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1. 90 © 2023 Indian Journal of Psychiatric Nursing | Published by Wolters Kluwer ‑ Medknow
Artificial Intelligence in Mental Health care
relapses of bipolar disorder.[9]
However, recent studies
found that AI models have variable performance in
diagnosing mental illness.[8]
Therapies
Patients can now receive cognitive behavioral therapy
treatment from AI‑powered virtual therapists such as
Woebot.[10]
Patients can communicate with these virtual
therapists by voice, video, or chat anytime.[11]
Similarly,
AI models are tested to deliver micro‑intervention for
parents[4]
and also significantly reduce the symptoms
of anxiety and depression during the COVID‑19
pandemic.[12]
AI‑based virtual reality therapy allows patients to
experience and confront their fears in a controlled and
safe environment. It is widely used for patients with
anxiety, phobia, and PTSD.[13]
Further, industrial AI
efficiently enhances workers’ mental health and addresses
a variety of mental health concerns.[14,15]
Speech analysis technology uses machine learning
algorithms to analyze speech patterns and identify
emotional states. This technology helps to identify
patients who are at risk of depression or anxiety and also
be used to monitor the effectiveness of therapy.[16]
Challenges
Because mental illnesses are highly subjective, have
complicated symptoms, differ from person to person,
and have strong sociocultural linkages, their diagnosis
requires thorough investigation.[17]
Joyce et al. argue
that the mental illness etiology, signs and symptoms,
and outcomes are highly interrelated. Further, the
determinants of mental illness are multi‑factorial,
i.e. biological, social, and psychological. Hence, the AI
models’ understandability of mental illness needs to be
heightened.[18]
Suppose an AI model is prepared with responses
from unauthentic data. In that case, it can offer false
information about the illness and improper guidance,
possibly harmful to persons with mental illness.[19,20]
The difficulties that AI in mental health must overcome
before it can contribute to a strong base as a support
tool in mental health management are indicated by the
absence of information to ensure reproducibility and
transparency.[21]
Based on nonrepresentative samples, there is a
possibility of creating biased models. Older adults have
been demonstrated to be capable of learning and using
tools with specialized programs; however, they are
Viewpoint
Mental health is one of the most important yet often
overlooked aspects of our well‑being. Due to
the shortage of mental health specialists and the rising
incidence of mental health problems, many people have
difficulty getting the mental health care they require.
Hence, there is a growing need for more effective,
affordable, and accessible forms of mental health
support. This is where artificial intelligence (AI) comes
in. This technology is changing how we think about
mental health and offers new hope to those struggling. In
this article, we will explore AI’s application, challenges,
and future concerns in mental health.
What is Artificial Intelligence?
According to the English Oxford Living Dictionary, AI is
“The theory and development of computer systems able
to perform tasks normally requiring human intelligence,
such as visual perception, speech recognition,
decision‑making, and translation between languages.”[1]
There are two types of AI. (i) Narrow (Weak) AI can
perform only a limited set of predetermined functions,
e.g. Apple’s Siri, Amazon’s Alexa. (ii) General (Strong)
AI is considered to match the human mind’s capacity for
independent thought because of its capability to process
a wide range of inputs.[2]
In 1950, Alan Turing introduced the Turing test to
determine if a computer could demonstrate the same
intelligence as a human. In 1956, John McCarthy coined
the term “Artificial Intelligence” at the first‑ever AI
conference at Dartmouth College.[3]
Since then, scientists
have been trying to develop AI models that can be applied
to many sectors and industries, such as automotive,
finance, and health care. The most common AI‑based
technologies used in health care include chatbots, virtual
reality therapy, and machine learning algorithms.
Application in Mental Healthcare
Screening
AI helps in understanding mental illness,[4]
and it is
used for the screening of severe mental illness[5]
with
clinical magnetic resonance imaging scans,[6]
bipolar
disorder,[5]
depression in old age[4,7]
Alzheimer’s,
mild cognitive impairment, autism spectrum disorder,
obsessive–compulsive disorder, and posttraumatic stress
disorder (PTSD).[5]
AI can examine data from various sources, including
social media, to find patterns of activity that might be
related to mental health problems. This data helps to
identify the high‑risk individuals;[8]
predict depressive

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Indian Journal of Psychiatric Nursing ¦ Volume 20 ¦ Issue 1 ¦ January-June 2023
at significant risk of being excluded from AI studies
due to their limited access to and familiarity with
technologies.[22]
There are no established guidelines for the appropriate
use of data standards and nursing terminologies. Nursing
documentation must be consistent even within a facility
adopting standard nursing terminology. Nursing data
cannot be routinely used for quality measurement or
improvement because of poor recordkeeping and a lack
of consensus on standards.[23]
Future
Earning the trust and confidence of clinicians should be
the foremost consideration in implementing any AI‑based
decision support system.[24]
While AI developers are keen
to concentrate on person‑like solutions, partnerships
with mental health professionals are necessary to ensure
a person‑centered approach to future mental health care
is required.[25]
Studies emphasize the value of contextualizing
interventions and recommend that scalable and
evidence‑based mental health care be available to
large populations through AIs.[12]
App Advisor is a
creative project of the App Evaluation Model that the
American Psychiatric Association developed to evaluate
applications for their effectiveness, acceptability, safety,
and capacity to provide mental health care.[20]
At the same time, strong laws are needed to protect
individuals or groups from harm by accessing, disclosing,
or manipulating mental health data.[26,27]
AI cannot accurately diagnose mental illnesses, so it
cannot replace clinicians’ diagnoses soon. The underlying
difficulty in diagnosing mental illnesses using AI is not
technological or entirely data‑related but rather our
general understanding of mental illness.[17]
Many years of
therapeutic transcripts are required to offer an inexpensive
tool capable of delivering complex and tailored therapeutic
models with high fidelity, compassion, and perfect recall
that can simultaneously engage thousands of clients.[28]
Conclusion
AI is paving the way for more personalized, efficient,
and effective mental health care. To realize AI’s potential
while reducing the possible harm, substantial effort
should go toward the careful and thoughtful introduction
of these AI technologies into global mental health.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
G Balamurugan, M Vijayarani1
, G Radhakrishnan2
Assistant Professor of National Apex Coordinating Centre for
Tele MANAS, National Institute of Mental Health and Neuro
Sciences (NIMHANS), 1
Department of Mental Health Nursing,
ESIC College of Nursing, 2
Department of Nursing, National
Institute of Mental Health and Neuro Sciences (NIMHANS),
Bengaluru, Karnataka, India
Address for correspondence: Dr. G Balamurugan,
Assistant Professor of Nursing National Apex Coordinating
Centre for Tele MANAS, National Institute of Mental Health and
Neuro Sciences (NIMHANS), Bengaluru - 560 029. Karnataka,
India.
E‑mail: gsvbm@yahoo.co.in
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How to cite this article: Balamurugan G, Vijayarani M, Radhakrishnan G.
Artificial intelligence in mental health care. Indian J Psy Nsg 2023;20:90-2.
Submitted: 30‑May‑2023; Revised: 07-Jun-2023; Accepted: 10-Jun-2023; Published: 05-Jul-2023
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DOI:
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