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Background: Spontaneous ventilation, essential for human life, is addressed by the nursing diagnosis “Ineffective Spontaneous Ventilation” which requires strong scientific support. Aim: This revision study aimed to elevate this nursing diagnosis to a higher level of evidence by clarifying its definition, clinical indicators, and differentiation from other diagnoses. The diagnosis is crucial for identifying patients with compromised breathing who may require respiratory support. Methods: Researchers searched the PubMed medical literature database for studies (2006-2021) on the "Ineffective Spontaneous Ventilation" diagnosis. Results: The search identified 45 studies, but after applying pre-defined criteria, only 10 articles were included in the final analysis. These articles mainly focused on the accuracy of defining characteristics for the diagnosis. Despite limitations of individual defining characteristics, Impaired Spontaneous Ventilation remains a valuable nursing diagnosis for patients with respiratory issues. Utilizing clusters of these characteristics and considering the specific context can significantly enhance the accuracy of ISV diagnosis. Conclusion: The findings unequivocally corroborate the definition of Impaired Spontaneous Ventilation, with eight out of ten articles providing validation. Moreover, the analysis proposes additional defining characteristics, namely dyspnea and cyanosis, to further refine the diagnosis. The clinical applicability of Impaired Spontaneous Ventilation extends to a wide range of patient populations and conditions. It serves as a critical marker for premature infants grappling with respiratory and cardiac challenges, trauma victims battling life-threatening injuries, and patients relying on mechanical ventilation in intensive care settings.

Introduction: Nursing care, despite constituting a significant portion of healthcare costs, often remains overlooked in healthcare data systems, which primarily focus on medical data. Incorporating standardized nursing language (SNL) into electronic health records has shown promise in predicting outcomes across various clinical settings. However, nurses' unfamiliarity with standardized terminologies poses a significant barrier to their implementation. NANDA-International (NANDA-I) nursing diagnoses (NDs) offer a standardized framework, yet their application in mental health (MH) settings remains underexplored. Objectives: The MINDSET study aims to establish a consensus among mental health nurses to develop a subset of nursing diagnoses tailored for MH and addiction EHRs. Methods: A multi-phase e-Delphi study will involve mental health nurses experienced in NANDA-I NDs from various countries. Through successive rounds of surveys, experts will assess the relevance of NDs in MH settings, with consensus determining the final subset. Results: The expected outcome is a concise subset of nursing diagnoses agreed upon by experts, facilitating their integration into clinical practice. This subset may offer nurses a manageable set of diagnoses closely aligned with MH contexts, enhancing their applicability and utility in daily care. Subsequent research could explore the prevalence of these diagnoses in MH settings and their associations with patient outcomes. Impact: The development of a tailored subset of nursing diagnoses holds potential to enhance nursing practice in MH settings, enabling more effective assessment and intervention strategies, ultimately improving patient outcomes.