“For Haitian culture, being older [is] a blessing”: Perceptions of Aging, Elderhood, and Dementia in a Haitian Born Sample
Bibliographic record
Abstract
This thesis investigates how first-generation Haitian immigrants in the United States understand and interpret dementia within the intersecting contexts of culture, migration, and biomedicine. While dementia is constructed as a pathological “loss of self” and a public health epidemic, in American biomedical and popular discourse, this study examines how Haitian-born individuals—socialized within a non-Western cultural and spiritual framework—make sense of cognitive decline and impairment in ways that diverge from Western biomedical narratives. Guided by theoretical orientations from medical anthropology, including Mark Nichter’s idioms of distress, Margaret Lock’s local biologies, and neuroanthropology, this research explores how cultural models of illness, aging, and the body shape Haitian immigrants’ perceptions of dementia. Using qualitative methods, including semi-structured interviews, and engagement with the Montreal Cognitive Assessment (MoCA), the study centers the experiences of late-aged Haitian immigrants residing in the United States. Findings reveal that participants often describe memory loss and cognitive changes through idioms emphasizing imbalance, disconnection, or interpersonal disturbance rather than neurodegeneration. Health and illness were understood as reflections of harmony or disharmony between the physical, social, and spiritual realms by Haitian people. In regard to the Montreal Cognitive Assessment (MoCA), participants expressed unfamiliarity with the MoCA, revealing that the assessment may be culturally incongruent and limited in capturing the full range of cognitive and social competence valued in Haitian contexts. This study highlights the incongruence between biomedical and Haitian cultural constructions of dementia, and between Western and Haitian perceptions of aging. Findings from the study also underscore the need for more culturally responsive approaches to cognitive assessment and elder care. By situating Haitian immigrants’ interpretations of dementia as acts of cultural continuity and adaptation, this research contributes to broader anthropological and gerontological scholarship on how migration, culture, and medicine shape experiences of aging and illness across transnational settings.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".