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Record W2913254245 · doi:10.1515/sjpain-2018-0323

The impact of comorbid pain and depression in the United States: results from a nationally representative survey

2019· article· en· W2913254245 on OpenAlex
Simranpal Dhanju, Sidney H. Kennedy, Susan Abbey, Joel Katz, Aliza Weinrib, Hance Clarke, Venkat Bhat, Karim S. Ladha

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

VenueScandinavian Journal of Pain · 2019
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsSt. Michael's HospitalToronto General HospitalYork UniversityUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineDepression (economics)CohortConfoundingPopulationLogistic regressionCohort studyNational Health and Nutrition Examination SurveyNational Health Interview SurveyPhysical therapyPsychiatryInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Background and aims The co-morbidity between pain and depression is a target of interest for treatment. However most of the published literature on the topic has used clinical cohorts as the population of interest. The goal of this study was to use a nationally representative sample to explore how health outcomes varied across pain and depression status in a cohort sampled from the general US population. Methods This was a cross-sectional analysis of adults ≥18 years in the 2009-2010 National Health and Nutrition Examination Survey. The cohort was stratified into: no pain/depression, pain alone, depression alone, and pain with depression. The primary outcome was self-reported general health status, and secondary outcomes were healthcare visits, overnight hospital stays and functional limitation. Survey weighted logistic regression was used to adjust for potential confounders. Results The cohort consisted of 4,213 individuals, of which 186 (4.4%) reported concurrent pain and depression. 597 (14.2%) and 253 (6.0%) were classified with either pain or depression alone, respectively. The majority of individuals with co-morbid pain and depression reported poor health (65.1%, p<0.001) and were significantly more likely than those with neither condition to rate their health as poor after adjustment (OR: 7.77, 95% CI: 4.24-14.26, p<0.001). Those with pain only or depression only were also more likely to rate their health as poor, albeit to a lesser extent (OR: 2.21, 95% CI: 1.21-2.34, p<0.001; OR: 3.75, 95% CI: 2.54-5.54, p<0.001, respectively). A similar pattern was noted across all secondary outcomes. Most notably, those with co-morbid pain and depression were the most likely to endorse functional limitation (OR: 13.15, 95% CI: 8.00-21.61, p<0.001). Comparatively, a similar trend was noted amongst those with pain only or depression only, though with a reduced effect size (OR: 4.23, 95% CI: 3.12-4.77, p<0.001; OR: 5.13, 95% CI: 3.38-7.82, p<0.001). Conclusions Co-morbid pain and depression in the general population resulted in markedly worse outcomes versus isolated pain or depression. Further, the effect appears to be synergistic. Given the substantial burdens of pain and depression, future treatments should aim to address both conditions simultaneously. Implications As a result of the co-morbidity between pain and depression, patients presenting with either condition should increase the index of suspicion among clinicians and prompt screening for the reciprocal condition. Early intervention for co-morbid pain and depression has the potential to mitigate future incidence of chronic pain and major depression.

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)0.017
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.838

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.330
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