TY - JOUR
T1 - Latent class analysis of eHealth behaviors among adults with epilepsy
AU - Kee, Dustin
AU - Jetté, Nathalie
AU - Blank, Leah J.
AU - Kummer, Benjamin R.
AU - Mazumdar, Madhu
AU - Agarwal, Parul
N1 - Funding Information:
L.J.B. has received grant support for projects unrelated to this work from the American Epilepsy Society, the Epilepsy Foundation, and the Mount Sinai Claude D. Pepper Older Americans Independence Center (5P30AG028741‐11). N.J. receives grant funding paid to her institution for grants unrelated to this work from NINDS (NIH U24NS107201, NIH IU54NS100064, NIH U24NS113849). She receives an honorarium for her work as an Associate Editor of . B.R.K. has served as a consultant for Atheneum Partners, Gehrson Lehrman Group, Syapse, and AlphaSights. He has received equity ownership for serving on the advisory board of Syntrillo. M.M. receives grant funding paid to her institution for grants unrelated to this work from NCI (P30CA196521, UM1CA121947, CA220491, U24CA224319‐01, DK124165, CA249765, CA195819), NCATS (TR002997), and NIA (AG028741, AG066605, P30AG028741, NR018462, R01AG054540). The other authors do not have any conflicts of interest to disclose. Epilepsia
Funding Information:
N.J. is the Bludhorn Professor of International Medicine at the Icahn School of Medicine at Mount Sinai.
Publisher Copyright:
© 2022 International League Against Epilepsy.
PY - 2023/2
Y1 - 2023/2
N2 - Objective: The objective of this study was to determine the proportions of uptake and factors associated with electronic health (eHealth) behaviors among adults with epilepsy. Methods: The 2013, 2015, and 2017 National Health Interview Surveys were analyzed. We assessed the proportions of use of five domains of eHealth in those with epilepsy: looked up health information on the internet, filled a prescription on the internet, scheduled a medical appointment on the internet, communicated with a health care provider via email, and used chat groups to learn about health topics. Multivariate logistic regressions were conducted to identify factors associated with any eHealth behaviors among those with active epilepsy. Latent class analysis was performed to identify underlying patterns of eHealth activity. Survey participants were classified into three discrete classes: (1) frequent, (2) infrequent, and (3) nonusers of eHealth. Multinomial logistic regression was performed to identify factors associated with frequency of eHealth use. Results: There were 1770 adults with epilepsy, of whom 65.87% had at least one eHealth behavior in the prior year. By domain, 62.61% looked up health information on the internet, 15.81% filled a prescription on the internet, 14.95% scheduled a medical appointment on the internet, 17.20% communicated with a health care provider via email, and 8.27% used chat groups to learn about health topics. Among those with active epilepsy, female sex, more frequent computer usage, and internet usage were associated with any eHealth behavior. Female sex and frequent computer use were associated with frequent eHealth use as compared to nonusers. Significance: A majority of persons with epilepsy were found to use at least one form of eHealth. Various technological and demographic factors were associated with eHealth behaviors. Individuals with lower eHealth behaviors should be provided with targeted interventions that address barriers to the adoption of these technologies.
AB - Objective: The objective of this study was to determine the proportions of uptake and factors associated with electronic health (eHealth) behaviors among adults with epilepsy. Methods: The 2013, 2015, and 2017 National Health Interview Surveys were analyzed. We assessed the proportions of use of five domains of eHealth in those with epilepsy: looked up health information on the internet, filled a prescription on the internet, scheduled a medical appointment on the internet, communicated with a health care provider via email, and used chat groups to learn about health topics. Multivariate logistic regressions were conducted to identify factors associated with any eHealth behaviors among those with active epilepsy. Latent class analysis was performed to identify underlying patterns of eHealth activity. Survey participants were classified into three discrete classes: (1) frequent, (2) infrequent, and (3) nonusers of eHealth. Multinomial logistic regression was performed to identify factors associated with frequency of eHealth use. Results: There were 1770 adults with epilepsy, of whom 65.87% had at least one eHealth behavior in the prior year. By domain, 62.61% looked up health information on the internet, 15.81% filled a prescription on the internet, 14.95% scheduled a medical appointment on the internet, 17.20% communicated with a health care provider via email, and 8.27% used chat groups to learn about health topics. Among those with active epilepsy, female sex, more frequent computer usage, and internet usage were associated with any eHealth behavior. Female sex and frequent computer use were associated with frequent eHealth use as compared to nonusers. Significance: A majority of persons with epilepsy were found to use at least one form of eHealth. Various technological and demographic factors were associated with eHealth behaviors. Individuals with lower eHealth behaviors should be provided with targeted interventions that address barriers to the adoption of these technologies.
KW - COVID-19
KW - eHealth
KW - epilepsy
KW - national survey database
UR - http://www.scopus.com/inward/record.url?scp=85145335621&partnerID=8YFLogxK
U2 - 10.1111/epi.17483
DO - 10.1111/epi.17483
M3 - Article
C2 - 36484565
AN - SCOPUS:85145335621
SN - 0013-9580
VL - 64
SP - 479
EP - 499
JO - Epilepsia
JF - Epilepsia
IS - 2
ER -