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Record W2987284088

Associations between low back pain and depression and somatization in a Canadian emerging adult population.

2017· article· en· W2987284088 on OpenAlexaffabout
David Robertson, Dinesh Kumbhare, Paul S. Nolet, John Srbely, Genevieve Newton

Bibliographic record

VenuePubMed · 2017
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of GuelphCanadian Memorial Chiropractic CollegeUniversity of Toronto
Fundersnot available
KeywordsSomatizationDepression (economics)Low back painMedicineBack painPopulationPhysical therapyPsychiatryPsychologyAnxietyAlternative medicine
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION: The association between depression, somatization and low back pain has been minimally investigated in a Canadian emerging adult population. METHODS: 1013 first year Canadian university students completed the Modified Zung Depression Index, the Modified Somatic Perception Questionnaire, and a survey about low back pain frequency and intensity. Multinomial logistic regression was used to measure associations between low back pain and depression and somatization, both independently and co-occurring. RESULTS: Over 50% of subjects reported low back pain across grades, and both depression and somatization were significantly positively associated with low back pain. Several positive associations between the cooccurrence of somatization and depression with various grades of low back pain were observed. DISCUSSION: These results suggest that low back pain, depression and somatization are relatively common at the onset of adulthood, and should be considered an important focus of public health.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.256
Teacher spread0.244 · 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 designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations57
Published2017
Admission routes2
Has abstractyes

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