天津护理 ›› 2024, Vol. 32 ›› Issue (6): 684-688.DOI: 10.3969/j.issn.1006-9143.2024.06.012

• 调查与分析 • 上一篇    下一篇

首发脑卒中患者行为决策水平现状及影响因素分析

梁珍珍 1 邹小燕 1 刘欢欢 2   

  1. (1.吉安市第一人民医院,江西 吉安 343000;2.吉安市中心人民医院)
  • 出版日期:2024-12-28 发布日期:2024-12-16

Analysis of current situation and influencing factors of behavioral decision-making level among patients with first-espisode stroke

LIANG Zhenzhen1 , ZOU Xiaoyan1 , LIU Huanhuan2   

  1. (1. Ji′an First People′s Hospital, Ji′an Jiangxi 343000;2. Ji′an Central People′s Hospital)
  • Online:2024-12-28 Published:2024-12-16

摘要: 目的:调查首发脑卒中患者行为决策水平现状,并分析其影响因素。方法:采用便利抽样法选取 2022 年 5 月至 2023 年 5 月吉安市某二级甲等医院收治的首发脑卒中患者为研究对象。采用一般资料调查表、 行为决策量表(Behavioral Decision-making Scale,BDMS)、心理弹性量表(Connor-Davidson Resilience Scale,CD-RISC)、家庭亲密度与适应性量表(Family Adaptability and Cohesion Evaluation Scale,FACESⅡ-CV)对患者进行调查。采用 Pearson 相关分析 BDMS 评分与 CD-RISC、FACESⅡ-CV 评分的相关性。采用多变量线性回归分析行为决策水平的影响因素。结果:194 例患者 BDMS 评分为(94.83±10.58) 分,CD-RISC 评分为(59.10±10.81)分,FACESⅡ-CV 评分为(115.03±14.89)分。单因素分析显示,BDMS 评分在性别、文化程度、婚姻状况、卒中家族史分层比较中差异有统计学意义(P<0.05)。Pearson 相关分析显示,BDMS 各维度评分及总分均与 CD-RISC、FACESⅡ-CV 评分呈正相关(P<0.05)。多变量线性回归分析显示,性别、文化程度、卒中家族史、CD-RISC 评分、FACESⅡ-CV 评分是影响首发脑卒中患者行为决策水平的因素(P<0.05)。结论:首发脑卒中患者行为决策水平有待提高,性别、文化程度、卒中家族史、心理弹性、家庭功能是其影响因素,临床可针对性制定干预方案促进行为决策水平提高。

关键词: 脑卒中, 行为决策, 心理弹性, 家庭功能

Abstract: Objective: To investigate the current situation of behavioral decision-making level , and analyze it′s influencing factors in patients with first-espisode stroke. Methods: Participants were recruited from patients with first-episode stroke admitted to Ji ′an First People′s Hospital from May 2022 to May 2023 by convenience sampling. The General Information Questionnaire, Behavioral Decision-making Scale (BDMS), Connor-Davidson Resilience Scale (CD-RISC) and Family Adaptability and Cohesion Evaluation Scale(FACESⅡ-CV) were used to evaluate the particiapants. Pearson correlation analysis was used to analyze the correlation between the scores of BDMS, CD-RISC, and FACESⅡ-CV. Multivariate linear regression was used to analyze the influencing factors of behavioral decision -making level. Results: The mean scores of BDMS, CD-RISC, and FACESⅡ-CV were(94.83±10.58) points, (59.10±10.81) points, and (115.03±14.89) points in 194 patients, respectively. Univariate analysis showed that the scores of BDMS were significantly different in the stratified comparison of gender, education level, marital status and family history of stroke(all P<0.05). Pearson correlation analysis showed that the scores of each dimension and total score of BDMS were positively correlated with the scores of CD-RISC and FACESⅡ-CV (all P<0.05). Multivariate linear regression analysis showed that female, education level, family history of stroke, CD-RISC score, FACESⅡ-CV score affected the behavioral decision-making level of patients with first-episode stroke (all P<0.05). Conclusion: The behavioral decision-making level of patients with first-episode stroke needs to be improved. Gender, education level, family history of stroke, psychological resilience and family function were its influencing factors. Targeted intervention programs in clinical should be formulated to promote the level of behavioral decision-making.

Key words: Stroke, Behavioral decision-making, Psychological resilience, Family function

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