The Use of the Power Step Shoe Insert to Manage Plantar Fasciitis Pain in Industrial Workers: A Seven-Year Pilot Report
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".