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Record W4409276882 · doi:10.1080/10888691.2025.2486063

Differences in daily lie-telling patterns from adolescence to older adulthood

2025· article· en· W4409276882 on OpenAlexaff
Angela D. Evans, Victoria W. Dykstra, Alison M. O’Connor

Bibliographic record

VenueApplied Developmental Science · 2025
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsBrock University
Fundersnot available
KeywordsPsychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

The current study cross-sectionally examined daily lie-telling patterns of adolescents, young adults, middle adults, and older adults. Participants (N = 298; Mage = 37.30, SD = 22.51, range = 13–86; 30.5% males) were alerted to complete surveys three times daily about their lie-telling behaviors, including the frequency, the type (self-oriented, other-oriented, or to conform), and the topic of lies told. The frequency of lie-telling was found to significantly differ across age groups suggesting a decrease in lying with age. When examining the types of lies, adolescents and young adults told more self-oriented lies compared to older adults, but no age differences were found for other-oriented lies or lies to conform. The topic of the lie was also found to vary by age, suggesting that age-relevant social goals and contexts may influence lie-telling patterns. Results provide the first comprehensive account of daily lie-telling across adolescence and adulthood.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.018
GPT teacher head0.296
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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