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Introduction: During the last decades, reforms in the organisation of mental health care (MHC) have been implemented in many countries. However, reforms are often partially implemented because of the resistance of stakeholders, especially in bottom-up and fragmented societies. So far, coalitions of stakeholders in the organisation of MHC has never been described. Objectives: The objective was to identify coalitions of stakeholders in relation to dimensions of the organisation of MHC. Methods: Using a national online survey in Belgium, data were collected on 469 stakeholders (policymakers, clinicians, managers, professional associations, user representatives). Seven dimensions of the MHC organisation were proposed to stakeholders: target group, geographical organisation of care, type of service provided, type of coordination, formalization of practice, provider payment mechanisms, and resource-pooling level. Classification was performed on stakeholders’ organisational choices with a non-metric cluster analysis. Results: Organisational choices of stakeholders in five clusters accounted for 50% of the variance. Coalitions have emerged around the following dimensions: geographical organisation of care, type of service provided, resource-pooling level and formalization of practices. Clusters composed of clinicians and professional associations favoured the autonomy of individual, specialised services while those composed of policymakers favoured generic services, the formalization of practice and integration at the network level in terms of provision, coordination, and funding of services. Conclusions: Coalitions that are composed of stakeholders with different backgrounds differ on the organisational dimensions that underlie issues of autonomy and identity of services. The definition of MHC policies and interventions should consider the impact of stakeholder coalitions.
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Smith, P., Nicaise, P., Thunus, S., Neyens, I., Walker, C., & Lorant, V. (2019). Stakeholder coalitions on the organisation of mental health care: a cluster analysis. ENMESH, Lisbon, Portugal. https://hdl.handle.net/2078.5/122920