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Enregistrement W2018641536 · doi:10.1111/j.1469-8749.2009.03397.x

Evaluating participation in children and young people with cerebral palsy

2009· letter· en· W2018641536 sur OpenAlexaboutno aff
Susan Ishøy Michelsen

Notice bibliographique

RevueDevelopmental Medicine & Child Neurology · 2009
Typeletter
Langueen
DomaineMedicine
ThématiqueCerebral Palsy and Movement Disorders
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCerebral palsyInternational Classification of Functioning, Disability and HealthQuality of life (healthcare)PsychologyGross Motor Function Classification SystemRecallTypically developingGross motor skillYoung adultDevelopmental psychologyMotor skillRehabilitationPsychiatryAutism

Résumé

récupéré en direct d'OpenAlex

Parents of children and young people with disabilities want, like all parents, a happy and meaningful life for their children. This means a high subjective quality of life and participation, defined in the International Classification of Functioning, Disability and Health (ICF) as 'involvement in life situations'. Society also seeks participation for citizens as expressed in two United Nations conventions on the rights of children and rights of persons with disabilities: children with disabilities are entitled to a life with equal opportunities to participate in family and societal life, like other children.1,2 Orlin et al. report the effects of age and gross motor function on participation of children and young people with cerebral palsy (CP) in the USA.3 The Canadian instrument Children's Assessment of Participation and Enjoyment (CAPE) was completed by 42% of the children or young people themselves, with the help of computer and pictures if needed. The remaining questionnaires were partly or entirely completed by parents. As children as young as 6 years reported how often, where, and with whom they participated in various activities during the last 4 months, there is likely to be some inaccurate recall. The authors categorized the participants by age (children 6–12y and young people 13–21y) and severity of motor impairment (Gross Motor Function Classification System levels I–V). Consistent with the literature, and as expected by the authors, participation decreases with increasing severity of motor impairment, implying that motor impairment is not fully compensated for. Orlin et al. specifically discuss participation in physical activities and its relevance for health and fitness in children and young people with severe motor impairments. Full participation in sport may need personal help, aids, or adaptations – in other words environmental adjustment. A recent study reveals large regional variation in participation of children with CP and suggests this might be explained by cross-country differences in provision of optimal environments.4 Rates of participation in physical activities in children and young people with CP are regarded as low by the authors. But do they mean low compared with what the children need or compared with children without disabilities? They found 14% of young people with CP did not participate in any physical activities; however, in a large survey of young people in the USA5, 25% of young people without disability did not participate in at least 60 minutes of physical activity over the preceding 7 days. These numbers are not comparable, but they confirm that even children without disabilities have low rates of physical activity. We do not know if the reasons for not taking part in physical activity are the same in the two groups. In planning health promotion it is valuable to know the reasons for non-participation and Orlin et al. suggest qualitative studies are needed to explore the thoughts behind the choices children make. Comparison of the participation of children with that of young people revealed a mixed pattern. As expected by the authors, children had higher overall participation and higher participation in recreational activities compared with young people. Young people were predicted to have higher participation in social activities but in fact did not. As mentioned by the authors, this may be related to characteristics of the CAPE which includes more activities appropriate for children than for young people. The concept of participation remains difficult to articulate in a manner which can be measured. Also, children will have a subjective view about their participation and there is debate about whether this should be captured as part of participation or reflected in a quality of life instrument. In the ICF, participation can be qualified by 'capacity' (what a child can do in an ideal environment) and 'performance' (what a child actually does in the environment in which they live). Differences between capacity and performance, according to the ICF, are due to environmental or personal factors. One such personal factor is choice and, as recently discussed by Morris,6 it is important to consider such personal factors if we are to respect an individual's right to choose their activities. Since individual choices will vary between activities, it may be relevant to measure choice or preference at the same time as participation, whilst realizing its subjective nature. CAPE has a companion measure called Preferences for Activities of Children where preferences are assessed. It remains a challenge to develop measures which capture the essence of participation and then to use them in clinical settings and in societal evaluations of children and young people with CP and other disabilities.

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)0,003
score de la tête « metaresearch » (Gemma)0,006
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,020
Score d'incertitude au seuil0,039

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,006
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0010,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,019
Tête enseignante GPT0,290
Écart entre enseignants0,271 · 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'étudeObservationnel
Domainenon disponible
GenreEmpirique

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

En bref

Citations4
Publié2009
Routes d'admission1
Résumé présentoui

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