Bibliographic record
Abstract
Last January, we launched volume 22 with an editorial recounting a year full of publication highlights for the journal in 2023.1 At the time, it seemed unlikely that we could match these accomplishments in 2024, but in hindsight, we should have known better. This past year included multiple new and continued initiatives, not to mention more than 2600 journal pages, focused on evidence synthesis and evidence-based health care. We concluded last year’s editorial with a teaser: 2024 would introduce the JBI Evidence Synthesis Impact Award presented to the authors of the systematic review published the previous year with the most potential to impact health care policy or practice.1 The winners of the inaugural award were the authors of the review “Effect of dexamethasone administration for postoperative nausea and vomiting prophylaxis on glucose levels in adults with diabetes undergoing elective surgery: a systematic review with meta-analysis.”2 Members of the editorial office and the editorial advisory board were pleased to present the award at the 2024 Global Evidence Summit in Prague in September.3 Details about the award eligibility criteria and selection process can be found on the journal website: https://journals.lww.com/jbisrir/Pages/Impact_Award.aspx. In issue 3, JBI Evidence Synthesis featured a selection of methodology-themed papers to coincide with what is now JBI’s annual Methodology Month in March. As in years past, this issue focused on methodological guidance for conducting evidence syntheses. Of particular note were the additions to our Risk of Bias series, including the revised JBI critical appraisal tool for assessing risk of bias in quasi-experimental studies,4 along with an accompanying paper summarizing the different tool structures and approaches to risk of bias assessment.5 This issue also included a paper from members of the JBI Adelaide GRADE Centre with a comprehensive explanation of which JBI methodologies are suitable for GRADE assessment and how to apply the GRADE approach in a JBI systematic review.6 In a response to a commentary on redundant systematic reviews,7 the senior editors of JBI Evidence Synthesis shared their thoughts on how to address the proliferation of “zombie reviews,” the term bestowed on protocols or registrations that are abandoned without a complete review.8 To survive the apocalypse of zombie reviews, the editors offered a comprehensive list of steps the evidence synthesis community should take, many of which are already embedded in our journal’s practices. To conclude the many highlights from Methodology Month, we published a pilot study mapping the alignment of publications in JBI Evidence Synthesis to the United Nations Sustainable Development Goal (SDG) 3, which relates to global health and well-being.9 This 2-part study included a desktop audit of published systematic and scoping reviews and an author survey.9 Tracking authors’ awareness of the SDGs and their intention to use them in their synthesis work is an important step toward helping the JBI Collaboration meet the SDG targets by producing locally contextualized evidence. Moving forward to issue 6, leaders from JBI, the Campbell Collaboration, and Cochrane coauthored an editorial expressing their commitment to deeper collaboration, more coordinated approaches, and meaningful partnerships to advance evidence-based practice and achieve better results for individuals and communities.10 As a global organization, JBI recognizes the value of collaboration across the evidence ecosystem. Working together across various contexts is essential, as by its very nature, evidence-based decision-making requires involvement of researchers, policymakers, health providers, and consumers at both local and global levels. This was further emphasized by the commitment between the 3 organizations to develop the Building a Global Evidence Synthesis Community initiative for collaborative efforts, which was also introduced during the Global Evidence Summit in Prague. Some of the other content featured in the journal last year included a 2-part scoping review from a team of authors in Canada who reported on the legal and ethical aspects of organ donation following medical assistance in dying (MAiD), as well as the existing processes and procedures.11,12 In 2016, Canada became the first country to legalize MAiD. Since then, several more countries across Europe, the Americas, and Australasia have legalized the practice, with each having their own set of criteria both for patients and for health care professionals who administer MAiD.13 There are numerous complexities surrounding MAiD, with one of the more recent being the practice of organ donation following MAiD. To introduce the project in an editorial, the authors discussed how offering organ donation to patients undergoing MAiD requires consideration of patient autonomy and emotional vulnerability, as well as the importance of regulatory frameworks.14 We are particularly proud of two issues that were themed around populations of considerable interest to readers and researchers alike: nurses and long-term care residents. To coincide with both International Day of the Midwife and International Nurses Day in May, we presented a scoping review15 on factors that influence the longevity of newcomers to the nursing and midwifery professions, as well as a scoping review16 on wound management provided by advanced practice nurses. In August, a trio of reviews focused on adults living in long-term care facilities.17–19 A mixed methods review17 explored socially assistive technologies that allow residents to stay in touch with family and friends; a systematic review18 evaluated the effectiveness of physical rehabilitation on functioning and quality of life in residents with dementia; and a qualitative review19 presented the experiences of loneliness and depression among residents and their spouses after separation due to long-term care placement. An insightful and emphatic editorial introducing these reviews did not mince words on the need to prioritize residents’ quality of life.20 It is worth noting that the reviews of particular interest to readers in 2024 covered a broad scope of topics and methodologies, from how lifestyle-based interventions can mitigate risks around cardiovascular disease (a systematic review of effectiveness),21 to the effectiveness and family experiences of interventions that promote partnerships between families and health care staff in intensive care units (a mixed methods systematic review),22 to the integration of health equity in health service and delivery systems in high-income countries (a scoping review).23 This reflects the diverse interests of our readers and highlights the importance of providing authors with a broad platform to showcase their research. To further promote the dissemination of evidence-based research, the JBI Evidence Synthesis editorial office once again signed on as a World Evidence-Based Healthcare ambassador for 2024. The blog “Methodology matters: delivering trustworthy research across the global evidence community”24 examined how methodology is an important underpinning to rigorous research and how JBI methodology has been adopted by sectors beyond health care, such as the legal sector, construction industry, and even human resources. The blog also highlighted some of the other initiatives of the journal aimed at increasing accessibility to research as well as getting papers published, some of which, unfortunately, have had a low uptake. In other achievements for 2024, we published 13 abstracts in languages other than English, including Chinese, Danish, Finnish, French, German, Japanese, Norwegian, and Spanish, aiming to further engage health professionals in their primary language. The social media campaigns to promote these abstracts and reviews reached over 2000 readers, which is encouraging for what could be considered a niche audience. Also in 2024, we continued to promote the JBI Best Practice Information Sheets alongside the relevant systematic reviews. These brief summaries, developed by review authors together with researchers from JBI, present the findings and conclusions of systematic reviews, complete with helpful infographics, to highlight the recommendations clinicians can apply in practice. As you can see, it was another incredibly busy but rewarding year for the journal. We thank our readers, authors, editors, and peer reviewers for helping us grow. We look forward to discovering what 2025 has in store for JBI Evidence Synthesis and the entire evidence synthesis community.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.030 | 0.195 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".