Europe PMC
Do data resources managed by EMBL-EBI and our collaborators make a difference to your work?
If so, please take 10 minutes to fill in our survey, and help us make the case for why sustaining open data resources is critical for life sciences research.

This website requires cookies, and the limited processing of your personal data in order to function. By using the site you are agreeing to this as outlined in our privacy notice and cookie policy.

Abstract 


Objective

This study aims to investigate the application of protective restraint nursing interventions in intensive care unit (ICU) patients and their impact on the incidence of unplanned extubation and skin damage.

Methods

A total of 90 ICU patients admitted to Hai'an People's Hospital between January 2019 and December 2020 were randomly assigned to either the experimental group or the control group in a 1:1 ratio. The control group received conventional nursing care, while the experimental group received protective restraint nursing interventions. The Hospital Anxiety and Depression (HAD) scale, a clinical tool used to assess patients' levels of anxiety and depression, was employed to evaluate patients' emotional states before and after the intervention. A Patient Clinical Satisfaction Survey Questionnaire developed by our department was used to assess patient satisfaction after nursing. Compliance and the incidence of adverse reactions were compared between the two groups.

Results

The experimental group exhibited significantly lower HADS scores, higher nursing satisfaction, and a lower incidence of unplanned extubation, skin damage, and adverse reactions compared to the control group (all P < .05).

Conclusions

Protective restraint care demonstrates substantial benefits for ICU patients by reducing the incidence of unplanned extubation, preventing skin damage during treatment, improving compliance, and facilitating recovery. These findings support the clinical application and promotion of protective restraint nursing interventions.

Similar Articles 


To arrive at the top five similar articles we use a word-weighted algorithm to compare words from the Title and Abstract of each citation.