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Consensus-Dominant Futures in Nursing: A Co-Citation and Co-Word Science-Mapping Analysis of Future-Framed
Alex S Borromeo1, Estelle Rose M Lerma1, David S Bote1
1College of Nursing, Bulacan State University, Malolos, Bulacan, Philippines.
Background:
Futures thinking considers multiple possible, preferred, and undesirable futures; strategic foresight applies this orientation to planning. Nursing leaders face workforce instability, digital health adoption, and recurrent disruptions that demand anticipatory action.
Purpose:
To map how future-framed approaches appear in nursing-indexed journal literature (1990-2025) and identify leadership, education, and policy gaps.
Methods:
English-language Web of Science Core Collection journal articles and reviews (searched 08 Nov 2025) were screened for a substantive future-framed purpose in nursing. Co-citation analysis mapped frequently co-cited references, and co-word analysis mapped high-frequency author-keyword patterns.
Findings:
The Web of Science search generated n = 4478 raw imported records. After sequential metadata-based screening, n = 3137 records were retained as the final verified eligible corpus. Co-citation and co-word analyses identified four citation-based clusters and four author-keyword themes within the screened corpus. Within the retrieved corpus, co-citation patterns were consensus-dominant, anchored in Delphi guidance, consensus measurement, and reporting standards, alongside methodological and leadership/education reform texts. Co-word themes clustered around clinical risk, outcomes, long-term care, and measurement; nursing workforce, quality, leadership, patient safety, and work environment; Delphi/consensus-based nursing management and guideline development; and nursing education, implementation, attitudes, and learning/program development.
Conclusions:
Within the indexed journal record, future-framed nursing scholarship is growing but is most often operationalized through consensus-oriented pathways; explicit foresight tools such as scanning, scenarios, backcasting, and futures literacy remain comparatively sparse in titles, abstracts, and keywords.
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