International Development Research Centre

Background Scaling primary care innovations to benefit broader populations is a key priority for decision-makers. While the science of effective scaling evolves, little is known about innovations that scale spontaneously , i.e., without deliberate guidance. Objectives To assess the spontaneous scaling process of STAT-C, a training workshop supporting management of sick leave related to common mental health disorders, and its perceived effects on primary care services and beneficiaries. Methods We conducted a mixed-methods descriptive single-case study using an Integrated Knowledge Translation (iKT) approach involving patient users. The case was defined as the spontaneous scaling of STAT-C, presented at the Quebec College of Family Physicians’ Innovation Symposium and assessed using a selection criteria checklist. Over one year, we observed the scaling process through monthly meetings with the innovation team and collected documents to retrace key steps. We conducted interviews with decision-makers, healthcare professionals, and end-users, along with a focus group with the innovation team. Data were analyzed thematically using documents, interviews, and meetings. The scaling process was examined using the Scaling Impact principles: justification, optimal scale, coordination, and dynamic evaluation. Results STAT-C met 71% of selection criteria. Fourteen participants were interviewed: innovation team (n = 2), healthcare professionals (n = 5), decision-makers (n = 4), and end-users (n = 3). Technical justifications included the need to standardize information across professionals (n = 10), while moral ones emphasized alignment with patient values (n = 8). Interviews revealed limited awareness of dynamic evaluation and a lack of indicators supporting further scaling. Ethical rationales reflected goal-oriented and duty-based reasoning. Preliminary data suggested improvements in healthcare professionals’ self-reported competence in managing CMHD-related sick leave, offering early indications of the innovation’s relevance. Conclusion This study highlights strategies, challenges, and outcomes of spontaneous scaling under real-world conditions, showing how pathways emerge, strategies evolve, and ethical dimensions shape decision-making.

BACKGROUND:Patient and public involvement (PPI) is recognized as essential for scaling interventions in health and social services, but there are few guidelines to support it. We sought consensus on strategies for involving patients and the public in scaling in an equitable and meaningful way. METHODS:We conducted a participatory consensus study inspired by Delphi techniques. We used as a starting point 23 PPI strategies for scaling (on the involvement continuum, from providing information to full co-production) as identified in a 2024 scoping review. First, we established a steering committee, intended to include patient or public representatives, to validate the relevance of the 23 strategies for inclusion in an online survey consensus process to confirm their applicability to PPI. Second, researchers, health professionals, policymakers, and patient or public representatives completed the online survey to assess the validated strategies against four evaluation criteria: equity, comprehensiveness, adaptability and significance. We used the DELPHISTAR checklist to report results and the GRIPP2 framework to report PPI in the study. FINDINGS:All 23 PPI strategies were found relevant by the steering committee and proceeded to the 2-round consensus process to evaluate 92 items (23 strategies x 4 criteria). By April, 2025, 14 participants had completed the first round and nine had also completed the second. Participants included patient and public representatives (n = 5), researchers (n = 6), health professionals (n = 3) and policymakers (n = 2) mostly based in Canada (n = 10). Of 23 PPI strategies assessed, 19 achieved consensus on at least one of the four criteria. Three strategies (Service users' needs assessment, Organizational advisory groups and Co-leadership in quality and safety improvement) achieved consensus across all criteria, while four strategies did not reach consensus on any. Co-leadership in quality and safety improvement (88.3%), Co-leadership in policymaking (87.3%) and Service users' needs assessment (87.3%) achieved the highest global scores. Consensus was reached on 44/92 items, most frequently for equity. These strategies were primarily situated in the organization of health and social care and the co-production level of the involvement continuum. CONCLUSIONS:The strategies prioritized by stakeholders were not necessarily the ones most frequently discussed in the literature. We recommend systematically involving patient and public representatives throughout scaling, including when choosing PPI strategies. PATIENT OR PUBLIC CONTRIBUTION:A patient instructor was involved in the steering committee, sharing decisions on study design, data collection instruments and dissemination of findings. Patient and public representatives also took part in the consensus process, and their feedback was considered equal to that of the other experts.

India's One Nation One Subscription (ONOS) initiative proposes a groundbreaking model to democratise access to scholarly knowledge by negotiating nationwide subscriptions to paywalled academic journals. This paper critically examines ONOS's potential to transform India's research ecosystem, addressing its objectives, implementation challenges, and socio-economic implications. Through a comparative analysis of global models - such as the EU's Plan S, Germany's Projekt Deal, Egypt's Egyptian Knowledge Bank, South Africa's national licensing consortium, and Peru's open-access repository; the study identifies key lessons for India. While ONOS promises to bridge the urban-rural knowledge divide and reduce institutional costs by 30-40%, its success hinges on overcoming publisher resistance, funding uncertainties, and infrastructural inequities. The paper advocates for a hybrid approach that integrates ONOS with open-access mandates and public-private partnerships to balance affordability and sustainability. By contextualising ONOS within India's ambitions under the National Education Policy 2020, this research underscores the initiative's role in fostering inclusive growth and positioning India as a global research leader.

Artificial intelligence depends on large-scale compute resources and their supporting infrastructure. However, AI governance debates treat compute primarily as a technical input rather than as an outcome of investment, ownership, and financial control. This paper examines AI infrastructure investment flows across Africa through a systematic analysis of 46 publicly announced projects totalling USD $12.7 billion between 2019 and 2025. Using a value chain framework, we analyze who invests in AI-relevant infrastructure and where investments concentrate. Our findings reveal a highly concentrated landscape dominated by global data center operators, hyperscale technology firms, and development finance institutions, clustering in South Africa, Kenya, Nigeria, and Egypt. We introduce asymmetrical interdependence to describe a structural condition in which capital and physical infrastructure account for 73% of total funding while control remains concentrated in the compute layer among a small number of global technology firms. We argue that compute governance must account for capital flows, ownership, and control, not only geographic access, because these dynamics shape AI compute equity. Infrastructure presence is necessary but insufficient for meaningful governance capacity.