Whose voices are still silent: Applying an intersectionality lens to existing evidence on cognitive impairment in older adults with combined hearing and vision impairment
Bibliographic record
Abstract
Abstract Background Age‐related sensory loss is a significant yet understudied public health problem. Evidence suggests that sensory loss in older adults is associated with an increased risk of cognitive impairment, functional decline, and social isolation. However, older adults with combined vision and hearing impairment (dual sensory impairment/DSI) are often overlooked in ageing as well as Alzheimer’s research. We synthesized existing evidence on cognitive impairment in older adults with DSI. Given the importance of diversity and inclusion in ageing and healthcare research, we applied the lens of intersectionality to the review data with the aim of exploring whose voices among older adults with DSI are not represented and whose voices are captured in the existing evidence. Method We conducted a scoping review using the methodological framework by Arskey and O’Malley (2005). The review considered empirical studies that explored cognitive impairment in older adults with DSI. The search was conducted across eleven scientific databases (CINAHL, Embase, Global Health, Mednar, OAIster, OpenGrey, PsycEXTRA, PsycINFO, PubMed, Web of Science, and WorldWideScience) in June 2020. Following the content analysis approach, the extracted data were later analyzed applying the intersectionality lens to capture attributes such as age, sex, gender identity, class, culture, disability, education, ethnicity, geography, indigeneity, and immigration status. Result Of 11,595 studies retrieved, fifty‐six (n = 56) were included in the review, demonstrating how limited the evidence is that exists on cognitive impairment among older adults with DSI. The majority of studies focused on older men with DSI from high‐income countries (Australia, Canada, Japan, Netherlands, UK, and the USA), with the exception of one study from India. Only a few studies reported binary gender differences, with no studies reporting cognitive impairment in gender diverse older population. Attributes such as immigration status and indigeneity were not reported, though the race and ethnicity of older adults were presented in some studies. Conclusion The review highlights important knowledge gaps related to cognitive impairment in older adults with DSI, which is a heterogeneous group. Researchers need to go beyond traditional approaches to promote the intersectionality paradigm in their research to provide evidence that is more representative and inclusive in nature.
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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 | 0.095 | 0.273 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.036 | 0.028 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.013 | 0.020 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".