medRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2023,
Volume and Issue:
unknown
Published: Aug. 5, 2023
ABSTRACT
University
students
are
particularly
susceptible
to
developing
high
levels
of
stress,
which
occur
when
environmental
demands
outweigh
an
individual’s
ability
cope.
The
growing
advent
mental
health
smartphone
apps
has
led
a
surge
in
use
by
university
seeking
ways
help
them
cope
with
stress.
Use
these
afforded
researchers
the
unique
collect
extensive
amounts
passive
sensing
data
including
GPS
and
step
detection.
Despite
this,
little
is
known
about
relationship
between
Further,
there
no
established
methodologies
or
tools
predict
stress
from
this
group.
In
study,
we
establish
clear
machine
learning-based
methodological
pipeline
for
processing
extracting
features
that
may
be
relevant
context
health.
We
then
methodology
determine
students.
doing
so,
offer
first
proof-of-principle
utility
our
highlight
can
indeed
digitally
phenotype
Journal of American College Health,
Journal Year:
2025,
Volume and Issue:
unknown, P. 1 - 10
Published: Jan. 27, 2025
This
mixed-methods
study
examined
attitudes,
barriers,
and
preferences
for
mobile
mental
health
interventions
among
first-year
college
students.
351
students
(64%
women;
51%
non-Hispanic
White;
66%
Heterosexual)
from
two
campuses
completed
self-report
assessments
10
individual
semi-structured
interviews.
Paired
t-tests
compared
attitudes
various
mHealth
applications
logistic
regressions
sociodemographic
clinical
characteristics
of
app
users.
Themes,
topics,
quotes
interviews
were
derived
through
rapid
qualitative
analysis.
Mental
less
used
perceived
to
be
helpful
than
other
applications.
Past
use
was
best
predicted
by
past
formal
care.
Mobile
have
significant
potential
diversify
services
Despite
limited
engagement
with
these
resources,
openness
digital
is
quite
high.
Improving
intervention
features
increasing
problem-recognition
facilitate
help-seeking
may
result
in
greater
uptake.
Frontiers in Digital Health,
Journal Year:
2025,
Volume and Issue:
7
Published: Feb. 18, 2025
Mental
health
(MH)
smartphone
applications
(MH
apps)
can
support
the
increasing
MH
needs
of
postsecondary
students
and
mitigate
barriers
to
accessing
support.
Evaluating
app
acceptance
using
technology
models
is
recommended
improve
student
engagement
with
apps.
The
JoyPopTM
was
designed
youth
resilience
emotion
regulation.
associated
improved
MH,
but
its
has
yet
be
evaluated
quantitatively.
present
study
used
Unified
Theory
Acceptance
Use
Technology
(UTAUT2)
evaluate
examine
constructs
moderators
influencing
(i.e.,
behavioural
intention)
use
app.
Participants
were
183
attending
a
Canadian
University
who
for
one
week
completed
measures
before
after
Relationships
posited
by
UTAUT2
tested
partial
least
squares
structural
equation
modelling
(PLS-SEM).
Most
participants
accepted
model
explained
substantial
variance
in
intention
use.
Performance
expectancy,
hedonic
motivation,
facilitating
conditions
predicted
intention,
Age
moderated
association
between
intention.
Experience
relationship
performance
social
influence
on
Results
provide
insight
into
factors
ability
engage
students.
also
valuable
insights
evaluating
optimally
designing
Trials,
Journal Year:
2025,
Volume and Issue:
26(1)
Published: April 10, 2025
Abstract
Background
In
the
face
of
extensive
waiting
times
for
outpatient
psychotherapy,
prescriptible
digital
health
applications
(DiGA)
are
a
useful
and
effective
addition
to
range
available
therapy
options
patients
with
mild
moderate
depression.
However,
older
adults
particular
challenge
in
implementing
DiGA
since
higher
age
is
decisive
predictor
lower
literacy.
The
necessity
an
independent
use
prescribed
therefore
associated
challenges
providers.
practice,
it
crucial
not
leave
patients,
especially
adults,
alone
after
prescribing,
but
maintain
close
contact
overcome
technical
motivational
barriers
ensure
that
novel
application
used.
this
difficult
physicians
psychotherapists
due
critical
healthcare
system
situation
Germany
described
above.
Another
support
needed.
Hence,
main
hypothesis
study
additional
implementation
nurses
leads
percentage
depressive
symptoms
starting
compared
prescription
information
alone.
Methods
Two
depression
were
permanently
approved
at
time
funding
application.
Using
most
suitable
one
them,
as
shown
pilot
study,
feasibility
will
be
examined
within
randomized
proof
concept
study.
our
nurse
trained
using
DiGA.
outcome
(first
session
started:
yes/no)
8
weeks.
Major
secondary
outcomes
patient-relevant
outcomes,
recruitment
intervention,
factors
moderating
effect
or
predicting
target
group.
Best
practice
guidelines
elaborated
on
how
improve
successful
population.
Discussion
Germany,
currently
little
used,
by
people
low
affinity.
This
example
disorders
show
whether
possible
increase
usage
rate
so
can
become
serious
option.
Trial
registration
DRKS:
DRKS00033535.
Registered
February
2,
2024.
Al Musyrif Jurnal Bimbingan dan Konseling Islam,
Journal Year:
2025,
Volume and Issue:
8(1), P. 38 - 51
Published: April 18, 2025
Mental
health
problems
can
be
an
obstacle
to
achieving
psychological
well-being.
are
susceptible
being
experienced
by
anyone,
including
teenagers.
Teenagers
tend
unable
understand
their
mental
condition
and
potential.
The
aim
of
this
research
is
find
out:
the
creation
development
SAKERA
(Self-care,
Knowing
Excellent
Potential
Realizing
Dreams)
application,
teenagers'
response
(interest)
in
Sakera
use
application
help
identify
personal
potential
adolescents.
This
(R&D).
subjects
were
17
students
at
MA
Al-Djufri
Pamekasan.
results
show
that,
first,
"very
suitable"
used
as
alternative
determine
Second,
positive
or
high
criteria.
Third,
contributes
applications
that
detecting
early
indications
identifying
one's
Journal of Technology in Behavioral Science,
Journal Year:
2023,
Volume and Issue:
9(3), P. 428 - 439
Published: Nov. 11, 2023
Abstract
Low-
and
middle-income
countries
(LMICs)
are
tasked
with
providing
adequate
accessible
mental
health
care.
However,
this
has
been
a
slow
process
due
to
the
lack
of
resources.
With
recent
advances
in
technology,
apps
offer
opportunity
provide
care
that
is
affordable.
This
study
explored
efficacy
LMICs
using
AAAQ
framework.
A
systematic
review
following
PRISMA
guidelines
studies
published
from
2015
2021.
Seven
met
inclusion
criteria
were
analysed
content
analysis
thematic
synthesis.
Themes
centred
around
availability
systems
LMICs,
some
barriers
accessing
care,
need
for
be
congruent
communities
they
used
quality
apps.
The
offers
valuable
insight
towards
mediating
struggles
faced
implementation
appropriate
Frontiers in Psychiatry,
Journal Year:
2024,
Volume and Issue:
15
Published: Aug. 26, 2024
Introduction
University
students
are
particularly
susceptible
to
developing
high
levels
of
stress,
which
occur
when
environmental
demands
outweigh
an
individual’s
ability
cope.
The
growing
advent
mental
health
smartphone
apps
has
led
a
surge
in
use
by
university
seeking
ways
help
them
cope
with
stress.
Use
these
afforded
researchers
the
unique
collect
extensive
amounts
passive
sensing
data
including
GPS
and
step
detection.
Despite
this,
little
is
known
about
relationship
between
Further,
there
no
established
methodologies
or
tools
predict
stress
from
this
group.
Methods
In
study,
we
establish
clear
machine
learning-based
methodological
pipeline
for
processing
extracting
features
that
may
be
relevant
context
health.
Results
We
then
methodology
determine
students.
Discussion
doing
so,
offer
first
proof-of-principle
utility
our
highlight
can
indeed
digitally
phenotype
Clinical
trial
registration
Australia
New
Zealand
Trials
Registry
(ANZCTR),
identifier
ACTRN12621001223820.
BACKGROUND
Fostering
innovative
and
more
effective
interventions
to
support
active
ageing
strategies
since
youth
is
crucial
help
this
population
adopt
healthier
lifestyles
using
technologies
they
are
already
familiar
with.
mHealth,
especially
apps
wearables,
promising
tools
for
aspect
due
their
versatility
ease
of
use.
OBJECTIVE
The
aim
investigate
if
young
adults
(18-26
years
old)
use
or
wearables
monitor
improve
health
variables
(i.e.,
physical
activity,
diet
mental
health),
how,
also
assessing
most
used
wearables.
Finally,
the
importance
many
characteristics
functions
will
be
evaluated.
METHODS
This
cross-sectional
study
a
public
involvement
framework
an
anonymous
web
survey,
created
disseminated
on
Italian
territory
3
months.
It
was
made
5
sections:
I)
demographics,
II)
mobile
wearable
devices
activity
sports,
III)
diet,
IV)
health,
V)
preferences
about
devices.
RESULTS
A
total
693
questionnaires
were
analysed
sample
presented
equal
gender
distribution
(females:
52,4%).
Participants
app
46,2%,
while
respectively
8,6%
22,5%.
Moreover,
frequency
these
daily
base,
prevalent
Apps
identified
as
important
user-friendliness,
having
all
contents
free,
loading
speed
icon
clarity.
CONCLUSIONS
might
addressed
kick-off
expand
interest
in
other
variables,
such
health.
further
studies
should
deepen
factors
behind
motivation
adopting
exploring
possible
barriers
facilitators.
JMIR Medical Education,
Journal Year:
2024,
Volume and Issue:
unknown
Published: March 8, 2024
Despite
the
high
prevalence
of
mental
health
problems
among
medical
students
and
physicians,
help-seeking
remains
low.
Digital
approaches
offer
beneficial
opportunities
to
increase
well-being,
for
example,
via
mobile
apps.
This
study
aimed
assess
acceptance,
its
underlying
predictors,
tailored
e-mental
apps
by
focusing
on
stress
management
promotion
personal
skills.
From
November
2022
July
2023,
a
cross-sectional
was
conducted
with
245
at
University
Duisburg-Essen,
Germany.
Sociodemographic,
health,
eHealth-related
data
were
assessed.
The
Unified
Theory
Acceptance
Use
Technology
(UTAUT)
applied.
Differences
in
acceptance
examined
multiple
hierarchical
regression
analysis
conducted.
general
(mean
3.72,
SD
0.92).
Students
job
besides
school
reported
higher
(t107.3=-2.16;
P=.03;
Padj=.027;
Cohen
d=4.13)
as
well
loads
anxiety
symptoms
(t92.4=2.36;
P=.02;
Padj=.03;
d=0.35).
t
values
estimated
using
2-tailed
test.
Regression
revealed
that
significantly
predicted
(β=.11;
P=.045),
depressive
(β=-.11;
P=.05),
internet
(β=-.12;
P=.01),
digital
overload
(β=.1;
P=.03),
3
UTAUT
core
predictors-performance
expectancy
(β=.24;
P<.001),
effort
(β=.26;
social
influence
(β=.43;
P<.001).
predictors
lay
valuable
basis
development
implementation
within
education
foster
their
health.
More
research
validated
measures
is
needed
replicate
our
findings
further
investigate
students'
specific
needs
demands
regarding
framework
