Using qualitative Health Research methods to improve patient and public involvement and engagement in research
Notice bibliographique
Résumé
Plain English summary Patient engagement (or patient and public involvement) in health research is becoming a requirement for many health research funders, yet many researchers have little or no experience in engaging patients as partners as opposed to research subjects. Additionally, many patients have no experience providing input on the research design or acting as a decision-making partner on a research team. Several potential risks exist when patient engagement is done poorly, despite best intentions. Some of these risks are that: (1) patients’ involvement is merely tokenism (patients are involved but their suggestions have little influence on how research is conducted); (2) engaged patients do not represent the diversity of people affected by the research; and, (3) research outcomes lack relevance to patients’ lives and experiences. Qualitative health research (the collection and systematic analysis of non-quantitative data about peoples’ experiences of health or illness and the healthcare system) offers several approaches that can help to mitigate these risks. Several qualitative health research methods, when done well, can help research teams to: (1) accurately incorporate patients’ perspectives and experiences into the design and conduct of research; (2) engage diverse patient perspectives; and, (3) treat patients as equal and ongoing partners on the research team. This commentary presents several established qualitative health research methods that are relevant to patient engagement in research. The hope is that this paper will inspire readers to seek more information about qualitative health research, and consider how its established methods may help improve the quality and ethical conduct of patient engagement for health research. Abstract Background Research funders in several countries have posited a new vision for research that involves patients and the public as co-applicants for the funding, and as collaborative partners in decision-making at various stages and/or throughout the research process. Patient engagement (or patient and public involvement) in health research is presented as a more democratic approach that leads to research that is relevant to the lives of the people affected by its outcomes. What is missing from the recent proliferation of resources and publications detailing the practical aspects of patient engagement is a recognition of how existing research methods can inform patient engagement initiatives. Qualitative health research, for example, has established methods of collecting and analyzing non-quantitative data about individuals’ and communities’ lived experiences with health, illness and/or the healthcare system. Included in the paradigm of qualitative health research is participatory health research, which offers approaches to partnering with individuals and communities to design and conduct research that addresses their needs and priorities. Discussion The purpose of this commentary is to explore how qualitative health research methods can inform and support meaningful engagement with patients as partners. Specifically, this paper addresses issues of: rigour (how can patient engagement in research be done well?); representation (are the right patients being engaged?); and, reflexivity (is engagement being done in ways that are meaningful, ethical and equitable?). Various qualitative research methods are presented to increase the rigour found within patient engagement. Approaches to engage more diverse patient perspectives are presented to improve representation beyond the common practice of engaging only one or two patients. Reflexivity, or the practice of identifying and articulating how research processes and outcomes are constructed by the respective personal and professional experiences of researchers and patients, is presented to support the development of authentic, sustainable, equitable and meaningful engagement of patients as partners in health research. Conclusions Researchers will need to engage patients as stakeholders in order to satisfy the overlapping mandate in health policy, care and research for engaging patients as partners in decision-making. This paper presents several suggestions to ground patient engagement approaches in established research designs and methods.
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 | 0,277 | 0,372 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,007 | 0,012 |
| Communication savante | 0,012 | 0,009 |
| Science ouverte | 0,004 | 0,010 |
| Intégrité de la recherche | 0,004 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,002 |
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; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».