BMC Psychology (Jan 2023)

Using computer-based habit versus chess-based cognitive remediation training as add-on therapy to modify the imbalance between habitual behavior and cognitive control in tobacco use disorder: protocol of a randomized controlled, fMRI study

  • Damian Karl,
  • Alfred Wieland,
  • Yury Shevchenko,
  • Nadja Grundinger,
  • Noah Machunze,
  • Sarah Gerhardt,
  • Herta Flor,
  • Sabine Vollstädt-Klein

DOI
https://doi.org/10.1186/s40359-023-01055-z
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 11

Abstract

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Abstract Background Although the vast majority of smokers are aware of the enormous preventable health hazards caused by smoking, only a small percentage of smokers manage to remain abstinent in the long term. One possible explanation for this discrepancy lies in the inflexibility of addictive behavior and associated disadvantageous decision‐making. According to a dual‐process theory of decision‐making, two distinct decision systems can be identified. One slow deliberate system based on desirable expectations of outcome value described as goal‐directed behavior and a fast reflexive system based on habitual instrumental behavior and driven by reinforcement experienced in the past. In the course of addiction development, an imbalance occurs between habitual behavior and goal-directed. The present study aims to investigate the modifiability of the balance between habitual and goal-directed behavior at the neurobiological and behavioral level in smokers using two different novel add-on therapies. We hypothesize that both interventions change the balance between goal-directed and habitual behavior, but by different mechanisms. Whereas a cognitive remediation treatment should directly improve cognitive control, in contrast an implicit priming task should affect the early processing and the emotional valence of smoking and smoking cues. Methods We will conduct a randomized controlled study in treatment-seeking individuals with tobacco use disorder applying either chess-based cognitive remediation training (N = 30) or implicit computer-based habit-modifying training (N = 30) as add on therapy compared to the standard smoking cessation group therapy (N = 30) only. We will address neurobiological and neuropsychological correlates associated with craving, reward devaluation, cue reactivity and attentional bias. In addition, various effects of treatment and prediction of treatment outcome will be examined using behavioral and neural measures. Discussion The present study will apply different examination methods such as functional magnetic resonance imaging, neuropsychological tests, and self-report before and after the interventions. This allows the identification of intervention-specific mechanisms and therefore potential neurobiology-based specific treatment targets for individuals with Tobacco Use Disorder. Trial registration: Registered at clinicaltrials.gov/ct2/show/NCT03764969 (05 December 2018).

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