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Record W2037420498 · doi:10.4088/jcp.10m06628

Lifespan Persistence of ADHD

2012· article· en· W2037420498 on OpenAlexaff
Atilla Turgay, D. Wayne Goodman, Philip Asherson, Robert Lasser, T. Babcock, Michael L. Pucci, Russell A. Barkley

Bibliographic record

VenueThe Journal of Clinical Psychiatry · 2012
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsToronto General HospitalUniversity of Toronto
Fundersnot available
KeywordsContext (archaeology)ComorbidityPsychologyAttention deficit hyperactivity disorderPsychiatryMental healthStressorPsychopathologyChild and adolescent psychiatryClinical psychology

Abstract

fetched live from OpenAlex

Article Abstract Background: The understanding that attention-deficit/hyperactivity disorder (ADHD) often persists throughout life has heightened interest of patients, families, advocates, and professionals in a longitudinal approach to management. Such an approach must recognize and address known patient- and systems-based challenges of long-term mental health treatment, shifting of clinical presentations of ADHD, and commonality of psychiatric comorbidity with ADHD. Objective: The ADHD Life Transition Model is a step toward developing criteria to optimize recognition and clinical management of ADHD (eg, response, remission) across an individual's lifespan and across diverse medical subspecialties. To support therapeutic efficiency and adaptability, our proposed model highlights periods when external resources for managing ADHD are reduced, cognitive and behavioral stressors are increased, and individuals may be reevaluating how they perceive, accept, and adhere to ADHD treatment. Such a model aims to support the clinical community by placing in context new findings, which suggest that the prevention of adult psychopathology in individuals with pediatric ADHD may be possible. Conclusions: The ADHD Life Transition Model seeks to improve care for individuals with ADHD by (1) underscoring that ADHD persists beyond childhood in at least two-thirds of patients, (2) raising awareness of the need to approach ADHD from a chronic illness standpoint, and (3) increasing mental health professionals†diligence in symptom recognition and management of ADHD across developmental phases from childhood through adulthood. J Clin Psychiatry © Copyright 2012 Physicians Postgraduate Press, Inc. Submitted: October 8, 2010; accepted: November 2, 2011. Online ahead of print: January 10, 2012 (doi:10.4088/JCP.10m06628). † Deceased Corresponding author: David W. Goodman, MD, Johns Hopkins at Green Spring Station, 10751 Falls Rd, Ste 306, Lutherville, MD 21093 (dgoodma4@jhmi.edu).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.234
GPT teacher head0.468
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), 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

Citations202
Published2012
Admission routes1
Has abstractyes

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