Health Literacy, Cognitive Impairment, and Diabetes Knowledge Among Incarcerated Persons Transitioning to the Community
Bibliographic record
Abstract
ABSTRACT Purpose The purpose of this study was to evaluate the relationships of health literacy (HL; Short Test of Functional Health Literacy), cognitive impairment (CI), and diabetes knowledge (DK) among incarcerated persons transitioning to the community. Methods Using preintervention data from a quasi-experimental nonequivalent control group study evaluating the feasibility of a six-session literacy-tailored Diabetes Survival Skills intervention for incarcerated men transitioning to the community, we conducted correlational analyses among the Short Test of Functional Health Literacy, Montreal Cognitive Assessment, and Spoken Knowledge in Low Literacy in Diabetes Scale using the SPSS PROCESS macro and bias-corrected bootstrapping to test the meditational hypothesis: HL mediates the relationship between CI and DK. Results Participants (N = 73) were incarcerated for 1–30 years with a mean age of 47 (9.9) years, 40% Black, 19% White, and 30% Hispanic, with 78% having high school/GED or less education. Most (70%) screened positive for CI and had low DK, and 20% had marginal or inadequate HL. HL, CI, and DK were positively associated with each other. Controlling for race, age, and group (control/experimental), cognitive function had a significant direct effect on HL (b = 0.866, p = 0.0003) but not on DK (b = 0.119, p = 0.076). Results indicated a significant indirect effect of cognitive functioning on DK via HL, 95% confidence interval [0.300, 0.1882]. Conclusion Intervention approaches aimed at increasing HL or tailored to low HL in the presence of CI may be effective in increasing DK in this population. Implications Given the low risk to high benefit of implementing literacy-tailored approaches to persons in prison and the population demographics from studies supporting a high degree of CI, nurses should consider implementing literacy-tailored approaches and screening for CI before participation in all educational programs.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".