A New Nosology: Mental Illness as Maladaptive Misinformation Processing

A New Nosology: Mental Illness as Maladaptive Misinformation Processing

This research proposes a novel conceptualization of mental illness, moving beyond the prevailing "harmful dysfunction" model to redefine psychopathology as "maladaptive misinformation processing." This framework posits that the core of mental disorder is a persistent inability to distinguish, categorize, and respond appropriately to veridical information versus misinformation. Drawing on philosophical information theory, which rigorously separates truth-bearing information from "pseudo-information," this approach aims to provide a more precise, scientifically grounded, and less value-laden foundation for psychiatric nosology. The proposal outlines a theoretical analysis to demonstrate how this definition avoids the cultural relativism and teleological ambiguities inherent in current models. It will explore how this epistemic failure can manifest at two distinct levels: the processing of raw physical information (e.g., sensory distortions in psychosis) and the processing of abstract semantic information (e.g., delusional belief systems). The primary objective is to establish a criterion for disorder that remains robust even in social contexts where epistemic irrationality is normalized, thereby offering a more stable and objective basis for diagnosis and research.

Theoretical Background: The Crisis of Definition

The dominant functionalist model in the philosophy of psychiatry, Jerome Wakefield's "harmful dysfunction" (HD) analysis, defines mental disorder as a conjunction of a factual component (a dysfunction) and a value component (harm). Specifically, a condition is a disorder if an internal mechanism fails to perform a function for which it was designed by natural selection, and this failure is deemed harmful or undesirable by society. Despite its influence, this model faces critical, potentially fatal, objections.

The "dysfunction" criterion is fraught with difficulty. It relies on a teleological concept of "evolutionary design," which attributes a purpose or intention to the non-agentive process of natural selection. This is scientifically problematic, as many mental functions may be adaptively neutral by-products (exaptations) rather than direct adaptations shaped for a specific purpose. Defining the "natural function" of a complex cognitive mechanism is often a matter of speculation rather than scientific determination.

The "harm" criterion introduces an inescapable cultural relativism. Because harm is defined by societal judgment, the boundary between disorder and non-disorder can shift dramatically across cultures and historical periods. This allows for situations where clear epistemic irrationality might be considered non-harmful or even adaptive within a specific social context, thereby failing to qualify as a disorder under the HD model.

A Proposed Solution: An Epistemic, Information-Theoretic Framework

To resolve these issues, this research proposes a shift from a functionalist-evolutionary framework to an epistemic, information-theoretic one. The philosophical anchor for this model is Luciano Floridi's veridicality thesis, which posits that for something to count as semantic information, it must be truthful.4 This thesis has a profound implication: misinformation and disinformation are not flawed types of information but are categorically different entities—"semantic junk" or "pseudo-information". This provides a sharp, objective, and non-negotiable distinction between what is information and what is not.

Building on this, mental illness can be reconceptualized as a systemic failure in the cognitive architecture responsible for differentiating veridical data (information) from non-veridical data (misinformation). This failure is "maladaptive" not because it violates an assumed evolutionary design, but because it fundamentally prevents the organism from forming an accurate model of its environment, leading to flawed predictions, decisions, and behaviors. This definition can be applied at two distinct levels of processing, reflecting different domains of cognitive science.

• Failure in Processing Physical Information: This refers to the processing of raw data from sensory organs and internal physiological states. A breakdown at this level results in a failure to accurately model the immediate physical world. This could manifest as hallucinations (perceiving stimuli that are not present) or perceptual distortions (misperceiving stimuli that are present), as seen in psychotic disorders.

• Failure in Processing Semantic Information: This refers to the processing of abstract, conceptual knowledge, including facts, meanings, beliefs, and the relationships between them. A failure at this level results in a distorted model of reality at a conceptual level. This manifests as delusions, paranoia, or the deeply entrenched, irrational belief systems characteristic of delusional disorders or obsessive-compulsive disorder.

Methodology

This project is primarily a theoretical and conceptual doctorate. The methodology will consist of three main components:

1. Conceptual Analysis: A rigorous philosophical analysis will be conducted to compare the logical consistency, explanatory power, and scientific tractability of the HD model versus the proposed "maladaptive misinformation processing" (MMP) model. This will involve a systematic deconstruction of the core assumptions of each model.

2. Case Study Analysis: The two models will be applied to classic psychiatric case studies and diagnostic categories (e.g., schizophrenia, delusional disorder, body dysmorphic disorder). This analysis will aim to demonstrate the MMP model's superior precision and its ability to circumvent the problems of cultural relativism and teleological speculation that plague the HD model.

3. Literature Synthesis: Findings from cognitive psychology, computational neuroscience, and philosophy of information will be integrated to provide an empirical basis for the mechanisms of "misinformation processing." This will connect the high-level philosophical concept to concrete research on belief formation, delusion, and cognitive biases.

Reframing mental illness in these epistemic terms provides a significant theoretical advance. It shifts the diagnostic focus away from subjective distress ("harm") and speculative evolutionary history ("dysfunction") and toward objective, and potentially measurable, processing deficits. The concepts of "harm" and "dysfunction" are notoriously difficult to operationalize and quantify. hmm In contrast, information processing is amenable to computational modeling. The ability to distinguish a veridical signal from non-veridical noise is a quantifiable task central to fields like signal detection theory and Bayesian inference. This opens the possibility of modeling specific psychopathologies as distinct types of failures within a computational cognitive architecture. For example, delusions could be modeled as the product of assigning pathologically high confidence (precision) to incorrect prior beliefs, while hallucinations could be modeled as a failure to correctly infer the causes of sensory input due to a noisy sensory channel. This approach moves psychiatry closer to computational neuroscience, providing a potential "lingua franca" to connect clinical symptoms to underlying neural computations and paving the way for targeted interventions designed to correct specific processing errors.

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