What is known about Cycling Without Age: A Scoping Literature Review
Bibliographic record
Abstract
Abstract The Cycling Without Age (CWA) program provides residents of long-term care homes with a bike ride experience, as a volunteer pedals them around the community in a specially designed trishaw. There is limited evidence of the program's effectiveness on older adults, pilots, and communities. The purpose of this literature review is to scope and summarize contemporary CWA discourses to generate future research questions that will provide evidence for future implementation of CWA. Data collection and analysis followed Arksey and O'Malley's 2005 framework. A systematic search was conducted in PubMed, OMNI, and Ebscohost databases. A grey literature search strategy incorporated: grey literature databases, customized Google searches, targeted websites, consultation with expert librarians, and a social media analysis on Twitter, Facebook and LinkedIn. Content analysis was used to identify the key themes. A total of 165 sources (2 peer-reviewed, 103 grey literature, 60 social media) were included in the final analysis. The three main themes were (a) meaning from being on a bike, (2) impacts of CWA, and (3) formation of relationships. Findings suggest that the CWA program brought valuable meaning to the participants' lives, significantly improved their happiness, and was associated with the formation of new and diverse intergenerational relationships. A large amount of anecdotal evidence, social media chatter, and global adoption of CWA indicate its importance and potential to satisfy the need of older adults to engage with society. Future research on the physical and mental health benefits of CWA is required to support further implementation of the program.
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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 | 0.011 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.032 | 0.025 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".