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Background  The most important and contested element of nursing identity may be the patient-centredness of nursing, though this concept is not well-treated in the nursing identity literature. More conceptually-based mapping of nursing identity constructs are needed to help nurses shape their identity. The field of computational text analytics offers new opportunities to scrutinise how growing disciplines such as health services research construct nursing identity. This paper maps the conceptual content of scholarly health services research in PubMed as it relates to the patient-centeredness of nursing.    Methods  Computational text analytics software was used to analyse all health services abstracts in the database PubMed since 1986. Abstracts were treated as indicative of the content of health services research. The database PubMed was searched for all research papers using the term “service” or “services” in the abstract or keywords for the period 01/01/1986 to 30/06/2013. A total of 234,926 abstracts were obtained. Leximancer software was used in 1) mapping of 4,144,458 instances of 107 concepts; 2) analysis of 106 paired concept co-occurrences for the nursing concept; and 3) sentiment analysis of the nursing concept versus patient, family and community concepts, and clinical concepts.    Results  Nursing is constructed within quality assurance or service implementation or workforce development concepts. It is relatively disconnected from patient, family or community care concepts.    Conclusions  For those who agree that patient-centredness should be a part of nursing identity in practice, this study suggests that there is a need for development of health services research into both the nature of the caring construct in nursing identity and its expression in practice. More fundamentally, the study raises questions about whether health services research cultures even value the politically popular idea of nurses as patient-centred caregivers and whether they should.

Nursing identity and patient-centredness in scholarly health services research: a computational text analysis of PubMed abstracts 1986–2013