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eHealth Literacy: In the Quest of the Contributing Factors

eHealth Literacy: In the Quest of the Contributing Factors

More specifically, the demographic variables of age and education are documented in the studies of Baker et al. [17], Petch et al. [18], Watkins and Xie [19]; while Schwartz et al. [20], Andreasen et al. [21], Rudd et al. [22], and Veenhorf et al. [23], along

Sofia Xesfingi, Athanassios Vozikis

Interact J Med Res 2016;5(2):e16


eHealth Literacy Interventions for Older Adults: A Systematic Review of the Literature

eHealth Literacy Interventions for Older Adults: A Systematic Review of the Literature

Rather, e Health interventions often use learning theory to guide interventions (eg, Xie [18-20]).

Ivan Watkins, Bo Xie

J Med Internet Res 2014;16(11):e225


Psychometric Properties of Patient-Facing eHealth Evaluation Measures: Systematic Review and Analysis

Psychometric Properties of Patient-Facing eHealth Evaluation Measures: Systematic Review and Analysis

Xie et al [28] addressed decision-making autonomy, defined as the level of decision making desired when information about health conditions is electronically available.No instrument included a complete psychometric evaluation (Multimedia Appendix 2).

Bonnie J Wakefield, Carolyn L Turvey, Kim M Nazi, John E Holman, Timothy P Hogan, Stephanie L Shimada, Diana R Kennedy

J Med Internet Res 2017;19(10):e346


Internet-Based and Mobile-Based General Practice: Cross-Sectional Survey

Internet-Based and Mobile-Based General Practice: Cross-Sectional Survey

Based on Xie et al [5], the consulting methods included video chat, voice chat, telephone, image, and message. The details of the consultation are provided in a study conducted by Tu et al [4].

Yan Qiu, Ying Liu, Wen Ren, Yunqing Qiu, Jingjing Ren

J Med Internet Res 2018;20(9):e266