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Record W1511610793

Outcome measures and their everyday use in chiropractic practice.

2010· article· en· W1511610793 on OpenAlexaffabout
Paul M Hinton, Randall C. McLeod, Blaine Broker, C Elizabeth Maclellan

Bibliographic record

VenuePubMed · 2010
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsPrince Albert Grand Council
Fundersnot available
KeywordsChiropracticOutcome (game theory)Alternative medicineBaseline (sea)Computer scienceClinical PracticeMedicineData sciencePhysical therapyPathology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVES: To describe the extent to which chiropractors utilize standardized outcome and various clinical measures to systematically document patients' baseline health status and responses to treatment, with particular consideration being given towards quantifiable outcome instruments. STUDY DESIGN: Cross-sectional mailed survey. PARTICIPANTS: Registered chiropractors in the province of Saskatchewan. METHODS: A survey was mailed to all registrants of the Chiropractors' Association of Saskatchewan. Respondents graded their frequency of using various standardized pencil-and-paper instruments and functional chiropractic, orthopaedic and neurological tests in the contexts of both the initial intake assessment ('always,' 'commonly,' 'occasionally,' or 'never') and the course of subsequent treatment (after 'each visit,' after '9-12 visits,' 'annually,' when patient 'not responding,' on 'dismissal/discharge,' 'never' or for some 'other' reason). Data were tabulated for all item and response category combinations as frequencies and percentages using the total sample size as the denominator. RESULTS: Of 164 registered chiropractors, 62 (38%) returned a completed questionnaire. A pain diagram was the most commonly used subjective outcome measure and was administered routinely (either "always" or "commonly") by 75% of respondents, at either the initial consultation or during a subsequent visit. Numerical rating and visual analogue scales were less popular (routinely used by 59% and 42% respectively). The majority of respondents (80%) seldom ("occasionally" or "never") used spine pain-specific disability indices such as the Low Back Revised Oswestry, Neck Disability Index or the Roland-Morris Questionnaire. As well, they did not use standardized psychosocial instruments such as the Beck Depression Index, or general health assessment measures such as the SF-36 or SF-12 questionnaire. Neurological testing was the most commonly used objective outcome measure. Most respondents (84% to 95%) indicated that they continually monitored neurological status through dermatomal, manual muscle strength and deep tendon reflex testing. Ranges of motion were routinely measured by 95% of respondents, usually visually (96%) rather than goniometrically or by some other specialized device (7%). CONCLUSIONS: Our findings suggest that the majority of chiropractors do not use psychosocial questionnaires or condition-specific disability indices to document baseline or subsequent changes in health status. Chiropractors are more likely to rely on medical history taking and pain drawings during an initial intake assessment, as well as neurological and visually estimated range of motion testing during both initial intake and subsequent treatment visits.

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)0.023
metaresearch head score (Gemma)0.071
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 score0.023
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.071
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.045
GPT teacher head0.292
Teacher spread0.247 · 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

Citations15
Published2010
Admission routes2
Has abstractyes

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