“It’s Good. It’s Really Good.”: Perspectives of Older Adults, Exercise/Recreation Professionals, and Primary Care Providers on Designing a Movement Behavior Intervention Using the Staircase Approach
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Interventions targeting sedentary behavior in older adults have reported mixed success for behavior change. The previously proposed Staircase Approach offers a novel strategy to support long-term behavior change by targeting a reduction in sedentary time before progressing to increasing physical activity levels. The current study aimed to understand the perceptions of older adults, exercise/recreation professionals, and primary care providers (PCPs) about the critical components of a new intervention based on the Staircase Approach. METHODS: Participants (older adults, 65+ years; PCPs; and exercise/recreation professionals) from three Canadian provinces (Alberta, Ontario, and New Brunswick), participated in semistructured focus groups. Transcripts from the sessions were analyzed using reflexive thematic analysis in the context of a previously conducted review by our team. RESULTS: There were 17 focus groups (n = 50): four in older adults (n = 14), five with PCPs (n = 14), and eight with exercise/recreation professionals (n = 22). Participants expressed varying opinions on the components necessary for a relevant intervention. The need to embed options within the intervention, and to promote and deliver the intervention, was clear. Some themes were consistent across and within groups (e.g., simple, motivational messaging), whereas others differed (e.g., education, delivery mode, and contact). PCPs added insights about the needs of older adults who typically do not participate in research. CONCLUSION: Older adults have varied requirements, preferences, and skill levels that necessitate providing many options in any newly designed intervention. Significance/Implications: The intervention for the new Staircase Approach will require collaboration between multiple sectors to be successful.
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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 | 0.019 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".