Personality types revisited-a literature-informed and data-driven approach to an integration of prototypical and dimensional constructs of personality description.
PLoS One
; 16(1): e0244849, 2021.
Article
en En
| MEDLINE
| ID: mdl-33411758
A new algorithmic approach to personality prototyping based on Big Five traits was applied to a large representative and longitudinal German dataset (N = 22,820) including behavior, personality and health correlates. We applied three different clustering techniques, latent profile analysis, the k-means method and spectral clustering algorithms. The resulting cluster centers, i.e. the personality prototypes, were evaluated using a large number of internal and external validity criteria including health, locus of control, self-esteem, impulsivity, risk-taking and wellbeing. The best-fitting prototypical personality profiles were labeled according to their Euclidean distances to averaged personality type profiles identified in a review of previous studies on personality types. This procedure yielded a five-cluster solution: resilient, overcontroller, undercontroller, reserved and vulnerable-resilient. Reliability and construct validity could be confirmed. We discuss wether personality types could comprise a bridge between personality and clinical psychology as well as between developmental psychology and resilience research.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Personalidad
Tipo de estudio:
Etiology_studies
/
Prognostic_studies
Límite:
Adult
/
Female
/
Humans
/
Male
País/Región como asunto:
Europa
Idioma:
En
Revista:
PLoS One
Asunto de la revista:
CIENCIA
/
MEDICINA
Año:
2021
Tipo del documento:
Article
País de afiliación:
Alemania
Pais de publicación:
Estados Unidos