Purpose: To explore the effect of nursing based on the hopeless self-esteem theory plus multi-dimensional intensive nursing on the self-esteem level and prognosis of elderly patients with acute cerebral infarction (ACI) complicated with depression.

Methods: Eighty patients with ACI complicated with depression who were treated in our hospital from September 2018 to September 2020 were selected and randomized into the observation group and the control group (n = 40 each). The observation group received the model of hopeless self-esteem theory combined with multi-dimensional intensive nursing, while the control group received conventional nursing. The clinical efficacy, depression degree, self-esteem level, living ability, quality of life, and attribution mode were compared.

Results: The overall effective rate was reported at a notably higher rate in the observation group (90.00%) compared to the control group (65.00%) (P < 0.05); After intervention, the observation group had a markedly lower Geriatric Depression Scale (GDS) score than the control group (P < 0.05); After intervention, the observation group showed appreciably higher Rosenberg Self Esteem Scale (RSES) score and Barthel index compared to the control group (P < 0.05); After intervention, the observation group had a remarkably higher level of the quality of life in all dimensions than the control group (P < 0.05); After intervention, there were more positive events in the observation group as compared to the control group (P < 0.05), whereas there were more negative events in the control group as compared to the observation group (P < 0.05).

Conclusion: The hopeless self-esteem theory combined with multi-dimensional intensive nursing can apparently increase the self-esteem level of patients, establish a positive attribution mode, beef up their self-confidence, reduce the degree of depression, upgrade their postoperative living ability and quality of life, and improve prognosis and clinical efficacy.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8340256PMC

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