Applying Systems Thinking Approaches to Address Preventive Health Factors through Public Parks and Recreation Agencies
Bibliographic record
Abstract
Within the United States parks and recreation agencies (P&R) manage public facilities, spaces, lands, and recreation programs. Public health (PH) evidence has increasingly pointed to local public P&R agencies as critical for promoting preventive health. Programs and strategies are available, but most P&R agencies have limited resources and lack local knowledge on which to base actions. However, the research base is growing. The global research question has shifted from asking IF P&R agencies can positively affect PH factors, to HOW they can best do so with limited resources.This research adapted a systems theory approach to how local public P&R agencies are addressing health factors. Methods included a literature review along with iterative exploration through a three-stage Delphi panel study with 17 P&R agency Expert Panelists in the U.S and Canada. Panelists were identified through a waterfall selection process. Each had at least three years of senior administration experience with interest in addressing PH factors.The study explored which preventive factors appear to be most modifiable by P&R. Results indicated increased physical activity, improved nutrition, enhanced safety or perception of safety, increased social and parental engagement, improved transportation and access to locations (especially nature), and cessation or reduced overconsumption of tobacco and alcohol. However, the priority of factors varies by community, and the continuing challenge is determining the priority of the factors for agencies and their partners to address. Community-specific data are not typically readily available to P&R agencies. Programs, strategies, internal methods, policies, and documents utilized by agencies were collected. Thirty-one related national initiatives (programs) were identified and ranked by the panelists.Key common strategies for P&R were identified. Results indicated a need to focus strategies on leadership and adequate funding to create a strong organizational culture of systematic assessment for addressing PH through allocation of P&R staff and financial resources. Systems thinking analysis and strategies can improve outcomes for cultural ethics of inclusion and equity, equitable access to assets and programs, collaboration with other partners, utilization of crime prevention and environmental design strategies, increased health promotions and education, and centralized tracking and evaluation of feasible measures.Implications for research include needs for additional validation and dissemination of research, evidence-based tools, and proven methods. There continues to be a strong need to help address gaps in knowledge transfer between research and practice realms. Management implications suggest methods for practice to enhance systems-thinking approaches for better preventive health outcomes through P&R in communities.
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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 | 0.044 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".