Bridging the divide: supporting and mentoring trainees to conceptualize, plan, and integrate engagement of people with lived experience in health research
Notice bibliographique
Résumé
Health researchers are encouraged by governments, funders, and journals to conduct research in partnership with people with lived experience. However, conducting research with authentic engagement and partnership with those who are experts by experience, but may not have research methods training, requires resources and specialized skills. The McMaster Collaborative for Health and Aging developed a fellowship program for trainees that builds their capacity to conduct research in partnership with older adults with relevant lived experience. We share this case example, with its successes and challenges, to encourage creative reformation of traditional research training. The Collaborative used an iterative design process, involving researchers, trainees and older adult and caregiver partners, who, together, developed a fellowship program for trainees that provides support and mentorship to plan and conduct health research in partnership with people with lived experience. Since 2022, the Partnership in Research Fellowship has been offered biannually. The application process was purposefully designed to be both constructive and supportive. Opportunities for one-on-one consultations; key resources, including a guide for developing a plan to involve people with relevant lived experience; and feedback from older adult and researcher reviewers are provided to all applicants. Successful trainees engage with older adult and caregiver partners from the Collaborative to advance and enhance a range of skills from facilitating partner meetings to forming advisory committees. Trainees are awarded $1500 CAD to foster reciprocal partnerships. Ten graduate students from various disciplines have participated. Trainees reported positive impacts on their knowledge, comfort, and approach to partnered research. However, the time required for undertaking partnered research activities and involving diverse partners remain obstacles to meaningful engagement. Partnering with people with lived experience in the design of educational programs embeds the principles of partnership and can increase the value and reward for all involved. We share the Partnership in Research Fellowship as a case example to inspire new and transformative approaches in research training and mentorship that will move the field forward from engagement theory to meaningful enactment. Health researchers are encouraged by governments, funders, and journals to conduct research in partnership with individuals with relevant health conditions or experience. However, conducting research with individuals who are experts by experience, but may not have research training, requires resources and specialized skills. The McMaster Collaborative for Health and Aging developed a fellowship program to support and mentor trainees to conduct their research in partnership with people with lived experience and turn engagement theory into action. The Collaborative involved researchers, trainees, and older adults in the development of the fellowship program. Since 2022, the Partnership in Research Fellowship has been offered twice a year. The application process was designed to be both supportive and informative. Opportunities for one-on-one consultations; key resources, including guiding questions to consider when planning to involve people with relevant lived experience; and feedback from older adults and researchers, are provided to all applicants. Each trainee receives $1500 CAD to support building strong, two-way partnerships. Since the fellowship’s launch, 10 graduate students from different fields have participated. Trainees reported improvements in their knowledge and comfort to partner with people with lived experience in research. However, challenges, such as the extra time needed for conducting partnered research as well as locating and involving those from diverse backgrounds, were identified. Involving people with lived experience in the design of research training incorporates partnership principles and may enhance the benefits and satisfaction for everyone involved. We share the Partnership in Research Fellowship, as an example, to inspire new approaches in research training and mentorship.
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 | 0,041 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».