Proposal and Strategy for Nursing-Led Research: Protocol for an Unfunded Clinical Trial
Notice bibliographique
Résumé
BACKGROUND: Clinical trials are known to provide cause-and-effect results and data with low levels of bias. However, a lack of funding for clinical trials, which are considered expensive, means that academic sponsors are rarely able to conduct them. Academic trials are considered highly relevant for the valuable results they provide for clinical questions. This is why initiatives to conduct unfunded clinical trials have been identified as an important issue to pay attention to in future studies. Therefore, we present our initiative through Rogers' theory, which is highlighted in the literature for diffusing innovative change across organizations. OBJECTIVE: The purpose of this paper was to describe our case regarding management for conducting a nonfunded nurse-led clinical trial based on our previous low-interventional clinical trial across a specific health organization and with nurses. METHODS: We conducted a low-intervention, nonexternally funded clinical trial using the human and material resources available on site. We managed our trial in a clinical trial unit where there were staff, sources, and ongoing commercial clinical trials. We conducted our trial based on an ongoing commercial trial, and, to do so, we needed behavioral changes. We relied on Rogers' theory, and we identified strengths and barriers to change by analyzing actors' characteristics, perceptions of the situation, motivation, and information. Afterward, we divided the staff according to their characteristics related to innovation and change into permanent staff (research staff with a culture of change) and nonpermanent staff (nursing staff with occasional attendance and resistance to change). First, we preselected only those nurses who were more aware of change (innovators and pioneers) to participate in our trial to avoid a massive rejection, and later, we asked others to join (late adopters). We followed Rogers' phases. For research staff who were aware of the funding, we focused on the "persuasion phase," while for nursing staff, we mixed the "knowledge and persuasion phases" and used pioneers and early adopters as a positive example for other nurses as well as nonfinancial incentives (persuasion). Our trial consisted of different methods of vein cannulation, which was performed in the ongoing commercial trial. Thus, the entire development of our low-interventional clinical trial was conducted without interfering at any point with the parallel commercial clinical trial. RESULTS: Our management allowed effective conduct of our study, and we met our aims without external funding and without ethical impact during the commercial clinical trial. Costs remained low, primarily because the major expenses were covered by the commercial clinical trial as an inherent part of its design. CONCLUSIONS: Our initiative to conduct a low-intervention clinical trial with no or limited funding was cost-effective. This initiative can be used by researchers with valuable academic research questions who do not have the external funding to conduct studies. TRIAL REGISTRATION: ClinicalTrials.gov NCT04027218; https://clinicaltrials.gov/study/NCT04027218. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/56062.
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 | 0,275 | 0,289 |
| Méta-épidémiologie (sens strict) | 0,005 | 0,004 |
| Méta-épidémiologie (sens large) | 0,005 | 0,006 |
| Bibliométrie | 0,008 | 0,006 |
| Études des sciences et des technologies | 0,008 | 0,008 |
| Communication savante | 0,009 | 0,009 |
| Science ouverte | 0,006 | 0,008 |
| Intégrité de la recherche | 0,020 | 0,023 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,115 | 0,054 |
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 source (Gemma direct ou Codex distillé), 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 ».