15 The Role of Race and Adverse Childhood Experiences on Predicting Cognitive Ability on the Montreal Cognitive Assessment (MoCA).
Bibliographic record
Abstract
Objective: Awareness of risk factors associated with any form of impairment is critical for formulating optimal prevention and treatment planning. Millions worldwide suffer from some form of cognitive impairment, with the highest rates amongst Black and Hispanic populations. The latter have also been found to achieve lower scores on standardized neurocognitive testing than other racial/ethnic groups. Understanding the socio-demographic risk factors that lead to this discrepancy in neurocognitive functioning across racial groups is crucial. Adverse childhood experiences (ACEs), are one aspect of social determinants of health. ACES have been linked to a greater risk of future memory impairment, such as dementia. Moreover, higher instances of ACEs have been found amongst racial minorities. Considering the current literature, the purpose of this exploratory research is to better understand how social determinants, more specifically, ACEs, may play a role in the development of cognitive impairment. Participants and Methods: This cross-sectional study included data from an urban, public Midwestern academic medical center. There was a total of 64 adult clinical patients that were referred for a neuropsychological evaluation. All patients were administered a standardized neurocognitive battery that included the Montreal Cognitive Assessment (MoCA) as well as a 10-item ACE questionnaire, which measures levels of adverse childhood experiences. The sample was 73% Black and 27% White. The average age was 66 (SD=8.6) and average education was 12.6 years (SD=3.4). A two-way ANOVA was conducted to evaluate the interaction of racial identity (White; Black) and ACE score on MoCA total score. An ACE score >4 was categorized as “high”; ACE <4 was categorized as “low.” Results: There was not a significant interaction of race and ACE group on MoCA score (p=.929) nor a significant main effect of ACE score (p=.541). Interestingly, there was a significant main effect of Race on MoCA (p=.029). White patients had an average MoCA score of 21.82 (sd=4.77). Black patients had an average MoCA score of 17.54 (sd=5.91). Conclusions: Overall, Black patients demonstrated statistically lower scores on the MoCA than White patients. There was no significant difference on MoCA score between races when also accounting for ACE scores. Given this study’s findings, one’s level of adverse childhood experiences does not appear to impact one’s cognitive ability later in life. There is a significant difference in cognitive ability between races, specifically Black and White people, which suggests there may be social determinants other than childhood experiences to be explored that influence cognitive impairment.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".