S06-3: We Walk. Developing and pilot testing a dyadic intervention to promote outdoor walking in people after stroke: benefits, challenges and solutions
Bibliographic record
Abstract
Abstract Purpose After stroke, physical activity (PA) levels are low, risking secondary stroke, cardiovascular disease, falls and poor mobility. Regular PA reduces these risks. Walking is a preferred PA option for stroke survivors, and social support influences uptake and maintenance of behaviours. We therefore developed WeWalk, a person-centred, dyadic peer-support behavioural intervention supported by walking buddies, to promote regular walking after stroke. This study evaluated participants’ experiences of WeWalk to refine it ready for effectiveness testing and implementation. Methods Intervention: WeWalk involved facilitated face-to-face and telephone sessions with a researcher with behaviour change training, supported by intervention handbooks and diaries. Dyads agreed walking goals and plans, monitored progress, and developed strategies for maintaining walking. Evaluation Data were collected through semi-structured interviews and facilitator fieldnotes during intervention delivery, and were analysed using thematic analysis, guided by a theoretical framework of acceptability. Results We recruited 21 dyads comprising community-dwelling PWS and their walking buddies. Eighteen dyads completed exit interviews, one dyad was lost to follow-up and two withdrew with ill-health. We identified three themes: acceptability evolves with experience, mutuality, and person-centredness with personally relevant tailoring. As dyads recognised how WeWalk components supported walking, perceptions of acceptability grew. Effort receded as goals and enjoyment of walking together were realised. The dyadic structure provided accountability, and participants’ confidence developed as they experienced physical and psychological benefits of walking. WeWalk required careful facilitation. It worked best when dyads exhibited relational connectivity and mutuality in setting and achieving goals however in a few dyads agreeing and enacting mutual goals was more challenging. Tailoring intervention components to individual circumstances and values supported dyads in achieving meaningful goals. Conclusions WeWalk is feasible and acceptable, illustrating the potential of dyadic interventions after stroke. However, its complexity requires considered implementation strategies. Data highlight the need for careful matching of dyads, facilitation of dyadic working by practitioners who can support development of dyadic relationships; and community structures linked to healthcare pathways that support implementation. We have worked with charities health services organisations to plan and develop these implementation strategies and report the challenges and potential solutions to delivering this complex intervention.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".