may lead to a lack of diversity in partners and/or bullying and requires recognizing that not all patient/public partners bring the same experiences, skills or perspectives to research teams; (3) Power and tokenism. Tokenism occurs when patient/public perspectives in PPI are mostly ignored, results when power and resources are disproportionately concentrated, and can be perpetuated by funding and funding agency infrastructures; and, (4) PPI as a commodity or product. PPI may be seen or used as a means to extract experiences or validate one's work without truly involving patients/public contributors in the research design and process. PPI aligns with a broader trend of academic research methodologies grounded in standpoint epistemology (that is, how a person's social identity influences what they know). We include practical recommendations for researchers and for patient/public partners to share power more equitably on research teams.
Conclusion: In our experiences on health research teams, patient/public partners are often the most vulnerable and most disadvantaged members of the team who experience the largest power inequities. We hope our identified themes about power, the context related to power, and our reflections and recommendations on them inspire those holding power on research teams to share that power.
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http://dx.doi.org/10.1186/s40900-025-00745-9 | DOI Listing |
BMC Nurs
September 2025
Department of Nursing Administration, Faculty of Nursing, Alexandria University, Alexandria, Egypt.
Background: Organizational virtuousness and just culture, which both foster justice, honesty, and trust, have a major impact on positive work environments in the healthcare industry. Strengthening nurses' emotional engagement and vocational commitment requires these components. With an emphasis on the mediating function of just culture, this study attempts to investigate the relationship between organizational virtuousness and nurses' vocational commitment.
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September 2025
Interdisciplinary Orthopedics, Department of Orthopedics Surgery, Aalborg University Hospital, Aalborg, Denmark.
Functional recovery after total knee arthroplasty (TKA) varies widely among individuals, and traditional assessments often fail to detect subtle changes in real-world walking ability. Wearable sensors offer continuous and objective tracking of gait outside of clinical settings. In this prospective, longitudinal study, thirty-one patients undergoing unilateral TKA wore thigh-mounted accelerometers continuously from 2 weeks before surgery through 90 days postoperatively.
View Article and Find Full Text PDFBariatric surgery is an effective treatment for morbid obesity, but patient outcomes differ greatly because of a variety of phenotypes, comorbidities, and postoperative adherence. In bariatric care, artificial intelligence (AI) and machine learning (ML) are becoming revolutionary tools because traditional predictive models based on BMI and demographic variables are unable to account for these complexities. To put it simply, AI is a branch of computer science that enables machines to perform tasks that typically require human intelligence.
View Article and Find Full Text PDFEnviron Monit Assess
September 2025
School of Materials Engineering, Changzhou Vocational Institute of Industry Technology, Changzhou, 213000, People's Republic of China.
A multi-indicator framework was developed to resolve multi-source pollution in highly urbanized rivers, demonstrated in the Qinhuai River Basin, Nanjing, China. Water quality index (WQI) stratification was integrated with dissolved organic matter (DOM) fluorescence components, hydrochemical ions, and conventional parameters and analyzed using positive matrix factorization (PMF). Correlation analysis further elucidated source compositions and interactions.
View Article and Find Full Text PDFJ Math Biol
September 2025
School of Mathematical Sciences and Institute of Natural Sciences, MOE-LSC, CMA-Shanghai, Shanghai Jiao Tong University, Shanghai, China.
It has been noticed that when the waiting time distribution exhibits a transition from an intermediate time power-law decay to a long-time exponential decay in the continuous time random walk model, a transition from anomalous diffusion to normal diffusion can be observed at the population level. However, the mechanism behind the transition of waiting time distribution is rarely studied. In this paper, we provide one possible mechanism to explain the origin of such a transition.
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