JMIR Research Protocols,
Journal Year:
2024,
Volume and Issue:
13, P. e53857 - e53857
Published: Feb. 22, 2024
Background
Computational
psychiatry
has
the
potential
to
advance
diagnosis,
mechanistic
understanding,
and
treatment
of
mental
health
conditions.
Promising
results
from
clinical
samples
have
led
calls
extend
these
methods
risk
assessment
in
general
public;
however,
data
typically
used
with
are
neither
available
nor
scalable
for
research
population.
Digital
phenotyping
addresses
this
by
capitalizing
on
multimodal
widely
created
sensors
embedded
personal
digital
devices
(eg,
smartphones)
is
a
promising
approach
extending
computational
improve
Objective
Building
recommendations
existing
work,
we
aim
create
first
set
that
tailored
studying
population;
includes
multimodal,
sensor-based
behavioral
features;
designed
be
shared
across
academia,
industry,
government
using
gold
standard
privacy,
confidentiality,
integrity.
Methods
We
stratified,
random
sampling
design
2
crossed
factors
(difficulties
emotion
regulation
perceived
life
stress)
recruit
sample
400
community-dwelling
adults
balanced
high-
low-risk
episodic
Participants
complete
self-report
questionnaires
assessing
current
lifetime
psychiatric
medical
diagnoses
treatment,
psychosocial
functioning.
then
7-day
situ
collection
phase
providing
daily
audio
recordings,
passive
sensor
collected
smartphones,
self-reports
mood
significant
events,
verbal
description
events
during
nightly
phone
call.
same
baseline
6
12
months
after
phase.
Self-report
will
scored
methods.
Raw
processed
suite
summary
features
time
spent
at
home).
Results
Data
began
June
2022
expected
conclude
July
2024.
To
date,
310
participants
consented
study;
149
completed
questionnaire
intensive
phase;
61
31
6-
12-month
follow-up
questionnaires,
respectively.
Once
completed,
proposed
made
academic
researchers,
stepped
maximize
privacy.
Conclusions
This
as
complementary
research,
goal
advancing
within
aims
support
field’s
move
away
siloed
laboratories
collecting
proprietary
toward
interdisciplinary
collaborations
incorporate
clinical,
technical,
quantitative
expertise
all
stages
process.
International
Registered
Report
Identifier
(IRRID)
DERR1-10.2196/53857
Japanese Psychological Research,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Oct. 13, 2024
Abstract
In
recent
years,
near‐infrared
spectroscopy
(NIRS)
has
garnered
significant
attention
for
its
potential
clinical
applications
as
a
non‐invasive
and
straightforward
method
measuring
brain
functions.
While
NIRS
become
useful
in
psychiatric
contexts
by
aiding
the
differential
diagnosis
of
depression,
application
psychology
is
still
developing.
Due
to
ecological
validity,
which
allows
measurements
natural
settings,
shows
promise
revealing
dynamic
elements
psychotherapy
process.
this
study,
we
conducted
scoping
literature
review
use
psychotherapeutic
interactions,
exploring
unveil
complexities
settings
involving
interpersonal
interactions.
Employing
approach,
systematically
searched
PubMed,
PsycINFO,
Web
Science
databases
articles
published
through
October
19,
2023
about
studies
using
measurement
instrument:
This
yielded
various
therapeutic
Of
155
retrieved
results
that
remained
after
initial
screening,
seven
met
inclusion
criteria.
these,
six
examined
synchronization
functions
simultaneous
activity
(hyperscanning)
two
participants.
The
revealed
that,
despite
anticipated
NIRS,
it
evident
there
dearth
research
focusing
on
interactions
during
psychotherapy.
Furthermore,
few
available
have
not
explored
changes
line
with
progression
Consequently,
future
should
address
whether
can
effectively
assess
alterations
function
resulting
from
micro‐level
events,
such
interaction
between
therapists
clients
Journal of Clinical Medicine,
Journal Year:
2023,
Volume and Issue:
13(1), P. 180 - 180
Published: Dec. 28, 2023
Leprosy
is
a
neglected
tropical
disease
that
can
cause
physical
injury
and
mental
disability.
Diagnosis
primarily
clinical,
but
be
inconclusive
due
to
the
absence
of
initial
symptoms
similarity
other
dermatological
diseases.
Artificial
intelligence
(AI)
techniques
have
been
used
in
dermatology,
assisting
clinical
procedures
diagnostics.
In
particular,
AI-supported
solutions
proposed
literature
aid
diagnosis
leprosy,
this
Systematic
Literature
Review
(SLR)
aims
characterize
state
art.
This
SLR
followed
preferred
reporting
items
for
systematic
reviews
meta-analyses
(PRISMA)
framework
was
conducted
following
databases:
ACM
Digital
Library,
IEEE
ISI
Web
Science,
Scopus,
PubMed.
Potentially
relevant
research
articles
were
retrieved.
The
researchers
applied
criteria
select
studies,
assess
their
quality,
perform
data
extraction
process.
Moreover,
1659
studies
retrieved,
which
21
included
review
after
selection.
Most
images
skin
lesions,
classical
machine
learning
algorithms,
multi-class
classification
tasks
develop
models
diagnose
reviewed
did
not
target
leprosy
as
study’s
primary
objective
rather
different
diseases
(among
them,
leprosy).
Although
constantly
evolving,
area
still
its
early
stage,
then
are
required
make
AI
mature
enough
transformed
into
practice.
Expanding
efforts
on
diagnosis,
coupled
with
advocacy
open
science
leveraging
diagnostic
support,
yield
robust
influential
outcomes.
JMIR Research Protocols,
Journal Year:
2024,
Volume and Issue:
13, P. e53857 - e53857
Published: Feb. 22, 2024
Background
Computational
psychiatry
has
the
potential
to
advance
diagnosis,
mechanistic
understanding,
and
treatment
of
mental
health
conditions.
Promising
results
from
clinical
samples
have
led
calls
extend
these
methods
risk
assessment
in
general
public;
however,
data
typically
used
with
are
neither
available
nor
scalable
for
research
population.
Digital
phenotyping
addresses
this
by
capitalizing
on
multimodal
widely
created
sensors
embedded
personal
digital
devices
(eg,
smartphones)
is
a
promising
approach
extending
computational
improve
Objective
Building
recommendations
existing
work,
we
aim
create
first
set
that
tailored
studying
population;
includes
multimodal,
sensor-based
behavioral
features;
designed
be
shared
across
academia,
industry,
government
using
gold
standard
privacy,
confidentiality,
integrity.
Methods
We
stratified,
random
sampling
design
2
crossed
factors
(difficulties
emotion
regulation
perceived
life
stress)
recruit
sample
400
community-dwelling
adults
balanced
high-
low-risk
episodic
Participants
complete
self-report
questionnaires
assessing
current
lifetime
psychiatric
medical
diagnoses
treatment,
psychosocial
functioning.
then
7-day
situ
collection
phase
providing
daily
audio
recordings,
passive
sensor
collected
smartphones,
self-reports
mood
significant
events,
verbal
description
events
during
nightly
phone
call.
same
baseline
6
12
months
after
phase.
Self-report
will
scored
methods.
Raw
processed
suite
summary
features
time
spent
at
home).
Results
Data
began
June
2022
expected
conclude
July
2024.
To
date,
310
participants
consented
study;
149
completed
questionnaire
intensive
phase;
61
31
6-
12-month
follow-up
questionnaires,
respectively.
Once
completed,
proposed
made
academic
researchers,
stepped
maximize
privacy.
Conclusions
This
as
complementary
research,
goal
advancing
within
aims
support
field’s
move
away
siloed
laboratories
collecting
proprietary
toward
interdisciplinary
collaborations
incorporate
clinical,
technical,
quantitative
expertise
all
stages
process.
International
Registered
Report
Identifier
(IRRID)
DERR1-10.2196/53857
