Deviation from the balanced time perspective and depression and anxiety symptoms: the mediating roles of cognitive-behavioral emotion regulation in a cross-cultural model
Frontiers in Psychiatry,
Год журнала:
2025,
Номер
16
Опубликована: Фев. 7, 2025
Time
perspective
(TP)
influences
how
individuals
perceive
and
classify
their
past,
present,
future,
impacting
cognition,
behavior,
psychological
outcomes.
Deviation
from
the
balanced
time
(DBTP)
is
associated
with
mental
health
problems
(e.g.,
depression
anxiety).
Emotion
regulation
(ER)
encompasses
cognitive
behavioral
processes
to
regulate
emotions,
maladaptive
strategies
like
rumination
withdrawal
linked
anxiety.
Despite
extensive
research
on
TP
ER,
joint
impact,
particularly
in
context
of
anxiety,
cultural
differences
remain
underexplored.
Participants
(N
=
513
Iranian,
N
470
Turkish)
completed
self-report
questionnaires
perspective,
symptoms.
A
moderated
mediation
model
was
assessed,
incorporating
exogenous
variable
DBTP,
ER
as
mediators,
endogenous
variables
depressive
anxiety
The
accounted
for
variations
paths
a
moderator.
Significant
associations
were
found
between
strategies,
depression,
Mediation
analyses
revealed
that
both
(except
adaptive
strategies)
significantly
mediated
DBTP
Additionally,
multigroup
suggested
these
mediating
effects
consistent
across
Iranian
Turkish
samples,
exceptions
strategies.
study
highlights
crucial
role
TPs
predicting
symptoms,
notable
nuances.
Specifically,
exacerbate
while
mitigate
them
primarily
contexts.
Cultural
subtleties
are
discussed
detail.
Язык: Английский
Time matters for mental health: a systematic review of quantitative studies on time perspective in psychiatric populations
Current Opinion in Psychiatry,
Год журнала:
2024,
Номер
37(4), С. 309 - 319
Опубликована: Май 16, 2024
Purpose
of
review
The
ability
to
perform
mental
time
travels
and
develop
representations
the
past,
present,
future
is
one
distinctive
capacities
human
mind.
Despite
its
pronounced
consequences
for
motivation,
cognition,
affect,
subjective
well
being,
perspective
(TP)
has
been
outside
mainstream
psychiatry
clinical
psychology.
We
highlight
role
psychological-temporal
phenomena
in
various
disorders
summarize
current
research
on
TP
psychopathology.
Recent
findings
Our
ultimately
comprised
21
articles,
including
18
unique
datasets.
It
revealed
that
persons
with
different
psychiatric
diagnoses
(attention
defict
hyperactivity
disorder
(ADHD),
alcohol
dependence,
anxiety
disorders,
depression,
bipolar
disorder,
personality
posttraumatic
stress
schizophrenia)
display
temporal
profiles
than
control
groups.
also
found
marked
associations
between
features
symptom
severity.
effects
specific
TPs
vary
across
some
extent
age
groups,
a
consistent,
widespread,
nonspecific
effect
past-negative
less
balanced,
inflexible
profile.
Summary
Based
review,
biases
are
crucial
factors
development,
while
adaptive
can
serve
as
protective
against
disorders.
Understanding
cognitive-temporal
processes
enhance
comprehension
psychopathological
conditions
facilitate
development
temporality-focused
interventions.
Язык: Английский
Understanding the Immediate and Longitudinal Effects of Emotion Reactivity and Deviation from the Balanced Time Perspective on Symptoms of Depression and Anxiety: Latent Growth Curve Modeling
International Journal of Cognitive Therapy,
Год журнала:
2024,
Номер
unknown
Опубликована: Сен. 14, 2024
Язык: Английский
Automatic detection of obsessive-compulsive disorder from EEG signals based on Hilbert-Huang transform and sparse coding classification
Journal of Intelligent & Fuzzy Systems,
Год журнала:
2024,
Номер
unknown, С. 1 - 13
Опубликована: Март 19, 2024
Obsessive-compulsive
disorder
(OCD)
is
a
chronic
disease
and
psychosocial
that
significantly
reduces
the
quality
of
life
patients
affects
their
personal
social
relationships.
Therefore,
early
diagnosis
this
particular
importance
has
attracted
attention
researchers.
In
research,
new
statistical
differential
features
are
used,
which
suitable
for
EEG
signals
have
little
computational
load.
Hilbert-Huang
transform
was
applied
to
EEGs
recorded
from
26
OCD
30
healthy
subjects
extract
instant
amplitude
phase.
Then,
modified
mean,
variance,
median,
kurtosis
skewness
were
calculated
phase
data.
Next,
difference
these
between
various
pairs
channels
calculated.
Finally,
different
scenarios
feature
classification
examined
using
sparse
nonnegative
least
squares
classifier.
The
results
showed
mean
interhemispheric
channel
produces
high
accuracy
95.37%.
frontal
lobe
brain
also
created
most
distinction
two
groups
among
other
lobes
by
producing
90.52%
accuracy.
addition,
extracted
frontal-parietal
network
produced
best
(93.42%)
compared
networks
examined.
method
proposed
in
paper
dramatically
improves
individuals
much
better
previous
machine
learning
techniques.
Язык: Английский