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The relations between sociotropy and autonomy, positive and negative affect and two proposed depression subtypes
J B Jolly1, M J Dyck, T A Kramer
1Department of Psychology, Mississippi College, Clinton 39058, USA.
The British Journal of Clinical Psychology
|February 1, 1996
Summary
This study explored connections between personality traits like sociotropy and autonomy, and affect states such as positive and negative affect, in depressed patients. Findings suggest sociotropy relates to negative affect, while autonomy links to positive affect, impacting depression subtypes differently.
Area of Science:
- Psychology
- Clinical Psychology
- Personality Psychology
Background:
- Sociotropy (SOC) and autonomy (AUT) represent cognitive/personality models of interpersonal dependence and self-direction.
- Positive affect (PA) and negative affect (NA) describe emotional and personality styles.
- Understanding these constructs is crucial for differentiating depression subtypes.
Purpose of the Study:
- To examine the relationships between SOC/AUT and PA/NA.
- To investigate how these models relate to two proposed depression subtypes.
- To assess the predictive utility of SOC and AUT for depression symptom clusters.
Main Methods:
- The study involved 60 adult outpatients diagnosed with depression.
- Measures assessed sociotropy, autonomy, positive affect, and negative affect.
- Depression symptom clusters were analyzed in relation to personality and affect variables.
Main Results:
- Significant shared variance was found between sociotropy (SOC) and negative affect (NA) scores.
- Facets of autonomy (AUT) showed moderate relationships with low positive affect (PA).
- Autonomous depressive symptoms appeared more specific to depression than sociotropic symptoms.
Conclusions:
- The findings suggest distinct relationships between personality models (SOC/AUT) and affect models (PA/NA) in depressed individuals.
- Autonomous symptoms may be more indicative of depression than sociotropic symptoms.
- The study did not confirm the predictive value of SOC and AUT for symptom clusters, potentially due to measurement limitations.