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Record W2741892507 · doi:10.51415/10321/2037

The efficacy of manipulation and mobilization in the treatment of Morton's neuroma

2002· dissertation· en· W2741892507 on OpenAlexaboutno aff
Neetu Govender

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMedicine
TopicPeripheral Nerve Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePlaceboNeuromaAnklePhysical therapyMobilizationFoot (prosody)MassageMcGill Pain QuestionnaireJoint mobilizationClinical trialRandomized controlled trialSurgeryVisual analogue scaleRange of motionAlternative medicineInternal medicine

Abstract

fetched live from OpenAlex

The purpose of this randomised, placebo-controlled clinical trial was to investigate the efficacy of foot and ankle manipulation and mobilization as opposed to a placebo treatment (de-tuned ultrasound), in terms of objective and subjective findings in the treatment of Morton's neuroma. This clinical trial consisted of two groups, each with twenty patients. Patients who were diagnosed by the researcher as suffering from Morton's neuroma were included in the study. The patients were randomly allocated into the respective groups. The ages of the patients ranged from 23 to 79 years old. Group A received the de-tuned ultrasound as the placebo treatment and Group B received foot and ankle manipulation and mobilization as well as the de-tuned ultrasound to eliminate any massage effect that may have been incurred. It was hypothesised that foot and ankle manipulation and mobilization would be effective in the treatment of Morton's neuroma. The treatment protocol consisted of a course of six treatments over a treatment period of three weeks. Subjective and objective measurements were taken at the initial, third and final consultations. Subjective data was obtained via the use of the Numerical Rating Scale 101, the Short-form McGill Pain Questionnaire and the Foot Function Index. Objective data was obtained by means of digital algometer measurements

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.733
Threshold uncertainty score0.247

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.025
GPT teacher head0.305
Teacher spread0.280 · 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

Citations1
Published2002
Admission routes1
Has abstractyes

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