How To Help Someone With Depression

Credit...Francesco Ciccolella

Jeff Zuckerman and his wife had been married for 30 years when she started battling bipolar disorder and depression. She had her first monthslong manic episode in the spring of 2015. Immediately after, she was thrust into a severe depression. The health crises rocked the couple’s marriage.

“You have to understand that for her, depression is not sadness so much as it is emptiness,” explained Mr. Zuckerman, 68, who is a freelance writer and editor in Minneapolis. When his wife’s depression was at its worst, she remained in bed, with the blinds drawn, for months. She stopped showering and hardly spoke.

“This is a woman who had been so active, who had run our family. She was a mom, she worked, all of that stuff, and then she fell into this depression that was so deep,” said Mr. Zuckerman, who wrote a book — “Unglued: A Bipolar Love Story” — about loving a spouse in the grips of mental illness.

Millions of Americans are in relationships with partners who are prone to depression. An estimated 21 million adults in the United States have experienced at least one major depressive episode, while in parts of the country up to 10 percent of people have seasonal affective disorder, or SAD, a syndrome that tends to kick in during the fall and winter as the daylight hours grow shorter.

When helping your partner weather a battle with depression, experts say there are ways to be supportive while also caring for yourself.

Learn more about depression.

Familiarizing yourself with some of the physical and emotional markers of depression may help you identify if your partner is simply in a bad mood, burned out or is living with depression. Common signs include loss of interest in regular activities, changes in appetite or sleep or unexplained physical symptoms, such as headaches or back pain that tend to last for at least two weeks, according to the National Institute of Mental Health.

Learning more about what depression is and how it affects people may also help you protect yourself emotionally, respond with more empathy and avoid taking your partner’s behaviors personally.

“If one partner doesn’t understand that their partner is suffering from depression, they may mistake things like a loss of interest in romance or sex as a personal rejection,” explained Xavier Amador, a clinical psychologist and co-author of “When Someone You Love Is Depressed.”

Cultivate curiosity about your partner’s experience.

When your partner is in pain, you may feel an urge to dive right in and tell them what you think is happening. But try to lead by asking questions, Dr. Amador said. Ask your partner how they are feeling. Tell them you’d like to understand more about what they’re going through.

If your partner is defensive, Dr. Amador recommends a strategy known as “reflective listening.” For instance, if you ask your loved one how they are feeling and they tell you they are fine and there is nothing wrong, you respond with something along the lines of: “What you’re telling me is that there’s nothing wrong, is that correct? Can I tell you what I’ve noticed?” Dr. Amador explained.

If you make an effort to lead with questions rather than rushing to share your opinion, your partner is more likely to feel heard and valued, not judged, he said.

Acknowledge your own limitations.

To help a loved one get diagnosis and treatment, you can call potential providers and set up appointments, or compile a list of clinicians for them to contact. But experts say it is also important to remember that you cannot force anyone to get help, and that pushing too hard can backfire.

“It’s a balancing act,” said Lily Brown, director at the Center for the Treatment and Study of Anxiety with the University of Pennsylvania’s Perelman School of Medicine. “Of course, you want to make yourself available to talk and to suggest how they can get help, but if you’re doing too much driving the boat, the person who is struggling with depression actually can start to feel a little more helpless and a little more hopeless.”

She added that partners who put too much care-taking responsibility on themselves are also often overcome with feelings of guilt and shame when they are unable to fix the problem.

You shouldn’t have to be your partner’s sole support, especially in situations where they may be in danger. Keep in mind that depression can increase the risk of self-harm and suicidal thoughts — and the 988 Suicide & Crisis Lifeline offers resources to find help for a loved one in crisis.

Prioritize your own mental health.

Romantic partners can affect each other’s health and health-related behaviors in ways good and bad, and Dr. Amador noted there is some research to suggest that depressive symptoms can be, in a way, contagious.

“If you’re living with somebody who is depressed and feeling helpless — and oftentimes doesn’t want to get help — then you can start to feel depressed and helpless,” Dr. Amador explained.

It is imperative that you support your own mental health, both Dr. Amador and Dr. Brown emphasized. If you are experiencing symptoms of depression, reach out to a health care provider for evaluation. But even if you are not, you may find it helpful to see a therapist or to join a peer-led support group.

Mr. Zuckerman is a volunteer facilitator of a National Alliance on Mental Illness, or NAMI, support group for families and partners of people with mental health conditions. And it has helped him connect with a community of people who understand what he is going through. Every other week, Mr. Zuckerman and 10 to 15 or so other partners discuss coping skills; help each other process feelings of grief or guilt; and offer a safe space to share their challenges and successes.

Make time for things you enjoy.

In addition to connecting with a therapist or support group as needed, it is also important to find other ways to prioritize self-care. It does not have to be time-consuming or complicated, Dr. Brown said. Simply getting out of the house for a bit and making time for the activities you enjoy can help protect your own emotional well being when your partner is struggling.

Spend time outside in nature, get involved in some form of advocacy or move your body. Research has shown, for instance, that jogging for 15 minutes a day, or doing less strenuous exercise like walking or gardening for an hour, may have a protective effect against depression.

And “socialize, socialize, socialize — whatever that looks like for you,” Dr. Amador recommended. “It is really important to get that social support and release.” You may encourage your partner to join you in your efforts to get out and exercise or connect with others, but keep in mind that loss of interest in normal activities or hobbies is a symptom of depression.

Mr. Zuckerman’s wife — who has given her husband her blessing to share their story, but only without disclosing her name — has been stable for three years, and said things between the couple are “great.” They go to movies, concerts and dance performances together. They cook, spend time with their grandchildren and attend synagogue.

But Mr. Zuckerman also continues to remind himself that it is not selfish for him to prioritize self-care.

“We fundamentally love our partners and our spouses, and at a gut level, we know it’s an illness. We know you can’t blame somebody for being sick,” Mr. Zuckerman said. “Yet what we go through as a result of it can be overwhelming.”

Catherine Pearson

Source: How to Help Someone With Depression – The New York Times

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Neurodiversity Is Not Enough We Should Embrace Psydiversity

Holly Roos and her son Parker, who is autistic, touch feet as they read stories on the couch at their home in Canton, Illinois, 4 April 2012. Photo by Jim Young/Reuters

The concept of ‘neurodiversity’ has gained enormous cultural influence in recent years. Computer scientists and ‘techies’ wear the ‘neurodiverse’ label with pride; businesses are building ‘neurodiverse’ workforces; scriptwriters strive to represent and cast ‘neurodivergent’ people. Those framed as ‘different’ have been given a remarkable new lens through which to reimagine that variance.

The sociologist Judy Singer coined the term ‘neurodiversity’ in the late 1990s. Inspired by other emancipatory social movements based on race and gender, Singer used her standing as an autistic person to rally together neurodivergent people. This was partly a response to what Singer called the ‘social constructivist’ view of autism, where the condition was seen as having no solid biological basis.

This denied the reality of neurological difference, according to Singer. In reply, she offered up ‘neurodiversity’ in the spirit of biodiversity, in that it recognised and respected natural variance among humans. The movement quickly gained support via online forums and new social networks.

Since Singer’s first use of the term, neurodiversity has widened beyond autism to include people who identify with categories such as attention deficit hyperactivity disorder (ADHD), dyslexia, bipolar disorder, depression and more. It’s come to mean any real mental differences – neither choices nor simply illnesses – that aren’t problems to solve so much as enrichments for society.

Neurodiversity has done brilliant work in breaking down social barriers, challenging stigmas, and raising awareness. But it also contains limitations, and these are becoming increasingly prominent as the concept expands into new domains. The main premise of the neurodiversity movement is that society should be robust enough to embrace and celebrate all people, no matter how their brains are ‘wired’.

That’s a laudable goal and shouldn’t be tricky for anyone to wrap their head around. Yet since the beginning, critics of neurodiversity have claimed that its mantra of radical acceptance could hinder treatments and interventions for those who are suffering. Embracing neurodivergent thought too enthusiastically, they say, risks distracting from genuine physical, emotional or social needs that require attention.

This debate quickly descends into unhelpful recriminations. But it also distracts from a deeper philosophical problem that neurodiversity must confront as it expands into new territory. Neurodiversity’s vision of inclusion, alluring as it is, tends to rely on the idea that neural wiring is at the root of all differences in how humans relate to the world.

But reducing diversity to brain-based distinctions can stand in the way of more sensitive and potentially fruitful ways of understanding mental life. In fact, the success of neurodiversity has exposed the glaring lack of any shared vision or sense of solidarity around mental difference that isn’t anchored in brain-based accounts. So while we can applaud neurodiversity’s ethos of acceptance, we should question its commitment to achieving legitimacy through false ‘neuro’ certainties.

There is a different way forward, in which we fashion our political advocacy and scientific reasoning not on the brain but the ‘mind’. I call this programme ‘psydiversity’. Psydiversity rejects the claim that mental states can be cleanly and predictably mapped on to the brain. Instead, it augments the valuable work of neurodiversity by demonstrating that mental processes and the way we understand them change and evolve through history.

Indeed, psydiversity holds that the mind and ‘human nature’ are not unitary things, but are profoundly embedded and even constituted by the society and context in which they appear. That isn’t to deny the reality of difference, but rather to situate this reality as part of an unfolding social and historical process.

If there’s one aspect of neurodiversity that’s core to its agenda, it’s the ‘neuro’ prefix. The term ‘neuro’ actually stems from the ancient Greek ‘neûron’ or the Latin ‘nervus’, defining nerves or the nervous system. Contemporary neuroscientific approaches have their origins in the early 19th century, when physiologists such as Franz Joseph Gall, Charles Bell, and François Magendie used a combination of human anatomical studies and terrifying animal vivisections to identify the relation between brain, spinal cord and nervous system.

By the early 20th century, neurologists had created detailed maps of the brain and nervous system, and had named many distinct conditions such as cerebral palsy and hemiplegia. It wasn’t until the 1990s, though, that the brain sciences began to really assert themselves in other branches of human knowledge. Via new imaging and genomic testing technologies, evidence emerged that differences in human emotion and behaviour could be traced to differences within people’s brains.

This spawned a number of ‘neuro-’ prefixes that could be attached to subjects as disparate as ‘neuroeducation’, ‘neuroethics’, ‘neuroanthroplogy’, ‘neuroaesthetics’ and ‘neurolaw’. The former US president George Bush called the 1990s the ‘decade of the brain’, while the philosophers Fernando Vidal and Francisco Ortega declared that the neurosciences were leading us to believe that ‘we are our brains’.

Once a treatment or medical tool exists, social, financial and political forces tend to push up diagnoses . All this fervour sprang from the belief that brain-based sciences and genetic research could transform society for the better. When the Dutch geneticist Han Brunner claimed that deficiencies in the MAOA gene could be responsible for an increased propensity to violence, this inspired hopes that moral judgments about ‘good’ and ‘bad’ behaviour could be transformed into progressive scientific research and treatment. Continue reading…..

By: Bonnie Evans

Source: Neurodiversity is not enough. We should embrace psydiversity | Aeon Essays

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Digital Transformation Depends on Diversity

Across industries, businesses are now tech and data companies. The sooner they grasp and live that, the quicker they will meet their customer needs and expectations, create more business value and grow. It is increasingly important to re-imagine business and use digital technologies to create new business processes, cultures, customer experiences and opportunities.

One of the myths about digital transformation is that it’s all about harnessing technology. It’s not. To succeed, digital transformation inherently requires and relies on diversity. Artificial intelligence (AI) is the result of human intelligence, enabled by its vast talents and also susceptible to its limitations.

Therefore, it is imperative for organizations and teams to make diversity a priority and think about it beyond the traditional sense. For me, diversity centers around three key pillars.

People

People are the most important part of artificial intelligence; the fact is that humans create artificial intelligence. The diversity of people — the team of decision-makers in the creation of AI algorithms — must reflect the diversity of the general population.

This goes beyond ensuring opportunities for women in AI and technology roles. In addition, it includes the full dimensions of gender, race, ethnicity, skill set, experience, geography, education, perspectives, interests and more. Why? When you have diverse teams reviewing and analyzing data to make decisions, you mitigate the chances of their own individual and uniquely human experiences, privileges and limitations blinding them to the experiences of others.

One of the myths about digital transformation is that it’s all about harnessing technology. It’s not.

Collectively, we have an opportunity to apply AI and machine learning to propel the future and do good. That begins with diverse teams of people who reflect the full diversity and rich perspectives of our world.

Diversity of skills, perspectives, experiences and geographies has played a key role in our digital transformation. At Levi Strauss & Co., our growing strategy and AI team doesn’t include solely data and machine learning scientists and engineers. We recently tapped employees from across the organization around the world and deliberately set out to train people with no previous experience in coding or statistics.

We took people in retail operations, distribution centers and warehouses, and design and planning and put them through our first-ever machine learning bootcamp, building on their expert retail skills and supercharging them with coding and statistics.

We did not limit the required backgrounds; we simply looked for people who were curious problem solvers, analytical by nature and persistent to look for various ways of approaching business issues. The combination of existing expert retail skills and added machine learning knowledge meant employees who graduated from the program now have meaningful new perspectives on top of their business value. This first-of-its-kind initiative in the retail industry helped us develop a talented and diverse bench of team members.

Data

AI and machine learning capabilities are only as good as the data put into the system. We often limit ourselves to thinking of data in terms of structured tables — numbers and figures — but data is anything that can be digitized.

The digital images of the jeans and jackets our company has been producing for the past 168 years are data. The customer service conversations (recorded only with permissions) are data. The heatmaps from how people move in our stores are data. The reviews from our consumers are data. Today, everything that can be digitized becomes data. We need to broaden how we think of data and ensure we constantly feed all data into AI work.

Most predictive models use data from the past to predict the future. But because the apparel industry is still in the nascent stages of digital, data and AI adoption, having past data to reference is often a common problem. In fashion, we’re looking ahead to predict trends and demand for completely new products, which have no sales history. How do we do that?

We use more data than ever before, for example, both images of the new products and a database of our products from past seasons. We then apply computer vision algorithms to detect similarity between past and new fashion products, which helps us predict demand for those new products. These applications provide much more accurate estimates than experience or intuition do, supplementing previous practices with data- and AI-powered predictions.

At Levi Strauss & Co., we also use digital images and 3D assets to simulate how clothes feel and even create new fashion. For example, we train neural networks to understand the nuances around various jean styles like tapered legs, whisker patterns and distressed looks, and detect the physical properties of the components that affect the drapes, folds and creases. We’re then able to combine this with market data, where we can tailor our product collections to meet changing consumer needs and desires and focus on the inclusiveness of our brand across demographics.

Furthermore, we use AI to create new styles of apparel while always retaining the creativity and innovation of our world-class designers.

Tools and techniques

In addition to people and data, we need to ensure diversity in the tools and techniques we use in the creation and production of algorithms. Some AI systems and products use classification techniques, which can perpetuate gender or racial bias.

For example, classification techniques assume gender is binary and commonly assign people as “male” or “female” based on physical appearance and stereotypical assumptions, meaning all other forms of gender identity are erased. That’s a problem, and it’s upon all of us working in this space, in any company or industry, to prevent bias and advance techniques in order to capture all the nuances and ranges in people’s lives. For example, we can take race out of the data to try and render an algorithm race-blind while continuously safeguarding against bias.

We are committed to diversity in our AI products and systems and, in striving for that, we use open-source tools. Open-source tools and libraries by their nature are more diverse because they are available to everyone around the world and people from all backgrounds and fields work to enhance and advance them, enriching with their experiences and thus limiting bias.

An example of how we do this at Levi Strauss & Company is with our U.S. Red Tab loyalty program. As fans set up their profiles, we don’t ask them to pick a gender or allow the AI system to make assumptions. Instead, we ask them to pick their style preferences (Women, Men, Both or Don’t Know) in order to help our AI system build tailored shopping experiences and more personalized product recommendations.

Diversity of people, data, and techniques and tools is helping Levi Strauss & Co. revolutionize its business and our entire industry, transforming manual to automated, analog to digital, and intuitive to predictive. We are also building on the legacy of our company’s social values, which has stood for equality, democracy and inclusiveness for 168 years. Diversity in AI is one of the latest opportunities to continue this legacy and shape the future of fashion.

By: Katia Walsh

Source: Digital transformation depends on diversity | TechCrunch

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