Building capacity in patient-oriented research: reflections on cultivating relationships within a high-secure forensic mental health hospital
Notice bibliographique
Résumé
Building trusting relationships is critical to the success of patient-oriented research. However, in high-secure forensic mental health settings, distrust, discrimination, and restrictive practices pose unique barriers to building relationships. This commentary explores the challenges, strategies, and lessons learned in fostering meaningful connections with forensic patients at a high-secure hospital. Initially focused on assessing readiness to conduct patient-oriented research, the team pivoted to relationship building, guided by the mentorship of peer researchers and patient advocates. Navigating institutional complexities, the team adopted a patient-centered approach informed by the principles of respect and human connection. Key strategies included shadowing experienced patient advocates embedded within the hospital, attending patient community meetings, and engaging in informal interactions with patients. These efforts enabled the team to move from observing interactions to engaging in patients’ daily lives through shared experiences. A major milestone was the successful planning and execution of a knowledge sharing event that brought together patients, staff, researchers, and external stakeholders to explore how to put patient-oriented research approaches into practice. Despite the progress, the team faced many challenges, including skepticism from staff and patients, and disruptions inherent to a high-secure environment. The commentary discusses critical lessons for overcoming these challenges, including the importance of patience, adaptability, and respecting boundaries. It emphasizes the intrinsic value of building relationships beyond research outcomes and advocates for incorporating diverse team expertise to foster trust and authentic connections. The commentary also highlights the perspectives of a current forensic patient and co-author, who shares how the team’s efforts made him feel valued as a person. His reflections add to the narrative by highlighting the impact of respectful interactions on relationships. By sharing these insights, this commentary aims to inspire other research teams to prioritize relationship building as a foundational step toward meaningful participatory research in forensic mental health care. Building trust is important for patient-oriented research, but it can be especially hard in high-secure forensic mental health hospitals. Distrust, discrimination, and strict rules make it hard to form connections. This article explores the challenges and strategies of a research team in building relationships with patients in a high-secure hospital. The team started by looking at whether hospital staff and patients were ready for patient-oriented research but quickly realized that building relationships should be a first step. They worked with peer researchers, patient advocates, and mentors to focus on respect and human connection. They learned from patient advocates, attended patient meetings, and talked informally with patients. Over time, they became more involved in patients’ daily lives. One important moment was an event where patients, staff, and researchers gathered to discuss how patient-oriented research can be done at the hospital. The team still faced challenges, like distrust from staff and patients, as well as disruptions in the hospital. They learned to be patient, flexible, and to respect boundaries. Building trust and real connections helped them go beyond just research goals. A patient who helped write this article shared how the team made him feel valued as a person, not just a patient. By sharing these experiences, the article hopes to encourage other researchers to focus on building relationships in forensic patient-oriented 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 | 0,028 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,012 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,026 |
| 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 ».