Reporting health research translation and impact in the curriculum vitae: a survey
Notice bibliographique
Résumé
BACKGROUND: Increasingly, health researchers must demonstrate the impact and real-life applications of their research. We investigated how health researchers with expertise in knowledge translation report research translation activities and impact on their curriculum vitae (CV). METHODS: We conducted a cross-sectional survey of health researchers with expertise in knowledge translation as we anticipated best practices in CV reporting from this specialized group. Our survey asked participants about their reporting of research translation and impact activities on their CVs, intention to report, and barriers and facilitators to reporting such activities on their CVs. We calculated univariate descriptive statistics for all quantitative data. Linear regression models determined predictors of researchers' intention to report research translation and impact activities on their CVs. We analyzed open-ended qualitative responses using content analysis. RESULTS: One hundred and fifty-three health researchers responded to the survey (response rate = 29%). Most respondents were Canadian, were female, and had a doctoral degree. Eighty-two percent indicated they reported at least one research translation and/or impact indicator on their CVs. Of those, health researchers commonly reported the following: advisory/regulatory committee membership related to research program (83%), research translation award(s) (61%), and academic performance assessments (59%). Researchers least commonly indicated the following: citation metric scores (31%), summaries of impact (21%), and requests to use research materials and/or products (19%). Fewer than half of the health researchers intended to report knowledge translation (43%) and impact (33%) on their CVs. Strong beliefs about capabilities and consequences of reporting research translation and/or impact were significant predictors of intention. Main barriers were as follows: CV templates do not include research translation and impact activities, participants perceived employers do not value research translation and impact activities, and lack of metrics to evaluate research translation and impact. Ninety-six percent were unaware of a CV template formatted to include research translation and/or impact reporting. CONCLUSIONS: Knowledge translation and impact indicators on the CV are inconsistently reported by our sample of health researchers. Modifiable barriers should be addressed to support more consistent reporting of such activities, including providing a CV template that includes research translation and impact as well as clear metrics to quantify them.
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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 | 0,092 | 0,234 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,006 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».