142 related articles for article (PubMed ID: 33156810)
1. eHealth Practices in Cancer Survivors With BMI in Overweight or Obese Categories: Latent Class Analysis Study.
Lin AW; Baik SH; Aaby D; Tello L; Linville T; Alshurafa N; Spring B
JMIR Cancer; 2020 Dec; 6(2):e24137. PubMed ID: 33156810
[TBL] [Abstract][Full Text] [Related]
2. Predictors of eHealth usage: insights on the digital divide from the Health Information National Trends Survey 2012.
Kontos E; Blake KD; Chou WY; Prestin A
J Med Internet Res; 2014 Jul; 16(7):e172. PubMed ID: 25048379
[TBL] [Abstract][Full Text] [Related]
3. Factors Associated With Online Patient-Provider Communications Among Cancer Survivors in the United States During COVID-19: Cross-sectional Study.
Kim J; Linos E; Fishman DA; Dove MS; Hoch JS; Keegan TH
JMIR Cancer; 2023 May; 9():e44339. PubMed ID: 37074951
[TBL] [Abstract][Full Text] [Related]
4. Use of eHealth and mHealth technology by persons with multiple sclerosis.
Marrie RA; Leung S; Tyry T; Cutter GR; Fox R; Salter A
Mult Scler Relat Disord; 2019 Jan; 27():13-19. PubMed ID: 30296732
[TBL] [Abstract][Full Text] [Related]
5. Using Latent Class Growth Modeling to Examine Longitudinal Patterns of Body Mass Index Change from Adolescence to Adulthood.
Becnel JN; Williams AL
J Acad Nutr Diet; 2019 Nov; 119(11):1875-1881. PubMed ID: 31302035
[TBL] [Abstract][Full Text] [Related]
6. Impact of the Method of Delivering Electronic Health Behavior Change Interventions in Survivors of Cancer on Engagement, Health Behaviors, and Health Outcomes: Systematic Review and Meta-Analysis.
Furness K; Sarkies MN; Huggins CE; Croagh D; Haines TP
J Med Internet Res; 2020 Jun; 22(6):e16112. PubMed ID: 32574147
[TBL] [Abstract][Full Text] [Related]
7. Modeling and Predicting Outcomes of eHealth Usage by European Physicians: Multidimensional Approach from a Survey of 9196 General Practitioners.
Torrent-Sellens J; Díaz-Chao Á; Soler-Ramos I; Saigí-Rubió F
J Med Internet Res; 2018 Oct; 20(10):e279. PubMed ID: 30348628
[TBL] [Abstract][Full Text] [Related]
8. eHealth literacy and Web 2.0 health information seeking behaviors among baby boomers and older adults.
Tennant B; Stellefson M; Dodd V; Chaney B; Chaney D; Paige S; Alber J
J Med Internet Res; 2015 Mar; 17(3):e70. PubMed ID: 25783036
[TBL] [Abstract][Full Text] [Related]
9. Modelling and Predicting eHealth Usage in Europe: A Multidimensional Approach From an Online Survey of 13,000 European Union Internet Users.
Torrent-Sellens J; Díaz-Chao Á; Soler-Ramos I; Saigí-Rubió F
J Med Internet Res; 2016 Jul; 18(7):e188. PubMed ID: 27450189
[TBL] [Abstract][Full Text] [Related]
10. Patterns of digital health access and use among US adults: A latent class analysis.
Hegeman P; Vader D; Kamke K; El-Toukhy S
Res Sq; 2024 Jan; ():. PubMed ID: 38352382
[TBL] [Abstract][Full Text] [Related]
11. Overweight/obesity and weight-related treatment among patients in U.S. federally supported health centers.
Lebrun LA; Chowdhury J; Sripipatana A; Nair S; Tomoyasu N; Ngo-Metzger Q
Obes Res Clin Pract; 2013; 7(5):e377-90. PubMed ID: 24304480
[TBL] [Abstract][Full Text] [Related]
12. Examining Internet and eHealth Practices and Preferences: Survey Study of Australian Older Adults With Subjective Memory Complaints, Mild Cognitive Impairment, or Dementia.
LaMonica HM; English A; Hickie IB; Ip J; Ireland C; West S; Shaw T; Mowszowski L; Glozier N; Duffy S; Gibson AA; Naismith SL
J Med Internet Res; 2017 Oct; 19(10):e358. PubMed ID: 29070481
[TBL] [Abstract][Full Text] [Related]
13. Prevalence and Factors Influencing Use of Internet and Electronic Health Resources by Middle-Aged and Older Adults in a US Health Plan Population: Cross-Sectional Survey Study.
Crouch E; Gordon NP
JMIR Aging; 2019 Mar; 2(1):e11451. PubMed ID: 31518256
[TBL] [Abstract][Full Text] [Related]
14. Parent-Focused Childhood and Adolescent Overweight and Obesity eHealth Interventions: A Systematic Review and Meta-Analysis.
Hammersley ML; Jones RA; Okely AD
J Med Internet Res; 2016 Jul; 18(7):e203. PubMed ID: 27443862
[TBL] [Abstract][Full Text] [Related]
15. Latent class analysis of eHealth behaviors among adults with epilepsy.
Kee D; Jetté N; Blank LJ; Kummer BR; Mazumdar M; Agarwal P
Epilepsia; 2023 Feb; 64(2):479-499. PubMed ID: 36484565
[TBL] [Abstract][Full Text] [Related]
16. Weight loss motivations: a latent class analysis approach.
Lemon SC; Schneider KL; Wang ML; Liu Q; Magner R; Estabrook B; Druker S; Pbert L
Am J Health Behav; 2014 Jul; 38(4):605-13. PubMed ID: 24636123
[TBL] [Abstract][Full Text] [Related]
17. Preferences for Health Information Technologies Among US Adults: Analysis of the Health Information National Trends Survey.
Asan O; Cooper Ii F; Nagavally S; Walker RJ; Williams JS; Ozieh MN; Egede LE
J Med Internet Res; 2018 Oct; 20(10):e277. PubMed ID: 30341048
[TBL] [Abstract][Full Text] [Related]
18. Sociodemographic and Health Correlates of Multiple Health Behavior Adherence among Cancer Survivors: A Latent Class Analysis.
Fong AJ; Llanos AAM; Ashrafi A; Zeinomar N; Chokshi S; Bandera EV; Devine KA; Hudson SV; Qin B; O'Malley D; Paddock LE; Stroup AM; Evens AM; Manne SL
Nutrients; 2023 May; 15(10):. PubMed ID: 37242237
[TBL] [Abstract][Full Text] [Related]
19. Health behaviors, obesity, and marital status among cancer survivors: a MEPS study.
Song L; Guan T; Guo P; Tan X; Bryant AL; Wood WA; Sung AD; Kent EE; Keyserling TC
J Cancer Surviv; 2023 Apr; 17(2):499-508. PubMed ID: 36409440
[TBL] [Abstract][Full Text] [Related]
20.
; ; . PubMed ID:
[No Abstract] [Full Text] [Related]
[Next] [New Search]
