{'fraction_non_alphanumeric': 0.013679890560875513, 'fraction_numerical': 0.0, 'mean_word_length': 5.834890965732087, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Review: A realist logic model of the links between nurse staffing and the outcomes of nursing

Some of the best known research in nursing of the past decade has examined connections between nurse staffing levels and a variety of endpoints, especially negative outcomes for patients and nurses in hospitals. The staffing–outcomes literature has provided ongoing reminders of the importance of considering nurses’ contributions to care in the management of health services and of the urgency of stabilising the supply of nurses across countries. However, developing evidence-informed health services management and health policy from the findings has been a greater challenge than garnering attention for the literature’s more striking results. Although studies in this literature are generally reassuring in confirming some of our instincts regarding nurses’ impacts, they are remarkably inconsistent in their findings, no doubt because the staffing–outcomes association is clearly conditioned by many factors and takes variable forms across different indicators of staffing and quality and clinical populations. This complexity is a separate issue from the fundamental challenges in measurement, research design and analysis that always provide competing explanations for findings in this field, both positive and negative. The staffing–outcomes literature has developed without much of a theoretical base for the most part, with few researchers attempting to test or even articulate (except in very broad and speculative terms) mechanisms explaining the associations identified or account for the many situations where anticipated linkages have failed to appear. Taking more thorough stock of this literature and clearly laying out likely mechanisms for the operation of the association are both vital for making informed policy decisions from it. The logic model approach used here guides designers and evaluators of services in articulating assumptions regarding linkages between structures, processes and outcomes. This is a particularly important undertaking in today’s environment, since changing clinical management or service organisation (including staffing) without reflecting on and