BACKGROUND
Health
professionals
face
significant
psychological
burdens
including
burnout,
anxiety,
and
depression,
which
can
negatively
impact
their
well-being
patient
care.
Traditional
health
interventions
often
encounter
limitations
such
as
a
lack
of
accessibility
privacy.
Artificial
intelligence
(AI)
chatbots
are
emerging
promising
solutions
to
these
challenges
by
providing
accessible
immediate
support.
Therefore,
it
is
necessary
systematically
evaluate
the
characteristics
effectiveness
AI
designed
specifically
for
professionals.
OBJECTIVE
This
scoping
review
aims
existing
literature
on
use
support
among
METHODS
Following
Arksey
O’Malley’s
framework,
comprehensive
search
was
conducted
across
eight
databases,
covering
articles
published
from
2018
2024,
backward
forward
citation
tracking
manual
searching
included
articles.
Articles
were
screened
relevance
based
inclusion
exclusion
criteria,
2,465
retrieved,
10
met
criteria
review.
RESULTS
Among
articles,
three
employed
development
study
design.
Six
delivered
via
mobile
platforms,
four
web-based
all
enabling
one-on-one
interactions.
Natural
language
processing
(NLP)
algorithms
commonly
used
cognitive
behavioral
therapy
(CBT)
techniques
applied
in
Usability
evaluated
six
with
generally
high
satisfaction
rates;
however,
dropout
rates
remained
high,
particularly
emotionally
intense
situations.
Improvements
burnout
observed
studies,
although
one
reported
an
increase
depressive
symptoms.
CONCLUSIONS
show
promise
tools
offering
personalized
interventions.
Nonetheless,
further
research
required
establish
standardized
protocols
validate
long-term
Future
studies
should
focus
refining
chatbot
designs
assessing
diverse
Journal of Medicine Surgery and Public Health,
Год журнала:
2024,
Номер
3, С. 100099 - 100099
Опубликована: Апрель 17, 2024
Artificial
Intelligence
(AI)
has
emerged
as
a
transformative
force
in
various
fields,
and
its
application
mental
healthcare
is
no
exception.
Hence,
this
review
explores
the
integration
of
AI
into
healthcare,
elucidating
current
trends,
ethical
considerations,
future
directions
dynamic
field.
This
encompassed
recent
studies,
examples
applications,
considerations
shaping
Additionally,
regulatory
frameworks
trends
research
development
were
analyzed.
We
comprehensively
searched
four
databases
(PubMed,
IEEE
Xplore,
PsycINFO,
Google
Scholar).
The
inclusion
criteria
papers
published
peer-reviewed
journals,
conference
proceedings,
or
reputable
online
databases,
that
specifically
focus
on
field
offer
comprehensive
overview,
analysis,
existing
literature
English
language.
Current
reveal
AI's
potential,
with
applications
such
early
detection
health
disorders,
personalized
treatment
plans,
AI-driven
virtual
therapists.
However,
these
advancements
are
accompanied
by
challenges
concerning
privacy,
bias
mitigation,
preservation
human
element
therapy.
Future
emphasize
need
for
clear
frameworks,
transparent
validation
models,
continuous
efforts.
Integrating
therapy
represents
promising
frontier
healthcare.
While
holds
potential
to
revolutionize
responsible
implementation
essential.
By
addressing
thoughtfully,
we
may
effectively
utilize
enhance
accessibility,
efficacy,
ethicality
thereby
helping
both
individuals
communities.
JMIR Mental Health,
Год журнала:
2024,
Номер
11, С. e59479 - e59479
Опубликована: Июль 29, 2024
Abstract
Global
rates
of
mental
health
concerns
are
rising,
and
there
is
increasing
realization
that
existing
models
care
will
not
adequately
expand
to
meet
the
demand.
With
emergence
large
language
(LLMs)
has
come
great
optimism
regarding
their
promise
create
novel,
large-scale
solutions
support
health.
Despite
nascence,
LLMs
have
already
been
applied
health–related
tasks.
In
this
paper,
we
summarize
extant
literature
on
efforts
use
provide
education,
assessment,
intervention
highlight
key
opportunities
for
positive
impact
in
each
area.
We
then
risks
associated
with
LLMs’
application
encourage
adoption
strategies
mitigate
these
risks.
The
urgent
need
must
be
balanced
responsible
development,
testing,
deployment
LLMs.
It
especially
critical
ensure
fine-tuned
health,
enhance
equity,
adhere
ethical
standards
people,
including
those
lived
experience
concerns,
involved
all
stages
from
development
through
deployment.
Prioritizing
minimize
potential
harms
maximize
likelihood
positively
globally.
Social Media + Society,
Год журнала:
2025,
Номер
11(1)
Опубликована: Янв. 1, 2025
Generative
chatbots
based
on
artificial
intelligence
technology
have
become
an
essential
channel
for
people
to
obtain
health
information.
They
provide
not
only
comprehensive
information
but
also
real-time
virtual
companionship.
However,
the
provided
by
AI
may
be
completely
accurate.
Employing
a
3
×
2
experimental
design,
research
examines
effects
of
interaction
types
with
AI-generated
content
(AIGC),
specifically
under
companionship
and
knowledge
acquisition
scenarios,
willingness
share
health-related
rumors.
In
addition,
it
explores
impact
nature
rumors
(fear
vs
hope)
role
altruistic
tendencies
in
this
context.
The
results
show
that
are
more
willing
situation.
Fear-type
can
stimulate
people’s
than
hope-type
Altruism
plays
moderating
role,
increasing
scenario
companionship,
while
decreasing
acquisition.
These
findings
support
Kelley’s
three-dimensional
attribution
theory
negativity
bias
theory,
extend
these
field
human–computer
interaction.
study
help
understand
rumor
spreading
mechanism
context
theoretical
improvement
chatbots.
Dementia
is
a
progressive
neurodegenerative
disorder
that
affects
cognitive
abilities
including
memory,
reasoning,
and
communication
skills,
leading
to
gradual
decline
in
daily
activities
social
engagement.
In
light
of
the
recent
advent
Large
Language
Models
(LLMs)
such
as
ChatGPT,
this
paper
aims
thoroughly
analyse
their
potential
applications
usefulness
dementia
care
research.
Medicina,
Год журнала:
2024,
Номер
60(12), С. 2085 - 2085
Опубликована: Дек. 19, 2024
Background
and
Objectives:
This
systematic
review
examines
the
integration
of
gamified
health
promotion
strategies
in
school
settings,
with
a
focus
on
their
potential
to
positively
influence
behaviors
promote
well-being
among
adolescents.
study
explores
incorporation
cognitive
behavioral
therapy
(CBT),
artificial
intelligence,
neuropsychological
principles
interventions,
aiming
enhance
engagement
effectiveness.
Materials
Methods:
A
narrative
synthesis
56
studies,
following
PRISMA
guidelines,
underscores
significant
impact
these
interventions
mental
outcomes,
emphasizing
reductions
anxiety,
depression,
burnout
while
improving
coping
skills
lifestyle
habits.
The
key
areas
emotional
regulation,
flexibility,
adherence
mechanisms
is
explored
through
quantitative
qualitative
syntheses
underscore
intervention
effectiveness
design
principles.
Results:
highlights
high-quality
evidence
supporting
use
gamification
educational
settings
calls
for
further
research
optimize
elements
address
implementation
barriers.
findings
propose
that
well-designed
can
effectively
engage
students,
healthy
behaviors,
improve
acknowledging
need
studies
explore
underlying
long-term
effects.
Conclusions:
Gamified
embed
CBT
are
promising
promoting
schoolchildren.
Although
indicates
they
effective
psychological
needed
features
overcome
challenges
ensure
wider
more
sustainable
application.
JMIR Human Factors,
Год журнала:
2025,
Номер
12, С. e67682 - e67682
Опубликована: Фев. 14, 2025
Health
professionals
face
significant
psychological
burdens
including
burnout,
anxiety,
and
depression.
These
can
negatively
impact
their
well-being
patient
care.
Traditional
health
interventions
often
encounter
limitations
such
as
a
lack
of
accessibility
privacy.
Artificial
intelligence
(AI)
chatbots
are
being
explored
potential
solutions
to
these
challenges,
offering
available
immediate
support.
Therefore,
it
is
necessary
systematically
evaluate
the
characteristics
effectiveness
AI
designed
specifically
for
professionals.
This
scoping
review
aims
existing
literature
on
use
support
among
Following
Arksey
O'Malley's
framework,
comprehensive
search
was
conducted
across
eight
databases,
covering
studies
published
before
2024,
backward
forward
citation
tracking
manual
searching
from
included
studies.
Studies
were
screened
relevance
based
inclusion
exclusion
criteria,
2465
retrieved,
10
met
criteria
review.
Among
studies,
six
delivered
via
mobile
platforms,
four
web-based
all
enabling
one-on-one
interactions.
Natural
language
processing
algorithms
used
in
cognitive
behavioral
therapy
techniques
applied
Usability
evaluated
through
participant
feedback
engagement
metrics.
Improvements
depression,
burnout
observed
although
one
reported
an
increase
depressive
symptoms.
show
tools
by
personalized
accessible
interventions.
Nonetheless,
further
research
required
establish
standardized
protocols
validate
Future
should
focus
refining
chatbot
designs
assessing
diverse
Abstract
In
the
USA
and
globally,
public
provisioning
systems
are
evolving
in
two
fundamental
ways.
The
first
is
to
reorganize
from
decentralized
services
coordination
around
of
care.
second
widespread
integration
AI
into
multiple
social
service
areas
including
mental
health
diagnosis,
needs
assessment,
delivery.
While
has
displayed
tremendous
potential
across
various
dimensions
health,
prediction,
monitoring,
treatment,
use
also
introduces
new
challenges
performance
accountabilities.
This
chapter
explores
care
Peoria,
Illinois,
for
coordinating
organizations
serving
vulnerable
populations.
Practitioners
identified
barriers
logistical,
social,
cultural,
internal
organizational
challenges.
Lessons
case
motivate
a
broader
exploration
with
deeper
dive
area.
Concerns
included
promote
balanced
conversation
on
opportunities
accountabilities
using
provisioning.
As
becomes
more
widespread,
continuous
interrogation
reflection
necessary
realize
consistent
values
organizations,
be
publics
that
benefit
these
programs,
minimize
unintended
consequences.
Purpose
The
COVID-19
pandemic
has
intensified
the
demand
and
use
of
healthcare
resources,
prompting
search
for
efficient
solutions
under
budgetary
constraints.
In
this
context,
increasing
artificial
intelligence
telemedicine
emerged
as
a
key
strategy
to
optimize
delivery
resources.
Consequently,
chatbots
have
innovative
tools
in
various
fields,
such
mental
health
patient
monitoring,
offering
therapeutic
conversations
early
interventions.
This
systematic
review
aims
explore
current
state
sector,
meticulously
evaluating
their
effectiveness,
practical
applications,
potential
benefits.
Methods
was
conducted
following
PRISMA
guidelines,
utilizing
three
databases,
including
PubMed,
Web
Science,
Scopus,
identify
relevant
studies
on
cost
over
past
5
years.
Results
Several
articles
were
identified
through
database
(
n
=
31).
chatbot
interventions
categorized
by
similar
types.
reviewed
highlight
diverse
applications
healthcare,
support,
medical
information,
appointment
management,
education,
lifestyle
changes,
demonstrating
significant
across
these
areas.
Conclusion
Furthermore,
there
are
challenges
regarding
implementation
chatbots,
compatibility
with
other
systems,
ethical
considerations
that
may
arise
different
settings.
Addressing
issues
will
be
essential
maximize
benefits
mitigate
risks,
ensure
equitable
access
innovations.
