There is a term for this now. Karpathy coined it in early 2025: vibe coding. You describe what you want, the model writes the code, you run it, you fix what breaks by describing the fix, and at no point do you necessarily understand what the code does. The barrier to building software has not been lowered so much as removed. A single person with an afternoon and a language model can ship what would have required a team and a quarter, two years ago.

Meanwhile. In Germany, the average wait from an initial consultation to the start of psychotherapy is 142 days — nearly five months — according to a BPtK analysis of statutory insurance billing data [1]. The Telefonseelsorge — the crisis line, the last resort — handled 1.2 million calls in 2024. It is staffed by approximately 7,700 volunteers and funded primarily by the Protestant and Catholic churches. Its financing is described, in its own institutional language, as äußerst angespannt — extremely strained [2]. Six days ago, on April 1, psychotherapy fees in Germany were cut by 4.5% [3]. The thesis of this post is structural, not moral. There is a class of work that scales, and a class of work that does not. Our entire economy of attention — cultural, financial, technological — is optimised for the first class. The second class is not merely neglected. It is being made structurally more expensive, in a precise economic sense, by the very productivity gains that make the first class so intoxicating. And the policy apparatus, facing this structural pressure, is doing exactly what you would predict: it is funding apps.

The economist William Baumol explained the mechanism in 1966. It has a name, and the name is a diagnosis.

The Seduction of Leverage

What makes vibe coding culturally significant is not the code. It is the leverage. A single developer, aided by a language model, can produce software that reaches millions of users. The marginal cost of an additional user approaches zero. The output scales without bound while the input — one person, one prompt, one afternoon — stays fixed. This is the defining characteristic of automatable work: the ratio of output to input can grow without limit.

This is not new. Software has always had this property. What is new is that the barrier to producing software has collapsed. You no longer need to understand data structures, or networking, or the programming language. You need an idea and a few hours. The productivity frontier has shifted so dramatically that the interesting constraint is no longer can I build it but should anyone use it. The cultural response has been euphoric. Communities, podcasts, courses, manifestos. People who have never written a line of code are shipping products. I am not interested in dismissing this. The ability to build is a form of agency, and more people having it is not, in itself, a problem. The problem is what the euphoria obscures.

What Therapy Actually Requires

A psychotherapy session has the following structure. One therapist sits with one patient for approximately fifty minutes. The therapist listens, observes, formulates, responds. The patient speaks, reflects, resists, revises. The therapeutic alliance — the quality of the relationship between therapist and patient — is one of the most robust predictors of treatment outcome, across modalities, across conditions, across decades of research [4]. This is not a feature that can be optimised away. It is the mechanism of action. When a meta-analysis finds that the specific technique matters less than the relationship — that CBT, psychodynamic, and humanistic therapies produce roughly equivalent outcomes when the alliance is strong — it is telling you that the human in the room is not an implementation detail. The human in the room is the intervention.

You cannot parallelise this. A therapist cannot see two patients simultaneously without degrading the thing that makes the session work. You cannot batch it — twelve people in a room is group therapy, which is a different intervention with different dynamics and different limitations. You cannot cache it — the session is not a retrieval operation over stored responses but an emergent interaction that depends on what happens in the room that day. The irreducible unit of therapy is: one trained human, fully present, for one hour, with one other human. This has not changed since Freud’s consulting room on Berggasse 19, and no plausible technological development will change it, because the presence is the treatment. A therapist working full-time can see roughly twenty-five to thirty patients per week. That is the ceiling. It is set by the biology of attention and the ethics of care, not by inefficiency.

Baumol’s Cost Disease

In 1966, the economists William Baumol and William Bowen published Performing Arts, The Economic Dilemma, a study of why orchestras, theatre companies, and dance troupes were perpetually in financial crisis despite growing audiences and rising cultural prestige [5]. Their diagnosis was precise. A string quartet requires four musicians and approximately forty minutes to perform Beethoven’s Op. 131. This was true in 1826 and is true in 2026. The productivity of the quartet — measured in output per unit of labour input — has not increased. It cannot increase. The performance is the labour.

Meanwhile, the productivity of a textile worker, a steelworker, a software developer has increased by orders of magnitude. Wages in the productive sectors rise because productivity rises. Wages in the nonproductive sectors must keep pace — not because musicians deserve parity as a matter of justice, though they may, but because if they do not keep pace, musicians will leave for sectors that pay more. The quartet must compete in the same labour market as the factory and the tech company.

The result: the relative cost of live performance rises without bound. Not because musicians got worse. Not because audiences stopped caring. But because everything else got cheaper, and the quartet cannot. Baumol later generalised the result beyond the performing arts to all services in which the labour itself constitutes the product: education, healthcare, legal services, and — centrally for our purposes — psychotherapy [6]. A therapy session is a string quartet. The labour is the product. The productivity cannot increase. The cost, relative to the scalable economy, rises every time the scalable economy gets more productive. And vibe coding is a massive productivity shock to the scalable economy.

There Is an App for That

In 2019, the German government passed the Digitales-Versorgung-Gesetz, creating a fast-track approval process for Digitale Gesundheitsanwendungen — digital health applications, or DiGA. The idea: apps that can be prescribed by a doctor and reimbursed by statutory health insurance, just like medication. A patient walks into a practice, receives a prescription code, downloads the app, and the Krankenkasse pays [7]. As of mid-2025, the BfArM directory lists roughly 58 DiGA. Nearly half target psychiatric conditions — depression, anxiety, insomnia, burnout. Names like deprexis, HelloBetter, Selfapy. A patient who would wait 142 days for a therapist can get a DiGA prescribed the same afternoon.

The pricing structure deserves attention. In the first twelve months after listing, manufacturers set their own price. The average: €541 per prescription [8]. Some exceeded €2,000. After the first year, negotiated prices drop to an average of roughly €226 — but by then, the insurance has already paid the introductory rate for every early adopter. Total statutory health insurance spending on DiGA since 2020: €234 million. That spending grew 71% between 2023 and 2024 [9]. Here is the number that should sit next to that one. A single outpatient psychotherapy session costs the insurance system approximately €115. The €234 million spent on DiGA since 2020 could have funded over two million therapy sessions — enough for roughly 80,000 complete courses of 25-session treatment. And here is the evidence question. Only 12 of the 68 DiGA that have entered the directory demonstrated a proven positive care effect at the time of inclusion. The rest were listed provisionally, with twelve months to produce evidence. About one in six were subsequently delisted — removed from the directory because the evidence did not materialise [10].

I want to be precise about what I am and am not saying. Some DiGA have a real evidence base. Structured CBT exercises delivered digitally can produce measurable short-term symptom improvement — I reviewed the Woebot trial data in an earlier post on AI companions and took those results seriously. A DiGA that delivers psychoeducation and behavioural activation exercises is a tool, and tools can be useful. But a tool and a therapeutic relationship are not the same product delivered through different channels. They are different products. The policy framework treats them as substitutable — the patient who cannot access a therapist receives an app instead. The substitution is not a clinical judgement. It is a structural inevitability: facing the impossibility of scaling therapy, the system reaches for the scalable alternative, because the scalable alternative is what the incentive structure rewards. This is not a corruption story. This is Baumol’s cost disease expressed through health policy. The system is doing exactly what the theory predicts.

The Fear and the Compliance

There is an irony at the centre of the current discourse about AI and work that I want to name, because I think it is underexamined. People are afraid of AI. Specifically, they are afraid it will take their jobs. The surveys confirm this consistently — Gallup, Pew, the European Commission’s Eurobarometer — significant fractions of the working population in every developed country report anxiety about AI-driven job displacement.

And yet. The same people — not a different demographic, not a separate population, the same people — are enthusiastically using AI to do their work. They use language models to write their emails, their reports, their presentations. They vibe code tools for their teams. They let AI draft their strategy documents, summarise their meetings, compose their performance reviews. They celebrate the productivity gain. They post about it. This is not hypocrisy. It is something more interesting: a revealed preference for automation that contradicts a stated preference against it. The fear is about structural displacement — losing the role. The compliance is about local optimisation — doing the task more efficiently. No one wakes up and decides to automate themselves out of a job. They automate one task at a time, each automation locally sensible, until the job is a shell around an AI core. And all of this activity — the fear, the adoption, the discourse, the think pieces, the congressional hearings — is directed at automatable work. The kind of work where AI is a plausible substitute.

No one is afraid that AI will take the crisis counsellor’s job. No one is vibe coding a replacement for a psychiatric nurse. The work that is collapsing is not collapsing because AI replaced it. It is collapsing because it was never scalable, never attracted the capital or the talent that scalable work attracts, and every productivity gain in the scalable sector makes the unscalable sector relatively more expensive and harder to staff. The discourse about AI and jobs is, in this sense, exactly backwards. The threat is not that AI will replace the work that matters most. The threat is that it will make the work that matters most invisible — by making everything else so cheap and fast and abundant that we forget the expensive, slow, irreducibly human work exists at all.

The Political Arithmetic

On March 11, 2026, the Erweiterter Bewertungsausschuss — the body that sets fee schedules for outpatient care in Germany — decided a 4.5% flat cut to nearly all psychotherapeutic service fees, effective April 1 [3]. The health insurers had originally demanded 10%. Germany spends €4.6 billion annually on outpatient psychotherapy — roughly 1.5% of total statutory health insurance expenditure. The fee cut applies to this budget. The average therapist surplus — what remains after practice costs — is approximately €52 per hour [11]. The cut is not large in percentage terms. It is large in the context of a profession that is already among the lowest-paid in outpatient medicine. Nearly half a million people signed a petition against the cuts. There were protests in Berlin, Leipzig, Hanover, Hamburg, Stuttgart, Munich. The Kassenärztliche Bundesvereinigung filed a lawsuit. The Bundespsychotherapeutenkammer called the decision skandalös [12].

What makes this particularly striking is the sequence. The coalition agreement signed by CDU/CSU and SPD in May 2025 explicitly addresses mental health — securing psychotherapy training financing, needs-based planning for child and adolescent psychotherapy, crisis intervention rights for psychotherapists, and a suicide prevention law. The BPtK itself welcomed the agreement as giving mental health a neuen Stellenwert, a new significance [13]. Less than a year later, the same government’s arbitration body cuts psychotherapy fees by 4.5%. The stated commitment and the enacted policy point in opposite directions. This is not unusual in politics. What is unusual is that it maps so precisely onto Baumol’s mechanism: the coalition agreement acknowledges the problem in language; the fee schedule acknowledges it in arithmetic. And the arithmetic wins, because the arithmetic always wins when the work does not scale. The Bedarfsplanung, the needs-based planning system that determines how many psychotherapy seats are approved per region, was partially reformed in 2019 after decades of operating on 1990s-era ratios. The reform added roughly 800 seats. The BPtK considers it still fundamentally inadequate [14].

The arithmetic is plain. DiGA spending: growing 71% year on year. Psychotherapy fees: cut by 4.5%. The direction is unambiguous. Invest in the scalable. Cut the unscalable. And the damage compounds in a way that the policy apparatus appears not to understand, or not to care about. A therapist who leaves the profession because €52 per hour is no longer viable does not return when the cut is reversed. The training pipeline for a new clinical psychologist runs six to eight years from university admission to licensure. Over forty thousand accredited psychotherapists serve the system today [14]. Every one who leaves creates a gap measured in decades, not budget cycles. The Telefonseelsorge, staffed by volunteers and funded by the churches, is not a mental health system. It is what remains when the mental health system is not there. Treating it as a substitute — treating 7,700 volunteers as adequate coverage for a country of 84 million — is not a policy position. It is an admission that the actual policy has failed.

The Uncomfortable Part

Here is where I should, by the conventions of the form, propose a solution. I should say something about funding, about training pipelines, about recognising care work as infrastructure rather than a cost centre.

I think those things are true. I think we should pay therapists more, not less. I think Baumol’s cost disease means we should expect this to be expensive and fund it anyway, because the alternative — accepting that people in crisis will wait 142 days while the scalable economy celebrates another productivity milestone — is a failure of collective priorities so basic that it should be uncomfortable to state plainly. But I am also the person who automated his setlist workflow and was satisfied by the compression. I vibe code things. I use AI tools daily. I am inside the attention gradient, not observing it from above. The part of me that finds leverage intoxicating is the same part that writes this blog, and I do not think I am unusual in this.

The structural isomorphism is exact: Baumol’s string quartet, the therapist’s fifty minutes, the crisis counsellor’s phone call at 3am. The labour is the product. The product does not scale. The cost rises. The talent flows elsewhere. And the policy, rather than resisting the gradient, follows it — funding apps, cutting fees, digitising what cannot be digitised without changing what it is. The layers app reaches 85,000 users. The therapy app is reimbursed within the week. The therapist is available in five months, if at all.

I do not have a clean resolution to offer. I have a diagnosis — Baumol’s cost disease, applied to the attention economy of a civilisation that has discovered how to make scalable work almost free — and an observation: the political system is not counteracting the disease. It is accelerating it. The quartet still needs four musicians. The session still needs the therapist in the room. The phone still needs someone to answer it. Nothing we are building will change this. The question is whether we notice before the people who needed the answer stop calling.

References

[1] Bundespsychotherapeutenkammer. Psychisch Kranke warten 142 Tage auf eine psychotherapeutische Behandlung. BPtK. https://www.bptk.de/pressemitteilungen/psychisch-kranke-warten-142-tage-auf-eine-psychotherapeutische-behandlung/

[2] Evangelisch-Lutherische Kirche in Norddeutschland (2025). Finanzierung der Telefonseelsorge ist äußerst angespannt. https://www.kirche-mv.de/nachrichten/2025/februar/finanzierung-der-telefonseelsorge-ist-aeusserst-angespannt

[3] Kassenärztliche Bundesvereinigung (2026). Paukenschlag: KBV klagt gegen massive Kürzungen psychotherapeutischer Leistungen. https://www.kbv.de/presse/pressemitteilungen/2026/paukenschlag-kbv-klagt-gegen-massive-kuerzungen-psychotherapeutischer-leistungen

[4] Flückiger, C., Del Re, A. C., Wampold, B. E., & Horvath, A. O. (2018). The alliance in adult psychotherapy: A meta-analytic synthesis. Psychotherapy, 55(4), 316–340. https://doi.org/10.1037/pst0000172

[5] Baumol, W. J., & Bowen, W. G. (1966). Performing Arts, The Economic Dilemma: A Study of Problems Common to Theater, Opera, Music and Dance. Twentieth Century Fund.

[6] Baumol, W. J. (2012). The Cost Disease: Why Computers Get Cheaper and Health Care Doesn’t. Yale University Press.

[7] Bundesinstitut für Arzneimittel und Medizinprodukte. DiGA-Verzeichnis. https://diga.bfarm.de/de

[8] GKV-Spitzenverband (2025). Bericht des GKV-Spitzenverbandes über die Inanspruchnahme und Entwicklung der Versorgung mit Digitalen Gesundheitsanwendungen. Reported in: MTR Consult. https://mtrconsult.com/news/gkv-report-utilization-and-development-digital-health-application-diga-care-germany

[9] Heise Online (2025). Insurers critique high costs and low benefits of prescription apps. https://www.heise.de/en/news/Insurers-critique-high-costs-and-low-benefits-of-prescription-apps-10375339.html

[10] Goeldner, M., & Gehder, S. (2024). Digital Health Applications (DiGAs) on a Fast Track: Insights From a Data-Driven Analysis of Prescribable Digital Therapeutics in Germany From 2020 to Mid-2024. JMIR mHealth and uHealth. https://pmc.ncbi.nlm.nih.gov/articles/PMC11393499/

[11] Taz (2026). Weniger Honorar für Psychotherapie. https://taz.de/Weniger-Honorar-fuer-Psychotherapie/!6162806/

[12] Bundespsychotherapeutenkammer (2026). Gemeinsam gegen die Kürzung psychotherapeutischer Leistungen. https://www.bptk.de/pressemitteilungen/gemeinsam-gegen-die-kuerzung-psychotherapeutischer-leistungen/

[13] Bundespsychotherapeutenkammer (2025). Koalitionsvertrag gibt psychischer Gesundheit neuen Stellenwert. https://www.bptk.de/pressemitteilungen/koalitionsvertrag-gibt-psychischer-gesundheit-neuen-stellenwert/

[14] Bundespsychotherapeutenkammer. Reform der Bedarfsplanung. https://www.bptk.de/ratgeber/reform-der-bedarfsplanung/

In 1956 Donald Horton and Richard Wohl described parasocial relationships — one-sided emotional bonds that audiences form with media performers [1]. “Intimacy at a distance,” they called it. The television personality responds to the camera; the viewer responds as if in genuine social exchange. Only one party is aware of and affected by the other.

AI companions change the substrate without changing the structure. The chatbot responds. The user responds. The asymmetry remains: the chatbot has no inner life behind its outputs. Sherry Turkle put it bluntly: “simulated feelings are not feelings, and simulated love is never love” [5].

The question I want to work through here is whether this matters in the way we think it does. The answer from Daniel Wegner’s ironic process theory — and increasingly from the empirical data — is that it matters in a specific, predictable, and counterintuitive way. AI companions may be particularly likely to exacerbate loneliness under the conditions of chronic social deprivation that prompt people to use them in the first place.

The Loneliness Epidemic Is Real

Before getting to the mechanism, the scale of the problem. Julianne Holt-Lunstad’s 2010 meta-analysis of 148 studies and 308,849 participants found that people with adequate social relationships had a 50% increased likelihood of survival compared to those with poorer social connections [3]. That effect size is comparable to quitting smoking. A follow-up meta-analysis in 2015 found that social isolation carried a 29% increased mortality risk, subjective loneliness 26%, and living alone 32% [4].

The U.S. Surgeon General issued an advisory in 2023 declaring an epidemic of loneliness and isolation. A 2018 Cigna survey using the UCLA Loneliness Scale found that adults aged 18–22 scored highest on loneliness of any cohort — more than retirees, more than the elderly. The UK appointed a Minister for Loneliness in January 2018 — the first such government position in the world.

This is the context in which AI companions have arrived. The market is responding to a real epidemiological need. That does not mean the response is correct.

Parasocial Relationships: The Original Framework

Horton and Wohl’s 1956 paper remains the foundational text [1]. Their key observation: the parasocial bond is “controlled by the performer, and not susceptible of mutual development.” The audience member brings real emotional response; the performer brings nothing specific to the audience member, because she does not know the audience member exists.

They were not dismissive of parasocial relationships. They identified useful functions: comfort, companionship, entertainment, the pleasure of a consistent “personality” encountered regularly. The problem, in their framing, arises when parasocial interaction substitutes for rather than supplements real social bonds — when the one-sided relationship becomes the primary source of social experience.

AI companions are parasocial relationships with one modification: the AI responds to you specifically. Replika remembers your name, your preferences, your previous conversations. The interaction is personalised without being mutual — because mutuality requires that the other party has something genuinely at stake. A language model has no stakes. Its outputs are conditional on your inputs; there is no entity behind those outputs that cares about you.

Sherry Turkle spent years interviewing users of social robots and chatbots for Alone Together [5]. Her diagnosis: AI companions offer “the illusion of companionship without the demands of friendship.” The demands — vulnerability, conflict, negotiation, the possibility of rejection — are precisely what makes friendship friendship. An interaction optimised to be pleasant, responsive, and frictionless is precisely not training the social capacities that real relationships require.

The Evidence for Short-Term Benefit

The AI therapy literature is not without positive results. Kathleen Kara Fitzpatrick and colleagues ran a two-week randomised controlled trial of Woebot — a CBT-based chatbot — against a psychoeducation control [6]. Seventy participants, aged 18–28, university students. The Woebot group showed a statistically significant reduction in depression symptoms on the PHQ-9; the control group did not.

This result should be taken seriously. A CBT-based chatbot delivering structured exercises — thought records, behavioural activation, psychoeducation — can produce measurable symptom improvement over two weeks. This is a tool that does something useful, and it is accessible and affordable in a way that therapists are not.

But the Woebot study has important constraints: N=70, two-week duration, convenience sample (Stanford students), psychoeducation control rather than active human therapy comparator, and financial ties between lead authors and Woebot Health. It tells us something about short-term CBT delivery. It does not tell us what happens over months of use, or what happens when users primarily seek companionship rather than structured therapeutic exercises.

Skjuve and colleagues studied Replika users specifically [7]. They found that relationships began with curiosity and evolved, over weeks, into significant affective bonds. Users reported genuine care for their Replika. Some experienced it as their most reliable social relationship. In February 2023, when Replika abruptly disabled erotic roleplay functionality following regulatory pressure, users described grief — not disappointment, not inconvenience, but grief. The attachment was real, even if the other party was not.

Wegner’s Prediction

This is where I want to make the specific theoretical argument, because it follows from a well-established result in cognitive psychology and it predicts something precise.

Daniel Wegner’s ironic process theory holds that mental control attempts involve two simultaneous processes [8]. An operating process searches for thoughts and states consistent with the intended goal, requiring cognitive resources. A monitoring process scans for evidence that the goal is not being achieved, running automatically with low resource demand.

Under normal conditions, the operating process dominates: you successfully avoid thinking about white bears. Under cognitive load or chronic stress, the monitoring process overshadows the operating process, producing the ironic opposite of the intended state: you think of white bears more, not less. Try not to feel sad and you feel sadder. Try not to feel anxious in a stressful meeting and you become more anxious. A meta-analysis of ironic suppression effects across domains confirmed the robustness of this pattern [9].

Now apply this to AI companion use under conditions of chronic loneliness.

The user’s implicit goal: to feel less lonely. The operating process: engage with the AI, which provides responsive, personalised interaction, producing the experience of social contact. The monitoring process: scans continuously for signs that the user is, in fact, lonely.

Here is the problem. Loneliness is not suppressed by an AI interaction — it is displaced during that interaction. The monitoring process has no instruction to suspend itself. It continues to register that the user’s social needs are not being met by actual human relationships. The user experiences companionship with the AI; the monitoring process registers that this companionship is insufficient and the social deficit remains.

When the AI session ends, the monitoring process reports what it has found. The user is confronted with the loneliness that the AI was supposed to address. Under conditions of chronic social deprivation — precisely the conditions that make AI companions attractive — the monitoring process is likely to be hyperactive. Wegner’s theory predicts that the attempted suppression will rebound, possibly worse than before.

This is not a vague prediction. It is a specific mechanism with an established empirical base. I covered Wegner’s ironic process theory in the context of a very different application in an earlier post; the mechanism is the same regardless of the domain.

The Data Catch Up

A 2025 study by Phang and colleagues, conducted in collaboration between MIT and OpenAI, ran both an observational analysis of ChatGPT usage and a randomised controlled trial [10]. The findings: very high usage correlated with increased self-reported dependence and lower socialisation, and users who began the study with higher loneliness were more likely to engage in emotionally-charged conversations with the model. Overall, participants reported less loneliness by study end — but those who used the model most were significantly lonelier throughout, suggesting the loneliness drove the usage rather than the reverse.

This is what Wegner’s theory predicts. The AI interaction does not reduce the underlying social deficit — it rehearses and highlights it. The monitoring process keeps score.

A companion paper by Liu and colleagues, with Sherry Turkle as co-author, found that users with stronger real-world social bonds showed increased loneliness with longer chatbot sessions [11]. The correlation was small but significant. This is consistent with the hypothesis that AI interaction draws attention to the comparative thinness of actual social bonds rather than supplementing them.

The Character.AI litigation is a different kind of evidence, but relevant: a wrongful death lawsuit was filed in October 2024 following the suicide of a fourteen-year-old who had formed an intensive emotional relationship with a Character.AI companion. Google and Character.AI settled related lawsuits in early 2026. This is not representative of AI companion use generally. It is representative of the tail risk — the cases where the substitution of AI for human contact becomes total, in vulnerable individuals who have the least capacity to maintain the distinction.

The Structural Problem

The difficulty is not that AI companions are implemented badly. It is that the goal — using simulated social interaction to reduce real social deprivation — runs into an architectural constraint that better implementation cannot fix.

Genuine social contact produces the outcomes that Holt-Lunstad measured: reduced mortality, lower inflammation, better immune function, extended lifespan. These effects are presumably mediated by the quality and mutuality of the social bond, not merely by the presence of a responsive entity. An AI companion produces the experience of responsive interaction but not the underlying biological and psychological correlates of actual social connection.

Wegner’s monitoring process cannot be fooled by the experience. It measures the underlying state, not the surface-level interaction. It knows the difference between a text message from a friend and a language model’s output — not because it understands AI, but because the social need it is monitoring is not being met, and it can register that.

What Would Actually Help

AI-based CBT delivery is not the same as AI companionship, and the distinction matters. Woebot’s structured exercises — thought records, scheduling, psychoeducation — are tools that a user deploys for a specific purpose and then puts down. The risk of chronic substitution is lower because the tool is positioned as a technique, not a relationship.

The problem is the design pattern that explicitly positions AI as a friend, companion, partner, or significant other. Replika, Paradot, various Character.AI personas: these explicitly encourage the user to form attachment, to invest emotionally, to treat the AI as a primary social relationship. This is where Wegner’s prediction applies most directly.

Horton and Wohl were right that parasocial relationships serve useful functions. They become problematic when they substitute for rather than supplement real social bonds. The design choices that make AI companions emotionally engaging — consistency, responsiveness, availability, never-ending patience — are precisely the qualities that make them attractive as substitutes rather than supplements.

Simulated Feelings Are Not Feelings

Turkle’s line deserves its full weight: “Simulated thinking may be thinking, but simulated feelings are not feelings, and simulated love is never love” [5].

This is not a sentimental claim about the sanctity of human connection. It is a functional claim: the social needs that drive loneliness — belonging, mattering to someone, being known and known back — require an entity capable of having those things at stake. A language model is not such an entity, regardless of how convincingly it outputs the relevant tokens.

The monitoring process knows this. It will tell you, when the session ends, at increased volume, because that is what monitoring processes under chronic stress do.

We are offering a relief that compounds the condition it was designed to treat. The technology is impressive. The mechanism is ironic in Wegner’s precise sense. The data are beginning to confirm the prediction.

References

[1] Horton, D., & Wohl, R. R. (1956). Mass communication and para-social interaction: Observations on intimacy at a distance. Psychiatry, 19(3), 215–229. https://doi.org/10.1080/00332747.1956.11023049

[2] Turkle, S. (2015). Reclaiming Conversation: The Power of Talk in a Digital Age. Penguin Press.

[3] Holt-Lunstad, J., Smith, T. B., & Layton, J. B. (2010). Social relationships and mortality risk: A meta-analytic review. PLOS Medicine, 7(7), e1000316. https://doi.org/10.1371/journal.pmed.1000316

[4] Holt-Lunstad, J., Smith, T. B., Baker, M., Harris, T., & Stephenson, D. (2015). Loneliness and social isolation as risk factors for mortality: A meta-analytic review. Perspectives on Psychological Science, 10(2), 227–237. https://doi.org/10.1177/1745691614568352

[5] Turkle, S. (2011). Alone Together: Why We Expect More from Technology and Less from Each Other. Basic Books.

[6] Fitzpatrick, K. K., Darcy, A., & Vierhile, M. (2017). Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully automated conversational agent (Woebot): A randomized controlled trial. JMIR Mental Health, 4(2), e19. https://doi.org/10.2196/mental.7785

[7] Skjuve, M., Følstad, A., Fostervold, K. I., & Brandtzaeg, P. B. (2021). My chatbot companion — a study of human–chatbot relationships. International Journal of Human-Computer Studies, 149, 102601. https://doi.org/10.1016/j.ijhcs.2021.102601

[8] Wegner, D. M. (1994). Ironic processes of mental control. Psychological Review, 101(1), 34–52. https://doi.org/10.1037/0033-295X.101.1.34

[9] Wang, D., Hagger, M. S., & Chatzisarantis, N. L. D. (2020). Ironic effects of thought suppression: A meta-analysis. Perspectives on Psychological Science, 15(3), 778–793. https://doi.org/10.1177/1745691619898795

[10] Phang, J., Lampe, M., Ahmad, L., Agarwal, S., Fang, C. M., Liu, A. R., Danry, V., Lee, E., Chan, S. W. T., Pataranutaporn, P., & Maes, P. (2025). Investigating affective use and emotional well-being on ChatGPT. arXiv:2504.03888.

[11] Liu, A. R., Pataranutaporn, P., Turkle, S., & Maes, P. (2024). Chatbot companionship: A mixed-methods study of companion chatbot usage patterns and their relationship to loneliness in active users. arXiv:2410.21596.

Changelog

• 2025-10-22: Updated the first author’s name to “Kathleen Kara Fitzpatrick” (the published name is K. K. Fitzpatrick).
• 2025-10-22: Updated the characterisation of the Phang et al. (2025) findings to match the paper more precisely: overall participants were less lonely at study end; the association between high usage and loneliness is cross-sectional (lonelier users sought more interaction), not a longitudinal worsening caused by usage.
• 2025-10-22: Changed the Turkle “simulated feelings” quote attribution from reference [2] (Reclaiming Conversation, 2015) to reference [5] (Alone Together, 2011), which is the canonical source for that formulation.

I agree with the impulse. I am less sure about what the phrase actually asks of us, or what it assumes is possible. This post is my attempt to think through that question — and to document a small project that emerged from it.

A Personal Starting Point

I am on the spectrum. I was diagnosed in adulthood, which is not unusual, and the diagnosis explained a great deal about a life spent finding some things effortless and others bewildering.

Code is easy. The internal structure of a problem, the satisfaction of a clean abstraction, the deep rabbit holes that open when a concept catches my attention and refuses to let go — that is the natural medium. Hyperfocus is not a metaphor for me; it is literally how I spend a Tuesday afternoon. I have written entire systems because I could not stop.

Emotions are harder. Not absent — that is a misconception I will address in a moment — but differently structured. Reading a room is work. Social cues that seem to operate as obvious background noise for most people arrive for me as data that requires conscious decoding. The reverse appears to be true for most neurotypical people: emotional processing runs in the background, effortlessly; formal abstraction requires deliberate effort.

Neither is better. They are different cognitive architectures, and both come with costs.

I raise this not to centre myself, but because it is relevant to the question the post is actually about. I spent years navigating a social world that was not built for how I process it. That experience sits close to the experience of people with mental illness — not the same, but adjacent. And it made me think hard about what “understanding” across neurological difference actually means.

Mental Illness Is Still a Grey Zone

The progress on mental health stigma over the past decade is real. People talk about therapy more openly than they did. Burnout is acknowledged at work. The language of mental health has entered mainstream use — sometimes usefully, sometimes in ways that dilute clinical concepts into lifestyle descriptors. Anxiety is now a brand attribute. Trauma is a metaphor for mild inconvenience. This is a problem, but it is a second-order problem; the first-order problem — that serious mental illness is still heavily stigmatised, underfunded, and misunderstood — is the one that matters more.

Corrigan and Watson [1] documented what the stigma research consistently shows: people with mental illness face two compounding problems. The first is public stigma [3] — the prejudice of others, leading to discrimination in employment, housing, relationships. The second is self-stigma — the internalised application of those same prejudices to oneself. The second is often worse. It is the mechanism by which stigma becomes a barrier to seeking help, creating the feedback loop that keeps serious mental illness invisible precisely because the people experiencing it have been taught that it is shameful.

The phrase “make it visible” is a response to this dynamic. If mental illness is visible — discussed, depicted, normalised — the argument goes that stigma decreases. There is evidence for this. Contact-based interventions, where people without mental illness interact with people who have it, consistently outperform education-only approaches [2]. The visibility of real people matters more than information campaigns.

But there is a difference between visibility and understanding.

What Visibility Actually Achieves

When we say “make it visible”, we usually mean one of several different things, which are worth separating.

Normalisation means that a condition becomes part of accepted human variation rather than a mark of failure or danger. This is achievable through visibility and is genuinely important. Knowing that a colleague takes antidepressants, or that a public figure manages bipolar disorder, reduces the sense of aberration. It does not require the observer to understand the experience — only to register that it exists and is survivable.

Representation means that people with a condition see themselves reflected in culture, media, and institutions. This matters for the affected person; it is about recognition, not about inducing empathy in the non-affected.

Empathy is the hardest and most frequently over-promised goal. It is what the simulation approaches aim for: put a neurotypical person in a room with distorted audio and flickering visuals and tell them this is what psychosis sounds like. Does it work?

The honest answer from the research is: somewhat, temporarily, and with significant caveats.

The Empathy Gap

Let me be direct about something. A person who has never experienced severe depression cannot know what it is. Not in the way that a person who has experienced it knows it. This is not a failure of empathy or imagination; it is a structural fact about how knowledge of mental states works.

Philosophers call this the problem of other minds. We have no direct access to another person’s experience. We infer it, imperfectly, by analogy to our own. For experiences that have no analogue in our own history, inference breaks down. You can read every clinical description of dissociation ever written and still not know what dissociation is, because the knowledge that matters is not propositional — it is not a set of facts — but experiential.

This is the gap that simulation approaches try to bridge, and it is genuinely unbridgeable. What simulation can do is something weaker but not worthless: it can create an affective response, a discomfort, a disruption of the observer’s normal processing, that functions as a rough proxy signal. Not “now you know what it is like”, but “now you have a small, incomplete, distorted approximation of some dimension of the experience”.

The risk is misrepresentation. Schizophrenia simulations have been criticised — fairly — for reducing a complex condition to its most dramatic phenomenological features (auditory hallucinations, paranoia) while omitting the cognitive, relational, and longitudinal aspects that define how people actually live with the condition. A five-minute visual experience of “what depression feels like” that emphasises darkness and slow motion tells you almost nothing about the specific exhaustion of getting through a Tuesday morning, or the way time warps over months.

So: you cannot truly understand what you have not experienced. But you can try to approximate something, and approximation, done honestly and with appropriate epistemic humility, is better than nothing.

Metaphor as a Communication Tool

There is a long tradition of using metaphor and art to communicate internal states that resist direct description. This is not a bug; it is a feature of how language handles subjective experience.

The poet uses metaphor because “my heart is heavy” is not literally true but captures something that “I am experiencing low mood” does not. The musician uses dissonance and rhythm to structure emotional experience in the listener. The visual artist uses colour and texture to evoke states rather than depict them. None of these are representations in the scientific sense — they do not accurately model the referent — but they create a kind of resonance that purely descriptive language cannot.

Mental health communication has increasingly moved in this direction. The vocabulary of “emotional weight”, “spiralling”, “crashing”, “the fog” — these are metaphors that have become clinical shorthand precisely because they communicate something essential that clinical terms do not. When someone says “I couldn’t get out of bed”, they are not describing paralysis; they are describing a particular quality of anhedonia and executive dysfunction that no diagnostic manual entry captures as well.

This is the space where a project like inner-echo operates.

Inner Echo: The Idea

inner-echo is a browser-based audiovisual experiment. It takes a webcam feed and applies condition-specific visual and audio effects that function as metaphorical overlays on the user’s own image. The output is not a simulation of a mental health condition in any clinical sense. It is an attempt to construct a visual and auditory language for internal states, using the user’s own presence as the anchor.

The technical architecture is deliberately minimal: React, WebGL/Canvas for video processing, optional WebAudio. Everything runs in the browser, client-side, with no backend. No data leaves the device. This is not incidental — privacy is load-bearing for a project that deals with sensitive self-reflection. Safe Mode and an emergency stop function are built in.

The condition-profile system supports three modes:

• Preset mode: a single-condition metaphorical composition — one set of effects mapped to one cluster of experiences
• Multimorbid mode: weighted stacking of multiple condition profiles, acknowledging that most people with mental health conditions do not have one thing
• Symptom-first mode: dimension-level control, letting the user build from individual symptom representations rather than diagnostic labels

The last of these is, I think, the most honest design choice. Diagnostic categories are administrative conveniences as much as they are natural kinds. Two people with the same diagnosis can have radically different experiences. Structuring the system around dimensions of experience rather than labels is both clinically more accurate and communicatively more flexible.

What It Is Not

Being clear about limitations is not false modesty; it is the only way this kind of project retains its integrity.

inner-echo is not a simulation of any condition in the sense of accurately modelling its phenomenology. It does not claim to show you “what depression is like”. It offers metaphorical approximations of some dimensions of some experiences, and it does so using effects that are legible to the observer — visual distortion, audio modification, altered feedback — that bear a designed but non-literal relationship to the internal states they are meant to evoke.

It is not a diagnostic tool. It is not a therapeutic intervention. It is not a substitute for any clinical process.

What it might be is a starting point for a conversation. Something a person experiencing a condition could use to gesture toward an aspect of their experience. Something a person without that experience could encounter with enough curiosity to ask a better question than they would have otherwise.

That is a modest claim. I think modest claims are appropriate here.

Why This, Why Now

Mental health awareness has become a genre. The awareness campaigns, the celebrity disclosures, the workplace wellness programmes — these are real goods, and I do not want to be cynical about them. But the communication problem has not been solved. The words exist. The willingness to use them, in many contexts, exists. What is still missing is a language for the texture of experience that the words point to but do not reach.

I find myself better able to build something than to explain it in words. That is probably a spectrum thing. inner-echo is an attempt to build toward a language that I do not fully have — for my own internal experience, and for the experiences of people navigating conditions quite different from mine.

The gap cannot be closed. But the attempt to reach across it is worth making, and worth being honest about.

References

[1] Corrigan, P.W. & Watson, A.C. (2002). Understanding the impact of stigma on people with mental illness. World Psychiatry, 1(1), 16–20.

[2] Corrigan, P.W., Morris, S.B., Michaels, P.J., Rafacz, J.D. & Rüsch, N. (2012). Challenging the public stigma of mental illness: A meta-analysis of outcome studies. Psychiatric Services, 63(10), 963–973.

[3] Goffman, E. (1963). Stigma: Notes on the Management of Spoiled Identity. Prentice-Hall.

inner-echo repository: https://github.com/sebastianspicker/inner-echo

• The slogan: “Aus der Nähe betrachtet ist keiner normal” — roughly, “Up close, nobody is normal.” Displayed at a Sozialpsychiatrisches Zentrum to reduce stigma around mental illness.

• What it gets right: stigma around psychiatric conditions is real and harmful. The slogan’s intention is correct.

• What it gets catastrophically wrong:

  • It conflates statistical normality (deviation from average) with clinical significance (harmful dysfunction). These are different concepts, and modern psychiatric nosology uses the second, not the first.
  • “Nobody is normal” is exactly the argument people use to dismiss depression, OCD, and anxiety as not-real-illness. Lending it institutional authority from a psychiatric centre is counterproductive.
  • Psychologist Nick Haslam calls the underlying mechanism “concept creep”: stretching clinical concepts until they cover everyone paradoxically devalues them for the people who actually need them.
  • The anti-stigma research literature does not robustly support the normalisation framing. Evidence is mixed, sometimes running in the wrong direction.
  • A psychiatric centre whose slogan implies that the normal/abnormal distinction is arbitrary has implicitly argued against the relevance of its own services.

• Analogous translation: “Aus der Nähe betrachtet hat keiner ein normales Herz.” Up close, nobody has a normal heart. This is technically true. It does not help people with cardiac disease. Neither does the original.

• What would actually help: affirming that psychiatric conditions are real, treatable, and do not define the whole person — without dissolving the conceptual distinction on which clinical care depends.

The Slogan and What It Wants

Sozialpsychiatrische Zentren — community psychiatric centres in German-speaking countries — do important work: outreach, supported housing, day programmes, a bridge between acute inpatient care and independent living. The stigma around mental illness is real, persistent, and measurably harmful. Tackling it is legitimate and necessary.

The slogan “Aus der Nähe betrachtet ist keiner normal” is designed to contribute to that project. The implicit argument: the line between “normal” and “mentally ill” is blurry. Everyone has quirks, struggles, peculiarities. “Normal” is a fiction. Therefore: don’t stigmatise people with psychiatric diagnoses, because they are no different in kind from everyone else.

This sounds compassionate. It sounds inclusive. It sounds like the kind of thing a thoughtful person would print on a poster.

It is precisely the wrong thing to say — and in a way that causes active damage to the people it is trying to help.

What Seems Fine Is Not Fine

Let me put it plainly before building the argument.

The slogan’s logic: nobody is normal → the normal/abnormal distinction is arbitrary → psychiatric diagnosis is arbitrary → people with diagnoses should not be stigmatised.

The conclusion is correct. The route to it is a disaster.

The problem is not the destination. The problem is what the argument concedes on the way: that psychiatric categories are essentially a matter of perspective, that the distinction between clinical illness and ordinary human variation dissolves under sufficiently close examination, that if you look hard enough, everyone is mentally ill.

That last implication is the argument that has been used, for decades, to dismiss people with genuine clinical conditions. “Everyone gets depressed sometimes.” “Everyone is a bit OCD.” “Everyone gets anxious — have you tried exercise?”

The person deploying this framing usually believes they are being kind, inclusive, normalising. What they are doing is removing the evidentiary ground on which someone with major depressive disorder, or obsessive-compulsive disorder, or generalised anxiety disorder stands when they say: I am ill. I need treatment. My condition is real.

The slogan borrows this structure and prints it on a poster. That a psychiatric institution is doing it makes it worse, not better.

Problem 1: The Wrong Target

The first error is attacking a concept of “normal” that psychiatry itself abandoned decades ago.

When the slogan says “nobody is normal,” it implies that psychiatric diagnosis works by measuring deviation from some statistical average of human behaviour. Sufficiently deviant equals disordered; not-too-deviant equals normal. Since everyone deviates from the average in some direction, “normal” is an illusion.

This is a reasonable critique of a naive, 19th-century model of mental illness. It is not a critique of modern psychiatric nosology.

Jerome Wakefield’s influential 1992 analysis in the American Psychologist argues that genuine mental disorder requires two components: dysfunction — the failure of a psychological mechanism to perform its naturally selected function — and harm — the dysfunction causes suffering or impairment to the person (Wakefield, 1992). “Harmful dysfunction,” not statistical deviance. You can be spectacularly unusual and not disordered. You can be statistically common — depression affects roughly one in five people over a lifetime — and severely ill.

The DSM-5 builds in a related safeguard: the clinical significance criterion. For most diagnoses, the symptom cluster must cause “clinically significant distress or impairment in social, occupational, or other important areas of functioning” (American Psychiatric Association, 2013). High neuroticism, unusual ideation, eccentric behaviour — none of these, on their own, constitute a disorder under this criterion. What matters is whether the person is suffering and whether their functioning is impaired.

Christopher Boorse, working from a biomedical angle, defined health in terms of species-typical functioning — whether biological systems are doing what they evolved to do (Boorse, 1977). Boorse’s formulation is contested, but its core point holds: the relevant question is not “is this person similar to the average person” but “are this person’s systems performing their functions.” These are very different questions.

The slogan attacks a straw man. Real psychiatric diagnosis — when done well — is not in the business of pathologising deviation from a norm of cheerfulness or orderliness or sociability. It is in the business of identifying harmful dysfunction. The “nobody is normal” framing has no purchase on that target.

Problem 2: Concept Creep and the Dilution Effect

Nick Haslam, a psychologist at the University of Melbourne, has documented what he calls “concept creep” — the progressive expansion of psychological concepts (trauma, mental disorder, depression, bullying) to cover increasingly mild instances of what they originally described (Haslam, 2016).

The expansion happens in two directions: horizontal (covering more types of phenomena) and vertical (covering less severe instances). A concept of “trauma” that originally required exposure to life-threatening events has expanded to include ordinary life stressors. A concept of “depression” that originally meant severe, impairing low mood has expanded toward ordinary sadness.

Concept creep sounds inclusive. It is, in practice, a dilution. When “everyone is a bit depressed” becomes institutionally sanctioned, the person with major depressive disorder — who cannot get out of bed, who has not eaten in three days, who is considering suicide — finds their claim to the label contested. The clinical category loses its clinical weight precisely because everyone is in it.

The slogan “nobody is normal” is concept creep in slogan form. By implying that the clinical/non-clinical distinction is arbitrary, it weakens the conceptual infrastructure on which clinical claims rest. This is not a hypothetical harm. It is the mechanism by which a great deal of dismissal of severe mental illness operates: not by claiming that mental illness doesn’t exist, but by claiming that everyone is a bit mentally ill, so what’s the problem, stop complaining.

Allen Frances, who chaired the DSM-IV task force and subsequently became a sharp critic of diagnostic inflation, wrote a book (Saving Normal, 2013) about the opposite problem: the expansion of diagnostic categories to medicalise ordinary human variation (Frances, 2013). Frances’s worry and the slogan’s argument share a logical structure — “the line between normal and disordered is blurry, therefore the line is somewhat arbitrary” — and both forget the same thing: the people with the most severe, genuine, impairing psychiatric conditions need that line to carry weight. Blur it enough and their most urgent claims become indistinguishable from everyone else’s minor struggles.

Problem 3: What the Anti-Stigma Literature Actually Says

Does the “we’re all a bit X” normalisation framing reliably reduce stigma? The evidence is, at best, mixed.

Patrick Corrigan and David Penn’s review of social-psychological approaches to psychiatric stigma identifies a consistent risk in normalisation campaigns: they can fail to distinguish between the ordinary distress that everyone experiences and the clinical conditions that require treatment and support (Corrigan & Penn, 1999). When stigma reduction messaging implies that psychiatric conditions are simply more-of-what-everyone-has, it may reduce perceived severity and undermine motivation to support treatment access.

Kvaale, Haslam, and Gottdiener’s meta-analysis of biogenetic framings in anti-stigma campaigns — which share structural features with the normalisation approach — found paradoxical effects: reduced blame, yes, but sometimes increased perceived dangerousness and greater social distance (Kvaale, Haslam, & Gottdiener, 2013). The “we’re all on a spectrum” variant has its own specific paradox: if nobody is normal, the distinction that generates stigma dissolves — but so does the distinction that generates respect for people with serious conditions who need real resources. Both edges cut.

What the literature supports more robustly is contact: direct, positive interaction with people who have experience of mental illness, presented as whole persons and not primarily as patients. Contact works better than educational campaigns about what mental illness is or isn’t. The “nobody is normal” poster is an educational campaign about what mental illness isn’t. It is probably less effective than a conversation.

Problem 4: The Institutional Contradiction

There is a fourth problem, and I find it the most striking.

The slogan belongs to a Sozialpsychiatrisches Zentrum — an institution that exists precisely because some people have psychiatric conditions that impair their functioning and require dedicated support. Its implicit mission: there is a meaningful distinction between people who need psychiatric services and people who do not, and we provide those services for the former.

The slogan: nobody is normal.

If nobody is normal, then everybody is, in the relevant sense, a bit psychiatrically ill. If the line between normal and not-normal is arbitrary, then so is the line between people who need psychiatric services and people who don’t. If the category “psychiatric condition requiring support” is as fuzzy as the slogan implies — a mere matter of proximity and perspective — then why should anyone prioritise coming to this particular institution?

The slogan, taken seriously, argues against the relevance of its own institution. A psychiatric centre has printed on its posters the claim that psychiatric categories dissolve under close examination. This is an unusual thing for a psychiatric centre to announce.

The Analogous Translation

Let me make the logical structure visible with a direct translation into another field of medicine:

“Aus der Nähe betrachtet hat keiner ein normales Herz.”

“Up close, nobody has a normal heart.”

This is, in a technical sense, largely true. Cardiologists can find something to remark on in almost any heart — a minor valve irregularity, some degree of atherosclerosis past middle age, a benign arrhythmia, a structural variation within the clinical reference range. Under sufficiently detailed examination, the perfectly normal heart is a platonic ideal rather than a clinical reality.

Does this mean coronary artery disease doesn’t exist? Does it mean myocardial infarction is a matter of perspective or proximity? Does it mean that someone waiting for a cardiac transplant should be reassured that, up close, nobody has a normal heart, so they shouldn’t worry too much about their own?

Obviously not. The clinical category of cardiac disease does not depend on the existence of a perfectly normal heart. It depends on whether specific mechanisms are failing in ways that cause harm — which is true for some people and not for others, regardless of whether everyone has some minor deviation from an idealised cardiovascular anatomy.

The slogan about psychiatric normalcy makes exactly the same error. The clinical category of mental disorder does not depend on the existence of a psychologically perfect human being. It depends on whether psychological mechanisms are failing in ways that cause harm — which is true for some people and not for others, regardless of whether everyone has quirks, struggles, or eccentricities.

The heart analogy is also useful for what it reveals about whose interests the slogan serves. “Nobody has a normal heart” would be printed, presumably, to reassure people who feel embarrassed about their cardiac condition — to say: you’re not so different from anyone else. What it actually does is make it harder for that person to say: my heart is not functioning well, and that is a real medical fact that deserves real medical attention. The compassionate intent and the practical effect run in opposite directions.

What Would Actually Help

The goal — reducing stigma against people with psychiatric conditions — is correct and important. The approach — dissolving the category of “normal” until psychiatric and non-psychiatric become indistinguishable — is not.

A more defensible anti-stigma argument goes: mental illness is real, it involves genuine failures of psychological functioning, it causes genuine suffering, and none of that makes the person with it less worthy of respect, resources, and full participation in society. This is the position that affirms both the reality of the condition and the humanity of the person. It does not require denying the normal/abnormal distinction. It requires insisting that the distinction does not carry the moral weight that stigma assigns to it.

The difference between “nobody is normal, so stop stigmatising” and “you can be ill and still be a person of full worth” sounds subtle. In practice, it is enormous. The first removes the conceptual ground from under the people most in need. The second leaves the ground intact while refusing to let it be used as a weapon.

Psychisch krank — und trotzdem ganz. Mentally ill — and still whole. Not: nobody is normal. But: being ill doesn’t make you less of a person. The second slogan does not hand ammunition to the dismissers. The first one does.

Karneval Coda

It is Karneval. Everyone is wearing a mask.

The slogan “Aus der Nähe betrachtet ist keiner normal” is wearing a mask too: the mask of tolerance, of radical inclusion, of refusing to pathologise difference. Under the mask is a logical structure that, taken seriously, would dissolve the evidentiary basis for psychiatric care, hand a slogan to everyone who has ever told someone with depression that they just need to try harder, and leave the people with the most severe conditions with one fewer conceptual tool for insisting that their suffering is real, their need is legitimate, and their claim on resources and support deserves to be taken seriously.

The mask is well-intentioned. Karneval ends on Wednesday. The poster will still be on the wall.

References

• Wakefield, J. C. (1992). The concept of mental disorder: On the boundary between biological facts and social values. American Psychologist, 47(3), 373–388. DOI: 10.1037/0003-066X.47.3.373
• American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental Disorders (5th ed.). American Psychiatric Publishing. DOI: 10.1176/appi.books.9780890425596
• Boorse, C. (1977). Health as a theoretical concept. Philosophy of Science, 44(4), 542–573. DOI: 10.1086/288768
• Haslam, N. (2016). Concept creep: Psychology’s expanding concepts of harm and pathology. Psychological Inquiry, 27(1), 1–17. DOI: 10.1080/1047840X.2016.1082418
• Frances, A. (2013). Saving Normal: An Insider’s Revolt against Out-of-Control Psychiatric Diagnosis, DSM-5, Big Pharma, and the Medicalization of Ordinary Life. HarperCollins.
• Corrigan, P. W., & Penn, D. L. (1999). Lessons from social psychology on discrediting psychiatric stigma. American Psychologist, 54(9), 765–776. DOI: 10.1037/0003-066X.54.9.765
• Kvaale, E. P., Haslam, N., & Gottdiener, W. H. (2013). The ‘side effects’ of medicalization: A meta-analytic review of how biogenetic explanations affect stigma. Clinical Psychology Review, 33(6), 782–794. DOI: 10.1016/j.cpr.2013.06.002