Community nurses’ experiences of receiving targeted support in a regional nursing consortium: a qualitative study - Cheng, Wen lin; Wang, Shuo; Zhang, DongMei; Li, Rui; Bian, Kaixin; Zhang, Jia; Zhang, Yifan; Tu, Jin; Yan, Meijun; Zhou, Jun; Song, Shuang Yuan (Frontiers in Public Health, 2025)
BackgroundRegional nursing consortia aim to optimize nursing resource allocation and enhance the quality of primary care. However, community nurses often encounter challenges that diminish their motivation and professional satisfaction, hindering effective implementation. Notably, their lived experiences remain under-explored.AimTo explore community nurses’ experiences of receiving support within regional nursing consortia, to improve the model’s effectiveness and sustainability.MethodsBetween November and December 2024, 162 community nurses affiliated with a regional nursing consortium were considered eligible. From this pool, 10 nurses were purposively selected for in-depth interviews until data saturation was reached. The interviews were analyzed using Colaizzi’s phenomenological method.ResultsThree major themes and ten subthemes emerged: (1) Nurses acknowledged the mentoring model’s positive effects, including expanded practice scope, professional development, and increased confidence in managing complex cases. (2) Enthusiasm for active participation was low due to heavy workloads, stress, and dissatisfaction with performance-based pay. (3) Nurses held high expectations for the model, including broader project coverage, varied support formats, insurance-funded services, clearer role boundaries, and expanded patient engagement.ConclusionWhile community nurses value the support provided through the regional nursing consortium, their engagement remains limited. To enhance participation, initiatives should reduce workload, diversify support approaches, and expand project scope. Strengthening professional development and improving incentive mechanisms are essential. Additionally, outreach efforts targeting patients and families should be increased to maximize the model’s impact.