What does it take to get a diagnosis? Dementia recognition and diagnosis pathways among Indigenous peoples
Bibliographic record
Abstract
Abstract Background Patients, caregivers, and providers face an oftentimes‐confusing healthcare terrain around dementia diagnostics and care given the lack of standardization for screening and evaluation of neurocognitive disorders. This can be further compounded by systemic healthcare inequalities and historical and present‐day marginalization faced by Indigenous populations. Method We present a segment of a pilot study (NIH R56 AG 62307) which sought to explore the impact of Alzheimer’s disease and related dementias (ADRDs) in Indigenous populations across four diverse settings, three in the United States and one in Canada. Community‐based researchers conducted key informant interviews with healthcare providers (n = 20) and sequential focus groups (SFGs) with local health care staff and formal caregivers (14 sessions, n = 17). Data were coded based on research questions and objectives in consultation with project leaders, coders, and community‐based researchers. Result In recognizing a cognitive change, all participants identified the importance of family members who often brought their concerns to the attention of a healthcare provider. Additionally, participants in the US and Canada identified events like hospital admissions as a “catastrophic event” (e.g., injury, missed medication, physical decline) as another route for diagnosis. A unique pathway that Canadian participants identified was the role of personal support workers (PSWs) and community nurses in noticing cognitive changes among individuals they served. Finally, providers mentioned various pathways for receiving a dementia diagnosis. While all providers mentioned taking steps to rule out other reasons for cognitive decline, the specific next step for the diagnosis varied widely. The possible professionals to see for a diagnosis included social workers, family doctors, tribal dementia care specialists, behavioral health specialists, psychiatrists, and neurologists. Conclusion Family members are crucial in recognizing the changes associated with ADRDs. A strength of the Canadian healthcare system is that PSWs and community nurses can also help identify changes, potentially before hazardous “catastrophic events” bring people to the hospital. Once a cognitive change has been identified, the diagnostic pathway is complicated, non‐standardized, and irregular – in other words difficult to navigate. Policies and procedures need to be put in place, delineating standardized protocols to better help family caregivers and patients dealing with ADRDs.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".