» Articles » PMID: 31623620

Psychological Primitives Can Make Sense of Biopsychosocial Factor Complexity in Psychopathology

Overview
Journal BMC Med
Publisher Biomed Central
Specialty General Medicine
Date 2019 Oct 19
PMID 31623620
Citations 7
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Many agree that the biopsychosocial contributions to psychopathology are complex, yet it is unclear how we can make sense of this complexity. One approach is to reduce this complexity to a few necessary and sufficient biopsychosocial factors; although this approach is easy to understand, it has little explanatory power. Another approach is to fully embrace complexity, proposing that each instance of psychopathology is caused by a partially unique set of biopsychosocial factors; this approach has high explanatory power, but is impossible to comprehend. Due to deficits in either explanatory power or comprehensibility, both approaches limit our ability to make substantial advances in understanding, predicting, and preventing psychopathology. Thus, how can we make sense of biopsychosocial factor complexity?

Main Text: There is a third possible approach that can resolve this dilemma, with high explanatory power and high comprehensibility. This approach involves understanding, predicting, and preventing psychopathology in terms of a small set of psychological primitives rather than biopsychosocial factors. Psychological primitives are the fundamental and irreducible elements of the mind, mediating all biopsychosocial factor influences on psychopathology. All psychological phenomena emerge from these primitives. Over the past decade, this approach has been successfully applied within basic psychological science, most notably affective science. It explains the sum of the evidence in affective science and has generated several novel research directions. This approach is equally applicable to psychopathology. The primitive-based approach does not eliminate the role of biopsychosocial factors, but rather recasts them as indeterminate causal influences on psychological primitives. In doing so, it reframes research away from factor-based questions (e.g., which situations cause suicide?) and toward primitive-based questions (e.g., how are suicidality concepts formed, altered, activated, and implemented?). This is a valuable shift because factor-based questions have indeterminate answers (e.g., infinite situations could cause suicide) whereas primitive-based questions have determinate answers (e.g., there are specific processes that undergird all concepts).

Conclusion: The primitive-based approach accounts for biopsychosocial complexity, ties clinical science more directly to basic psychological science, and could facilitate progress in understanding, predicting, and preventing psychopathology.

Citing Articles

Patterns of childhood trauma co-occurrence and its predictivity for suicidality: A machine learning approach.

Niu W, Feng Y, Xu S, Cui X, Ma Z, Wang Y iScience. 2025; 28(2):111877.

PMID: 40041770 PMC: 11876937. DOI: 10.1016/j.isci.2025.111877.


Heterogeneity in momentary affective experiences related to suicidal urges in a non-clinical sample of adult handgun owners and non-owners recruited from the community.

Bryan C, Bozzay M, Tabares J, Daruwala S, Butner J, Gorka S J Affect Disord. 2024; 368:439-447.

PMID: 39299584 PMC: 11560658. DOI: 10.1016/j.jad.2024.09.119.


Understanding suicidal transitions in Australian adults: protocol for the LifeTrack prospective longitudinal cohort study.

Batterham P, Gendi M, Christensen H, Calear A, Shand F, Sunderland M BMC Psychiatry. 2023; 23(1):821.

PMID: 37940886 PMC: 10634090. DOI: 10.1186/s12888-023-05335-1.


Invariance-based causal prediction to identify the direct causes of suicidal behavior.

Goddard A, Xiang Y, Bryan C Front Psychiatry. 2022; 13:1008496.

PMID: 36451770 PMC: 9701748. DOI: 10.3389/fpsyt.2022.1008496.


Does Body Mass Index Confer Risk for Future Suicidal Thoughts and Behaviors? A Meta-analysis of Longitudinal Studies.

Harris L, Broshek C, Ribeiro J Curr Obes Rep. 2022; 11(2):45-54.

PMID: 35174455 DOI: 10.1007/s13679-022-00468-y.


References
1.
Lindquist K, Barrett L . A functional architecture of the human brain: emerging insights from the science of emotion. Trends Cogn Sci. 2012; 16(11):533-40. PMC: 3482298. DOI: 10.1016/j.tics.2012.09.005. View

2.
Lindquist K, Wager T, Kober H, Bliss-Moreau E, Barrett L . The brain basis of emotion: a meta-analytic review. Behav Brain Sci. 2012; 35(3):121-43. PMC: 4329228. DOI: 10.1017/S0140525X11000446. View

3.
Hoemann K, Barrett L . Concepts dissolve artificial boundaries in the study of emotion and cognition, uniting body, brain, and mind. Cogn Emot. 2018; 33(1):67-76. PMC: 6399041. DOI: 10.1080/02699931.2018.1535428. View

4.
Gendron M, Barrett L . Reconstructing the Past: A Century of Ideas About Emotion in Psychology. Emot Rev. 2010; 1(4):316-339. PMC: 2835158. DOI: 10.1177/1754073909338877. View

5.
Touroutoglou A, Lindquist K, Dickerson B, Barrett L . Intrinsic connectivity in the human brain does not reveal networks for 'basic' emotions. Soc Cogn Affect Neurosci. 2015; 10(9):1257-65. PMC: 4560947. DOI: 10.1093/scan/nsv013. View