Abstract PO-016: A latent class analysis of communication patterns between Hispanic and non-Hispanic childhood cancer survivors, parents, and medical providers

2022 ◽  
Author(s):  
Carol Y. Ochoa ◽  
Junhan Cho ◽  
Kimberly A. Miller ◽  
Lourdes Baezconde-Garbanati ◽  
Randall Y. Chan ◽  
...  
Keyword(s):  
Cancer Survivors ◽  
Latent Class Analysis ◽  
Childhood Cancer ◽  
Latent Class ◽  
Childhood Cancer Survivors ◽  
Communication Patterns ◽  
Class Analysis ◽  
Medical Providers

scholarly journals Acculturation, Mental Health, and Quality of Life am ong Hispanic Childhood Cancer Survivors: A Latent Class Analysis

2018 ◽  
Vol 28 (1) ◽  
pp. 55 ◽  
Author(s):  
Jessica Tobin ◽  
Kimberly A. Miller ◽  
Lourdes Baezconde-Garbanati ◽  
Jennifer B. Unger ◽  
Ann S. Hamilton ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Depressive Symptoms ◽  
Cancer Survivors ◽  
Latent Class Analysis ◽  
Childhood Cancer ◽  
High Probability ◽  
Latent Class ◽  
Childhood Cancer Survivors ◽  
Class Analysis

<p class="Pa7"><strong>Objective: </strong>Acculturation appears to be an important aspect of the association between ethnicity and disease, but it has not been explored in depth among childhood cancer survivors (CCS). The purpose of our study was to identify distinct acculturative profiles among Hispanic CCS and to assess dif­ferences in quality of life and depressive symptoms.</p><p class="Pa7"><strong>Design: </strong>Latent class analysis was used to identify distinct acculturative profiles using 9 indicator items reflecting Hispanic and An­glo cultural orientation. Multinomial logistic regression was performed to explore differ­ences in depressive symptoms and quality of life between acculturation classes.</p><p class="Pa7"><strong>Setting and Participants: </strong>Participants were diagnosed in Los Angeles County, Califor­nia, USA between 2000-2007 and were recruited for the study in 2009.</p><p class="Pa7"><strong>Main Outcome Measures: </strong>Center for Epi­demiologic Studies depression scale and the PedsQL 4.0 quality of life scale.</p><p class="Pa7"><strong>Results: </strong>Three distinct acculturation classes emerged. All classes displayed a high prob­ability of endorsing all Anglo orientation items. One class additionally demonstrated a high probability of endorsing all Hispanic orientation items and was labeled bicultural (40%); another demonstrated low probabil­ity of endorsing the Hispanic items so was labeled assimilated (32%); and the last dem­onstrated a high probability of endorsing only the Hispanic items related to language use and was labeled linguistically Hispanic/ culturally Anglo (LH) (28%).</p><p class="Pa8"><strong>Conclusions: </strong>The assimilated group had significantly more depressive symptoms and lower quality of life than the other two groups. This may indicate that loss of the Hispanic culture may be associated with poorer psychosocial health among CCS.</p><p class="Pa8"><em>Ethn Dis. </em>2018;28(1):55-60; doi:10.18865/ ed.28.1.55.</p>

scholarly journals Patterns of comorbidities in hospitalised cancer survivors for palliative care and associated in-hospital mortality risk: A latent class analysis of a statewide all-inclusive inpatient data

2019 ◽  
Vol 33 (10) ◽  
pp. 1272-1281 ◽  
Author(s):  
Lan Luo ◽  
Wei Du ◽  
Shanley Chong ◽  
Huibo Ji ◽  
Nicholas Glasgow
Keyword(s):  
Risk Factors ◽  
Palliative Care ◽  
Hospital Mortality ◽  
Cancer Survivors ◽  
Latent Class Analysis ◽  
Cancer Patients ◽  
Mortality Risk ◽  
Latent Class ◽  
Class Analysis ◽  
Hospital Deaths

Background: At the end of life, cancer survivors often experience exacerbations of complex comorbidities requiring acute hospital care. Few studies consider comorbidity patterns in cancer survivors receiving palliative care. Aim: To identify patterns of comorbidities in cancer patients receiving palliative care and factors associated with in-hospital mortality risk. Design, Setting/Participants: New South Wales Admitted Patient Data Collection data were used for this retrospective cohort study with 47,265 cancer patients receiving palliative care during the period financial year 2001–2013. A latent class analysis was used to identify complex comorbidity patterns. A regression mixture model was used to identify risk factors in relation to in-hospital mortality in different latent classes. Results: Five comorbidity patterns were identified: ‘multiple comorbidities and symptoms’ (comprising 9.1% of the study population), ‘more symptoms’ (27.1%), ‘few comorbidities’ (39.4%), ‘genitourinary and infection’ (8.7%), and ‘circulatory and endocrine’ (15.6%). In-hospital mortality was the highest for ‘few comorbidities’ group and the lowest for ‘more symptoms’ group. Severe comorbidities were associated with elevated mortality in patients from ‘multiple comorbidities and symptoms’, ‘more symptoms’, and ‘genitourinary and infection’ groups. Intensive care was associated with a 37% increased risk of in-hospital deaths in those presenting with more ‘multiple comorbidities and symptoms’, but with a 22% risk reduction in those presenting with ‘more symptoms’. Conclusion: Identification of comorbidity patterns and risk factors for in-hospital deaths in cancer patients provides an avenue to further develop appropriate palliative care strategies aimed at improving outcomes in cancer survivors.

scholarly journals Heterogeneity in quality of life of long‐term colon cancer survivors: a latent class analysis of the population‐based PROFILES registry

2020 ◽  
Author(s):  
Felix J. Clouth ◽  
Arturo Moncada‐Torres ◽  
Gijs Geleijnse ◽  
Floortje Mols ◽  
Felice N. Erning ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Colon Cancer ◽  
Cancer Survivors ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Population Based ◽  
Class Analysis

scholarly journals eHealth Practices in Cancer Survivors With BMI in Overweight or Obese Categories: Latent Class Analysis Study (Preprint)

2020 ◽  
Author(s):  
Annie Wen Lin ◽  
Sharon H Baik ◽  
David Aaby ◽  
Leslie Tello ◽  
Twila Linville ◽  
...  
Keyword(s):  
Cancer Survivors ◽  
Latent Class Analysis ◽  
Health Information ◽  
Latent Class ◽  
Electronic Device ◽  
Ethnic Disparities ◽  
Sociodemographic Characteristics ◽  
Class Analysis ◽  
Class Membership ◽  
Health Related

BACKGROUND eHealth technologies have been found to facilitate health-promoting practices among cancer survivors with BMI in overweight or obese categories; however, little is known about their engagement with eHealth to promote weight management and facilitate patient-clinician communication. OBJECTIVE The objective of this study was to determine whether eHealth use was associated with sociodemographic characteristics, as well as medical history and experiences (ie, patient-related factors) among cancer survivors with BMI in overweight or obese categories. METHODS Data were analyzed from a nationally representative cross-sectional survey (National Cancer Institute’s Health Information National Trends Survey). Latent class analysis was used to derive distinct classes among cancer survivors based on sociodemographic characteristics, medical attributes, and medical experiences. Logistic regression was used to examine whether class membership was associated with different eHealth practices. RESULTS Three distinct classes of cancer survivors with BMI in overweight or obese categories emerged: younger with no comorbidities, younger with comorbidities, and older with comorbidities. Compared to the other classes, the younger with comorbidities class had the highest probability of identifying as female (73%) and Hispanic (46%) and feeling that clinicians did not address their concerns (75%). The older with comorbidities class was 6.5 times more likely than the younger with comorbidities class to share eHealth data with a clinician (odds ratio [OR] 6.53, 95% CI 1.08-39.43). In contrast, the younger with no comorbidities class had a higher likelihood of using a computer to look for health information (OR 1.93, 95% CI 1.10-3.38), using an electronic device to track progress toward a health-related goal (OR 2.02, 95% CI 1.08-3.79), and using the internet to watch health-related YouTube videos (OR 2.70, 95% CI 1.52-4.81) than the older with comorbidities class. CONCLUSIONS Class membership was associated with different patterns of eHealth engagement, indicating the importance of tailored digital strategies for delivering effective care. Future eHealth weight loss interventions should investigate strategies to engage younger cancer survivors with comorbidities and address racial and ethnic disparities in eHealth use.

scholarly journals eHealth Practices in Cancer Survivors With BMI in Overweight or Obese Categories: Latent Class Analysis Study

JMIR Cancer ◽  
10.2196/24137 ◽  
2020 ◽  
Vol 6 (2) ◽  
pp. e24137
Author(s):  
Annie Wen Lin ◽  
Sharon H Baik ◽  
David Aaby ◽  
Leslie Tello ◽  
Twila Linville ◽  
...  
Keyword(s):  
Cancer Survivors ◽  
Latent Class Analysis ◽  
Health Information ◽  
Latent Class ◽  
Electronic Device ◽  
Ethnic Disparities ◽  
Sociodemographic Characteristics ◽  
Class Analysis ◽  
Class Membership ◽  
Health Related

Background eHealth technologies have been found to facilitate health-promoting practices among cancer survivors with BMI in overweight or obese categories; however, little is known about their engagement with eHealth to promote weight management and facilitate patient-clinician communication. Objective The objective of this study was to determine whether eHealth use was associated with sociodemographic characteristics, as well as medical history and experiences (ie, patient-related factors) among cancer survivors with BMI in overweight or obese categories. Methods Data were analyzed from a nationally representative cross-sectional survey (National Cancer Institute’s Health Information National Trends Survey). Latent class analysis was used to derive distinct classes among cancer survivors based on sociodemographic characteristics, medical attributes, and medical experiences. Logistic regression was used to examine whether class membership was associated with different eHealth practices. Results Three distinct classes of cancer survivors with BMI in overweight or obese categories emerged: younger with no comorbidities, younger with comorbidities, and older with comorbidities. Compared to the other classes, the younger with comorbidities class had the highest probability of identifying as female (73%) and Hispanic (46%) and feeling that clinicians did not address their concerns (75%). The older with comorbidities class was 6.5 times more likely than the younger with comorbidities class to share eHealth data with a clinician (odds ratio [OR] 6.53, 95% CI 1.08-39.43). In contrast, the younger with no comorbidities class had a higher likelihood of using a computer to look for health information (OR 1.93, 95% CI 1.10-3.38), using an electronic device to track progress toward a health-related goal (OR 2.02, 95% CI 1.08-3.79), and using the internet to watch health-related YouTube videos (OR 2.70, 95% CI 1.52-4.81) than the older with comorbidities class. Conclusions Class membership was associated with different patterns of eHealth engagement, indicating the importance of tailored digital strategies for delivering effective care. Future eHealth weight loss interventions should investigate strategies to engage younger cancer survivors with comorbidities and address racial and ethnic disparities in eHealth use.

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