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Record W7027337783

Chiropractors can do: testing the feasibility of intervening to optimize chiropractic care for adults with neck pain disorders: a pilot cluster randomized controlled trial

2016· dissertation· en· W7027337783 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2016
Typedissertation
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsChiropracticRandomized controlled trialGuidelineNeck painIntervention (counseling)Spinal manipulationManual therapyAlternative medicineCluster randomised controlled trial
DOInot available

Abstract

fetched live from OpenAlex

Background: Neck pain in adults is common and a leading cause of physical disability. Recently, a guideline was developed for the management of non-specific neck pain (NSNP) with the aim of improving the quality of the delivery of chiropractic care. One key guideline recommendation is to undertake multimodal care for patients with NSNP. The aim of this pilot study was to determine the feasibility of implementing a multifaceted knowledge translation intervention by promoting the use of multimodal care by chiropractors managing patients with NSNP. Methods: The design was a cluster randomized controlled pilot and feasibility trial. Chiropractors in private practice in Canada were approached to participate in the study. Consenting chiropractors were randomized to receive either a theory-based educational intervention in the experimental group or simply a printed copy of the guideline in the control group. Each chiropractor was asked to recruit five neck pain patients. Primary feasibility outcomes for both chiropractors and patients included were rates of: 1) recruitment, 2) retention, and 3) adherence to the intervention. Secondary outcomes included were scores of behavioural constructs (level of knowledge and self-efficacy) for recommended multimodal care. Clinical outcomes were pain intensity and neck pain-specific disability. Results: Due to slow recruitment, a total of 400 chiropractors received a postal mailed invitation to participate. In total, 47 chiropractors were randomized to the intervention or the control group according to the random sequence allocation. Fifteen withdrew from the study, leaving a total of 32 participants. Eleven chiropractors in the intervention group completed the webinars and e-learning modules, two partially completed them and three did not register. Overall, nine chiropractors recruited a total of 29 patients (n=11, intervention group; n=18 control group). Sixty-three percent (n=7) of patients in the intervention group and 56% (n=10) in the control group completed all the outcome measures at baseline and at 3-month follow-up and attended follow-up visits and performed home exercises. Over half (54%, n=6) of chiropractors in the intervention group reported being familiar with the guideline and the BAP compared with 71.1% (n=5) in the control group. Confidence in implementing BAP was lower in the intervention group (27.3%, n=3). Of those who completed the trial, 17 patients completed all the 3-month follow-up outcome measures and the end of study questionnaires (n=7; intervention group and n=10; control group). Patients in the intervention group reported significant reduction in pain (P= 0.027) and reduction in disability scores severity (P= 0.033) from baseline to 3-month follow-up. Conclusion: In this pilot cluster randomized controlled trial, patient recruitment, retention and adherence of both chiropractors and patients were challenging. To overcome these challenges, a thorough evaluation of potential barriers, outcomes and possible solutions must be considered prior to embarking in a larger trial.

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)0.011
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.014
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0130.001

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 head0.023
GPT teacher head0.293
Teacher spread0.270 · 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 designRandomized trial
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
Published2016
Admission routes1
Has abstractyes

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