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

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. OBJEC...

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Autores principales: Lin, Annie Wen, Baik, Sharon H, Aaby, David, Tello, Leslie, Linville, Twila, Alshurafa, Nabil, Spring, Bonnie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7746487/
https://www.ncbi.nlm.nih.gov/pubmed/33156810
http://dx.doi.org/10.2196/24137
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author Lin, Annie Wen
Baik, Sharon H
Aaby, David
Tello, Leslie
Linville, Twila
Alshurafa, Nabil
Spring, Bonnie
author_facet Lin, Annie Wen
Baik, Sharon H
Aaby, David
Tello, Leslie
Linville, Twila
Alshurafa, Nabil
Spring, Bonnie
author_sort Lin, Annie Wen
collection PubMed
description 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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spelling pubmed-77464872020-12-21 eHealth Practices in Cancer Survivors With BMI in Overweight or Obese Categories: Latent Class Analysis Study Lin, Annie Wen Baik, Sharon H Aaby, David Tello, Leslie Linville, Twila Alshurafa, Nabil Spring, Bonnie JMIR Cancer Original Paper 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. JMIR Publications 2020-12-03 /pmc/articles/PMC7746487/ /pubmed/33156810 http://dx.doi.org/10.2196/24137 Text en ©Annie Wen Lin, Sharon H Baik, David Aaby, Leslie Tello, Twila Linville, Nabil Alshurafa, Bonnie Spring. Originally published in JMIR Cancer (http://cancer.jmir.org), 03.12.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Cancer, is properly cited. The complete bibliographic information, a link to the original publication on http://cancer.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Lin, Annie Wen
Baik, Sharon H
Aaby, David
Tello, Leslie
Linville, Twila
Alshurafa, Nabil
Spring, Bonnie
eHealth Practices in Cancer Survivors With BMI in Overweight or Obese Categories: Latent Class Analysis Study
title eHealth Practices in Cancer Survivors With BMI in Overweight or Obese Categories: Latent Class Analysis Study
title_full eHealth Practices in Cancer Survivors With BMI in Overweight or Obese Categories: Latent Class Analysis Study
title_fullStr eHealth Practices in Cancer Survivors With BMI in Overweight or Obese Categories: Latent Class Analysis Study
title_full_unstemmed eHealth Practices in Cancer Survivors With BMI in Overweight or Obese Categories: Latent Class Analysis Study
title_short eHealth Practices in Cancer Survivors With BMI in Overweight or Obese Categories: Latent Class Analysis Study
title_sort ehealth practices in cancer survivors with bmi in overweight or obese categories: latent class analysis study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7746487/
https://www.ncbi.nlm.nih.gov/pubmed/33156810
http://dx.doi.org/10.2196/24137
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