Article(id=1322931504959062542, tenantId=1146029695717560320, journalId=1220038315760373764, issueId=1322931411006665649, articleNumber=null, orderNo=null, doi=10.12102/j.issn.1009-6493.2026.13.012, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1751558400000, receivedDateStr=2025-07-04, revisedDate=1778947200000, revisedDateStr=2026-05-17, acceptedDate=null, acceptedDateStr=null, onlineDate=1793341049661, onlineDateStr=2026-10-30, pubDate=1783612800000, pubDateStr=2026-07-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793341049661, onlineIssueDateStr=2026-10-30, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793341049661, creator=13701087609, updateTime=1793341049661, updator=13701087609, issue=Issue{id=1322931411006665649, tenantId=1146029695717560320, journalId=1220038315760373764, year='2026', volume='40', issue='13', pageStart='2193', pageEnd='2384', issueExtLink='null', onlineDate='null', pubDate='1783612800000', pubDateStr='2026-07-10', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793341027261, creator='13701087609', updateTime=1793343114456, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322940165425082661, tenantId=1146029695717560320, journalId=1220038315760373764, issueId=1322931411006665649, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322940165425082662, tenantId=1146029695717560320, journalId=1220038315760373764, issueId=1322931411006665649, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2278, endPage=2286, ext={EN=ArticleExt(id=1322931505781146127, articleId=1322931504959062542, tenantId=1146029695717560320, journalId=1220038315760373764, language=EN, title=Longitudinal trajectories and influencing factors of activation in chronic heart failure patients based on latent class growth model, columnId=1220689484526572183, journalTitle=Chinese Nursing Research, columnName=Original Articles, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the potential categories of longitudinal trajectories of patient activation in individuals with chronic heart failure and to analyze their influencing factors.

Methods

Patients with chronic heart failure admitted to our hospital from January 2023 to August 2024 were selected as the study subjects.Before discharge(T1),surveys were conducted using a general information questionnaire,the Chinese version of the Patient Activation Measure(PAM13),the FRAIL scale(to screen for frailty risk),and the Social Support Rating Scale(SSRS).Patient activation was reassessed using the Chinese version of the PAM 13 at 1 month(T2),3 months(T3),and 6 months(T4) after discharge.Spearman correlation analysis was used to examine the correlations of patient activation scores across the four time points.Latent class growth modeling was employed to identify potential categories of patient activation trajectories,and multinomial logistic regression was performed to analyze the influencing factors of these trajectory categories.

Results

A total of 216 patients completed the study.The patient activation scores at T1,T2,T3,and T4 were 54.6 (40.1,66.0),56.4(43.4,73.1),51.4(41.7,63.2),and 51.4(42.1,66.0),respectively.Spearman correlation analysis showed positive correlations among patient activation scores at all four time points(all P<0.01).The latent class growth model identified three distinct trajectory categories:high activation-stable group(27.3%),moderate activation-declining group(32.9%),and low activation-gradually increasing group(39.8%).Multinomial Logistic regression revealed that education level,NYHA functional class,comorbidities,frailty status,and social support were significant influencing factors for the trajectory categories of patient activation in chronic heart failure patients(all P<0.05).

Conclusions

There is significant inter-individual heterogeneity in the trajectories of patient activation among chronic heart failure patients,which are influenced by education level,NYHA functional class,comorbidities,frailty status,and social support.Healthcare providers should implement targeted interventions based on the characteristics of patients' activation trajectories to comprehensively improve their activation levels.

, authors=Min CHEN, Xian YUAN, Juan GENG, authorsList=Min CHEN, Xian YUAN, Juan GENG, authorCompany=null, correspAuthors=Juan GENG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322931506389320210, articleId=1322931504959062542, tenantId=1146029695717560320, journalId=1220038315760373764, language=CN, title=基于潜类别增长模型的慢性心力衰竭病人积极度纵向轨迹及影响因素, columnId=1220689484681761433, journalTitle=护理研究, columnName=科研论著, runingTitle=null, highlight=null, articleAbstract=
目的

探究慢性心力衰竭病人积极度纵向轨迹的潜在类别,并分析其影响因素。

方法

选取2023年1月—2024年8月我院收治的慢性心力衰竭病人为研究对象。在病人出院前(T1)采用一般资料调查表及中文版病人积极度量表(PAM 13)、衰弱风险筛查工具(FRAIL)、社会支持评定量表(SSRS)进行调查;在出院后1个月(T2)、3个月(T3)、6个月(T4)采用中文版病人积极度量表评估病人的积极度。采用Spearman相关性分析4个时间点病人积极度的相关性;通过潜类别增长模型识别病人积极度轨迹的潜在类别,并采用多分类Logistic回归分析病人积极度轨迹潜在类别的影响因素。

结果

216例病人完成研究。T1、T2、T3、T4时病人积极度评分依次为54.6(40.1,66.0)分、56.4(43.4,73.1)分、51.4(41.7,63.2)分、51.4(42.1,66.0)分。Spearman相关性分析显示,4个时间点的病人积极度评分均呈正相关(均P<0.01)。潜类别增长模型识别的病人积极度轨迹被划分为3个类别:高积极度-维持组(27.3%)、中积极度-下降组(32.9%)、低积极度-缓升组(39.8%)。多分类Logistic回归分析结果显示,文化程度、心功能分级、合并症、衰弱情况、社会支持是慢性心力衰竭病人积极度轨迹潜在类别的影响因素(均P<0.05)。

结论

慢性心力衰竭病人积极度轨迹存在群体异质性,其受到文化程度、心功能分级、合并症、衰弱情况、社会支持的影响。医护人员应根据病人积极度轨迹特点给予针对性干预,提高病人积极度水平。

, authors=陈敏, 袁娴, 耿娟*, *, authorsList=陈敏, 袁娴, 耿娟, authorCompany=null, correspAuthors=耿娟, authorNote=

陈敏,护师,本科

, correspAuthorsNote=
耿娟,E-mail:
GENG Juan, E-mail:
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rfOrder=41, authorNames=徐筱璐, 徐翠荣, 郝天天, journalName=现代临床护理, refType=null, unstructuredReference=徐筱璐,徐翠荣,郝天天.健康生态学视角下慢性心力衰竭健康管理综合评价指标体系的构建[J].现代临床护理,2023,22(9):57-65., articleTitle=健康生态学视角下慢性心力衰竭健康管理综合评价指标体系的构建, refAbstract=null), Reference(id=1322931512974377575, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931504959062542, doi=null, pmid=null, pmcid=null, year=2021, volume=21, issue=11, pageStart=36, pageEnd=40, url=null, language=null, rfNumber=43, rfOrder=42, authorNames=郑旻嘉, 汤静, 龚素蓉, journalName=上海护理, refType=null, unstructuredReference=郑旻嘉,汤静,龚素蓉,等.冠心病患者积极度现状及影响因素调查[J].上海护理,2021,21(11):36-40., articleTitle=冠心病患者积极度现状及影响因素调查, refAbstract=null), Reference(id=1322931513054069352, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931504959062542, doi=null, pmid=null, pmcid=null, year=2018, volume=18, issue=1, pageStart=7, pageEnd=null, url=null, language=null, rfNumber=44, rfOrder=43, authorNames=Overbeek A, Rietjens J A C, Jabbarian L J, journalName=BMC Geriatrics, refType=null, unstructuredReference=Overbeek A,Rietjens J A C,Jabbarian L J,et al.Low patient activation levels in frail older adults:a cross-sectional study[J].BMC Geriatrics,2018,18(1):7., articleTitle=Low patient activation levels in frail older adults:a cross-sectional study, refAbstract=null), Reference(id=1322931513158926953, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931504959062542, doi=null, pmid=null, pmcid=null, year=2024, volume=38, issue=2, pageStart=369, pageEnd=373, url=null, language=null, rfNumber=45, rfOrder=44, authorNames=胡亦伟, 熊晓云, 孙兴兰, journalName=护理研究, refType=null, unstructuredReference=胡亦伟,熊晓云,孙兴兰,等.抗阻训练对老年慢性心力衰竭合并衰弱病人的影响[J].护理研究,2024,38(2):369-373., articleTitle=抗阻训练对老年慢性心力衰竭合并衰弱病人的影响, refAbstract=null), Reference(id=1322931513272173162, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931504959062542, doi=null, pmid=null, pmcid=null, year=2024, volume=23, issue=1, pageStart=524, pageEnd=null, url=null, language=null, rfNumber=46, rfOrder=45, authorNames=Skolasky R L, Nolan S, Pierre R, journalName=BMC Nursing, refType=null, unstructuredReference=Skolasky R L,Nolan S,Pierre R,et al.Nurse-led web-based self-management program to improve patient activation and health outcomes in patients with chronic low back pain:an acceptability and feasibility pilot study[J].BMC Nursing,2024,23(1):524., articleTitle=Nurse-led web-based self-management program to improve patient activation and health outcomes in patients with chronic low back pain:an acceptability and feasibility pilot study, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1322931506670338579, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931504959062542, xref=1, ext=[AuthorCompanyExt(id=1322931506678727188, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931504959062542, companyId=1322931506670338579, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1The Affiliated Huai'an Hospital of Xuzhou Medical University/Huai'an Second People's Hospital, Jiangsu 223000 China), AuthorCompanyExt(id=1322931506687115797, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931504959062542, companyId=1322931506670338579, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1徐州医科大学附属淮安医院/淮安市第二人民医院,江苏 223000)])], figs=[ArticleFig(id=1322931508431946289, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931504959062542, language=EN, label=Figure 1, caption=Trajectory plot of the latent class growth model for patient activation in chronic heart failure patients, figureFileSmall=xOa+4RVuQ7H+YVADr5Uh0A==, figureFileBig=x8IGWkWxGmyHlJP5z8uMJA==, tableContent=null), ArticleFig(id=1322931508503249458, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931504959062542, language=CN, label=图1, caption=慢性心力衰竭病人积极度的潜类别增长模型轨迹图, figureFileSmall=xOa+4RVuQ7H+YVADr5Uh0A==, figureFileBig=x8IGWkWxGmyHlJP5z8uMJA==, tableContent=null), ArticleFig(id=1322931508725547571, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931504959062542, language=EN, label=Table 1, caption=

Patient activation scores at four time points and their correlations in patients with chronic heart failure

, figureFileSmall=null, figureFileBig=null, tableContent=
时间点病人积极度(分)相关性(r值)
T1T2T3T4
T154.6(40.1,66.0)①1.000
T256.4(43.4,73.1)0.8871.000
T351.4(41.7,63.2)①0.8660.8161.000
T451.4(42.1,66.0)①0.8290.7620.7741.000
), ArticleFig(id=1322931508796850740, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931504959062542, language=CN, label=表1, caption=

慢性心力衰竭病人4个时间点积极度评分及相关性

, figureFileSmall=null, figureFileBig=null, tableContent=
时间点病人积极度(分)相关性(r值)
T1T2T3T4
T154.6(40.1,66.0)①1.000
T256.4(43.4,73.1)0.8871.000
T351.4(41.7,63.2)①0.8660.8161.000
T451.4(42.1,66.0)①0.8290.7620.7741.000
), ArticleFig(id=1322931508884931125, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931504959062542, language=EN, label=Table 2, caption=

Fit indices for latent class growth model of patient activation trajectories in chronic heart failure patients

, figureFileSmall=null, figureFileBig=null, tableContent=
类别LLAICBICaBICEntropyP值类别概率
LMRTBLRT
1-3 519.4227 050.8447 071.0967 052.083
2-3 235.6716 489.3426 519.7206 491.2000.930<0.001<0.0010.690/0.310
3-3 089.6866 203.3736 243.8766 205.8500.957<0.001<0.0010.273/0.329/0.398
4-3 077.4366 184.8716 235.5016 187.9680.9050.067<0.0010.245/0.116/0.366/0.273
5-3 069.8766 175.7526 236.5076 179.4680.9210.055<0.0010.185/0.227/0.370/0.088/0.130
), ArticleFig(id=1322931508956234294, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931504959062542, language=CN, label=表2, caption=

慢性心力衰竭病人积极度轨迹的潜类别增长模型拟合结果

, figureFileSmall=null, figureFileBig=null, tableContent=
类别LLAICBICaBICEntropyP值类别概率
LMRTBLRT
1-3 519.4227 050.8447 071.0967 052.083
2-3 235.6716 489.3426 519.7206 491.2000.930<0.001<0.0010.690/0.310
3-3 089.6866 203.3736 243.8766 205.8500.957<0.001<0.0010.273/0.329/0.398
4-3 077.4366 184.8716 235.5016 187.9680.9050.067<0.0010.245/0.116/0.366/0.273
5-3 069.8766 175.7526 236.5076 179.4680.9210.055<0.0010.185/0.227/0.370/0.088/0.130
), ArticleFig(id=1322931509019148855, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931504959062542, language=EN, label=Table 3, caption=

Univariate analysis of factors influencing latent classes of patient activation trajectories in chronic heart failure patients

, figureFileSmall=null, figureFileBig=null, tableContent=
项目分类高积极度-维持组(n=59)中积极度-下降组(n=71)低积极度-缓升组(n=86)统计值P
性别 [例(%)]男31(52.54)40(56.34)44(51.16)χ2=0.4340.805
女28(47.46)31(43.66)42(48.84)
年龄(岁)63.22±7.3663.49±6.6664.53±6.70F=0.7700.464
体质指数(kg/m2)23.21±2.3423.11±2.5222.97±2.40F=0.1810.834
文化程度 [例(%)]初中及以下14(23.73)28(39.44)40(46.51)
高中/中专22(37.29)26(36.62)29(33.72)χ2=10.1340.038
专科及以上23(38.98)17(23.94)17(19.77)
婚姻状况[例(%)]有配偶55(93.22)64(90.14)77(89.53)χ2=0.6110.737
无配偶4(6.78)7(9.86)9(10.47)
家庭人均月收入[例(%)]<3 000元18(30.51)19(26.76)24(27.91)
3 000~5 000元26(44.07)33(46.48)41(47.67)χ2=0.3490.986
>5 000元15(25.42)19(26.76)21(24.42)
心血管病家族史[例(%)]有9(15.25)4(5.63)4(4.65)χ2=6.1550.046
无50(84.75)67(94.37)82(95.35)
心力衰竭病因[例(%)]缺血性心脏病39(66.10)50(70.42)55(63.95)χ2=0.7440.689
非缺血性心脏病20(33.90)21(29.58)31(36.05)
心力衰竭病程(年)2.4(1.6,3.4)2.3(1.0,3.2)1.9 (1.0,3.3)H=2.0690.355
NYHA心功能分级[例(%)]Ⅰ级/Ⅱ级44(74.58)41(57.75)45(52.33)χ2=7.4920.024
Ⅲ级/Ⅳ级15(25.42)30(42.25)41(47.67)
合并症[例(%)]有21(35.59)39(54.93)54(62.79)χ2=10.5820.005
无38(64.41)32(45.07)32(37.21)
医疗费用支付方式[例(%)]省/市医保53(89.83)62(87.32)78(90.70)
新型农村合作医疗4(6.78)6(8.45)4(4.65)χ2=1.0640.900
其他2(3.39)3(4.23)4(4.65)
衰弱情况[例(%)]无衰弱32(54.24)14(19.72)21(24.42)
衰弱前期15(25.42)40(56.34)28(32.56)χ2=31.086<0.001
衰弱12(20.34)17(23.94)37(43.02)
社会支持(分)37.78±5.4632.87±6.2929.97±5.17F=33.657<0.001
), ArticleFig(id=1322931509107229240, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931504959062542, language=CN, label=表3, caption=

慢性心力衰竭病人积极度轨迹潜在类别影响因素的单因素分析

, figureFileSmall=null, figureFileBig=null, tableContent=
项目分类高积极度-维持组(n=59)中积极度-下降组(n=71)低积极度-缓升组(n=86)统计值P
性别 [例(%)]男31(52.54)40(56.34)44(51.16)χ2=0.4340.805
女28(47.46)31(43.66)42(48.84)
年龄(岁)63.22±7.3663.49±6.6664.53±6.70F=0.7700.464
体质指数(kg/m2)23.21±2.3423.11±2.5222.97±2.40F=0.1810.834
文化程度 [例(%)]初中及以下14(23.73)28(39.44)40(46.51)
高中/中专22(37.29)26(36.62)29(33.72)χ2=10.1340.038
专科及以上23(38.98)17(23.94)17(19.77)
婚姻状况[例(%)]有配偶55(93.22)64(90.14)77(89.53)χ2=0.6110.737
无配偶4(6.78)7(9.86)9(10.47)
家庭人均月收入[例(%)]<3 000元18(30.51)19(26.76)24(27.91)
3 000~5 000元26(44.07)33(46.48)41(47.67)χ2=0.3490.986
>5 000元15(25.42)19(26.76)21(24.42)
心血管病家族史[例(%)]有9(15.25)4(5.63)4(4.65)χ2=6.1550.046
无50(84.75)67(94.37)82(95.35)
心力衰竭病因[例(%)]缺血性心脏病39(66.10)50(70.42)55(63.95)χ2=0.7440.689
非缺血性心脏病20(33.90)21(29.58)31(36.05)
心力衰竭病程(年)2.4(1.6,3.4)2.3(1.0,3.2)1.9 (1.0,3.3)H=2.0690.355
NYHA心功能分级[例(%)]Ⅰ级/Ⅱ级44(74.58)41(57.75)45(52.33)χ2=7.4920.024
Ⅲ级/Ⅳ级15(25.42)30(42.25)41(47.67)
合并症[例(%)]有21(35.59)39(54.93)54(62.79)χ2=10.5820.005
无38(64.41)32(45.07)32(37.21)
医疗费用支付方式[例(%)]省/市医保53(89.83)62(87.32)78(90.70)
新型农村合作医疗4(6.78)6(8.45)4(4.65)χ2=1.0640.900
其他2(3.39)3(4.23)4(4.65)
衰弱情况[例(%)]无衰弱32(54.24)14(19.72)21(24.42)
衰弱前期15(25.42)40(56.34)28(32.56)χ2=31.086<0.001
衰弱12(20.34)17(23.94)37(43.02)
社会支持(分)37.78±5.4632.87±6.2929.97±5.17F=33.657<0.001
), ArticleFig(id=1322931509203698233, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931504959062542, language=EN, label=Table 4, caption=

Variable assignment

, figureFileSmall=null, figureFileBig=null, tableContent=
项目变量赋值
因变量病人积极度潜在类别低积极度-缓升组(0,0),高积极度-维持组(1,0),中积极度-下降组(0,1)
自变量文化程度初中及以下(0,0),高中/中专(1,0),专科及以上(0,1)
心血管病家族史无=1,有=2
NYHA心功能分级Ⅰ级/Ⅱ级=1,Ⅲ级/Ⅳ级=2
合并症无=1,有=2
衰弱情况无衰弱(0,0),衰弱前期(1,0),衰弱(0,1)
社会支持原值输入
), ArticleFig(id=1322931509287584314, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931504959062542, language=CN, label=表4, caption=

变量赋值

, figureFileSmall=null, figureFileBig=null, tableContent=
项目变量赋值
因变量病人积极度潜在类别低积极度-缓升组(0,0),高积极度-维持组(1,0),中积极度-下降组(0,1)
自变量文化程度初中及以下(0,0),高中/中专(1,0),专科及以上(0,1)
心血管病家族史无=1,有=2
NYHA心功能分级Ⅰ级/Ⅱ级=1,Ⅲ级/Ⅳ级=2
合并症无=1,有=2
衰弱情况无衰弱(0,0),衰弱前期(1,0),衰弱(0,1)
社会支持原值输入
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Logistic regression analysis of factors influencing latent classes of patient activation trajectories in chronic heart failure patients

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因变量自变量回归系数标准误Wald χ2 值POR值95%CI
下限上限
高积极度-维持组常量-7.2181.53522.103<0.001
文化程度 专科及以上1.4450.5526.8600.0094.2421.43912.508
高中/中专0.6810.5161.7400.1871.9760.7185.435
心血管病家族史1.2400.7692.5980.1073.4550.76515.598
NYHA心功能分级-0.9230.4474.2660.0390.3970.1650.954
合并症-1.1100.4406.3640.0120.3290.1390.781
衰弱情况 衰弱-1.1250.5364.4110.0360.3250.1140.928
衰弱前期-0.7250.5411.8000.1800.4840.1681.397
社会支持0.2260.04031.251<0.0011.2531.1581.356
中积极度-下降组常量-4.0741.23410.9040.001
文化程度 专科及以上0.3540.4520.6130.4341.4240.5883.452
高中/中专0.2850.3970.5160.4731.3300.6112.897
心血管病家族史0.2370.7850.0910.7631.2680.2725.911
NYHA心功能分级-0.2700.3490.5990.4390.7640.3861.512
合并症-0.2660.3520.5700.4500.7670.3851.528
衰弱情况 衰弱-0.2720.4810.3200.5720.7620.2961.957
衰弱前期0.9570.4584.3760.0362.6041.0626.385
社会支持0.1160.03412.0030.0011.1231.0521.199
), ArticleFig(id=1322931509442773564, tenantId=1146029695717560320, journalId=1220038315760373764, articleId=1322931504959062542, language=CN, label=表5, caption=

慢性心力衰竭病人积极度轨迹潜在类别影响因素的Logistic回归分析

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因变量自变量回归系数标准误Wald χ2 值POR值95%CI
下限上限
高积极度-维持组常量-7.2181.53522.103<0.001
文化程度 专科及以上1.4450.5526.8600.0094.2421.43912.508
高中/中专0.6810.5161.7400.1871.9760.7185.435
心血管病家族史1.2400.7692.5980.1073.4550.76515.598
NYHA心功能分级-0.9230.4474.2660.0390.3970.1650.954
合并症-1.1100.4406.3640.0120.3290.1390.781
衰弱情况 衰弱-1.1250.5364.4110.0360.3250.1140.928
衰弱前期-0.7250.5411.8000.1800.4840.1681.397
社会支持0.2260.04031.251<0.0011.2531.1581.356
中积极度-下降组常量-4.0741.23410.9040.001
文化程度 专科及以上0.3540.4520.6130.4341.4240.5883.452
高中/中专0.2850.3970.5160.4731.3300.6112.897
心血管病家族史0.2370.7850.0910.7631.2680.2725.911
NYHA心功能分级-0.2700.3490.5990.4390.7640.3861.512
合并症-0.2660.3520.5700.4500.7670.3851.528
衰弱情况 衰弱-0.2720.4810.3200.5720.7620.2961.957
衰弱前期0.9570.4584.3760.0362.6041.0626.385
社会支持0.1160.03412.0030.0011.1231.0521.199
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基于潜类别增长模型的慢性心力衰竭病人积极度纵向轨迹及影响因素
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陈敏 , 袁娴 , 耿娟 *, *
护理研究 | 科研论著 2026,40(13): 2278-2286
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护理研究 |科研论著 2026 , 40 (13) : 2278 -2286
基于潜类别增长模型的慢性心力衰竭病人积极度纵向轨迹及影响因素
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陈敏, 袁娴, 耿娟*, *
作者信息
  • 1徐州医科大学附属淮安医院/淮安市第二人民医院,江苏 223000
通讯作者:
耿娟,E-mail:
GENG Juan, E-mail:
作者简介:

陈敏,护师,本科

Longitudinal trajectories and influencing factors of activation in chronic heart failure patients based on latent class growth model
Min CHEN, Xian YUAN, Juan GENG
Affiliations
  • 1The Affiliated Huai'an Hospital of Xuzhou Medical University/Huai'an Second People's Hospital, Jiangsu 223000 China
出版时间: 2026-07-10 doi: 10.12102/j.issn.1009-6493.2026.13.012
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目的

探究慢性心力衰竭病人积极度纵向轨迹的潜在类别,并分析其影响因素。

方法

选取2023年1月—2024年8月我院收治的慢性心力衰竭病人为研究对象。在病人出院前(T1)采用一般资料调查表及中文版病人积极度量表(PAM 13)、衰弱风险筛查工具(FRAIL)、社会支持评定量表(SSRS)进行调查;在出院后1个月(T2)、3个月(T3)、6个月(T4)采用中文版病人积极度量表评估病人的积极度。采用Spearman相关性分析4个时间点病人积极度的相关性;通过潜类别增长模型识别病人积极度轨迹的潜在类别,并采用多分类Logistic回归分析病人积极度轨迹潜在类别的影响因素。

结果

216例病人完成研究。T1、T2、T3、T4时病人积极度评分依次为54.6(40.1,66.0)分、56.4(43.4,73.1)分、51.4(41.7,63.2)分、51.4(42.1,66.0)分。Spearman相关性分析显示,4个时间点的病人积极度评分均呈正相关(均P<0.01)。潜类别增长模型识别的病人积极度轨迹被划分为3个类别:高积极度-维持组(27.3%)、中积极度-下降组(32.9%)、低积极度-缓升组(39.8%)。多分类Logistic回归分析结果显示,文化程度、心功能分级、合并症、衰弱情况、社会支持是慢性心力衰竭病人积极度轨迹潜在类别的影响因素(均P<0.05)。

结论

慢性心力衰竭病人积极度轨迹存在群体异质性,其受到文化程度、心功能分级、合并症、衰弱情况、社会支持的影响。医护人员应根据病人积极度轨迹特点给予针对性干预,提高病人积极度水平。

慢性心力衰竭  /  病人积极度  /  轨迹  /  潜类别增长模型  /  影响因素  /  纵向研究
Objective

To explore the potential categories of longitudinal trajectories of patient activation in individuals with chronic heart failure and to analyze their influencing factors.

Methods

Patients with chronic heart failure admitted to our hospital from January 2023 to August 2024 were selected as the study subjects.Before discharge(T1),surveys were conducted using a general information questionnaire,the Chinese version of the Patient Activation Measure(PAM13),the FRAIL scale(to screen for frailty risk),and the Social Support Rating Scale(SSRS).Patient activation was reassessed using the Chinese version of the PAM 13 at 1 month(T2),3 months(T3),and 6 months(T4) after discharge.Spearman correlation analysis was used to examine the correlations of patient activation scores across the four time points.Latent class growth modeling was employed to identify potential categories of patient activation trajectories,and multinomial logistic regression was performed to analyze the influencing factors of these trajectory categories.

Results

A total of 216 patients completed the study.The patient activation scores at T1,T2,T3,and T4 were 54.6 (40.1,66.0),56.4(43.4,73.1),51.4(41.7,63.2),and 51.4(42.1,66.0),respectively.Spearman correlation analysis showed positive correlations among patient activation scores at all four time points(all P<0.01).The latent class growth model identified three distinct trajectory categories:high activation-stable group(27.3%),moderate activation-declining group(32.9%),and low activation-gradually increasing group(39.8%).Multinomial Logistic regression revealed that education level,NYHA functional class,comorbidities,frailty status,and social support were significant influencing factors for the trajectory categories of patient activation in chronic heart failure patients(all P<0.05).

Conclusions

There is significant inter-individual heterogeneity in the trajectories of patient activation among chronic heart failure patients,which are influenced by education level,NYHA functional class,comorbidities,frailty status,and social support.Healthcare providers should implement targeted interventions based on the characteristics of patients' activation trajectories to comprehensively improve their activation levels.

chronic heart failure  /  patient activation  /  trajectory  /  latent class growth model  /  influencing factors  /  longitudinal study
陈敏, 袁娴, 耿娟. 基于潜类别增长模型的慢性心力衰竭病人积极度纵向轨迹及影响因素. 护理研究, 2026 , 40 (13) : 2278 -2286 . DOI: 10.12102/j.issn.1009-6493.2026.13.012
Min CHEN, Xian YUAN, Juan GENG. Longitudinal trajectories and influencing factors of activation in chronic heart failure patients based on latent class growth model[J]. Chinese Nursing Research, 2026 , 40 (13) : 2278 -2286 . DOI: 10.12102/j.issn.1009-6493.2026.13.012
慢性心力衰竭是一种复杂的临床综合征群,源于心脏结构或功能的异常,引起心功能下降,通常作为各种心脏疾病发展的终末阶段,其特征是发病率高、病程长、生活质量低,影响着全球超6 400万人[1],预测到2050年心力衰竭患病率将上升2.7%~3.8%[2]。Ma[3]报道慢性心力衰竭病人出院后6个月内再住院率高达23.6%。慢性心力衰竭病人病情稳定出院后需进行长期的自我管理,以维持病情稳定状态,降低再住院率,改善健康结局。《中国防治慢性病中长期规划(2017—2025年)》也鼓励病人积极管理自身健康[4]。病人积极度最早由美国Hibbard等[5]提出,指的是病人在疾病治疗康复过程中的主动参与度与积极投入程度,包括自我健康管理能力、健康相关信息的积极寻求以及预防疾病恶化的知识、技能、信心和行为,表现为病人在慢性病管理过程中重视自身的作用和地位。但有研究显示,中国慢性病病人的积极度水平较低,使其难以融入慢性病自我管理系统[6]。Creber等[7]针对心力衰竭病人积极度的研究显示,仅39%病人“采取行动”。病人积极度水平低会削弱病人对抗疾病的信心和动力,导致依从性下降、症状监测与响应延迟,自我管理能力弱化,影响心理社会功能与生活质量;而提高病人积极度水平有助于改善健康结局、提高生活质量、降低再住院率、减轻医疗负担[8]。因此,关注病人积极度至关重要。目前,关于慢性心力衰竭病人积极度的研究较少,病人积极度理论反映了积极度呈动态变化,涉及多阶段过程,同时受多因素影响,其水平变化还可作为健康结局的重要预测指标[9]。因此,研究病人积极度纵向轨迹及其影响因素更具临床意义。潜类别增长模型在识别群体异质性发展模式中具有显著优势[10],本研究则通过潜类别增长模型分析病人积极度的纵向发展轨迹及其潜在类别,并剖析影响因素,旨在为制定精准化、差异化、阶段性的干预策略提供科学依据,推动慢性心力衰竭病人全程管理方案优化与健康结局改善。
本研究为纵向研究。采用便利抽样法,选取2023年1月—2024年8月我院收治的慢性心力衰竭病人为研究对象。根据潜类别增长模型识别类别的准确性、稳健性要求[11],且采用贝叶斯信息准则(Bayesian information criterion,BIC)作为选择模型的重要考虑指标时,样本量应≥200例[12]。同时考虑样本缺失率15%,则需要样本量至少230例,本研究在T1时纳入了232例慢性心力衰竭病人,满足样本量需求。纳入标准:慢性心力衰竭符合《中国心力衰竭诊断和治疗指南2018》[13]中的诊断标准;年龄>18岁;认知功能和语言沟通交流能力正常;接受随访,自愿参与调查,签署知情同意书。排除标准:合并呼吸衰竭、肝肾功能障碍;合并恶性肿瘤、慢性消耗性疾病(肺结核、系统性红斑狼疮等);既往有脑外伤、脑卒中疾病史;神经系统疾病史(阿尔茨海默病、癫痫、多发性硬化症等);精神疾病、听力障碍、视力障碍;肢体功能严重障碍。脱落与剔除标准:中途退出;研究期间发生其他严重疾病;失访;死亡。本研究经医学伦理委员会批准(审批号:HEYLL202366)。
结合研究目的与临床情况,在文献调研[14-16]及专家咨询的基础上编制一般资料表,包括性别、年龄、体质指数、文化程度、婚姻状况、家庭人均月收入、心血管病家族史、心力衰竭病因、心力衰竭病程、美国纽约心脏病协会(New York Heart Association,NYHA)心功能分级、合并症、医疗费用支付方式。
原量表由Hibbard等[17]开发,用于评估病人在自我管理中的知识、技能及自信度;陈士巧等[18]修订汉化PAM13应用于慢性心力衰竭病人并证实信效度理想。PAM13包含认知、技能、行动、信念4个维度,共13个条目,“非常不同意”至“非常同意”依次计1~4分,0分为“不适用”。总分为原始分,再依据Hibbard等[17]设计的评分转换表,标准化为100分制得分,转换后的病人积极度评分为0~100分,评分越高,说明病人积极度水平越高。Hibbard等[17]根据转换后的评分划分为4个水平:第1水平<47.0分,代表病人不能发挥主观能动性,不知所措;第2水平47.1~55.1分,代表病人缺乏管理疾病的信心与知识;第3水平55.2~67.0分,代表病人主动接受治疗,但缺乏技能与信心支持自我管理行为;第4水平≥67.1分,代表病人有信心面对疾病与付出行动。本研究中PAM13总Cronbach's α系数为0.939。
量表由Morley等[19]编制,卫尹等[20]汉化,Cronbach's α系数为0.826,用于测评躯体领域的衰弱。该量表包括疲乏、耐力、步行、疾病、体重5个方面。每个方面“是”计1分,“否”计0分,总分0~5分,0分代表无衰弱,1~2分代表衰弱前期,≥3分代表衰弱。本研究中FRAIL量表的Cronbach's α系数为0.809。
SSRS由肖水源[21]编制,目前广泛用于评定社会支持水平。包含客观支持(3个条目)、主观支持(4个条目)、对支持的利用度(3个条目)3个维度、共10个条目。条目1~4、条目8~10计分1~4分;条目5分为5项,每项计分1~4分(代表从“无”到“全力支持”);条目6、7有几个来源计几分(分别9个来源),“无”则计0分。总分12~66分,评分越高提示社会支持水平越高。本研究中SSRS的Cronbach's α系数为0.812。
参照既往慢性心力衰竭纵向研究[22-23]以及病人积极度纵向研究[24]时间点的选择(住院时以及出院后1个月、3个月、6个月),根据《中国心力衰竭诊断和治疗指南2018》[13]的随访要求,结合慢性心力衰竭病人的病情状态及随访时间,本研究选择的调查时间点为出院前(T1)、出院后1个月(T2)、出院后3个月(T3)、出院后6个月(T4)。收集资料前,对调查者进行统一培训,正式调查时先向病人说明目的、意义、内容等,取得知情同意后开始调查。T1时主要通过一般资料调查表及PAM13、FRAIL、SSRS进行现场问卷调查;T2~T4门诊随访当天通过现场调查、电话随访调查等形式调查病人积极度。由于疾病等原因不便填写者,由调查者逐一读题询问并记录。所有调查均由研究者及时检查有效性,若发现漏项、错误等,第一时间与病人确认并纠正。
1)研究设计:前期回顾大量国内外相关文献,结合慢性心力衰竭相关临床实践,确定选题的科学性、可行性、临床价值;病例入选严格依据纳入与排除标准筛选,减少个体偏倚;选择条目数相对不多、信效度良好、应用具有针对性或广泛性的调查工具,增强问卷可读性、调查可行性、调查效率。2)研究实施:对调查者进行理论培训与实操培训,培训通过后方可参与研究,在研究过程中定期组织研究人员进行经验交流和问题讨论,及时解决遇到的困难和问题;每次随访前,提前与病人进行沟通,告知随访时间、方式和内容等,取得病人的配合。3)数据处理:每例病人设有单独编号,执行保密原则;双人核对并录入数据,确保数据准确性。4)伦理原则:遵循知情同意原则、保密原则、有益无害原则。
采用SPSS 26.0统计软件和Mplus 8.3软件分析数据。定性资料以例数、百分比(%)表示,比较采用χ2检验;定量资料服从正态分布以均数±标准差(x±s)表示,组间比较采用单因素方差分析;偏态分布的定量资料以中位数、四分位数[M(P25,P75)]表示,相关性采用Spearman相关性分析,组间比较采取非参数Kruskal-Wallis H检验,T1~T4积极度评分比较采用Friedman秩和检验,Bonferroni校正法进行两两对比。采用Mplus 8.3软件进行潜类别增长模型分析,从单一类别开始,逐个增加模型中的类别数,比较各模型拟合指标,综合比较并选择最佳模型。模型拟合指标主要为:对数似然值(Log-likelihood,LL)、赤池信息准则(Akaike Information Criterion,AIC)、BIC、校正后BIC(adjusted BIC,aBIC)、信息熵(Entropy)、罗-梦戴尔-鲁本校正似然比检验(Lo-Medell-Rubin likelihood ratio test,LMRT)、基于Bootstrap的似然比检验(Bootstrap likelihood ratio test,BLRT)。其中,AIC、BIC、aBIC越低,模型拟合越好;LMRT、BLRT检验P<0.05时代表k个类别模型优于k-1个类别模型;Entropy范围0~1,当信息熵>0.8时提示模型分类精准度>90%[25]。最后,通过多分类Logistic回归分析慢性心力衰竭病人积极度轨迹潜在类别的影响因素。P<0.05为差异有统计学意义。
本研究在T1时纳入了232例慢性心力衰竭病人;T2时3例主动退出、1例因电话及住址变更失联,共228例完成随访与调查;T3时2例主动退出、3例失去联系,共223例完成随访与调查;T4时1例意外死亡、2例病情加重住院治疗、2例主动退出、2例失去联系,最终216例病人完成随访与调查。216例慢性心力衰竭病人中,男115例,女101例;年龄44~77(63.83±6.86)岁;体质指数17.9~29.1(23.08±2.41)kg/m2;心力衰竭病因:缺血性心脏病144例,非缺血性心脏病72例。
慢性心力衰竭病人4个时间点积极度评分比较差异有统计学意义(χ2=65.288,P<0.001);4个时间点病人积极度评分整体呈先上升后降低的趋势。Spearman相关性分析显示,4个时间点的病人积极度评分均呈正相关(均P<0.01),提示病人积极度变化的连续型,满足潜类别增长模型拟合病人积极度轨迹的前提。结果见表1。
针对慢性心力衰竭病人积极度4个时间点的评分,建立1~5个类别参数进行潜类别增长分析。各潜在类别的模型拟合结果显示,随着潜类别数增加,AIC、BIC、aBIC呈下降趋势,当拟合4个类别时,LMRT检验无统计学意义(P>0.05),提示4类模型不优于3类模型;而当保留3个类别时,LMRT、BLRT检验均P<0.001,且3个类别时Entropy值最高。因此,选择3个类别模型作为最优模型。拟合结果见表2。
根据潜类别增长模型的3个类别,形成病人积极度轨迹图(见图1),根据轨迹变化特征对各类别进行命名。类别1:病人积极度起始值最高(截距=71.944,P<0.001),但随时间推移保持相对平稳趋势、全程变化无统计学意义(斜率=-0.132,P=0.711),故命名为“高积极度-维持组”,共59例(27.3%)。类别2:病人积极度起始值中等(截距=57.597,P<0.001),随时间推移出现明显下降趋势(斜率=-1.891,P<0.001),故命名为“中积极度-下降组”,共71例(32.9%)。类别3:病人积极度起始值最低(截距=39.838,P<0.001),随时间推移出现缓慢升高趋势(斜率=0.683,P=0.005),斜率较低、上升趋势较缓,故命名为“低积极度-缓升组”,共86例(39.8%)。
单因素分析结果显示,文化程度、心血管病家族史、NYHA心功能分级、合并症、衰弱情况、社会支持在不同潜在类别分组中比较差异有统计学意义(均P<0.05)。见表3。
以慢性心力衰竭病人积极度潜在类别为因变量,以单因素分析中有统计学意义的变量为自变量(赋值方式见表4),纳入多分类Logistic回归模型。结果显示,文化程度、NYHA心功能分级、合并症、衰弱情况、社会支持是慢性心力衰竭病人积极度轨迹潜在类别的影响因素(均P<0.05)。见表5。
本研究结果显示,慢性心力衰竭病人T1时积极度评分54.6(40.1,66.0)分,与Creber等[7]报道的心力衰竭住院病人积极度中位评分(55.6分)相对接近;而T2、T3、T4时病人积极度评分56.4(43.4,73.1)分、51.4(41.7,63.2)分、51.4(42.1,66.0)分,整体呈先上升后降低的趋势。分析原因为:T2时(出院后1个月)整体积极度得分上升,可能与出院期的干预强化有关,出院前医护人员会强调症状监测、用药规范、饮食与生活方式等内容,短期内有利于提高依从性与疾病管理效能[26];且经过住院治疗后病人呼吸困难、乏力等症状减轻,身体机能逐渐得到恢复,管理疾病的意愿与能力更强,故出院后1个月积极度水平有所提高。而出院后3、6个月,积极度评分相比出院后1个月明显降低,与Rijken等[27]报道的慢性病病人积极度水平随时间推移出现降低趋势有相似之处,可能原因为慢性心力衰竭病程长,病人长期坚持困难,且症状反复,心理压力增加,会导致对自我管理效果的怀疑[28];若同时合并高血压、糖尿病等,可能增加管理疾病的难度与信心,导致积极度下降。Tusa等[29]研究也指出,随着时间的推移,病人在尝试管理慢性病时可能会经历多次失败,这可能导致沮丧和无能为力,使病人对疾病管理变得被动,故而积极度降低。根据Hibbard等[17]对积极度水平的划分,可以看出本研究病人积极度水平在T1~T4均有较大提升空间。Anderson等[30]研究表明,高水平的病人积极度与住院风险降低相关[RR=0.69,95%CI(0.61~0.77)],病人积极度与医疗资源利用关系密切。因此,需关注并助力提高慢性心力衰竭病人积极度水平。
本研究通过潜类别增长模型识别出慢性心力衰竭病人积极度纵向轨迹分为3个类别:“高积极度-维持组”(27.3%)、“中积极度-下降组”(32.9%)、“低积极度-缓升组”(39.8%)。说明病人积极度变化轨迹存在群体异质性。27.3%的病人积极度水平变化处于高积极度-维持状态,说明此类病人起始积极度水平更高,在疾病进程中保持稳定,反映对疾病较好的认知、主动参与自我管理、具有一定的自我管理能力和信心,这也与Kim等[31]报道的心力衰竭病人自我保健行为(基线及出院后1、3、6个月)变化轨迹为“高-持续”的这一类别相契合,还与Pancani等[32]报道的心力衰竭病人自我照顾自信与维持的“高水平-维持”轨迹相契合。而32.9%的病人起始积极度中等,但随时间推移出现下降,这伴随依从性降低、自我管理信心降低与行为减少,长期治疗与疾病管理也可能出现心理倦怠,或因管理效果不佳而产生挫败感导致积极性衰减。根据病人积极度理论[9],此类病人对疾病具备一定认知,但随时间推移,病人对健康促进行为有所懈怠、疏于自我管理。“低积极度-缓升组”占比最高(39.8%),说明很大一部分病人起始积极度水平相对低,表现为被动接受治疗干预、应对信心与能力不足、自我管理意识薄弱,虽有上升趋势但很缓慢,反映有潜在积极度提高的信号,有待进一步追踪与干预。郝娟娟[24]针对脑卒中病人积极度的研究也识别出了“低积极度-上升”这一轨迹,目前有关心力衰竭病人积极度的研究尚少,但是本研究潜类别增长模型分析结果为分层干预提供了新视角,提示护理人员应制定和实施差异化、个体化的干预策略,对于“高积极度-维持组”需强化自我管理积极度的延续性;对于“中积极度-下降组”识别积极性下降的诱因,精准干预以防止积极度下降;对于“低积极度-缓升组”重点提升疾病认知,长期投入以提高积极度和加速上升趋势。
本研究显示,相较于“低积极度-缓升组”,文化程度专科及以上[OR=4.242,95%CI(1.439,12.508)]、社会支持水平更高[OR=1.253,95%CI(1.158,1.356)]的病人更易归于“高积极度-维持组”。病人积极度量表条目如“我了解我健康问题的根源与起因”“我知道如何避免让我的健康状况产生更多的问题”等,反映了病人的疾病认知、健康管理意识及能力等[33],而心衰管理涉及复杂的药物机制、症状监测等,专科及以上文化程度病人知识水平与健康素养更高,具备更强的理解、信息转化及应用能力,主动管理意识与持续的信念更强,积极度更高且更趋于稳定。陈建静等[34]研究指出,知识是积极的前提,其中不仅涉及积极主动汲取新信息,还包括外部优势资源的输送,侧面提示文化程度对积极水平的可能影响。本研究病人社会支持评分与陈俊杰等[35]报道的慢性心力衰竭病人社会支持结果相接近。社会支持水平更高的群体可更多获得实际帮助、精神支持、情感鼓励等,利于缓冲疾病管理造就的心理压力,激发自我管理的潜力[36],从而在保持高积极度状态下防止因挫折而下降,进而维持稳定。Kim等[31]研究中也发现,更高的健康素养和社会支持可预测心力衰竭病人进入“高-持续”的自我保健行为轨迹组。因此,护理人员需结合病人文化程度实施分层健康教育,助力提高病人认知与健康素养;并主动评估社会支持网络,加强多学科团队支持,还可增加过渡期护理干预以提升社会支持水平,促进积极度增高或高水平-稳定状态[37]。
本研究显示,相较于“低积极度-缓升组”,衰弱前期[OR=2.604,95%CI(1.062,6.385)]、社会支持水平更高[OR=1.123,95%CI(1.052,1.199)]的病人更易归于“中积极度-下降组”。本研究中衰弱前期病人占38.43%,稍低于丁华等[38]报道的慢性心力衰竭衰弱前期率42.9%,可能与样本量差异、个体化差异有关。衰弱前期介于健康与衰弱之间的过渡阶段,随时间延长可伴疲劳、活动耐量降低、虚弱等[39],生理上的转变可能影响病人的效能感与自信心,表现为积极性滑落。社会支持水平更高的病人更易进入“中积极度-下降组”主要是受起始水平的影响,本研究出于前瞻性预测考虑,对社会支持水平仅调查了出院前单个时点,这一阶段社会支持水平更高对积极度的正向影响更大[40],但随时间变化可能因心理转变削弱主动管理动机,此部分病人内在动力随时间弱化,积极性下降。因此,护理人员需早期识别与评估衰弱前期,设计低负荷管理方案,抓住衰弱前期的可逆性预防向衰弱的发展;基于病人为中心的支持导向建立“病人-家属-医护”协同机制促进社会支持可持续提升,实现社会支持积极影响的持续性,减少后期积极度下降的偏移。Almutairi等[41]研究表明,社区健康指导提供个性化的支持,在改善慢性病自我管理和病人积极度方面效果较好。徐筱璐等[42]从健康生态学视角构建了包含社会支持的慢性心力衰竭综合评价指标体系,均为优化健康管理及提高可持续性提供了借鉴。
本研究显示,相对于“高积极度-维持组”,心功能分级Ⅲ级/Ⅳ级、有合并症、衰弱的病人更易归于“低积极度-缓升组”。心功能分级Ⅲ级/Ⅳ级的病人病情状态更严重,病人静息或轻微活动会出现呼吸困难等症状,日常活动受限,病人践行健康管理的耐受度和能力有限,自理能力与恢复力降低[38],积极度低。慢性心力衰竭若合并糖尿病、高血压等合并症,一方面伴有更多的身体不适,心理与身体负担增加,活动能力下降;另一方面需同时遵循多重医嘱与用药方案,疾病管理的难度更高,会影响病人自我健康管理的能力与信心,故积极度低。郑旻嘉等[43]研究也发现,有合并症的冠心病病人积极度水平更低。而随时间推移,病人有缓冲的时间逐步掌握管理技能,管理复杂度随时间进展有所下降,故积极度出现缓慢回升,但后续如何变化有待延长随访时间进一步观察。衰弱反映生理系统功能与储备降低,对不良结局的脆弱性与敏感度增加。Overbeek等[44]研究表明,衰弱与病人积极度呈负相关,衰弱者更难以自我管理健康。衰弱病人生理功能减退、症状负担增加,管理行为受限于活动能力,主动积极性相对低,需长时间重建管理信心。因此,临床应加强多学科协作,根据心功能分级与合并症情况,优化用药方案与用药管理干预,提高个体化干预效果;在精准营养支持基础上通过呼吸操、柔韧运动、平衡训练以及抗阻训练[45]改善衰弱状况,减轻衰弱状态对积极度的不利影响。Skolasky等[46]研究还发现,护士主导的基于网络的自我管理计划可提高病人积极度水平。因此,可从多方面着手助力提高病人积极度水平,进而改善康复结局。
慢性心力衰竭病人积极度轨迹存在群体异质性,其受到文化程度、心功能分级、合并症、衰弱情况、社会支持的影响。医护人员应根据病人积极度轨迹特点给予针对性干预,整体提高病人积极度水平。本研究由于人力与时间条件等有限,仅调查我院慢性心力衰竭病人,可能有样本选择偏倚,随访时间也有待延长,未来可进一步开展长周期、大样本、多中心的追踪调查研究,为临床护理提供更多参考。

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2026年第40卷第13期
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doi: 10.12102/j.issn.1009-6493.2026.13.012
  • 接收时间:2025-07-04
  • 首发时间:2026-10-30
  • 出版时间:2026-07-10
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  • 收稿日期:2025-07-04
  • 修回日期:2026-05-17
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    1徐州医科大学附属淮安医院/淮安市第二人民医院,江苏 223000

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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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