March 26, 2025 • 14 mins
In today's digital age, mental health has become a significant concern worldwide. With the rapid advancement of Artificial Intelligence (AI), the question arises - Can AI be the lifesaver for mental health? In this video, we explore the potential of AI in revolutionizing the mental health landscape. From chatbots to machine learning algorithms, we delve into the various ways AI can help diagnose, treat, and prevent mental health issues. Join us as we discuss the possibilities and limitations of AI in mental health, and what the future may hold for this innovative technology.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:01):
Welcome, friends, to another episode of the
Telewellness Hub podcast.
I'm Marta Hamilton, your host,and today I want to dive into AI
a little bit more.
I got some great feedback andquestions from everyday
listeners who are consumers ofhealthcare, from healthcare
providers themselves.
There's a lot of questionsgoing on about AI.
(00:22):
I mean, it's affecting everypart of our lives, and so I
thought it would be good to do alittle bit of a follow-up today
.
So what I really am hoping totalk about today is really
having the opportunity to diveinto the world of AI and
challenge myself to find out ifit can actually be a lifesaver
(00:43):
for mental health, to find outif it can actually be a
lifesaver for mental health.
I think a lot of the discussionright now among providers is
will AI try to be a replacementfor mental health?
And I want to challenge us tothink about, well, challenge
myself too, to think about thepossibility that AI might
(01:05):
actually have the opportunity tobe a tool, maybe even a
life-saving tool for mentalhealth.
Mental health care in general,whether we have AI or not, is at
a really critical juncture.
With the increasing prevalenceof mental health disorders, the
need for innovative solutionshas never been more important.
(01:28):
I live in Texas, I'm a Texaslicensed professional counselor
and did you know, even though wehave so much tech flocking to
this area, so much innovationyou know we think of places like
Austin and all the innovationgoing on here the reality is
(01:49):
that Texas ranks last out of allthe states in the United States
.
We rank last in access tomental health care providers and
last and when you think of that, that's really just unreal to
think of that.
Even if you want to get, you'reready to take the step to find
(02:11):
a provider, it's we rank last inyour ability to access a
provider and there are hundredsof people for every one mental
health provider.
There are hundreds of people,so one provider.
We want to make an impact, wewant to have appointments
available, but the reality iswe're restricted by time.
We only have so many time slotsavailable per potential client
(02:37):
and we need technology.
Innovation is key, I think,when it comes to mental health
care and what's more is even ifyou have insurance.
Recent polls show that two outof three people who have
insurance say that, even withinsurance, mental health care is
(03:00):
too expensive because of maybeyou have a high deductible,
maybe even co-pays If you'reneeding to see a therapist once
a week and your co-pay is $35,that's a lot of money right now
that could be going towardsother essentials, especially
when we think of the cost ofgoods and inflation right now.
So it's really important, Ithink, as a provider and as
(03:23):
someone who has sought out andhas received therapy right I'm a
client and a provider and assomeone who has kids, my
daughters have received servicesfor their dyslexia which were
under a 504 considereddisability and now under an IEP
in Texas.
(03:43):
I just, it touches our livesmental health care.
It touches our lives, the needfor and innovation within this
realm.
So this is where I wanted to.
I did some research.
I wanted to talk a little bitmore about AI after our previous
episode.
If you haven't listened to thatepisode, you can find it on any
(04:05):
of the podcast episodes, justthe one prior to last week.
Last week was a really awesomeepisode about finding what sets
your heart on fire and adaptingto big change, and the one
before that it will be the oneon AI our first introduction
conversation about AI and so Iwant to talk a little bit more
about where AI comes in in termsof a technology that's being
(04:28):
hailed as a game changer in theindustry, but can AI really
transform treatment and supportsystems for the better?
So our first episode was justreally an overview and this
one's.
I really want to hone in onthis.
The potential is definitelyundeniable.
Based on my research, ai hasthe capability to analyze vast
amounts of data, providepersonalized treatment plans and
(04:51):
even offer potentially 24-7support to those in need.
So it's an opportunity torevolutionize the way we
approach mental health care,making it more efficient, more
effective and more accessible toall.
But before we dive into thatworld of AI, it's essential to
understand the context.
So mental health care hastraditionally been a
(05:12):
human-centric field, relyingheavily, as I mentioned earlier.
In a human-centric field,relying heavily, as I mentioned
earlier, on face-to-faceinteractions and individual
billable time slots types ofinteractions.
And while these methods mayhave a lot of benefits so many
(05:33):
and I've experienced thebenefits not just from a
provider standpoint, but from aclient they're often really time
consuming.
It can be expensive and limitedin their reach.
I, as a provider, want to reachmore people, but the way it has
been done traditionally, it'simpossible.
So what's the current state ofthe mental health care and how
(05:55):
can AI make a difference.
The mental health statistics arestaggering One in four people
in the United States willexperience a mental health
disorder, with depression andanxiety being the most common.
So take a room full of peopleone in four of them.
And traditional treatmentmethods often involve medication
(06:17):
, therapy or a combination ofboth.
However, these methods havetheir limitations and many
people struggle to access thecare that they need, and that's
where the emergence of AItechnologies offer a glimmer of
hope.
There's AI powered chatbots,for instance, and they can
provide immediate support andguidance to those who need it.
(06:39):
Predictive analytics can helpidentify high risk individuals,
enabling early intervention andprevention, and personalized
therapy programs can be tailoredto an individual's specific
needs and preferences.
Basically, we could take out alot of the guesswork, so that
when I usually would have anintake questionnaire like what
(07:02):
are you hoping to gain fromtherapy?
Rank the symptoms from a scaleof one to 10.
And imagine if I can utilize AIFor me it's incredible when I
think of it as a therapist andthey could take someone what
they're hoping to gain fromtheir time with you and turn it
into a personalized treatmentplan based on the best practices
(07:23):
, like what the research showsis the best and it's going to
help them the best, because whensomeone comes to me and they're
going to be my client, I wanttheir time and their money to
really make a difference intheir lives.
They're setting aside time outof their day to spend time
working on their mental health.
They're setting aside resourcesto do this.
I want to make sure that theirtime is well spent with me, and
(07:48):
I think AI can facilitate thatthrough this way.
And AI can also help addressthe shortage of mental health
professionals.
And AI can also help addressthe shortage of mental health
professionals, especially inrural and underserved areas, and
so, by automating routine tasks, ai can free up human resources
, allowing professionals tofocus more on complex cases and
(08:09):
provide more empathic care.
So when I take a closer look atsome of the exciting
applications of AI and mentalhealth, for me that's really
exciting to be able to do thosethings.
Chatbots like Wobot are alreadybeing used to provide emotional
support and guidance to users.
These chatbots can monitor auser's mood, offer personalized
(08:31):
advice and even detect earlywarning signs of mental health
disorders.
Predictive analytics is alsoanother promising area of
research.
By analyzing large data sets,ai algorithms can identify
patterns and behaviors that mayindicate a higher risk of mental
health disorders, and thisenables healthcare professionals
to intervene early, providingtargeted support and prevention
(08:54):
strategies.
With most things, earlypreventative care can make a
huge difference.
Personality insights are alsobeing used to develop more
effective therapy programs.
By analyzing an individual'spersonality traits, ai can
recommend personalized therapiesand coping strategies that are
(09:14):
even more likely to succeed.
So we've all taken those.
Like in business, for example,we can use our personality
traits to understand what kindof leader we are, what kind of
people we work best with, whatkind of careers are best for us.
Imagine if we can do this byanalyzing personality traits to
know what kind of therapy isgoing to be best for me.
However, you know, ai is notwithout its limitations, so one
(09:38):
of the significant concerns isthe potential for bias in AI
algorithms.
If these algorithms are trainedon biased data, they actually
may perpetuate harmfulstereotypes and exacerbate
existing inequalities.
This one's huge.
When I was in a PhD program, Iwanted to measure response bias
(09:59):
in assessments and I was lookingat things like IQ tests, which
are normed not on Spanishspeaking individuals, for
example, and so you have thesetests that are used in schools
for kids for the IQ, and whilethey may be um developed based
on an assessment of thousands ofindividuals who speak English.
(10:21):
When it comes to figuring outlike, okay, we're going to test,
when it comes to creating thistest, they'll say we're going to
test on about 30, 40 peoplefrom Puerto Rico and we're going
to whatever it shows the IQ isfor that group of populations
we're going to.
That's the norming group,that's what's going to apply to
every single child, every singlebilingual child who does a
(10:44):
Spanish a test, an IQ test inSpanish in the United States.
And, as we know, there are manydifferences.
There's bias based on whatcountry of origin, how the
language is spoken in the home,what they're exposed to.
There's just a lot ofdifferences.
There's bias based on whatcountry of origin, how the
language is spoken in the home,what they're exposed to.
There's just a lot ofdifferences.
So a little sidetrack, just alittle input on that.
When it comes to bias data, itexists, but imagine having these
(11:07):
large databases that have a lotof biases in them.
It could perpetuate theseharmful stereotypes.
It could actually do more harmthan good and create bigger gaps
and inequalities.
That's why, as mental healthproviders, I think it's really
important and not just as mentalhealth providers, as healthcare
providers in general, that wereally are paying attention to
(11:28):
AI and really being able tofigure out ways to ensure best
practices through it, and soanother ethical dilemma is the
need for human oversight.
That brings me to that inAI-driven mental health care,
while AI can provide immediatesupport, it's essential to have
(11:51):
a human professional or manyhuman professionals, for that
matter involved in thedecision-making process to
ensure that complex cases arehandled with empathy and
compassion, because AI isultimately programmed right.
It's programmed Um.
Someone needs to teach AI howto think and respond Um, but
(12:13):
there are.
There are ways.
People are so unique thatthere's not a one size fits all,
and that's where we need ahuman uh to really be able to
oversee the AI driven mentalhealth care.
Despite these challenges, thereare numerous examples of
successful AI implementations inmental health.
The UK's national healthservice, for instance, has
(12:34):
launched over has launchedseveral AI powered chatbots to
provide emotional support topatients.
In the US, companies likeMindStrong Health are using AI
to develop more effectivetherapy programs for individuals
with mental health disorders.
Research collaborations betweentech companies and healthcare
professionals are also startingto gain some momentum.
Collaborations between techcompanies and healthcare
(12:55):
professionals are also startingto gain some momentum.
These collaborations aredriving innovation and ensuring
that AI solutions areevidence-based while being
patient-centric.
I think that's the key isfinding that balance Like let's
balance the tech, the evidenceand put the patient first.
So what does the future hold forAI and mental health?
(13:16):
While there are risks andchallenges, the potential
benefits are undeniable.
Ai can augment and increasehuman care.
It can provide more efficient,effective and accessible support
systems.
However, it's essential thatremember that AI is a tool.
It's not a replacement forhuman care.
The human touch is critical inmental health care so critical
(13:38):
and AI should be used to supportand enhance human services, not
replace them.
As we move forward, it'scrucial to prioritize
transparency, accountability andethical responsibility in AI
development, and by doing so, Ibelieve that we can harness the
power of AI to transform mentalhealth care, making it more
inclusive, more compassionateand more effective.
(14:01):
Thanks for joining me on thisjourney into the world of AI and
mental health.
If you're interested inlearning more, I'd love to hear
your thoughts in the commentsbelow or send a message directly
to me.
My email ismartatelawalmushubcom.
Don't forget to check out othervideos on technology and
healthcare, and let's keepexploring the exciting
possibilities of AI and mentalhealthcare together.
(14:23):
Let's keep the conversationgoing.
Share your insight in thecomments, subscribe for more
deep dives into tech andwellness, and stay tuned as we
explore the future of AI andhealthcare.
Until next time, take care andkeep questioning the
possibilities.
Welcome, friends, to another episode of the
Telewellness Hub podcast.
I'm Marta Hamilton, your host,and today I want to dive into AI
a little bit more.
I got some great feedback andquestions from everyday
listeners who are consumers ofhealthcare, from healthcare
providers themselves.
There's a lot of questionsgoing on about AI.
(00:22):
I mean, it's affecting everypart of our lives, and so I
thought it would be good to do alittle bit of a follow-up today
.
So what I really am hoping totalk about today is really
having the opportunity to diveinto the world of AI and
challenge myself to find out ifit can actually be a lifesaver
(00:43):
for mental health, to find outif it can actually be a
lifesaver for mental health.
I think a lot of the discussionright now among providers is
will AI try to be a replacementfor mental health?
And I want to challenge us tothink about, well, challenge
myself too, to think about thepossibility that AI might
(01:05):
actually have the opportunity tobe a tool, maybe even a
life-saving tool for mentalhealth.
Mental health care in general,whether we have AI or not, is at
a really critical juncture.
With the increasing prevalenceof mental health disorders, the
need for innovative solutionshas never been more important.
(01:28):
I live in Texas, I'm a Texaslicensed professional counselor
and did you know, even though wehave so much tech flocking to
this area, so much innovationyou know we think of places like
Austin and all the innovationgoing on here the reality is
(01:49):
that Texas ranks last out of allthe states in the United States
.
We rank last in access tomental health care providers and
last and when you think of that, that's really just unreal to
think of that.
Even if you want to get, you'reready to take the step to find
(02:11):
a provider, it's we rank last inyour ability to access a
provider and there are hundredsof people for every one mental
health provider.
There are hundreds of people,so one provider.
We want to make an impact, wewant to have appointments
available, but the reality iswe're restricted by time.
We only have so many time slotsavailable per potential client
(02:37):
and we need technology.
Innovation is key, I think,when it comes to mental health
care and what's more is even ifyou have insurance.
Recent polls show that two outof three people who have
insurance say that, even withinsurance, mental health care is
(03:00):
too expensive because of maybeyou have a high deductible,
maybe even co-pays If you'reneeding to see a therapist once
a week and your co-pay is $35,that's a lot of money right now
that could be going towardsother essentials, especially
when we think of the cost ofgoods and inflation right now.
So it's really important, Ithink, as a provider and as
(03:23):
someone who has sought out andhas received therapy right I'm a
client and a provider and assomeone who has kids, my
daughters have received servicesfor their dyslexia which were
under a 504 considereddisability and now under an IEP
in Texas.
(03:43):
I just, it touches our livesmental health care.
It touches our lives, the needfor and innovation within this
realm.
So this is where I wanted to.
I did some research.
I wanted to talk a little bitmore about AI after our previous
episode.
If you haven't listened to thatepisode, you can find it on any
(04:05):
of the podcast episodes, justthe one prior to last week.
Last week was a really awesomeepisode about finding what sets
your heart on fire and adaptingto big change, and the one
before that it will be the oneon AI our first introduction
conversation about AI and so Iwant to talk a little bit more
about where AI comes in in termsof a technology that's being
(04:28):
hailed as a game changer in theindustry, but can AI really
transform treatment and supportsystems for the better?
So our first episode was justreally an overview and this
one's.
I really want to hone in onthis.
The potential is definitelyundeniable.
Based on my research, ai hasthe capability to analyze vast
amounts of data, providepersonalized treatment plans and
(04:51):
even offer potentially 24-7support to those in need.
So it's an opportunity torevolutionize the way we
approach mental health care,making it more efficient, more
effective and more accessible toall.
But before we dive into thatworld of AI, it's essential to
understand the context.
So mental health care hastraditionally been a
(05:12):
human-centric field, relyingheavily, as I mentioned earlier.
In a human-centric field,relying heavily, as I mentioned
earlier, on face-to-faceinteractions and individual
billable time slots types ofinteractions.
And while these methods mayhave a lot of benefits so many
(05:33):
and I've experienced thebenefits not just from a
provider standpoint, but from aclient they're often really time
consuming.
It can be expensive and limitedin their reach.
I, as a provider, want to reachmore people, but the way it has
been done traditionally, it'simpossible.
So what's the current state ofthe mental health care and how
(05:55):
can AI make a difference.
The mental health statistics arestaggering One in four people
in the United States willexperience a mental health
disorder, with depression andanxiety being the most common.
So take a room full of peopleone in four of them.
And traditional treatmentmethods often involve medication
(06:17):
, therapy or a combination ofboth.
However, these methods havetheir limitations and many
people struggle to access thecare that they need, and that's
where the emergence of AItechnologies offer a glimmer of
hope.
There's AI powered chatbots,for instance, and they can
provide immediate support andguidance to those who need it.
(06:39):
Predictive analytics can helpidentify high risk individuals,
enabling early intervention andprevention, and personalized
therapy programs can be tailoredto an individual's specific
needs and preferences.
Basically, we could take out alot of the guesswork, so that
when I usually would have anintake questionnaire like what
(07:02):
are you hoping to gain fromtherapy?
Rank the symptoms from a scaleof one to 10.
And imagine if I can utilize AIFor me it's incredible when I
think of it as a therapist andthey could take someone what
they're hoping to gain fromtheir time with you and turn it
into a personalized treatmentplan based on the best practices
(07:23):
, like what the research showsis the best and it's going to
help them the best, because whensomeone comes to me and they're
going to be my client, I wanttheir time and their money to
really make a difference intheir lives.
They're setting aside time outof their day to spend time
working on their mental health.
They're setting aside resourcesto do this.
I want to make sure that theirtime is well spent with me, and
(07:48):
I think AI can facilitate thatthrough this way.
And AI can also help addressthe shortage of mental health
professionals.
And AI can also help addressthe shortage of mental health
professionals, especially inrural and underserved areas, and
so, by automating routine tasks, ai can free up human resources
, allowing professionals tofocus more on complex cases and
(08:09):
provide more empathic care.
So when I take a closer look atsome of the exciting
applications of AI and mentalhealth, for me that's really
exciting to be able to do thosethings.
Chatbots like Wobot are alreadybeing used to provide emotional
support and guidance to users.
These chatbots can monitor auser's mood, offer personalized
(08:31):
advice and even detect earlywarning signs of mental health
disorders.
Predictive analytics is alsoanother promising area of
research.
By analyzing large data sets,ai algorithms can identify
patterns and behaviors that mayindicate a higher risk of mental
health disorders, and thisenables healthcare professionals
to intervene early, providingtargeted support and prevention
(08:54):
strategies.
With most things, earlypreventative care can make a
huge difference.
Personality insights are alsobeing used to develop more
effective therapy programs.
By analyzing an individual'spersonality traits, ai can
recommend personalized therapiesand coping strategies that are
(09:14):
even more likely to succeed.
So we've all taken those.
Like in business, for example,we can use our personality
traits to understand what kindof leader we are, what kind of
people we work best with, whatkind of careers are best for us.
Imagine if we can do this byanalyzing personality traits to
know what kind of therapy isgoing to be best for me.
However, you know, ai is notwithout its limitations, so one
(09:38):
of the significant concerns isthe potential for bias in AI
algorithms.
If these algorithms are trainedon biased data, they actually
may perpetuate harmfulstereotypes and exacerbate
existing inequalities.
This one's huge.
When I was in a PhD program, Iwanted to measure response bias
(09:59):
in assessments and I was lookingat things like IQ tests, which
are normed not on Spanishspeaking individuals, for
example, and so you have thesetests that are used in schools
for kids for the IQ, and whilethey may be um developed based
on an assessment of thousands ofindividuals who speak English.
(10:21):
When it comes to figuring outlike, okay, we're going to test,
when it comes to creating thistest, they'll say we're going to
test on about 30, 40 peoplefrom Puerto Rico and we're going
to whatever it shows the IQ isfor that group of populations
we're going to.
That's the norming group,that's what's going to apply to
every single child, every singlebilingual child who does a
(10:44):
Spanish a test, an IQ test inSpanish in the United States.
And, as we know, there are manydifferences.
There's bias based on whatcountry of origin, how the
language is spoken in the home,what they're exposed to.
There's just a lot ofdifferences.
There's bias based on whatcountry of origin, how the
language is spoken in the home,what they're exposed to.
There's just a lot ofdifferences.
So a little sidetrack, just alittle input on that.
When it comes to bias data, itexists, but imagine having these
(11:07):
large databases that have a lotof biases in them.
It could perpetuate theseharmful stereotypes.
It could actually do more harmthan good and create bigger gaps
and inequalities.
That's why, as mental healthproviders, I think it's really
important and not just as mentalhealth providers, as healthcare
providers in general, that wereally are paying attention to
(11:28):
AI and really being able tofigure out ways to ensure best
practices through it, and soanother ethical dilemma is the
need for human oversight.
That brings me to that inAI-driven mental health care,
while AI can provide immediatesupport, it's essential to have
(11:51):
a human professional or manyhuman professionals, for that
matter involved in thedecision-making process to
ensure that complex cases arehandled with empathy and
compassion, because AI isultimately programmed right.
It's programmed Um.
Someone needs to teach AI howto think and respond Um, but
(12:13):
there are.
There are ways.
People are so unique thatthere's not a one size fits all,
and that's where we need ahuman uh to really be able to
oversee the AI driven mentalhealth care.
Despite these challenges, thereare numerous examples of
successful AI implementations inmental health.
The UK's national healthservice, for instance, has
(12:34):
launched over has launchedseveral AI powered chatbots to
provide emotional support topatients.
In the US, companies likeMindStrong Health are using AI
to develop more effectivetherapy programs for individuals
with mental health disorders.
Research collaborations betweentech companies and healthcare
professionals are also startingto gain some momentum.
Collaborations between techcompanies and healthcare
(12:55):
professionals are also startingto gain some momentum.
These collaborations aredriving innovation and ensuring
that AI solutions areevidence-based while being
patient-centric.
I think that's the key isfinding that balance Like let's
balance the tech, the evidenceand put the patient first.
So what does the future hold forAI and mental health?
(13:16):
While there are risks andchallenges, the potential
benefits are undeniable.
Ai can augment and increasehuman care.
It can provide more efficient,effective and accessible support
systems.
However, it's essential thatremember that AI is a tool.
It's not a replacement forhuman care.
The human touch is critical inmental health care so critical
(13:38):
and AI should be used to supportand enhance human services, not
replace them.
As we move forward, it'scrucial to prioritize
transparency, accountability andethical responsibility in AI
development, and by doing so, Ibelieve that we can harness the
power of AI to transform mentalhealth care, making it more
inclusive, more compassionateand more effective.
(14:01):
Thanks for joining me on thisjourney into the world of AI and
mental health.
If you're interested inlearning more, I'd love to hear
your thoughts in the commentsbelow or send a message directly
to me.
My email ismartatelawalmushubcom.
Don't forget to check out othervideos on technology and
healthcare, and let's keepexploring the exciting
possibilities of AI and mentalhealthcare together.
(14:23):
Let's keep the conversationgoing.
Share your insight in thecomments, subscribe for more
deep dives into tech andwellness, and stay tuned as we
explore the future of AI andhealthcare.
Until next time, take care andkeep questioning the
possibilities.
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