2026-10-14T08:16:01Z
https://api.figshare.com/v2/oai
oai:figshare.com:article/34000096
2026-09-25T17:49:02Z
category_45
category_734
category_106
portal_5
item_type_3
month_year_09_2026
<p>Multiple linear regression for eHEALS (n = 113).</p>
Samar Thabet Jallad (25111642)
Maysa Kassabry (25111645)
Adel Taher Takruri (25111648)
Sociology
Biological Sciences not elsewhere classified
Science Policy
facilitating conditions showed
multiple linear regression
item adapted technology
related perception domains
internet remained significant
2 </ sup
div >< p
use factors associated
289 – 0
year nursing students
related perceptions score
mean eheals score
perceived internet skills
whether overall ai
related technology
use comparisons
nursing education
multiple testing
related perceptions
significantly associated
positively associated
independently associated
perceived usefulness
perceived importance
perceived ability
way analyses
regrouped one
regrouped internet
positively correlated
pearson correlations
participants completed
level findings
level correlation
intervention studies
interpreted cautiously
increasingly relevant
health literacy
descriptive statistics
artificial intelligence
59 ),
34 ).
177 ).
<div><p>Artificial intelligence (AI) and e-health literacy are increasingly relevant to nursing education; however, the relationship between nursing students’ perceptions and acceptance of AI and their perceived ability to locate, evaluate, and apply online health information remains insufficiently examined in Palestine. This cross-sectional study examined e-health literacy, AI-related technology-acceptance perceptions, Internet-use factors associated with these constructs, and whether overall AI-related perceptions were independently associated with e-health literacy among 113 third- and fourth-year nursing students. Participants completed the 8-item eHealth Literacy Scale (eHEALS) and a 28-item adapted technology-acceptance questionnaire covering seven AI-related perception domains, with negatively worded items reverse scored where required. Descriptive statistics, regrouped one-way analyses of variance, Pearson correlations with Holm adjustment for multiple testing, and multiple linear regression were performed. The mean eHEALS score was 3.53 (SD 0.59), and the overall AI-related perceptions score was 3.35 (SD 0.34). Overall AI-related perceptions were positively correlated with eHEALS (r = 0.387, Holm-adjusted p < .001). Facilitating conditions showed the largest domain-level correlation with eHEALS (r = 0.450, Holm-adjusted p < .001), whereas anxiety was not significantly associated with eHEALS. After adjustment for year of study, perceived Internet skills, and perceived importance of the Internet, overall AI-related perceptions remained independently associated with eHEALS (B = 0.643, 95% CI 0.289–0.998, p < .001; model R<sup>2</sup> = 0.177). Among the regrouped Internet-use comparisons, only perceived usefulness of the Internet remained significant after Holm correction. Overall, AI-related perceptions and perceived e-health literacy were positively associated in this sample, although the cross-sectional design precludes conclusions regarding directionality or causality. Further multi-site, longitudinal, and intervention studies are warranted, and domain-level findings should be interpreted cautiously because several adapted subscales demonstrated low internal consistency.</p></div>
2026-09-25T17:48:53Z
Dataset
Dataset
10.1371/journal.pdig.0001737.t005
https://figshare.com/articles/dataset/_p_Multiple_linear_regression_for_eHEALS_n_113_p_/34000096
CC BY 4.0