Evolving partnerships: engagement methods in an established health services research team
Notice bibliographique
Résumé
BACKGROUND: The Translating Research in Elder Care (TREC) program is a partnered health services research team that aims to improve the quality of care and quality of life for residents and quality of worklife for staff in nursing homes. This team includes academic researchers, trainees, research staff, citizens (persons living with dementia and family/friend caregivers of persons living in nursing homes), and decision-makers (ministries of health, health authorities, operators of nursing homes). The TREC team has experience working with health system partners but wanted to undertake activities to enhance the collaboration between the academic researchers and citizen members. The aim of this paper is to describe the TREC team members' experiences and perceptions of citizen engagement and identify necessary supports to promote meaningful engagement in health research teams. METHODS: We administered two online surveys (May 2018, July 2019) to all TREC team members (researchers, trainees, staff, decision-makers, citizens). The surveys included closed and open-ended questions guided by regional and international measures of engagement and related to respondents' experience with citizen engagement, their perceptions of the benefits and challenges of citizen engagement, and their needs for training and other tools to support engagement. We analyzed the closed-ended responses using descriptive statistics. RESULTS: We had a 78% response rate (68/87) to the baseline survey, and 27% response rate (21/77) to the follow-up survey. At baseline, 30 (44%) of respondents reported they were currently engaged in a research project with citizen partners compared to 11(52%) in the follow-up survey. Nearly half (10(48%)) of the respondents in the follow-up reported an increase in citizen engagement over the previous year. Respondents identified many benefits to citizen engagement (unique perspectives, assistance with dissemination) and challenges (the need for specific communication skills, meeting organizing and facilitation, and financial/budget support), with little change between the two time points. Respondents reported that the amount of citizen engagement in their research (or related projects) had increased or stayed the same. CONCLUSIONS: Despite increasing recognition of the benefits of including persons with lived experience and large-scale promotion efforts, the research team still lack sufficient training and resources to engage non-academic partners. Our research identified specific areas that could be addressed to improve the engagement of citizens in health research.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,112 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,006 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
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 tête enseignante, 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 ».