Comment on AO Spine Knowledge Forums Promote Collaboration and Elevate the Impact of Research: Bibliometric Analysis

To the Editor,

We read with interest the bibliometric study titled “AO Spine Knowledge Forums Promote Collaboration and Elevate the Impact of Research: Bibliometric analysis” by de Souza et al ¹ which provides a comprehensive evaluation of publication trends associated with the AO Spine Knowledge Forums (KFs). The authors are to be commended for their innovative approach in highlighting the role of formalized research networks in advancing spine research. However, several methodological aspects merit further scrutiny to strengthen the interpretability and reproducibility of their findings.

First, the study’s reliance on manual author identification through name-based Web of Science queries introduces significant risk for author misclassification. Over a 45-year period, variability in name formatting, institutional affiliations, and publication attributions could have resulted in both over-inclusion and underrepresentation of KF members’ publications. Incorporating persistent author identifiers such as ORCID iDs ² or leveraging algorithmic author disambiguation tools would enhance the accuracy and fidelity of author attribution, thereby improving the reliability of bibliometric comparisons.

Second, the study attributes increased scholarly productivity and collaboration to the formation of the KFs post-2010; however, the absence of a comparator group or time-series controls limits causal inference. Without accounting for secular trends in scientific publishing, academic maturation of researchers, or other systemic shifts (eg, increased international collaboration across fields), the observed associations may reflect temporal correlation rather than a direct organizational effect. Employing quasi-experimental designs, such as difference-in-differences analysis or matched cohort comparisons, would strengthen claims regarding the KF model’s unique impact. ³

Third, the presentation of statistical findings would benefit from enhanced rigor. While P-values and R² values are provided, the omission of confidence intervals constrains the interpretability of effect sizes and limits readers’ ability to assess the precision of estimates. Including 95% confidence intervals and sensitivity analyses would bolster statistical transparency and allow for more nuanced evaluation of the study’s claims regarding trends in collaboration and journal impact factor. ⁴

In conclusion, while de Souza et al ¹ provide an important model for evaluating the influence of collaborative research networks, addressing key methodological and statistical limitations in future studies will enhance the validity and generalizability of such bibliometric assessments.