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Validating the eHealth Literacy Scale in Rural Adolescents
Author(s) -
Giger Jarod T.,
Barnhart Sheila,
Feltner Fran,
Slone Melissa,
Lawler Michael J.,
Windsor Leah,
Windsor Alistair
Publication year - 2020
Publication title -
the journal of rural health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.439
H-Index - 57
eISSN - 1748-0361
pISSN - 0890-765X
DOI - 10.1111/jrh.12509
Subject(s) - structural equation modeling , health literacy , confirmatory factor analysis , ehealth , rurality , literacy , sample size determination , scale (ratio) , sample (material) , medicine , polychoric correlation , statistics , gerontology , psychology , rural area , mathematics , correlation , health care , geography , economics , economic growth , pedagogy , chemistry , geometry , cartography , pathology , chromatography
Purpose Given that the recent eHealth literacy literature supports the properties of the 3‐factor eHealth literacy scale (eHEALS) model in samples with millennials, adults, and older adults, the appropriate next step is to establish whether the model can be reproduced in a rural adolescent sample. The purpose of this study was to evaluate the recent 3‐factor model by Paige and associates with a sample of seventh‐grade students. Methods This cross‐sectional study included a subsample of students (n = 146) from 3 school districts in Appalachian Kentucky. We used confirmatory factor analysis (CFA) procedures and small sample model fit guidelines to evaluate our model, and the 1‐sample bootstrap algorithm with bias‐corrected and accelerated 95% confidence intervals to estimate associations among eHEALS and health and technology variables. Findings A total of 137 students, or 61% of enrolled seventh‐grade students, completed the study. CFA results showed eHEALS 3‐factor loadings—information awareness, information seeking, and information engagement—were high (≥0.63) and statistically significant. We observed evidence of a good model fit (root mean square error of approximation [RMSEA] = 0.07, standardized root mean square residual [SRMR] = 0.03, comparative fit index [CFI] = 0.99) and results are comparable with Paige and associates’ model fit (RMSEA = 0.06, SRMR = 0.08, CFI = 0.98). Correlations showed that students with more access to technology were associated with higher information seeking (r = 0.31) and higher information engagement (r = 0.23). eHealth literacy scores did not differ by level of rurality or gender. Conclusions The 3‐factor eHEALS is a reliable and valid instrument in assessing eHealth literacy in a group of rural seventh graders from Appalachian Kentucky.