Interactive changes in depression and loneliness symptoms prior to and during the COVID-19 pandemic: A longitudinal network analysis
Psychiatry Research,
Год журнала:
2024,
Номер
333, С. 115744 - 115744
Опубликована: Янв. 21, 2024
Язык: Английский
Prevalence and network structure of depression, insomnia and suicidality among mental health professionals who recovered from COVID-19: a national survey in China
Translational Psychiatry,
Год журнала:
2024,
Номер
14(1)
Опубликована: Май 30, 2024
Abstract
Psychiatric
syndromes
are
common
following
recovery
from
Coronavirus
Disease
2019
(COVID-19)
infection.
This
study
investigated
the
prevalence
and
network
structure
of
depression,
insomnia,
suicidality
among
mental
health
professionals
(MHPs)
who
recovered
COVID-19.
Depression
insomnia
were
assessed
with
Patient
Health
Questionnaire
(PHQ-9)
Insomnia
Severity
Index
questionnaire
(ISI7)
respectively.
Suicidality
items
comprising
suicidal
ideation,
plan
attempt
evaluated
binary
response
(no/yes)
items.
Network
analyses
Ising
model
conducted
to
identify
central
symptoms
their
links
suicidality.
A
total
9858
COVID-19
survivors
enrolled
in
a
survey
MHPs.
The
depression
47.10%
(95%
confidence
interval
(CI)
=
46.09–48.06%)
36.2%
(95%CI
35.35–37.21%),
respectively,
while
overall
was
7.8%
7.31–8.37%).
key
nodes
included
“Distress
caused
by
sleep
difficulties”
(EI
1.34),
“Interference
daytime
functioning”
(ISI5)
1.08),
“Sleep
dissatisfaction”
(ISI4)
0.74).
“Fatigue”
(PHQ4)
(Bridge
EI
1.98),
1.71),
“Motor
Disturbances”
(PHQ8)
1.67)
important
bridge
symptoms.
flow
indicated
that
edge
between
“Suicidality”
(SU)
“Guilt”
(PHQ6)
showed
strongest
connection
(Edge
Weight=
1.17,
followed
-
“Sad
mood”
(PHQ2)
Weight
0.68)).
analysis
results
suggest
play
critical
role
activation
insomnia-depression-suicidality
survivors,
is
more
susceptible
influence
depressive
These
findings
may
have
implications
for
developing
prevention
intervention
strategies
conditions
Язык: Английский
Depression and anxiety among Macau residents during the COVID-19 outbreak: A network analysis perspective
Frontiers in Psychiatry,
Год журнала:
2023,
Номер
14
Опубликована: Апрель 26, 2023
Background
The
2019
novel
coronavirus
disease
(COVID-19)
outbreak
affected
people’s
lifestyles
and
increased
their
risk
for
depressive
anxiety
symptoms
(depression
anxiety,
respectively
hereafter).
We
assessed
depression
in
residents
of
Macau
during
“the
6.18
COVID-19
outbreak”
period
explored
inter-connections
different
from
the
perspective
network
analysis.
Methods
In
this
cross-sectional
study,
1,008
completed
an
online
survey
comprising
nine-item
Patient
Health
Questionnaire
(PHQ-9)
seven-item
Generalized
Anxiety
Disorder
Scale
(GAD-7)
to
measure
respectively.
Central
bridge
depression-anxiety
model
were
evaluated
based
on
Expected
Influence
(EI)
statistics,
while
a
bootstrap
procedure
was
used
test
stability
accuracy
model.
Results
Descriptive
analyses
indicated
prevalence
62.5%
[95%
confidence
interval
(CI)
=
59.47–65.44%],
50.2%
[95%CI
47.12–53.28%],
45.1%
42.09–48.22%]
participants
experienced
comorbid
anxiety.
“Nervousness-Uncontrollable
worry”
(GADC)
(EI
1.15),
“Irritability”
(GAD6)
1.03),
“Excessive
(GAD3)
1.02)
most
central
symptoms,
(bridge
EI
0.43),
“restlessness”
(GAD5)
0.35),
“Sad
Mood”
(PHQ2)
0.30)
key
that
emerged
Conclusion
Nearly
half
outbreak.
identified
analysis
are
plausible,
specific
targets
treatment
prevention
related
Язык: Английский