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The Economic Impact of Depression Treatment in India

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Can understanding the economic impact of depression treatment help alleviate the burden of this pervasive illness in India? This study cross-randomizes pharmacotherapy and livelihoods assistance among 1000 adults in Karnataka, showing benefits in reducing depression severity with combined interventions, although not significantly improving earnings or human capital investment.

Image courtesy of interviewee. November 6, 2024

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This video discusses the intersection of mental health and economics, emphasizing the importance of understanding mental health issues in the context of economic development. The speaker notes that awareness of mental illness has grown, particularly after the COVID-19 pandemic, but acknowledges that before, there was limited understanding within economic academic circles. The speaker highlights that people in lower-middle-income countries often face high rates of mental health issues, such as depression and anxiety, particularly linked to poverty.

The speaker explains their research approach, wearing two "hats": as a social scientist wanting to understand how economists should consider mental health and as a policymaker aiming to apply effective interventions within complex contexts. They outline two main pathways through which mental health impacts economic behaviors: the productivity channel (where depression affects job performance and decision-making) and the preference channel (where lack of motivation influences long-term planning and investment).

The findings from an intervention study revealed that combining pharmacotherapy with livelihood support led to improved mental health outcomes and longer-lasting effects. However, the livelihood intervention alone did not yield significant results. The speaker suggests that group interactions within the livelihood program might have helped individuals feel less isolated and prompted them to adhere better to their treatment regimens.

Further exploration showed positive effects on human capital investment in children, particularly among older children. While the study showed these interventions could work, it also highlighted the challenges in generalizing the findings and the need for continual monitoring of outcomes.

The speaker emphasizes the importance of recognizing the broader impacts of mental health interventions, not just on the individuals receiving treatment but also on their families and communities, thereby improving overall economic stability. This video concludes that effective strategies must be developed for scaling mental health interventions in community settings, utilizing existing infrastructure while addressing barriers to care, including stigma and lack of awareness.

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Here are five key points summarized from the video:

1. **Mental Health and Economic Well-being**: The speaker emphasizes the link between mental health and economic behavior, particularly noting that mental illnesses like depression and anxiety are prevalent in lower middle-income countries. They explain how mental health issues can impact people's economic choices and overall well-being.

2. **Research and Policy Integration**: The speaker discusses their dual role as both a researcher and a policymaker, trying to understand mental illness from an economic perspective while also considering practical interventions that can be implemented to help affected populations. They highlight the importance of utilizing existing tools shown to work in higher-income countries and adapting them to different convideos.

3. **Depression's Economic Channels**: Two main channels through which depression affects economic behavior are identified: the productivity channel (mental health symptoms impairing job performance and decision-making) and the preference channel (depression leading to a lack of motivation towards future investments). Both channels illustrate how mental health can influence economic outcomes such as employment, consumption, and investment decisions.

4. **Intervention Outcomes and Spillover Effects**: The study mentioned in the video indicates that providing pharmacotherapy alongside a livelihoods intervention resulted in improved mental health and economic outcomes. Notably, it suggests positive spillover effects on the children of individuals receiving treatment, particularly among older children transitioning between primary and secondary school.

5. **Barriers to Treatment**: The speaker outlines barriers to accessing mental health care that exist even within communities that have some existing infrastructure, such as stigma, lack of awareness about mental health, and the debilitating nature of depression itself. They stress the necessity of education, community support, and tailored systems to help individuals seek care effectively.

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Here are some key quotes from the video regarding mental health, economics, and their interplay:

1. **On the Understudied Nature of Mental Health in Economics**:
- "Mental health through the lens of economics and economic development... was, in my opinion, still understudied."

2. **Increased Awareness Post-COVID**:
- "I think people's awareness of the prevalence and human costs of mental illness has really increased after COVID."

3. **Correlation Between Poverty and Mental Illness**:
- "There is a positive correlation between poverty and affected disorders like depression and anxiety."

4. **Misconceptions about Depression and Economic Conditions**:
- "I thought that, you know, world country malaise... it's the reverse... people whose lives are really hard and complex... feel high rates of stress, depression, anxiety."

5. **Understanding Mental Illness in Economic Convideo**:
- "I want to understand how should economists think of mental illness... it is more than any other health condition that there are some unique features."

6. **Impact of Depression on Economic Behavior**:
- "A kind of crucial component of depression is anhedonia... [which] can directly impact economic choices and behaviors."

7. **Productivity and Preference Channels**:
- "Two pathways through which a disorder like depression can have an impact on economic choices, behaviors, and outcomes."

8. **The Importance of Treatment**:
- "Successfully inducing people with depression to seek treatment would... spill over on economic outputs such as labor market behavior, employment, income."

9. **Speculative Nature of Research Findings**:
- "I want to be very clear that all I am about to say is completely speculative."

10. **Human Capital Investment in Children**:
- "When we split children around their median age, we found that for older children... there are positive, statistically significant, but also big in economic terms, effects."

11. **Implications for Policy**:
- "When we target one outcome, which is... the mental wellbeing of adults, hopefully there are downstream positive impacts also on other people."

12. **On Existing Infrastructure for Mental Health Treatment**:
- "We were using the existing local infrastructure... we didn't go with the army of psychiatrists... we collaborated with the local NGO."

13. **Barriers to Seeking Treatment**:
- "There are three big barriers... lack of knowledge... reluctance to seek treatment... depression itself prevents you from seeking care."

14. **The Role of Social Workers**:
- "India has a structure... hundreds or thousands of social workers who cover a specific set of localities and families."

These quotes highlight the interconnection between mental health and economic development, emphasizing the importance of understanding mental illness within an economic framework and the implications for policy and treatment accessibility.

X-TIMESTAMP-MAP=LOCAL:00:00:00.000,MPEGTS:90000

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Really interested in, mental health through the lens

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of economics and economic development, which,

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at the time I started to work in this field, was,

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in my opinion, still understudied.

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Uh, I, I think people's awareness of the

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prevalence and, human costs

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of mental illness has really increased after covid.

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But before there was limited knowledge even in

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econ academic circles.

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And I felt that, no, this was really important.

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Uh, as, as, development economists, we want

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to like alleviate human suffering

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and bring, you know, happiness and wellbeing to people.

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And, I realized that, you know,

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many people in lower middle income countries suffer.

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In fact, one thing that I found really interesting

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and that I didn't know at the time is

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that there is a positive correlation between poverty

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and, affected disorders like depression and anxiety.

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When I started to work on this, I thought that, you know,

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depression is some kind of, you know, first,

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world country malaise, where we know we stare at the horizon

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and think about life's meaninglessness.

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Well, you know, we drink champagne or something like that.

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In fact, it's the reverse, which, which sort

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of makes sense in hindsight.

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It's, it is people whose lives are really hard and complex

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and who feel that they don't have a safety net.

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So any little shock can have, like, dramatic

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and disastrous consequences really feel high rates

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of no stress, depression, anxiety.

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And so as a development economist,

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it was seemed like first order to, to try

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and understand that when my research, I wear, sort

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of two hats.

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Uh, one is, the scientists, the social scientists.

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So I want to understand, how should economists think

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of mental illness?

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Uh, it is more, as I will talk about, you know,

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I believe it is more than any other health condition

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that there are some, you know, unique features that,

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that make it really important to understand within a context

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of, you know, what we call, like, you know, constraint,

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utility maximization.

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So what people want,

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and what people do to get what they want

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and what barriers they're facing.

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Uh, but at the same time, there's also the policymaker hat,

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which is, you know, a lot of people suffer.

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We have tools that, have been shown to work in,

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you know, in Europe, in the United States.

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Uh, how can we use those tools

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and apply them in a context

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where everything is much more complicated?

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Uh, so, so it's more kind of the pragmatic, aspect of,

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of, in social science.

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My, working hypothesis when I start

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to do research in mental health is that, there,

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there are some unique features of, of depression that

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directly feeds into economic behaviors.

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Uh, and if you think about the key symptoms of depression,

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it sort of makes sense,

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because, you know, a kind of a crucial component

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of depression is, anhedonia

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or the inability, sorry,

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I don't know if I'm pronouncing these words probably,

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but it's the inability to derive pleasure from lives.

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Uh, good things. Uh, so, so this feeling of, you know,

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basically lives, life's meaninglessness

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and worthlessness that can directly,

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impact economic choices

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and behaviors in a way that I'm gonna describe in a minute,

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are the key, symptoms.

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Uh, you know, disruptive eating

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or sleeping patterns, impaired cognition

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and decision making, inability

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to concentrate, or rumination.

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So all of these things can have, clear,

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and potentially big impacts on economic outcomes, such

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as, consumption income, human capital,

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but also economic choices as the choice of how much, when

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and where to work, the choice of whether to consume, save,

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and invest, the choice of what to do for one's families

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and one's children's wellbeing.

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And so, as economists, we like to sort of, you know,

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group things into, into labels.

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And so if we wanna do that, we can say that there's a,

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productivity channel

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through which depression can affect economic,

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choices, behaviors, and outcomes.

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And this is this idea that, you know, if I'm tired

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or sluggish or unsure

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or prone to make mistakes, that is going

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to affect my performance, both on the job,

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but also my performance in when I have

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to make important decisions for the present

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and future wellbeing of which is investments.

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So, so, so employment investments,

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labor outcomes are all affected

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through this productivity channel.

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And then there's the preference channel, which is like,

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you know, if nothing is worth it, very, very simplified,

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you know, what's the point of it?

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All right? At the core

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of investment decision is this trade off between, you know,

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bearing a costs right now for a future reward,

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which is not even certain in many cases.

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And so, if you are thinking about, you know,

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what's the point of anything, then why should I, you know,

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make a sacrifice now for, you know, in order to,

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for me or my children to achieve a better, future.

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Uh, so this, again, this components pessimism,

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this inability to feel pleasure might have,

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potentially an impact on investment.

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And so these are like two, this is a generalization

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of course, and it might be on the channels,

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but this productivity

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and preferences channels are potentially pathways

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through which,

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a disorder like depression can have an impact on economic

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choices, behaviors, and outcomes.

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Plus, you know, key hypothesis was that,

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we would be able to entice people

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with depression to seek treatment.

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It's kind of more like the practical, the policy aspects

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of the story, which, if I have time,

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I think I would like to talk more

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because it's, it's an interesting, point, in terms

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of the more economic hypothesis, was that,

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in successfully inducing people with depression

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to seek treatment would not only

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improve their mental wellbeing,

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but it would also spill over on economic outputs such as,

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labor market behavior, employment, income,

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therefore consumption and, potentially also investment.

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So again, this idea that this combination

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of being better at, you know, producing, making choices,

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and also caring more, if I want to use a very basic language

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to, to summarize this productivity

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and preferences, pathways would result in higher employment,

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income consumption, and higher investment in, you know,

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whatever it is that is important

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for those people and their families.

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I want to, be very clear that all I am about

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to say is completely speculative.

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And that's one of the limitations of the, you know,

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this type of interventions that we do.

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We design interventions and we look at effects,

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but then, you know, whether something happened in one way

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or the other, why that happened is, you know, is,

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is highly speculative.

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So, so we discover, and,

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and with another, caveat or,

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or, you know, important clarification,

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which is this idea that in our study, we

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provided pharmacotherapy in the form of antidepressants,

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and we provided this very light touch livelihoods

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intervention, which was a combination of two group meetings

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that was centered around, income generating processes.

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So people would talk about, you know, this is what I want.

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Uh, these are the obstacles that I have to achieving.

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You know, I wanna have a job, or I wanna have,

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I want start up a business,

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or I would like to have a better job,

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and here's why, you know,

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these are the difficulties I'm phasing.

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And then they would brainstorm together on how to

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solve these problems, followed by an individualized,

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intervention where members of the NGO that we work

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with were working with people to sort of

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make whatever they wanted happen.

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It were the two things that we did.

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And we cross randomized it so that some groups

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that only pharmacotherapy, some groups that only

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what is called this livelihood intervention

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and some group, achieved both.

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So now the livelihood intervention on its own

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didn't do much.

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Uh, in fact, you know, if we know, if we test the hypothesis

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that it had any impacts, we,

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we don't find any evidence that it does.

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At the same time, when,

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the livelihood intervention was paired

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with the pharmacotherapy intervention, we found

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that the effects of pharmacotherapy were, bigger,

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both in terms of, the impacts on depression,

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but also on the duration of this impact.

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So people were feeling much better, where when, in addition

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to, to, to being offered for psychotherapy,

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they were also offered

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to participate in this livelihood intervention,

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and they felt much better.

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But also for, for, for more time. For longer time.

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Uh, now why is that the case?

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So, as I said, you know, we don't know what we speculate

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and what we actually want

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to investigate in the future research is that,

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this livelihood intervention,

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and in particular, the group meeting component, had some

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function that very loosely resembled some aspects of,

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of group psychotherapy.

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You know, people were not

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provided with no insights into cognitive behavioral therapy.

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They were in thought, you know, tools to like manage stress

205
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or to reframe their thoughts.

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But at the same time, I think the acts of being together,

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realizing that they weren't alone,

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there were other people who were going through, you know,

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something similar, this idea of, both acknowledging

210
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and voicing obstacles,

211
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but also reframing them in a way of, you know, here's

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what we could do to solve this problem

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or to figure this out, could potentially have had, kind

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of a, a complimentary effect on pharmacotherapy,

215
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both through, for example, making them more likely

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to take the medicines.

217
00:10:07.885 --> 00:10:10.785
So at a practical level, in fact, we have some evidence

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that, adherence

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to medication was a bit higher in the group

220
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that was being offered both treatments,

221
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but also, as I said, more akin to this idea of, of therapy

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that kind of helps you think about, you know, your life

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and your problems in a slightly different way.

224
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Or, you know, even this idea of just not being alone,

225
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just feeling that you are not a weird,

226
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there are many other people

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who are going through something similar.

228
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Again, we cannot tell what exactly of these components

229
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or if they work at all, but that's our architecture.

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When we look at the impacts on

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what we call human capital investment in children,

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which is this combination of enrolling children in school,

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children attending classes, doing their homework,

234
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and not working, so not providing child labor.

235
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We find that,

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if we lump all children in age school years together,

237
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so I think five to 18,

238
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we do not find statistically significant average effects.

239
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So the effects are positive,

240
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but no, they're not strong enough

241
00:11:10.765 --> 00:11:12.225
to be statistically significant.

242
00:11:13.565 --> 00:11:16.305
At the same time, when we split children

243
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around their median age, which is 12, we found that

244
00:11:20.125 --> 00:11:25.065
for older children, so children aged 13 to 18,

245
00:11:25.075 --> 00:11:28.705
there are positive, statistically significant,

246
00:11:28.765 --> 00:11:31.865
but also like big in economic terms, effects.

247
00:11:31.865 --> 00:11:32.865
So both economically

248
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and statistically significant positive impact on this kind

249
00:11:36.425 --> 00:11:38.465
of composite index of human capital investments,

250
00:11:38.465 --> 00:11:39.705
which is excellent news.

251
00:11:40.285 --> 00:11:42.505
So first question is like, you know, what is going on?

252
00:11:42.965 --> 00:11:44.265
Uh, so, so we wanted to sort

253
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of understand why these effects are

254
00:11:46.385 --> 00:11:47.585
concentrated among older the children.

255
00:11:48.235 --> 00:11:49.785
Again, we don't know for sure,

256
00:11:50.045 --> 00:11:53.225
but a good candidate for this heterogeneity,

257
00:11:53.465 --> 00:11:57.365
why only all older children benefit is that actually

258
00:11:58.065 --> 00:12:00.645
all these outcomes that we were considering being enrolled

259
00:12:00.645 --> 00:12:02.005
in school, attending school and,

260
00:12:02.105 --> 00:12:04.885
and, child labor, not so much homework,

261
00:12:05.295 --> 00:12:07.485
there wasn't really much room for improvements

262
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among the younger children

263
00:12:08.795 --> 00:12:11.365
because, you know, nobody was really working after school.

264
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So there was no child labor among the, no,

265
00:12:13.945 --> 00:12:16.405
the younger children, and pretty much everybody was

266
00:12:16.645 --> 00:12:18.045
enrolled and attending school.

267
00:12:18.145 --> 00:12:20.285
So, so, so maybe there were some benefits,

268
00:12:20.425 --> 00:12:23.965
but not along the outcomes that we were able to measure.

269
00:12:24.505 --> 00:12:26.045
Uh, and this is a common phenomenon.

270
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It's not only a phenomenon in India,

271
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it's a broader phenomenon in many lower middle income

272
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countries, at which now we've done huge improvements in

273
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getting children to complete primary school,

274
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and there is a big drop in attendance, as,

275
00:12:39.195 --> 00:12:41.925
they graduate from primary to secondary education.

276
00:12:42.145 --> 00:12:45.085
And so we think that's what we hope that what we are seeing

277
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is that we are getting some of these children

278
00:12:48.745 --> 00:12:52.125
to not drop out of school as they transition from primary

279
00:12:52.265 --> 00:12:54.805
to secondary education and all these following things.

280
00:12:54.825 --> 00:12:56.725
So they are enrolled, they attend

281
00:12:56.725 --> 00:12:59.165
because they spend more time in school than perhaps they

282
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spend less time, working.

283
00:13:02.095 --> 00:13:06.315
Um, however, as always, you know,

284
00:13:06.315 --> 00:13:07.435
this is just one data point.

285
00:13:07.595 --> 00:13:09.555
So it's one study with a thousand households.

286
00:13:09.555 --> 00:13:10.595
You know, India is a big country.

287
00:13:10.815 --> 00:13:14.275
So, so no, we should always be, careful about, you know,

288
00:13:14.275 --> 00:13:17.075
generalizing for one study also.

289
00:13:17.385 --> 00:13:21.115
This is a good and, promising starting point,

290
00:13:21.495 --> 00:13:22.795
but who knows what's happening, right?

291
00:13:22.855 --> 00:13:26.595
All we can tell is that two years of, you know, one

292
00:13:26.595 --> 00:13:28.635
or two years after the end of this intervention,

293
00:13:28.935 --> 00:13:31.595
we see this increase in human capital investment

294
00:13:31.705 --> 00:13:33.315
that parents do for older children.

295
00:13:34.145 --> 00:13:35.795
It's a promising first step,

296
00:13:36.535 --> 00:13:40.035
but we must learn what happens later, right?

297
00:13:40.055 --> 00:13:42.075
So may maybe they enrolled them, you know,

298
00:13:42.075 --> 00:13:43.515
in the first grade of secondary school,

299
00:13:43.535 --> 00:13:44.915
and then these effects faded out

300
00:13:45.075 --> 00:13:47.475
because as their, you know, mental health improvement faded

301
00:13:47.475 --> 00:13:49.475
out, and also their attention to the future

302
00:13:49.535 --> 00:13:51.715
of their children, you know, went back to, to, to,

303
00:13:51.775 --> 00:13:52.835
to the baseline.

304
00:13:53.175 --> 00:13:55.555
So we don't know. It seems definitely positive,

305
00:13:55.555 --> 00:13:57.075
because if you never take the first step,

306
00:13:57.075 --> 00:13:59.395
then you will not be able to take a second step.

307
00:13:59.415 --> 00:14:00.555
But, but we need more data

308
00:14:01.095 --> 00:14:02.995
and we need to re survey these families

309
00:14:02.995 --> 00:14:05.315
and the children to see what is really happening now

310
00:14:05.315 --> 00:14:06.875
that they're young, men

311
00:14:06.935 --> 00:14:08.715
and women out, you know, in the world.

312
00:14:09.395 --> 00:14:13.275
A very, kind of practical, compelling

313
00:14:13.275 --> 00:14:15.515
and important first of the policy implications.

314
00:14:15.735 --> 00:14:19.155
The one is kind of, sort of,

315
00:14:19.665 --> 00:14:21.075
hopefully becoming obvious.

316
00:14:21.135 --> 00:14:24.635
Now, this idea that when we target one outcome, which is,

317
00:14:24.635 --> 00:14:27.475
you know, the mental wellbeing of, of adults,

318
00:14:27.705 --> 00:14:29.475
hopefully there are downstream

319
00:14:29.995 --> 00:14:31.715
positive impacts also on other people,

320
00:14:31.715 --> 00:14:33.515
what we call positive spillover reflect.

321
00:14:33.815 --> 00:14:36.675
And so if you really wanna have a full understanding

322
00:14:36.775 --> 00:14:39.515
of the impacts of these interventions, we need to, we need

323
00:14:39.515 --> 00:14:41.875
to go beyond the sort of primary outcomes.

324
00:14:42.415 --> 00:14:43.915
Uh, and this is important also

325
00:14:43.915 --> 00:14:45.635
for practical concerns, right?

326
00:14:45.635 --> 00:14:47.195
Because, you know, we have policy

327
00:14:47.195 --> 00:14:48.515
makers have limited budgets.

328
00:14:48.615 --> 00:14:50.875
So not only do they want to find effective policies,

329
00:14:51.005 --> 00:14:52.485
but the policies that have the highest

330
00:14:52.485 --> 00:14:53.765
certain of their investment.

331
00:14:53.945 --> 00:14:58.805
And so, if I can show that not only are adults better for up

332
00:14:58.805 --> 00:15:01.205
to two years after being treated with this course

333
00:15:01.205 --> 00:15:03.405
of antidepressants, but I, we can see

334
00:15:03.405 --> 00:15:04.805
that potentially their adult,

335
00:15:04.805 --> 00:15:07.725
their older children are on a pathway for better future.

336
00:15:08.225 --> 00:15:10.645
It means that the potential long-term benefits

337
00:15:10.645 --> 00:15:13.445
of this intervention are much higher than if we just said,

338
00:15:13.445 --> 00:15:15.685
look, you know, these people have better mental

339
00:15:15.685 --> 00:15:16.925
health for two years after.

340
00:15:17.465 --> 00:15:19.405
So, so that's number one, measuring

341
00:15:19.405 --> 00:15:23.325
and understanding the full, scale of the policy impacts.

342
00:15:24.005 --> 00:15:27.085
I think there are other kind of more like fine tune,

343
00:15:27.145 --> 00:15:30.485
but nevertheless important, considerations.

344
00:15:30.825 --> 00:15:33.605
One is that there are some windows

345
00:15:33.785 --> 00:15:36.685
of opportunities in which interventions can be really

346
00:15:36.685 --> 00:15:37.965
important, right?

347
00:15:38.065 --> 00:15:41.605
For example, as we've shown, is that if we really also want

348
00:15:41.605 --> 00:15:44.725
to improve the human capital, accumulation of children,

349
00:15:45.505 --> 00:15:46.605
we might,

350
00:15:46.685 --> 00:15:48.125
and again, we have limited budget,

351
00:15:48.225 --> 00:15:50.045
so we cannot treat everybody at once.

352
00:15:50.265 --> 00:15:53.005
We might want to target parents of children

353
00:15:53.145 --> 00:15:55.885
who are transitioning between primary and secondary school,

354
00:15:55.885 --> 00:15:58.045
because that's where we have these kind of positive,

355
00:15:58.045 --> 00:16:00.685
effects that go beyond the impacts on, on the people

356
00:16:00.685 --> 00:16:01.725
who are receiving medication,

357
00:16:01.745 --> 00:16:03.205
but spill over onto their children.

358
00:16:03.545 --> 00:16:06.525
So windows of opportunities, are,

359
00:16:06.625 --> 00:16:08.965
can be also an important policy consideration.

360
00:16:09.625 --> 00:16:12.765
And the third one is that now we have another tool

361
00:16:13.305 --> 00:16:16.005
in our toolkit of potentially successful

362
00:16:16.265 --> 00:16:17.445
policy interventions.

363
00:16:17.445 --> 00:16:19.045
Again, you know, with this caveat, we need to be able

364
00:16:19.045 --> 00:16:20.925
to replicate, because now we've seen, for example,

365
00:16:20.955 --> 00:16:24.085
that there's things like, you know, improving the quantity

366
00:16:24.105 --> 00:16:26.325
and quality of the supply of schools, you know, being,

367
00:16:26.725 --> 00:16:30.325
building better more schools, can be really important.

368
00:16:30.425 --> 00:16:33.405
In fact, it's crucial. We know that,

369
00:16:33.405 --> 00:16:35.805
eliminating some barriers for children to go to school,

370
00:16:35.805 --> 00:16:37.365
like giving them money or giving them

371
00:16:37.525 --> 00:16:38.965
bicycles, that's also important.

372
00:16:38.965 --> 00:16:41.685
And now we know that also treating the parents can be

373
00:16:41.805 --> 00:16:43.405
as important to, to, again,

374
00:16:43.405 --> 00:16:46.085
have all these big impacts on education.

375
00:16:46.245 --> 00:16:51.125
I think doing these studies, has, clinical value.

376
00:16:51.415 --> 00:16:53.525
Right? Now, of course, I'm not a psychiatrist, so I'm,

377
00:16:53.525 --> 00:16:55.605
I'm not going to, you know, speak about the, you know,

378
00:16:55.605 --> 00:16:56.845
the specifics and the IES

379
00:16:56.845 --> 00:16:59.165
and the know serotonin and, and all of that.

380
00:17:00.185 --> 00:17:01.965
But the truth of the matter is that

381
00:17:02.545 --> 00:17:05.165
all these clinical studies that we have of the effectiveness

382
00:17:05.225 --> 00:17:08.925
of antidepressants tend to have a window of like six,

383
00:17:09.255 --> 00:17:10.285
maybe 12 months.

384
00:17:10.535 --> 00:17:13.045
There was maybe one study that went up to 18 months

385
00:17:13.175 --> 00:17:15.125
after the, the no, the intervention.

386
00:17:15.865 --> 00:17:20.325
Uh, so we don't really even know, how long the impacts

387
00:17:20.325 --> 00:17:22.365
of these medications, remain.

388
00:17:22.425 --> 00:17:25.565
And so, we should do, we should learn,

389
00:17:25.705 --> 00:17:27.725
we should know this answer, but it's very important

390
00:17:27.725 --> 00:17:29.845
because these medications are prescribed to, I don't know,

391
00:17:30.035 --> 00:17:31.325
mids of people worldwide

392
00:17:31.745 --> 00:17:34.205
and also especially, here in the United States,

393
00:17:34.225 --> 00:17:37.805
but I believe also in Europe, there's a debates about,

394
00:17:37.845 --> 00:17:40.685
whether these medications are overprescribed with people,

395
00:17:40.905 --> 00:17:42.045
for example, being put on

396
00:17:42.045 --> 00:17:43.765
antidepressants and remaining for decades.

397
00:17:44.225 --> 00:17:46.885
And so understanding what is the optimal duration

398
00:17:47.385 --> 00:17:48.685
of a course of medication?

399
00:17:48.785 --> 00:17:50.885
Is it, does it make sense to give people medication

400
00:17:50.905 --> 00:17:52.685
for like, you know, six to eight months of a year

401
00:17:53.065 --> 00:17:56.365
and then stop, gradually tap it out and see what happens,

402
00:17:56.585 --> 00:17:59.845
and then maybe resume the medication provision once they

403
00:17:59.845 --> 00:18:02.725
have, you know, another spell of the pressure if,

404
00:18:02.795 --> 00:18:03.805
that arises.

405
00:18:04.345 --> 00:18:07.245
So, so, no, as I said, you know, with the,

406
00:18:07.795 --> 00:18:11.125
that I'm not a psychiatrist, I, I, I think, you know,

407
00:18:11.125 --> 00:18:14.285
this study, should be one of many that's really try

408
00:18:14.285 --> 00:18:16.925
to measure, the, the long-term effects

409
00:18:17.065 --> 00:18:19.245
of a single course of pharmacotherapy,

410
00:18:19.245 --> 00:18:21.525
because these are medication that is used commonly,

411
00:18:21.525 --> 00:18:23.125
and we really don't know that yet.

412
00:18:23.465 --> 00:18:25.605
So, so clinical value,

413
00:18:26.855 --> 00:18:31.375
I think it's also helpful for kind of the practicalities

414
00:18:31.755 --> 00:18:34.735
of, the scaling of lysis, right?

415
00:18:34.795 --> 00:18:39.255
So, so again, it goes back to this question, should we think

416
00:18:39.255 --> 00:18:43.415
of antidepressants as a medication to, to,

417
00:18:43.475 --> 00:18:44.735
to treat like, you know,

418
00:18:44.735 --> 00:18:46.655
chronic diseases like diabetes, right?

419
00:18:46.655 --> 00:18:49.775
You know, you need to take insulin, forever,

420
00:18:50.595 --> 00:18:52.895
or should we think of it as something that, you know, is, is

421
00:18:53.415 --> 00:18:56.655
provided on demand when people are experiencing a, you know,

422
00:18:56.755 --> 00:18:59.415
severe, depressive disorder and then to be tapered

423
00:18:59.415 --> 00:19:00.655
and then to be monitored?

424
00:19:01.075 --> 00:19:03.335
And that's going to be important in terms of, you know,

425
00:19:03.765 --> 00:19:08.055
what kind of infrastructure do we need to create to, to,

426
00:19:08.115 --> 00:19:09.655
to treat, depression.

427
00:19:09.955 --> 00:19:13.055
One, important thing that this study has shown is that,

428
00:19:13.395 --> 00:19:18.155
pharmacotherapy, can be successfully

429
00:19:19.035 --> 00:19:23.515
provided in a community setting also in low

430
00:19:23.515 --> 00:19:25.475
and middle income countries, which I believe

431
00:19:26.385 --> 00:19:29.435
perhaps the first piece of evidence that we have, you know,

432
00:19:29.435 --> 00:19:30.915
we have other, you know, studies

433
00:19:31.015 --> 00:19:32.155
in a more controlled setting.

434
00:19:32.855 --> 00:19:34.435
Uh, but this was kind of in the wild.

435
00:19:34.495 --> 00:19:37.355
So we went to this, localities and,

436
00:19:37.615 --> 00:19:38.715
and, you know, we, we,

437
00:19:39.055 --> 00:19:41.435
we weren't even sure if people would not be willing

438
00:19:41.455 --> 00:19:42.555
to participate, to be honest.

439
00:19:42.615 --> 00:19:43.755
So even the fact that, you know,

440
00:19:43.755 --> 00:19:46.235
the showing up was a big success, in our books.

441
00:19:46.855 --> 00:19:49.395
Uh, so, so feasibility, that's, that's very important.

442
00:19:50.215 --> 00:19:52.755
Um, the other thing that I want to emphasize,

443
00:19:52.755 --> 00:19:53.955
which is important for scale

444
00:19:53.975 --> 00:19:58.395
and it's kind of a, a kind of half empty health full story,

445
00:19:58.455 --> 00:20:02.195
is that, one important characteristic of a study is

446
00:20:02.195 --> 00:20:06.195
that we were using the existing local infrastructure.

447
00:20:06.735 --> 00:20:09.995
So we didn't go with the army or psychiatrist or nurses

448
00:20:10.375 --> 00:20:13.555
or, you know, our community, workers.

449
00:20:14.495 --> 00:20:17.035
In fact, we collaborated with the local NGO O

450
00:20:17.035 --> 00:20:19.715
that had been doing pretty much what they did, with us

451
00:20:19.975 --> 00:20:21.395
for, you know, at least 20 years,

452
00:20:21.455 --> 00:20:24.635
and with a local hospital that's already

453
00:20:25.395 --> 00:20:28.155
provided pro bono, for immunotherapy

454
00:20:28.415 --> 00:20:29.875
to low income people with depression.

455
00:20:29.875 --> 00:20:31.315
So again, we didn't reinvent the

456
00:20:31.315 --> 00:20:32.395
wheel, in fact, quite the reverse.

457
00:20:32.415 --> 00:20:36.075
We, we used exactly the structure that was preexisting.

458
00:20:36.695 --> 00:20:41.115
So this is good because our locality, the,

459
00:20:41.175 --> 00:20:43.675
our study area is not unique in India.

460
00:20:43.695 --> 00:20:46.035
So there are other areas where there are other NGOs

461
00:20:46.035 --> 00:20:49.365
that provide similar services, other community, workers

462
00:20:49.555 --> 00:20:51.205
that could have the role

463
00:20:51.205 --> 00:20:54.005
that the NGO played if such an NGO does not exist,

464
00:20:54.095 --> 00:20:57.045
other hospitals that provides, you know, perhaps infrequent

465
00:20:57.185 --> 00:20:59.765
and perhaps not perfect, but they do provide mental health

466
00:20:59.765 --> 00:21:00.845
care through pharmac psychotherapy.

467
00:21:01.305 --> 00:21:04.525
So this is really good because that's kind of the helpful,

468
00:21:04.785 --> 00:21:06.965
the helpful is that we can sort

469
00:21:06.965 --> 00:21:09.605
of easily scale it up in the sense that we don't need

470
00:21:09.605 --> 00:21:11.405
to build a hospital and wait for 10 years

471
00:21:11.415 --> 00:21:13.045
until we train new psychiatrists.

472
00:21:13.045 --> 00:21:15.765
You know, we, we already have the, the, the infrastructure,

473
00:21:16.385 --> 00:21:18.845
the sort of half empty is that, well, you know,

474
00:21:19.505 --> 00:21:21.565
we had infrastructure, so why is it

475
00:21:21.565 --> 00:21:23.365
that people were getting treated right?

476
00:21:24.095 --> 00:21:26.525
Which goes back to, I don't know if I talked about it,

477
00:21:26.525 --> 00:21:28.445
but the, the way I'm thinking about, you know,

478
00:21:28.445 --> 00:21:30.365
what are the barriers to mental healthcare provision,

479
00:21:30.385 --> 00:21:32.125
at least in this setting, it seems like there are

480
00:21:33.305 --> 00:21:34.775
three big barriers are the usual.

481
00:21:34.795 --> 00:21:36.535
One is that lack of infrastructure, right?

482
00:21:36.535 --> 00:21:38.575
So the supply side, you know, there aren't enough hospitals

483
00:21:38.575 --> 00:21:42.695
and there's psychiatrists, et cetera, but it's also,

484
00:21:42.695 --> 00:21:44.495
and that's not the case because we have those.

485
00:21:44.755 --> 00:21:46.655
Uh, and so there's the demand side one,

486
00:21:46.655 --> 00:21:48.575
which is a combination of lack of knowledge.

487
00:21:48.715 --> 00:21:51.215
So people may not be aware that first

488
00:21:51.215 --> 00:21:53.655
what they have is an illness, a disorder,

489
00:21:53.755 --> 00:21:55.655
and second that, you know, there are medicines

490
00:21:55.655 --> 00:21:57.135
that can treat it,

491
00:21:57.315 --> 00:22:02.295
or it could be, reluctance, to seek treatment

492
00:22:02.295 --> 00:22:05.935
because there are, social barriers that mental health,

493
00:22:06.035 --> 00:22:08.855
mental illness is highly stigmatized in the study area.

494
00:22:08.875 --> 00:22:10.815
And so people might not seek treatment

495
00:22:10.815 --> 00:22:15.105
because they're embarrassed of, you know, just coming out

496
00:22:15.125 --> 00:22:16.865
to the neighbors or maybe, you know, they're afraid

497
00:22:16.865 --> 00:22:19.385
that their husbands would divorce them, all sort of reasons.

498
00:22:19.725 --> 00:22:22.625
The final one, which is the more insidious, is that actually

499
00:22:23.395 --> 00:22:26.555
depression itself prevents you from

500
00:22:27.215 --> 00:22:28.545
seeking care, right?

501
00:22:28.605 --> 00:22:31.625
So, so a, a, a famous psychiatrist called Depression,

502
00:22:31.785 --> 00:22:33.185
a paralysis of the will.

503
00:22:33.645 --> 00:22:36.305
And so that's, you know, it's this kind of paralyzing,

504
00:22:36.305 --> 00:22:41.105
condition that makes even like the most obvious, easy acts,

505
00:22:41.125 --> 00:22:42.745
really daunting and overwhelming.

506
00:22:42.845 --> 00:22:45.345
And so even when there are hospitals and there's a structure

507
00:22:45.445 --> 00:22:46.505
and you know about it,

508
00:22:46.565 --> 00:22:48.145
and you're not afraid of doing it,

509
00:22:48.205 --> 00:22:50.025
it is still a lot to overcome.

510
00:22:50.395 --> 00:22:52.665
Which brings me to kind of the practical thing.

511
00:22:52.965 --> 00:22:55.625
So, so again, generalizing from the study,

512
00:22:55.725 --> 00:22:58.505
it seems like having hospitals and psychiatrists

513
00:22:58.505 --> 00:23:01.025
and medication and telling people about depression.

514
00:23:01.025 --> 00:23:04.345
So educating, the, the, the society about depression

515
00:23:04.565 --> 00:23:07.425
and de-stigmatizing is not going to be enough.

516
00:23:07.425 --> 00:23:08.465
For sure, it's gonna matter,

517
00:23:08.885 --> 00:23:12.225
but we really need to find a system that helps people get,

518
00:23:12.365 --> 00:23:13.785
you know, in the clinic, which is

519
00:23:13.785 --> 00:23:15.865
what our wonderful NGO did.

520
00:23:16.525 --> 00:23:20.225
Now the good news is that India actually has a structure for

521
00:23:20.225 --> 00:23:23.305
that to happen because, it has a series,

522
00:23:23.785 --> 00:23:27.385
I think hundreds or thousands of,

523
00:23:28.125 --> 00:23:31.785
social workers, who cover a specific set of, you know,

524
00:23:31.785 --> 00:23:32.945
localities and families.

525
00:23:32.945 --> 00:23:33.945
They called AHA workers.

526
00:23:34.525 --> 00:23:37.105
And so if we did,

527
00:23:37.135 --> 00:23:39.785
implement a system in which the screening

528
00:23:39.885 --> 00:23:44.625
for mental illness, became sort of a default,

529
00:23:44.845 --> 00:23:46.965
And then they helped people, you know, they kind

530
00:23:46.965 --> 00:23:50.605
of brought people through the door of the clinic, then,

531
00:23:51.085 --> 00:23:55.405
I suspect that we could use, in the most,

532
00:23:55.965 --> 00:23:58.565
efficient and effective way the existing infrastructure in

533
00:23:58.565 --> 00:24:01.005
India so that, you know, people who suffer can have the care

534
00:24:01.035 --> 00:24:02.685
that they deserve and need.

Exploring Mental Health in Economic Development

00:00:00 - Really interested in, mental health through the lens of economics and economic development, which, at the time I started to work in this field, was, in my opinion, still understudied. I, I think people's awareness of the prevalence and, human costs of mental illness has really increased after covid. But before there was limited knowledge even in econ academic circles.

00:00:33 - as, as, development economists, we want to like alleviate human suffering and bring, you know, happiness and wellbeing to people. And, I realized that, you know, many people in lower middle income countries suffer. In fact, one thing that I found really interesting and that I didn't know at the time is that there is a positive correlation between poverty and, affected disorders like depression and anxiety. When I started to work on this, I thought that, you know,

00:01:05 - world country malaise, where we know we stare at the horizon and think about life's meaninglessness. Well, you know, we drink champagne or something like that. In fact, it's the reverse, which, which sort of makes sense in hindsight. It's, it is people whose lives are really hard and complex and who feel that they don't have a safety net. So any little shock can have, like, dramatic and disastrous consequences really feel high rates of no stress, depression, anxiety.

Exploring Mental Health and Economic Behavior

00:01:36 - it was seemed like first order to, to try and understand that when my research, I wear, sort of two hats. one is, the scientists, the social scientists. So I want to understand, how should economists think of mental illness? it is more, as I will talk about, you know, I believe it is more than any other health condition that there are some, you know, unique features that, that make it really important to understand within a context

00:02:09 - utility maximization. So what people want, and what people do to get what they want and what barriers they're facing. but at the same time, there's also the policymaker hat, which is, you know, a lot of people suffer. We have tools that, have been shown to work in, you know, in Europe, in the United States. how can we use those tools and apply them in a context where everything is much more complicated? so, so it's more kind of the pragmatic, aspect of,

00:02:39 - My, working hypothesis when I start to do research in mental health is that, there, there are some unique features of, of depression that directly feeds into economic behaviors. and if you think about the key symptoms of depression, it sort of makes sense, because, you know, a kind of a crucial component of depression is, anhedonia or the inability, sorry, I don't know if I'm pronouncing these words probably, but it's the inability to derive pleasure from lives.

The Economic Impact of Depression on Decision-Making

00:03:16 - basically lives, life's meaninglessness and worthlessness that can directly, impact economic choices and behaviors in a way that I'm gonna describe in a minute, are the key, symptoms. you know, disruptive eating or sleeping patterns, impaired cognition and decision making, inability to concentrate, or rumination.

00:03:46 - and potentially big impacts on economic outcomes, such as, consumption income, human capital, but also economic choices as the choice of how much, when and where to work, the choice of whether to consume, save, and invest, the choice of what to do for one's families and one's children's wellbeing. And so, as economists, we like to sort of, you know, group things into, into labels.

00:04:16 - productivity channel through which depression can affect economic, choices, behaviors, and outcomes. And this is this idea that, you know, if I'm tired or sluggish or unsure or prone to make mistakes, that is going to affect my performance, both on the job, but also my performance in when I have to make important decisions for the present and future wellbeing of which is investments. So, so, so employment investments,

Impact of Depression on Economic Choices

00:04:45 - through this productivity channel. And then there's the preference channel, which is like, you know, if nothing is worth it, very, very simplified, you know, what's the point of it? All right? At the core of investment decision is this trade off between, you know, bearing a costs right now for a future reward, which is not even certain in many cases. And so, if you are thinking about, you know, what's the point of anything, then why should I, you know, make a sacrifice now for, you know, in order to,

00:05:18 - so this, again, this components pessimism, this inability to feel pleasure might have, potentially an impact on investment. And so these are like two, this is a generalization of course, and it might be on the channels, but this productivity and preferences channels are potentially pathways through which, a disorder like depression can have an impact on economic choices, behaviors, and outcomes.

00:05:49 - we would be able to entice people with depression to seek treatment. It's kind of more like the practical, the policy aspects of the story, which, if I have time, I think I would like to talk more because it's, it's an interesting, point, in terms of the more economic hypothesis, was that, in successfully inducing people with depression to seek treatment would not only

Exploring Economic Outcomes of Mental Health Interventions

00:06:19 - but it would also spill over on economic outputs such as, labor market behavior, employment, income, therefore consumption and, potentially also investment. So again, this idea that this combination of being better at, you know, producing, making choices, and also caring more, if I want to use a very basic language to, to summarize this productivity and preferences, pathways would result in higher employment,

00:06:52 - whatever it is that is important for those people and their families. I want to, be very clear that all I am about to say is completely speculative. And that's one of the limitations of the, you know, this type of interventions that we do. We design interventions and we look at effects, but then, you know, whether something happened in one way or the other, why that happened is, you know, is, is highly speculative. So, so we discover, and, and with another, caveat or,

00:07:23 - which is this idea that in our study, we provided pharmacotherapy in the form of antidepressants, and we provided this very light touch livelihoods intervention, which was a combination of two group meetings that was centered around, income generating processes. So people would talk about, you know, this is what I want. these are the obstacles that I have to achieving. You know, I wanna have a job, or I wanna have, I want start up a business, or I would like to have a better job, and here's why, you know, these are the difficulties I'm phasing.

Enhancing Mental Health Outcomes: The Impact of Combined Interventions

00:07:55 - solve these problems, followed by an individualized, intervention where members of the NGO that we work with were working with people to sort of make whatever they wanted happen. It were the two things that we did. And we cross randomized it so that some groups that only pharmacotherapy, some groups that only what is called this livelihood intervention and some group, achieved both. So now the livelihood intervention on its own didn't do much. in fact, you know, if we know, if we test the hypothesis

00:08:28 - we don't find any evidence that it does. At the same time, when, the livelihood intervention was paired with the pharmacotherapy intervention, we found that the effects of pharmacotherapy were, bigger, both in terms of, the impacts on depression, but also on the duration of this impact. So people were feeling much better, where when, in addition to, to, to being offered for psychotherapy, they were also offered to participate in this livelihood intervention,

00:08:57 - But also for, for, for more time. For longer time. now why is that the case? So, as I said, you know, we don't know what we speculate and what we actually want to investigate in the future research is that, this livelihood intervention, and in particular, the group meeting component, had some function that very loosely resembled some aspects of, of group psychotherapy. You know, people were not provided with no insights into cognitive behavioral therapy.

Building Together: Community Support and Mental Health

00:09:31 - or to reframe their thoughts. But at the same time, I think the acts of being together, realizing that they weren't alone, there were other people who were going through, you know, something similar, this idea of, both acknowledging and voicing obstacles, but also reframing them in a way of, you know, here's what we could do to solve this problem or to figure this out, could potentially have had, kind

00:10:03 - both through, for example, making them more likely to take the medicines. So at a practical level, in fact, we have some evidence that, adherence to medication was a bit higher in the group that was being offered both treatments, but also, as I said, more akin to this idea of, of therapy that kind of helps you think about, you know, your life and your problems in a slightly different way. Or, you know, even this idea of just not being alone,

00:10:32 - there are many other people who are going through something similar. Again, we cannot tell what exactly of these components or if they work at all, but that's our architecture. When we look at the impacts on what we call human capital investment in children, which is this combination of enrolling children in school, children attending classes, doing their homework, and not working, so not providing child labor. We find that, if we lump all children in age school years together,

Impact of Mental Health Interventions on Children's Education Outcomes

00:11:04 - we do not find statistically significant average effects. So the effects are positive, but no, they're not strong enough to be statistically significant. At the same time, when we split children around their median age, which is 12, we found that for older children, so children aged 13 to 18, there are positive, statistically significant, but also like big in economic terms, effects. So both economically

00:11:36 - of composite index of human capital investments, which is excellent news. So first question is like, you know, what is going on? so, so we wanted to sort of understand why these effects are concentrated among older the children. Again, we don't know for sure, but a good candidate for this heterogeneity, why only all older children benefit is that actually all these outcomes that we were considering being enrolled in school, attending school and, and, child labor, not so much homework,

00:12:07 - among the younger children because, you know, nobody was really working after school. So there was no child labor among the, no, the younger children, and pretty much everybody was enrolled and attending school. So, so, so maybe there were some benefits, but not along the outcomes that we were able to measure. and this is a common phenomenon. It's not only a phenomenon in India, it's a broader phenomenon in many lower middle income countries, at which now we've done huge improvements in getting children to complete primary school,

Transitioning Educational Outcomes: The Impact of Mental Health Interventions

00:12:39 - they graduate from primary to secondary education. And so we think that's what we hope that what we are seeing is that we are getting some of these children to not drop out of school as they transition from primary to secondary education and all these following things. So they are enrolled, they attend because they spend more time in school than perhaps they spend less time, working. however, as always, you know,

00:13:07 - So it's one study with a thousand households. You know, India is a big country. So, so no, we should always be, careful about, you know, generalizing for one study also. This is a good and, promising starting point, but who knows what's happening, right? All we can tell is that two years of, you know, one or two years after the end of this intervention, we see this increase in human capital investment that parents do for older children. It's a promising first step,

00:13:40 - So may maybe they enrolled them, you know, in the first grade of secondary school, and then these effects faded out because as their, you know, mental health improvement faded out, and also their attention to the future of their children, you know, went back to, to, to, to the baseline. So we don't know. It seems definitely positive, because if you never take the first step, then you will not be able to take a second step. But, but we need more data and we need to re survey these families and the children to see what is really happening now that they're young, men

Understanding the Policy Implications of Mental Health Interventions

00:14:09 - A very, kind of practical, compelling and important first of the policy implications. The one is kind of, sort of, hopefully becoming obvious. Now, this idea that when we target one outcome, which is, you know, the mental wellbeing of, of adults, hopefully there are downstream positive impacts also on other people, what we call positive spillover reflect. And so if you really wanna have a full understanding of the impacts of these interventions, we need to, we need

00:14:42 - and this is important also for practical concerns, right? Because, you know, we have policy makers have limited budgets. So not only do they want to find effective policies, but the policies that have the highest certain of their investment. And so, if I can show that not only are adults better for up to two years after being treated with this course of antidepressants, but I, we can see that potentially their adult, their older children are on a pathway for better future. It means that the potential long-term benefits

00:15:13 - look, you know, these people have better mental health for two years after. So, so that's number one, measuring and understanding the full, scale of the policy impacts. I think there are other kind of more like fine tune, but nevertheless important, considerations. One is that there are some windows of opportunities in which interventions can be really important, right? For example, as we've shown, is that if we really also want

Targeting Mental Health Interventions for Children Transitioning Schools

00:15:45 - we might, and again, we have limited budget, so we cannot treat everybody at once. We might want to target parents of children who are transitioning between primary and secondary school, because that's where we have these kind of positive, effects that go beyond the impacts on, on the people who are receiving medication, but spill over onto their children. So windows of opportunities, are, can be also an important policy consideration. And the third one is that now we have another tool

00:16:16 - policy interventions. Again, you know, with this caveat, we need to be able to replicate, because now we've seen, for example, that there's things like, you know, improving the quantity and quality of the supply of schools, you know, being, building better more schools, can be really important. In fact, it's crucial. We know that, eliminating some barriers for children to go to school, like giving them money or giving them bicycles, that's also important. And now we know that also treating the parents can be as important to, to, again,

00:16:46 - I think doing these studies, has, clinical value. Right? Now, of course, I'm not a psychiatrist, so I'm, I'm not going to, you know, speak about the, you know, the specifics and the IES and the know serotonin and, and all of that. But the truth of the matter is that all these clinical studies that we have of the effectiveness of antidepressants tend to have a window of like six, maybe 12 months. There was maybe one study that went up to 18 months after the, the no, the intervention.

Reevaluating Antidepressant Duration and Efficacy

00:17:20 - of these medications, remain. And so, we should do, we should learn, we should know this answer, but it's very important because these medications are prescribed to, I don't know, mids of people worldwide and also especially, here in the United States, but I believe also in Europe, there's a debates about, whether these medications are overprescribed with people, for example, being put on antidepressants and remaining for decades. And so understanding what is the optimal duration

00:17:48 - Is it, does it make sense to give people medication for like, you know, six to eight months of a year and then stop, gradually tap it out and see what happens, and then maybe resume the medication provision once they have, you know, another spell of the pressure if, that arises. So, so, no, as I said, you know, with the, that I'm not a psychiatrist, I, I, I think, you know, this study, should be one of many that's really try to measure, the, the long-term effects of a single course of pharmacotherapy,

00:18:21 - and we really don't know that yet. So, so clinical value, I think it's also helpful for kind of the practicalities of, the scaling of lysis, right? So, so again, it goes back to this question, should we think of antidepressants as a medication to, to, to treat like, you know, chronic diseases like diabetes, right? You know, you need to take insulin, forever,

Community-Based Pharmacotherapy for Depression

00:18:53 - provided on demand when people are experiencing a, you know, severe, depressive disorder and then to be tapered and then to be monitored? And that's going to be important in terms of, you know, what kind of infrastructure do we need to create to, to, to treat, depression. One, important thing that this study has shown is that, pharmacotherapy, can be successfully provided in a community setting also in low

00:19:26 - perhaps the first piece of evidence that we have, you know, we have other, you know, studies in a more controlled setting. but this was kind of in the wild. So we went to this, localities and, and, you know, we, we, we weren't even sure if people would not be willing to participate, to be honest. So even the fact that, you know, the showing up was a big success, in our books. so, so feasibility, that's, that's very important. the other thing that I want to emphasize, which is important for scale

00:19:58 - is that, one important characteristic of a study is that we were using the existing local infrastructure. So we didn't go with the army or psychiatrist or nurses or, you know, our community, workers. In fact, we collaborated with the local NGO O that had been doing pretty much what they did, with us for, you know, at least 20 years, and with a local hospital that's already

Leveraging Existing Infrastructure for Mental Health Care

00:20:28 - to low income people with depression. So again, we didn't reinvent the wheel, in fact, quite the reverse. We, we used exactly the structure that was preexisting. So this is good because our locality, the, our study area is not unique in India. So there are other areas where there are other NGOs that provide similar services, other community, workers that could have the role that the NGO played if such an NGO does not exist, other hospitals that provides, you know, perhaps infrequent

00:20:59 - care through pharmac psychotherapy. So this is really good because that's kind of the helpful, the helpful is that we can sort of easily scale it up in the sense that we don't need to build a hospital and wait for 10 years until we train new psychiatrists. You know, we, we already have the, the, the infrastructure, the sort of half empty is that, well, you know, we had infrastructure, so why is it that people were getting treated right? Which goes back to, I don't know if I talked about it, but the, the way I'm thinking about, you know,

00:21:30 - at least in this setting, it seems like there are three big barriers are the usual. One is that lack of infrastructure, right? So the supply side, you know, there aren't enough hospitals and there's psychiatrists, et cetera, but it's also, and that's not the case because we have those. and so there's the demand side one, which is a combination of lack of knowledge. So people may not be aware that first what they have is an illness, a disorder, and second that, you know, there are medicines that can treat it, or it could be, reluctance, to seek treatment

Overcoming Stigma in Mental Health Treatment

00:22:06 - mental illness is highly stigmatized in the study area. And so people might not seek treatment because they're embarrassed of, you know, just coming out to the neighbors or maybe, you know, they're afraid that their husbands would divorce them, all sort of reasons. The final one, which is the more insidious, is that actually depression itself prevents you from seeking care, right? So, so a, a, a famous psychiatrist called Depression, a paralysis of the will.

00:22:36 - condition that makes even like the most obvious, easy acts, really daunting and overwhelming. And so even when there are hospitals and there's a structure and you know about it, and you're not afraid of doing it, it is still a lot to overcome. Which brings me to kind of the practical thing. So, so again, generalizing from the study, it seems like having hospitals and psychiatrists and medication and telling people about depression. So educating, the, the, the society about depression

00:23:07 - For sure, it's gonna matter, but we really need to find a system that helps people get, you know, in the clinic, which is what our wonderful NGO did. Now the good news is that India actually has a structure for that to happen because, it has a series, I think hundreds or thousands of, social workers, who cover a specific set of, you know, localities and families. They called AHA workers. And so if we did,

Leveraging Existing Infrastructure for Mental Health Care in India

00:24:01 - for mental illness, became sort of a default, And then they helped people, you know, they kind of brought people through the door of the clinic, then, I suspect that we could use, in the most, efficient and effective way the existing infrastructure in India so that, you know, people who suffer can have the care that they deserve and need.

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