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Article(id=1241023858623435480, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023847537897695, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202409047, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1725292800000, receivedDateStr=2024-09-03, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773812745004, onlineDateStr=2026-03-18, pubDate=1737734400000, pubDateStr=2025-01-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773812745004, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773812745004, creator=13701087609, updateTime=1773812745004, updator=13701087609, issue=Issue{id=1241023847537897695, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='2', pageStart='193', pageEnd='384', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773812742361, creator=13701087609, updateTime=1773812823817, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241024189247845056, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023847537897695, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241024189247845057, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023847537897695, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=297, endPage=302, ext={EN=ArticleExt(id=1241023858971562740, articleId=1241023858623435480, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Analysis of latent profiles and related factors for primary caregivers burden in families with cancer patients, columnId=1228016567846367388, journalTitle=Modern Preventive Medicine, columnName=Health Policy and Management, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the potential categories of primary caregiver burden in families of cancer patients and their potential related factors, and to provide scientific basis for more targeted policy interventions.

Methods

From February to April 2023, we conducted a questionnaire survey among the primary family caregivers of cancer patients at the Third Affiliated Hospital of Harbin Medical University using convenience sampling. Latent profile analysis was employed to identify potential categories of caregiver burden. The modified BCH method was used to assess the differences in family resilience, individual resilience, and caregiving ability across different burden categories.

Results

A total of 367 participants were included in the study, and their caregiving burden was divided into two categories, named "mild caregiver burden group" and "moderate and severe caregiver burden group". The respondents of "moderate to heavy caregiver burden" were mostly female who were highly educated and had spouse and children. Different potential categories of family caregiver burden profiles showed statistically significant differences in family resilience (χ2=5.333，P=0.021), individual resilience (χ2=31.687，P<0.001), and caregiving ability (χ2=13.391，P<0.001).

Conclusion

There are heterogeneous subgroups of primary caregiver burden in families of cancer patients, and policy makers should implement targeted interventions to reduce the burden of primary caregivers for families with cancer patients, and to improve their personal and family resilience and caring abilities.

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目的

本研究旨在探究癌症患者家庭主要照顾者负担的潜在类别及其潜在相关因素，为采取更具针对性的政策干预措施提供科学依据。

方法

研究于2023年2月—4月采用方便抽样选取哈尔滨医科大学附属第三医院癌症患者家庭主要照顾者作为调查对象开展问卷调查，利用潜在剖面分析探索癌症患者家庭照顾者负担的潜在类别，采用R3STEP法的多项式logistic回归分析探讨人口学变量与照顾负担在类别的不同关联，使用修正的BCH 法验证照顾负担的不同潜在类别对家庭韧性、照顾者个人韧性及照顾能力的差异性。

结果

研究共纳入367名参与者，其照顾负担分为2个类别，分别为 “轻度照顾者负担组”和“中重度照顾者负担组”。“中重度照顾者负担”的受访者多以女性、高学历、配偶和子女为主要特征。不同潜在类别的家庭照顾者负担剖面，在家庭韧性（χ2=5.333，P=0.021）、个人韧性（χ2=31.687，P<0.001）、照顾能力（χ2=13.391，P<0.001）上的差异具有统计学意义。

结论

癌症患者家庭主要照顾者负担存在异质性亚组，政策制定者应实施有针对性的干预措施，以降低癌症患者家庭主要照顾者负担，进而改善其个人与家庭韧性及照顾能力水平。

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刘欢，E-mail：
, copyrightStatement=本刊刊出的所有文章不代表中华预防医学会和本刊编委会的观点，除非特别声明。, copyrightOwner=中华预防医学会和四川大学华西公共卫生学院, extLink=null, articleAbsUrl=null, sourceXml=bz5W6F/P17+HgE7BJoOSYw==, magXml=+PN2bdmLaAMzXmKqdcXkwg==, pdfUrl=null, pdf=B21NhfaSxJtu3YrbHAte9w==, pdfFileSize=747798, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=5rs3W5nOMu6IPprqBMIpOQ==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=yzOnP8Gj2nFBUa+3ORDa9g==, mapNumber=null, authorCompany=null, fund=null, authors=

黄维奇（1999—），男，博士在读，研究方向：卫生应急、健康政策

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黄维奇（1999—），男，博士在读，研究方向：卫生应急、健康政策

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黄维奇（1999—），男，博士在读，研究方向：卫生应急、健康政策

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(In Chinese), articleTitle=Analysis of development status quo and countermeasures of hospice care service under the background of aging, refAbstract=null)], funds=[Fund(id=1241023867951567117, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023858623435480, awardId=72304079, language=CN, fundingSource=国家自然科学基金项目(72304079), fundOrder=null, country=null), Fund(id=1241023868073201936, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023858623435480, awardId=LBH-Z21181, language=CN, fundingSource=黑龙江省博士后(LBH-Z21181), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241023861119046586, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023858623435480, xref=null, ext=[AuthorCompanyExt(id=1241023861135823805, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023858623435480, companyId=1241023861119046586, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Health Management, Harbin Medical University, Harbin, Heilongjiang 150081, China), AuthorCompanyExt(id=1241023861144212416, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023858623435480, companyId=1241023861119046586, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=哈尔滨医科大学卫生管理学院，黑龙江　哈尔滨　150081)])], figs=[ArticleFig(id=1241023864981999791, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023858623435480, language=EN, label=Fig.1, caption=Sample Adjusted Bayesian information criteria change trend graph, figureFileSmall=kycHyBnXX1ywtZHymB/QcA==, figureFileBig=5rs3W5nOMu6IPprqBMIpOQ==, tableContent=null), ArticleFig(id=1241023865099440313, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023858623435480, language=CN, label=图1, caption=样本校正的贝叶斯信息准则变化趋势图, figureFileSmall=kycHyBnXX1ywtZHymB/QcA==, figureFileBig=5rs3W5nOMu6IPprqBMIpOQ==, tableContent=null), ArticleFig(id=1241023865338515656, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023858623435480, language=EN, label=Fig.2, caption=Feature distribution based on two potential categories of the Cancer Family caregiver Burden Scale, figureFileSmall=vRDaFi+kVKuFXwB2erwttw==, figureFileBig=hw9PL8WISPyJcdpRWmaK/w==, tableContent=null), ArticleFig(id=1241023865405624528, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023858623435480, language=CN, label=图2, caption=基于癌症家庭照顾者负担量表2个潜在类别的特征分布, figureFileSmall=vRDaFi+kVKuFXwB2erwttw==, figureFileBig=hw9PL8WISPyJcdpRWmaK/w==, tableContent=null), ArticleFig(id=1241023865493704917, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023858623435480, language=EN, label=Table 1, caption=

Sociodemographiccharacteristicsof primary family caregivers of cancer patients

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变量分类人数(n)百分比(%)
性别女16043.6
男20756.4
年龄(岁)19~358021.8
36~438824.0
44~5210127.5
≥539726.4
缺失10.3
与患者的关系配偶13336.2
子女18249.6
父母102.7
儿媳/女婿184.9
兄弟姐妹143.8
其他102.7
是否为独生子女是15642.5
否21157.5
文化程度小学及以下215.7
初中10829.4
高中9525.9
大学及以上14339.0
就业状况在业21759.1
无业15040.9
家庭人均月收入(元)<2 0008623.4
2 000~3 9998523.2
4 000~5 9995314.4
≥6 00014339.0
平均每天照顾时间(h)≤67921.5
7~1212032.7
>1216745.5
缺失10.3
), ArticleFig(id=1241023865598562522, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023858623435480, language=CN, label=表1, caption=

癌症患者家庭主要照顾者社会人口学资料

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变量分类人数(n)百分比(%)
性别女16043.6
男20756.4
年龄(岁)19~358021.8
36~438824.0
44~5210127.5
≥539726.4
缺失10.3
与患者的关系配偶13336.2
子女18249.6
父母102.7
儿媳/女婿184.9
兄弟姐妹143.8
其他102.7
是否为独生子女是15642.5
否21157.5
文化程度小学及以下215.7
初中10829.4
高中9525.9
大学及以上14339.0
就业状况在业21759.1
无业15040.9
家庭人均月收入(元)<2 0008623.4
2 000~3 9998523.2
4 000~5 9995314.4
≥6 00014339.0
平均每天照顾时间(h)≤67921.5
7~1212032.7
>1216745.5
缺失10.3
), ArticleFig(id=1241023865732780257, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023858623435480, language=EN, label=Table 2, caption=

Fitting indicators of potential category of primary family caregiver burden

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模型AICBICaBICEntropyLMR(P)BLRT(P)类别概率
124 453.98324 618.00824 484.758---1.000
223 251.53823 501.48123 298.4340.926<0.001<0.0010.285/0.715
322 925.25623 261.11722 988.2720.8820.065<0.0010.206/0.294/0.501
422 535.18322 956.96222 614.3190.9180.134<0.0010.204/0.439/0.276/0.081
), ArticleFig(id=1241023865871192297, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023858623435480, language=CN, label=表2, caption=

癌症患者家庭主要照顾者负担潜在类别模型拟合指标

, figureFileSmall=null, figureFileBig=null, tableContent=
模型AICBICaBICEntropyLMR(P)BLRT(P)类别概率
124 453.98324 618.00824 484.758---1.000
223 251.53823 501.48123 298.4340.926<0.001<0.0010.285/0.715
322 925.25623 261.11722 988.2720.8820.065<0.0010.206/0.294/0.501
422 535.18322 956.96222 614.3190.9180.134<0.0010.204/0.439/0.276/0.081
), ArticleFig(id=1241023866047353070, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023858623435480, language=EN, label=Table 3, caption=

Descriptive data andresults of difference tests for predictive variables between the two groups

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变量分类轻度照顾者负担组
(n=103)		中重度照顾者负担组
(n=264)		βSEOR(95%CI)P
性别女0.3280.4800.9670.2842.630(1.51, 4.59)0.001
男0.6720.520
年龄(岁)19~350.3040.1870.1090.1381.115(0.85, 1.46)0.428
36~430.2310.243
44~520.2220.296
≥530.2420.273
与患者的关系配偶0.2780.3960.3900.1121.477(1.19, 1.84)< 0.001
子女0.5200.487
父母0.0100.034
儿媳/女婿0.0680.042
兄弟姐妹0.0470.034
其他0.0770.007
是否为独生子女是0.4870.6100.1770.2871.194(0.68, 2.09)0.537
否0.5130.390
文化程度小学及以下0.0370.0650.3460.1631.413(1.03, 1.95)0.034
初中0.1830.339
高中0.2400.266
大学及以上0.5400.329
就业状况在业0.3470.4340.0860.2841.090(0.62, 1.90)0.762
无业0.6530.566
家庭人均收入(元)<2 0000.1410.2720.2130.1121.237(0.99, 1.54)0.058
2 000~3 9990.2230.235
4 000~5 9990.1760.132
≥6 0000.4610.361
平均每天照顾时间（h）≤ 60.3700.155-0.2970.1850.743(0.52, 1.07)0.108
7~120.2060.374
>120.4250.471
), ArticleFig(id=1241023867582468342, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023858623435480, language=CN, label=表3, caption=

两组被试在预测变量上的描述性数据及差异性检验结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量分类轻度照顾者负担组
(n=103)		中重度照顾者负担组
(n=264)		βSEOR(95%CI)P
性别女0.3280.4800.9670.2842.630(1.51, 4.59)0.001
男0.6720.520
年龄(岁)19~350.3040.1870.1090.1381.115(0.85, 1.46)0.428
36~430.2310.243
44~520.2220.296
≥530.2420.273
与患者的关系配偶0.2780.3960.3900.1121.477(1.19, 1.84)< 0.001
子女0.5200.487
父母0.0100.034
儿媳/女婿0.0680.042
兄弟姐妹0.0470.034
其他0.0770.007
是否为独生子女是0.4870.6100.1770.2871.194(0.68, 2.09)0.537
否0.5130.390
文化程度小学及以下0.0370.0650.3460.1631.413(1.03, 1.95)0.034
初中0.1830.339
高中0.2400.266
大学及以上0.5400.329
就业状况在业0.3470.4340.0860.2841.090(0.62, 1.90)0.762
无业0.6530.566
家庭人均收入(元)<2 0000.1410.2720.2130.1121.237(0.99, 1.54)0.058
2 000~3 9990.2230.235
4 000~5 9990.1760.132
≥6 0000.4610.361
平均每天照顾时间（h）≤ 60.3700.155-0.2970.1850.743(0.52, 1.07)0.108
7~120.2060.374
>120.4250.471
), ArticleFig(id=1241023867674743040, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023858623435480, language=EN, label=Table 4, caption=

Test results of differences in outcome variables between the two subjects groups

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变量轻度照顾者负担(n=103)中重度照顾者负担(n=264)χ2P
SE SE
家庭韧性77.9200.89175.4100.5825.3330.021
个人韧性29.6470.50026.1890.33531.687<0.001
照顾能力6.6110.5829.2120.38213.391<0.001
), ArticleFig(id=1241023867800572167, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023858623435480, language=CN, label=表4, caption=

两组被试在结果变量上的差异性检验结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量轻度照顾者负担(n=103)中重度照顾者负担(n=264)χ2P
SE SE
家庭韧性77.9200.89175.4100.5825.3330.021
个人韧性29.6470.50026.1890.33531.687<0.001
照顾能力6.6110.5829.2120.38213.391<0.001
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癌症患者家庭主要照顾者负担潜在剖面及相关因素分析
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黄维奇 , 黄诗颖 , 李晗琦 , 郑冬兰 , 刘欢
现代预防医学 | 卫生政策与管理 2025,52(2): 297-302
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现代预防医学 | 卫生政策与管理 2025, 52(2): 297-302
癌症患者家庭主要照顾者负担潜在剖面及相关因素分析
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黄维奇, 黄诗颖, 李晗琦, 郑冬兰, 刘欢
作者信息
  • 哈尔滨医科大学卫生管理学院，黑龙江　哈尔滨　150081

    • 黄维奇（1999—），男，博士在读，研究方向：卫生应急、健康政策

通讯作者:

刘欢，E-mail：
Analysis of latent profiles and related factors for primary caregivers burden in families with cancer patients
Wei-qi HUANG, Shi-ying HUANG, Han-qi LI, Dong-lan ZHENG, Huan LIU
Affiliations
  • School of Health Management, Harbin Medical University, Harbin, Heilongjiang 150081, China
出版时间: 2025-01-25 doi: 10.20043/j.cnki.MPM.202409047
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摘要
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目的

本研究旨在探究癌症患者家庭主要照顾者负担的潜在类别及其潜在相关因素，为采取更具针对性的政策干预措施提供科学依据。

方法

研究于2023年2月—4月采用方便抽样选取哈尔滨医科大学附属第三医院癌症患者家庭主要照顾者作为调查对象开展问卷调查，利用潜在剖面分析探索癌症患者家庭照顾者负担的潜在类别，采用R3STEP法的多项式logistic回归分析探讨人口学变量与照顾负担在类别的不同关联，使用修正的BCH 法验证照顾负担的不同潜在类别对家庭韧性、照顾者个人韧性及照顾能力的差异性。

结果

研究共纳入367名参与者，其照顾负担分为2个类别，分别为 “轻度照顾者负担组”和“中重度照顾者负担组”。“中重度照顾者负担”的受访者多以女性、高学历、配偶和子女为主要特征。不同潜在类别的家庭照顾者负担剖面，在家庭韧性（χ2=5.333，P=0.021）、个人韧性（χ2=31.687，P<0.001）、照顾能力（χ2=13.391，P<0.001）上的差异具有统计学意义。

结论

癌症患者家庭主要照顾者负担存在异质性亚组，政策制定者应实施有针对性的干预措施，以降低癌症患者家庭主要照顾者负担，进而改善其个人与家庭韧性及照顾能力水平。

癌症  /  家庭主要照顾者  /  照顾负担  /  潜在剖面分析
Objective

To explore the potential categories of primary caregiver burden in families of cancer patients and their potential related factors, and to provide scientific basis for more targeted policy interventions.

Methods

From February to April 2023, we conducted a questionnaire survey among the primary family caregivers of cancer patients at the Third Affiliated Hospital of Harbin Medical University using convenience sampling. Latent profile analysis was employed to identify potential categories of caregiver burden. The modified BCH method was used to assess the differences in family resilience, individual resilience, and caregiving ability across different burden categories.

Results

A total of 367 participants were included in the study, and their caregiving burden was divided into two categories, named "mild caregiver burden group" and "moderate and severe caregiver burden group". The respondents of "moderate to heavy caregiver burden" were mostly female who were highly educated and had spouse and children. Different potential categories of family caregiver burden profiles showed statistically significant differences in family resilience (χ2=5.333，P=0.021), individual resilience (χ2=31.687，P<0.001), and caregiving ability (χ2=13.391，P<0.001).

Conclusion

There are heterogeneous subgroups of primary caregiver burden in families of cancer patients, and policy makers should implement targeted interventions to reduce the burden of primary caregivers for families with cancer patients, and to improve their personal and family resilience and caring abilities.

Cancer  /  Primary family caregiver  /  Caregiving burden  /  Latent profile analysis
黄维奇, 黄诗颖, 李晗琦, 郑冬兰, 刘欢. 癌症患者家庭主要照顾者负担潜在剖面及相关因素分析. 现代预防医学, 2025 , 52 (2) : 297 -302 . DOI: 10.20043/j.cnki.MPM.202409047
Wei-qi HUANG, Shi-ying HUANG, Han-qi LI, Dong-lan ZHENG, Huan LIU. Analysis of latent profiles and related factors for primary caregivers burden in families with cancer patients[J]. Modern Preventive Medicine, 2025 , 52 (2) : 297 -302 . DOI: 10.20043/j.cnki.MPM.202409047
正文
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中国已然成为全球癌症负担最重国家之一[1]。癌症在给患者带来巨大病痛折磨的同时，也给患者家庭尤其是家庭主要照顾者带来沉重负担[2]。既往针对癌症患者家庭照顾者负担测量的研究较为有限，多使用非特异性工具[3-4]，普遍未考虑到癌症患者家庭主要照顾者的潜在分类特征[5]，忽略了个体间的异质性。有研究指出，长时间繁重的照顾工作所催生出的包含经济、身体、心理和社会等多维度负担会极大冲击照顾者的承受与应对能力，降低其个人韧性[6]。同时，面对沉重的负担，往往需要调动整个家庭的资源来抵抗逆境并从中恢复，即家庭韧性[7]。此外，照顾能力通常被视为一种完成照顾任务的多维度综合性能力[8]。在缺乏指导或无事先准备的情况下，沉重照顾负担势必会进一步挤占照顾者提升其照顾能力所需的各类资源。然而，少有学者关注到癌症患者家庭主要照顾者负担与家庭韧性、个人韧性和照顾能力之间的潜在关系。
本研究旨在使用特异性测量工具，探究癌症患者家庭主要照顾者负担的潜在类别及其特征差异。同时将照顾者的家庭韧性、个人韧性、照顾能力，以及社会人口学因素纳入模型，以探究其与癌症患者家庭主要照顾者负担潜在类别的关联。
1　对象与方法
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1.1　研究对象
本研究采用方便抽样，于2023年2月—2023年4月，选取哈尔滨医科大学附属肿瘤医院癌症患者家庭主要照顾者作为调查对象。在调研开始前，招募2名硕士研究生作为调查员，经项目负责人展开系统培训后负责联系受访者，研究遵循自愿和匿名的原则，在征得受访者知情同意后开展面对面调查。问卷调查研究对象纳入标准：(1)年龄>18岁；(2)照顾者承担癌症患者主要照顾责任（临时照顾患者的亲属和朋友以及提供有偿照顾服务的护工不在本研究调查范围）；(3)愿意接受本次调查。在调查过程中，调查员仅逐字阅读问卷项目，而不提供任何进一步的解释，调查过程持续15~20 min。每份问卷完成后，调查员立即审核问卷，并邀请参与者补充填写任何遗漏的项目。研究最终收回问卷402份。剔除信息不完整的问卷后共获有效问卷367份，有效率为91.2%。研究已获哈尔滨医科大学伦理委员会批准。
1.2　研究工具
1.2.1　癌症患者家庭主要照顾者一般资料
一般社会人口学资料包括年龄、性别、与患者关系、是否为独生子女、文化程度、就业状况、家庭人均月收入和平均每天照顾时间。由于年龄这一连续变量不符合正态分布，其中位数为36岁，四分位数分别为44岁和53岁。研究将其划分为四个区间：19~35岁、36~43岁、44~52岁和53岁及以上。
1.2.2　癌症患者家庭主要照顾者负担量表
使用课题组前期开发的癌症患者家庭主要照顾者负担的特异性量表来衡量受访者照顾负担水平。量表共21个条目，各条目均采用Likert 5级评分法（0=没有，4=总是），满分84分，得分越高表明癌症患者家庭主要照顾者负担越重。在本研究中，该量表Cronbach α=0.859，信度良好。
1.2.3　Connor-Davidson个人韧性量表
采用中文版Connor-Davidson个人韧性量表[9]评估癌症患者主要照顾者个人韧性，满分40分，得分越高表明照顾者个人韧性越强。该量表在既往针对癌症患者家庭主要照顾者群体的研究中得到过验证[10]。在本研究中，该量表Cronbach α=0.867，信度良好。
1.2.4　家庭照顾者照顾能力量表
Lee等人[11]编制的家庭照顾者照顾能力量表，用以测量癌症患者家庭主要照顾者照顾能力。量表共25个条目，满分50分，得分越高表明照顾者照顾能力越差。该量表的可靠性在既往针对癌症患者家庭主要照顾者群体研究中得到验证[12]，在本研究中也表现出了良好的信度（Cronbach α=0.807）。
1.2.5　家庭复原力问卷
研究采用卜彤等人[13]编制的契合中国文化特点的家庭复原力问卷评估家庭韧性。问卷共20个条目，满分100分，得分越高表明受访者家庭韧性越强。在既往针对癌症患者群体的研究中，家庭复原力问卷表现出了良好的信度[14]，这与本研究相一致（Cronbach α=0.862）。
1.3　统计分析
研究利用SPSS 26.0进行共同方法偏差检验和描述性统计分析。Mplus 8.3用以开展LPA。AIC、BIC和aBIC取值越低，Entropy越接近于1，正确归类程度越高。基于Bootstrap似然比检验 (bootstrap likelihood ratio test, BLRT)和LMR(Lo-Mendell-Rubin)检验P<0.05时，代表k类别模型显著优于k-1类别模型[15]。使用R3STEP添加人口学因素作为预测变量，构建回归混合模型并进行后续多项式回归分析，并采用修正的BCH法添加“家庭韧性”、“心理韧性”和“照顾能力”作为结果变量，考察不同癌症患者家庭主要照顾者负担潜在类别与各相关因素及各连续结果变量之间的差异性。
2　结果
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2.1　共同方法偏差控制和检验
通过采用现场调研、匿名调查等手段控制共同方法偏差，采用Harman单因素检验对可能存在的共同方法偏差进行检验。结果显示，有5个因子特征根大于1，最大因子解释变异量为28.53%（<40%），因此，本研究不存在严重的共同方法偏差问题。
2.2　一般资料分析
家庭主要照顾者年龄多集中在44~52岁(27.5%)，近五成家庭主要照顾者是患者子女，约40%的家庭主要照顾者是独生子女，将近一半照顾者每天照顾患者平均时间超过12 h（见表1）。
2.3　癌症患者家庭主要照顾者负担的潜在剖面分析
对癌症患者家庭主要照顾者负担进行潜在剖面分析，分类数从1分类开始依次增加，模型拟合指标见表2。所有分类的熵值均在0.9以上，随着分类数的增多，AIC、BIC与aBIC值逐渐降低，当保留2个潜在类别时，LMR和BLRT均有统计学意义，当保留3个潜在类别时，P(LMR)>0.05，提示此模型适配不符。通过绘制样本校正的贝叶斯信息准则变化趋势图，可以看出2类模型后aBIC的图形趋于平缓（见图1）。综合考虑类别的模型拟合度、简洁性和可解释性，研究选择2类模型作为当前样本的最优模型。
进一步绘制两个类别在癌症患者家庭主要照顾者负担量表21个条目上的得分分布情况（见图2）。类别1在每个条目上的得分均明显低于类别2。研究将类别1（n=103，28.5%）命名为“轻度照顾者负担组”，类别2（n=264，71.5%）命名为“中重度照顾者负担组”。
2.4　人口学变量对癌症患者家庭主要照顾者负担潜类别的影响
研究采用R3STEP命令进行多项式logistic回归分析。由表3可知，癌症患者家庭照顾者的性别、与患者的关系和文化程度在癌症患者家庭主要照顾者负担的两个潜在类别上的差异具有统计学意义(P<0.05)，即男性、与患者是配偶或子女关系、大学及以上学历的照顾者表现出较低的照顾负担。
2.5　连续变量的差异性检验结果
不同潜在类别的家庭照顾者负担剖面在家庭韧性、个人韧性、照顾能力上的差异均存在统计学意义（P<0.05）。具体而言，轻度照顾者负担组具备较高的家庭韧性（，SE =0.891）和个人韧性（，SE=0.500），而中重度照顾者负担组具备较高的照顾能力（，SE=0.382）（见表4）。
3　讨论
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癌症患者家庭主要照顾者的照顾负担存在明显的群体异质性，可分为轻度和中重度照顾者负担组两个潜在类别，照顾者普遍具有较高水平的照顾负担，且经济负担差距最为突出。一方面，癌症患者家庭面临高昂诊疗和药品费用所致的经济负担。另一方面，受困于家庭经济水平，照顾者难以聘请专业照顾人员提供照顾支持。尽管我国已在40多个城市开展长期护理保险的试点工作[16]。但目前参保者多为职工医保人群。政府应进一步完善医保目录动态调整机制及药品集中带量采购政策，不断增补抗癌药物并引导药物降价。同时逐步扩大长期护理保险覆盖范围并探索多渠道筹资机制。
不同类别的照顾负担在照顾者个人韧性和家庭韧性上体现出的差异具有统计学意义，与既往研究结果一致[17-18]。医学技术的进步延长了癌症患者的存活周期，患者需更长期、反复的治疗与照护。照顾者往往需投入大量的时间、财力、体力和精力，极易产生焦虑、抑郁等心理问题，进而对其心理韧性产生影响[18]。此外，长期的照顾负担还可能导致照顾者家庭出现“裂痕”。患癌家庭往往会寻求安宁疗护服务以获得“喘息”机会。我国近年来逐步重视为慢性病或失能患者家庭提供多形式的安宁疗护服务支持[19]。但相关机构总量少且多集中在经济发达地区，相关服务内容也尚未纳入医保目录[20]。研究建议，政府和医疗机构应协同提供广泛的支持机制，为家庭照顾者提供长期的心理咨询与疏导。同时，进一步推动安宁疗护纳入医保范围，减少癌症患者家庭的负担与压力。
值得注意的是，负担越重的照顾者其照顾能力水平往往越低。对于高照顾负担的家庭主要照顾者来说，多维度负担问题势必会占用其学习掌握专业照顾能力的时间与精力。同时，沉重的负面情绪也势必会影响其处理与家庭成员之间关系的能力。政府应积极动员社区基层医疗卫生机构开展有关疾病和护理知识培训和指导，并通过定期随访了解癌症患者病情以及照顾者的相关护理需求。
需要承认的是本研究存在一定不足和局限性。首先，研究类型为横断面研究，未能建立变量间的因果关系。其次，研究采用方便抽样且仅在单中心展开了调查，可能无法反映我国癌症患者家庭主要照顾者负担整体情况。最后，研究纳入的相关因素对癌症患者家庭主要照顾者负担不同类别的影响解释有限，未来需扩大样本量和调查范围，并纳入更多相关因素进行更为深入研究。
基金
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  • 国家自然科学基金项目(72304079)
  • 黑龙江省博士后(LBH-Z21181)
文献
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参考文献 引证文献
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2025年第52卷第2期
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doi: 10.20043/j.cnki.MPM.202409047
  • 接收时间：2024-09-03
  • 首发时间：2026-03-18
  • 出版时间：2025-01-25
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  • 收稿日期：2024-09-03
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国家自然科学基金项目(72304079)
黑龙江省博士后(LBH-Z21181)
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    哈尔滨医科大学卫生管理学院，黑龙江　哈尔滨　150081

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2种不同金属材料的力学参数
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species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
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species		 占总种数比例
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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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