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Record W4416287353 · doi:10.70070/cksrnb91

The Temporal and Bidirectional Relationship Between Low Back Pain and Mental Health Disorders: A Systematic Review and Synthesis of Longitudinal Evidence

2025· article· W4416287353 on OpenAlexaboutno aff
Tri Sandy Wibawa Mukti, Allan Yudhiatmoko, Eka Puji Lestari

Bibliographic record

VenueThe International Journal of Medical Science and Health Research · 2025
Typearticle
Language
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsDepression (economics)ComorbidityLongitudinal studyLow back painAnxietyMental healthSystematic reviewProspective cohort studyCohort study

Abstract

fetched live from OpenAlex

Introduction: Low back pain (LBP) is the leading global cause of disability. Its comorbidity with mental health disorders (MHDs) such as depression and anxiety is highly prevalent, complicating treatment and worsening prognosis. However, the temporal direction of this relationship remains ambiguous in cross-sectional literature. This systematic review synthesizes longitudinal evidence to clarify the bidirectional relationship between LBP and MHDs. Methods: A systematic review was conducted following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. PubMed, Google Scholar, Semantic Scholar, Springer, Wiley Online Library databases were searched for prospective cohort studies published between January 1990 and December 2024. Inclusion was restricted to longitudinal studies assessing the bidirectional link: (1) baseline MHDs predicting new-onset LBP, or (2) baseline LBP predicting new-onset MHDs. Risk of bias was assessed using the Newcastle-Ottawa Scale (NOS). Results: Fifteen longitudinal studies met the inclusion criteria. The evidence confirms a significant bidirectional relationship. (1) Meta-analysis data from included reviews demonstrate that baseline depressive symptoms significantly increase the risk of developing new-onset LBP (pooled OR = 1.59; 95% CI 1.26–2.01) (Pinheiro et al., 2015). (2) Conversely, baseline chronic LBP (CLBP) prospectively predicts the onset of depression (OR = 1.28; 95% CI 1.01-1.61) (Dickson et al., 2022) and dysthymia (HR = 1.53) (Schmaling and Nounou, 2018). Comorbid MHDs are significant prognostic indicators for worse LBP outcomes, including higher pain intensity (P=0.11), greater disability (P=0.16), and poorer recovery (RR=0.91) (Pinheiro et al., 2016). Discussion: The synthesis of longitudinal evidence confirms a reciprocal, prognostically significant relationship. This comorbidity is not incidental but is underpinned by shared neurobiological pathways, including monoaminergic system disruption (serotonin, norepinephrine), Hypothalamic-Pituitary-Adrenal (HPA) axis dysregulation, and neuroplastic changes in shared brain regions (e.g., anterior cingulate cortex, prefrontal cortex). The findings mandate a shift from a purely biomedical to an integrated biopsychosocial (BPS) model of care. Conclusion: The relationship between LBP and MHDs is bidirectional and significant. We recommend the implementation of routine, integrated screening protocols and multidisciplinary treatment pathways to address this comorbidity, as treating either condition in isolation is likely to be ineffective.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.039
metaresearch head score (Gemma)0.123
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.039
Threshold uncertainty score0.206

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.123
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0110.016
Bibliometrics0.0100.009
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.185
GPT teacher head0.522
Teacher spread0.337 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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