Lessons learned in practice-based research: Studying language interventions for young children in the real world
Notice bibliographique
Résumé
Background and aims Practice-based research holds potential as a promising solution to closing the research-practice gap, because it addresses research questions based on problems that arise in clinical practice and tests whether systems and interventions are effective and sustainable in a clinical setting. One type of practice-based research involves capturing practice by collecting evidence within clinical settings to evaluate the effectiveness of current practices. Here, we describe our collaboration between researchers and clinicians that sought to answer clinician-driven questions about community-based language interventions for young children (Are our interventions effective? What predicts response to our interventions?) and to address questions about the characteristics, strengths, and challenges of engaging in practice-based research. Methods We performed a retrospective chart review of 59 young children who had participated in three group language interventions at one publicly funded community clinic between 2012 and 2017. Change on the Focus on the Outcomes of Communication Under Six (FOCUS), a government mandated communicative participation measure, was extracted as the main outcome measure. Potential predictors of growth during intervention were also extracted from the charts, including type of intervention received, attendance, age at the start of intervention, functional communication ability pre-intervention, and time between pre- and post-intervention FOCUS scores. Results Overall, 49% of children demonstrated meaningful clinical change on the FOCUS after their participation in the language groups. Only 3% of participants showed possibly meaningful clinical change, while the remaining 46% of participants demonstrated not likely meaningful clinical change. There were no significant predictors of communicative participation growth during intervention. Conclusions Using a practice-based research approach aimed at capturing current practice, we were able to answer questions about the effectiveness of interventions delivered in real-world settings and learn about factors that do not appear to influence growth during these interventions. We also learned about benefits associated with engaging in practice-based research, including high clinical motivation, high external validity, and minimal time/cost investment. Challenges identified were helpful in informing our future efforts to examine other possible predictors through development of a new, clinically feasible checklist, and to pursue methods for improving collection of outcome data in the clinical setting. Implications: Clinicians and researchers can successfully collaborate to answer clinically informed research questions while considering realistic clinical practice and using research-informed methods and principles. Practice-based research partnerships between researchers and clinicians are both valuable and feasible.
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 | 0,117 | 0,198 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,006 | 0,015 |
| Communication savante | 0,014 | 0,013 |
| Science ouverte | 0,005 | 0,007 |
| Intégrité de la recherche | 0,004 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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.
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 ».