A MULTILEVEL ANALYSIS OF PHYSICAL ACTIVITY INTERVENTIONS IMPLEMENTED IN THE KAHNAWAKE SCHOOLS DIABETES PREVENTION PROJECT
Bibliographic record
Abstract
There is growing consensus among researchers interested in physical activity (PA) promotion that ecologically based PA interventions offer strong potential for promoting activity involvement in populations. Although some PA promotion initiatives have been directed at a variety of targets within a multitude of settings, optimal combinations of strategies for promoting PA within a community setting have not been identified. Our purpose was to provide a detailed description of the PA interventions implemented in 1996 and 1997 in the Kahnawake Schools Diabetes Prevention Project (KSDPP), a Mohawk community-based participatory project to prevent type 2 diabetes that has led to increases in fitness among participating children (Horn et al., 2000). In a first step towards a more finegrained analysis of PA interventions, we applied a recently developed analytical procedure (Lévesque et al., 2000) to archival and interview data about the interventions implemented by KSDPP. This procedure allows us to assess the variability in intervention targets (e.g., individuals, small groups (i.e., interpersonal environment), organizations, communities, political players/systems), strategies for change (i.e., arrangement of target(s) and links between them), and delivery settings (i.e., organization, community). The final database included 47 different interventions. Descriptive analyses revealed that overall, interventions targeted most often the interpersonal environment (46.8% of interventions), while type of strategy implemented was most often a direct attempt to change the interpersonal environment (44.7% of interventions), most often within a community setting (77.8% of interventions). These findings suggest that community-based PA promotion programs are designed and implemented as complex packages that contain a host of multi-target, multisetting intervention strategies. We conclude that only when we are able to make order of this entanglement will it be possible to understand the processes underlying the impact of PA promotion interventions.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".