Authorship, titles and open access as drivers of citation performance in orthopaedics: a scientometric analysis - Journal of Orthopaedics and Traumatology

Background Bibliometric analyses are increasingly used to explore how scientific knowledge is created, disseminated, and perceived. In orthopaedics, research output has expanded rapidly over the past decade, yet the factors determining whether an article achieves wide visibility and scholarly impact remain poorly understood. Beyond the inherent quality of a study, elements such as authorship patterns, title construction, and open access (OA) availability may play an essential role in shaping citation performance. However, evidence in this field is still limited and sometimes contradictory, highlighting the need for large-scale, field-specific analyses. Methods Orthopaedic publications from 2010 to 2020 were identified in Scopus using the keyword ‘orthopaedic’. After duplicate removal, 97,806 unique articles were included with complete data on authorship, titles, citation counts, study design, and OA status. Citation rates were normalised per year since publication. Associations between bibliographic features and citation performance were assessed using multiple linear regression, while differences across title styles and study designs were evaluated with comparative statistical testing. Exploratory modelling was performed to identify combinations of authorship and title characteristics linked to the highest predicted citation rates. Results Larger author teams were associated with higher citation rates (β = 0.108 citations/year per additional author, 95% confidence interval [CI] 0.103–0.114, p < 0.001). OA articles achieved a mean increase of 0.175 citations/year compared with non-OA (p = 0.001). Title length in characters correlated positively with citation rate (β = 0.023 per character, p < 0.001), whereas title length in words showed a negative association (β = −0.183 per word, p < 0.001). The presence of a colon (+0.314 citations/year, p < 0.001) or dash (+0.187, p = 0.001) increased citation performance, while question marks (−0.476, p < 0.001) and all-capital titles (mean 0.71 citations/year) reduced it. Regarding study design, network meta-analyses achieved the highest citation rate (mean 6.64 citations/year), followed by systematic reviews (5.66), meta-analyses (5.08) and narrative reviews (4.81). Randomised controlled trials (3.90) and clinical trials (3.86) performed at an intermediate level, whereas observational studies (2.40), case series (1.79), technical notes (1.33), case reports (0.77), editorials (0.51) and commentaries (0.25) showed consistently lower citation performance (p < 0.0001). Conclusions In orthopaedic research, collaboration, OA availability and concise, well-structured titles with selected punctuation contribute to higher citation performance, while unconventional title formatting reduces visibility. Although useful for optimising dissemination, ethical authorship practices and rigorous scientific standards remain more critical than citation metrics.

A two-stage model for factors influencing citation counts

This work aims to study a count response random variable, the number of citations of a research paper, affected by some explanatory variables through a suitable regression model. Due to the fact that the count variable exhibits substantial variation since the sample variance is larger than the sample mean, the classical Poisson regression model seems not to be appropriate. We concentrate attention on the negative binomial regression model, which allows the variance of each measurement to be a function of its predicted value. Nevertheless, the process of citations of papers may be divided into two parts. In the first stage, the paper has no citations, and the second part provides the intensity of the citations. A hurdle model for separating the documents with citations and those without citations is considered. The dataset for the empirical application consisted of 43,190 research papers in the field of Economics and Business from 2014-2021, obtained from The Lens database. Citation counts and social attention scores for each article were gathered from Altmetric database. The main findings indicate that both collaboration and funding have a positive impact on citation counts and reduce the likelihood of receiving zero citations. Higher journal impact factors lead to higher citation counts, while lower peer review ratings lead to fewer citations and a higher probability of zero citations. Mentions in news, blogs, and social media have varying but generally limited effects on citation counts. Open access via repositories (green OA) correlates with higher citation counts and a lower probability of zero citations. In contrast, OA via the publisher's website without an explicit open license (bronze OA) is associated with higher citation counts but also with a higher probability of zero citations.

A year in review – evaluating the launch of IJTLD OPEN: Ingenta Connect

Does Open Access Foster Interdisciplinary Citation? Decomposing Open Access Citation Advantage

The existence of an open access (OA) citation advantage, that is, whether OA increases citations, has been a topic of interest for many years. Although numerous previous studies have focused on whether OA increases citations, expectations for OA go beyond that. One such expectation is the promotion of knowledge transfer across various fields. This study aimed to clarify whether OA, especially gold OA, increases interdisciplinary citations in various natural science fields. Specifically, we measured the effect of OA on interdisciplinary and within-discipline citation counts by decomposing an existing metric of the OA citation advantage. The results revealed that OA increases both interdisciplinary and within-discipline citations in many fields and increases only interdisciplinary citations in chemistry, computer science, and clinical medicine. Among these fields, clinical medicine tends to obtain more interdisciplinary citations without being influenced by specific journals or papers. The findings indicate that OA fosters knowledge transfer to different fields, which extends our understanding of its effects.

An analysis of the effects of sharing research data, code, and preprints on citations

Calls to make scientific research more open have gained traction with a range of societal stakeholders. Open Science practices include but are not limited to the early sharing of results via preprints and openly sharing outputs such as data and code to make research more reproducible and extensible. Existing evidence shows that adopting Open Science practices has effects in several domains. In this study, we investigate whether adopting one or more Open Science practices leads to significantly higher citations for an associated publication, which is one form of academic impact. We use a novel dataset known as Open Science Indicators, produced by PLOS and DataSeer, which includes all PLOS publications from 2018 to 2023 as well as a comparison group sampled from the PMC Open Access Subset. In total, we analyze circa 122’000 publications. We calculate publication and author-level citation indicators and use a broad set of control variables to isolate the effect of Open Science Indicators on received citations. We show that Open Science practices are adopted to different degrees across scientific disciplines. We find that the early release of a publication as a preprint correlates with a significant positive citation advantage of about 20.2% (±.7) on average. We also find that sharing data in an online repository correlates with a smaller yet still positive citation advantage of 4.3% (±.8) on average. However, we do not find a significant citation advantage for sharing code. Further research is needed on additional or alternative measures of impact beyond citations. Our results are likely to be of interest to researchers, as well as publishers, research funders, and policymakers.