Younger and Older Adults’ Health Lies to Close Others
Bibliographic record
Abstract
OBJECTIVES: Lying is a common social behavior; however, there is limited research on lying about health and if this differs into later life. This study sought to explore age differences in the frequency of and motivations behind telling health-related lies and if lying differs within romantic and parent/child relationships. METHODS: Younger (N = 158) and older adults (N = 149) reported how often they told general health-related lies, how often they lied about health to their romantic partner and parent or adult child, and why they told health lies. RESULTS: Compared with older adults, younger adults lied more frequently to conceal sickness and pain as well as to feign sickness. Younger adults also told more health lies to their parent than their romantic partner, but older adults lied to their adult child and partner at similar rates. Younger adults reported lying more about their health because they felt ashamed or embarrassed and they worried about what others would think of them compared with older adults. DISCUSSION: These results suggest that health-related honesty may increase in later life and that younger and older adults differ in why they tell health lies. Implications for psychological theory on lying about one's health and health interventions are discussed.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".