Setting research priorities in age-related vision loss: The first step in a critical participatory action research approach
Why this work is in the frame
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Bibliographic record
Abstract
There are no known examples of studies utilizing a critical participatory action research (CPAR) approach with older adults aging with vision loss, to better understand how environmental factors impact activity engagement. As such, the aim of this article was to share the process of initiating a CPAR approach with older adults with age-related vision loss to identify a set of research and/or rehabilitation priorities related to the influence of physical, social, cultural, political, and institutional environmental factors on activity engagement. This study utilized a CPAR approach. Eight older adults (aged 65 years of age and older) with a diagnosis of age-related vision loss (including macular degeneration, glaucoma, and/or diabetic retinopathy) took part in three half-day meetings as well as a one-on-one interview over a period of 2 months. Through a series of facilitated group discussions, the older adults identified research and/or rehabilitation priorities related to how environmental influences support or limit the participation of older adults with age-related vision loss (ARVL) in everyday activities. Three research and/or rehabilitation priorities were identified including (1) community mobility; (2) assistive technology; and (3) community support and services. For each priority, the older adults, along with the researchers, answered four key questions including (1) What do we need to know more about? (i.e., research question); (2) How could we learn more about this? (i.e., proposed methods of data collection); (3) Who would we need to involve as key stakeholders? (i.e., participants); and (4) What would change look like? (i.e., action potential). This study shared the process of initiating a CPAR process with eight older adults with ARVL to identify research and/or rehabilitation priorities. By doing so, this study will help to provide direction for future ARVL research and rehabilitation that is grounded, methodologically, in a CPAR approach.
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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 | 0.010 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it