Exploring the impact of generative AI tools on healthcare delivery in Tanzania
Journal of Health Organization and Management,
Год журнала:
2025,
Номер
unknown
Опубликована: Март 31, 2025
Purpose
This
study
explores
the
impact
of
generative
AI
tools
on
healthcare
delivery
in
Tanzania.
It
examines
its
potential
to
enhance
efficiency,
accessibility
and
decision-making
health
informatics
while
addressing
infrastructure,
ethics
equity
challenges
low-resource
settings.
Design/methodology/approach
A
mixed-methods
approach
was
employed,
combining
quantitative
surveys
with
100
respondents
qualitative
semi-structured
interviews
30
participants,
including
professionals
patients
from
urban
rural
areas
Quantitative
data
were
analysed
using
descriptive
inferential
statistics,
examined
thematic
analysis
identify
recurring
patterns
insights.
Findings
The
reveals
significant
disparities
digital
literacy
adoption
between
showing
higher
acceptance
than
patients.
While
ChatGPT
perceived
as
a
useful
tool
for
enhancing
delivery,
concerns
about
infrastructure
limitations,
privacy
algorithmic
bias
prominent.
Participants
highlighted
infrastructural
barriers,
such
unreliable
Internet
electricity,
major
adoption.
Originality/value
is
one
first
examine
role
like
system.
provides
empirical
insights
into
opportunities
barriers
integration
emphasizes
importance
localized,
equitable
ethical
implementations
tailored
specific
needs
underserved
areas.
Язык: Английский
Interactivity, humanness, and trust: a psychological approach to AI chatbot adoption in e-commerce
BMC Psychology,
Год журнала:
2024,
Номер
12(1)
Опубликована: Окт. 28, 2024
This
study
aims
to
investigate
the
impact
of
interactivity
and
perceived
humanness
on
trust
toward
AI
chatbots
in
e-commerce
setting.
Moreover,
this
also
examine
mediation
effect
relationship
between
intention
adopt
for
as
well
e-commerce.
used
a
time
lag
approach
collect
data
from
343
customers
southern
region
China.
The
were
collected
online
through
questionnaire
designed
Chinese
language
using
survey
firm.
findings
indicated
that
there
is
significant
chatbots.
mediating
relationships
In
addition,
found
moderating
influence
enjoyment
settings.
provides
unique
perspective
expectation-confirmation
theory
adopting
emerging
technologies
shopping
insights
designers
business
firms
develop
businesses
facilitate
chatbot
feature
Язык: Английский
AI-Assisted Emotion Recognition: Impacts on Mental Health Education and Learning Motivation
International Journal of Emerging Technologies in Learning (iJET),
Год журнала:
2023,
Номер
18(24), С. 34 - 48
Опубликована: Дек. 19, 2023
With
the
rapid
advancements
in
artificial
intelligence
(AI)
technology,
its
deployment
field
of
education
has
gained
considerable
attention,
particularly
context
mental
health
education.
Addressing
mounting
academic
and
social
pressures
faced
by
contemporary
students
necessitates
utilization
cutting-edge
techniques
to
accurately
discern
their
emotional
states
deliver
customized
learning
resources.
Existing
methodologies
for
often
fall
short
due
an
over-reliance
on
educators’
experience
observations,
as
well
challenges
handling
complex
multimodal
data.
This
research
aims
investigate
integration
audio-visual
features
using
a
transformer
architecture
emotion
recognition.
An
enhanced
probabilistic
matrix
factorization
(PMF)
model
been
concurrently
developed
facilitate
tailored
content
recommendations
students.
The
goal
is
provide
more
accurate
effective
approach
Язык: Английский
Mediating effects of artificial intelligence on the relationship between academic engagement and mental health among Chinese college students
Frontiers in Psychology,
Год журнала:
2024,
Номер
15
Опубликована: Ноя. 7, 2024
Introduction
Academic
engagement
of
Chinese
college
students
has
received
increasing
research
attention
due
to
its
impact
on
Students’
Mental
health
and
wellbeing.
The
emergence
artificial
intelligence
(AI)
technologies
marked
the
beginning
a
new
era
in
education,
offering
innovative
tools
approaches
enhance
learning.
Still,
it
can
be
viewed
from
positive
negative
perspectives.
This
study
utilizes
Theory
Planned
Behavior
(TPB)
as
theoretical
framework
analyze
mediating
role
students’
attitudes
toward
AI,
perceived
social
norms,
behavioral
control,
their
intention
use
AI
relationships
between
academic
health.
Methods
involved
total
2,423
with
mean
age
approximately
20.53
±
1.51
years.
survey
was
conducted
through
Questionnaire
Star,
using
secure
website
designed
specifically
for
study.
Hayes’
PROCESS
Macro
(Version
4.2)
Model
80
SPSS
29.0,
multivariate
regression
analysis
chain
mediation
model
that
allows
multiple
mediators
tested
sequentially,
been
used.
statistical
test
explored
direct
indirect
effects
(X)
mental
(Y)
series
mediators:
attitude
(M1),
subjective
norm
(M2),
control
over
(M3),
(M4).
Results
relationship
(β
=
0.0575;
p
<
0.05),
well
identifying
key
factors
such
0.1039;
0.05)
0.0672;
highlights
potential
enhancing
well-being.
However,
non-significant
0.0135),
norms
–0.0005),
suggest
more
is
needed
understand
nuances
these
fully.
Discussion
Overall,
contributes
growing
body
literature
education
offers
practical
implications
improving
support
settings.
Язык: Английский
Application of Computer Vision Techniques to Study the Relationship between Mental Stress and Pupil Diameter among Student Population
International Journal of Online and Biomedical Engineering (iJOE),
Год журнала:
2024,
Номер
20(08), С. 49 - 66
Опубликована: Май 21, 2024
Stress
is
a
state
of
mental
tension,
which
helps
us
to
cope
with
challenges
in
our
life.
It
makes
progressive
when
it
positive,
but
excessive
negative
stress
that
perseveres
for
long
time
leads
depressiveness.
Longer
stressed
stage
human
being
changes
the
size,
functionality
and
frequency
response
many
internal
external
body
parameters.
By
applying
computer
vision
techniques,
these
parameters
can
be
tracked
get
useful
information
about
affected
person.
Many
studies
show
pupil
diameter
varies
significantly
effect
stress.
Our
work
based
on
study
variation
diameters
not
university
students.
With
application
different
supervised
machine
learning
algorithms,
we
have
observed
dilates
more
case
students
than
non-stressed
We
also
found
pupils
they
were
positive
emotional
states
their
states.
This
will
helpful
researchers
who
are
working
field
emotion
detection
recognition
affective
disorder
analysis.
Язык: Английский