Dominated by a “market capitalism”, i.e., an economic model promoting the buying and selling of goods and services, we nowadays live in a competitive, stressfull and mass consumption society, where people increasingly exhibit behaviors aimed at satisfying personal and material desires (Pérez and Esposito, 2010). Throughout their life, many people will engage in “excessive consumption acts”, but only some of them will move toward unrestrictive, unrestrained, uncontrolled, maladaptive, i.e., addictive, behaviors. Repeating an activity despite the explicitly stated desire to stop it due to its harmful individual and social consequences is the hallmark of an addictive behavior (Santangelo et al., 2022).
Decades of research have tried to understand which mechanisms trigger the onset as well as the long-term maintenance of such behaviors. Why and how can an arbitrary activity, such as buying clothes, eating food, watching TV series, drinking alcohol or gambling on sport events, become so central in a person life, and so compulsive that it will overtake all other activities? Classic addictions to drugs or substances may be understood by means of their reinforcing properties on specific brain networks. Indeed, despite their various molecular targets, addictive substances (such as alcohol, cocaine, heroin, tobacco) will act, by increasing dopamine level, on a common biological pathway, i.e., the mesolimbic circuit, and more precisely, in the nucleus accumbens of the ventral striatum, resulting in an interoceptive feeling of pleasure (reward) (Di Chiara and Imperato, 1998). Repeated exposure to the substance will promote the encoding of the rewarding properties of this event, acting therefore as a reinforcement learning signal, increasing the incentive salience of this reward and stimulating motor action (Berridge and Robinson, 1998). Transition from “simple impulses to consume” toward “compulsive behaviors” appears to be linked to a dysfunctional (pre)frontal control system, implicated in future-oriented processes and regulating current actions in relation to long-term goal-directed motivations (Robinson and Berridge, 2003). Overall, a substance-related addictive behavior may be seen as a reinforced-learned automatic response (a habit) to a highly salient activity, resisting to devaluation as well as to goal-inappropriateness (see Lüscher et al., 2020 for a review).
Nowadays, the mechanisms behind how such habits are learned and operate remain a topic of ongoing research, with controversies regarding the exact contribution of (overestimated) habitual processes vs. (underestimated) contextual goal-directed processes in the long-term maintenance of maladaptive behaviors (Bouton, 2021; Buabang et al., 2021). Also, if we can clearly imagine how those substances, acting as neurotoxic agents that kill neurons (Singh and Verma, 2020), could impact various brain systems—such as contributing to the hypo-activity of control regions in the frontal cortex—the situation is even less clear when we consider non-substance-related addictive behaviors. Indeed, in the absence of any ingestion of a neurotoxic agent, how can we understand that behaviors such as playing video games, gambling, watching TV or social media use may become “addictive”, and represent (mainly among youths) a significant public health concern? Of course, all these behaviors are “rewarding”, therefore also creating through the dopamine mesolimbic system highly salient cues hijacking attention and stimulating compulsive action (Vidal and Meshi, 2023). But how can we explain the transition to compulsion in the absence of any neurotoxic effect?
Several explicative “individual risk factors” for the development of addictive behaviors from adolescence to adulthood have been proposed, such as consumption motives (social, pleasure, coping…), family history (genetic part as well as education), associated conduct disorders, inter-individual differences in cognitive control or emotional regulation skills, personality traits (impulsivity, sensation seeking, risk taking…) or gender (Petit et al., 2013). Some evidence also points to implicit cognitions, i.e., unconscious learned associations in memory (“When I feel bad, if I drink, I feel better”), which may explain why people can engage in behaviors they know being life threatening (Stacy and Wiers, 2010 for a review). Altogether, all of this makes the story particularly complex, and, despite decades of research, it still triggers more questions than responses. Addictive behaviors related or not to a substance present a strong common neurobiological link (Grant et al., 2006), but also some specific patterns of response to rewarding cues (Dubuson et al., 2023). Given their high co-occurrence (Burleigh et al., 2019) and the rise in polydrug use (Crummy et al., 2020), further research is highly needed for improving the understanding of the mechanisms triggering the onset of such maladaptive behaviors (maybe by promoting more translational research going from animal to human research), as well as prevention and treatment strategies. Prevention is particularly difficult to achieve, as, due to the huge number of potential contributive factors, it is impossible to give a clear recipe to apply. Studies that will help to define profiles of high-risk people for developing addictive behaviors remain therefore of the highest importance at the fundamental and clinical levels, as moreover, we are all aware that the impact of current conventional proposed treatments (based on detoxification, psychotherapy and anti-craving medication), is modest. Aggregate substance use disorder (SUD) remission (abstinence) rates were 10–15% for any given year (Fleury et al., 2016), pointing to the urgent need to find complementary and effective add-on tools, not only to globally enhance quality of care, but also to reduce treatment gap (only a small proportion—around 10%—of adults with SUD seeks treatment) (Knopf, 2024).
The last decades have seen the emergence of various forms of add-on tools. New dimensions of psychological interventions were proposed and tested, such as the use of mindfulness (Korecki et al., 2020); of eye movement desensitization and reprocessing (EMDR; Carletto et al., 2018); of cognitive behavioral therapy (CBT; Ray et al., 2020); of cognitive bias modification programs (CBM; Manning et al., 2019); or of new technologies promoting remote or automated interventions through web-based or smartphone-based apps (Ferreri et al., 2018). Neurocognitive models also described two opposite systems underlying addictive behaviors: an abnormal bottom-up (impulsive, limbic) system generating implicit attentional biases (increased attention specifically related to alcohol cues), a “wanting” (craving, i.e., desire to drink) behavior and an automatic approach tendency, which cannot be “regulated” by a weakened reflective/executive (control, prefrontal) system that cannot inhibit approach tendencies (Wiers et al., 2007). On this basis, many studies have sought to promote abstinence by decreasing attentional biases and/or increasing inhibitory skills, through cognitive training (MacLean et al., 2018; Verdejo-Garcia et al., 2023), by using neuromodulation tools such as TMS (Antonelli et al., 2021) or tDCS (Lupi et al., 2017); or even by combining cognitive training programs with neuromodulation tools (Dubuson et al., 2023). Tools such as neurofeedback (Russo et al., 2023) or virtual reality (Tsamitros et al., 2021) were also used for this purpose. Many studies also focused on assessing biomarkers, i.e., biological markers associated with behavioral changes, that can predict or correlate with disease trajectories and treatment responses (Volkow et al., 2015; Campanella et al., 2020; Poireau et al., 2022). Nevertheless, despite all these efforts, current clinical outcomes remain modest (e.g., Fascher et al., 2024). This at least suggests that further studies should try to renew their approach of SUD clinical care (fostering for instance longer lengths of services; Beaulieu et al., 2021), and/or rely on refined SUD models (promoting for instance the inclusion of stress in neurocognitive models; Noël et al., 2013).
On this basis, an important role to be played by this section Addictive Behaviors in Frontiers in Psychology is to provide a platform for sharing and promoting the scientific outcomes of theoretical as well as empirical works highlighting the mechanisms triggering compulsive behaviors, elucidating protective as well as risky factors, or including new methods and/or experimental paradigms to face with the various forms of addictive behaviors. Importantly, the heterogeneous as well as (sometimes) the counter-intuitive data that SUD researchers have obtained so far clearly stresses the extreme complexity of this phenomenon. This should naturally push further studies to adopt a more integrative perspective, in which theoretical models would involve, in an interdisciplinary approach, social, behavioral, neural, emotional, cognitive and clinical manifestations of addictive behaviors as well as methodological parameters that better approximate the addictive experience, in order to help the field move toward improved understanding, prevention, diagnosis, and treatment (Diehl et al., 2018; Corley et al., 2024).
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Author contributions
SC: Writing – review & editing, Writing – original draft.
Funding
The author(s) declare financial support was received for the research, authorship, and/or publication of this article. SC wad supported by the Belgian Fund of Scientific Research (Fonds de la Recherche Scientifique; F.R.S./FNRS) and by the Brugmann Foundation.
Conflict of interest
The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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References
1
Antonelli M. Fattore L. Sestito L. Di Giuda D. Diana M. Addolorato G. (2021). Transcranial magnetic stimulation: a review about its efficacy in the treatment of alcohol, tobacco and cocaine addiction. Addict. Behav.114:106760. 10.1016/j.addbeh.2020.106760
2
Beaulieu M. Tremblay J. Baudry C. Pearson J. Bertrand K. (2021). A systematic review and meta-analysis of the efficacy of the long-term treatment and support of substance use disorders. Soc. Sci. Med.285:114289. 10.1016/j.socscimed.2021.114289
3
Berridge K. C. Robinson T. E. (1998). What is the role of dopamine in reward: hedonic impact, reward learning, or incentive salience?. Brain Res. Rev.28, 309–369. 10.1016/S0165-0173(98)00019-8
4
Bouton M. E. (2021). Context, attention, and the switch between habit and goal-direction in behavior. Learn. Behav.49, 349–362. 10.3758/s13420-021-00488-z
5
Buabang E. K. Boddez Y. De Houwer J. Moors A. (2021). Don't make a habit out of it: impaired learning conditions can make goal-directed behavior seem habitual. Motivat. Sci.7, 252–263. 10.1037/mot0000218
6
Burleigh T. L. Griffiths M. D. Sumich A. Stavropoulos V. Kuss D. J. (2019). A systematic review of the co-occurrence of gaming disorder and other potentially addictive behaviors. Curr. Addict. Rep.6, 383–401. 10.1007/s40429-019-00279-7
7
Campanella S. Schroder E. Kajosch H. Hanak C. Veeser J. Amiot M. et al . (2020). Neurophysiological markers of cue reactivity and inhibition subtend a three-month period of complete alcohol abstinence. Clin. Neurophysiol.131, 555–565. 10.1016/j.clinph.2019.10.020
8
Carletto S. Oliva F. Barnato M. Antonelli T. Cardia A. Mazzaferro P. et al . (2018). EMDR as add-on treatment for psychiatric and traumatic symptoms in patients with substance use disorder. Front. Psychol.8:2333. 10.3389/fpsyg.2017.02333
9
Corley C. Craig A. Sadek S. Marusich J. A. Chehimi S. N. White A. M. et al . (2024). Enhancing translation: a need to leverage complex preclinical models of addictive drugs to accelerate substance use treatment options. Pharmacol. Biochem. Behav.243:173836. 10.1016/j.pbb.2024.173836
10
Crummy E. A. O'Neal T. J. Baskin B. M. Ferguson S. M. (2020). One is not enough: understanding and modeling polysubstance use. Front. Neurosci.14:569. 10.3389/fnins.2020.00569
11
Di Chiara G. Imperato A. (1998). Drugs abused by humans preferentially increase synaptic dopamine concentrations in the mesolimbic system of freelymoving rats. Proc. Natl. Acad. Sci. U. S. A.85, 5274–5278. 10.1073/pnas.85.14.5274
12
Diehl M. M. Lempert K. M. Parr A. C. Ballard I. Steele V. R. Smith D. V. (2018). Toward an integrative perspective on the neural mechanisms underlying persistent maladaptive behaviors. Eur. J. Neurosci.48:1870. 10.1111/ejn.14083
13
Dubuson M. Noël X. Kornreich C. Hanak C. Saeremans M. Campanella S. (2023). A comparative event-related potentials study between alcohol use disorder, gambling disorder and healthy control subjects through a contextual go/nogo task. Biology12:643. 10.3390/biology12050643
14
Fascher M. Nowaczynski S. Spindler C. Strobach T. Muehlhan M. (2024). Neural underpinnings of response inhibition in substance use disorders: weak meta-analytic evidence for a widely used construct. Psychopharmacology241, 1–17. 10.1007/s00213-023-06498-1
15
Ferreri F. Bourla A. Mouchabac S. Karila L. (2018). e-Addictology: an overview of new technologies for assessing and intervening in addictive behaviors. Front. Psychiatry9:51.
16
Fleury M. J. Djouini A. Hu?nh C. Tremblay J. Ferland F. Ménard J. M. et al . (2016). Remission from substance use disorders: a systematic review and meta-analysis. Drug Alcohol Depend.168, 293–306. 10.1016/j.drugalcdep.2016.08.625
17
Grant J. E. Brewer J. A. Potenza M. N. (2006). The neurobiology of substance and behavioral addictions. CNS Spectr.11, 924–930. 10.1017/S109285290001511X
18
Knopf A. (2024). WHO says there's a critical gap worldwide for SUD treatment. Alcohol. Drug Abuse Wkly.36, 6–7. 10.1002/adaw.34183
19
Korecki J. R. Schwebel F. J. Votaw V. R. Witkiewitz K. (2020). Mindfulness-based programs for substance use disorders: a systematic review of manualized treatments. Subst. Abuse Treat. Prev. Policy15, 1–37.
20
Lupi M. Martinotti G. Santacroce R. Cinosi E. Carlucci M. Marini S. et al . (2017). Transcranial direct current stimulation in substance use disorders: a systematic review of scientific literature. J. ECT33, 203–209. 10.1097/YCT.0000000000000401
21
Lüscher C. Robbins T. W. Everitt B. J. (2020). The transition to compulsion in addiction. Nat. Rev. Neurosci.21, 247–263. 10.1038/s41583-020-0289-z
22
MacLean R. R. Sofuoglu M. Brede E. Robinson C. Waters A. J. (2018). Attentional bias in opioid users: a systematic review and meta-analysis. Drug Alcohol Depend.191, 270–278. 10.1016/j.drugalcdep.2018.07.012
23
Manning V. Garfield J. B. Mroz K. Campbell S. C. Piercy H. Staiger P. K. et al . (2019). Feasibility and acceptability of approach bias modification during methamphetamine withdrawal and related methamphetamine use outcomes. J. Subst. Abuse Treat.106, 12–18. 10.1016/j.jsat.2019.07.008
24
Noël X. Brevers D. Bechara A. (2013). A triadic neurocognitive approach to addiction for clinical interventions. Front. Psychiatry4:179. 10.3389/fpsyt.2013.00179
25
Pérez F. Esposito L. (2010). The global addiction and human rights: Insatiable consumerism, neoliberalism, and harm reduction. Perspect. Glob. Dev. Technol.9, 84–100. 10.1163/156914910X487933
26
Petit G. Kornreich C. Verbanck P. Cimochowska A. Campanella S. (2013). Why is adolescence a key period of alcohol initiation and who is prone to develop long-term problem use?: A review of current available data. Socioaffecti. Neurosci. Psychol.3:21890. 10.3402/snp.v3i0.21890
27
Poireau M. Milpied T. Maillard A. Delmaire C. Volle E. Bellivier F. et al . (2022). Biomarkers of relapse in cocaine use disorder: a narrative review. Brain Sci.12:1013. 10.3390/brainsci12081013
28
Ray L. A. Meredith L. R. Kiluk B. D. Walthers J. Carroll K. M. Magill M. (2020). Combined pharmacotherapy and cognitive behavioral therapy for adults with alcohol or substance use disorders: a systematic review and meta-analysis. JAMA Netw. Open3, e208279–e208279. 10.1001/jamanetworkopen.2020.8279
29
Robinson T. Berridge K. (2003). Addiction. Annu. Rev. Psychol.54, 25–53. 10.1146/annurev.psych.54.101601.145237
30
Russo G. M. Smith S. Sperandio K. R. (2023). A meta-analysis of neurofeedback for treating substance use disorders. J. Counsel. Dev.101, 143–156. 10.1002/jcad.12466
31
Santangelo O. E. Provenzano S. Firenze A. (2022). Risk factors for addictive behaviors: a general overview. Int. J. Environ. Res. Public Health19:6583. 10.3390/ijerph19116583
32
Singh P. Verma P. (2020). Neurotoxicity: a devastation to CNS. Eur J Mol Clin Med7, 4831–4840.
33
Stacy A. W. Wiers R. W. (2010). Implicit cognition and addiction: a tool for explaining paradoxical behavior. Annu. Rev. Clin. Psychol.6, 551–575. 10.1146/annurev.clinpsy.121208.131444
34
Tsamitros N. Sebold M. Gutwinski S. Beck A. (2021). Virtual reality-based treatment approaches in the field of substance use disorders. Curr. Addict. Rep.8, 399–407. 10.1007/s40429-021-00377-5
35
Verdejo-Garcia A. Rezapour T. Giddens E. Khojasteh Zonoozi A. Rafei P. Berry J. et al . (2023). Cognitive training and remediation interventions for substance use disorders: a Delphi consensus study. Addiction118, 935–951. 10.1111/add.16109
36
Vidal C. Meshi D. (2023). Behavioral addictive disorders in children and adolescents. J. Am. Acad. Child Adolesc. Psychiatry62, 512–514. 10.1016/j.jaac.2022.07.819
37
Volkow N. D. Koob G. Baler R. (2015). Biomarkers in substance use disorders. ACS Chem. Neurosci.6, 522–525. 10.1021/acschemneuro.5b00067
38
Wiers R. W. Bartholow B. D. van den Wildenberg E. Thush C. Engels R. C. Sher K. J. et al . (2007). Automatic and controlled processes and the development of addictive behaviors in adolescents: a review and a model. Pharmacol. Biochem. Behav.86, 263–283. 10.1016/j.pbb.2006.09.021
Summary
Keywords
addictive behaviors, compulsion, dependence, mechanisms, biomarkers, treatment
Citation
Campanella S (2024) Addictive behaviors: decades of research, but still so many questions!. Front. Psychol. 15:1485118. doi: 10.3389/fpsyg.2024.1485118
Received
23 August 2024
Accepted
18 October 2024
Published
06 November 2024
Volume
15 - 2024
Edited and reviewed by
Antoine Bechara, University of Southern California, United States
Updates
Copyright
© 2024 Campanella.
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: Salvatore Campanella salvatore.campanella@chu-brugmann.be
Disclaimer
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.