MétaCan
Menu
← Retour à la cohorte
Enregistrement W324429764 · doi:10.1177/070674371205701001

Treating Psychopathology in Adults with Developmental Disabilities: Glass Half Empty or Half Full?

2012· editorial· en· W324429764 sur OpenAlexvenueno aff
Luc Lecavalier

Notice bibliographique

RevueThe Canadian Journal of Psychiatry · 2012
Typeeditorial
Langueen
DomaineNeuroscience
ThématiqueAutism Spectrum Disorder Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPsychologyPsychopathologyPsychiatryComorbidityIntellectual disabilityAutismPervasive developmental disorderAutism spectrum disorderClinical psychology

Résumé

récupéré en direct d'OpenAlex

Abbreviations ADHD attention-deficit hyperactivity disorder ASD autism spectrum disorder DD developmental disability DR differential reinforcement ID intellectual disability It has long been known that behaviour and emotional problems occur at high rates in people with IDs and DDs.1 It is also well established that these problems can start at an early age and persist throughout the lifespan.2,3 Behaviour and emotional problems are costly to society and may ostracize people and their caregivers, clearly a countercurrent to the present Zeitgeist of inclusion. These problems can be quite stressful and dangerous for caregivers. For these reasons, psychopathology has long been, and continues to be, one of the central issues of DDs. The 2 comprehensive reviews45 provide an accurate depiction of the present state of affairs in IDs and ASD. In the first review, Dr Johnny L Matson and colleagues4 discuss discrepancies between clinical realities and best evidence practice. My own experience converges with these observations: psychiatric diagnoses are misunderstood and behavioural technologies are underused. Why is it so? An obvious explanation for the diagnostic challenges is that self-report is of limited value in many people with DDs, who, by definition, have impaired insight and communication skills. Until new technologies are developed, caregiver observations will be at the forefront of diagnostic endeavours. Numerous rating instruments have been developed but the gold standard continues to remain elusive. As a result, fundamental issues, such as phenomenology, prevalence, comorbidity, and course of psychopathology, are not well understood. This measurement problem impacts the possibility of replicating findings, which is at the heart of scientific progress. Simply put, we do not know to what extent intellectual deficits or ASD alter the typical clinical presentation of psychiatric syndromes. In many ways, diagnostic difficulties are inherent to DDs, especially in lower-functioning people. Suboptimal use of behavioural technology is a different story. Functional assessments are not used as much as they should be. Treatment decisions are often not data-driven. We can reflect on these issues in terms of efficacy and effectiveness. Efficacious treatments are those that prove beneficial for patients in well-controlled treatment studies. Effectiveness entai Is showing that efficacious treatment can be transported from the research setting to the community where there is more variation in subject selection and treatment implementation. No serious scientist would argue against the validity of operant conditioning. It is the short-term cost and practicalities that hamper optimal use of many behavioural methods. One of the biggest challenges to applied behavioural interventionists is undoubtedly the transfer of technology in a world with increased regulations and financial constraints and high staff burnout and turnover. In the second review, Dr Peter Sturmey5 provides a synthesis of the treatment literature in DDs. The review shows that there are many publications on the topic. Conversely, it indicates that the available evidence for treatments is quite limited. Of course, a distinction must be made between ineffective or harmful treatments and those that are not currently supported by enough quality research. Most (but not all) applied researchers would agree that rigorous treatment studies entail randomization, comparison to alternative treatments, blind evaluations, standardized outcome measures, standardized doses, and a large enough sample size for meaningful analyses and generalization of results.6,7 I sadly agree that there are too few methodologically robust studies of DDs. Why is it so? An obvious observation is that only a small proportion of the population has a DD, which makes study recruitment a serious obstacle. Imagine the researcher who wants to study the safety and efficacy of an alpha agonist on hyperactivity and aggression in adults with ASD. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,012
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,007
Score d'incertitude au seuil0,025

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,012
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0020,004
Science ouverte0,0010,002
Intégrité de la recherche0,0030,004
Charge utile insuffisante (le modèle a refusé de juger)0,0070,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,018
Tête enseignante GPT0,284
Écart entre enseignants0,265 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2012
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueThe Canadian Journal of Psychiatry→Même sujetAutism Spectrum Disorder Research→Travaux en français237 207→