Prospective Mental Images: A Transdiagnostic Approach to Negative Affectivity and Mood Dysregulation among Borderline Personality Disorder and Depression.
Julia KroenerCaroline SchaitzZrinka Sosic-VasicPublished in: Behavioral sciences (Basel, Switzerland) (2024)
There is initial evidence that patients diagnosed with Borderline Personality Disorder (BPD) experience intrusive prospective mental images about non-suicidal self-injury (NSSI). These images, in turn, are associated with the conduct of NSSI. As the negative emotional valence of intrusive images has been established across clinical disorders, negative affectivity might play a key role linking mental imagery and psychopathology. Therefore, the present study aimed to investigate the possible mediating role of symptoms of depression as a proxy for negative affectivity linking intrusive prospective imagery to psychopathology in patients diagnosed with BPD. A total of 233 participants (84 diagnosed with MDD, 66 diagnosed with BPD, 83 healthy controls) completed questionnaires on negative affectivity (BDI-II) and prospective intrusive imagery (IFES-S). Before controlling for negative affectivity, there was a positive correlation between group and intrusive prospective imagery, indicating that healthy participants displayed lower amounts of intrusive prospective images in comparison to patients diagnosed with MDD or BPD. After entering negative affectivity as a mediator, the variable group was no longer associated with intrusive prospective images; however, negative affectivity showed a strong and positive relationship with the group on one side, and intrusive prospective imagery on the other, indicating that negative affectivity mediates the association between intrusive prospective images and clinical disorders. The presented findings point towards a mediating role of negative affectivity in the manifestation of intrusive prospective imagery, not only within BPD, but also in patients with MDD. The possibility of intrusive images acting as a transdiagnostic feature, where negative affectivity and mood dysregulation are at the core of the clinical disorder, are being discussed.
Keyphrases
- deep learning
- end stage renal disease
- convolutional neural network
- optical coherence tomography
- chronic kidney disease
- ejection fraction
- newly diagnosed
- peritoneal dialysis
- major depressive disorder
- mental health
- machine learning
- depressive symptoms
- prognostic factors
- patient reported outcomes
- sleep quality
- living cells
- sensitive detection
- fluorescent probe