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Record W2285010475

Thoracic Pain: An Observational Study of Chiropractic Treatment on Pain and Wellbeing within a Student Setting

2011· article· en· W2285010475 on OpenAlexaboutno aff
Marcus McDonald, Stavros Ktenas, Shane Turner, Bo Sung Yoon, Michael Maljanek, Daniel Curtis Wilson

Bibliographic record

VenueRMIT Research Repository (RMIT University Library) · 2011
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsChiropracticObservational studyPhysical therapyMedicineMcGill Pain QuestionnaireMental healthLow back painAlternative medicinePsychiatryVisual analogue scaleInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Objective: The purpose of this study is to observe non-specific thoracic spinal pain and wellbeing in patients before and after Chiropractic intervention in a student setting.\n\nDesign and Setting: A prospective practice-based observational study of patients receiving Chiropractic treatment for non-specific thoracic spinal pain (NS-TSP) presenting to RMIT students in teaching clinics.\n\nClinical Features: 23 patients were treated within a multi-modal therapy framework. Methods: Outcome measures: Short form RAND-36 and Short form McGill Pain Questionnaire were administered on the initial consultation before treatment and again after the sixth treatment.\n\nResults: The short form McGill (Total, VAS, PPI) and the physical component summary of the Short form Rand-36 revealed a statistical significance post treatment (p<0.05). No significant difference could be detected on the Mental component summary of RAND-36 (p=0.08). Conclusion: It would appear that there is statistical improvement of pain and physical health status of wellbeing following a multimodal treatment approach by senior Chiropractic students. No significant change was recorded in the mental component summary of RAND-36. Further investigation of NS-TSP is warranted due to the lack of research currently available.

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 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)0.002
metaresearch head score (Gemma)0.000
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 score0.022
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.142
GPT teacher head0.363
Teacher spread0.221 · 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 teacher head, 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

Citations0
Published2011
Admission routes1
Has abstractyes

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