Trends of Low Back Pain Research in Older and Working-Age Adults from 1993 to 2023: A Bibliometric Analysis
Bibliographic record
Abstract
Daniel KY Zheng,1 Gregory N Kawchuk,2 André E Bussières,3,4 Fadi M Al Zoubi,1 Jan Hartvigsen,5 Siu Ngor Fu,1 Katie de Luca,6 Debra K Weiner,7,8 Jaro Karppinen,9,10 Dino Samartzis,11 Manuela L Ferreira,12 Jinlong Wu,13 Liz Dennett,2 Arnold YL Wong1 1Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, People’s Republic of China; 2University of Alberta, Edmonton, Canada; 3Université McGill, Montreal, Canada; 4Université du Québec à Trois-Rivières, Trois‑Rivières, Canada; 5University of Southern Denmark, Odense, Denmark; 6Central Queensland University, Brisbane, Australia; 7University of Pittsburgh, Pittsburgh, PA, USA; 8VA Pittsburgh Healthcare System, Pittsburgh, PA, USA; 9Research Unit of Health Sciences and Technology, University of Oulu, Oulu, Finland; 10Rehabilitation Services of South Karelia Social and Health Care District, Lappeenranta, Finland; 11Rush University Medical Center, Chicago, IL, USA; 12The University of Sydney, Sydney, Australia; 13Southwest University, Chongqing, People’s Republic of ChinaCorrespondence: Arnold YL Wong, Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, People’s Republic of China, Tel +852 2766 6741, Email arnold.wong@polyu.edu.hkAbstract: Although the number of publications focusing on low back pain in older adults (LBP-O) and working-age adults (LBP-W) has been growing for decades, comparative research trends in these two populations, which may help to guide future investigation, have not been rigorously explored. This analysis aimed to describe publication patterns and trends of research targeting LBP-O and LBP-W over the last three decades. Peer-reviewed LBP-O and LBP-W articles published between 1993 and 2023 were retrieved from the Web of Science, which provided the details of annual publication volume, and prominent journals/countries/institutions. The relationship between the annual publication volumes and years was analyzed by Spearman correlation analysis. The hot topics and emerging trends were analyzed by VOSviewer and CiteSpace, respectively. A total of 4217 LBP-O-related and 50,559 LBP-W-related documents were included. The annual publication volumes of LBP-O and LBP-W articles increased over the years (r=0.995 to 0.998, p< 0.001). The United States had the highest number of prominent institutions publishing relevant articles. The most prolific journal for LBP-O (5.4%) and LBP-W-related (6.1%) papers is the journal “Spine”. Cognitive behavioral therapy, intervertebral disc (IVD) degeneration, physiotherapy, physical activity, and walking were the recent hot topics and physical activity was an emerging trend in LBP-O, while surgery and IVD degeneration (also a hot topic) were emerging trends in LBP-W. This study highlights the paucity of LBP-O-related research in the past. The United States and the journal Spine stand out in LBP research. The research trend of physical activity in LBP-O is consistent with the recognized importance of physical activity for older adults in general, and for managing LBP-O in particular. Conversely, the emerging trends of surgery and intervertebral disc degeneration in LBP-W research highlight a focus on the biomedical model of LBP despite LBP being a biopsychosocial condition.Keywords: low back pain, older adults, working-age adults, bibliometrics, intervertebral disc degeneration, physical activity, surgery
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.034 | 0.075 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".