Neonatal nurses’ experiences with generative AI in clinical decision-making: a qualitative exploration in high-risk nicus
BMC Nursing,
Год журнала:
2025,
Номер
24(1)
Опубликована: Апрель 7, 2025
Neonatal
nurses
in
high-risk
Intensive
Care
Units
(NICUs)
navigate
complex,
time-sensitive
clinical
decisions
where
accuracy
and
judgment
are
critical.
Generative
artificial
intelligence
(AI)
has
emerged
as
a
supportive
tool,
yet
its
integration
raises
concerns
about
impact
on
nurses'
decision-making,
professional
autonomy,
organizational
workflows.
This
study
explored
how
neonatal
experience
integrate
generative
AI
examining
influence
nursing
practice,
dynamics,
cultural
adaptation
Saudi
Arabian
NICUs.
An
interpretive
phenomenological
approach,
guided
by
Complexity
Science,
Normalization
Process
Theory,
Tanner's
Clinical
Judgment
Model,
was
employed.
A
purposive
sample
of
33
participated
semi-structured
interviews
focus
groups.
Thematic
analysis
used
to
code
interpret
data,
supported
an
inter-rater
reliability
0.88.
Simple
frequency
counts
were
included
illustrate
the
prevalence
themes
but
not
quantitative
measures.
Trustworthiness
ensured
through
reflexive
journaling,
peer
debriefing,
member
checking.
Five
emerged:
(1)
Decision-Making,
93.9%
reported
that
AI-enhanced
required
human
validation;
(2)
Professional
Practice
Transformation,
with
84.8%
noting
evolving
role
boundaries
workflow
changes;
(3)
Organizational
Factors,
97.0%
emphasized
necessity
infrastructure,
training,
policy
integration;
(4)
Cultural
Influences,
87.9%
highlighting
AI's
alignment
family-centered
care;
(5)
Implementation
Challenges,
90.9%
identified
technical
barriers
strategies.
can
support
effectiveness
depends
structured
reliable
culturally
sensitive
implementation.
These
findings
provide
evidence-based
insights
for
policymakers
healthcare
leaders
ensure
enhances
expertise
while
maintaining
safe,
patient-centered
care.
Язык: Английский
Development and psychometric evaluation of the artificial intelligence attitude scale for nurses
BMC Nursing,
Год журнала:
2025,
Номер
24(1)
Опубликована: Апрель 22, 2025
Язык: Английский
Nurses’ Perception of Artificial Intelligence-Driven Monitoring Systems for Enhancing Compliance With Infection Prevention and Control Measures in Al-Ahsa, Saudi Arabia
Cureus,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 24, 2025
Background
Healthcare-associated
infections
(HCAIs)
represent
a
major
risk
to
patient
safety,
increasing
morbidity,
mortality,
and
costs.
Effective
infection
prevention
control
(IPC)
compliance
is
crucial,
but
nurse
adherence
remains
inconsistent,
necessitating
innovative
solutions
such
as
artificial
intelligence
(AI)-driven
monitoring.
However,
the
success
of
technologies
heavily
relies
on
perceptions
acceptance
frontline
healthcare
workers,
particularly
nurses.
This
study
aimed
determine
nurses'
perception
AI-driven
monitoring
in
improving
IPC
selected
hospitals.
Methodology
A
cross-sectional
was
conducted
among
nurses
working
at
public
hospital
Al-Ahsa,
Saudi
Arabia.
Computer-generated
numbers
randomly
246
structured,
self-administered
questionnaire
used
gather
data
demographics,
knowledge,
perceptions,
perceived
barriers
practices.
Descriptive
statistics
were
utilized
for
continuous
variables,
while
inferential
statistics,
chi-square,
categorical
variables
analyse
results.
Results
Out
nurses,
183
(74.4%)
had
average
knowledge
about
AI
applications
The
overall
mean
score
regarding
AI-based
measures
17.00
±
3.97
out
20,
which
showed
that
most
moderate
some
domains
scored
well.
Regarding
practices,
many
positive
attitude.
insufficient
training,
financial
limitations,
limited
organizational
support
are
critical
barriers.
There
significant
association
found
between
level
age,
highest
educational
qualification,
job
role,
technology-based
training
(p
<
0.05).
Nurses
expressed
willingness
adopt
systems
if
adequate
ensured.
Conclusion
may
enhance
addressed,
helping
reduce
HCAIs
improve
safety.
Its
depends
addressing
key
infrastructure,
stakeholder
support.
These
findings
can
guide
policymakers
leaders
effectively
adopting
solutions.
Язык: Английский
Empowering Care: Transforming Nursing Through Artificial Intelligence
IntechOpen eBooks,
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 28, 2025
This
chapter
explores
the
roles
of
artificial
intelligence
(AI)
in
nursing,
highlighting
its
potential
to
enhance
patient
care,
streamline
clinical
workflows,
and
support
evidence-based
decision-making
nursing
research.
It
discusses
applications
AI
predictive
analytics,
personalized
virtual
assistants
while
addressing
ethical
considerations
evolving
role
nurses
AI-driven
healthcare.
The
addresses
critical
adopting
such
as
implications,
privacy,
need
for
equitable
access
tools.
content
is
based
on
a
narrative
synthesis
relevant
literature,
identified
through
searches
healthcare
databases,
including
PubMed
Cumulative
Index
Nursing
Allied
Health
Literature
(CINAHL),
using
terms
“artificial
intelligence,”
“nursing
practice,”
education,”
research.”
importance
training
workforce
work
effectively
with
technologies
augment,
rather
than
replace,
human
judgment
care.
Additionally,
case
studies
real-world
examples
illustrate
successful
implementation
solutions
lessons
learned
best
practices.
Through
future
projections,
emphasizes
integrating
empower
improve
health
outcomes.
Язык: Английский