Mental Health Issues In the Workplace - US Data

Nearly one-third (32%) of employees experience worsening mental health symptoms, including anxiety, depression, and ADHD, compared to the previous 6 months;
Extensive analysis from 65 studies in 2022 revealed high prevalence rates among workers: 15% for anxiety disorders, 11% for mood disorders, and 7% for substance use disorders;
62% of 1,500 U.S. employees faced anxiety and depression; 20% missed work due to these issues;
Depression-related presenteeism costs US employers $44 billion yearly, exceeding absenteeism and medical expenses;
Only 50% of those needing mental health care get it due to stigma and accessibility issues, highlighting the urgent need for workplace support.

Looking at the data, it’s apparent that these issues would also be of significance for overall employee health in the workplace and business operations.

What Is the Impact of Mental Health Issues on Workplaces?

There's a real cost in terms of loss of productivity, not only to external conditions that are outside of businesses' influence but also due to internal company culture which can lead to employees leaving the workplace. In multiple studies, it’s often cited as the main cause of workers’ churn.

There are a number of independent studies that estimate between four to five times return on investment, if you're investing in mental health. So there is a straight positive ROI back to companies for that investment. Investing in employee mental health gives people the skills to become more resilient and effective in the workplace. Finally, people are much more likely, more than double likely, to recommend a workplace if they believe that their employer truly cares.

Challenges in Mental Health Software Development and Implementation

According to Alon, the biggest challenge - and the biggest opportunity - is understanding the users’ needs and providing them with what they really need. This requires launching a digital product as soon as possible even if it’s not perfect. It's one thing to theorize about potential customers and their expectations, and another - to launch and see how they interact with the product.

The MVP release will help you find answers to these vital questions:

Are users enjoying and benefiting from therapy sessions?
Are the features and functionalities that you’re building impactful?
Is your product driving change and helping people get better?

As for the challenges in implementing mental health support in real-life workplace, Alon commented that what teams may be struggling with is buy-in from the leadership. Employees can clearly see when certain measures are implemented just to tick a box and won’t be modeling the expected behavior.

When companies use Panda, the engagement from the C-level executives is not only encouraged but also ensured by the leaders participating in the sessions and telling their own stories from a mental health perspective. This gives other team members an opportunity to be vulnerable as well with the main message being: ‘It’s ok not to be ok’.

Moving Away From Reactive Mental Health Care

When you look at the traditional mental health industry, it’s still very much focused on reactive care, meaning that patients can get help when they’re dealing with mental health issues. That’s - obviously - very important, but what Panda Health tries to do is different.

Instead of focusing on helping users only when they need it, their digital product is aimed at offering proactive mental health care where users are able to spot and mitigate some symptoms on their own, even before they will become apparent. Panda can guide them to health by suggesting ways to improve their sleep and nutrition, to avoid the risk of acute illnesses in the long term. Even if they will deal with more symptoms later on, the patients will already be aware of how and why to seek additional support. This way, users can also become more resilient and better equipped to manage any changes and uncertainties in their lives.

How is Panda ensuring the security of user data?

What’s important is that all users interact with the app on an anonymous basis so there are no visible elements that could be used to identify them. Even if you decide to speak up during a live event, your voice is disguised so no one would be able to recognize you. Panda’s app is an anonymous safe environment where patients can start their mental health journey on their own terms and in their own time.

That’s also very different from a traditional mental health care environment where you get into a room with a therapist, sometimes with a group of strangers as well, and you have to be vulnerable with them. While this type of therapy can also and has been proven to be effective, stigma around mental health issues can mean that using technology to share your concerns, doubts, and thoughts may beeasier for patients and serve as a safe first step in addressing their health challenges.

As of recently, the team at Panda has been also implementing AI-based features within the app, with the support from Monterail.

AI in Mental Health - Panda Health’s Case Study

While using AI for mental health care can be a sensitive topic, this technology can play a pivotal role in tackling the mental health epidemic. Here’s how Panda Health uses AI in its digital product.

One of the features where AI is involved are live sessions with therapists where users can ask the host or other participants any questions they may have but they can also query Panda’s AI assistant, Luna, and get responses in real time. There are also live sessions where Luna is the host where users can also type their questions and get answers during these live events.

Panda also offers AI coaching where users can use technology to develop their skills and get guidance on how to do that. These sessions are short - only 5 to 10 minutes a day - but can help users quickly achieve their specific objectives.

In the Panda app, artificial intelligence is also used to build macro profiles for individual users and offer them personalized services at the right time. The technology is also implemented to address any risks and predict situations where users may be asking for more advanced help. Again, it’s all part of the proactive mental health approach.

There’s also a feature for team leaders that helps them analyze and understand how healthy their team culture is and what methods they may want to use to help individual team members. Here’s where leaders can access anonymized data to create content and interventions to support their teams.

Benefits of Using AI in Mental Health Digital Products

When it comes to the benefits of using artificial intelligence in the Panda app and in mental health care in general, Alon lists a number of pros:

AI-based triage of patients - AI-enhanced tools for mental health care have been deemed effective by multiple studies and can serve as first-line support for people who need quick and practical help;

Increased accessibility - as mentioned, one of the challenges of the mental health sector is the lack of specialists who could treat patients - AI tools could help with this issue;

Dismantling the stigma around using mental health care - for some people, it may be easier to discuss their struggles and symptoms with a machine before they reach out to a human therapist;

Faster diagnosis and treatment plans - AI solutions can help mental health professionals diagnose patients much faster and prepare personalized treatment plans.

This is not to state that human specialists will become obsolete at some point - according to Alon, ‘there'll always be a place for mental health professionals, but AI will allow for better diagnosis. Imagine you could bring your AI mental health profile with you to your first therapy session, with all the data, a summary of everything that you've dealt with, and possible diagnoses'.

Ethical Considerations to Keep in Mind When Implementing AI

From Alon’s perspective, AI-enhanced tools for mental health software are still more suitable for educational purposes, and cannot be safely used where more advanced and intricate support is needed. One of the things to keep in mind when implementing technology for mental health care is that when patients express thoughts of self-harm, emergency help handled by humans, not AI, will be necessary. As it’s the case with healthcare in general, mental health services should be centered around the principle of ‘do no harm’.

AI-based features will be particularly suitable and useful in triage and escalation activities though where patients with more complicated issues can be directed to real health professionals, and those with challenges where relaxation techniques and mental health awareness would be enough, can be guided by technology to consider self-help measures.

Over to You

There you have it: a summary from the Monterail event with Alon Lits of Panda Health. If you’d like to be notified about our next events - follow our page on LinkedIn. The mental health sector is and will be one of our focus areas at Monterail, so make sure to check more information on how we approach mental health software development on our website:

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