Urban Care Farming to Enhance Quality of Life Among Older Adults: Protocol for a Waitlist Randomized Trial
Bibliographic record
Abstract
Background: Population aging poses challenges to health systems and costs, and evidence shows that older adults spend a long time in ill health. Improving healthspan, time spent in good health, allows older adults to contribute and improve in their quality of life. Active and healthy aging are crucial to improving healthspan. Urban care farming (UCF) is a behavioral intervention that is purported to enhance active and healthy aging. Objective: This trial evaluates the effectiveness of a care farming intervention in improving the quality of life and biopsychosocial health outcomes of older participants. Methods: We conducted a parallel group, 2-arm pragmatic waitlist randomized trial with a 1:1 allocation, in which participants were randomized into either the intervention or waitlist control arm. Community-dwelling participants aged 50-85 years, without any mobility issues, were recruited. Participants in the intervention arm commenced the 24-week UCF program, while waitlist control participants received no intervention during this period. The primary (World Health Organization Quality of Life-brief version) and secondary outcomes were collected at baseline, 6th month, and 12th month after the intervention group completed the trial. Secondary outcomes include objectively measured physiological outcomes, cognition, frailty, and self-reported psychosocial outcomes. Intervention effects were estimated using mixed-effects difference-in-differences regression to account for repeated measurements. Results: The randomized controlled trial commenced in April 2024, with the intervention group starting first. By April 2024, we had enrolled 137 participants at commencement, with 67 participants randomized to the intervention group and 70 to the control group. The intervention arm started in April 2024 and concluded in September 2024. Baseline data were collected in March 2024, and 6-month follow-up data were collected in September 2024. The waitlist control participants began the UCF intervention at the end of September 2024 and concluded in April 2025. Data collection for the 12-month follow-up concluded in May 2025. Analysis of the baseline and 6-month follow-up data is still ongoing. Conclusions: The outcomes of this study will contribute to the understanding of UCF on quality of life and health. This trial has potential positive implications for public health, as it utilizes a robust research design and methods to provide empirical insights into the multifaceted health benefits of the multicomponent UCF intervention. This trial could also serve as a model for future intervention research on scalable, community-based programs. Taken together, the UCF content and the outcomes, process, and economic evaluations completed through this study could inform scalable models of the UCF intervention, with potential implications for public health strategies to address health issues related to population aging.
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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 | 0.027 | 0.024 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.086 | 0.013 |
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".