The concept at the heart of the paper is cognitive disorganization, a term that covers a cluster of observable difficulties: trouble sustaining attention, difficulty sequencing the steps of a task, problems accessing language when it is needed, and disruptions in discourse organization, the ability to assemble speech into a coherent, goal-directed flow. In help-seeking youth, these difficulties frequently appear alongside unusual experiences, such as odd perceptual events or strange beliefs, and alongside functional decline at school, at home, or among peers. The traditional clinical reflex is to read this combination as a signal of emerging psychosis risk. Niederlohmann does not dismiss that possibility, but he insists it is only one of several plausible readings, and that a responsible formulation must be able to distinguish between them rather than collapsing everything into a single ominous label.

The proposed framework rests on four questions. First, what is the young person’s developmental baseline, meaning the level of attentional, linguistic, and organizational functioning that was typical for them before the current difficulties emerged? Second, which functions vary within the person across cognitive load, context, and time, a question that probes whether the disorganization is stable or fluctuates predictably under stress, fatigue, or specific environmental demands? Third, what is actually happening in the environment, and how is the young person interpreting it, particularly with respect to threat? Fourth, do established clinical-risk indicators require formal assessment or referral, for example when unusual experiences or functional decline cross thresholds that standard instruments are designed to detect? Each question addresses a different assessment task, and the author emphasizes that they may be considered together as a proposed clinical heuristic rather than a rigid protocol.

The developmental-baseline question deserves particular attention because it changes the meaning of everything that follows. A young person whose discourse organization has always been somewhat fragile, perhaps due to a longstanding developmental language difference, presents a very different formulation picture from one whose speech became disorganized over the course of weeks. Without anchoring the assessment to a documented baseline, clinicians risk mistaking a stable trait for an acute deterioration, or vice versa. This is why the framework insists that formulation begin with what is known about the individual’s prior functioning, gathered from school records, family report, and previous clinical contacts, before any interpretive weight is placed on current presentation.

The second question, concerning within-person variability, draws on a body of acute-stress research showing that stress can affect specific executive outcomes under studied conditions. Executive functions, the umbrella term for abilities such as working memory, cognitive flexibility, and inhibitory control, are known to be sensitive to acute stressors in controlled experimental settings. Niederlohmann’s treatment of this evidence is notably careful. He argues that extrapolating these laboratory findings to discourse organization, to threat meanings, or to reality testing in help-seeking youth is not yet sufficiently supported by the literature. In other words, it is reasonable to hypothesize that a young person’s disorganized speech worsens under stress, but that remains a domain-specific formulation hypothesis to be tested, not an established property of the presentation. The distinction matters enormously in clinical practice, where a plausible-sounding stress explanation can quietly harden into an assumed fact.

The third question moves the assessment outward, into the environment itself. Cognitive disorganization does not develop in a vacuum, and the framework asks clinicians to document what is genuinely occurring in the young person’s life, including any actual harm, coercion, or danger, and separately to assess how the young person interprets those events. A teenager who lives in a genuinely threatening household and a teenager who misreads benign social cues as hostile may both present with vigilance, fragmented speech, and unusual beliefs, but the appropriate responses differ radically. The paper is emphatic on this point: assessment of genuine environmental harm, safeguarding needs, and urgent medical or psychiatric risk takes precedence over explanatory interpretation. Before any formulation is debated, the clinician must establish whether the young person is safe.

The fourth question functions as a safety net within the heuristic itself. Established clinical-risk indicators, the signs that research and practice guidelines have flagged as warranting formal assessment, must be checked systematically rather than assumed away by an elegant explanatory narrative. If a young person shows indicators associated with psychosis risk, the framework directs the clinician toward formal assessment or referral, regardless of how compelling an alternative developmental or stress-based explanation might appear. This ordering reflects a core epistemic commitment of the paper: explanatory hypotheses are useful only insofar as they do not displace the detection of established risk.

Perhaps the most methodologically interesting feature of the Perspective is its explicit distinction between three tiers of knowledge: direct evidence, adjacent findings, and clinical hypotheses. Direct evidence in this domain is comparatively thin; adjacent findings, such as the acute-stress effects on executive outcomes, are real but bounded to the conditions in which they were studied; and clinical hypotheses, such as the idea that stress sensitivity explains a particular young person’s disorganized discourse, must be held as testable propositions. The author proposes that prospective studies should measure these domains separately, assessing the reliability of the four-question heuristic, its incremental clinical value over existing approaches, and its safety, meaning its capacity to avoid missing genuine risk, against explicit alternative explanations and falsification criteria. This is a demanding research agenda, and the paper does not pretend the heuristic has already met it.

The publication also carries a transparent account of its own production. The author discloses that generative AI tools were used during early manuscript development for brainstorming and preliminary mapping of potentially relevant literature, and later for English-language copy editing, with all suggestions independently evaluated and all cited sources verified by the author, who accepts full responsibility for the content. The article reports no original research involving human participants; all clinical illustrations are constructed, and no participant data were collected. The author declares income from clinical practice, teaching, supervision, and psychotherapy training, as well as work as an author and translator of professional literature, as potentially relevant interests. No funding was received for the manuscript. These declarations sit within a growing norm of openness about how perspective papers are assembled, and they do not alter the substance of the argument, but they give readers the information needed to weigh it.

What, then, is the practical takeaway for clinicians, services, and researchers watching the field of youth mental health? The contribution, as Niederlohmann frames it, is organizational rather than discovery-based: the paper does not introduce new syndromes or new instruments, but arranges established assessment domains around observable difficulties and documented uncertainty. For a clinician confronting a disorganized, distressed young person, the four questions offer a sequence that starts with the individual’s own developmental history, maps the fluctuation of functions under load and context, examines the environment and its interpretation, and only then triggers formal risk pathways where indicators demand it. For researchers, the paper issues a challenge: stop treating stress sensitivity and disorganization as a single bundled phenomenon, and design studies that measure the domains separately, with explicit criteria for when a formulation hypothesis should be rejected. If that agenda is pursued, the heuristic could help services move beyond the binary of over-pathologizing unusual cognition and under-detecting genuine emerging illness, a balance that matters most for the young people whose futures depend on getting the interpretation right the first time.

Subject of Research: A transdiagnostic developmental formulation approach to cognitive disorganization in help-seeking youth

Article Title: Cognitive disorganization in help-seeking youth: a transdiagnostic developmental formulation perspective

Article References: Niederlohmann, E. (2026). Cognitive disorganization in help-seeking youth: a transdiagnostic developmental formulation perspective. Discover Psychology. https://doi.org/10.1007/s44202-026-00939-6

Image Credits: AI Generated

DOI: 10.1007/s44202-026-00939-6

Keywords: cognitive disorganization, clinical formulation, transdiagnostic, adolescent mental health, developmental psychopathology, psychosis risk, psychological assessment, safeguarding, stress sensitivity, executive function, help-seeking youth, clinical heuristics

That moment of misdirection, described by Dr. Danilo Rojas-Velasquez of Harvard Medical School and Beth Israel Deaconess Medical Center in a new viewpoint article published in Academic Psychiatry, sits at the heart of an argument that is gaining urgency across academic medicine: the language clinicians write into charts is not a neutral record but a durable force that shapes how every subsequent clinician perceives a patient. Psychiatry, a chart-heavy specialty in which practitioners learn to scan prior notes for buzzwords that key early hypotheses, is particularly exposed. Words travel with patients across years of records, and the language chosen by one team determines how the next team imagines the person in the bed.

Clinical medicine has already made a deliberate effort to soften the edges of its vocabulary. Undomiciled has largely replaced homeless, non-adherent has supplanted non-compliant, and declined is preferred to refused. These substitutions reflect a genuine ethical awareness that stigmatizing descriptors can follow patients for decades. But Rojas-Velasquez argues that such lexical swaps can function as a kind of hygiene that leaves the underlying clinical gaze unchanged. A patient called non-adherent by a frustrated team is not necessarily better understood than one called non-compliant; the person is simply described in the currently sanctioned vocabulary. The deeper issue is not which words are approved but what those words do once they are placed in a chart and begin to circulate.

The empirical evidence behind this concern is substantial. A growing body of research documents that stigmatizing language in the medical record measurably alters downstream clinical decisions, including pain management and the intensity of diagnostic workups. Studies have found that descriptors such as pleasant and cooperative are applied unevenly across patient race, meaning that the chart itself can become a vector for the transmission of bias. Physician use of stigmatizing language in patient records has been documented systematically in large-scale analyses, and researchers have shown that negative framing in one note propagates into the impressions formed by later readers. Yet documentation is still often treated as a matter of mechanics: billing compliance, problem-list hygiene, and the architecture of the assessment and plan. The ethics of clinical language, what a clinician is actually doing to a patient when writing about them, has remained a hidden curriculum, absorbed by osmosis from whichever notes a trainee happens to read.

Into this landscape, ambient scribes and large language model-assisted documentation are arriving faster than the educational infrastructure can adapt. Randomized trials of ambient AI scribes in clinical practice are already underway, and health systems are deploying the tools at scale. The technical mechanism of concern is subtle but consequential: AI tools inherit and polish the linguistic conventions of their training data, which means that stigmatizing patterns already present in charts are being laundered into outputs that feel more authoritative precisely because they are fluent. A trainee who might once have written that a patient seems frustrated may now sign a note describing him as hostile and uncooperative simply because that is what the model produced. Fluency, in this context, is not accuracy; it is a cosmetic upgrade applied to inherited bias.

There is also an educational cost. Historically, the note has been the place where clinical formulation happens. Writing was thinking, and the attending’s question of why a trainee described a patient in a particular way was a teaching moment built directly into the workflow. When the note arrives pre-formed by an algorithm, that moment is structurally removed unless educators deliberately rebuild it. The formulation step, in which a clinician weighs observations, considers alternative explanations, and commits to a reasoned characterization of the patient, is being quietly absorbed by the model. What remains for the trainee is verification, which is a fundamentally different and far less formative cognitive task.

In response, the article proposes three practical steps for teaching note writing in the age of AI. The first is to teach note-reading before note-writing. On a rotation, a resident might review prior documentation, name the impression those notes created, and then compare that impression with what actually emerges at the bedside. The point is not to grade the prior note or its author but to make the chart’s authorial power visible before the resident adds to it. This exercise converts an invisible influence into an object of explicit study, allowing trainees to feel firsthand how a one-line summary can pre-load an entire clinical encounter with assumptions.

The second step is to build a next-reader pause into supervision. Before signing a note, the trainee considers how it would read to a covering clinician at three in the morning, to the patient with portal access, and to a family member reviewing the chart. Open Notes initiatives and patient-facing documentation have already shifted the audience for clinical writing; patients can now read the words written about them, and imagining these readers helps residents notice attributions and tones of voice that would otherwise pass unexamined. Qualitative work on patient-centered documentation in the era of open notes suggests that this kind of deliberate audience-awareness changes how clinicians draft, encouraging precision and fairness over shorthand judgment.

The third step treats the editing of AI-drafted notes as genuine clinical work rather than clerical review. If formulation is being absorbed by the model, the trainee’s task is not merely to check grammar or fill gaps but to interrogate what the draft has already decided: where observations have hardened into character judgments, where hedge words have drifted toward unwarranted certainty, and where descriptors would not survive the next-reader test. The article suggests a weekly note rounds, in which a team reviews and revises an anonymized AI-drafted note together, turning a hidden judgment back into a shared teaching moment. In this arrangement, the AI draft becomes a specimen to be dissected rather than a product to be signed, restoring the pedagogical function that automation threatened to erase.

The chart remains one of the few places in medicine where a patient is constructed in their absence, by people with power over them, in language they have historically been unable to see. Open Notes is changing the last part of that sentence, and ambient AI is changing the second, but the construction itself endures, and arguably matters more now than it did when notes lived in locked basements. Consultation-liaison psychiatrists, who live in other clinicians’ notes before they ever meet their patients, are unusually positioned to notice this dynamic. They watch language do its quiet work, and they write notes that will in turn shape how the next team thinks. Whether the current generation of trainees inherits a thoughtful relationship to that responsibility, or simply a more polished vocabulary applied at greater speed, will depend in large part on how medical educators decide to teach it. The stakes are not stylistic. They concern who patients become on paper before anyone meets them in person, and whether the accelerating machinery of AI-assisted documentation amplifies clinical understanding or merely automates its failures.

Subject of Research: Teaching ethical clinical documentation and note-writing skills to psychiatry trainees in the era of AI-assisted medical records

Article Title: Teaching Note Writing in the Age of AI: Three Practical Steps

Article References: Rojas-Velasquez, D. (2026). Teaching Note Writing in the Age of AI: Three Practical Steps. Academic Psychiatry. https://doi.org/10.1007/s40596-026-02434-5

Image Credits: AI Generated

DOI: 10.1007/s40596-026-02434-5

Keywords: clinical documentation, artificial intelligence, psychiatry education, stigmatizing language, medical records, ambient AI scribes, large language models, Open Notes, clinical formulation, medical bias, consultation-liaison psychiatry, graduate medical education