Sustainable human movements – a threshold concept with potential to open up new perspectives in physiotherapy
Bibliographic record
Abstract
There is a call to action for physiotherapists worldwide to contribute to the transition towards 'sustainable health'. In this paper, we build upon the current definition of 'sustainable health' and also on 'sustainable physical activity' to introduce and theoretically substantiate the concept of sustainable human movements, and suggest a definition thereof. Sustainable human movements will be described as a threshold concept with three aligned critical concepts; (i) movement control, including forces as causes of emerging movements, (ii) movement quality, referring to how movements are performed in terms of optimisation, and (iii) physical literacy, including motivation, confidence and physical competence. A deep understanding of these concepts, combined with a collaboration and learning approach applied together with the patient, is proposed to enable a sustainable human movement approach to permeate physiotherapy theory and practice. To facilitate this, a generic and easily accessible tool has recently been developed. It combines support for structured observational movement analysis and pedagogical support for creating a mutual and extended understanding of a patient's lived experience. This encourages the patient to become actively involved and take responsibility for promoting his/her 'sustainable health'. The aims of this paper are to a) suggest a theoretical framework for and definition of the concept sustainable human movements, and b) introduce a clinical tool that ultimately aims at promoting sustainable movements and health.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.046 |
| Scholarly communication | 0.011 | 0.021 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".