A Comparison of Three Dementia Screening Instruments Administered by Telephone in China
Bibliographic record
Abstract
Implementation of valid and efficient case-finding methods to screen for cognitive impairment is important for identifying people during the earliest stages of dementia. The Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE), Information-Memory-Concentration Test (IMCT), and Blessed-Roth Dementia Scale (BRDS) are assessment tools commonly used in China. This study investigated the usefulness of administering these scales by telephone. Subjects ( N= 132: 74 females, 58 males) from Xuanwu Hospital, Capital University of Medical Sciences in Beijing, China were recruited for participation in this study; 132 collateral informants who accompanied the subjects to their appointments provided IQCODE and BRDS data. Senior neurologists using Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria (American Psychiatric Publishing, 2000), patient history, physical examination, neuropsychological tests, neuroradiology, and laboratory tests made the dementia diagnoses. Blinded personnel administered the IQCODE, IMCT, and BRDS by telephone and face-to-face in the clinic in counter-balanced administration order. Independent subsamples of 20 subjects were selected for assessment of test-retest and inter-rater reliabilities of the telephone assessments. Correlations between the face-to-face and telephone administrations of the scales were good, ranging from .80 to .97. The administration order of assessment methods did not affect the results. Inter-rater and test-retest reliabilities were satisfactory. The sensitivity and specificity of each scale exceeded 80 percent, demonstrating scale validity and clinical utility. The results support reliable and valid administration of these dementia assessments in person or over the telephone. The appropriate selection of assessment instruments is dependent upon the characteristics of the patient population and the intended use of the results. Use of telephone assessments may provide a valid and efficient method to screen elderly people for early detection of dementia symptoms and to monitor the effectiveness of treatment.
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 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 | 0.000 | 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) | 0.001 | 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 teacher head, 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".