Intergenerational transmission of personality disorder: general or disorder-specific?

ABSTRACT

This study investigates intergenerational relationships between the father’s personality disorder (PD) traits and the PD traits of his male and female offspring. We examine whether the intergenerational transmission of PD is due to the father transmitting a general vulnerability to all PDs, or whether the transmission is more specific to particular PDs. Structural Equation Modelling techniques are used to investigate a hypothesised model, based on Livesley’s [(2007). A framework for integrating dimensional and categorical classifications of personality disorder. Journal of Personality Disorders, 21(2), 199–224. https://doi.org/10.1521/pedi.2007.21.2.199] conceptualisation, which reorganises the DSM PD traits into four dimensions: Emotional Dysregulation, Dissocial Behaviour, Inhibitedness, and Compulsivity. General and specific transmission effects are examined for each model. The data comes from the Cambridge Study in Delinquent Development, a large-scale prospective longitudinal survey of 411 males and their biological offspring. Findings revealed that the intergenerational transmission of PD traits from fathers to female offspring appeared to be both general and disorder-specific. Firm conclusions could not be drawn about the intergenerational transmission of PD traits from fathers to male offspring, as the data did not fit the hypothesised model.

KEYWORDS:

• Intergenerational transmission
• Personality disorders
• Longitudinal studies
• DSM
• structural equation modeling

Acknowledgements

The authors wish to thank all the families involved in the CSDD.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 The APA Dictionary of Psychology defines a Heywood case as ‘any correlation coefficient, regression coefficient, factor loading, or similar parameter estimate having a value that is impossible or very rare (e.g., a negative error variance estimate). Heywood cases may indicate any of the following: a sample that is too small to adequately estimate the parameters; data that do not have a normal distribution or that contain outliers; a misspecified model that is not appropriate for the data; or a parameter whose true value is so close to a boundary (e.g., 1 or 0) in the population that its estimate exceeded this limit due to sampling fluctuation’ (VandenBos, 2015). See also Heywood and Filon (1931).

Additional information

Funding

This research was made possible by grants from the UK Home Office, the UK Department of Health and Social Care, the UK Department for Education, the Rayne Foundation, the Barrow Cadbury Trust and the Smith Richardson Foundation.