Navigating Decisional Capacity Assessments for People with Dementia: Social Workers’ Strategies and Challenges at the Intersection of Cognitive Impairment and Social Inequality
Bibliographic record
Abstract
BACKGROUND: Legislation across the globe has called on social workers and other health professionals to support the rights of persons with dementia to remain as autonomous as possible in all aspects of their lives. Yet, protecting rights can become complex when professionals are also called on to assess for decisional capacity. OBJECTIVE: This study explores social workers' experiences conducting psychosocial capacity assessments with persons with dementia at long-term and home care settings, and the strategies they use to support decisional inclusion, autonomy, and empowerment. METHODS: Guided by the principles of constructivist grounded theory (CGT), five in-depth interviews were conducted with social workers, 4 worked at LTC and 1 worked at homecare, and they have been called on to participate in at least one capacity assessment in the last five years in Montreal Quebec Canada. All interviews were transcribed and analyzed thematically. RESULTS: Our findings suggest that social inequities such as ageism, ableism, and racism, the absence of family or community support and scarcity of resources can work together to erode the persons with dementia's sense of autonomy. Social workers emphasized that building trust, engaging families and communities, and addressing broader social issues are paramount to help foster inclusion and empower individuals within decision-making contexts. However, attending to these critical issues can be challenging without the necessary organizational support. CONCLUSION AND IMPLICATIONS: Supporting persons with dementia during capacity assessments is a complex process that demands social workers to navigate a web of social, organizational, and interpersonal challenges. While relational strategies-like strengthening social connections and empowering persons with dementia-offer promising ways to address these difficulties, tight organizational budgets and competing priorities can create barriers to this work. Ultimately, social workers' success in promoting autonomy and inclusion depends not only on their individual efforts, but also on the systemic conditions that shape their work.
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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 | 0.023 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.012 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".