When is data too old to inform nursing science and practice?
Notice bibliographique
Résumé
A long delay between research data collection and publication time can impede clinicians from having the most up-to-date information to inform their practice. This is concerning since an often-cited statistic states that it takes an average of 17 years for 14% of research evidence to be widely implemented into clinical practice (Westfall et al., 2007). Efforts to close the gap between evidence generation and practice change are, therefore, important. Given the rapid pace of change in health care, one wonders if older data are an appropriate foundation upon which to base innovation in patient care. When is data too old to have scientific and clinical relevance? Internationally, journals with a high impact factor scrutinize the timeliness or currency of data in manuscripts submitted for publication (Welsh et al., 2018). For example, the Journal of Advanced Nursing (JAN) specifies in its authorship guideline that the period of data collection should ideally be no more than 3 years before submission of the manuscript. However, should all data be judged with the same age lens? Should all nursing journals use the same 3-year cut-off? As journal editors, we recognize that this time restriction may be perceived as arbitrary. In this editorial, we aim to describe the rationale behind this development and offer considerations for those wishing to publish older data. Practice change cannot occur if clinicians are unaware of the research that has been performed. For research results to reach the widest possible audience, they should be published in an indexed journal, which increases the credibility and visibility of the work. JAN is committed to the advancement of evidence-based nursing, midwifery and healthcare by disseminating high-quality research and scholarship of contemporary relevance and with the potential to advance knowledge for practice. Understandably, the review process in which manuscripts are sent to academic referees who read them and produce a critical analysis is a formidable task. The academic reviews need to be collated and sent back to the authors for response and manuscript revision. This review process contributes to the quality and transparency of the research. However, it also adds time between research data collection and publication. Hence, selecting papers with a 3-year data cut-off may enhance the contemporary relevance of the findings for practice. The COVID-19 pandemic has emphasized the importance of data currency in international journals. The emergence of new diseases or healthcare delivery challenges can render prior research inadequate and, in many respects, outdated for informing clinical interventions. There is an urgent need for rapid accounts of practice at the point-of-care so that health stakeholders are appraised of the issues confronting patients, nurses and health systems. Research investment has responded to this, and other health challenges in recent years. For example, there has been a significant move towards greater collaboration between researchers, nurses, patients and family caregivers to address the needs identified as important by the community. Chalmers and Glasziou (2009) estimate that, despite growing human and financial investment, 85% of funding for health research is wasted in multiple ways including non-publication. Research that is not published in a timely manner may contribute to a ‘Groundhog Day’ effect, whereby questions already addressed may be unnecessarily reproduced (Hong et al., 2022). Therefore, delays in publishing data may increase the expense and overall burden of research including unnecessary use of limited grant funding, study participants' time and collaborator resources. Understandably, applying a 3-year cut-off may be experienced as a controversial or unwelcome development by some. Prioritizing newer data has been described as a sort of ‘ageism of knowledge’; valorizing the new may appear to communicate that older data have no relevance or usefulness (Gottlieb, 2003). This may disregard methodological strengths, unique data collection methods and innovative use of theory. Furthermore, this may leave investigators with a great deal of potentially useful but unpublished data. Restrictions to a 3-year data window may also ignore the common problem of inadequate time to complete data collection, analyse and publish the main findings before authors must write and obtain more funding, that is, a vicious cycle. Those in clinician–scientist or tenure track appointments may find themselves in this vexing circumstance. We encourage all researchers to pursue publication of their work, regardless of the age of their data. We contend that newer research data holds particular relevance for substantiating emerging issues and advancing clinical practice. However, older research may remain scientifically indispensable for defining where we have come from and envisioning where we need to go. Proactive methods to avoid research languishing in unpublished format may include drafting a manuscript template during data collection and analysis, distributing writing work among research team members, and targeting shorter manuscript formats (e.g. letters, reports, visual abstracts, etc.). As submission to an indexed journal can be a time-intensive process, considerations should first be given to the author guidelines to ensure the manuscript aligns with data currency requirements. Where it does not but the data is still useful, this should be addressed in a covering letter or a letter of enquiry to the journal. Attention should also be given to alternative routes for disseminating older data through institutional and open access repositories, where users can make research outputs available in a discoverable, citable and sharable manner. Timely movement of research data into publication is advantageous for a constantly evolving clinical practice context. JAN is committed to the identification and prompt dissemination of promising practices and critical thinking, which can have substantial positive impacts on nurses' abilities to meet the needs and expectations of patients, populations and health systems. Delays in publication are seen as a waste of scarce resources and add to the burden of research. It may not always be possible to publish within a 3-year window; however, authors should attempt to meet this expectation wherever possible. Where there has been an unavoidable delay, this can be addressed in the covering letter to the editors. Other routes to publication, particularly for manuscripts involving older data, exist and should be considered to maximize the scientific and clinical benefits of research. Editorials are opinion pieces. This piece has not been subject to peer review and the opinions expressed are those of the authors. Dale Craig and M. Logsdon are editors of JAN. None of the authors have relevant political or other affiliations to declare.
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 | 0,016 | 0,062 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,000 |
| Communication savante | 0,000 | 0,005 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,004 |
| 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 ».