Content validation of the NANDA-I nursing diagnosis risk for perioperative hypothermia (00254)

The objectives of this study were to refine and validate the NANDA-I nursing diagnosis risk for perioperative hypothermia (RPH) (00254).

A quantitative, descriptive study was carried out according to the adapted diagnostic content validation model by Fehring. Data from a previously conducted literature study were triangulated with expert validation data to examine the nursing diagnosis RPH as well as potentially suggested new factors resulted from the literature review. In addition, the Wisdom of Crowds model was also considered. A nonprobability sampling technique, including purposive and snowball sampling methods, was used to recruit a panel of nurse experts. An anonymous and standardized questionnaire was developed in three languages for data collection. For validation, descriptive statistics, weighted ratios, and a one-sample T-test were used.

Ninety-two nurse experts from seven countries and three continents participated in this study. Fifty-eight nurse experts (63%) were female, and 33 (36%) were male, with a mean age of 42.26 years and 19.22 years of working experience. The diagnosis label, definition, 4 out of 5 risk factors (RF), 6 out of 14 at-risk populations (ARPs), and 5 out of 9 associated conditions (ACs) were classified as major. One RF, eight ARP, and four ACs were considered minor. In addition, the experts validated 1 RF, 5 ARP, and 12 ACs from a previous literature study at least minor.

The nursing diagnosis RPH (00254) could be confirmed by specialized experts. No RF, ARP, or AC of the current nursing diagnosis needed to be rejected, and the added diagnostic indicators increased the robustness of the diagnosis.

A precise concept of the nursing diagnosis RPH improves nurses' clinical reasoning and strengthens an individualized, evidence-based care plan.