Information-motivation-behavioral guided nursing for stroke patients with pulmonary dysfunction: A randomized controlled trial

医学 随机对照试验 冲程(发动机) 物理疗法 护理部 重症监护医学 物理医学与康复 内科学 机械工程 工程类
作者
Peng Xia,Hui-Qin Ni,Yongmei Liu,Jinling Zhu,Yuting Bai
出处
期刊:World Journal of Clinical Cases [Baishideng Publishing Group]
卷期号:12 (24): 5549-5557 被引量:1
标识
DOI:10.12998/wjcc.v12.i24.5549
摘要

BACKGROUND Patients with stroke frequently experience pulmonary dysfunction. AIM To explore the effects of information-motivation-behavioral (IMB) skills model-based nursing care on pulmonary function, blood gas indices, complication rates, and quality of life (QoL) in stroke patients with pulmonary dysfunction. METHODS We conducted a controlled study involving 120 stroke patients with pulmonary dysfunction. The control group received routine care, whereas the intervention group received IMB-model-based nursing care. Various parameters including pulmonary function, blood gas indices, complication rates, and QoL were assessed before and after the intervention. RESULTS Baseline data of the control and intervention groups were comparable. Post-intervention, the IMB model-based care group showed significant improvements in pulmonary function indicators, forced expiratory volume in 1 sec, forced vital capacity, and peak expiratory flow compared with the control group. Blood gas indices, such as arterial oxygen pressure and arterial oxygen saturation, increased significantly, and arterial carbon dioxide partial. pressure decreased significantly in the IMB model-based care group compared with the control group. The intervention group also had a lower complication rate (6.67% vs 23.33%) and higher QoL scores across all domains than the control group. CONCLUSION IMB model-based nursing care significantly enhanced pulmonary function, improved blood gas indices, reduced complication rates, and improved the QoL of stroke patients with pulmonary dysfunction. Further research is needed to validate these results and to assess the long-term efficacy and broader applicability of the model.
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