The Age Of Diagnosis

The Age of Diagnosis: Understanding Modern Medical Expansion and Its Impact

Overview and Core Thesis

The Age of Diagnosis by Dr. Suzanne O’Sullivan examines the troubling phenomenon of overdiagnosis and overmedicalisation in modern medicine. The book argues that while Diagnosis provides substantial benefits for those with severe disease, Diagnostic expansion—driven by technology, financial incentives, and social pressure—is pathologizing normal human variation and converting healthy people into patients.

The central challenge to conventional wisdom is that “earlier Diagnosis is always better.” O’Sullivan demonstrates how Diagnostic labels themselves can be powerful interventions that create real physical symptoms through the nocebo effect and predictive coding, often causing more harm than benefit for mild cases.

The Problem of Diagnostic Expansion

Understanding Overdiagnosis and Overmedicalisation

Overdiagnosis refers to correct diagnoses that harm patients because treatment is neither needed nor beneficial—detecting medical problems before they cause clinical harm. Overmedicalisation turns ordinary human differences, behaviors, and life stages into medical problems requiring doctor intervention. Both arise through:

• Overdetection: Using new technologies to find earlier/milder disease
• Expanded disease definitions: Moving Diagnostic thresholds for what counts as abnormal (also called “diagnostic creep”)

The statistics reveal alarming trends:

• ADHD diagnoses increased 48%
• Depression rates rose 25% in a single year
• Autism prevalence exploded from 4 in 10,000 fifty years ago to 1 in 100 today
• Cancer diagnoses projected to exceed 2 million in the US in 2024
• Diabetes affects 537 million people globally

The Role of Technology and Financial Incentives

Diagnostic expansion creates perverse incentives. Specialists have financial stakes in identifying more patients; their reputations and incomes grow with patient volume. Hyperspecialization creates “silos” where specialists lack general medical training to generate alternative diagnoses and cannot assess harm holistically.

A 2018 study found that 73% of physicians acknowledged unnecessary testing as a serious problem, yet nearly 50% ordered at least one unnecessary test weekly—driven by:

• Fear of litigation (doctors are rarely sued for overdiagnosis)
• Patient insistence
• Financial incentives

Approximately 30% of US healthcare spending provides no benefit; the UK estimates 20% of clinical work has no effect on outcomes.

The Power of Diagnostic Labels

The Nocebo Effect and Predictive Coding

Diagnostic labels are not inert facts—they are powerful interventions that can create real physical symptoms through the nocebo effect (opposite of placebo). Through predictive coding, the brain uses past experience and expectations to predict bodily responses. When someone learns they have a disease or are at risk of one, this knowledge fundamentally alters how they perceive their body.

This expectation-driven process causes people to:

• Notice and worry about ordinary bodily changes they would normally filter out
• Interpret normal sensations as symptoms
• Behave in ways consistent with their Diagnosis

Valentina’s case exemplifies this mechanism. After learning she had a 50% chance of inheriting Huntington’s disease from her mother, she began experiencing clumsy movements, dizziness, and mood swings. The more attention she paid to these sensations, the worse they became. When genetic testing revealed she did not carry the Huntington’s gene, these symptoms either disappeared or became manageable—demonstrating they resulted from expectation and fear, not pathological process.

Labeling Effects Across Conditions

Research shows this labeling effect operates across multiple conditions:

• Children and placebo response: A 2018 sham MRI study demonstrated children’s powerful responsiveness to expectation—children told they received a placebo that would relax and focus them showed strong symptom reduction simply from being told to expect it
• Long COVID patterns: Multiple studies demonstrate that Anxiety, depression, perceived stress, loneliness, and negative life events predict long COVID symptoms better than positive viral tests
• Diagnostic self-fulfilling prophecies: Once diagnosed, people often begin experiencing the expected symptoms through heightened awareness and expectation

Case Studies in Diagnostic Expansion

Huntington’s Disease: the Burden of Predictive Diagnosis

Huntington’s disease testing exemplifies the profound dilemma of predictive genetic Diagnosis—knowing decades in advance that you will develop an incurable neurodegenerative condition. HD is caused by a single gene variant on chromosome 4 (autosomal dominant), meaning:

• 50% chance of inheritance
• Absolute certainty of developing the disease if the gene is present
• Mid-life emergence causing progressive dementia, movement disorders, and psychiatric problems
• No effective treatment

The testing paradox: Early surveys found 90% of at-risk people said they would take the test; however, when actually offered testing, only 5-18% globally accept it. This gap suggests many people find that hope sustains them better than certainty.

Psychological consequences of predictive Diagnosis include:

• Depression and suicidal ideation
• Loss of healthy years to worry
• Impacts on driving and employment
• Potential medical discrimination
• Interpreting ordinary bodily changes as disease signs

Stephanie’s experience illustrates the protective power of delayed Diagnosis. She lived without an HD Diagnosis for 30 years, allowing her to pursue career, family, and ambitions freely. When diagnosed at age 52, this “blissful ignorance” was revealed as protective—she accomplished more during those decades without knowing her genetic status than she might have with early knowledge.

Lyme Disease: Test Subjectivity and Diagnostic Controversy

Lyme disease’s discovery history reveals Diagnosis as fundamentally subjective despite appearing objective. Patient Polly Murray spent 21 years investigating her family’s mystery illnesses before a doctor took her seriously in 1975.

The disease and testing:

• Caused by bacterium Borrelia burgdorferi transmitted by tick bite
• Typically causes bullseye rash, flu-like symptoms, and potentially multi-system disease
• Testing involves two stages: ELISA (enzyme-linked immunosorbent assay) followed by Western blot
• Crucially, these are not Diagnostic tests—they are supportive evidence requiring interpretation within clinical context

The problem of test interpretation:

• A positive test does not mean Lyme disease; it indicates exposure or past infection
• False positives occur from cross-reactivity with other infections or autoimmune disorders
• False negatives happen if tests target wrong bacterial strains, are done too early, or are poorly calibrated
• In the New Forest (UK), 25% of forestry workers tested positive for Borrelia burgdorferi without any symptoms—showing exposure does not equal disease

The “Lyme wars”—fierce debate between doctors arguing underdiagnosis versus overdiagnosis—demonstrate how the same test can Support opposite conclusions depending on pretest probability: the likelihood the patient has disease based on symptoms and exposure history.

Consequences of Diagnostic expansion:

• The CDC found that 1,016 of 1,261 people referred with a Lyme disease Diagnosis had no evidence of active or recent infection (80% misdiagnosis rate)
• In 2022, while 63,000 cases met CDC standards, electronic health records showed 476,000 people treated for Lyme disease—over 400,000 without official Diagnosis confirmation
• Specific private labs in the US and Germany are responsible for huge proportions of positive results in patients who tested negative repeatedly at local labs

Chronic Lyme disease (CLD) represents the extreme of this expansion. The US National Institute of Allergies and Infectious Diseases defines CLD as “symptoms in people who have no clinical or Diagnostic evidence of a current or past infection”—essentially a misdiagnosis by definition.

Long Covid: Patient-Driven Diagnosis Without Definition

Long COVID was coined by Elisa Perego via Twitter hashtag on May 20, 2020, to describe persistent symptoms after mild COVID-19 infection. From inception, it lacked:

• A disease definition
• Specific symptoms
• Diagnostic test requirements

This made it a self-Diagnosis with no proof of infection needed. A negative COVID test didn’t count against it; 70% of one UK Support group had tested negative for the virus.

Inverted disease patterns: Most infectious illnesses cause more severe long-term effects in those most severely ill acutely, but long COVID was more common after mild infection than in hospitalized severe cases.

The psychosomatic explanation: A substantial proportion of long COVID—particularly in those with mild or self-diagnosed infection—is best explained as psychosomatic illness. Evidence includes:

• Multiple studies show Anxiety, depression, perceived stress, loneliness, and negative life events predict long COVID better than positive viral tests
• One Norwegian study found loneliness or negative life events in the year prior to COVID were better predictors than a positive test
• A French study found self-reported infection more likely to lead to long COVID than laboratory-confirmed infection

Psychosomatic illness characteristics observed in long COVID:

• Flitting symptoms defying anatomical explanation
• Different bodily systems affected in different combinations
• Non-hospitalized patients with wider and more severe symptoms than hospitalized patients
• Sufferers most short of breath often having the most normal lung function tests

Rather than a single illness, long COVID represents consequences of pandemic isolation with no institutional Support, combined with nocebo effects, excess attention to the body, predictive coding, and fear spread through social media.

Autism Diagnosis: Expansion Beyond Recognition

Autism has undergone dramatic Diagnostic expansion since Leo Kanner’s 1943 description of 11 severely impaired children with “extreme Autistic aloneness” and complete inability to relate to others.

Diagnostic prevalence explosion:

• 4 in 10,000 fifty years ago to 1 in 100 today
• In 2023, California reported 1 in 22 eight-year-olds Autistic; Northern Ireland 1 in 20; Texas 1 in 64; France 1 in 144
• Male-to-female ratio shifted from 4:1 (1980s) to 3:1 currently to approaching 2:1
• Adult diagnoses increased 150% between 2008-2016
• Between 1998-2018, autism diagnoses rose 787% in the UK

DSM-5 changes (2013) dramatically reorganized autism Diagnosis:

• Reduced essential symptoms needed for Diagnosis
• Combined social and communication problems into one symptom list
• Abolished PDD-NOS and Asperger’s as separate diagnoses
• Removed requirement for symptom appearance before age 3 (now just “early developmental period”)
• Allowed Diagnosis based on “masking” even if no Autistic traits are visible

Diagnostic inconsistency is severe:

• A 2022 US study reassessing community-diagnosed Autistic children by research standards found 47% didn’t actually meet research criteria
• A recent UK study found Diagnostic rates varying from 35-85% across Assessment centers
• Official Assessment ideally involves hours of semi-structured interviews (ADOS and ADI-R), observations across environments, teacher corroboration, and multidisciplinary consensus

Systemic pressures undermine proper Assessment:

• England has 1.2 million people waiting for autism Assessment
• Lengthy multidisciplinary assessments are difficult to maintain
• Some US autism centers train education professionals in ADOS, and Oregon allows school Diagnosis without medical evaluation
• Teachers lack psychological knowledge to rule out other medical disorders mimicking autism

The impairment problem: “Impairment”—essential for Diagnosis—is undefined at the mild end. One assessor explained it as “comes at a cost” (exhausted after supermarket, needing time to recalibrate), entirely subjective.

Consequences of expansion: Severe autism becomes invisible as discourse is dominated by mild, articulate, self-identified voices. Uta Frith, a pioneering autism researcher, warns that “the Diagnosis of autism has been stretched to breaking point” and that mixing severe non-verbal autism with late-identified mild cases makes meaningful research nearly impossible.

People like Elijah—a 20-year-old with severe autism requiring round-the-clock care, non-verbal except for five-word sentences, self-injurious—are sidelined by those advocating for de-medicalization of mild traits.

Adhd: Diagnostic Inflation and Biologizing

ADHD Diagnosis has exploded globally:

• From 7% global prevalence in children to 22% in Iran, 14% in Tunisia
• In the US, ADHD rose from 6% (1990s) to 10% (2016) in children
• UK teenagers doubled 2000–2018
• Most striking: adult ADHD diagnoses went from rare to 1 in 20 in some places, almost all mild
• The UK saw a 400% increase in adults seeking ADHD Diagnosis 2020–2023

Diagnostic inconsistency:

• Norway (with free healthcare) varies from <1% to >8% Diagnosis rates between regions
• US rates range 5% (California) to 14% (Mississippi)
• The word “often” in DSM-5 criteria is subjective
• Immaturity may be confused with neurodevelopment: youngest children in school cohorts are diagnosed more frequently than older classmates

Biological evidence limitations:

• Brain differences exist (slightly smaller volumes in some studies) but are not abnormalities—only group comparisons
• Radiologists cannot diagnose ADHD on brain scans; people with ADHD have normal scans
• Twin studies show 76–88% heritability, but genome-wide association studies show only 22%, suggesting non-genetic factors dominate

The neurodiversity framing: Coined in 1998 by sociologist Judy Singer, “Neurodiversity” is not a medical term but sounds like one, lending false authority. Singer explained: “Neuroscientists were the new priesthood, so I thought, let’s put them together. Neurodiversity sounds really important.”

Biologizing mental health: ADHD is now framed as a neurobiological disorder despite weak biomedical evidence. This obscures social and environmental factors:

• Childhood abuse, neglect, trauma, and witnessing violence increase ADHD risk
• The DSM-5 notes ADHD signs may be “completely absent when the individual is receiving frequent rewards, is under close supervision, in a novel setting, or engaged in interesting activities”

Medication concerns:

• Among DSM-5 ADHD working group advisers, 78% disclosed financial ties to drug companies
• Stimulant prescriptions increased sevenfold in the UK (last 10 years), tenfold for adults in New Zealand (2006–2022), and 250% in the US (2006–2016)
• A 2022 Cochrane review of 24 trials (5,066 people) found no good evidence methylphenidate (Ritalin) was superior to placebo in adults

Brca Variants and Risk-Reducing Surgery

The discovery of BRCA1 (1994) and BRCA2 (1995) genes revolutionized cancer risk Assessment. However, the predictive value differs critically from Huntington’s disease: a BRCA variant is a risk factor, not a certainty.

Risk levels:

• High-risk BRCA1 variants carry 60–85% lifetime breast cancer risk and 40–60% ovarian cancer risk
• BRCA2 variants confer 40–65% and 10–20% respectively
• Unlike Huntington’s disease (incurable), women with BRCA variants can choose preventative surgery or intensive surveillance

Risk-reducing surgery reduces respective cancer risks by 95%. However:

• 10–15% of women undergoing mastectomy and 40% undergoing oophorectomy would never have developed cancer if untreated—making them overdiagnosed by definition
• These women received unnecessary surgery with permanent consequences

Roisin’s story illustrates the psychological impact. Diagnosed at 25 with an 87% breast cancer and 60% ovarian cancer risk, she had a double mastectomy at 26, then oophorectomy at 30. She describes aftermath as traumatic—grief over losing the ability to breastfeed, body image struggles, sexual dysfunction, surgical menopause at 30 causing mood disorders, cardiovascular risk, osteoporosis. She acknowledges doing it “out of fear” and is “still not really sure if it was my decision.”

Risk prediction problems:

• Models accurate for high-risk familial populations may not apply to those without cancer family histories
• The UK Biobank shows many healthy people in their 60s–70s carry high-risk BRCA variants yet never developed cancer
• NHS England now offers free BRCA testing to anyone over 18 with one or more Jewish grandparents—even without family history
• Geographic variation is striking: USA/UK have ~50%/40% risk-reducing surgery uptake; France, Germany, Poland average 5–11%

Direct-to-consumer genetic testing dangers:

• Over 26 million people have used commercial genetic tests costing £129–148
• Bypasses counseling requirements and uses non-clinical-grade sequencing with up to 96% false positive rates
• Judith, a journalist, bought an ancestry test and clicked “accept” without reading terms, receiving a positive BRCA1 result via email—no counseling, no clinical-grade confirmation

Cancer Screening: Saving Lives While Creating Overdiagnosis

Cancer screening saves lives but also creates substantial overdiagnosis.

Statistics and impact:

• NHS England estimates screening saves 10,000 lives yearly, but among those lives are people treated for early cancers that would never have progressed
• A 2023 US study estimated 31% of breast cancers diagnosed in women over 70 were overdiagnosed
• A French study found €100+ million spent on overdiagnosed thyroid cancer in four years
• For prostate cancer screening, while some lives are saved, as many as 20 men per 1,000 screened are diagnosed with and treated for cancer that would never have caused problems

Screening effectiveness questions:

• A 2023 meta-analysis of 2 million screened people found that for large bowel cancer, screening extended lifespan by only 110 days
• For other cancers, there was no evidence screening allowed people to live longer (all-cause mortality)
• Thyroid ultrasound screening increased diagnoses fourfold with zero reduction in late-stage cancer or deaths
• A Cochrane review estimated: for every 2,000 women screened, one life is saved but ten receive unnecessary treatment

The core problem: Scientists cannot distinguish slow-growing, indolent cancers from aggressive ones. Detroit autopsies found early prostate cancer in 45% of men in their 50s and 70% in their 60s, yet only 13% develop clinically significant disease.

The Severity-Based Harm-Benefit Analysis

The Critical Importance of Disease Severity

For severe disease, Diagnosis provides undeniable benefits: a child with severe autism supported by a one-to-one tutor has “all to gain and little to lose” through labeling because the severity speaks for itself. Severe depression, severe ADHD, and severe autism all benefit from pathways to treatment, expert Support, and Accommodations.

However, the harm-to-benefit calculation reverses for mild cases. The same label carries identical treatment risks but dramatically less potential benefit, making the harm-to-benefit ratio unfavorable. A person with subtle, masked autism faces high vulnerability to labeling effects yet gains “substantially less from medication, school Accommodations and other types of Support.”

The author uses cancer treatment as an analogy: chemotherapy’s horrific side effects are justified for someone dying of cancer but not for someone with a few cells that may never grow. Similarly, a person with subtle autism faces high vulnerability to labeling effects yet gains substantially less from treatment.

Pathologizing Normal Human Variation

Society has developed unrealistic expectations of health, success, and aging, leading to pathologization of ordinary human experience:

• Sadness, even when understandable (grief, disappointment), has become medicalized as depression
• Failure to achieve desired goals is increasingly explained through medical Diagnosis rather than accepted as normal limitation
• Menopause is spoken of as “a looming catastrophe” despite being natural
• Sleep less than seven hours is feared despite being normal aging
• Ordinary forgetfulness and emotional fluctuation are now ADHD
• Shyness and social difficulty are autism

The author argues these are cultural problems, not medical ones: “An expectation of constant good health, graceful ageing and an obedient body and mind has left people unprepared for those ordinary bodily declines that affect us all.”

Practical Strategies for Navigating Diagnosis

1. Severity-Based Diagnostic Decision-making

When considering whether a Diagnosis is appropriate, assess whether the individual’s symptoms/traits cause genuine impairment across multiple life domains (functioning, relationships, work, education). Mild traits affecting only specific contexts may not warrant Diagnosis.

Ask: “What is the specific harm this causes to this specific person?” If harm is mild and inconsistent, Diagnosis may cause more harm through labeling than benefit through intervention.

How to apply:

• Before accepting a Diagnosis, seek a second opinion from a generalist physician (not a specialist) who knows you as a whole person
• Verify that symptoms actually impair multiple areas of life, not just appear unusual
• Understand what treatments/Accommodations the Diagnosis unlocks—and whether they’re worth the identity shift and potential limitations

2. Clinical Context Interpretation of Medical Tests

Remember that tests alone cannot diagnose. All tests have false positive and false negative rates dependent on disease prevalence in the tested population, calibration, timing, and confounding variables.

Ask your doctor:

1. What is my pretest probability (how likely am I to have this disease based on my symptoms and risk factors)?
2. What are the false positive and false negative rates for this specific test?
3. What confounding variables might affect this result?
4. If this result were negative, would it change your clinical impression?
5. What is the next step if this result is positive?

3. Assessing Harm-to-Benefit Ratios

Before accepting a Diagnosis or beginning treatment, explicitly weigh potential benefits against potential harms.

Ask:

1. What specific evidence shows this treatment/Diagnosis improves my life?
2. What are the documented harms?
3. For my specific severity level, is there evidence showing benefit outweighs harm?
4. What alternatives exist?

4. Recognizing Nocebo Effects and Protecting Against Diagnosis-Induced Harm

Understand that Diagnostic labels can create symptoms through expectation and predictive coding. Once someone learns they have a disease, their expectations change, often causing them to notice ordinary bodily changes they would normally filter out.

Protective strategies:

• If recently diagnosed, limit exposure to symptom lists and Support groups focused entirely on illness before establishing your own baseline experience
• Notice whether you develop new symptoms after learning about them
• Consider whether your symptoms existed before Diagnosis or emerged after
• Seek balance between medical Support and activities/identities unrelated to your Diagnosis

5. Seeking Generalist Medical Perspective

Specialists have financial stakes in expanding their disease definitions and identifying more patients within their specialty. Generalists (primary care physicians), by contrast, have no stake in increasing diagnoses and are better positioned to notice when too much Diagnosis has made a patient worse.

How to apply:

• If you’ve accumulated multiple diagnoses from different specialists, ask your primary care physician to review your entire medical file holistically
• Ask: Do these diagnoses explain my overall condition, or is there a simpler unifying explanation?
• Are any treatments contradicting each other?
• Have I become over-medicalized?

Key Insights and Counterintuitive Perspectives

The Protective Power of Diagnostic Ignorance

Common belief: Earlier Diagnosis is always better and prevents harm. The book reveals: For conditions with no effective treatment or those decades away from symptom onset, the knowledge of disease can create more harm than benefit through decades of Anxiety and life limitation.

Tests Are Subjective, Not Objective

Common belief: Medical tests provide objective truth about disease presence. The book reveals: All tests have false positive and false negative rates depending on calibration, timing, population, and interpretation. The same test result means different things in different contexts—making Diagnosis fundamentally subjective despite appearing technical.

Severe Autism Becomes Invisible When Mild Cases Expand

Common belief: More Diagnosis of autism is good because it identifies previously missed cases. The book reveals: As Diagnostic criteria broaden to include milder presentations, discourse shifts toward mild cases, resources concentrate on high-functioning individuals, and severe autism becomes invisible.

Psychosomatic Illness Is Not Imaginary or Malingering

Common belief: Psychosomatic means “not real” or “all in your head.” The book reveals: Psychosomatic illness is entirely real—the brain genuinely creates symptoms through expectation, fear, and predictive coding. The distinction matters: recognizing an illness as psychosomatic allows different treatment approaches.

Risk Factors Are Not Diseases, Yet Society Treats Them As Such

Common belief: Having a BRCA variant means you will get cancer. The book reveals: BRCA variants confer risk, not certainty. Unlike Huntington’s disease (certain if gene present), many BRCA carriers never develop cancer. Yet risk-reducing surgery decisions are made as though risk equals certainty.

Medication Efficacy Is Often Overstated

Common belief: ADHD medication significantly improves functioning in adults. The book reveals: A 2022 Cochrane review found methylphenidate no better than placebo in adults. Depression’s “serotonin theory” was disproven by a 2023 Nature meta-analysis.

Critical Warnings and Considerations

Mental Health Warnings

This book challenges psychiatric Diagnosis and medication efficacy, particularly for mild-to-moderate presentations. For people with severe mental illness, psychiatric Diagnosis and medication can be life-saving. However, for those with mild depression, Anxiety, or ADHD, non-medical interventions may be equally or more effective.

Do not discontinue psychiatric medication based on this book’s arguments without consulting your prescriber; abrupt cessation can cause harm.

When to Seek Professional Help

This book is not an argument against medical care—it’s an argument against unnecessary and potentially harmful medicalization. Seek professional help if:

• Your symptoms genuinely impair multiple areas of your life
• You’ve suffered significant trauma or abuse
• You’re experiencing suicidal thoughts
• Medical investigation has revealed an actual disease
• You’re isolated and struggling without Support

Resources and Further Reading

Organizations and Resources

• Additude Magazine for ADHD resources
• Autism Self Advocacy Network for Autistic-led resources
• [ADDA](https://ADD.org) (Attention Deficit Disorder Association) for adult ADHD Support
• AANE (Autism & Asperger’s Network) for autism resources
• Understood for learning differences

Key References and Research

• DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition)
• CDC (Centers for Disease Control) epidemiological data
• UK Biobank large-scale genetic study
• Nature journal 2023 meta-analysis on depression and serotonin
• Cochrane Review 2022 meta-analysis of ADHD medication trials
• NHS (National Health Service, UK) screening data and Diagnostic practices

Important Figures and Researchers

• Uta Frith - pioneering autism researcher
• Judy Singer - Australian sociologist who coined “neurodiversity”
• Leo Kanner - psychiatrist who first described autism in 1943
• Lorna Wing - researcher who expanded autism concept to spectrum
• Allen Frances - psychiatrist who chaired DSM-4 task force

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