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Record W2598744219 · doi:10.4172/2165-7556.1000150

The Use of the Power Step Shoe Insert to Manage Plantar Fasciitis Pain in Industrial Workers: A Seven-Year Pilot Report

2016· article· en· W2598744219 on OpenAlexaboutno aff
Eric Durak

Bibliographic record

VenueJournal of Ergonomics · 2016
Typearticle
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsPlantar fasciitisInsert (composites)MedicineEngineeringComputer sciencePhysical therapyPhysical medicine and rehabilitationMechanical engineeringAlternative medicine

Abstract

fetched live from OpenAlex

We tested the effects of the Power Step shoe insert in a group of Facilities Management employees (n=23 staff, seventeen men, six woman, average 15 years of university service), 80% of whom have been clinically diagnosed with Plantar Fasciitis. Inserts were handed out to staff that qualified based on diagnosis beginning in 2008, and regular staff surveys were solicited every six months thereafter. New inserts were given to staff each year as they qualified. Over the course of seven years, eight staff personnel retired or left the program, and 10 were added to the program. Wear and tear of the insert, and pain levels based on McGill 1-10 rating scale were used each year. In the seven years of the program- the average length of use was 4.5 years, and pain levels were reduced from 4.83 (year one average) to 1.60, which includes new personnel who were added after 2010. Changes were also seen over time with individual workers who used the Power Steps for more than two years, seeing a decrease and levelling off of pain levels from the first year of use. The results of this program show that over time the chronic pain levels associated with work efforts in staff with Plantar Fasciitis are reduced by a statistically significant amount and clinically based on the addition of long- term Power Step inserts added to work boots and shoes in Facilities Management staff. This trend is continual even for newer users, and comparisons with non-power step usage shows significant variations in pain levels.

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)0.001
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 score0.398
Threshold uncertainty score0.205

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.049
GPT teacher head0.255
Teacher spread0.206 · 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
Published2016
Admission routes1
Has abstractyes

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