Establishment of a patient and public involvement and engagement group to support clinical trials in Pakistan: Initial lessons learned
Notice bibliographique
Résumé
Patient and public involvement and engagement (PPIE) in clinical trials is increasingly recognized as vital for ensuring research relevance and accessibility. Despite its proven benefits, PPIE remains limited, particularly in low- and middle-income countries, and more examples of effective strategies for involvement are needed. This commentary outlines the establishment of a PPIE group for clinical trials in a lower-middle-income country setting with limited research infrastructure. We established Pakistan’s first ever PPIE group for clinical trials within a new clinical trials unit at Ziauddin University in Karachi. The objectives of our project were focused on group formation, redesign of informed consent documents for trials, and dissemination of trial results to the public. Recruitment strategies involved referrals from clinicians and existing collaborators as well as engagement at public events, distribution of advertising leaflets and social media posts. Ten potential members were selected based on motivation, commitment and ability to contribute critically, with six members continuing their involvement long-term. An existing tool designed to establish the access needs of public partners was adapted to our project to help us document and account for members’ expectations and support requirements. The process of using the tool enabled deep engagement, clarified roles, and fostered trust between coordinators and group members. Patient and public members gained confidence about the legitimacy of the project and felt more comfortable participating in the first group meeting. Lessons learned emphasize the importance of wide-ranging engagement efforts and transparent discussions about expectations to build effective collaborative relationships. Our experience demonstrates the feasibility of establishing a PPIE group for clinical trials in Pakistan and highlights strong public interest for research involvement. The use of a formal tool to document needs, prior experiences and expectations encouraged relationship-building and helped coordinators make relevant accommodations for members. This account contributes to the growing body of literature on effective PPIE practices, emphasizing the value of tailored support and transparent communication in facilitating meaningful public involvement in clinical trials. Working together with patients and members of the public has the potential of making clinical trials better, more person-centered and relevant. Unfortunately, partnerships between trial researchers and the public are still uncommon. It is not known what the best ways are to involve the public in clinical trials, especially when it comes to non-Western populations. We set up the first-ever patient and public involvement and engagement group to support clinical trials in Pakistan. In this commentary, we share our initial experiences of successfully establishing the group and the two main lessons we learned. Ten group members were identified by widely advertising our project to doctors, community organizations, patients and their carers at our hospital. Before the first group meeting, two coordinators met with each potential member to discuss and document their interests, expectations and needs. Both researchers and group members felt that these discussions were a good use of their time and helped make the project a success. The first main lesson learned from our experience was that enough time, funding, staff and resources are needed to identify members and build meaningful collaborative partnerships. The second main lesson learned was that honest discussions are needed at the very beginning of a collaboration about expectations. Our experience shows that involving patients and members of the public in clinical trials in Pakistan is possible and we hope it inspires and helps other researchers in their patient and public engagement efforts.
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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 | 0,106 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,000 |
| Bibliométrie | 0,003 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,005 |
| Intégrité de la recherche | 0,001 | 0,010 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».