Roser Granero
Isabel Krug
Susana Jiménez-Murcia- 1Department of Psychobiology and Methodology, Universitat Autònoma de Barcelona - UAB, Barcelona, Spain
- 2Ciber Fisiopatología Obesidad y Nutrición (CIBERobn), Instituto Salud Carlos III, Madrid, Spain
- 3Psychoneurobiology of Eating and Addictive Behaviors Group, Neuroscience Program, Institut d'Investigació Biomèdica de Bellvitge - IDIBELL, l'Hospitalet de Llobregat, Spain
- 4Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, VIC, Australia
- 5Department of Psychiatry, Hospital Universitari de Bellvitge, L'Hospitalet de Llobregat, Spain
- 6Department of Clinical Sciences, School of Medicine, Universitat de Barcelona - UB, L'Hospitalet de Llobregat, Spain
Editorial on the Research Topic
New advancement in network and path-analysis approaches for the study of disorders within the impulse-compulsive spectrum disorders
Conceptualization of the impulsive-compulsive disorders spectrum
The reference taxonomies in the clinical and research settings [the Diagnostic and Statistical Manual of Mental Disorders DSM-5 (1) and the International Classification of Diseases ICD-11 (2)], define the impulsive-compulsive disorder spectrum (ICDS) as a range of diverse separated diagnostic categories. These categorical classifications are essentially based on the classical biological model, consider each disorder within the ICDS as a different nosological unit, and assume the existence of a latent underlying process as the cause of the pattern of symptoms (described in a criteria list). The rationale for defining the ICDS as a group of distinct symptom structures and clinical endo-phenotypes is the presence of repetitive behaviors (in some cases ritualistic actions) with reduced control to inhibit actions, even in the presence of severe negative consequences and harms (3, 4). Patients within the ICDS perceive their problematic behaviors as urgent and irresistible, and experience pleasurable feelings while carrying out these actions (5). Other common characteristics are age of onset variation between childhood to young adulthood, fluctuating lifelong course, extensive impact on the quality of life, and comorbid associations with diverse psychiatric conditions. Common neurobiological processes have also been associated to the onset and the progression of the diverse disorders within the ICDS (6), such as changes in the dopaminergic system of a mesocorticolimbic circuit, the so-called reward system (which involves different areas in the midbrain).
Epidemiological studies warn that clinical conditions under the ICDS may be underdiagnosed within clinical and population-based samples. The complex health states and the multiple inter-related symptoms could not be spontaneously reported by patients (because they perceive shame or fear due to the social stigma, or even because they do not know that the symptoms can be effectively treated) (7–9). On other occasions the symptoms identified are attributed to the presence of a concrete disorder, and likely comorbid conditions are not assessed (and therefore, neglected).
New methodological research approaches for the study of ICDS
The empirical evidence sustaining separate categorical taxonomies grouped within the ICDS is largely based on statistical procedures such as general/generalized linear models and classification procedures (cluster analysis and latent class analysis). But arguments against classical categorical taxonomies exist, and alternative problem-oriented systems support that the diverse endo-phenotypes grouped into wide ranges such as the ICDS are better embedded through myriads of multivariable inter-connected systems. These alternative models contemplate mutually interacting-dynamic biological, psychological, inter-personal and contextual impacts on the individuals' health. In addition, these alternative systems suppose that boundaries between diagnostic entities may be not clearly defined, and that these fuzzy limits are better explained through the presence of potential transdiagnostic characteristics and/or patterns of symptoms (10). Path-analysis and network analysis are statistical approaches that can contribute to the development of these new diagnostic formulations, through powerful tools for examining and visualizing complex structures in a more realistic way than classical procedures (11).
Path-analysis is aimed to examine a set of simultaneous relationships between variables and estimating the magnitude and significance of direct and indirect effects (meditational links). This approach has been historically used to test a theoretical model with causal relationships between variables (12). But current studies use path-analysis for both exploratory and confirmatory modeling, and therefore it is now employed to theory testing and theory development (13). Path-analysis is usually implemented as a case of structural equation modeling (14), and it is visualized through path-diagrams. The model specification (rationale for the underlying paths) is based on the cumulate empirical evidence.
Network analyses employ tools from Graph Theory aimed to characterize spatial/functional structures between the nodes (15–17), which represent the patterns of relationships among symptoms (18). In medical clinical research, network structures are visualized through diagrams based on nodes (plotted as circles which are the representation of the symptoms and/or other features of the endo-phenotypes) and edges (plotted as connector-lines which characterize the associations between the nodes) (19–23). Concepts related to the network analysis are centrality (identification of the key symptoms associated to the onset, the severity and the progression of the clinical profiles) and closeness (identification of the linkage or transition capacity of the nodes, particularly useful for the study of the pathways to comorbid conditions) (22, 24–27).
Motivation for this Research Topic
The manuscripts included in this Research Topic provide new empirical evidence (obtained through diverse methodological approaches (including path-analysis and network analysis), that contribute to a better understanding of the onset, the progression, and the structure of the diverse endo-phenotypes within the ICDS.
One study of this Research Topic is aimed to test the validity of the neuroscientific theory on the dominance of compulsivity over impulsivity in severe cases of behavioral addictions, including gambling disorder, internet gaming, exercise dependence, compulsive buying, and hair-pulling (Demetrovics et al.). The data collected from a large population-based sample (n = 2,710) show that compulsivity dominates over impulsivity in the more severe symptomatic states of the behavioral addictions, which could be interpreted as a shift from reward-driven to relief-driven and habitual behavior in the disease course. This process seems congruent with findings in animal models of addiction based on neuroscientific evidence.
Other work of this topic focused on the incentive sensitization theory is aimed to test the dissociation between “wanting” and “liking” across different substance related disorders (including alcohol, nicotine, cannabis, and other drugs) and addictive behaviors (gambling disorder, overeating, gaming, pornography use, sex, social media use, Internet use, TV-series watching, shopping, and work) (File et al.). The results of a path-analysis provide support about the role of incentive sensitization in both potentially problematic substance use and behavioral addictions. Interesting, the structural equation model also suggests that impulsivity might not be directly associated with problematic engagement in substance use and problematic addictive behaviors, but indirect impacts emerge through the meditational role of “wanting.”
A third work in this Research Topic uses path-analysis for assessing the associations between diverse impulsivity measures (including self-reported, behavioral data and the experiential discounting task) with compulsivity measures (registered through neuropsychological tools) (Mestre-Bach et al.). The results obtained among a clinical sample of gambling disorder patients (n = 132) show that the gambling severity levels are differently explained by the diverse aspects of impulsivity and compulsivity. And this specific outcome reinforces the idea that impulsivity and compulsivity constitute two multifactorial constructs with distinct impacts on the gambling profiles.
Other three studies included in this Research Topic are aimed to obtain evidence regarding the underlying relationships among a set of symptoms covering different constructs related to the ICDS. The manuscript of González-Bueso et al. obtains differences in the sexual behaviors and other sociodemographic and clinical variables between patients with online-compulsive sexual behavior (OCSB, n = 36) vs. non-online compulsive sexual behavior (non-OCSB, n = 44). Compared with a healthy control group, both clinical sub-samples show worse psychopathology state, higher harm avoidance and self-transcendence levels, and lower self-directness and cooperativeness. Compared to OCSB, non-OCSB patients also exhibit higher likelihood of sexually transmitted diseases, higher odds of homosexual and bisexual orientation, higher anxiety levels and more difficulties in sexual impulse control.
The study of Reivan Ortiz et al. uses path-analysis for testing a meditational model explaining the perfectionism level among a clinical sample of patients who met diagnostic criteria for anorexia nervosa, bulimia nervosa and obsessive-compulsive disorder (n = 187). The results of this work show a direct effect of the preoccupation with errors and goals manage on the perfectionism score, as well as an indirect effect mediated by the emotion (dys)regulation severity. In addition, invariance by the diagnostic subtype is achieved, and this concrete outcome is interpreted as evidence about the role of the perfectionism construct as a non-adaptive criterion that exacerbates the symptom level related with eating disorders and obsessive-compulsive disorders.
The last manuscript of this Research Topic, the study of Cascino et al. investigates the association of the eating disorders key symptoms and other psychological measures (including aggressiveness) through network analysis, among a clinical sample of women with bulimia nervosa (n = 69). In this work, interceptive awareness and ineffectiveness are the nodes with the highest centrality in the network composed by the eating disorder symptoms, while guilt is the only negative emotion with bi-directionally associations within the eating problems. Likewise, verbal hostility and resentment are the highly central nodes in the network profile defined by the hostility measures. And the variables with the higher bridge strength centrality in a network defined with the complete phenotype were impulsivity, drive for thinness, ascetism, guilt and hostility.
Conclusion
The results obtained in the studies collected in this Research Topic are consistent with previous research, which suggest the relevant role of impulsivity within ICDS. Impulsivity constitutes a complex multifaceted psychological construct, strongly related with the difficulties in the control of thoughts and behaviors: individuals with high impulsivity levels show speedy responses with low reflection, despite possible negative consequences and harms (28). Impulsivity has also been conceptualized as an endophenotype of vulnerability and a transdiagnostic feature, characterized by patterns of risky health-related decision-making, that can be displayed as a temporary state and/or a generalized trait over time and across contexts that may contribute to multiple psychiatric disorders (29, 30). For example, a current systematic review and voxel-based meta-analysis focused on the relationships between brain morphology and trait impulsivity, has identified impulsivity-related volumetric gray matter alterations in prefrontal, temporal, and parietal cortices, as well as interaction effects of age and gender (31). Within the ICDS, neurobiological basis of impairment in some executive functions have been related to behavioral inhibition and impulsivity (32). Adequate executive functioning is a requisite to achieve an adequate adaptation to the environment and its demands, and includes diverse multiple neurological processes located in the prefrontal lobes and subcortical connections: reasoning, planning, decision-making, organization, flexibility, inhibition, working memory, and monitoring. Compared to healthy controls, ICDS patients have been found to exhibit deficits on neurocognitive domains involving attention, verbal and visual memory, visual-spatial abilities, shifting capacity, top-down control, and flexible responding (33, 34). Moreover, neuroimaging studies have observed changes in the activity in the orbitofrontal cortex and ventral striatum in discounting tasks (a measure of the impulsivity related to disinhibition and impaired reward sensitivity). Compared to healthy-control samples, patients within ICDS exhibit increased risk taking/probability discounting (e.g., choosing larger but less probable rewards instead of smaller but more probable ones), and altered delay discounting (e.g., choosing immediate smaller rewards over delayed larger ones) (35, 36).
Studies collected in this Research Topic also provide evidence regarding the different role of the compulsive vs. the impulsive processes in the disorders within the ICDS, and this precise difference is reflected in the form of a compulsive-impulsive continuum (37). One side of the continuum includes disorders with a compulsive nature (i.e., obsessive-compulsive disorder, anorexia nervosa, body dysmorphic disorder and hypochondria), while the other side of the continuum comprises disorders with an impulsive component i.e., behavioral addictions (i.e., gambling disorder, gaming addiction, compulsive buying-shopping, and sex addiction) and eating disorders with binge-purging symptomatology (i.e., bulimia nervosa and binge eating disorder). Individuals with the compulsive types of disorders normally avoid potential risk and seek security, mainly because they perceive high harm avoidance and are unable to resist the need for decreasing anxiety and distress levels (38). Conversely, the impulsive type of mental illnesses are characterized by the incapacity of patients for adequately estimating the probability and the severity of risky actions, as well as the potential harms and negative consequences of these actions (39).
In relation to the above, deficits in the impulse control processes are characteristics in all the conditions within the ICDS (40, 41), but drive for impulsivity differs amongst the two continuums: while impulsive-repetitive behaviors are the result of risk taking (seeking pleasure) during the initial stages for patients with impulsive related disorders, risk avoidance (decreasing negative mood states, anxiety and distress) is the basis of uncontrolled behaviors among patients with compulsive related disorders (37, 42). The conceptualization of a common spectrum also assumes that the different/opposite systems sustaining compulsive and impulsive behaviors can co-exist in the same patients throughout the progression of the diseases (longitudinal comorbidity) (43). In fact, although impulse related disorders are characterized by the pursuit of gratification or reward, as has been mentioned, in many cases it occurs only in the short term. Moreover, this immediate gratification disappears as the condition progresses (44). Studies also suggest that impulsivity and compulsivity may be considered as a phenomenological and comorbid overlap, in the sense that they both imply core problems with top-down inhibitory control (33, 40).
Implications
The new evidence-based knowledge revealed by the studies grouped in this Research Topic can contribute to adapt and develop new assessment tools, with high sensitivity to identify the presence of the diverse symptoms and signs connected to the ICDS. Results can also contribute to improve and create precise treatment tools, for a careful monitoring of the multiple behaviors-domains of patients within the ICDS (the interventions should be adapted to the specific needs of each patient).
Other research fields can also contribute to develop new non-invasive quantitative procedures to identify networks of structural and functional brain changes in patient within the ICDS. For example, into the psychoradiology area, an emerging field that applies radiological imaging techniques to the study of mental illness (45, 46), with the aim to provide a new basis for transform the diagnostic task from a set of separate symptom-based syndromes to an imaging-based taxonomy (47). Ultimately, efficient prevention and intervention of ICDS rely in a good understanding of how the diverse pathological processes develop.
Author contributions
All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.
Funding
This editorial was funded from Ministerio de Ciencia, Innovación y Universidades (grant RTI2018-101837-B-100). FIS PI20/132, FIS PI17/01167 received aid from the Instituto Salud Carlos III (Ministerio de Sanidad, Servicios Sociales e Igualdad). The research was also funded by the Delegación del Gobierno para el Plan Nacional sobre Drogas (2019I47 and 2021I031), CIBER Fisiología Obesidad y Nutrición (CIBERobn) is an initiative of ISCIII. We thank CERCA Programme/Generalitat de Catalunya for institutional support. Fondo Europeo de Desarrollo Regional (FEDER) Una manera de hacer Europa/A way to build Europe. RG was supported by the Catalan Institution for Research and Advanced Studies (ICREA-Academia, 2021-Programme). The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
1. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders (5th ed.). (2013). doi: 10.1176/appi.books.9780890425596
2. World Health Organization. ICD-11: International Classification of Diseases (11th revision). (2019). Available online at: https://icd.who.int/
3. Berlin GS, Hollander E. Compulsivity, impulsivity, and the DSM-5 process. CNS Spectr. (2014) 19:62–8. doi: 10.1017/S1092852913000722
4. Stahl C, Voss A, Schmitz F, Nuszbaum M, Tüscher O, Lieb K, et al. Behavioral components of impulsivity. J Experi Psychol Gene. (2014) 143:850–86. doi: 10.1037/a0033981
5. Weinstein A, Mezig H, Mizrachi S, Lejoyeux M. A study investigating the association between compulsive buying with measures of anxiety and obsessive–compulsive behavior among internet shoppers. Compr Psychiatry. (2015) 57:46–50. doi: 10.1016/j.comppsych.2014.11.003
6. Grant JE, Kim SW. Brain circuitry of compulsivity and impulsivity. CNS Spectrum. (2014) 19:21–7. doi: 10.1017/S109285291300028X
7. García-Soriano G, Rufer M, Delsignore A, Weidt S. Factors associated with non-treatment or delayed treatment seeking in OCD sufferers: a review of the literature. Psychiatry Res. (2014) 220:1–10. doi: 10.1016/j.psychres.2014.07.009
8. Parra-Díaz P, Chico-García JL, Beltrán-Corbellini Á, Rodríguez-Jorge F, Fernández-Escandón CL, Alonso-Cánovas A, et al. Does the country make a difference in impulse control disorders? A systematic review. Movement Disord Clin Pract. (2020) 8:25–32. doi: 10.1002/mdc3.13128
9. Schulte J, Schulz C, Wilhelm S, Buhlmann U. Treatment utilization and treatment barriers in individuals with body dysmorphic disorder. BMC Psychiatry. (2020) 20:69. doi: 10.1186/s12888-020-02489-0
10. McNally RJ. Can network analysis transform psychopathology? Behav Res Ther. (2016) 86:95–104. doi: 10.1016/j.brat.2016.06.006
11. Boschloo L, van Borkulo CD, Rhemtulla M, Keyes KM, Borsboom D, Schoevers RA. The network structure of symptoms of the diagnostic and statistical manual of mental disorders. PLoS ONE. (2015) 10:e0137621. doi: 10.1371/journal.pone.0137621
12. Kline RB. Principles and Practice of Structural Equation Modeling (2nd Edition ed.). New York, NY: The Guilford Press (2005).
13. MacCallum RC, Austin JT. Applications of structural equation modeling in psychological research. Annu Rev Psychol. (2000) 51:201–26 doi: 10.1146/annurev.psych.51.1.201
14. von Oertzen T. Power equivalence in structural equation modelling. Br J Math Stat Psychol. (2010) 62:257–72. doi: 10.1348/000711009X441021
15. Borsboom D. A network theory of mental disorders. World Psychiatry. (2017) 16:5–13. doi: 10.1002/wps.20375
16. Borsboom D, Cramer A, Kalis A. Brain disorders? Not really: Why network structures block reductionism in psychopathology research. Behav Brain Sci. (2018) 42:e2. doi: 10.1017/S0140525X17002266
17. Borsboom D, Cramer AOJ. Network analysis: an integrative approach to the structure of psychopathology. Annu Rev Clin Psychol. (2013) 9:91–121. doi: 10.1146/annurev-clinpsy-050212-185608
18. Barabási AL, Gulbahce N, Loscalzo J. Network medicine: a network-based approach to human disease. Nat Rev Genet. (2011) 12:56–68. doi: 10.1038/nrg2918
19. Borgatti SP, Mehra A, Brass DJ, Labianca G. Network analysis in the social sciences. Science. (2009) 323:892–5. doi: 10.1126/science.1165821
20. Bringmann LF, Vissers N, Wichers M, Geschwind N, Kuppens P, Peeters F, et al. A network approach to psychopathology: new insights into clinical longitudinal data. PLoS ONE. (2013) 8:e60188. doi: 10.1371/journal.pone.0060188
21. Clifton A, Webster G. An introduction to social network analysis for personality and social psychologists. Soc Psychol Personal Sci. (2017) 8:442–53. doi: 10.1177/1948550617709114
22. Cramer AOJ, Waldorp LJ, van der Maas HLJ, Borsboom D. Comorbidity: a network perspective. Behav Brain Sci. (2010) 33:137–93. doi: 10.1017/S0140525X09991567
23. Hevey D. Network analysis: a brief overview and tutorial. Health Psychol Behav Med. (2021) 6:301–28. doi: 10.1080/21642850.2018.1521283
24. Braun U, Schaefer A, Betzel RF, Tost H, Meyer-Lindenberg A, Bassett DS. From maps to multi-dimensional network mechanisms of mental disorders. Neuron. (2018) 97:14–31. doi: 10.1016/j.neuron.2017.11.007
25. Epskamp S, van Borkulo CD, van der Veen DC, Servaas MN, Isvoranu AM. Personalized network modeling in psychopathology: the importance of contemporaneous and temporal connections. Clin Psychol Sci. (2018) 6:416–27. doi: 10.1177/2167702617744325
26. Fried EI, van Borkulo CD, Cramer AOJ, Boschloo L, Schoevers RA, Borsboom D. Mental disorders as networks of problems: a review of recent insights. Soc Psychiatry Psychiatr Epidemiol. (2017) 52:1–10. doi: 10.1007/s00127-016-1319-z
27. Fried EI, Cramer AOJ. Moving forward: challenges and directions for psychopathological network theory and methodology. Perspect Psychol Sci. (2017) 12:999–1020. doi: 10.1177/1745691617705892
28. Belin-Rauscent A, Daniel ML, Puaud M, Jupp B, Sawiak S, Howett D, et al. From impulses to maladaptive actions: the insula is a neurobiological gate for the development of compulsive behavior. Mol Psychiatry. (2016) 21:491–9. doi: 10.1038/mp.2015.140
29. Devoe DJ, Anderson A, Bahji A, Singh M, Patten SB, Soumbasis A, et al. The prevalence of impulse control disorders and behavioral addictions in eating disorders: a systematic review and meta-analysis. Front Psychiatry. (2022) 12:724034. doi: 10.3389/fpsyt.2021.724034
30. Esteves M, Moreira PS, Sousa N, Leite-Almeida H. Assessing impulsivity in humans and rodents: taking the translational road. Front Behav Neurosci. (2021) 15:647922. doi: 10.3389/fnbeh.2021.647922
31. Pan N, Wang S, Zhao Y, Lai H, Qin K, Li J, et al. Brain gray matter structures associated with trait impulsivity: A systematic review and voxel-based meta-analysis. Hum Brain Mapp. (2021) 42:2214–35. doi: 10.1002/hbm.25361
32. Bari A, Robbins TW. Inhibition and impulsivity: behavioral and neural basis of response control. Prog Neurobiol. (2013) 108:44–79. doi: 10.1016/j.pneurobio.2013.06.005
33. Dalley JW, Everitt BJ, Robbins TW. Impulsivity, compulsivity, and top-down cognitive control. Neuron. (2011) 69:680–94. doi: 10.1016/j.neuron.2011.01.020
34. Morein-Zamir S, Papmeyer M, Pertusa A, Chamberlain SR, Fineberg NA, Sahakian BJ, et al. The profile of executive function in OCD hoarders and hoarding disorder. Psychiatry Res. (2014) 215:659–67. doi: 10.1016/j.psychres.2013.12.026
35. Probst CC, van Eimeren T. The functional anatomy of impulse control disorders. Curr Neurol Neurosci Rep. (2013) 13:386. doi: 10.1007/s11910-013-0386-8
36. Wang Q, Chen C, Cai Y, Li S, Zhao X, Zheng L, et al. Dissociated neural substrates underlying impulsive choice and impulsive action. Neuroimage. (2016) 134:540–9. doi: 10.1016/j.neuroimage.2016.04.010
37. Robbins TW, Gillan CM, Smith DG, de Wit S, Ersche KD. Neurocognitive endophenotypes of impulsivity and compulsivity: towards dimensional psychiatry. Trends Cognit Sci. (2012) 16:81–91. doi: 10.1016/j.tics.2011.11.009
38. Mattina GF, Slyepchenko A, Steiner M. Obsessive-compulsive and related disorders. Handb Clin Neurol. (2020) 175:369–86. doi: 10.1016/B978-0-444-64123-6.00025-4
39. Dalley JW, Robbins TW. Fractionating impulsivity: Neuropsychiatric implications. Nat Rev Neurosci. (2017) 18:158–71. doi: 10.1038/nrn.2017.8
40. Fineberg NA, Chamberlain SR, Goudriaan AE, Vanderschuren LJ, Gillan CM, Shekar S, et al. New developments in human neurocognition: clinical, genetic, and brain imaging correlates of impulsivity and compulsivity. CNS Spectr. (2014) 19:69–89. doi: 10.1017/S1092852913000801
41. Leeman RF, Rowland B, Gebru NM, Potenza MN. Relationships among impulsive, addictive and sexual tendencies and behaviours: a systematic review of experimental and prospective studies in humans. Philos Transact R Soc London. (2019) 374:20180129. doi: 10.1098/rstb.2018.0129
42. Chamberlain SR, Leppink EW, Redden SA, Grant JE. Are obsessive-compulsive symptoms impulsive, compulsive or both? Compr Psychiatry. (2016) 68:111–8. doi: 10.1016/j.comppsych.2016.04.010
43. Miquel M, Nicola SM, Gil-Miravet I, Guarque-Chabrera J, Sanchez-Hernandez A. A Working hypothesis for the role of the cerebellum in impulsivity and compulsivity. Front Behav Neurosci. (2019) 13:99. doi: 10.3389/fnbeh.2019.00099
44. el-Guebaly N, Mudry T, Zohar J, Tavares H, Potenza MN. Compulsive features in behavioural addictions: the case ofpathological gambling. Addiction. (2012) 107:1726–34. doi: 10.1111/j.1360-0443.2011.03546.x
45. Huang X, Gong Q, Sweeney JA, Biswal BB. Progress in psychoradiology, the clinical application of psychiatric neuroimaging. Br J Radiol. (2019) 92:20181000. doi: 10.1259/bjr.20181000
46. Li F, Sun H, Biswal BB, Sweeney J, Gong Q. Artificial intelligence applications in psychoradiology. Psychoradiology. (2021) 1:94–107. doi: 10.1093/psyrad/kkab009
Keywords: impulsive-compulsive disorders spectrum, psychiatric disorders, network analysis, path-analysis, impulsivity
Citation: Granero R, Krug I and Jiménez-Murcia S (2022) Editorial: New advancement in network and path-analysis approaches for the study of disorders within the impulse-compulsive spectrum disorders. Front. Psychiatry 13:1029122. doi: 10.3389/fpsyt.2022.1029122
Received: 26 August 2022; Accepted: 13 September 2022;
Published: 26 September 2022.
Edited by:
Qiyong Gong, Sichuan University, ChinaReviewed by:
Song Wanag, Sichuan University, ChinaCopyright © 2022 Granero, Krug and Jiménez-Murcia. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Susana Jiménez-Murcia, sjimenez@bellvitgehospital.cat