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Record W4408129682 · doi:10.1016/j.fhj.2025.100233

Low back pain: the forgotten public health epidemic

2025· article· en· W4408129682 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFuture Healthcare Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsWestern University
Fundersnot available
KeywordsPublic healthMedicineLow back painHistoryAlternative medicineNursingPathology

Abstract

fetched live from OpenAlex

Low back pain (LBP) is a global public health concern, resulting in significant healthcare utilisation and economic losses. The rise in LBP cases, particularly following lifestyle changes related to the COVID-19 pandemic, is seen as a pressing issue. Contributing factors such as obesity, sedentary behaviour and psychosocial stressors are frequently highlighted. In the context of future healthcare, it is argued that evidence-based management strategies, including clinical guidelines and rehabilitation services, must be prioritised. The integration of primary care with community-based support is essential to reduce unnecessary referrals to specialised care. Future healthcare systems will need to adopt more proactive approaches, emphasising prevention, early intervention and patient education. Addressing LBP effectively will not only reduce the current burden, but also help build resilient healthcare models capable of managing chronic conditions more efficiently. The focus on LBP in public health agendas is crucial for shaping a more sustainable and effective future healthcare landscape.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.697
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.336
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it