The role of artificial intelligence in enhancing nurses' work-life balance
Journal of Medicine Surgery and Public Health,
Год журнала:
2024,
Номер
3, С. 100135 - 100135
Опубликована: Авг. 1, 2024
Язык: Английский
Continuous nursing symptom management in cancer chemotherapy patients using deep learning
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Март 7, 2025
To
assess
the
efficacy
of
a
deep
learning
platform
for
managing
symptoms
in
chemotherapy
patients,
aiming
to
enhance
their
quality
life.
A
non-randomized
controlled
trial
was
conducted
from
September
2022
March
2024,
involving
144
patients
divided
into
intervention
(n
=
72)
and
control
groups.
The
group
received
platform,
whereas
standard
care.
Anxiety,
depression,
life
were
evaluated
using
SAS,
SDS,
QOL
scores
at
baseline
after
6
months.
Initial
non-significant
differences
between
groups
observed.
After
intervention,
significant
improvements
noted
various
aspects
(P
<
0.05).
high
satisfaction
score
4.93
±
0.13.
significantly
reduced
anxiety
depression
improved
demonstrating
patient
potential
clinical
application.
Clinical
registration:
registered
trials.gov
with
registration
number
ChiCTR2400093540.
first
date
06/12/2024.
Язык: Английский
Artificial intelligence in psychiatry: A systematic review and meta-analysis of diagnostic and therapeutic efficacy
Digital Health,
Год журнала:
2025,
Номер
11
Опубликована: Март 1, 2025
Artificial
Intelligence
(AI)
has
demonstrated
significant
potential
in
transforming
psychiatric
care
by
enhancing
diagnostic
accuracy
and
therapeutic
interventions.
Psychiatry
faces
challenges
like
overlapping
symptoms,
subjective
methods,
personalized
treatment
requirements.
AI,
with
its
advanced
data-processing
capabilities,
offers
innovative
solutions
to
these
complexities.
This
study
systematically
reviewed
meta-analyzed
the
existing
literature
evaluate
AI's
efficacy
care,
focusing
on
various
disorders
AI
technologies.
Adhering
PRISMA
guidelines,
included
a
comprehensive
search
across
multiple
databases.
Empirical
studies
investigating
applications
psychiatry,
such
as
machine
learning
(ML),
deep
(DL),
hybrid
models,
were
selected
based
predefined
inclusion
criteria.
The
outcomes
of
interest
efficacy.
Statistical
analysis
employed
fixed-
random-effects
subgroup
sensitivity
analyses
exploring
impact
methodologies
designs.
A
total
14
met
criteria,
representing
diverse
diagnosing
treating
disorders.
pooled
was
85%
(95%
CI:
80%-87%),
ML
models
achieving
highest
accuracy,
followed
DL
models.
For
efficacy,
effect
size
84%
82%-86%),
excelling
plans
symptom
tracking.
Moderate
heterogeneity
observed,
reflecting
variability
designs
populations.
risk
bias
assessment
indicated
high
methodological
rigor
most
studies,
though
algorithmic
biases
data
quality
remain.
demonstrates
robust
capabilities
offering
data-driven
approach
mental
healthcare.
Future
research
should
address
ethical
concerns,
standardize
methodologies,
explore
underrepresented
populations
maximize
transformative
health.
Язык: Английский
Attitudes of older patients toward artificial intelligence in decision-making in healthcare
Journal of Medicine Surgery and Public Health,
Год журнала:
2025,
Номер
unknown, С. 100193 - 100193
Опубликована: Апрель 1, 2025
Язык: Английский
Appreciative Inquiry in Nursing
IGI Global eBooks,
Год журнала:
2025,
Номер
unknown, С. 45 - 78
Опубликована: Апрель 4, 2025
In
the
dynamic
field
of
nursing,
fostering
a
positive,
sustainable,
and
emotionally
intelligent
workplace
is
paramount
for
patient
care
professional
well-being.
This
chapter
explores
role
Appreciative
Inquiry
(AI)
in
transforming
nursing
practices
through
strengths-based
approach,
leveraging
Emotional
Intelligence
(EI)
to
create
flourishing
environments.
By
shifting
from
problem-solving
possibility-seeking,
AI
empowers
nurses
co-create
resilient,
innovative,
compassionate
models.
The
delves
into
Five-D
Cycle
(Define,
Discover,
Dream,
Design,
Destiny),
illustrating
its
application
enhancing
leadership,
patient-centered
care.
Through
real-world
case
studies
empirical
research,
intersection
positive
psychology,
emotional
intelligence,
appreciative
inquiry
examined,
offering
strategies
building
sustainable
healthcare
ecosystems.
exploration
underscores
transformative
power
EI
cultivating
adaptive
fulfillment,
holistic
well-being
nursing.
Язык: Английский
Exploring artificial intelligence for healthcare from the health professionals’ perspective: The case of limited resource settings
Digital Health,
Год журнала:
2025,
Номер
11
Опубликована: Апрель 1, 2025
Introduction
Although
artificial
intelligence
(AI)
can
boost
clinical
decision-making,
personalize
patient
treatment,
and
advance
the
global
health
sectors,
there
are
unique
implementation
challenges
considerations
in
developing
countries.
The
perceptions,
attitudes,
behavioral
factors
among
users
limitedly
identified
Ethiopia.
Objective
This
study
aimed
to
explore
AI
healthcare
from
perspectives
of
professionals
a
resource-limited
setting.
Methods
We
employed
cross-sectional
descriptive
including
404
professionals.
Data
were
collected
using
self-structured
questionnaire.
A
simple
random
sampling
technique
was
applied.
used
SPSS
analyze
data.
Tables
graphs
present
findings.
Results
95.7%
response
rate
reported.
mean
age
respondents
32.57
±
5.34
SD.
Almost
254
(62.9%)
participants
Bachelors
Science
degree
holders.
Nearly
156
(38.6%)
medical
doctors.
More
than
50%
(52.2%)
them
said
would
be
applicable
for
diagnosis
treatment
purposes
organizations.
that
favorable
attitude,
good
knowledge,
formal
training
regarding
technologies
foster
decision-making
practices
more
efficiently
accurately.
Similarly,
our
also
potential
barriers
such
as
ethical
issues,
privacy
security
data
some
mention.
Conclusions
Our
revealed
positive
crucial
technologies.
In
addition,
this
self-reported
concerns
as;
data,
accuracy
systems.
Attention
could
given
overcome
systems
system.
Providing
training,
allocating
time
practice
tools,
incorporating
courses
curricula
education,
improving
knowledge
further
usage
settings.
Язык: Английский
The Role of Artificial Intelligence in Nursing Care: An Umbrella Review
Nursing Inquiry,
Год журнала:
2025,
Номер
32(2)
Опубликована: Апрель 1, 2025
Artificial
intelligence
(AI)
is
revolutionizing
nursing
by
enhancing
decision-making,
patient
monitoring,
and
efficiency.
Machine
learning,
natural
language
processing
(NLP),
predictive
analytics
claim
to
improve
safety
automate
tasks.
However,
a
structured
analysis
of
AI
applications
necessary
ensure
their
effective
implementation
in
practice.
This
umbrella
review
aimed
synthesize
existing
systematic
reviews
on
care,
providing
comprehensive
its
benefits,
challenges,
ethical
implications.
By
consolidating
findings
from
multiple
sources,
this
seeks
offer
evidence-based
insights
guide
the
responsible
integration
A
approach
was
employed
following
PRISMA
guidelines.
Multiple
databases,
including
PubMed,
CINAHL,
Scopus,
Web
Science,
IEEE
Xplore,
were
searched
for
articles
published
between
2015
2024.
Findings
synthesized
thematically
identify
key
trends,
limitations,
research
gaps.
13
studies,
emphasizing
AI's
impact
clinical
decision
support,
education,
workflow
optimization.
enhances
early
disease
detection,
minimizes
diagnostic
errors,
automates
documentation,
improving
data
privacy
risks,
biases,
concerns,
limited
literacy
hinder
integration.
presents
significant
opportunities
yet
successful
requires
addressing
ethical,
legal,
practical
challenges.
Adequate
training,
robust
governance
frameworks,
policies
ensuring
use
are
essential
into
Future
should
explore
long-term
impact,
training
models
nurses,
strategies
balance
AI-driven
efficiency
with
human-centered
care.
Язык: Английский
Healthcare Workers' Knowledge and Attitudes Regarding Artificial Intelligence Adoption in Healthcare: A Cross-sectional Study
Heliyon,
Год журнала:
2024,
Номер
10(23), С. e40775 - e40775
Опубликована: Ноя. 29, 2024
Язык: Английский
Enhancing fieldwork readiness in occupational therapy students with generative AI
Frontiers in Medicine,
Год журнала:
2024,
Номер
11
Опубликована: Окт. 16, 2024
The
rapid
integration
of
artificial
intelligence
(AI)
into
health
professions
education
is
revolutionizing
traditional
teaching
methodologies
and
enhancing
learning
experiences.
This
study
explores
the
use
generative
AI
to
aid
occupational
therapy
(OT)
students
in
intervention
planning.
OT
often
lack
background
knowledge
generate
a
wide
variety
interventions,
spending
excessive
time
on
idea
generation
rather
than
clinical
reasoning,
practice
skills,
patient
care.
can
enhance
creative
ideation
but
must
still
adhere
evidence-based
practice,
safety,
privacy
standards.
Students
used
ChatGPT
v.
3.5
lecture
assignment
integrate
analyzed
case
study,
generated
ideas
with
ChatGPT,
selected
interventions
that
aligned
client’s
needs,
provided
rationale.
They
conducted
searches
wrote
an
analysis
how
research
influenced
their
decisions.
results
demonstrate
AI’s
potential
as
valuable
tool
for
students,
comfort
understanding
ethical
safety
considerations.
Qualitative
feedback
highlighted
role
boosting
efficiency
creativity
planning,
most
expressing
strong
intent
due
its
ability
reduce
cognitive
load
innovative
ideas.
These
findings
suggest
integrating
curriculum
could
planning
improve
readiness.
Язык: Английский