Facilitators and Barriers of Large Language Model Adoption Among Nursing Students: A Qualitative Descriptive Study
Yingzhuo Ma,
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Tong Liu,
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Jianwei Qi
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et al.
Journal of Advanced Nursing,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 4, 2025
ABSTRACT
Aim
To
explore
nursing
students'
perceptions
and
experiences
of
using
large
language
models
identify
the
facilitators
barriers
by
applying
Theory
Planned
Behaviour.
Design
A
qualitative
descriptive
design.
Method
Between
January
June
2024,
we
conducted
individual
semi‐structured
online
interviews
with
24
students
from
13
medical
universities
across
China.
Participants
were
recruited
purposive
snowball
sampling
methods.
Interviews
in
Mandarin.
Data
analysed
through
directed
content
analysis.
Results
Analysis
revealed
10
themes
according
to
3
constructs
Behaviour:
(a)
attitude:
perceived
value
expectations
facilitators,
while
caution
posed
barriers;
(b)
subjective
norm:
media
effects
role
model
effectiveness
described
as
whereas
organisational
pressure
exerted
universities,
research
institutions
hospitals
acted
a
barrier
usage;
(c)
behavioural
control:
design
free
access
strong
incentives
for
use,
geographic
restrictions
digital
literacy
deficiencies
key
factors
hindering
adoption.
Conclusion
This
study
explored
attitudes,
norms
control
regarding
use
models.
The
findings
provided
valuable
insights
into
that
hindered
or
facilitated
Implications
Profession
Through
lens
this
study,
have
enhanced
knowledge
journey
models,
which
contributes
implementation
management
these
tools
education.
Impact
There
is
gap
literature
views
influence
their
usage,
addresses.
These
could
provide
evidence‐based
support
nurse
educators
formulate
strategies
guidelines.
Reporting
adheres
consolidated
criteria
reporting
(COREQ)
checklist.
Public
Contribution
No
patient
public
contribution.
Language: Английский
The Role of Artificial Intelligence Literacy and Innovation Mindset in Shaping Nursing Students' Career and Talent Self-Efficacy
Nurse Education in Practice,
Journal Year:
2024,
Volume and Issue:
82, P. 104208 - 104208
Published: Dec. 1, 2024
Language: Английский
Empowering nurses – a practical guide to artificial intelligence tools in healthcare settings: discussion paper
Contemporary Nurse,
Journal Year:
2025,
Volume and Issue:
unknown, P. 1 - 11
Published: Feb. 3, 2025
Background
The
rapid
growth
of
artificial
intelligence
in
healthcare
is
transforming
how
nurses
deliver
care
and
make
clinical
decisions.
From
supporting
diagnostics
to
providing
virtual
health
assistants,
offers
new
ways
enhance
patient
outcomes
streamline
processes.
However,
these
advancements
also
bring
challenges,
particularly
around
ethics,
potential
biases,
ensuring
technology
complements
rather
than
replaces
human
expertise.
Language: Английский
Exploring faculty perceptions and concerns regarding artificial intelligence Chatbots in nursing education: potential benefits and limitations
BMC Nursing,
Journal Year:
2025,
Volume and Issue:
24(1)
Published: April 18, 2025
To
examine
faculty
perceptions
of
artificial
intelligence
(AI)
chatbots
in
nursing
education,
focusing
on
their
usage
patterns,
perceived
benefits,
and
limitations.
A
cross-sectional
study.
The
study
surveyed
from
Jordan
the
United
States
using
a
self-reported
questionnaire.
Data
were
analyzed
descriptive
statistics
Multivariate
Analysis
Covariance
to
assess
variations
based
AI
chatbot
frequency
characteristics.
Among
474
members,
82.5%
familiar
with
at
least
one
chatbot.
Faculty
generally
acknowledged
benefits
chatbots,
including
enhanced
teaching
experiences,
improved
student
engagement,
support
for
independent
learning,
quick
access
medical
knowledge.
However,
concerns
about
misinformation,
reduced
faculty-student
interaction,
inadequacies
addressing
complex
clinical
scenarios
prevalent.
Legal
ethical
issues,
particularly
risk
misuse
AI-generated
information,
also
highlighted.
Frequent
users
demonstrated
significantly
greater
awareness
both
advantages
limitations
compared
infrequent
users.
challenges
highlighting
role
hands-on
experience
shaping
adoption.
adoption
is
primarily
driven
by
rather
than
limitations,
emphasizing
need
showcase
practical
while
concerns.
enhance
institutions
should
focus
demonstrating
through
targeted
training
guidelines.
Providing
structured
exposure
can
increase
confidence,
reinforcing
usefulness
strategies
mitigate
Future
research
may
effectiveness
programs
behaviors,
providing
valuable
insights
enhancing
integration
education.
Language: Английский
Use of artificial intelligence in nursing
LatIA,
Journal Year:
2024,
Volume and Issue:
2, P. 92 - 92
Published: Sept. 2, 2024
Introduction:
Artificial
Intelligence
(AI)
encompasses
technologies
such
as
machine
learning
and
neural
networks,
with
applications
across
various
fields.
The
World
Health
Organization
recognizes
its
potential
to
enhance
healthcare,
yet
emphasizes
the
need
address
ethical
considerations
in
implementation.
In
nursing,
AI
has
increase
autonomy
efficiency
care,
though
use
remains
limited
poorly
understood
within
profession.Objective:
To
analyze
of
nursing
by
evaluating
impact
on
care
functions,
administrative
tasks,
educational
activities,
research.Methods:
A
literature
review
was
conducted,
including
original
articles,
reviews,
bibliometric
studies.
research
focused
four
primary
functions
nursing.Results:
demonstrated
benefits
predictive
analytics
improving
patient
efficiency,
well
management
classification.
education,
generative
facilitates
development
materials,
although
it
presents
risks
bias.
research,
serves
an
assistant
data
search
analysis,
despite
facing
methodological
challenges.Conclusions:
significantly
transform
practice,
enhancing
both
quality
care.
However,
integration
necessitates
careful
limitations
ensure
a
positive
field.
Language: Английский