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Mann FD, Cuevas AG, Clouston SAP, Freilich CD, Krizan Z, Zuber S, Wänström L, Muniz-Terrera G, O'Keefe P, Voll S, Hofer S, Rodgers JL, Krueger RF. A novel approach to model cumulative stress: Area under the s-factor curve. Soc Sci Med 2024; 348:116787. [PMID: 38547807 PMCID: PMC11186517 DOI: 10.1016/j.socscimed.2024.116787] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 02/06/2024] [Accepted: 03/12/2024] [Indexed: 04/26/2024]
Abstract
OBJECTIVE Using a large longitudinal sample of adults from the Midlife in the United States (MIDUS) study, the present study extended a recently developed hierarchical model to determine how best to model the accumulation of stressors, and to determine whether the rate of change in stressors or traditional composite scores of stressors are stronger predictors of health outcomes. METHOD We used factor analysis to estimate a stress-factor score and then, to operationalize the accumulation of stressors we examined five approaches to aggregating information about repeated exposures to multiple stressors. The predictive validity of these approaches was then assessed in relation to different health outcomes. RESULTS The prediction of chronic conditions, body mass index, difficulty with activities of daily living, executive function, and episodic memory later in life was strongest when the accumulation of stressors was modeled using total area under the curve (AUC) of estimated factor scores, compared to composite scores that have traditionally been used in studies of cumulative stress, as well as linear rates of change. CONCLUSIONS Like endogenous, biological markers of stress reactivity, AUC for individual trajectories of self-reported stressors shows promise as a data reduction technique to model the accumulation of stressors in longitudinal studies. Overall, our results indicate that considering different quantitative models is critical to understanding the sequelae and predictive power of psychosocial stressors from midlife to late adulthood.
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Affiliation(s)
- Frank D Mann
- Program in Public Health, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA; Family, Population, and Preventive Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA.
| | - Adolfo G Cuevas
- Department of Social and Behavioral Sciences Department, School of Global Public Health at New York University, Manhattan, NY, USA
| | - Sean A P Clouston
- Program in Public Health, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA; Family, Population, and Preventive Medicine, Renaissance School of Medicine at Stony Brook University, Stony Brook, NY, USA
| | - Colin D Freilich
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Zlatan Krizan
- Department of Psychology, Iowa State University, Ames, IA, USA
| | - Sascha Zuber
- Institute of Aging and Lifelong Health, University of Victoria, Victoria, BC, V8N 1V8, Canada; Geneva Aging Research Center at University of Geneva, Geneva, Switzerland
| | - Linda Wänström
- Department of Computer and Information Science, Linköping University, 581 83, Linköping, Sweden
| | - Graciela Muniz-Terrera
- Ohio University Heritage College of Osteopathic Medicine (OUHCOM), Dublin, OH, 43016, USA; Edinburgh Dementia Prevention, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Patrick O'Keefe
- Department of Neurology, Oregon Health and Science University, Portland, OR, 97239, USA
| | - Stacey Voll
- Institute of Aging and Lifelong Health, University of Victoria, Victoria, BC, V8N 1V8, Canada
| | - Scott Hofer
- Institute of Aging and Lifelong Health, University of Victoria, Victoria, BC, V8N 1V8, Canada; Department of Neurology, Oregon Health and Science University, Portland, OR, 97239, USA
| | - Joseph L Rodgers
- Department of Psychology and Human Development, Vanderbilt University, Nashville, TN, 37232, USA
| | - Robert F Krueger
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
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Rossi G, Diaz-Batanero C. Differentiation of Self and Interpersonal Functioning with the Level of Personality Functioning Scale - Brief Form 2.0. J Pers Assess 2024; 106:60-71. [PMID: 37306356 DOI: 10.1080/00223891.2023.2218931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 05/17/2023] [Indexed: 06/13/2023]
Abstract
Research on Criterion A of the alternative model for personality disorders is recently expanding and provides mixed results concerning the unidimensional operational definition of severity by the model, characterized by impaired self (identity and self-direction) and interpersonal (empathy and intimacy) functioning. Studies resulted in one, as well as two or more factor structures. The present study demonstrated the importance of the structural and relational differentiation of self and interpersonal dimensions of personality functioning. One thousand seventy-four participants (community and clinical mixed sample) completed the Level of Personality Functioning Scale - Brief Form 2.0 (LPFS-BF 2.0), the Personality Inventory for DSM-5 Short Form and the Questionnaire for the World Health Organization Disability Assessment. An LPFS-BF 2.0 two-factor structure with self and interpersonal functioning factors was corroborated by confirmatory factor analyses and bifactor modeling. Joint Exploratory Factor Analysis of the LPFS-BF 2.0 domains with maladaptive personality domains clearly differentiated the personality functioning factors. While the self-functioning factor was more closely linked to negative affect (and to disinhibition and psychoticism), the interpersonal functioning factor connected to detachment. Self-functioning predicted functional impairment along and beyond personality domains. The LPFS-BF 2.0 appears a useful tool for clinical routine monitoring of both self and interpersonal functioning.
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Affiliation(s)
- Gina Rossi
- Personality and Psychopathology Research Group (PEPS), Department of Psychology, Vrije Universiteit Brussel (VUB), Belgium
| | - Carmen Diaz-Batanero
- Department of Clinical and Experimental Psychology, University of Huelva, Spain
- Mental health and drug use, Research Center for Natural Resources, Health and the Environment, University of Huelva, Spain
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