G45(P) Severe neurological impairment: towards an international consensus-based definition
Notice bibliographique
Résumé
Aims Following a thorough review of the literature, we have found significant inconsistency in the use of the term Severe Neurological Impairment (SNI) in the literature. We aimed to develop an international, consensus-based, multi-disciplinary definition of this term. Methods The Delphi process was chosen to achieve consensus on the definition of SNI. We collaborated with experts in 5 countries (Ireland, the UK, the USA, Canada and Australia) to disseminate an invitation to other colleagues in neurodisability in their own region. We specified that a multi-disciplinary panel was required. Those who wished to participate were asked to email us, as facilitators of the process, to confirm their desire to take part. Participants were asked to further disseminate the invitation to other colleagues, thus employing a snow-balling effect in the recruitment of expert panellists. The Delphi process proceeded over 3 rounds. Round 1 used free-text responses where panellists provided insight into their understanding of the term SNI. Responses were used to generate themes. In rounds 2 and 3 panellists were asked to rate their agreement with these themes in the definition of SNI. In the process of round 3 participants were provided with feedback on the previous round, including anonymous information on how the other panellists had voted as well as selected written feedback to provide an opportunity to consider other points of view. Items were brought forward to the final definition if they received more than 70% agreement, in line with accepted Delphi methodology. After round 3, a working definition of SNI was created. Further refinements were made based on comments from parent representatives and experts at an international conference. Results Thirty-four multi-disciplinary panellists participated in round 1 of the process falling to 31 in round 3, a 9% drop-out rate. Fifteen themes were generated from responses in round 1. Seven items were brought forward for inclusion in the final definition. Conclusion We have created an international, multi-disciplinary, consensus-based definition of SNI. This definition can be used to improve consistency in reporting of research, ultimately leading to improved outcomes for this unique and vulnerable cohort of children.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,108 | 0,154 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,009 |
| Communication savante | 0,006 | 0,007 |
| Science ouverte | 0,004 | 0,012 |
| Intégrité de la recherche | 0,007 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,003 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».