The development of lie-telling: the role of executive functioning and theory of mind in children’s prosocial and antisocial lying
Notice bibliographique
Résumé
Lying is a frequent behaviour in our daily interactions and emerges early in children's development.Deceiving others is a cognitively demanding task, as lie-telling has been found to place greater mental demands upon the individual than truth-telling.Although researchers have highlighted the role of cognitive skills on the capacity to tell a lie, these investigations have been limited in scope.Specifically, the majority of inquiries have focused on antisocial lie-telling of preschool and elementary school-aged children; yet children tell various forms of lies (i.e., prosocial and antisocial).Yet observational accounts of parents and researchers have found that children lie much younger than experimentally observed in laboratory settings.However, little empirical research has been conducted on the emergence of children's lie-telling (i.e., lies told prior to 3 years old).As a result, our understanding of children's lie-telling, both the emergence and use of various forms of lies, remains limited in scope.The current dissertation sought to address these gaps in the empirical research.Two manuscripts are included, which together document the role of executive functioning and Theory of Mind (i.e., ToM) in the development of lie-telling.The first manuscript of the dissertation examines the contribution of the executive functioning skills of working memory and inhibitory control to children's ability to tell prosocial lies (i.e., lies told for another individual's benefit).Children's ToM was also investigated in relation to prosocial lying through measures of second-order false-belief understanding.The Stroop and Digit Span tasks were used to measure inhibitory control and working memory.A total of 79 children between the ages of 6 and 12 years old completed a disappointing gift paradigm (i.e., DGP), designed to elicit prosocial lies and to measure children's ability to maintain such lies.Results reveal that children who told prosocial lies had significantly higher CHILDREN'S LIE-TELLING iii scores on measures of working memory and inhibitory control.Those children who were able to maintain their prosocial lies throughout questioning also had significantly higher performance on measures of second-order false-belief.These results provide evidence that prosocial lies are supported through the maturation of both executive functioning and ToM.The second manuscript examines the relation between preschool aged children's rudimentary lies, executive functioning, ToM and conceptual understanding of lies and truths.A total of 65 children between the ages of 2.5 and 3.5 years old participated in a modified temptation resistance paradigm (TRP).To examine executive functioning, children completed measures of inhibitory control and planning.Children's abilities to identify both truths and lies were also examined in relation to their actual lie-telling behaviour.Overall, a total of 29% of young children lied during the TRP.Results revealed significant differences between lie-tellers and truth-tellers on all measures of executive functioning, with lie-tellers having significantly better scores than truth-tellers.Moreover, lie-tellers also had significantly better accuracy in identifying both truths and lies.No significant differences between truth and lie-tellers were found on measures of ToM.As such, the results provide support for the role of executive functioning skills in the emergence of antisocial lie-telling.Taken together, the current research program provides support for a developmental model of lie-telling.Notably, results support the argument that children acquire lie-telling in developmental stages, with rudimentary lies being supported by the executive functioning skills of inhibitory control and planning.With age, executive functioning skills and ToM support other forms of lie-telling (i.e., prosocial), as well as improved lie-telling capacities (i.e., maintenance of lies through control of semantic leakage).
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».