USING THE ACT-OUT QUESTIONNAIRE TO INFORM ON COMMUNITY MOBILITY AND PARTICIPATION FOR PEOPLE LIVING WITH DEMENTIA
Bibliographic record
Abstract
Abstract For people living with dementia to continue living in their current residences or “age in place”, it is essential for them to sustain their participation in daily activities and maintain mobility within their communities. Community mobility encompasses the ability to reach places where they can participate in meaningful everyday life activities. It also includes transportation modes such as walking, biking, driving, or using public transport. Thus, we developed the Participation in ACTivities and Places OUTside Home (ACT-OUT) questionnaire based on a transactional perspective and understanding of the person-environment relationship as unfolding and dynamic, embedded and situated, and enacted and emplaced. The ACT-OUT, used in a sit-down interview setting, which can be followed by mobile (walking) interviews, to enable the collection of rich data about around 25 important places that people currently visit, have abandoned, or wish to visit. A second part of the questionnaire collects information on traveling to the place (e.g., frequency, transportation, familiarity) and on activities performed there. The ACT-OUT has been used in multiple countries, including Switzerland, Sweden, the UK, and Canada, and among different populations, notably people with and without dementia. Results show that people with dementia experience a higher rate of abandonment of places and for many more places than people without dementia. It highlights the importance of addressing community mobility and how we conceptualize, design, and adapt important places to support people living with dementia to participate in places and activities that can maintain their well-being and health as they age in their communities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".