The Age of Diagnosis

How Our Obsession with Medical Labels Is Making Us Sicker

By Suzanne O'Sullivan

Category: Psychology | Reading Duration: 21 min | Rating: 4.1/5 (14 ratings)

About the Book

The Age of Diagnosis (2025) argues that modern medicine and culture have become increasingly fixated on labels, expanding categories of illness in ways that can overpathologize everyday experience. It examines how the search for a name – across conditions from neurodiversity to persistent, unexplained symptoms – shapes care, community, and identity, sometimes helping and sometimes harming. It ultimately calls for a more cautious, context-aware approach that balances the relief of diagnosis with the risks of stigma, overtreatment, and misplaced certainty.

Who Should Read This?

Skeptical clinicians confronting overdiagnosis and label creep
Data-minded policymakers shaping evidence-based health guidelines
Thoughtful people navigating modern diagnostic culture

What’s in it for me? Learn to read labels, weigh risks, and make calmer clinical decisions.

Modern medicine can name more conditions than ever. That power is changing how we think, feel, and behave when we’re unwell – or simply different. A label can open clinic doors, unlock services, and bring relief. It can also harden uncertainty into identity, draw healthy people into care pathways, and turn risk into treatment.

From brain-based explanations of everyday struggles to gene panels promising foresight, diagnosis now acts as a cultural force as much as a clinical tool. The issue isn’t whether science helps – it does – but how far naming should reach, what evidence counts, and who pays when tests outpace understanding. In this Blink, you’ll learn how diagnostic labels shape care and identity, why clinical context must anchor every test, and where prediction tips into overdiagnosis. Let’s start by looking at predictive genetics and how a single Huntington’s result can rewrite a life.

Chapter 1: Predictive results can reshape lives long before illness

Predictive genetic testing promises certainty, but with Huntington’s disease that promise carries heavy weight. Huntington’s disease, or HD, is an autosomal-dominant single-gene condition affecting one of the chromosome pairs in human DNA. It causes progressive psychiatric, cognitive, and motor decline; chorea, or involuntary jerky movement, is the hallmark movement feature. Symptoms typically appear between the ages of 30 and 50, and life is shortened by roughly 10 to 25 years after onset.

Ever since the causal variant was identified in 1993, symptom-free relatives can learn decades in advance whether disease lies ahead. That knowledge reshapes lives. Valentina learned her mother had HD while pregnant with her first child. Overnight, she and her three siblings each faced a 50 percent chance of developing an incurable disorder. She watched over her mother’s slow change – mood swings, disinhibition, and later the fidgety movements and loss of balance – until a nursing home became necessary. Anxiety took hold: panic attacks, antidepressants, and years of indecision about testing.

Valentina’s own reproductive choices brought further strain. IVF with pre-implantation genetic testing, quoted at about £30,000 at the time, could avoid passing on the variant, yet she chose natural conception to prevent dividing her children into the “chosen” and the uncertain. In this context, genetic counseling becomes the anchor. Counselors emphasize that a predictive result can’t be unlearned – and that everyday slips, like tripping on a curb or having a rough night’s sleep, may suddenly feel like early decline. This is the nocebo effect: when negative expectations and hyperfocus on risk create or intensify real symptoms. Because the brain’s predictive coding shapes what we notice and how we interpret it, being primed for HD makes even harmless sensations feel like signs of disease.

Without care and support, prediction itself can distort the present. The pattern holds across countries. Surveys often show interest in testing, but in practice most at-risk adults walk away after counseling, and actual uptake lingers in the single digits to teens. Testing can help with life planning and getting timely support once true symptoms begin, but the consequences extend far beyond medicine – into insurance, work responsibilities, and difficult family disclosures. A predictive result is a warning, not a treatment. Handled thoughtfully, though, it can leave space for hope and intentional choices.

Chapter 2: Broad labels without solid evidence create confusion

Some diagnoses begin with a lab result; others grow from stories, symptoms, and a search for meaning. Take Lyme disease. Years of unexplained illness in Lyme, Connecticut, prompted investigation in 1975 and, in 1982, the culprit bacterium was identified in deer ticks. From there, a clear early picture – bullseye rash, flu-like illness – blurred into a wide constellation of complaints across joints, nerves, and the heart.

Testing has never fully fixed the blur. Standard practice uses two-stage antibody testing, but these look for an immune response, not the organism. Results shift with timing, geography, and lab methods, and antibodies can signal past exposure without disease, as seen in forestry workers with high positivity yet few symptoms. Guidelines insist that results be weighed against the full clinical story, because pretest probability matters. Scale data underline the confusion. A Johns Hopkins cohort found no evidence of active or recent infection in about 85 percent of referrals labeled as Lyme.

In the US in 2022, 63,000 cases met reporting standards, while electronic records show roughly 476,000 treated, indicating large numbers managed on suspicion alone. Meanwhile, Australia reports many diagnosed cases despite the absence of the known vector and bacterium. Long Covid took a different route to a similar endpoint. The idea of ongoing or returning symptoms after an initial coronavirus infection surfaced online in May 2020 and spread faster than agreed criteria.

Many people identified themselves without a confirmed infection, and more than two hundred symptoms accumulated under the label. Later definitions added minimum time frames, yet a consistent thread in studies is the role of context: persistent symptoms after mild or self-diagnosed infection often sit alongside normal investigations, high stress, social isolation, and strong expectations of illness. That does not make the symptoms unreal; it explains why they can persist and fluctuate when the body’s danger signals stay amplified by attention and worry. The lesson is practical: tests support, context leads, and careful, patient-centered listening prevents broad labels from overtaking good judgment.

Chapter 3: Looser autism definitions boost diagnoses and strain resources

Autism diagnoses have soared in recent decades – not because of a hidden epidemic, but because of shifting definitions, evolving clinical practice, and powerful cultural incentives. Understanding that mix is essential if we want to support people well without losing sight of those who need the most help. There’s no blood test or scan for autism. Diagnosis depends on observed social communication difficulties, along with repetitive or restricted behaviors that start early in life and cause real impairment.

Over time, that picture has broadened. What was once a narrow profile of severe social withdrawal is now understood as a spectrum that includes milder traits. Recent diagnostic manuals have merged subtypes into a single category, recognized that early signs can be masked or missed, and added sensory traits as a core component. With those changes, prevalence in the US has risen from about 4 in 10,000 children to about 1 in 36. Adult diagnoses are going up too, and the gender gap is narrowing. In practice, assessment is supposed to involve long interviews, multiple informants, and review by a team.

But overloaded clinics and long waits mean standards vary. Many adults say they’ve learned to mask traits at school or work. If clinicians accept that, low scores on observation tools may be discounted, and the diagnosis leans more on self-report than measured behavior. Childhood histories are another weak spot: parents forget details, teachers’ reports are long gone, and records often don’t exist. So criteria about early onset may end up inferred instead of evidenced. Even “impairment” itself is subjective.

One clinician might see grades, jobs, or relationships as proof of competence; another might focus on the exhaustion, shutdowns, or behind-the-scenes support needed to keep someone afloat. The result? Wide variation in who qualifies. For many adults, getting a diagnosis is validating – finally putting a name to lifelong struggles. But labels also shape identity, expectations, and treatment. Few studies track long-term benefits, especially for adults, and harms are rarely measured.

Medical framing can sometimes absorb trauma, bullying, or eating disorders into an unchangeable brain story. So what’s the bottom line? Diagnosis should stay anchored in careful, context-rich assessment. Support works best when needs are grouped in meaningful ways, so help matches the real challenges people face. And while broadening the criteria has helped many, we also need to protect resources for those who require intensive, ongoing help – without letting one broad label become the catch-all answer to every social and psychological problem.

Chapter 4: High-risk genes point to chances, not fate

Cancer genetics promises answers, but what it really delivers is probabilities. Take BRCA1 and BRCA2: they’re repair genes that normally protect us. But certain variants can raise lifetime breast cancer risk from about 12 percent to as high as 85 percent, and ovarian cancer risk from about 2 percent to 60 percent. These numbers don’t guarantee disease, but they do raise the stakes – pushing healthy people to face life-changing decisions long before any symptom appears.

Roisin’s story shows how those choices play out in real life. After watching her mother battle multiple cancers and losing her grandmother, she tested positive for a high-risk BRCA1 variant at just 25. Within months, she chose to have a double mastectomy, and later surgery to remove her ovaries and fallopian tubes. That meant sudden menopause and lasting effects on her body image, sexuality, and relationships. The surgeries cut her cancer risk by about 95 percent, and she feels less haunted now. But she’s also candid about the fear and family pressure that drove her decisions, the patchy psychological support along the way, and the fact that uncertainty never disappears completely.

That uncertainty runs through every option. Removing ovaries improves survival in high-risk women because ovarian cancer is often found late. Prophylactic mastectomy lowers risk sharply, but the survival benefit is less clear, so many women weigh surgery against intensive screening – yearly MRIs in their twenties, mammograms later – and the false alarms and anxiety that come with it. Screening more broadly has its own pitfalls: thyroid, prostate, melanoma, and breast cancer diagnoses have risen sharply in recent years without matching drops in advanced disease or deaths. A large review found that, outside of colorectal cancer, most screening programs add little or nothing to people’s overall lifespan. Who gets tested – and how – also matters.

Expanding BRCA testing to people without a strong family history, or using direct-to-consumer kits, can blur the meaning of results. Many panels only test for a handful of variants, leading to false reassurance or unnecessary panic. Any positive needs clinical confirmation and careful interpretation. Polygenic risk scores, while headline-grabbing, often add more noise than clarity for individuals.

That’s why context is everything. Genetics should be paired with personal stories and supported by counseling that acknowledges the weight of irreversible choices. Surveillance and watchful waiting deserve a place alongside surgery. And everyday levers – smoking, drinking, diet, weight, sun exposure – still shift cancer risks more than most genes ever will.

Chapter 5: Rethinking ADHD depression and neurodiversity

An ADHD diagnosis can feel like a breakthrough – finally a way to explain years of distractibility, impulsivity, low mood, and exhaustion. It can unlock services and support. But it also leaves gaps. Medication may sharpen focus, and workplaces can cut noise or interruptions, yet performance still wobbles and people often struggle to explain what really helps.

Years of “masking”– hiding fidgeting, pushing down impulses, performing competence – take their toll. A label can reframe that strain, but it doesn’t restore energy overnight. The definition itself has stretched. ADHD once meant tightly defined childhood patterns; now broader adult criteria include milder traits with fuzzy thresholds. Assessment relies heavily on interviews and self-report, so context and expectations shape outcomes as much as rating scales. Co-occurring conditions are common, and regional differences in diagnosis highlight just how subjective the process can be.

Popular brain-based explanations often get ahead of the science. Group brain differences in ADHD are small and nondiagnostic. Twin studies suggest heritability, but big genetic studies show only modest effects. Dopamine theories are inconsistent too. It’s a familiar pattern: depression was long tied to a “serotonin deficit,” but evidence is weak and drug benefits for mild cases often mirror placebos. Meanwhile, prescribing stimulants has surged even though rigorous reviews haven’t found a clear advantage of methylphenidate over a placebo in adults.

Support and medication can ease symptoms, but many people with mild difficulties don’t see big improvements in long-term outcomes. School accommodations often feel useful without translating into better learning, and short-term behavioral gains in children don’t always mean better quality of life as adults. Meanwhile, social factors like adversity, neglect, bullying, and poverty do play a huge role – and those can be changed. Identity also shapes outcomes. For some, a diagnosis becomes central to their self-concept – an “illness identity” that can amplify symptoms and lower expectations. On the other hand, a “recovery identity” flips the script: traits and moods are influences, not destiny.

Progress is measured by real-world gains like steadier relationships, sustainable routines, and reclaimed energy rather than just symptom checklists. Recovery-oriented communities build hope, teach coping skills, and keep the focus on practical levers like sleep, structure, connection, and meaningful activity. The goal is to find a balance: save intensive, sustained support for the most severe cases. For milder presentations, start with context.

Tackle stressors that can change. Try treatments on a time-limited basis. And most importantly, keep identity rooted in strengths and growth, not just a label.

Chapter 6: Genomic testing outpaces interpretation

When a child’s development is clearly off-track but no cause can be found, doctors sometimes use a placeholder: syndrome without a name, or SWAN. It signals real difficulty but doesn’t explain much, and it shows how heavily access to care and education still depends on having a recognized label. Sequencing is fast today, but understanding lags behind. Whole-genome sequencing took off after 2005 with next-generation methods.

Now an entire genome can be analyzed in about a day for under $1,000. The UK’s large-scale program, launched in 2012, gave firm diagnoses to about 1 in 5 people with unexplained conditions. That’s progress – but ultra-rare answers often explain symptoms without offering treatment, prognosis, or even a peer community. This results in limited practical value. Then there are variants of uncertain significance, or VUS – changes in DNA we can’t yet call harmless or harmful. Everyone carries millions of variants.

Even in cancer genes like BRCA, there are more than 72,000 unique versions, and only about 4,900 are known to be high-risk. What matters is context. Labs don’t read every letter equally; they focus on genes that match the clinical picture. A precise description sharpens the search, while vague ones like “mild developmental delay” just add ambiguity. The safest move is to treat uninterpretable results as “not yet meaningful” and plan a re-check, rather than sticking families with a label that might later be downgraded. Genomics is also moving into population screening.

Newborn sequencing pilots in the UK, US, and Australia aim to test thousands of babies, looking for treatable childhood-onset conditions but holding back adult-onset findings and VUS. The trade-offs are clear. A cystic fibrosis policy exercise showed genome sequencing would prevent about 10 missed diagnoses per year but create about 80 borderline cases that needed years of monitoring. That raises tough questions about consent, lifelong data use, and how much overdiagnosis we’re willing to accept. Prenatal testing brings similar challenges. Noninvasive prenatal testing (NIPT) estimates risk, but it doesn’t confirm disease.

The key is positive predictive value, which depends on pretest risk. For Down syndrome, a “high chance” result can still be wrong about one in five times. At one US hospital, invasive follow-up tests dropped from 38 percent in 2010 to just 2 percent in 2015, which made misplaced certainty more common. The message is clear: genomic tools are powerful, but they only help when paired with precise clinical stories, realistic statistics, and humility about what a name can – and can’t – deliver. The main takeaway of this Blink to The Age of Diagnosis by Suzanne O’Sullivan is that naming is powerful: it should open doors, not box people in. Diagnosis and genomics work best when they’re grounded in context, clear probabilities, and caution against overdiagnosis, especially where prediction runs ahead of understanding.

Final summary

When clinicians and patients slow down, match action to evidence, and balance stories with stats, care improves, anxiety eases, and options stay open. Used this way, labels become tools for timely support and better lives – not limits.

Okay, that’s it for this Blink. We hope you enjoyed it. If you can, please take the time to leave us a rating – we always appreciate your feedback. See you soon.

About the Author

Suzanne O’Sullivan, MD FRCP, is a consultant neurologist and clinical neurophysiologist whose work at UCLH/The National Hospital for Neurology and Neurosurgery has made her a leading voice on functional and psychosomatic disorders. Widely recognized for clear, compassionate science communication, she won the 2016 Wellcome Book Prize and has written the best sellers It’s All in Your Head, Brainstorm, and The Sleeping Beauties.