Automated Author ProfileJ., Jurist
J., Jurist
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.5 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
IntroductionThis secondary analysis of quality control data assessed principal components of personality dysfunction and their relationship to mentalizing in a sample of treatment-seeking women with severe personality disorders.MethodsThe Schedule for Nonadaptive and Adaptive Personality (SNAP) and the Movie for the Assessment of Social Cognition (MASC) were administered to 37 females in routine quality assessments of a specialized residential treatment program. Principal component analysis (PCA) of SNAP scores was used to determine dimensions of personality most significantly contributing to overall maladaptive personality functioning. Bootstrapped stepwise regression tested the relationship of dimensional personality indices to hypermentalizing and hypomentalizing on the MASC controlling for general psychiatric severity.ResultsFour principal components (PCs) explained 71.4% of the variance in personality dysfunction, mapping onto antisocial, obsessive-compulsive, borderline, and narcissistic personality constellations. The borderline and antisocial PCs were positively predictive of hypermentalizing. The obsessive-compulsive PC was positively predictive of hypomentalizing, while the antisocial PC was negatively predictive of hypomentalizing.ConclusionThe study reiterates prior findings of a relationship between hypermentalizing and borderline and antisocial personality profiles. It also contributes evidence to the limited research on hypomentalizing as a clinical indicator and potential treatment target for obsessive-compulsive personality, and provides evidence of a negative relationship between antisocial personality disorder and hypomentalizing. These findings provide clinical indications for enhancing and regulating mentalizing via attention to and interpretations of internal and interpersonal events in individuals with personality disorders. Further research is needed to replicate these associations in larger, more representative clinical samples.
Authors
- J., Jurist ;
- J.M., Traynor ;
- G.E., Murray ;
- B., Ren ;
- S.R., Masland ;
- S., Mermin ;
- K., Meehan ;
- L.W., Choi-Kain
IntroductionThis secondary analysis of quality control data assessed principal components of personality dysfunction and their relationship to mentalizing in a sample of treatment-seeking women with severe personality disorders.MethodsThe Schedule for Nonadaptive and Adaptive Personality (SNAP) and the Movie for the Assessment of Social Cognition (MASC) were administered to 37 females in routine quality assessments of a specialized residential treatment program. Principal component analysis (PCA) of SNAP scores was used to determine dimensions of personality most significantly contributing to overall maladaptive personality functioning. Bootstrapped stepwise regression tested the relationship of dimensional personality indices to hypermentalizing and hypomentalizing on the MASC controlling for general psychiatric severity.ResultsFour principal components (PCs) explained 71.4% of the variance in personality dysfunction, mapping onto antisocial, obsessive-compulsive, borderline, and narcissistic personality constellations. The borderline and antisocial PCs were positively predictive of hypermentalizing. The obsessive-compulsive PC was positively predictive of hypomentalizing, while the antisocial PC was negatively predictive of hypomentalizing.ConclusionThe study reiterates prior findings of a relationship between hypermentalizing and borderline and antisocial personality profiles. It also contributes evidence to the limited research on hypomentalizing as a clinical indicator and potential treatment target for obsessive-compulsive personality, and provides evidence of a negative relationship between antisocial personality disorder and hypomentalizing. These findings provide clinical indications for enhancing and regulating mentalizing via attention to and interpretations of internal and interpersonal events in individuals with personality disorders. Further research is needed to replicate these associations in larger, more representative clinical samples.
Authors
- J., Jurist ;
- J.M., Traynor ;
- G.E., Murray ;
- B., Ren ;
- S.R., Masland ;
- S., Mermin ;
- K., Meehan ;
- L.W., Choi-Kain