Prevalence of dementia and mild cognitive impairment among the older prisoner population in England and Wales: a cross-sectional study
Bibliographic record
Abstract
OBJECTIVES: To estimate the prevalence of dementia and mild cognitive impairment (MCI) in the older prisoner population in England and Wales and to establish risk of harm to self and others, activity of daily living needs and social networks of prisoners with likely MCI and dementia. DESIGN: We screened 869 older prisoners (aged 50 years and older) using the Montreal Cognitive Assessment (MoCA). Participants testing positive on the MoCA (≤23) were interviewed using the Addenbrooke's Cognitive Examination, Third Revision (ACE-III) and a range of standardised assessments were used to assess risks of externalised violence and of self-harm; activities of daily living needs; mental health needs; history and symptoms of brain injury (if applicable) and social networks. SETTING: The sample was drawn randomly from women's prisons (n=10) and a representative range of adult men's prisons (n=11) across England and Wales. PARTICIPANTS: Participants were aged 50 or over and resident in one of the participating prison establishments on the study's census day. MAIN OUTCOME MEASURE: ACE-III. RESULTS: We recruited 596 men and 273 women prisoners. Across the whole sample of older prisoners, the prevalence of dementia was 7.0% (95% CI 5.5%, 8.9%) (when weighted for sex and age), with the highest prevalence found among prisoners aged 70 years and older at 11.8% (95% CI 8.0%, 17.1%). The prevalence of dementia for men was 7.0% (95% CI 5.2%, 9.4%) and for women was 6.0% (95% CI 3.8%, 9.5%). Only two individuals (3%) who screened positively on the MoCA had a diagnosis of dementia in their prison healthcare notes, suggesting current under-recognition. The prevalence of MCI was 0.8% (95% CI 0.4% to 1.7%, weighted by age). Of those who screened positively on the MoCA, 32 (46%) participants had a high or very high risk of harm to self or others, and 70 (35%) had no friends with whom they could talk to about private matters or to call on for help (n=35, 50%). CONCLUSIONS: Approximately 1020 older adults living in prison have symptoms of likely dementia, and service provision for this group is inadequate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".