Design Thinking as an approach to develop sustainable physical activity and nutrition interventions in low re-sourced settings
Bibliographic record
Abstract
The objective of the study is to describe how design thinking as a participatory process can be applied in determining how sustainable physical activity and nutri-tion interventions should be implemented in a low resourced community in South Africa. Physical inactivity is the 4th leading cause of mortality world-wide. Asso-ciated with inactivity, a high prevalence of obesity is reported. Evidence based re-search indicate that sustainable physical activity and nutrition interventions will reduce the burden of physical inactivity and obesity. Poverty, and its inherent lack of food security, further impacts the health of people living marginalized, increas-ingly urban lifestyles. The intent of the project is to change attitudes and behavior towards physical activity participation and nutrition choices. Design thinking is typically implemented using a five-step process where the community is engaged with presenting the problem they experience, defining the problem, presenting so-lutions to the problem and finally developing a prototype in solving the problem they experience. The principle of the DT process is that the low resourced com-munity holds part of the answer to the problem and has a desire to change their health. The proposed solutions, coming directly from the participants, are there-fore considered viable. Once a desired prototype is developed and tested in the community, feasibility can be determined. The presence of these three factors, is expected to result in an innovation.
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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 | 0.068 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".