The state of mental health equity at work



Workplace mental health advocate Natasha Bowman, JD, SPHR speaks with Carol Harrison, President + Senior Partner at Global Gateway Advisors

May 30, 2024

The escalating mental health crisis impacts all of us in different ways.

  • Mental health is the chief health concern among U.S. adults, surpassing cancer, stress, obesity, and drug abuse.

  • But the U.S. is not alone. It is part of a global trend. Across 31 countries recently polled, an average of 44% said that mental health was their country’s top health concern.

Why it matters: Work amplifies broader societal issues that negatively affect mental health, especially among diverse communities, including discrimination and inequality. Yet, stigma and shame remain around discussing or disclosing mental health in work settings. Prioritizing mental health equity for employees is a critical forward-looking talent strategy.

Go deeper: During Mental Health Month, Global Gateway Advisors and CommPro convened a group of business, government and advocacy leaders to exchange ideas about how to address mental health equity in the workplace. The event featured special guest and workplace mental health advocate, Natasha Bowman, JD, SPHR.

Here are our key takeaways.

1. Mental health is essential to thriving workplaces.

By the numbers:

  • One in five employees globally manage a diagnosable mental health condition in any given year.

  • One in three U.S. workers said their jobs had a somewhat negative or extremely negative impact on their mental health.

  • Poor mental health at work can contribute to a decline in productivity, toxic workplace culture, higher rates of attrition and economic loss.

  • Mental health issues cost the US economy $47.6 billion annually in lost productivity (up to 12 unplanned absences a year).

What they’re saying:

  • “If your employees are mentally happy, they will stay longer, they will work better. We must think about mental health as an investment in our organizations.” – Jackson Budinger, Senior Director of Communications, Trevor Project

2. There is no one size fits all solution.

Every employee has unique experiences and identities that shape their perspective and affect how they approach mental health.

Employees experience significantly better mental health and engagement outcomes when their unique social identities are acknowledged and supported.

  • 34% of employees aged 18-29 and 28% of employees 30-49 reported that they considered quitting work due to the impact on mental health. Only 21% of employees aged 50-64 said the same.

  • Neurodivergent, LGBTQIA+ and Hispanic employees want more preventative support when it comes to their mental health.

  • Only one in three Black adults in the United States who need mental health care actually receive it.

What they’re saying:

  • “We are all on different mental health journeys. Creative and flexible accommodations empower employees to manage their mental health and wellbeing – and show up effectively at work.” – Natasha Bowman

  • “Carefully look at the composition of your team. For generation Alpha, it is easier to talk about mental health than Boomers. If you have a team with more Hispanic men, it will be tougher to talk about mental health, because it is not a part of their cultural ethos. It’s important to have a bespoke approach because people have different generational and cultural challenges.” – Event participant

3. Lack of communication and stigma stand in the way.

By the numbers:

  • 74% of full-time employees in the US say it is appropriate to discuss mental health concerns at work, yet only 58% say they feel comfortable.

  • 79% say that their work experience would be better if their leaders communicated they care about mental wellbeing.

What they’re saying:

  • “As I started to share my experience navigating bipolar disorder, one of the common themes I heard from people is that they thought I was brave and courageous to share my story. Many said they wanted to, but were afraid of what their employer would say. The stigma surrounding mental health at work prevents people from talking about it at all.” – Natasha Bowman 

4. Strategic communications can improve mental health and foster thriving workplaces.

Measure mental health. In the same way employers measure employee engagement, they can also measure employees’ mental health at work. Data can reveal how mental health impacts employees differently depending on where they’re based, their socio-cultural background and other demographics.

  • Using data and insights, employers can define what resources are needed – and how communications can help point employees to the right support.

Engage leadership to break down stigma through storytelling. When a senior leader opens up about their experiences with mental health, it can make employees with shared experiences feel seen and heard.

  • As Carmella Glover, Vice President, Head of Diversity, Equity and Inclusion at Page Society, said: “It takes one brave person and their story to move people and create a safe space. There is power in storytelling, so people know they are not alone.”

Provide clear, actionable messaging around mental health. “We need a ‘stop, drop, and roll’ for the steps to take when someone in your life needs you. This is one of the important communications challenges in mental health equity,” said Erika Soto Lamb, Vice President, Social Impact Strategy at Showtime/MTV Entertainment Studios at Paramount Global. “That’s why we partnered with Active Minds to launch a.s.k, or acknowledge, support, keep-in-touch.

  • Through creative messaging and employee engagement strategies, we can make resources more accessible to employees and provide actionable guidance for what to do when support is needed.

Ensure that conversations around mental health are inclusive of all backgrounds, cultures, abilities and perspectives.

  • “A person may need mental health Tuesday instead of Friday,” said Natasha Bowman. “Off-the-shelf policies do not work because they’re inflexible and not inclusive.”

  • The same goes for communications. As we shape communications to advance mental health equity at work, it is important to bring diverse stakeholders to the table, amplify stories that demonstrate the wide array of experiences a person can have with their mental health, and showcase how resources and solutions can be tailored to support employees’ unique needs.

Want to continue the conversation? Connect with Global Gateway Advisors on LinkedIn or get in touch via our website.

Innovations in drug discovery – and what communicators should know


September 5, 2023
As AI permeates business functions across nearly every industry, communicators can glean important lessons from the way each sector talks about the technological advancement and disruption in their respective fields. 

With respect to healthcare, researchers have leveraged AI in medicine for years, and we are beginning to see how life-changing treatments can reach the market much faster. 

  • The “patent cliff” – when the world’s 10 biggest drugmakers stand to lose nearly half their revenue by the end of the decade – is fast approaching. 
  • Meanwhile, more than 150 small-molecule drugs are in discovery using an AI-first approach, with more than 15 in clinical trials. The annual growth rate for that pipeline is nearly 40%, according to the Boston Consulting Group.

In this issue, we explore the evolving use of AI in drug discovery, and with it, the rising potential of real-word evidence (RWE). 

Then, we’ll evaluate the essential role that communicators play in shaping public perception and dialogue around the use of AI in drug and medical device development.

1. Moving from concept to market faster. How AI creates efficiencies in drug discovery

The big picture: Estimates vary, but it currently costs about $1 billion and takes roughly 10 years to develop a new drug, with only a fraction of them making it to the market. 

  • Change won’t be immediate. But AI can help scientists discover a drug faster by predicting how different molecules might behave in the body, and discarding dead-end compounds so promising candidates make it to clinical trials quicker.
  • While there is no shortcut in human clinical trials, AI can optimize and diversify patient pools by identifying high-potential candidates. Currently, just 5% of eligible patients participate in clinical research, which limits the ability to study drug efficacy for specific subgroups.

Go deeper: Decentralized clinical trials can facilitate patient engagement by using remote monitoring via wearable devices, which transmit real-world data (RWD) like vital signs and medication adherence to researchers. 

  • Researchers can use AI to analyze RWD for potential adverse events and safety signals, allowing earlier detection of potential drug safety issues.
  • In some cases, AI is helping drug companies bypass the animal testing stage, allowing them to use computer models of humans instead. Machine learning can also accelerate the repurposing of existing drugs, which is patentable.

What else? Rare diseases get a leg up from the Orphan Drug Tax Credit and the FDA’s fast track designation, but their small patient pools present tough challenges that discourage drugmakers from prioritizing research in this space

  • As a result, 95% of rare diseases have no approved treatments.
  • AI is getting better at finding subtle links in large swaths of information that even the finest minds could miss, which helps researchers repurpose drugs and develop new ones faster, even without a large sample size.

What they’re saying:

  • Eric Topol, Scripps Research Translational Institute: “There is no shortage of interest [in AI]. Every major pharma company has invested in partnerships with at least one, if not multiple, AI companies.”
  • David Ricks, Eli Lilly: “In a discovery process, you want to funnel wide. In the past, perhaps humans would just think of what they already knew about. The machine doesn’t. It just knows about everything that was there and it comes up with constructs that humans just don’t.” 
  • Tim Guilliams, Healx: “The potential to suddenly create a viable pipeline for many conditions with only a handful of patients, at the very least, gives real hope.”

Yes, but: Jim Weatherall, AstraZeneca’s VP of data science, AI and R&D, said the challenge for the next few years is pull-through, or to actually bring these drugs to market. He is otherwise optimistic: “We’ve been on a journey from ‘what is this?’ to ‘why did we ever do it any other way?’”

2. AI bolsters the pipeline from RWD to RWE

The big picture: Successful AI drug development requires high-quality, real world data, which is challenging to obtain and can be rife with privacy implications. RWD often comprises electronic health records, which present challenges at scale due to a lack of standardization (as they are collected outside the controlled environment of a clinical trial).

  • Some researchers believe the answer to these concerns could lie in synthetic data produced by applying predictive AI algorithms to RWD. In pharma, synthetic data could be used to handle large but sensitive samples, where regulatory restrictions and data privacy are involved, such as in cross-border research.
  • For now, synthetic data is a niche pursuit and hasn’t yet made its way into clinical use, largely due to concerns that it inaccurately represents the target population.

Go deeper: “The complexity and the variability in healthcare and science makes it a really hard problem to solve,” said Jim Swanson, chief information officer of Johnson & Johnson. “You can create synthetic data easily enough, but is it correlated enough to give you a specific and accurate example? That’s the problem you have to solve.”

  • As such, RWD is used increasingly throughout the drug development process, from identifying early targets to post-market safety surveillance. 
  • The ability to convert RWD to RWE using analytics is a crucial measure of success, as regulators recognize the benefits of RWE and fold them into decision-making. 
  • This is where AI comes in. Algorithms can identify patterns and relationships within RWD to produce RWE. It can then be used to predict patient outcomes and compare treatments to help researchers understand which are more effective and safe in the real-world setting.

3. Evaluating implications for communicators

The biopharma industry is on a precipice. A Morgan Stanley report estimates that even a modest improvement in early-stage drug development success rates could bring 50 novel therapies to market over 10 years.

After discovery comes the story. 

  • Communicating new science is tricky and can have a lasting negative impact if not done right. 
  • The challenge is figuring out how to communicate AI’s benefits and ethical considerations in medicine – when the first AI-developed drug eventually hits the market.

Here are five key considerations for communicators.

  1. Understand and be transparent about AI’s capabilities and limitations to build trust. Don’t shy away from the risks. 
  2. Be authentic and clear about the potential and limitations of AI. 
  3. Be true to the work and its impact. Use data and insights to educate. Leverage publications and medical meetings as opportunities. 
  4. Showcase the significant personal and societal impact of healthcare innovation on patients over the last century, with AI as the latest example.
  5. Proactively address concerns about data privacy and AI biases. Clearly communicate how your AI solutions adhere to regulations and best practices. Consider working with medical experts to create a campaign that speaks to the worries and anxieties of the public.

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