Using Exploratory Graph Analysis in validating the structure of the Technology Readiness Index2.0 in the health context (Preprint)
Опубликована: Фев. 7, 2025
BACKGROUND
With
a
continual
interest
in
technology
adoption
the
health
context,
good
understanding
of
psychological
determinants
is
great
importance.
Although
Technology
Readiness
Index2.0
(TRI2.0)
currently
most
comprehensive
measure
readiness
(TR),
there
are
discrepancies
between
factorial
structure
TRI2.0
found
initial
study
(four
factors)
and
other
studies
(two
factors).
OBJECTIVE
This
aimed
to
translate
TRI2.0,
determine
its
construct,
validate
Chinese
version
patient
sample
exposed
artificial
intelligence
technology.
METHODS
was
translated,
back-translated,
cross-culturally
adapted
using
Brislin
translation
model
form
version.
Baseline
data
326
participants
(age
30.92±11,
45.1%
males)
outpatient
department
were
analyzed.
Content
validity
checked
by
calculating
score
content
index
(S-CVI).
Exploratory
graph
analysis
(EGA)
conducted
evaluate
dimensionality
scale,
bootstrap
exploratory
approach
(bootEGA)
employed
assess
item
stability.
Confirmatory
factor
(CFA)
computed
test
measurement
models.
Cronbachɑ
test-retest
reliability
used
scale's
internal
consistency.
RESULTS
The
satisfactory
(S-CVI=
0.9).
Through
EGA
approach,
contains
four
factors,
which
consistent
with
result
original
CFA
further
confirmed
this
structure,
CFI
0.93,
SRMR
0.05,
RMSEA
0.064,
TLI
0.916
x2/df
2.38.
Overall
0.797.
patients’
(TRI2.0=
3.470
±
0.488)
higher
than
general
public
3.02
0.61).
CONCLUSIONS
Index
2.0
has
can
be
as
an
assessment
tool
for
context.
Patients
have
open
attitude
towards
new
AI
context
compared
toward
2015.
CLINICALTRIAL
Not
Applicable
Язык: Английский
Digital health literacy among the Spanish population: a descriptive and latent class analysis study
European Journal of Public Health,
Год журнала:
2025,
Номер
unknown
Опубликована: Март 18, 2025
Abstract
Spain
has
been
consolidating
the
implementation
of
digital
healthcare.
However,
there
is
not
a
comprehensive
picture
health
literacy
population
in
relation
to
existing
policies
and
practices.
To
identify
different
profiles
people
by
analysing
their
literacy,
with
ultimate
goal
providing
healthcare
organizations
indications
improve
relationship
between
system.
This
cross-sectional
survey
study
included
400
aged
≥18
years
from
May
2021
2022
Spain.
Participants
were
stratified
gender,
age
range,
residential
area
mirroring
Spanish
population,
recruited
an
online
panel
community
settings.
A
self-administered
was
used,
including
eHLQ
questionnaire
as
main
measure
sociodemographic
information.
The
level
medium
balanced
among
seven
dimensions
(ranging
2.60
2.77
out
5).
latent
class
analysis
revealed
five
based
on
scores
taking
into
account
age,
technology
use,
educational
level.
Access
services
that
work,
together
using
process
information,
challenge
identified
participants.
National
institutions
should
focus
only
educating
training
skills
but
also
reliable
useful
services.
first
provide
profile
questionnaire.
Язык: Английский