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Posts by Paul Costello1

Are Schools a Problem?

A dark school hallway in which students appear in silhouette.
Sam Sifton


By Sam Sifton I am the host of The Morning. NYT Nov 25th 2025

The numbers are staggering.

Nearly one in four 17-year-old boys in the United States has attention deficit hyperactivity disorder. In the early 1980s, a diagnosis of autism was delivered to one child in 2,500. That figure is now one in 31. Almost 32 percent of adolescents have at some point been given a diagnosis of anxiety. More than one in 10 have experienced a major depressive disorder, my colleague Jia Lynn Yang reports.

And the number of mental health conditions is expanding. A child might be tagged with oppositional defiance disorder or pathological avoidance disorder. “The track has become narrower and narrower, so a greater range of people don’t fit that track anymore,” an academic who studies children and education told Jia Lynn. “And the result is, we want to call it a disorder.”

Why did this happen? A lot of reasons. Kids spend hours on screens, cutting into their sleep, exercise and socializing — activities that can ward off anxiety and depression. Mental health screenings have improved.

And then there’s school itself: a cause of stress for many children and the very place that sends them toward a diagnosis.

In 1950, less than half of American children attended kindergarten. Only about 50 percent graduated from high school. After-school hours were filled with play or work. “But as the country’s economy shifted from factories and farms to offices, being a student became a more serious matter,” Jia Lynn writes. “The outcome of your life could depend on it.” College became a reliable path to the middle class.

Schools leaned into new standards of testing and put in place measures of accountability. The No Child Left Behind Act in 2002 made it federal law.

States rewarded schools for having high scores. They punished them for low ones. “Schools were treated more like publicly traded companies, with test scores as proxies for profits,” Jia Lynn writes. “Before long, schools had public ratings, so ubiquitous they now appear on real estate listings.”

And there were clear incentives to diagnose students with psychiatric disorders: Treatment of one student, especially a disruptive one, could lead to higher test scores across the classroom. And in some states, the test scores of students with a diagnosis weren’t counted toward a school’s overall marks, nudging results higher as well.

The metrics may have gotten many kids the support they needed. Either way, educational policymaking yielded a change: According to one analysis Jia Lynn found, the rate of A.D.H.D. among children ages 8 to 13 in low-income homes rose by half after the passage of No Child Left Behind.

A student in a classroom is writing math equations on a white board.
In San Luis, Ariz.Credit…Ariana Drehsler for The New York Times

The pressures on students became extreme. In 2020, Yale researchers found that nearly 80 percent of high schoolers said they were stressed.

And that stress has trickled down to younger and younger kids. Kindergartners learn best through play, not through the rote lessons in math and reading that began to enter classrooms. Preschoolers are not predisposed to sitting still. And yet as they, too, now face greater academic expectations, many are being expelled for misbehavior.

Even the school day became more regimented, with fewer periods of recess — by 2016, only eight states had mandatory recess in elementary schools. Class schedules are packed. “You’ve got seven different homework assignments that you’ve got to remember each night,” one expert told Jia Lynn. “Think of the cognitive load of a sixth-grade boy. I challenge many adults to do this.”

It’s a vicious cycle, where bad outcomes lead to worse outcomes.

And Jia Lynn writes about that beautifully:

By turning childhood into a thing that can be measured, adults have managed to impose their greatest fears of failure onto the youngest among us. Each child who strays from our standards becomes a potential medical mystery to be solved, with more tests to take, more metrics to assess. The only thing that seems to consistently evade the detectives is the world around that child — the one made by the grown-ups.

Read more about schools and the rise of childhood mental health disorders here. Don’t miss the comments that accompany the article, especially from parents and teachers. Many boil down to something a recently retired teacher wrote: “A child’s school day is insane.”

https://www.nytimes.com/2025/11/25/briefing/are-schools-a-problem.html?searchResultPosition=19

Why More People in the World Are Feeling Hopeful (Except Us)

a bleak photo of road lined with buildings
David Brooks

By David BrooksOpinion Columnist NYT August 7th 2025

I hope you don’t mind if I pierce the general gloom with a piece of wonderful news. More people around the world report that they are living better lives than before. Plus they are becoming more hopeful about the future. In a new survey, the Gallup organization interviewed people across 142 countries and asked them a series of questions to determine whether they felt they were thriving in their lives or struggling or, worst of all, suffering.

The number of people who say they are thriving has been rising steadily for a decade. The number of people who say they are suffering is down to 7 percent globally, tying with the lowest level since 2007. This trend is truly worldwide, with strong gains in well-being in countries as far-flung as Kosovo, Vietnam, Kazakhstan and Paraguay.

Unfortunately, there is a little bad news. Some people reported sharp declines in well-being. That would be us. The share of the population that is thriving is falling in America, Canada, Western Europe, Australia and New Zealand. In 2007, 67 percent of Americans and Canadians said they were thriving. Now it’s down to 49 percent.

To put it another way, the nations with some of the highest standards of living are seeing the greatest declines in well-being. We still enjoy higher absolute levels of well-being than nations in the developing world do, but the trend lines are terrible.

This should not be a surprise. I would say the most important social trend over the past decade has been the disconnect between our nation’s economic health and its social health. Over these years the American G.D.P. has surged, wages have risen, unemployment has been low, income inequality has gone down. At the same time, the suicide rate has surged, social isolation has surged, social trust is near rock bottom. According to a Gallup survey from January, the share of Americans who say they are “very satisfied” with their lives has hit a new low. According to the 2025 Edelman Trust Barometer report, only 30 percent of Americans feel optimistic for the next generation.S

What’s going on here?

People thrive when they live in societies with rising standards of living and dense networks of relationships, and where they feel their lives have a clear sense of purpose and meaning. That holy trinity undergirds any healthy society. It’s economic, social and spiritual.

I spoke with Dan Witters of Gallup, who broke down some of the contributors to social and spiritual health. People who are thriving are more likely to feel a strong attachment to their community. They feel proud of where they live. People are more likely to experience greater well-being when they join congregations and regularly attend religious services. Feeling your life has purpose and meaning, he adds, is a strong driver of where you think you are going to be five years from now.

The most comprehensive study of well-being is probably the Global Flourishing Study, led by Tyler J. VanderWeele of Harvard and Byron Johnson of Baylor. Their group has interviewed 200,000 people across 22 countries beginning in 2022. They found that a few countries do well across material, social and spiritual measures, notably Israel and Poland. A lot of countries score well materially, but the people who live in them are less likely to have a sense of clear purpose and meaning, like Japan and the Scandinavian nations. Other countries don’t do as well economically, but do very well socially and spiritually, like Indonesia, Mexico and the Philippines.

I’d say that the nations that are doing well in that Gallup thriving survey are those that are experiencing rising living standards while preserving their traditional social arrangements and value systems. The nations like America that are seeing declining well-being are fine economically, but their social and spiritual environments are deteriorating.

Why have rich nations lagged behind in this way? VanderWeele theorizes that maybe it’s a question of priorities. “I tend to think you end up getting what you value most,” he told me. “When a society is oriented toward economic gain, you will be moderately successful, but not if it’s done at the expense of meaning and community.”

I’d add that we in the West have aggressively embraced values that when taken to excess are poisonous to our well-being. Over the past several decades, according to the World Values Survey, North America, Western Europe and the English-speaking nations have split off culturally from the rest of the world. Since the 1960s we have adopted values that are more secular, more individualistic and more oriented around self-expression than the values that prevail in the Eastern Orthodox European countries such as Serbia, the Confucian countries like South Korea and the mostly Catholic Latin countries like Mexico.

The countries that made this values shift are seeing their well-being decline, according to that Gallup thriving survey. The countries that resisted this shift are seeing their well-being improve. The master trend in recent Western culture has been to emancipate the individual from the group, and now we are paying the social and spiritual price.

Two groups are particularly hard hit. First, young people. Those of us who are older can at least remember the pre-Bowling Alone era. But young people now have to grow up in a more distrustful and atomized world. It used to be that people’s happiness levels followed a U-shaped curve. People felt happier when young, then it dipped in middle age (it’s called having teenage children), and then happiness levels rose again around retirement. Now the curve looks more like a slope. People are more miserable when young, doing OK in middle age and happiest in their senior years. Young Americans are the worst off among all age groups in that Global Flourishing Study, as are young people in Australia, Brazil, Germany, Sweden, Britain and other Western countries.

Progressives, and especially young progressives, are the other group that is suffering. Since researchers started measuring these things in 1972, conservatives have almost always been happier than progressives because conservatives are more likely to do the things that correlate with happiness, like get married, go to church, give to charity, feel patriotic, have more sex and feel their life has meaning.

But around 2011 something changed. Lower happiness levels transmogrified into higher levels of depression and mental illness, a related but different thing. That year, young progressives began reporting a significant rise in depression rates. A few years later, conservatives began reporting a similar rise, but not to the same degree. A 2024 survey by the Foundation for Individual Rights and Expression found that 35 percent of “very conservative” college students said they suffer from poor mental health at least half the time, which is terrible, but 57 percent of “very liberal” students did, which is horrendous.

There’s a lot going on to explain these depression rates, but one of them has got to be that progressives are more likely to embrace the autonomy and social freedom ethos described in that World Values Survey, and this hyperindividualistic ethos is not good for your social and spiritual health.

Let’s be clear about what’s happened here: greed. Americans have become so obsessed with economic success that we’ve neglected the social and moral conditions that undergird human flourishing. Schools spend more time teaching professional knowledge than they do social and spiritual knowledge. The prevailing values worship individual choice and undermine the core commitments that precede choice — our love for family, neighborhood, nation and the truth. There’s a lot of cultural work to do.

https://www.nytimes.com/2025/08/07/opinion/happiness-community-wealth.html


Searching for the Source of a Fountain of Courage

By Natalie Angier   NYTimes

  • Jan. 3, 2011

In his 20 years as a firefighter and paramedic in Colorado Springs, Bruce Monson, 43, has had his little fist-bumps with death: a burning roof collapsing on top of him, toxic fumes nearly suffocating him.

Yet far more terrifying than any personal threats are what Mr. Monson describes as the “bad kid calls,” like the one from a mother who had put her 18-month-old son down in his crib right next to a window with a Venetian blind and its old-fashioned cord.

“The kid had grabbed the cord and gotten it twisted around his neck, and the mother came in and found him hanging there,” said Mr. Monson. “I’m the first one in the door, she’s in a panic, and she shoves the kid into my arms, crying, ‘Please save him, please save him!’ ”

The child’s body was blue, but Mr. Monson and his fellows met parental despair with professional focus and did everything they could. “We worked on him for over an hour,” said Mr. Monson. “It’s like a state of calm. You’re so tuned in to what you’re doing, you’re not thinking about the reality of the situation.”

Their best was not enough, however, and later, at the hospital, the terrible sadness settled in.

As Mr. Monson filled out his report, the mother sat in the trauma room’s designated “bereavement rocking chair,” rocking her dead son, saying her goodbyes, while family members filed in and wailed at the sight.

An image of that mother in her rocking chair comes to Mr. Monson’s mind every time he answers another “bad kid” call, spurring him to keep going, to never give up or grow sloppy or cynical, to simply do his job; and through doing his job, he has saved far more lives than he has lost.

Only once did he allow the furniture connection to spook him — when his own wife was at the same hospital having emergency surgery for a ruptured ectopic pregnancy, and his young daughter happened to climb onto the bereavement seat. “I knew it was a totally irrational thing to do,” he said, “but I made her get out of that chair.”

Courage is something that we want for ourselves in gluttonous portions and adore in others without qualification. Yet for all the longstanding centrality of courage to any standard narrative of human greatness, only lately have researchers begun to study it systematically, to try to define what it is and is not, where it comes from, how it manifests itself in the body and brain, who we might share it with among nonhuman animals, and why we love it so much.

A new report in the journal Current Biology describes the case of a woman whose rare congenital syndrome has left her completely, outrageously fearless, raising the question of whether it’s better to conquer one’s fears, or to never feel them in the first place.

In another recent study, neuroscientists scanned the brains of subjects as they struggled successfully to overcome their terror of snakes, identifying regions of the brain that may be key to our everyday heroics.

Researchers in the Netherlands are exploring courage among children, to see when the urge for courage first arises, and what children mean when they call themselves brave.

The theme of courage claims a long and gilded ancestry. Plato included courage among the four cardinal or principal virtues, along with wisdom, justice and moderation.

“As a major virtue, courage helps to define the excellent person and is no mere optional trait,” writes George Kateb, a political theorist and emeritus professor at Princeton University. “One of the worst reproaches in the world is to be called a coward.”

Yet defining what it means to be courageous has often proved as thistly as distinguishing the wise ones from the fools. For Plato and many other authorities, courage is above all a martial art, most readily displayed on the battlefield — the iconic brave solder running into the line of fire to retrieve an injured comrade.

But Dr. Kateb points out that if courage finds its highest expression in war, then the trait paradoxically becomes an immoral virtue, ennobling war and carnage by insisting that only in battle can men — and it usually is men — discover the depths of their nobility.

Marilynne Robinson, the novelist and social critic, has observed that courage is “dependent on cultural definition” and “rarely expressed except where there is sufficient consensus to support it.” Where religious martyrdom is lionized, there will be martyrs; where social or political protest is seen as glorious warfare in civvies, there will be a rash of red-faced declaimers, soapboxes on every street.

In pioneering work from 1970s and beyond, Stanley J. Rachman of the University of British Columbia and others studied the physiology and behavior of paratroopers as they prepared for their first parachute jump.

The work revealed three basic groups: the preternaturally fearless, who displayed scant signs of the racing heart, sweaty palms, spike in blood pressure and other fight-or-flight responses associated with ordinary fear, and who jumped without hesitation; the handwringers, whose powerful fear response at the critical moment kept them from jumping; and finally, the ones who reacted physiologically like the handwringers but who acted like the fearless leapers, and, down the hatch.

These last Dr. Rachman deemed courageous, defining courage as “behavioral approach in spite of the experience of fear.” By that expansive definition, courage becomes democratized and demilitarized, the property of any wallflower who manages to give the convention speech, or the math phobe who decides to take calculus.

Through interviews with some 320 children aged 8 to 13, Peter Muris of Erasmus University Rotterdam and his colleagues found that children also equate courage with the conquering of one’s fears, and more than 70 percent of the respondents claimed they had performed one or more brave acts, including rescuing a little brother who’d fallen in the swimming pool, saving a cat from a tree, biking home through the woods at night, and stealing money from one’s mother’s purse — yes, that will make the heart race, all right.

Joel Berger, a biologist with the Wildlife Conservation Society and the University of Montana, also distinguishes between animals that behave boldly for lack of experience — like mockingbirds unfamiliar with humans that will alight on the rim of a person’s cup to take a drink — and those that are aware of a danger but proceed in the face of it.

He cited the time he and his colleagues had immobilized a young bison in preparation for taking blood samples, and when they returned, an unrelated adult male bison was standing guard over the yearling, refusing to let the scientists approach.

“He knew that he could be attacked by us, and there was no genetic kinship involved,” said Dr. Berger. “Courage may be a human construct, but I’d call this a courageous, even heroic act.”

Seeking to capture the sensation of courage in real time, Yadin Dudai, a neurobiologist at the Weizmann Institute of Science in Rehovot, Israel, and his colleagues scanned the brains of people with a known phobia toward snakes as they were confronted with a live, large, harmless but indubitably serpentine corn snake.

Lying in the scanner, the subjects could choose either to allow a box holding the snake to come closer, or to keep it away. As reported last June in the journal Neuron, the participants who squelched their terror and pressed the “snake approach” button showed activation of a brain region called the subgenual anterior cingulate cortex.

Located toward the front of the brain, the structure has been implicated in depression and, intriguingly, altruistic behavior, and is thought to help negotiate between emotion and cognition, impulse and calculation.

The thumb-size bundle of neurons acknowledges the yellow belly within but then moves to stanch its quivering power. And it does this in large part by dialing down the activity of the amygdala, long known as the brain’s central headquarters of fear.

For the serious cowards among us, the chronic need to conquer fear can get tedious. Why not just skip the anterior cingulate reveille and muzzle the brain’s fear response for good? The story of SM, a 44-year-old woman whose rare genetic condition has selectively destroyed the brain’s twinned set of amygdala, shows the clear downside of a life without fear.

As Justin Feinstein, a clinical neuropsychologist at the University of Iowa, and his colleagues describe in Current Biology, the otherwise normal SM is incapable of being spooked.

She claimed to fear snakes and spiders, and maybe she did in her pre-disease childhood, but when the researchers took her to an exotic pet store, they were astonished to see that not only did she not avoid the snakes and spiders, she was desperate to hold them close.

The researchers took SM to a haunted house, and she laughed at the scary parts and blithely made the monster-suited employees jump. She was shown clips from famous horror films like “The Silence of Lambs” and “Halloween,” and she showed no flickers of fright.

This fearlessness may be fine in the safety of one’s living room, but it turns out that SM makes her own horror films in real life. She walks through bad neighborhoods alone at night, approaches shady strangers without guile, and has been repeatedly threatened with death.

“We have an individual who’s constantly putting herself into harm’s way,” said Mr. Feinstein. “If we had a million SMs walking around, the world would be a total mess.”

The bad calls would keep coming, and the rocking chairs never stop.

https://www.nytimes.com/2011/01/04/science/04angier.html

The Curiosity We Lost—and Why It Matters More than Ever

kieferpix

Key points

  • Curiosity is innate, not learned. Our natural curiosity fuels both learning and connection.
  • Structured systems can suppress curiosity.
  • In adulthood, our lost curiosity results in shallower relationships and less collaborative workplaces.
  • Reigniting curiosity rebuilds trust and connection.

Simon was recently walking through the park with his three-year-old daughter. Autumn had truly arrived, and brown leaves lay scattered across the ground beneath the bare trees. Simon’s daughter saw a small boy playing among the leaves and ran over to see what he was doing. The two quickly formed an unspoken bond as they joined forces, collecting the discarded leaves into piles.

If you have children, you are almost certainly familiar with this scene, or one like it. Children naturally want to understand what’s happening around them, and that curiosity helps them to connect with anyone, or anything, that intrigues them. When there’s something new and exciting to discover, social anxiety is easily forgotten. Connections are easily forged.

How often do you see adults engaging in the same way? We certainly find it easier to bond over something we know we have in common: Witness strangers hugging when their team has scored or singing together at their favourite band’s concert. But beyond those specific settings, we tend to be more reserved when meeting new people, very conscious of the proper social etiquette and careful not to cross boundaries.

What became of the natural curiosity we had when we were young? To that bridge between discovery and connection that opened new worlds and friendships?

Born Curious

Lydia Redman, an early years expert working for the Royal Borough of Greenwich in the UK, regards curiosity as a fundamental trait of young children. “We are born curious,” she said. “Curiosity is naturally innate in young children. I’ve never met a child whose curiosity wasn’t evident. Their brain makes thousands of connections every day.”

The childlike sense of wonder is fundamental to the qualities of effective learners that early childhood educators, like Redman, strive to nurture. The Tickell Review, reporting on the foundational impact of the early years, explains how children learn and outlines three key characteristics:

  • Playing and exploring (engagement)
  • Active learning (motivation)
  • Creating and thinking Critically (thinking)

Redman sees curiosity as “the root of all of those skills that we want children to develop.” The view aligns with research by Jonathan Haidt highlighting the importance of unstructured play in allowing children to freely explore and cultivate their natural curiosity.

Curiosity helps young people develop critical minds and build connections. It’s both a learning tool and a social link.article continues after advertisement

And it is just as important to us in adulthood as it is to children.

Where Does Our Curiosity Go?

In his book The Anxious Generation, Haidt contends that a decline in unstructured play, which began in the 1990s, has contributed to various developmental issues, including an inhibited capacity for curiosity, creativity, and problem-solving. Redman has also observed that as education becomes more formalised, curiosity is impacted.

“We begin to see less emphasis and less allowance for curiosity as people move through later childhood and into their teens. The British education system begins formal learning for children at a very early age. We place a great emphasis on knowledge and output, which can often lead to excessive cramming. It’s not helping our children to be curious and become problem solvers.”

A focus on regurgitating knowledge rather than solving problems, and the subsequent suppression of curiosity, impacts us as we transition from childhood to our teenage years and then into adulthood and the workplace.

We move from playground to classroom, then to lecture hall, and finally to meeting room. At each stage, we feel the weight of structure, hierarchy, and an increasing fear of giving the wrong response.

Our natural impulse to explore and challenge gets suppressed and replaced by a desire to conform and give the expected response.

Curiosity in the Workplace

The inhibition of curiosity impacts the workplace and our relationships. The pressure of deadlines and expectations adds to the suppression of our desire to explore. We concentrate on the agenda and the task in front of us, rather than seeking to learn and develop. Narrow conversations mean we miss the chance to get to know our colleagues better.

Of course, some workplaces promote more curiosity than others. People in the engineering and creative sectors still need to maintain a sense of play to succeed in their roles. However, that doesn’t mean their curiosity influences every aspect of their job.

As leaders, we must take the initiative and rekindle a sense of curiosity among those who work for and with us. Simple steps, such as encouraging more conversations and connections without an agenda, can have a significant impact. Allow time in meetings for small talk and catch-ups, and organise meetings in which you explore what could have been done differently on a recent project to improve outcomes—without assigning blame or finger-pointing.

Curiosity isn’t about knowing the answer; it’s about genuinely listening and seeking understanding. Leaders need to foster a culture in which there are no definitive or expected answers but in which exploration and challenge are embraced. Conversations should include active listening and authentic engagement, as modelled in The Curiosity Cycle..

The Foundation of Connection

Children who start playing together out of shared curiosity and play are not intentionally building relationships; they are discovering them naturally. As adults, many of us have lost that sense of magic and spontaneity. If we can reignite the spirit of exploration, we too can connect more deeply and form stronger relationships and more meaningful bonds, reliving the magic we experienced as children.

References

Dame Clare Tickell. (2011). The Early Years: Foundations for Life, Health and Learning.

Lukianoff, G., & Haidt, J. (2018). The Coddling of the American Mind: How good intentions and bad ideas are setting up a generation for failure. Penguin Books.

Haidt, J. (2024). The Anxious Generation: How the Great Rewiring of Childhood Is Causing an Epidemic of Mental Illness. New York, NY: Penguin Press.

About the Author

Andy Lopata

A specialist in professional relationships and networking for over 25 years, Andy Lopata is an experienced international speaker, podcast host, and the author of six books on the topic.

https://www.psychologytoday.com/us/blog/connected-leadership/202511/the-curiosity-we-lost-and-why-it-matters-more-than-ever

What Experiences Have Helped Build Your Confidence?

A surfer crashes into the water after being knocked off a surfboard by a wave.

By Shannon Doyne and Natalie Proulx
Dec. 2, 2025 NYTimes

Have you ever struggled with confidence? If so, have you ever had an experience that helped you learn to believe in yourself more?

Maybe it was learning or getting better at a skill, like photography or soccer. Maybe it was taking on a big responsibility, as in working a job or caring for your family pet. Or perhaps it was succeeding at something that once scared you, such as speaking in front of a crowd or making new friends.

What did you learn from this experience? How did it change you?

In “At a Queens Surf School, Kids’ Confidence Comes in Waves,” Aimee Ortiz writes about a surfing program for children in New York City that, for some students, “changed everything.” The article begins:

Ask Claudia Acuña about Louis Harris and the East Coast chapter of the Black Surfing Association, and she’ll tell you they “saved my kid’s life.”

For the last five years, Ms. Acuña and her son, Daniel Kelley, 14, have been part of a community that Mr. Harris built in Rockaway Beach, Queens.

Mr. Harris, 53, founded the chapter in 2016. The nonprofit, which is funded through donations and corporate sponsorships, offers free surfing lessons on summer weekend mornings and equipment to any child who shows up.

Parents whose children Mr. Harris has taught say his efforts have transformed their children’s lives.

Among them is Daniel. His mother, Ms. Acuña, said her son was depressed in the summer of 2020, dealing with the pandemic and bullying, when Mr. Harris’s surf school provided a lifeline.

The program “completely changed everything,” she said, adding that Daniel blossomed and his confidence soared. “As a mother,” she said, “it’s the most beautiful gift that any mother can have.”

Many children of color are not accustomed to seeing “surfers that look like them, that look like Mr. Lou,” Ms. Acuña said, referring to Mr. Harris, who is Black.

Mr. Harris, she added, had set an example as a positive male role model, noting that he had taught her son about masculinity “with the tenderness and the softness of the water.”

The article continues:

Suzanne Cope said the surf school has taught her son, Rocco, 12, “to fail over and over again” while still wanting “to go back and do the same thing to try and get better.” There are few opportunities for children “to really learn that kind of grit,” she said.

Students, read the entire article and then tell us:

  • Have you ever had an experience that helped improve your confidence, as learning to surf did for these children? If so, what was it, and how did it change you? If not, does the article inspire you to try something new?
  • How important are role models like Mr. Harris, the surf coach? Have you ever met someone — or looked up to someone from afar — who helped you believe in yourself? What did you learn from that person?
  • One mother said that surfing had taught her son “to fail over and over again” while still wanting “to go back and do the same thing to try and get better.” What is the value in learning to fail and then get back up and try again? Have you ever had an experience like that?
  • How confident of a person are you? If you’re working on building up your confidence, what is one activity or experience you might like to try to help support your self-image? How do you think it would help?

https://www.nytimes.com/2025/12/02/learning/what-experiences-have-helped-build-your-confidence.html?searchResultPosition=8

What Little Victory Would You Like to Celebrate?

An illustration shows a fish, mouth agape, celebrating its birthday. Cats look on.


By 
Natalie Proulx  NYT Dec 5th 2025

What good things — no matter how small — have happened in your life recently?

Did you turn in a school project you’ve been working on for weeks? Try out a different hairstyle and get compliments? Discover a new favorite snack? Score your first touchdown?

Do you take the time to acknowledge these little milestones and accomplishments enough in your life?

In “Little Victories,” a July edition of The Morning newsletter, Melissa Kirsch argues we should all be celebrating our tiny achievements more often:

This week, I went to a party thrown by a New York City deli to celebrate a specific varietal of herring. I was keen to attend because the concept of a herring party seemed delightful — an occasion for revelry that I’d never considered. I was intrigued to learn that in the Netherlands, this particular herring is traditionally fished for only a few months, when the herring’s body fat reaches at least 16 percent, for maximum flavor. The Dutch even have an annual festival, Flag Day, to honor the opening of herring season.

I had never celebrated herring before, but, then again, I haven’t celebrated most things. We tend to confine our parties to milestones (birthdays, holidays, housewarmings, weddings) and cultural events (the Oscars, the Super Bowl). Why must it be this way? Sure, if every day is a special occasion, then no day is, but it seems unnecessary to let the calendar totally dictate when we raise a glass or kick up our heels. Also, it’s sort of boring to glorify the same things year after year, when there’s so much else out there that’s worthy.

Once you begin considering all the micro-occasions deserving of a rager or at least an intimate soiree, you realize you’ve been letting so many opportunities for merrymaking just sail right by. A New Haircut Party sounds fun (you tried a new style, you look great) as does a My Back Pain Finally Went Away Party (has there ever been a more profound reason to exult?). New tattoo, old tattoo removal; the puppy spent a full night in the crate; no cavities — let’s rejoice!

Students, read the entire article and then tell us:

  • What is your reaction to the article? Do you agree with Ms. Hirsch that it’s important to acknowledge even the smallest of good things in our lives? Why, or why not?
  • What is one recent little victory that you’d like to celebrate? Why do you want to honor this moment or achievement?
  • How would you want to mark this occasion? Would you throw a party? Have a solo dance session in your living room? Go out for ice cream? Describe your ideal celebration.
  • Now that you’ve taken stock of at least one of your micro-joys, how do you feel? Is this something you do enough? Would you like to do it more often? How do you think it would affect your life if you did?

https://www.nytimes.com/2025/12/05/learning/what-little-victory-would-you-like-to-celebrate.html?searchResultPosition=4

Why Are So Many Young People Disconnected?

A male teenager lies in his bed looking at his phone. Photo by pressmaster/Adobe Stock
RAND

Stephanie BondsJennie W. Wenger

Expert InsightsPublished Oct 29, 2025

Key Takeaways

  • About 15 percent of young people in middle and high school (ages 11 to 18) become disconnected—that is, not engaging in school, training, or work—by ages 18 to 24.
  • Youth who eventually become disconnected are different from their connected peers across several dimensions at baseline: They are more likely to report symptoms of depression, use substances, engage in delinquent activities, and have weaker social support structures.
  • Suspension in school is a risk factor for later disconnection for males, even after accounting for other observed family and school characteristics.
  • Early pregnancy (before age 18) is a risk factor for disconnection for females, even after accounting for other observed family and school characteristics.

Young people who are neither in school nor working, often called disconnected youth or opportunity youth, face challenges that can lead to lower lifetime earnings, poorer health, and lower socioeconomic outcomes (Belfield, Levin, and Rosen, 2012; MaCurdy et al., 2006; Hair et al., 2009; Lewis, 2021). Disconnection also generates broader social costs through lost productivity and higher social spending. Effective policy solutions require a clear understanding of the factors that lead some youth to become disconnected.

Existing research points to a variety of potential factors that might influence disconnection in young adulthood, including family environment, mental health, educational attainment, and behavioral factors, among others (Cohen and Wills, 1985; Currie and Thomas, 2001; Furstenberg and Hughes, 1995; Heckman, Stixrud, and Urzua, 2006; Hanushek and Woessmann, 2008). However, data on these measures is limited and researchers are rarely able to follow young people prior to and across spells of disconnection.

In this paper, we use data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to examine who disconnected youth are and what factors precede disconnection (Harris and Udry, 2022). Add Health is a representative sample of adolescents who were in grades 7 through 12 during the 1994–1995 school year and have been followed through 2018. Our sample of disconnected youth consists of individuals aged 18 to 24 who were not in school and not working at the time of the third wave of the Add Health survey (conducted between 2001 and 2002).⁠[1] Nearly all (99.7 percent) of our respondents were connected at baseline, given that the initial sampling was restricted to students in middle and high school.⁠[2]

Overall, our findings highlight both the complexity of the pathways leading to disconnection and the potential for early targeted interventions to alter these trajectories. This paper will be of interest to researchers, policymakers, and practitioners who are developing programs that reconnect youth with education, training, or employment.

Who Is Disconnected?

We first examine the demographic characteristics of those who are disconnected. Overall, 15 percent of youth in our sample are disconnected. Disconnected youth are more likely to be female and twice as likely as connected youth to be a parent (Table 1).⁠[3] This appears to be driven by women with children: 32 percent of women with children are disconnected compared with 12 percent of women without children. Men with children have slightly higher rates of disconnection than do men without children (18 percent versus 13 percent) but much lower than the rate for women with children.

Disconnected youth have lower levels of education than do connected youth (Table 1): They are three times as likely to not complete high school and 50 percent more likely to have only a high school degree. They are far less likely to have attended college. Similar to other observational studies, we find that disconnected youth are more likely than connected youth to be Black and less likely to be White. Being Hispanic, Native American, Asian or Pacific Islander, or another race or ethnicity does not predict disconnection in this sample. Rates of disconnection are similar among those who were born in the United States and those who were not.⁠[4]

Table 1. Means of Demographic Characteristics, by Disconnected Status

Demographic CharacteristicConnectedDisconnectedDifference
Female0.490.550.06*
Parent0.150.310.16***
Less than high school education0.110.330.21***
Completed high school0.290.460.16***
Some college education or more0.600.22–0.38***
Hispanic0.110.120.01
White0.770.63–0.14***
Black0.140.280.14***
Native American0.040.040.01
Asian or Pacific Islander0.040.03–0.01
Other race0.060.060.00
Born in the United States0.930.950.02

SOURCE: Features data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) (Harris and Udry, 2022), a representative sample of adolescents who were in grades 7 to 12 during the 1994–1995 school year, and have been followed through 2018.

NOTE: We use individual (person) weights to create statistics that are representative of the U.S. population. Asterisks denote statistically significant differences at the 10 percent (*), 5 percent (**), and 1 percent (***) levels, respectively.

What Early-Life Factors Precede Disconnection?

Beyond examining who is disconnected, we also use the panel nature of the data to examine early-life characteristics that precede—and might explain—disconnection.⁠[5] Using the baseline wave that surveyed respondents when they were in school (ages 11 through 18), we construct baseline measures of explanatory variables that are thought to influence disconnection later in life (Table 2).⁠[6]

Table 2. Variable Descriptions

DomainVariables
Home environmentParental education and household income
Academic performance and engagementEnglish language arts (ELA) and math test scores and a binary indicator for suspension at baseline
Mental healthComposite measure of mental health using the Center for Epidemiologic Studies Depression (CES-D) scale
Substance useIndicators of substance initiation, including alcohol, cigarette, and drug use
DelinquencyIndex of delinquency, based on a set of survey measures
Social supportIndex of perceived social support from peers, family, and teachers, based on a set of survey measures

SOURCE: Features information from the National Longitudinal Study of Adolescent to Adult Health (Add Health) (Harris and Udry, 2022).

Home Environment

The data reveal several patterns (Figure 1). First, household and parental factors appear to be important for disconnection, consistent with the literature on parental factors and child socioeconomic outcomes (for examples of reviews, see Haveman and Wolfe, 1995; Duncan and Murnane, 2011). Students from below the top quartile of income and parental education are nearly twice as likely to be disconnected in young adulthood. Finally, females who had ever been pregnant at baseline (by ages 11 through 18) are significantly more likely to be disconnected later in life.

A bar chart that measures connection (blue) versus disconnection (magenta) across 13 factors
Figure 1. Early-Life Correlates of Disconnection

School: Academic Performance and Engagement

Students scoring within the top quartile in math and ELA test scores are less likely to become disconnected. This is consistent with a large body of research that suggests that academic performance predicts future labor market success (see Currie and Thomas, 2001; Heckman, Stixrud, and Urzua, 2006; Hanushek and Woessmann, 2008; among others). An indicator for whether a student was ever suspended at baseline (“ever suspended”) is significantly correlated with disconnection. This could reflect both behavioral issues and disengagement with school.

Mental Health

Disconnection is correlated with a higher likelihood of being clinically depressed at baseline, as measured by the CES-D scale (Radloff, 1977).⁠[7] This result masks substantial heterogeneity by gender. Young women who report symptoms of depression are significantly more likely to become disconnected. There are no significant differences in depression rates between disconnected versus connected males. As alternative indicators for mental health, we also examine self-reported suicidal ideation and suicide attempts. Both indicators are also higher for disconnected youth overall. Disconnected females have significantly higher suicidal ideation than connected females; disconnected males have higher (although not significantly different) suicide attempts than connected males. These results suggest that disconnected youth are more likely to have faced mental health challenges of some kind during high school.

Behavioral Risk Factors: Substance Use and Delinquency

A body of research links child conduct problems and substance use to poorer adult outcomes across education, employment, and health (Balsa, Giuliano, and French, 2011; Farrington, 2005; Fergusson, Horwood, and Ridder, 2005). We use a series of variables on substance use during high school (including alcohol, cigarettes, and illegal drugs) to examine how substance initiation correlates with disconnection. We also use a set of survey questions on delinquency to create an index for child conduct issues.⁠[8] This includes self-reported answers to questions asking whether the child has painted graffiti, damaged property, lied to parents or guardians about activities, stolen items, taken part in violence, or sold drugs at baseline. Disconnected youth have significantly higher reported cigarette and drug use during high school (the time of the baseline survey) than connected youth. Disconnected youth are 10 percent more likely to have ever smoked cigarettes during high school and nearly 20 percent more likely to have ever used drugs.⁠[9] There is no significant difference in alcohol use between the two groups. This pattern of results is similar across gender. Disconnected youth score significantly higher on the baseline delinquency index, suggesting that behavioral and conduct issues might be an important risk factor for disconnection. This is consistent with the higher likelihood of suspension discussed above.

Social Support

Finally, social support, whether from family, peers, or community, might be one mitigating factor that helps individuals navigate challenges during adolescence and ultimately reduce the risk of disconnection. Strong social ties have been linked to better adult outcomes, including educational attainment, labor market attachment, and psychological well-being (Cohen and Wills, 1985; Furstenberg and Hughes, 1995; Crosnoe and Elder, 2004). We constructed a social support index from a module measuring respondents’ reported feelings of being supported and understood by parents, teachers, and friends. Consistent with the literature, higher social support during high school is correlated with a reduction in disconnection in early adulthood.

Suspension for Males and Early Pregnancy for Females Strongly Correlate with Disconnected Status, All Else Being Equal

Our results so far have examined differences in means across disconnected and connected populations. However, these relationships might be picking up spurious correlation with other factors. As our final analysis, we use multivariate regression analysis to examine all factors together, both overall and separately by gender (Figure 2).⁠[10] This allows us to examine the relationship between each variable and disconnection, holding constant the influence of other factors. “Ever pregnant” and “ever suspended” remain highly positively correlated with disconnection. Examining the data separately by gender, “ever suspended” is only a significant correlate for males.⁠[11] “Ever pregnant” at baseline is, by definition, only a significant correlate for females.

Suspension and early pregnancy might be mediating factors through which the other covariates affect disconnection. We examine correlates of suspension for males and correlates of early pregnancy for females.⁠[12] For males, substance use (drugs and, to some extent, alcohol), high scores on the delinquency index, and being Black are positively correlated with suspension. Higher parental education, household income, ELA scores, and math scores are negatively correlated with suspension. These results are consistent with literature that suggests that school discipline, particularly suspension, is disproportionately applied to males and Black students (Okonofua and Eberhardt, 2015; Skiba et al., 2011). These practices are linked to worse academic and longer-term outcomes (Bacher-Hicks, Billings, and Deming, 2024; Perry and Morris, 2014). Alternative methods, such a restorative justice, have been shown to reduce suspensions, but they may need to be paired with academic supports to sustain achievement (Augustine et al., 2018; Gregory et al., 2016). Such measures may (or may not) serve to reduce eventual disconnection. For females, substance use (drugs), depression, and being Black are correlated with early pregnancy. These are purely correlational, but might shed light on risk factors that precede both early pregnancy and suspension and later disconnection.

Figure 2. Correlates of Disconnection, Regression-Adjusted

Probability of disconnection (with 95% CI)A dot plot comparing the probability of disconnection across many groups like female, household income, parent education, and Hispanic, for example.−0.2−0.100.10.20.30.4Female−0.0080.0470.101Household income (top quartile)−0.063−0.020.023Parent education (top quartile)−0.09−0.0420.006Parent married−0.085−0.0070.071Ever pregnant0.0860.2310.375ELA score (top quartile)−0.082−0.0270.028Math score (top quartile)−0.056−0.0080.041Ever suspended0.0660.1140.163Depression (CES-D)−0.067−0.0110.045Substance use: alcohol−0.089−0.0390.011Substance use: cigarettes−0.072−0.0160.041Substance use: drugs−0.0490.0760.202Delinquency Index−0.044−0.0150.013Social Support Index−0.043−0.024−0.005Hispanic−0.103−0.0210.061Black−0.0230.0810.184Native American−0.142−0.0390.064Asian/Pacific Islander−0.080.0070.093Other race−0.1250.0180.161Born in the United States−0.0870.0240.136

95% confidence intervals in brackets

  • Female = 0.0465 [-0.00783t to 0.101]
  • Household Income (Upper Quartile) = -0.0199 [-0.0625 to 0.0228]
  • Parent Education (Upper Quartile) = -0.0422 [-0.0902 to 0.00581]
  • Parent Married = -0.00722 [-0.0853 to 0.0708]
  • Ever Pregnant = 0.231 (p<0.01) [0.0862 to 0.375]
  • ELA Score (Upper Quartile) = -0.0271 [0.0821 to 0.0279]
  • Math Score (Upper Quartile) = -0.00765 [-0.0560 to 0.0407]
  • Ever Suspended = 0.114 (p<0.001) [0.0655 to 0.163]
  • Depression (CES-D) = -0.0110 [-0.0673 to 0.0453]
  • Substance Use: Alcohol = -0.0388 [-0.0888 to 0.0112]
  • Substance Use: Cigarettes = -0.0155 [-0.0718 to 0.0408]
  • Substance Use: Drugs = 0.0762 [-0.0492 to 0.202]
  • Delinquency Index = -0.0154 [-0.0435 to 0.0128]
  • Social Support Index = -0.0244 (p<0.05) [-0.0434 to -0.00547]
  • Hispanic = -0.0213 [-0.103 to 0.0608]
  • Black = 0.0805 [-0.0230 to 0.184]
  • Native American = -0.0388 [-0.142 to 0.0642]
  • Asian/Pacific Islander = 0.00660 [-0.0800 to 0.0932]
  • Other race = 0.0180 [-0.125 to 0.161]
  • Born in the United States = 0.0244 [-0.0869 to 0.136]
  • Constant = 0.127 (p<0.05) [0.00295 to 0.250]
  • Observations = 1598

SOURCE: Features data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) (Harris and Udry, 2022), a representative sample of adolescents who were in grades 7 to 12 during the 1994–1995 school year, and have been followed through 2018.

NOTE: This figure plots the coefficients from a linear regression of disconnection on the set of covariates. “White” is the excluded racial category. “Ever pregnant” is coded as 0 if the respondent was male. The upper and lower bounds show the 95-percent CI for each covariate. We use individual (person) weights to create statistics that are representative of the U.S. population.

The Path Forward

We provide preliminary evidence on the predictive factors that are associated with disconnection, including some of the first analyses using Add Health data to explore these relationships. Even in the years before disconnection emerges, youth who eventually become disconnected are different from their connected peers across several dimensions. They are more likely to report symptoms of depression, experience an early pregnancy, use substances, engage in delinquent activities, have weaker social support structures, and be suspended from school. Early pregnancy and school suspension, in particular, may serve as pathways through which other risk factors translate into later disconnection.

These estimates are descriptive rather than causal, and unobserved factors correlated with our explanatory variables may drive both early-life risks and eventual disconnection. However, this analysis highlights a set of risk factors that are likely to shape longer-run outcomes and provides a foundation for future research.

This work points to several implications for policymakers. First, early identification and prevention of risk factors associated with disconnection is critical. Eventual disconnection is correlated with academic performance, school suspension, early pregnancy, and substance use; this suggests that risks emerge early on. Preventative policies that reduce these risk factors and improve academic performance may reduce the likelihood of later disconnection.

Second, the links between suspension and disconnection suggest that restorative justice programs may not only be effective in reducing suspensions but also in reducing later disconnections. Restorative approaches emphasize repairing harm, relationship-building, and prevention, rather than excluding children from school. Evidence shows that restorative justice practices are effective in reducing suspension rates (Augustine et al., 2018; Gregory et al., 2016). This in turn may reduce the likelihood of youth disconnection by keeping students engaged in school.

Finally, evidence gaps remain. Evaluations of programmatic and policy interventions targeting these explanatory variables might help clarify mechanisms that lead to disconnection. For instance, evaluations of school-based programs that reduce suspensions or evaluations of interventions that delay early pregnancy could shed light on whether addressing these risk factors reduces disconnection. Importantly, future research should explicitly consider disconnection itself as a key outcome, assessing not only whether interventions affect intermediate risk factors but also whether they ultimately reduce the likelihood of youth becoming disconnected.

Appendix. Additional Figures

View Appendix

This appendix presents results from supplementary analyses referenced in the paper. Figure A.1 shows correlates of disconnection disaggregated by gender, Figure A.2 shows correlates of “ever suspended” among males, and Figure A.3 shows correlates of “ever pregnant” among females.

Figure A.1. Correlates of Disconnection: Male Versus Female, Regression-Adjusted

Probability of disconnection (with 95% CI)A dot plot comparing probability of disconnectedness of male versus female across various features like household income, parent education, ELA score, and math score, for example.Household income (upper quartile)−0.500.5Male−0.076−0.0320.013Female−0.1120.0210.154Parent education (upper quartile)−0.500.5Male−0.085−0.0370.011Female−0.164−0.0480.068ELA score (upper quartile)−0.500.5Male−0.067−0.0060.055Female−0.167−0.0770.013Math score (upper quartile)−0.500.5Male−0.074−0.0170.041Female−0.0980.0010.099Ever suspended−0.500.5Male0.0530.110.167Female−0.0290.1070.242Depression (CES-D)−0.500.5Male−0.124−0.0520.019Female−0.0090.0740.158Substance use: alcohol−0.500.5Male−0.104−0.0460.012Female−0.184−0.070.045Substance use: cigarettes−0.500.5Male−0.0510.0040.059Female−0.253−0.1060.041Substance use: drugs−0.500.5Male−0.0280.1180.265Female−0.1920.0420.276Delinquency Index−0.500.5Male−0.037−0.0070.023Female−0.114−0.0560.002Social Support Index−0.500.5Male−0.058−0.035−0.012Female−0.0340.0070.048Hispanic−0.500.5Male−0.109−0.0340.041Female−0.2040.0410.287Black−0.500.5Male−0.0070.1090.226Female−0.157−0.0290.098Native American−0.500.5Male−0.173−0.0810.012Female−0.2180.0990.417Asian/Pacific Islander−0.500.5Male−0.102−0.0230.056Female−0.1210.1640.449Other race−0.500.5Male−0.0740.0610.196Female−0.502−0.1510.2Born in the United States−0.500.5Male−0.090.0170.125Female−0.331−0.0070.317Ever pregnant−0.500.5MaleFemale0.0620.2160.369

95% confidence intervals in brackets

Household Income (Upper Quartile)

  • Male = -0.0317 [-0.0763 to 0.0129]
  • Female = 0.021 [-0.112 to 0.154]

Parent Education (Upper Quartile)

  • Male = -0.0371 [-0.0849 to 0.0108]
  • Female = -0.0476 [-0.164 to 0.0684]

ELA Score (Upper Quartile)

  • Male = -0.00632 [-0.0672 to 0.0545]
  • Female = -0.0772 [-0.167 to 0.0128]

Math Score (Upper Quartile)

  • Male = -0.0169 [-0.0744 to 0.0406]
  • Female = 0.00071 [-0.0980 to 0.0994]

Ever Suspended

  • Male = 0.110 (p<0.001) [0.0531 to 0.167]
  • Female = 0.107 [-0.0288 to 0.242]

Depression (CES-D)

  • Male = -0.0524 [-0.124 to 0.0190]
  • Female = 0.0743 [-0.00944 to 0.158]

Substance Use: Alcohol

  • Male = -0.0461 [-0.104 to 0.0119]
  • Female = -0.0695 [-0.184 to 0.0454]

Substance Use: Cigarettes

  • Male = 0.00379 [-0.0513 to 0.0589]
  • Female = -0.106 [-0.253 to 0.0410]

Substance Use: Drugs

  • Male = 0.118 [-0.0281 to 0.265]
  • Female = 0.0422 [-0.192 to 0.276]

Delinquency Index

  • Male = -0.00701 [-0.0366 to 0.0226]
  • Female = -0.0558 [-0.114 to 0.00225]

Social Support Index

  • Male = -0.0352 (p<0.01) [-0.0581 to -0.0123]
  • Female = 0.00696 [-0.0341 to 0.0481]

Hispanic

  • Male = -0.0339 [-0.109 to 0.0413]
  • Female = 0.0412 [-0.204 to 0.287]

Black

  • Male = 0.109 [-0.00726 to 0.226]
  • Female = -0.0293 [-0.157 to 0.0984]

Native American

  • Male = -0.0809 [-0.173 to 0.0115]
  • Female = 0.0992 [-0.218 to 0.417]

Asian/Pacific Islander

  • Male = -0.0228 [-0.102 to 0.0560]
  • Female = 0.164 [-0.121 to 0.449]

Other race

  • Male = 0.0609 [-0.0742 to 0.196]
  • Female = -0.151 [-0.502 to 0.200]

Born in the United States

  • Male = 0.0173 [-0.0902 to 0.125]
  • Female = -0.00718 [-0.331 to 0.317]

Ever Pregnant

  • Female = 0.216 (p<0.01) [0.0624 to 0.369]

Constant

  • Male = 0.127 (p<0.05) [0.0127 to 0.240]
  • Female = 0.306 [-0.0407 to 0.653]

Observations

  • Male = 1187
  • Female = 414

SOURCE: Features data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) (Harris and Udry, 2022), a representative sample of adolescents who were in grades 7 to 12 during the 1994–1995 school year, and have been followed through 2018.

NOTE: This figure plots the coefficients from a linear regression of disconnection on the set of covariates conducted separately for males and females. “White” is the excluded racial category. The upper and lower bounds show the 95-percent CIs for each covariate. We use individual (person) weights to create statistics that are representative of the U.S. population.

Figure A.2. Correlates of Ever Suspended for Males

Probability of suspension: Males (with 95% CI)A dot plot comparing probability of suspension of males across various features like household income, parent education, ELA score, and math score, for example.−0.2−0.100.10.20.30.4Household income (top quartile)−0.083−0.046−0.008Parent education (top quartile)−0.158−0.123−0.089ELA score (top quartile)−0.15−0.112−0.075Math score (top quartile)−0.091−0.057−0.024Depression (CES-D)−0.0390.0070.054Substance use: alcohol0.0020.0420.083Substance use: cigarettes−0.0260.0140.054Substance use: drugs0.0730.190.306Delinquency Index0.0840.1110.138Social Support Index−0.0140.0050.025Hispanic−0.0760.0080.092Black0.170.2350.3Native American−0.0440.0610.166Asian/Pacific Islander−0.0290.0620.152Other race−0.0870.020.128Born in the United States−0.163−0.087−0.011

95% confidence intervals in brackets

  • Household Income (Upper Quartile) = -0.0457 (p<0.05) [-0.0829 to -0.00845]
  • Parent Education (Upper Quartile) = -0.123 (p<0.001) [-0.158 to -0.0885]
  • ELA Score (Upper Quartile) = -0.112 (p<0.001) [-0.150 to -0.0748]
  • Math Score (Upper Quartile) = -0.0574 (p<0.001) [-0.0906 to -0.0242]
  • Depression (CES-D) = 0.00733 [-0.0391 to 0.0538]
  • Substance Use: Alcohol = 0.0424 (p<0.05) [0.00159 to 0.0832]
  • Substance Use: Cigarettes = 0.0143 [-0.0257 to 0.0543]
  • Substance Use: Drugs = 0.190 (p<0.01) [0.0730 to 0.306]
  • Delinquency Index = 0.111 (p<0.001) [0.0841 to 0.138]
  • Social Support Index = 0.00533 [-0.0140 to 0.0247]
  • Hispanic = 0.00800 [-0.0761 to 0.0921]
  • Black = 0.235 (p<0.001) [0.170 to 0.300]
  • Native American = 0.0614 [-0.0435 to 0.166]
  • Asian/Pacific Islander = 0.0617 [-0.0290 to 0.152]
  • Other race = 0.0202 [-0.0872 to 0.128]
  • Born in the United States = -0.0873 (p<0.05) [-0.163 to -0.0114]
  • Constant = 0.356 (p<0.001) [0.262 to 0.450]
  • Observations = 2545

SOURCE: Features data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) (Harris and Udry, 2022), a representative sample of adolescents who were in grades 7 to 12 during the 1994–1995 school year and have been followed through 2018.

NOTE: This figure plots the coefficients from a linear regression of suspension on the set of covariates conducted separately for males. “White” is the excluded racial category. The upper and lower bounds show the 95-percent CIs for each covariate. We use individual (person) weights to create statistics that are representative of the U.S. population.

Figure A.3. Correlates of Early Pregnancy for Females

Probability of early pregnancy: Females (with 95% CI)A dot plot comparing probability of early pregnancy across various features like household income, parent education, ELA score, and math score, for example.−0.1−0.0500.050.10.15Household income (top quartile)−0.020.0030.025Parent education (top quartile)−0.028−0.0110.005ELA score (top quartile)−0.0140.0090.033Math score (top quartile)−0.029−0.0090.01Depression (CES-D)0.0270.0540.08Substance use: alcohol−0.027−0.0020.023Substance use: cigarettes−0.0140.0060.025Substance use: drugs0.0290.0910.153Delinquency Index−0.02−0.0090.002Social Support Index−0.0040.0020.009Hispanic−0.0280.0240.076Black0.0030.0370.072Native American−0.052−0.0240.004Asian/Pacific Islander−0.0150.0260.067Other race−0.08−0.0280.025Born in the United States−0.041−0.0010.039

95% confidence intervals in brackets

  • Household Income (Upper Quartile) = 0.00262 [-0.0195 to 0.0247]
  • Parent Education (Upper Quartile) = -0.0114 [-0.0280 to 0.00521]
  • ELA Score (Upper Quartile) = 0.00915 [-0.0144 to 0.0327]
  • Math Score (Upper Quartile) = -0.00921 [-0.0287 to 0.0103]
  • Depression (CES-D) = 0.0538 (p<0.001) [0.0274 to 0.0802]
  • Substance Use: Alcohol = -0.00216 [-0.0270 to 0.0227]
  • Substance Use: Cigarettes = 0.00576 [-0.0135 to 0.0251]
  • Substance Use: Drugs = 0.0908 (p<0.01) [0.0286 to 0.153]
  • Delinquency Index = -0.00895 [-0.0197 to 0.00177]
  • Social Support Index = 0.00241 [-0.00443 to 0.00924]
  • Hispanic = 0.0238 [-0.0282 to 0.0758]
  • Black = 0.0371 (p<0.05) [0.00276 to 0.0715]
  • Native American = -0.0238 [-0.0518 to 0.00415]
  • Asian/Pacific Islander = 0.0262 [-0.0150 to 0.0674]
  • Other race = -0.0277 [-0.0801 to 0.0247]
  • Born in the United States = -0.000757 [-0.0409 to 0.0394]
  • Constant = 0.00562 [-0.0416 to 0.0528]
  • Observations = 1603

SOURCE: Features data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) (Harris and Udry, 2022), a representative sample of adolescents who were in grades 7 to 12 during the 1994–1995 school year and have been followed through 2018.

NOTE: This figure plots the coefficients from a linear regression of early pregnancy on the set of covariates conducted separately for females. “White” is the excluded racial category. The upper and lower bounds show the 95-percent CIs for each covariate. We use individual (person) weights to create statistics that are representative of the U.S. population.

Acknowledgments

We are grateful for the contributions and support of our colleagues Andrew Hoehn, Heather Schwartz, and Jennifer Kondo. We thank Ben Master and Christine Mulhern for their careful reviews. We are grateful to Monette Velasco, Libby Sweeney, Stephanie Lonsinger, and Mirka Vuollo for their assistance with editing and the publication process.

Notes

  1. Employment is measured as working for pay for at least ten hours per week. Therefore, anyone who is working less than ten hours per week or not working for pay (and otherwise not in school) is counted as disconnected by this measure.We examine the period of disconnection during Wave 3; at this point, respondents were 18 to 28 years old, with a median age of 22. Waves 1 and 2 were collected using a sample of adolescents who were in school at the time of the survey, thus disconnection during these waves is, by design, close to 0 percent. Respondents in Wave 4 were aged 25 through 33, and thus outside the age range of disconnected youth, although we can eventually use this sample to examine longer run outcomes of disconnection.For our analysis, we use the Add Health public-use sample, which is one-third of the size of the full restricted-use sample. Future planned analysis will use the full sample. Return to content⤴
  2. This means that our sample differs from the overall population of disconnected youth and those who were already disconnected at the time of high school; examining out-of-school students might reveal different characteristics that correlate with disconnection. Return to content⤴
  3. Seventeen percent of females are disconnected whereas 14 percent of males are disconnected. Return to content⤴
  4. These results are broadly similar to those found in Wenger and Bonds (2025). The differences likely stem from the different periods (Wenger and Bonds use data from 2019–2023) and perhaps from the different sampling frames (Add Health forms a sample from connected youth in high school). Return to content⤴
  5. We note that these results are exploratory and not a comprehensive set of all possible covariates. Future planned work will use the Add Health restricted data, which have the full sample of respondents and a richer set of data, allowing us to calculate disconnection at a more granular level, examine geographic variation, and examine a more comprehensive set of covariates. Return to content⤴
  6. We also examine a binary indicator for physical disability. Physical disability is correlated with disconnection but the sample of those disabled is extremely small (less than 1 percent) and thus our estimate is very imprecise. In future analyses, we will re-estimate this using the restricted-use sample which has three times the number of observations. Return to content⤴
  7. The CES-D scale typically has 20 questions, with a score of 16 or above indicating clinical depression (Radloff, 1977). The version in the Add Health has 19 questions, and so we code 15 or above as clinical depression. Results are robust to an alternative coding of 16 and above. Return to content⤴
  8. We create a means effect index of all 15 questions in the delinquency module to create our delinquency index. Return to content⤴
  9. Illegal drug use includes significantly higher marijuana, cocaine, and “other” drug use; there was no significant difference in inhalant use. Marijuana use was about 30 percent higher in the disconnected sample (from 25 to 33 percent) and cocaine use was about 60 percent higher (from 3 to 5 percent). Both of these differences are statistically significant. “Other” drug use (other drugs not included in marijuana, cocaine, and inhalants) was 12 percent higher in the disconnected sample (from 8 to 9 percent) but not statistically significant. Return to content⤴
  10. We estimated both a linear probability model and a logistic regression. Results are similar across models and so we show results from the linear model here. Return to content⤴
  11. See Figure A.1. in the appendix for these results. Return to content⤴
  12. See Figures A.2. and A.3. in the appendix for these results. Return to content⤴

References

  • Augustine, Catherine H., John Engberg, Geoffrey E. Grimm, Emma Lee, Elaine Lin Wang, Karen Christianson, and Andrea A. Joseph, Can Restorative Practices Improve School Climate and Curb Suspensions: An Evaluation of the Impact of Restorative Practices in a Mid-Sized Urban School District, RAND Corporation, RR-2840-DOJ, 2018. As of September 30, 2025: https://www.rand.org/pubs/research_reports/RR2840.html
  • Bacher-Hicks, Andrew, Stephen B. Billings, and David J. Deming, “The School to Prison Pipeline: Long-Run Impacts of School Suspensions on Adult Crime,” American Economic Journal: Economic Policy, Vol. 16, No. 4, November 2024.
  • Balsa, Ana I., Laura M. Giuliano, and Michael T. French, “The Effects of Alcohol Use on Academic Achievement in High School,” Economics of Education Review, Vol. 30, No. 1, 2011.
  • Belfield, Clive R., Henry M. Levin, and Rachel Rosen, The Economic Value of Opportunity Youth, Corporation for National and Community Service, 2012.
  • Cohen, Sheldon, and Thomas A. Wills, “Stress, Social Support, and the Buffering Hypothesis,” Psychological Bulletin, Vol. 98, No. 2, 1985.
  • Crosnoe, Robert, and Glen H. Elder, Jr., “Family Dynamics, Supportive Relationships, and Educational Resilience During Adolescence,” Journal of Family Issues, Vol. 25, No. 5, 2004.
  • Currie, Janet, and Duncan Thomas, “Early Test Scores, School Quality and SES: Longrun Effects on Wage and Employment Outcomes,” in Solomon Polachek, ed., Worker Wellbeing in a Changing Labor Market, Emerald Group Publishing Limited, 2001.
  • Duncan, Greg J., and Richard J. Murnane, eds., Whither Opportunity? Rising Inequality, Schools, and Children’s Life Chances, Russell Sage Foundation, 2011.
  • Farrington, David P., “Childhood Origins of Antisocial Behavior,” Clinical Psychology & Psychotherapy, Vol. 12, No. 3, 2005.
  • Fergusson, David M., L. John Horwood, and Elizabeth M. Ridder, “Show Me the Child at Seven: The Consequences of Conduct Problems in Childhood for Psychosocial Functioning in Adulthood,” Journal of Child Psychology and Psychiatry, Vol. 46, No. 8, 2005.
  • Furstenberg, Frank F., Jr., and Mary Elizabeth Hughes, “Social Capital and Successful Development Among At-Risk Youth,” Journal of Marriage and the Family, Vol. 57, No. 3, 1995.
  • Gregory, Anne, Kathleen Clawson, Alycia Davis, and Jennifer Gerewitz, “The Promise of Restorative Practices to Transform Teacher-Student Relationships and Achieve Equity in School Discipline,” Journal of Educational and Psychological Consultation, Vol. 26, No. 4, 2016.
  • Hair, Elizabeth C., Kristin A. Moore, Thomson J. Ling, Cameron McPhee-Baker, and Brett V. Brown, “Youth Who Are ‘Disconnected’ and Those Who Then Reconnect: Assessing the Influence of Family, Programs, Peers and Communities,” Child Trends, Vol. 37, July 2009.
  • Hanushek, Eric A., and Ludger Woessmann, “The Role of Cognitive Skills in Economic Development,” Journal of Economic Literature, Vol. 46, No. 3, 2008.
  • Harris, Kathleen Mullan, and J. Richard Udry, “National Longitudinal Study of Adolescent to Adult Health (Add Health), 1994–2018 [Public Use],” dataset, version 25, Carolina Population Center, University of North Carolina–Chapel Hill, Inter-university Consortium for Political and Social Research, August 9, 2022. As of October 7, 2025: https://doi.org/10.3886/ICPSR21600.v25
  • Haveman, Robert, and Barbara Wolfe, “The Determinants of Children’s Attainments: A Review of Methods and Findings,” Journal of Economic Literature, Vol. 33, No. 4, 1995.
  • Heckman, James J., Jora Stixrud, and Sergio Urzua, “The Effects of Cognitive and Noncognitive Abilities on Labor Market Outcomes and Social Behavior,” Journal of Labor Economics, Vol. 24, No. 3, 2006.
  • Lewis, Kristen, A Decade Undone: 2021 Update, Measure of America, July 29, 2021.
  • MaCurdy, Thomas, Bryan Keating, Sriniketh Suryasesha Nagavarapu, and David Glick, “Reprint of: Profiling the Plight of Disconnected Youth in America,” Journal of Econometrics, Vol. 243, No.1–2, July 2024.
  • Okonofua, Jason A., and Jennifer L. Eberhardt, “Two Strikes: Race and the Disciplining of Young Students,” Psychological Science, Vol. 26, No. 5, 2015.
  • Perry, Brea L., and Edward W. Morris, “Suspending Progress: Collateral Consequences of Exclusionary Punishment in Public Schools,” American Sociological Review, Vol. 79, No. 6, 2014.
  • Radloff, Lenore Sawyer, “The CES-D Scale: A Self-Report Depression Scale for Research in the General Population,” Applied Psychological Measurement, Vol. 1, No. 3, 1997.
  • Skiba, Russell J., Robert H. Horner, Choong-Geun Chung, M. Karega Rausch, Seth L. May, and Tary Tobin, “Race is Not Neutral: A National Investigation of African American and Latino Disproportionality in School Discipline,” School Psychology Review, Vol. 40, No. 1, 2011.
  • Wenger, Jennie W., and Stephanie Bonds, Understanding Disconnection Among American Youth, RAND Corporation, PE-A4207-1, October 2025. As of October 1, 2025: https://www.rand.org/pubs/perspectives/PEA4207-1.html

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More Support is Needed to Address Growing Student Need

12 November 2025 | Baltimore, MD –

The Partnership for Student Success (PSS) today announced the publication of a new report, Are K-12 Students Getting the Evidence-Based Supports They Need? Progress and Challenges Four Years After the Pandemic. The report, authored by Dr. Robert Balfanz and Vaughan Byrnes of the Everyone Graduates Center at the Johns Hopkins University School of Education, analyzes findings from a third annual nationally representative survey of K-12 public school principals, fielded by the RAND Corporation in partnership with PSS, to examine the deployment of evidence-based student supports and evolving student need.

The report concludes that four years after the height of the pandemic, there is widespread use of evidence-based and people-powered student supports–such as high-intensity tutoring, mentoring, student success coaching, postsecondary transition coaching, and wraparound supports–in public schools across the United States. But, public school principals indicate that continued growth in these interventions is needed to meet the scale of student needs.

Key findings from the report include:

  • High-intensity tutoring, mentoring, and wraparound supports are each provided in about half of the nation’s K-12 public schools, and in about two-thirds of high-poverty schools, with most schools offering these services providing them to 20% or fewer of their students.
  • Over the past three school years, an estimated 400,000 additional adults have stepped up to support K-12 students in public schools as tutors, mentors, postsecondary advisors, and wraparound support providers.
  • Four years after the height of the pandemic, public school principals report no let-up in student need with 30% to 40% reporting an increase in the number of students needing high-intensity tutoring, mentoring, or wraparound supports.

The report emphasizes that while implementation barriers exist to expanding evidence-based programs, there is a subset of schools that are proving that serving students at scale is possible, and outlines a range of resources and opportunities to support expansion of high-quality programs.

To learn more, read the full report on the Partnership for Student Success’ website or register for a webinar on the report’s key findings on Thursday, December 4th at 3:00pm ET.

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About the Partnership for Student Success: Based at the Everyone Graduates Center at the Johns Hopkins University School of Education, the Partnership for Student Success is a national coalition dedicated to expanding evidence-based and people-powered student supports for all K-12 students in the United States, with a particular focus on high-impact tutoring, mentoring, student success coaching, postsecondary transition coaching and wraparound/integrated student supports.

Contact: Kate Cochran kcochr17@jhu.edu

More Montgomery County students suspended so far this year

Montgomery County schools update student code of conduct amid equity  concerns

The BANNER Talia Richman10/29/2025 5:30 a.m. EDT

More suspensions went to students who are Hispanic, learning English or in special education

Montgomery County schools saw an increase in student suspensions at the start of this school year.

During the first five weeks of classes, the district recorded 296 out-of-school suspensions compared to 230 during the same period last school year.

The 29% increase was driven by more suspensions handed down to Hispanic students, children who are learning English and those who receive special education services.

The numbers — which will be discussed Thursday at the Montgomery County Public Schools board meeting — provide a glimpse into how the district’s new code of conduct is playing out. The data covers the first day of school through Sept. 30.

Read More

Montgomery County is losing students. Here’s why that matters.

Teacher pointing at paper on the floor with students.

Baltimore Banner Talia Richman10/14/2025 1:12 p.m.


Districts across the nation are confronting the consequences of lower birth rates and shifting demographic patterns

Montgomery County Public Schools enrollment dropped to a 10-year low.

Roughly 156,540 students attend county schools — a decrease of more than 2,600 kids since last year, according to preliminary data. While that’s less than a 2% drop, it’s part of a larger pattern of decline since the district’s peak enrollment in 2019.

MCPS predicts a more dramatic dive: a 9% dip from its 2019 peak to the enrollment forecast for 2031.

“This is an uncomfortable conversation for Montgomery County, because this has not been our experience for much of the past few decades,” MCPS Superintendent Thomas Taylor said.

The enrollment dive is part and parcel of big changes planned for Maryland’s largest district. The school system is in the midst of a boundary study for secondary campuses, and Taylor said he wants to expand that effort to elementary schools next.

Montgomery County is not alone in confronting enrollment declines. Districts across the country are confronting the consequences of lower birth rates and shifting demographic patterns.

“We’ve added a lot of housing, and we’ve added a lot of people, and we’ve grown very fast, but something else has changed,” Taylor said. “The percentage of households that have children has dramatically reduced.”

Fewer 5-year-olds

Montgomery County’s declines are driven by drops in kindergarten enrollment and international students.

The kindergarten data is straightforward to explain: Fewer children have been born in the county over the past several years.

The story of international student enrollment is more complex, with Taylor gesturing toward Washington but not going so far as to draw a line to the Trump administration’s aggressive approach to immigration.

“It may be causation, but it’s definitely correlation,” the superintendent said.

Maryland schools are funded based on enrollment, so fewer students in seats means less money flowing toward Montgomery County campuses.

In several cities across the country, school leaders have responded to enrollment drops by closing campuses — a painful choice that often devastates neighborhood families.

Taylor said it’s too soon to tell if those tough choices are in the county’s future.

“Not based on the projections that I have right now,” he said.

By 2031, the district anticipates enrollment dropping just below 150,000 students.

Talia Richman

talia.richman@thebanner.com

Talia Richman

Talia Richman is the Montgomery County education reporter at The Banner. She previously covered schools for The Dallas Morning News. The Education Writers Association has recognized Talia as among the best education beat reporters in the nation. Before her time in Texas, she covered schools and City Hall for The Baltimore Sun.

https://www.thebanner.com/education/k-12-schools/montgomery-county-schools-enrollment-drop-5VZSNAMBUNARNH4Y2VSRKYIWP