International Medical Education,
Год журнала:
2024,
Номер
3(4), С. 406 - 425
Опубликована: Окт. 9, 2024
Despite
the
potential
benefits
of
generative
artificial
intelligence
(genAI),
concerns
about
its
psychological
impact
on
medical
students,
especially
job
displacement,
are
apparent.
This
pilot
study,
conducted
in
Jordan
during
July–August
2024,
aimed
to
examine
specific
fears,
anxieties,
mistrust,
and
ethical
students
harbor
towards
genAI.
Using
a
cross-sectional
survey
design,
data
were
collected
from
164
studying
across
various
academic
years,
employing
structured
self-administered
questionnaire
with
an
internally
consistent
FAME
scale—representing
Fear,
Anxiety,
Mistrust,
Ethics—comprising
12
items,
3
items
for
each
construct.
Exploratory
confirmatory
factors
analyses
assess
construct
validity
scale.
The
results
indicated
variable
levels
anxiety
genAI
among
participating
students:
34.1%
reported
no
genAI‘s
role
their
future
careers
(n
=
56),
while
41.5%
slightly
anxious
61),
22.0%
somewhat
36),
2.4%
extremely
4).
Among
constructs,
Mistrust
was
most
agreed
upon
(mean:
12.35
±
2.78),
followed
by
Ethics
10.86
2.90),
Fear
9.49
3.53),
Anxiety
8.91
3.68).
Their
sex,
level,
Grade
Point
Average
(GPA)
did
not
significantly
affect
students’
perceptions
However,
there
notable
direct
association
between
general
elevated
scores
constructs
Prior
exposure
previous
use
modify
These
findings
highlight
critical
need
refined
educational
strategies
address
integration
into
training.
demonstrate
anxiety,
fear,
regarding
deployment
healthcare,
indicating
necessity
curriculum
modifications
that
focus
specifically
these
areas.
Interventions
should
be
tailored
increase
familiarity
competency
genAI,
which
would
alleviate
apprehensions
equip
physicians
engage
this
inevitable
technology
effectively.
study
also
highlights
importance
incorporating
discussions
courses
mistrust
human-centered
aspects
In
conclusion,
calls
proactive
evolution
education
prepare
new
AI-driven
healthcare
practices
ensure
well
prepared,
confident,
ethically
informed
professional
interactions
technologies.
Behavioral Sciences,
Год журнала:
2024,
Номер
14(7), С. 616 - 616
Опубликована: Июль 20, 2024
The
evolution
of
e-retail
and
the
contribution
artificial
intelligence
in
improving
algorithms
for
greater
customer
engagement
highlight
potential
these
technologies
to
develop
e-commerce
further,
making
it
more
accessible
personalized
meet
individual
needs.
This
study
aims
explore
psychosocial
factors
(subjective
norms;
faith;
consciousness;
perceived
control)
that
affect
AI-enabled
ease
use
their
impact
on
purchase
intention
online
retail.
We
will
also
assess
mediating
effect
between
consumer
intention.
A
quantitative
methodology
was
used,
1438
responses
were
collected
from
Portuguese
consumers
e-retail.
Structural
equation
modeling
used
statistical
treatment.
findings
indicate
subjective
norms
do
not
positively
use,
whereas
such
as
faith,
consciousness,
control
enhance
it.
Furthermore,
itself
boosts
Additionally,
effects
norms,
are
significantly
enhanced
when
mediated
by
highlighting
crucial
role
usability
shaping
behavior.
this
has
been
made
through
formulation
model
provides
a
systematized
perspective
about
influencers
intentions
extends
knowledge
offers
insights
into
e-commerce—artificial
directly
affects
plays
an
important
mediator
interaction
mechanisms
intentions.
Sustainability,
Год журнала:
2024,
Номер
16(17), С. 7351 - 7351
Опубликована: Авг. 26, 2024
Digital
technologies
have
revolutionized
the
business
field,
offering
significant
opportunities
for
small
and
medium-sized
enterprises
(SMEs)
to
enhance
sustainability
value
creation.
This
study
investigates
impact
of
digital
technology
adoption
on
economic
social
creation,
as
well
SME
performance.
Specifically,
it
examines
how
media
applications,
big
data
analytics,
IoT
blockchain
AI-enabled
applications
influence
within
SMEs.
We
employed
a
hybrid
approach
integrating
Structural
Equation
Modeling
(SEM)
Artificial
Neural
Network
(ANN)
techniques
using
SmartPLs
4.0
Application;
this
research
analyzes
these
relationships.
For
our
analysis,
were
collected
from
305
managers
operating
in
Upper
Sindh,
Pakistan,
specifically
major
cities
like
Sukkur,
Larkana,
Shikarpur,
Jacobabad,
Khairpur.
The
findings
reveal
that
significantly
contribute
both
creation
Conversely,
show
no
Importantly,
positively
correlates
with
enhanced
enriches
understanding
SMEs
particularly
enhancing
Through
advanced
methodologies
rigorous
bridges
theory
practical
SMEs’
transformation.
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Фев. 13, 2025
This
study
investigates
the
impact
of
Artificial
Intelligence
(AI)
adoption
on
sustainable
performance
small
and
medium-sized
enterprises
(SMEs).
Employing
a
hybrid
quantitative
approach,
this
research
combines
Partial
Least
Squares
Structural
Equation
Modeling
(PLS-SEM)
Neural
Networks
(ANN)
to
examine
influence
various
organizational,
technological,
external
factors
AI
adoption.
Key
considered
include
top
management
support,
employee
capability,
customer
pressure,
complexity,
vendor
relative
advantage.
Data
collected
from
305
SMEs
across
multiple
sectors
were
analyzed.
The
results
reveal
that
all
proposed
significantly
positively
affect
adoption,
with
advantage
being
most
influential
predictors.
Additionally,
technologies
substantially
enhances
economic,
social,
environmental
SMEs,
reflecting
improvements
in
operational
efficiency,
cost
reduction,
social
value
creation.
ANN
confirm
robustness
SEM
findings,
highlighting
critical
role
driving
sustainability
outcomes.
Furthermore,
emphasizes
positive
mediation
effects
organizational
performance,
indicating
serves
as
key
enabler
achieving
both
short-term
gains
long-term
objectives.
contributes
understanding
AI's
transformative
enhancing
developing
economies,
offering
strategic
insights
for
policymakers
business
leaders.
