Cost‐benefit and discriminant validity of a stepwise dementia case‐finding approach in an Asian older adult community
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Case-finding is a recommended approach for dementia early detection in the community. Aims: To investigate the discriminant validity and cost-effectiveness of a stepwise dementia case-finding approach in a Singaporean older adult community. Methods: The two-phase study was conducted in the community from 2009 to 2015 in Singapore. A total of 3780 participants (age ≥60 years) completed phase I (a brief cognitive screening); 918 completed phase II and were included in the final analysis. In phase I, all participants were administered the Abbreviated Mental Test (AMT) and the Progressive Forgetfulness Question (PFQ). Those who screened positive on either test were invited to phase II, whereby the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA) and a formal neuropsychological battery were administered, followed by the research diagnosis of no cognitive impairment, cognitive impairment no dementia (CIND)-Mild (≤2 impaired cognitive domains), CIND-Moderate (>2 impaired domains) or dementia. Receiver operating characteristic curve analyses were conducted for the different cognitive instruments. All discriminant indices were calculated, including sensitivity, specificity, positive and negative predictive values (NPV) and accuracy. Cost-effectiveness analysis was conducted by estimating the amount of screening time needed and the number of older adults requiring re-evaluation in two case-finding scenarios, ie, with or without preselection by the PFQ. Results: The stepwise case-finding approach (preselection by the PFQ, then MMSE or MoCA or AMT) showed an excellent NPV (>99%) and accuracy (>86%) for excluding dementia-free cases. Without preselection by the PFQ, screening time for the three cognitive tools were 317.5, 317.5 and 254 hours, with 159, 302 and 175 screen-positive older adults involved in further evaluation. By adopting the stepwise case-finding approach, total screening time were 156.5, 156.5 and 126.2 hours, which decreased by 50.7%, 50.7% and 50.3% as compared with those without preselection. Furthermore, after preselection, only 98, 167 and 145 screen-positive older adults required further evaluation, corresponding to a reduction of 38.4%, 44.7% and 17.1% in the numbers compared with those without preselection. Conclusions: A stepwise approach for dementia case-finding should be implemented in the community to minimise the time and resources needed for large-scale early detection of dementia.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it