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Record W4409321148 · doi:10.1111/acps.13811

Formulating Cognitive Functioning to Guide Personalised Treatment for People Diagnosed With Mental Disorders

2025· article· en· W4409321148 on OpenAlexaff
Kelly Allott, Shayden Bryce, Katie M. Douglas, Alexandra Stainton, Stephen J. Wood, Christopher R. Bowie

Bibliographic record

VenueActa Psychiatrica Scandinavica · 2025
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsQueen's University
FundersUniversity of Melbourne
KeywordsCognitionPsychologyCognitive skillPsychiatrySocial functioningClinical psychologyMedicinePsychotherapist

Abstract

fetched live from OpenAlex

ABSTRACT Introduction Objective and subjective cognitive impairment are highly prevalent in mental disorders and transdiagnostic phenomena. Cognitive impairment is associated with poorer functional outcomes and therefore requires treatment, but little guidance is available for clinicians. The aim of this article is to provide guidance for formulating an individual's cognitive profile and how this can be used to personalise treatments for optimum cognitive and functional outcomes. Methods We first critique current models of psychopathology in relation to assessing and addressing cognitive functioning in the clinic. This is followed by a description of key methods for assessing objective and subjective cognitive functioning and how this information can be used to formulate a patient's cognitive profile and tailor treatment. Results Within current models of psychopathology, cognition is inadequately or simplistically represented, is only viewed from a deficit lens without considering strengths, does not consider subjective perceptions of cognitive functioning, and therefore, generally does not provide utility for guiding clinical practice. Both the profile of cognitive functioning (strengths and weaknesses) and estimated change from premorbid levels are key considerations for tailoring cognitive and functional treatments. Cognitive profile and change can be assessed using standardised cognitive tests through normative and idiographic methods, respectively. Subjective perception of cognitive functioning is a neglected but important additional aspect of cognitive functioning that warrants assessment. The complete cognitive profile can be used to guide the selection of cognition‐focused treatments, including psychoeducation, lifestyle adaptations, cognitive remediation, compensatory strategies, environmental supports, psychological therapy, and medication review. Conclusions We propose that cognition should be assessed in addition to presenting psychopathology because it is an independent transdiagnostic predictor of functional outcomes, which can enhance personalised clinical care. We recommend assessing both objective and subjective cognitive functioning to formulate the personalised treatment for optimal functional outcomes and promote a culture of recovery that includes cognitive health.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.329
Teacher spread0.315 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2025
Admission routes1
Has abstractyes

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