JMIR Mental Health,
Journal Year:
2024,
Volume and Issue:
11, P. e54781 - e54781
Published: April 18, 2024
This
paper
explores
a
significant
shift
in
the
field
of
mental
health
general
and
psychotherapy
particular
following
generative
artificial
intelligence's
new
capabilities
processing
generating
humanlike
language.
Following
Freud,
this
lingo-technological
development
is
conceptualized
as
"fourth
narcissistic
blow"
that
science
inflicts
on
humanity.
We
argue
blow
has
potentially
dramatic
influence
perceptions
human
society,
interrelationships,
self.
should,
accordingly,
expect
changes
therapeutic
act
emergence
what
we
term
third
psychotherapy.
The
introduction
an
marks
critical
juncture,
prompting
us
to
ask
important
core
questions
address
two
basic
elements
thinking,
namely,
transparency
autonomy:
(1)
What
presence
therapy
relationships?
(2)
How
does
it
reshape
our
perception
ourselves
interpersonal
dynamics?
(3)
remains
irreplaceable
at
therapy?
Given
ethical
implications
arise
from
these
questions,
proposes
can
be
valuable
asset
when
applied
with
insight
consideration,
enhancing
but
not
replacing
touch
therapy.
JMIR Mental Health,
Journal Year:
2024,
Volume and Issue:
11, P. e58011 - e58011
Published: July 24, 2024
Knowledge
has
become
more
open
and
accessible
to
a
large
audience
with
the
"democratization
of
information"
facilitated
by
technology.
This
paper
provides
sociohistorical
perspective
for
theme
issue
"Responsible
Design,
Integration,
Use
Generative
AI
in
Mental
Health."
It
evaluates
ethical
considerations
using
generative
artificial
intelligence
(GenAI)
democratization
mental
health
knowledge
practice.
explores
historical
context
democratizing
information,
transitioning
from
restricted
access
widespread
availability
due
internet,
open-source
movements,
most
recently,
GenAI
technologies
such
as
language
models.
The
highlights
why
represent
new
phase
movement,
offering
unparalleled
highly
advanced
technology
well
information.
In
realm
health,
this
requires
delicate
nuanced
deliberation.
Including
may
allow,
among
other
things,
improved
accessibility
care,
personalized
responses,
conceptual
flexibility,
could
facilitate
flattening
traditional
hierarchies
between
care
providers
patients.
At
same
time,
it
also
entails
significant
risks
challenges
that
must
be
carefully
addressed.
To
navigate
these
complexities,
proposes
strategic
questionnaire
assessing
intelligence-based
applications.
tool
both
benefits
risks,
emphasizing
need
balanced
approach
integration
health.
calls
cautious
yet
positive
advocating
active
engagement
professionals
guiding
development.
emphasizes
importance
ensuring
advancements
are
not
only
technologically
sound
but
ethically
grounded
patient-centered.
JMIR Mental Health,
Journal Year:
2025,
Volume and Issue:
12, P. e70439 - e70439
Published: Jan. 6, 2025
Abstract
Generative
artificial
intelligence
(GenAI)
shows
potential
for
personalized
care,
psychoeducation,
and
even
crisis
prediction
in
mental
health,
yet
responsible
use
requires
ethical
consideration
deliberation
perhaps
governance.
This
is
the
first
published
theme
issue
focused
on
GenAI
health.
It
brings
together
evidence
insights
GenAI’s
capabilities,
such
as
emotion
recognition,
therapy-session
summarization,
risk
assessment,
while
highlighting
sensitive
nature
of
health
data
need
rigorous
validation.
Contributors
discuss
how
bias,
alignment
with
human
values,
transparency,
empathy
must
be
carefully
addressed
to
ensure
ethically
grounded,
intelligence–assisted
care.
By
proposing
conceptual
frameworks;
best
practices;
regulatory
approaches,
including
ethics
care
preservation
socially
important
humanistic
elements,
this
underscores
that
can
complement,
rather
than
replace,
vital
role
clinical
settings.
To
achieve
this,
an
ongoing
collaboration
between
researchers,
clinicians,
policy
makers,
technologists
essential.
PeerJ,
Journal Year:
2024,
Volume and Issue:
12, P. e17468 - e17468
Published: May 29, 2024
The
aim
of
this
study
was
to
evaluate
the
effectiveness
ChatGPT-3.5
and
ChatGPT-4
in
incorporating
critical
risk
factors,
namely
history
depression
access
weapons,
into
suicide
assessments.
Both
models
assessed
using
scenarios
that
featured
individuals
with
without
a
weapons.
estimated
likelihood
suicidal
thoughts,
attempts,
serious
suicide-related
mortality
on
Likert
scale.
A
multivariate
three-way
ANOVA
analysis
Bonferroni
post
hoc
tests
conducted
examine
impact
forementioned
independent
factors
(history
weapons)
these
outcome
variables.
identified
as
significant
factor.
demonstrated
more
nuanced
understanding
relationship
between
depression,
risk.
In
contrast,
displayed
limited
insight
complex
relationship.
consistently
assigned
higher
severity
ratings
variables
than
did
ChatGPT-3.5.
highlights
potential
two
models,
particularly
ChatGPT-4,
enhance
assessment
by
considering
factors.
JMIR Formative Research,
Journal Year:
2025,
Volume and Issue:
9, P. e68347 - e68347
Published: Jan. 6, 2025
Cognitive
assessment
is
an
important
component
of
applied
psychology,
but
limited
access
and
high
costs
make
these
evaluations
challenging.
This
study
aimed
to
examine
the
feasibility
using
large
language
models
(LLMs)
create
personalized
artificial
intelligence-based
verbal
comprehension
tests
(AI-BVCTs)
for
assessing
intelligence,
in
contrast
with
traditional
methods
based
on
standardized
norms.
We
used
a
within-participants
design,
comparing
scores
obtained
from
AI-BVCTs
those
Wechsler
Adult
Intelligence
Scale
(WAIS-III)
index
(VCI).
In
total,
8
Hebrew-speaking
participants
completed
both
VCI
AI-BVCT,
latter
being
generated
LLM
Claude.
The
concordance
correlation
coefficient
(CCC)
demonstrated
strong
agreement
between
AI-BVCT
(Claude:
CCC=.75,
90%
CI
0.266-0.933;
GPT-4:
CCC=.73,
0.170-0.935).
Pearson
correlations
further
supported
findings,
showing
associations
r=.84,
P<.001;
r=.77,
P=.02).
No
statistically
significant
differences
were
found
(P>.05).
These
findings
support
potential
LLMs
assess
intelligence.
attests
promise
AI-based
cognitive
increasing
accessibility
affordability
processes,
enabling
testing.
research
also
raises
ethical
concerns
regarding
privacy
overreliance
AI
clinical
work.
Further
larger
more
diverse
samples
needed
establish
validity
reliability
this
approach
develop
accurate
scoring
procedures.
Frontiers in Digital Health,
Journal Year:
2025,
Volume and Issue:
7
Published: Feb. 4, 2025
Introduction
Externalization
techniques
are
well
established
in
psychotherapy
approaches,
including
narrative
therapy
and
cognitive
behavioral
therapy.
These
methods
elicit
internal
experiences
such
as
emotions
make
them
tangible
through
external
representations.
Recent
advances
generative
artificial
intelligence
(GenAI),
specifically
large
language
models
(LLMs),
present
new
possibilities
for
therapeutic
interventions;
however,
their
integration
into
core
practices
remains
largely
unexplored.
This
study
aimed
to
examine
the
clinical,
ethical,
theoretical
implications
of
integrating
GenAI
space
a
proof-of-concept
(POC)
AI-driven
externalization
techniques,
while
emphasizing
essential
role
human
therapist.
Methods
To
this
end,
we
developed
two
customized
GPTs
agents:
VIVI
(visual
externalization),
which
uses
DALL-E
3
create
images
reflecting
patients'
(e.g.,
depression
or
hope),
DIVI
(dialogic
role-play-based
simulates
conversations
with
aspects
content.
tools
were
implemented
evaluated
clinical
case
under
professional
psychological
guidance.
Results
The
demonstrated
that
can
serve
an
“artificial
third”,
creating
Winnicottian
playful
enhances,
rather
than
supplants,
dyadic
therapist-patient
relationship.
successfully
externalized
complex
dynamics,
offering
avenues,
also
revealing
challenges
empathic
failures
cultural
biases.
Discussion
findings
highlight
both
promise
ethical
complexities
AI-enhanced
therapy,
concerns
about
data
security,
representation
accuracy,
balance
authority.
address
these
challenges,
propose
SAFE-AI
protocol,
clinicians
structured
guidelines
responsible
AI
Future
research
should
systematically
evaluate
generalizability,
efficacy,
across
diverse
populations
contexts.
