Association between subjective credulity assessment and judging deception in older adults
Bibliographic record
Abstract
BACKGROUND: The work is relevant, given the increasing proportion of older adults worldwide, as well as the growing rates of crimes against older people, notably phone fraud. AIM: The work aimed to assess the association between subjective credulity assessment and judging deception in older adults. METHODS: The study was conducted at the Russian Research and Clinical Center for Gerontology. It included three stages: assessing the actual ability to detect deception; subjective credulity assessment; and assessing the association between judging deception and subjective credulity. The study included 60 older participants (60–75 years, n = 36; 76–90 years, n = 24). Inclusion criteria were as follows: preserved neurocognitive function; absence of severe chronic medical conditions and mental disorders; preserved analytical capability; and no history of cerebrovascular accidents. The following assessment tools were used: Montreal Cognitive Assessment (MoCA); Pragmatic Interpretation Short Stories Winner’s Task (modified by Kolesova and Sergienko); Dembo–Rubinstein test; and UCLA Loneliness Scale (by Russell, Peplau, and Ferguson). Descriptive, comparative, correlation, and multivariate statistics were used for quantitative assessment. RESULTS: No significant relationships were found when examining the association between subjective credulity assessment and judging deception in older adults. However, following factorization, approximately 40% of participants were found to misjudge their ability to detect deception, irrespective of the actual accuracy of deception judgments. CONCLUSION: The two groups of older adults (60–75 years and 76–90 years) showed comparable ability to detect deception. Low ability to detect deception in these age groups is related to increased credulity and low subjective assessment of own mental capacity.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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; both teacher heads agree on what is shown here.
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".