Autism Diagnosis Today (5): Self-Diagnosis

Pressure on Diagnostic Services

In recent years, adult autism diagnostic services have come under exceptional pressure. Referral rates have surged, far outpacing clinical capacity, and exposing systemic limitations in provision. The consequences are stark. An NHS-funded diagnostic service in Oxfordshire, for example, recently closed its waiting list after estimating that it could take until 2043 to process its backlog of over 2,000 patients. For individuals referred before 2021, waiting times already stretch to four years, while more recent referrals may face delays of up to 19 years (Delgado 2024).

This is not an isolated case. Across England, NHS data show a marked increase in adults waiting longer than the recommended 13-week threshold for assessment – from 5,667 in 2019 to nearly 60,000 in 2024. Such figures illustrate not merely administrative inefficiency but a fundamental mismatch between demand and diagnostic capacity.

In response, some services have introduced triage systems to prioritise cases. A recent evaluation in West Yorkshire (Adamou et al. 2025) found that none of the triaged cases ultimately received an autism diagnosis, suggesting that many referrals may reflect broader psychological or social difficulties rather than clear evidence of autism. The triage approach helped redirect individuals to more appropriate services—clinically sensible, if not always consistent with expectations.

Such findings highlight a growing challenge for clinicians: distinguishing autism from other psychiatric or psychosocial conditions that can produce superficially similar presentations – such as anxiety, depression, trauma-related disorders, or personality disorders. Without careful developmental assessment, adult behavioural profiles alone risk creating a “final common pathway” that obscures diagnostic specificity.

The Rise of Self-Diagnosis

Alongside these pressures, self-diagnosis has expanded rapidly. Increasingly, individuals identify as autistic without formal assessment, drawing on online content, personal narratives, and popularised symptom checklists.

The phenomenon itself is not entirely new. Long before social media, Jerome K. Jerome captured the tendency toward self-diagnosis with characteristic irony in Three Men in a Boat (1889):

“I remember going to the British Museum one day to read up the treatment for… hay fever… I got down the book, and read all I came to read, and then, in an unthinking moment, I idly turned the leaves, and began to indolently study diseases, generally…  and, before I had glanced half down the list of ‘premonitory symptoms, it was borne in upon me that I had fairly got it… [He concludes that he suffers from nearly every disease listed]…the only malady… I had not got was housemaid’s knee. I had walked into that reading-room a happy healthy man. I crawled out a decrepit wreck ”

Over-identification with vaguely defined symptoms remains relative today, though it is now facilitated by algorithms rather than Victorian-era medical textbooks.

As Davis (2022) argues, the term “self-diagnosis” is itself misleading. Diagnosis is not merely the labelling of experience but the outcome of a structured clinical process conducted by trained professionals. Individuals may interpret their experiences, but applying psychiatric labels outside this framework carries no formal validity.

More accurately, what is occurring is personal appropriation (Davis 2010): the selective adoption of diagnostic categories to make sense of experience. Individuals draw on a mixture of sources—search engines, social media, anecdote—and reshape diagnostic criteria to fit their self-concept. Less appealing elements of clinical definitions tend to recede; more affirming ones are retained.

The result is a widening gap between clinical constructs and their popular counterparts. Diagnostic categories, once anchored in manuals such as the DSM, become “floating signifiers” – flexible enough to accommodate a wide range of everyday frustrations, disappointments, and ambiguities.

For some, this process does not end with disagreement from clinicians. Individuals may pursue private assessments or consult multiple professionals in succession – effectively “doctor shopping” in search of diagnostic agreement. Such behaviour is not unique to autism and is well recognised in the sociology of diagnosis (e.g. Rogers & Pilgrim 2010; Jutel 2011). While it is understandable in the context of long waiting times and unmet needs, it also reflects a shift in which diagnosis is treated less as a conclusion to be reached than as a goal to be secured.

Social Media and the Misinformation Ecosystem

Social media has become a central driver of this shift. Beyond disseminating information (and misinformation), it increasingly shapes expectations about diagnosis itself.

In some online spaces, users are explicitly advised how to obtain a diagnosis – by presenting exaggerated or stereotypical traits, framed, at times, as justified resistance to clinical authority. E.g.:

“You just have to tell them what they want to hear they think you’re lacking, super stereotypical day…You can’t make iContact, you flap your hands, you don’t understand how to have a conversation, you collect trains. You get the picture… If they won’t adapt, then we just learn how to manipulate their system”

While anecdotal, such examples illustrate a broader reframing: diagnosis as an outcome to be achieved rather than a judgement to be made.

This moves beyond misunderstanding into deliberate manipulation. Diagnosis is no longer simply established; it is, in some cases, actively pursued and strategically performed – potentially by rehearsing symptoms that align with simplified stereotypes. The consequences are predictable: distorted public images of autism and increasing strain on already overextended services.

At the same time, misinformation is widespread. Large-scale analyses (Carter et al. 2026) reveal that a substantial proportion of autism- and ADHD-related content on platforms such as TikTok is inaccurate – 41% in the case of autism and 52% for ADHD. Other studies report misinformation rates as high as 56%. Notably, misleading content often attracts more engagement than accurate material – a reminder that accuracy and popularity do not necessarily coincide.

Platform algorithms further intensify this dynamic, promoting highly engaging content and creating feedback loops in which repeated exposure normalises questionable claims. As Yeung et al. (2022) and Thapa et al. (2018) show, misleading content often outperforms reliable information in reach and appeal.

The result is a gradual flattening of diagnostic meaning. Simplified symptom lists encourage over-identification, while nuanced distinctions are lost. Ordinary variations in personality and responses to stress are increasingly reinterpreted through a diagnostic lens.

Diagnostic Boundaries and Conceptual Drift

The expansion of autism as a category must also be understood within a broader shift toward dimensional models of psychopathology. Subthreshold autistic traits are relatively common in clinical populations, particularly among young adults. However, the presence of such traits does not equate to a diagnosis (Folatti et al. 2024).

Within the medical model, autism requires impairment. Yet contemporary discourse increasingly emphasises “difference” over disorder (Hollingdale et al. 2025). While this may reduce stigma, it risks eroding the criteria that give the diagnosis coherence.

Casanova (2015) highlights related concerns when individuals with personality disorders self-identify as autistic. Although certain traits may overlap superficially, the underlying mechanisms differ. Conflating these conditions risks both misunderstanding and inappropriate treatment.

Identity, Incentives, and the Politics of Diagnosis

Self-diagnosis is not merely a cognitive process; it is also shaped by social incentives. Diagnostic labels can provide access to community, validation, and what Fellowes (2023) terms “social resources,” including advocacy and participation in research. As David and Deeley (2024) note, the appeal of diagnosis often lies in its capacity to render personal struggles intelligible and shared.

However, this dynamic also introduces new inequalities. As diagnostic categories expand to include milder or ambiguous cases, resources may be diverted away from those with more severe impairments. At the same time, individuals who are less articulate or unable to self-advocate – often those most affected – risk being marginalised within a discourse dominated by self-diagnosed voices.

There is also a notable asymmetry in which conditions are embraced. While autism and ADHD have gained social traction, other disorders – such as schizophrenia or personality disorders – remain heavily stigmatised and are rarely self-diagnosed. This suggests that the appeal of diagnosis depends not only on personal experience but by their perceived social meaning.

Misdiagnosis and Missed Care

One of the most significant risks of self-diagnosis is misattribution. Clinical studies indicate that only around half of individuals referred for autism assessment ultimately meet diagnostic criteria (Russell et al. 2016). Many present instead with treatable conditions such as obsessive–compulsive disorder, social anxiety, or depression.

Prematurely adopting an autism label may delay or divert appropriate care. Discrepancies between self-reported and clinician-assessed symptoms (Gu et al. 2024) further highlight the limitations of self-identification.

This is compounded by a broader difficulty in distinguishing autism from other conditions. McMahon (2024) shows that even well-educated individuals struggle to differentiate autism from other disabilities, pointing to widespread conceptual confusion.

The Cultural Expansion of Diagnosis

These developments sit within a wider culture of “diagnostic inflation” (Haslam 2025). Psychiatric labels have become embedded in everyday language, fuelled by social media and shifting cultural attitudes. While stigma has declined, boundaries have blurred.

Research suggests that adopting diagnostic labels for mild or ambiguous difficulties may have unintended consequences. Individuals who frame their experiences in diagnostic terms may feel less able to cope and more likely to view their difficulties as fixed and uncontrollable.

Expanding diagnostic categories may, therefore, be as constraining as it is liberating – offering explanation, while quietly narrowing perceived possibilities for change.

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The rise of self-diagnosis reflects broader cultural, technological, and institutional shifts. It emerges at the intersection of overstretched healthcare systems, the proliferation of online information, and shifting cultural understandings of identity and mental health.

While self-identification may offer meaning and community, it also carries significant risks – misdiagnosis, misinformation, conceptual drift, and the redistribution of already limited resources. More subtly, it risks transforming diagnosis itself: from a careful clinical judgement grounded in evidence and developmental history into something more negotiable, performative, and, at times, strategically pursued.

Autism remains, fundamentally, a medical diagnosis. Preserving its clinical integrity is not an act of gatekeeping, but a prerequisite for ensuring that it retains meaning, that support reaches those who need it most, and that the concept itself is not diluted to the point where it explains everything – and, therefore, ultimately, very little.