Journal of Medical Internet Research,
Год журнала:
2024,
Номер
27, С. e63548 - e63548
Опубликована: Ноя. 25, 2024
Background
Recent
advancements
in
artificial
intelligence
(AI)
have
changed
the
care
processes
mental
health,
particularly
decision-making
support
for
health
professionals
and
individuals
with
problems.
AI
systems
provide
several
domains
of
including
early
detection,
diagnostics,
treatment,
self-care.
The
use
flows
faces
challenges
relation
to
support,
stemming
from
technology,
end-user,
organizational
perspectives
disruption
processes.
Objective
This
study
aims
explore
decision-making,
focusing
on
3
key
areas:
characteristics
research
health;
current
applications,
decisions,
end
users,
user
flow
decision-making;
evaluation
implementation
elements
influencing
long-term
use.
Methods
A
scoping
review
empirical
evidence
was
conducted
across
5
databases:
PubMed,
Scopus,
PsycINFO,
Web
Science,
CINAHL.
searches
were
restricted
peer-reviewed
articles
published
English
after
2011.
initial
screening
at
title
abstract
level
by
2
reviewers,
followed
full-text
based
inclusion
criteria.
Data
then
charted
prepared
data
analysis.
Results
Of
a
total
1217
articles,
12
(0.99%)
met
These
studies
predominantly
originated
high-income
countries.
used
care,
self-care,
hybrid
contexts,
addressing
variety
Three
types
identified
terms
support:
diagnostic
predictive
AI,
treatment
selection
self-help
AI.
dynamics
type
end-user
interaction
system
design
diverse
complexity
integration
highlighted
impacting
functionality
processes,
factors
affecting
accuracy,
increase
demand,
trustworthiness,
patient-physician
communication,
engagement
systems.
Conclusions
design,
development,
present
substantial
sustainable
this
technology
shows
that
is
still
its
stages,
need
more
empirically
focused
real-world
aspects
requiring
further
investigation
include
AI-supported
human-AI
human-computer
perspectives,
longitudinal
assess
use,
shared
Social Sciences,
Год журнала:
2024,
Номер
13(7), С. 381 - 381
Опубликована: Июль 22, 2024
AI
has
the
potential
to
revolutionize
mental
health
services
by
providing
personalized
support
and
improving
accessibility.
However,
it
is
crucial
address
ethical
concerns
ensure
responsible
beneficial
outcomes
for
individuals.
This
systematic
review
examines
considerations
surrounding
implementation
impact
of
artificial
intelligence
(AI)
interventions
in
field
well-being.
To
a
comprehensive
analysis,
we
employed
structured
search
strategy
across
top
academic
databases,
including
PubMed,
PsycINFO,
Web
Science,
Scopus.
The
scope
encompassed
articles
published
from
2014
2024,
resulting
51
relevant
articles.
identifies
18
key
considerations,
6
associated
with
using
wellbeing
(privacy
confidentiality,
informed
consent,
bias
fairness,
transparency
accountability,
autonomy
human
agency,
safety
efficacy);
5
principles
development
technologies
settings
practice
positive
(ethical
framework,
stakeholder
engagement,
review,
mitigation,
continuous
evaluation
improvement);
7
practices,
guidelines,
recommendations
promoting
use
(adhere
transparency,
prioritize
data
privacy
security,
mitigate
involve
stakeholders,
conduct
regular
reviews,
monitor
evaluate
outcomes).
highlights
importance
By
addressing
privacy,
bias,
oversight,
evaluation,
can
that
like
chatbots
AI-enabled
medical
devices
are
developed
deployed
an
ethically
sound
manner,
respecting
individual
rights,
maximizing
benefits
while
minimizing
harm.
Applied Sciences,
Год журнала:
2024,
Номер
14(13), С. 5889 - 5889
Опубликована: Июль 5, 2024
Mental
health
disorders
are
a
leading
cause
of
disability
worldwide,
and
there
is
global
shortage
mental
professionals.
AI
chatbots
have
emerged
as
potential
solution,
offering
accessible
scalable
interventions.
This
study
aimed
to
conduct
scoping
review
evaluate
the
effectiveness
feasibility
in
treating
conditions.
A
literature
search
was
conducted
across
multiple
databases,
including
MEDLINE,
Scopus,
PsycNet,
well
using
AI-powered
tools
like
Microsoft
Copilot
Consensus.
Relevant
studies
on
chatbot
interventions
for
were
selected
based
predefined
inclusion
exclusion
criteria.
Data
extraction
quality
assessment
performed
independently
by
reviewers.
The
yielded
15
eligible
covering
various
application
areas,
such
support
during
COVID-19,
specific
conditions
(e.g.,
depression,
anxiety,
substance
use
disorders),
preventive
care,
promotion,
usability
assessments.
demonstrated
benefits
improving
emotional
well-being,
addressing
conditions,
facilitating
behavior
change.
However,
challenges
related
usability,
engagement,
integration
with
existing
healthcare
systems
identified.
hold
promise
interventions,
but
widespread
adoption
hinges
systems.
Enhancing
personalization
context-specific
adaptation
key.
Future
research
should
focus
large-scale
trials,
optimal
human–AI
integration,
ethical
social
implications.
Indian Journal of Psychological Medicine,
Год журнала:
2024,
Номер
unknown
Опубликована: Июль 28, 2024
Background:
Psychotherapy
is
crucial
for
addressing
mental
health
issues
but
often
limited
by
accessibility
and
quality.
Artificial
intelligence
(AI)
offers
innovative
solutions,
such
as
automated
systems
increased
availability
personalized
treatments
to
improve
psychotherapy.
Nonetheless,
ethical
concerns
about
AI
integration
in
care
remain.
Aim:
This
narrative
review
explores
the
literature
on
applications
psychotherapy,
focusing
their
mechanisms,
effectiveness,
implications,
particularly
depressive
anxiety
disorders.
Methods:
A
was
conducted,
spanning
studies
from
January
2009
December
2023,
empirical
evidence
of
AI’s
impact
Following
PRISMA
guidelines,
authors
independently
screened
selected
relevant
articles.
The
analysis
28
provided
a
comprehensive
understanding
role
field.
Results:
results
suggest
that
can
enhance
psychotherapy
interventions
people
with
depression,
especially
chatbots
internet-based
cognitive-behavioral
therapy.
However,
achieve
optimal
outcomes,
necessitates
resolving
privacy,
trust,
interaction
between
humans
AI.
Conclusion:
study
emphasizes
potential
AI-powered
therapy
conversational
address
symptoms
depression
effectively.
article
highlights
importance
cautiously
integrating
into
services,
considering
relationship
should
prioritize
patient
well-being
assist
professionals
while
also
considerations
prospective
benefits
Frontiers in Psychiatry,
Год журнала:
2025,
Номер
16
Опубликована: Фев. 4, 2025
Background
The
proliferation
of
chatbots
in
the
digital
mental
health
sector
is
gaining
momentum,
offering
a
promising
solution
to
address
pressing
shortage
professionals.
By
providing
accessible
and
convenient
services
support,
are
poised
become
primary
technological
intervention
bridging
gap
between
needs
available
resources.
Objective
This
study
undertakes
thorough
bibliometric
analysis
discourse
on
applications
health,
with
objective
elucidating
underlying
scientific
patterns
that
emerge
at
intersection
chatbot
technology
care
global
scale.
Methods
software
Biblioshiny
VOSviewer
were
used
conduct
comprehensive
261
articles
published
Web
Science
Core
Collection
2015
2024.
Publications
distribution
analyzed
measure
productivity
countries,
institutions,
sources.
Scientific
collaboration
networks
generated
analyze
influence
as
well
communications
countries
institutions.
Research
topics
trends
formulated
by
using
keyword
co-occurrence
network.
Results
Over
last
decade,
researches
utilization
has
appeared
be
increasing
steadily
an
annual
rate
46.19%.
United
States
have
made
significant
contributions
development
expansion
publications,
accounting
for
27.97%
total
research
output
2452
citation
counts.
England
came
second
US
terms
publications
citations,
followed
Australia,
China,
France.
National
Center
France
ranked
first
among
all
Imperial
College
London
University
Zurich.
number
Journal
Medical
Internet
was
exceptionally
high,
12.26%
articles,
JMIR
Mental
Health
most
influential
publication
sources
average
citations
per
article.
Collaboration
universities
USA,
Kingdom,
Switzerland,
Singapore
demonstrated
high
level.
network
highlights
prominent
techniques
this
multidisciplinary
area
reveals
5
topics,
showing
overlap
clusters.
High-frequency
such
“ChatGPT”,
“machine
learning”,
“large
language
models”
underscore
current
state
research,
highlighting
cutting-edge
advancements
frontiers
field.
Conclusions
provides
in-depth
status,
associated
over
decade.
It
offers
insights
professionals
without
AI
background
individuals
interested
chatbots.
findings
suggest
hold
role
promoting
well-being
exhibit
considerable
potential
demonstrating
empathy,
curiosity,
understanding,
collaborative
capabilities
users.
Societies,
Год журнала:
2024,
Номер
14(8), С. 148 - 148
Опубликована: Авг. 10, 2024
The
future
of
education
relies
on
the
integration
information
technologies,
emphasizing
importance
equity
and
inclusiveness
for
quality
education.
Teacher
programs
are
essential
fostering
qualified
educators
future.
Integrating
AI
in
is
crucial
to
ensure
inclusivity
comprehensive
services
all.
This
study
aims
evaluate
student
teachers’
perceptions
using
learning
teaching,
provide
suggestions
enhancing
sustainable
through
technologies.
A
qualitative
research
design
was
adopted
gather
experiences
from
240
teachers
who
participated
a
seminar
usage
completed
self-reflection
tasks.
These
teachers,
enrolled
various
teaching
methods
principal
courses,
contributed
thematic
analysis.
reveals
that
should
be
carefully
planned
incorporated
into
lesson
plans
enhance
personalized
learning.
Student
reported
supports
motivates
process,
effectively
transforming
students’
needs
experiences.
However,
they
also
noted
potential
drawbacks,
such
as
imposing
restrictions
profession,
replacing
producing
biased
results.
suggests
capacity-building
strategies
enriched
across
different
courses
raise
awareness
about
AI’s
applications.
Informatics,
Год журнала:
2024,
Номер
11(2), С. 37 - 37
Опубликована: Июнь 3, 2024
Generative
AI
refers
specifically
to
a
class
of
Artificial
Intelligence
models
that
use
existing
data
create
new
content
reflects
the
underlying
patterns
real-world
data.
This
contribution
presents
study
aims
show
what
current
perception
arts
educators
and
students
education
is
with
regard
generative
Intelligence.
It
qualitative
research
using
focus
groups
as
collection
technique
in
order
obtain
an
overview
participating
subjects.
The
design
consists
two
phases:
(1)
generation
illustrations
from
prompts
by
students,
professionals
tool;
(2)
(N
=
5)
artistic
education.
In
general,
coincides
usefulness
tool
support
illustrations.
However,
they
agree
human
factor
cannot
be
replaced
AI.
results
obtained
allow
us
conclude
can
used
motivating
educational
strategy
for
Sustainability,
Год журнала:
2024,
Номер
16(15), С. 6648 - 6648
Опубликована: Авг. 3, 2024
This
paper
delves
into
the
fusion
of
artificial
intelligence
(AI)
and
emotional
(EQ)
by
analyzing
frameworks
international
sustainability
agendas
driven
UNESCO,
WEF,
UNICEF.
It
explores
potential
AI
integrated
with
EQ
to
effectively
address
Sustainable
Development
Goals
(SDGs),
a
focus
on
education,
healthcare,
environmental
sustainability.
The
integration
use
is
pivotal
in
using
improve
educational
outcomes
health
services,
as
emphasized
UNESCO
UNICEF’s
significant
initiatives.
highlights
evolving
role
understanding
managing
human
emotions,
particularly
personalizing
education
healthcare.
proposes
that
ethical
AI,
combined
principles,
has
power
transform
societal
interactions
decision-making
processes,
leading
more
inclusive,
sustainable,
healthier
global
community.
Furthermore,
this
considers
dimensions
deployment,
guided
UNESCO’s
recommendations
ethics,
which
advocate
for
transparency,
accountability,
inclusivity
developments.
also
examines
World
Economic
Forum’s
insights
AI’s
revolutionize
learning
healthcare
underserved
populations,
emphasizing
significance
fair
advancements.
By
integrating
perspectives
from
prominent
organizations,
offers
strategic
approach
combining
EQ,
enhancing
capacity
systems
meaningfully
challenges.
In
conclusion,
advocates
establishment
new
Goal,
SDG
18,
focused
across
all
sectors,
ensuring
technology
advances
well-being
humanity
Frontiers in Artificial Intelligence,
Год журнала:
2024,
Номер
7
Опубликована: Окт. 16, 2024
Anxiety
disorders
are
psychiatric
conditions
characterized
by
prolonged
and
generalized
anxiety
experienced
individuals
in
response
to
various
events
or
situations.
At
present,
regarded
as
the
most
widespread
globally.
Medication
different
types
of
psychotherapies
employed
primary
therapeutic
modalities
clinical
practice
for
treatment
disorders.
However,
combining
these
two
approaches
is
known
yield
more
significant
benefits
than
medication
alone.
Nevertheless,
there
a
lack
resources
limited
availability
psychotherapy
options
underdeveloped
areas.
Psychotherapy
methods
encompass
relaxation
techniques,
controlled
breathing
exercises,
visualization
exposure
cognitive
interventions
such
challenging
negative
thoughts.
These
vital
disorders,
but
executing
them
proficiently
can
be
demanding.
Moreover,
with
distinct
prescribed
medications
that
may
cause
withdrawal
symptoms
some
instances.
Additionally,
inadequate
face-to-face
restricted
capacity
predict
monitor
health,
behavioral,
environmental
aspects
during
initial
phases.
In
recent
years,
has
been
notable
progress
developing
utilizing
artificial
intelligence
(AI)
based
applications
environments
improve
precision
sensitivity
diagnosing
treating
categories
As
result,
this
study
aims
establish
efficacy
AI-enabled
addressing
existing
challenges
managing
reducing
reliance
on
medication,
investigating
potential
advantages,
issues,
opportunities
integrating
AI-assisted
healthcare
enabling
personalized
therapy.
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