Abstract：
OBJECTIVE: Our study explores cancer care disruption among different demographic subgroups. It also investigates these disruptions\' impacts on cancer survivors\' mental and physical well-being.
METHODS: Pooled cross-sectional survey data.
METHODS: Health Information Trends Survey for Surveillance Epidemiology and End Results, HINTS-SEER.
METHODS: n = 1234 cancer survivors participated in the study and completed the survey.
METHODS: Outcome variables were treatment disruption in cancer care, mental health and physical health perceptions, age, race, education, income, and sexual orientation.
METHODS: Multiple imputations were used to address missing data. Descriptive statistics were conducted to understand the perceptions of care disruption. Partial least squares structural equation models were employed for data analysis, adjusted for socio-demographics.
RESULTS: COVID-19 impacted cancer treatment and follow-up appointments (69.45%), routine cancer screening (60.70%), and treatment plans (73.58%), especially among elderly patients. It changed the interactions with health care providers (HCP) for 28.03% of the participants. Older adults were 2.33 times more likely to experience treatment appointment disruptions. People who thought their contact with their doctors changed during COVID-19 were more likely to be older adults (65 or more) (OR = 3.85, P = .011), white (OR >1, P = .002), and with higher income (OR = 1.81, P = .002). The changes to cancer treatment and follow-up medical appointments negatively impacted the well-being of the patients (mental: β = -.006, P = .043; physical: β = -.001, P = .006), routine screening and preventative care visits (mental: β = -.029, P = .031; physical: β = -.003, P = .008), and cancer treatment plans (mental: β = -.044, P = .024; physical: β = -.021, P = .040).
CONCLUSIONS: Our findings underscore the crucial requirement for implementing focused interventions aimed at alleviating the discrepancies in the accessibility of cancer care across diverse demographic groups, particularly during times of emergency, in order to mitigate any potential disruptions in care.
METHODS: Pooled cross-sectional survey data.
METHODS: Health Information Trends Survey for Surveillance Epidemiology and End Results, HINTS-SEER.
METHODS: n = 1234 cancer survivors participated in the study and completed the survey.
METHODS: Outcome variables were treatment disruption in cancer care, mental health and physical health perceptions, age, race, education, income, and sexual orientation.
METHODS: Multiple imputations were used to address missing data. Descriptive statistics were conducted to understand the perceptions of care disruption. Partial least squares structural equation models were employed for data analysis, adjusted for socio-demographics.
RESULTS: COVID-19 impacted cancer treatment and follow-up appointments (69.45%), routine cancer screening (60.70%), and treatment plans (73.58%), especially among elderly patients. It changed the interactions with health care providers (HCP) for 28.03% of the participants. Older adults were 2.33 times more likely to experience treatment appointment disruptions. People who thought their contact with their doctors changed during COVID-19 were more likely to be older adults (65 or more) (OR = 3.85, P = .011), white (OR >1, P = .002), and with higher income (OR = 1.81, P = .002). The changes to cancer treatment and follow-up medical appointments negatively impacted the well-being of the patients (mental: β = -.006, P = .043; physical: β = -.001, P = .006), routine screening and preventative care visits (mental: β = -.029, P = .031; physical: β = -.003, P = .008), and cancer treatment plans (mental: β = -.044, P = .024; physical: β = -.021, P = .040).
CONCLUSIONS: Our findings underscore the crucial requirement for implementing focused interventions aimed at alleviating the discrepancies in the accessibility of cancer care across diverse demographic groups, particularly during times of emergency, in order to mitigate any potential disruptions in care.
摘要：
目的：我们的研究探讨了不同人口统计学亚组之间的癌症护理中断。它还调查了这些“对癌症幸存者的影响”的精神和身体健康。
方法：汇总横断面调查数据。
方法：用于监测流行病学和最终结果的健康信息趋势调查，HINTS-SEER.
方法：n=1234名癌症幸存者参与了研究并完成了调查。
方法：结果变量是癌症治疗中的治疗中断，心理健康和身体健康观念，年龄,种族,教育,收入,和性取向。
方法：使用多重插补来解决缺失数据。进行了描述性统计以了解对护理中断的看法。采用偏最小二乘结构方程模型进行数据分析，根据社会人口统计进行了调整。
结果：COVID-19影响癌症治疗和随访（69.45%），常规癌症筛查（60.70%），和治疗计划(73.58%)，尤其是老年患者。它改变了28.03％的参与者与医疗保健提供者（HCP）的互动。老年人经历治疗预约中断的可能性是2.33倍。认为在新冠肺炎期间与医生联系发生改变的人更有可能是老年人(65岁或以上)(OR=3.85，P=0.011)，白色（OR>1，P=.002），收入较高(OR=1.81，P=0.002)。癌症治疗和后续医疗预约的变化对患者的健康产生了负面影响（精神：β=-.006，P=.043；身体：β=-.001，P=.006），常规筛查和预防性护理访问（精神：β=-.029，P=.031；身体：β=-.003，P=.008），和癌症治疗计划（精神：β=-.044，P=.024；身体：β=-.021，P=.040）。
结论：我们的研究结果强调了实施重点干预措施的关键要求，目的是减轻不同人口群体在癌症护理可及性方面的差异。特别是在紧急情况下，以减轻护理中的任何潜在中断。
方法：汇总横断面调查数据。
方法：用于监测流行病学和最终结果的健康信息趋势调查，HINTS-SEER.
方法：n=1234名癌症幸存者参与了研究并完成了调查。
方法：结果变量是癌症治疗中的治疗中断，心理健康和身体健康观念，年龄,种族,教育,收入,和性取向。
方法：使用多重插补来解决缺失数据。进行了描述性统计以了解对护理中断的看法。采用偏最小二乘结构方程模型进行数据分析，根据社会人口统计进行了调整。
结果：COVID-19影响癌症治疗和随访（69.45%），常规癌症筛查（60.70%），和治疗计划(73.58%)，尤其是老年患者。它改变了28.03％的参与者与医疗保健提供者（HCP）的互动。老年人经历治疗预约中断的可能性是2.33倍。认为在新冠肺炎期间与医生联系发生改变的人更有可能是老年人(65岁或以上)(OR=3.85，P=0.011)，白色（OR>1，P=.002），收入较高(OR=1.81，P=0.002)。癌症治疗和后续医疗预约的变化对患者的健康产生了负面影响（精神：β=-.006，P=.043；身体：β=-.001，P=.006），常规筛查和预防性护理访问（精神：β=-.029，P=.031；身体：β=-.003，P=.008），和癌症治疗计划（精神：β=-.044，P=.024；身体：β=-.021，P=.040）。
结论：我们的研究结果强调了实施重点干预措施的关键要求，目的是减轻不同人口群体在癌症护理可及性方面的差异。特别是在紧急情况下，以减轻护理中的任何潜在中断。
