Effectiveness of Transcranial Alternating Current Stimulation (tACS) and Cognitive Bias Modification (CBM) in Treating Anxiety, Depression, Attentional Bias, and Drug Craving in Opioid-Dependent Patients; A Randomized controlled trial

doi:10.21203/rs.3.rs-4275457/v1

Introduction:

Substance Use Disorders (SUDs) pose significant challenges globally, with opiate addiction being particularly prevalent. This study investigates the impact of transcranial alternating current stimulation (tACS) at 10 Hz and individual alpha frequencies (IAF), along with cognitive bias modification (CBM), on drug craving, anxiety, depression, and attention bias in individuals with SUDs.

Methods:

Participants (N = 72) were allocated to control, tACS 10 Hz, tACS IAF, Sham, CBM, and CBM+tACS groups (n = 12 each). Measures included demographic questionnaires, dot probe tasks, Desires for Drug Questionnaires (DDQ), DASS-21 assessments, and Visual Analog Scale (VAS) for craving. Mixed repeated measures ANOVA were conducted, revealing significant interactions (TIME*GROUP), indicating differential treatment effects over time.

Findings:

The study involved 72 substance abusers divided into six groups: control, tACS.10 Hz, tACS Real, Sham, CBM, and CBM+tACS. Demographic variables were similar among groups. Mixed ANOVA showed significant TIME*GROUP interactions for all assessments. Significant differences were found in depression, anxiety, drug dependence, and visual analog scale measures.

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Conclusion:

In summary, while tACS and CBM alone did not significantly reduce substance-related outcomes, their combined approach showed promise. This study highlights the brain's adaptability to electrical stimulation and underscores the need for further exploration in understanding and treating SUDs. Limitations include restricted participant access and reliance on verbal induction of craving, emphasizing the need for robust study designs and diverse measures in future research.

Transcranial Alternating Current Stimulation

tACS

Cognitive Bias Modification

CBM

Anxiety

Depression

Internalizing symptoms

Craving

Attention bias

Substance use disorders

Opioid use disorders

Addictions

Substance use disorders (SUDs) are persistent and severe problems in contemporary societies, with profound consequences (Ouzir & Errami, 2016). Conceptually, SUDs are chronic, neurological diseases influenced by genetic, physiological, and social factors. SUDs are characterized by impaired self-control and a compulsion to engage in specific behaviors despite awareness of their harmful consequences(Gipson & Beckmann, 2023; Sripada, 2022)Opioid SUDs, such as heroin and opium abuse, are especially prevalent in countries like Iran and can significantly impact cognitive functions like learning, memory, and attention (Rezapour et al., 2021). Individuals with SUDs often experience cognitive and psychological consequences, including depression and anxiety during withdrawal. Additionally, cognitive issues like craving and attentional bias can complicate clinical presentations and contribute to relapse (Marissen et al., 2006).

Anxiety and depression are particularly important psychological disorders associated with SUDs. They can lead to substance use as a way to cope with symptoms and social issues related to opiates, anxiety, and depression (Davoudi et al., 2017). Elevated negative emotional states in individuals with mood and anxiety disorders may increase the likelihood of craving episodes and drug use relapse (Preston & Epstein, 2011). Anxiety and depression are present at all stages of SUDs, and studies have shown that negative mood is associated with substance use (Buckner et al., 2015). Withdrawal-induced depression can persist for weeks and elevate suicide risk (Swan & Chang, 2003). Off special importance, depressive disorders and SUDs are common and challenging conditions that often coexist, necessitating new treatment options. Neuroimaging studies suggest common neurological mechanisms underlying depressive disorders and SUDs (Dunlop et al., 2017).The anterior cingulate cortex and deficits in cognitive control are implicated in the neural links between depression, anxiety, and SUDs (Riesel et al., 2019).

As mentioned, Chronic substance use can lead to cognitive deficits affecting attention, learning, memory, and reasoning. Executive functions like working memory, cognitive flexibility, and inhibition control may be particularly affected (Gupta et al., 2018). Specific cognitive deficits associated with drug use include impaired cognitive flexibility and attention (Lyvers & Yakimoff, 2003). Attentional bias, which involves altered attention allocation to specific stimuli, plays a significant role in SUDs and may contribute to the inability to control substance abuse behaviors (MacLean et al., 2018). Attentional bias is evident in anxiety disorders, depression, and addiction(Field et al., 2016; Suslow et al., 2020; Thomas et al., 2013; Wieser & Keil, 2020). This bias is particularly evident in craving, where individuals focus on stimuli resembling their substance use process (Bollen et al., 2024; Nejati et al., 2011). Craving is a central phenomenon in substance abuse and relapse, with significant implications for treatment(Culbertson et al., 2010; Hormes & Rozin, 2010; Vafaie & Kober, 2022). Conventional treatments for craving and substance withdrawal shown limited efficacy (Hone-Blanchet et al., 2015).

Various treatments, such as cognitive behavioral therapy (CBT), third-wave therapies, and psychoanalytical therapies, are available for managing anxiety, depression, and psychological issues in SUDs. Cognitive behavioral therapy has emerged as a common non-pharmacological treatment for SUDs, showing greater efficacy compared to the twelve-step program and group counseling, However, CBT is not always effective, and according to some studies patients may struggle to modify their cognitive patterns (Baker et al., 2014). Recent advancements in neuroscience have led to increased interest in noninvasive brain stimulation as a treatment modality. Cognitive bias modification (CBM) and transcranial electrical stimulation with alternating current (tACS) have garnered attention in recent years (Paulus, 2011).

Stimulation techniques like transcranial electrical stimulation (TES) and cognitive bias modification (CBM) show promise in understanding neuropsychological functions and retraining cognitive biases (Bocci et al., 2019; Wells & Beevers, 2010). Transcranial direct current electrical stimulation (tDCS) can influence decision-making processes related to impulsivity in addictive disorders (Boggio et al., 2010). Targeting specific brain regions using tDCS has shown promise in reducing craving (Hone-Blanchet et al., 2015). Transcranial electrical stimulation with alternating current (tACS) is another promising technique that modulates brain waves using alternating electrical currents (Wu et al., 2021). To the authors' best knowledge, unlike tDCS, there has been no focused research on the effects of tACS on substance use disorder. Many studies have shown that tDCS can affect depression, craving, attentional bias, impulsivity, etc. tACS and tDCS are very similar, but the difference between the two can be expressed by the fact that, unlike tDCS, which induces the current on average in a full cycle, tACS is used to interact with normal brain oscillations rather than applying direct electrical current (Tavakoli & Yun, 2017).

As mentioned, tACS stimulation is accompanied by alternating frequency of the brain waves, and alpha waves (8 and 12 Hz) are of great importance concerning anxiety levels and mood status. The frequency of 10 Hz dominates the recording of alpha brain waves during rest. As a result, due to the interest in understanding the brain processes in the resting state, which is defined as the basis of brain activities, this frequency is used as the baseline (classical frequency) for quantitative analysis. It is one of the most important physiological indicators of brain function (Shaw, 2003). These spontaneous brain activities have a high intra-individual stability that shows significant changes between individuals (Posthuma et al., 2001) and also change with age and psychological states (Scally et al., 2018) . Individual alpha frequency (IAF) has been linked to cognitive functions and intelligence (Corcoran et al., 2018). However, more research is needed to fully understand the effects of tACS on SUDs.

In addition to the non-invasive treatments mentioned above, CBM was considered in recent studies to target the attentional bias in SUDs (Harvey et al., 2004). CBM refers to computer tasks that help retrain cognitive biases. Cognitive biases include a broad category of automatic processes that may even proceed with conscious intentions. For example, the attention of an addicted person to the signs of drugs; may cause a tendency to act based on stimuli (Wiers et al., 2015).

The present study aimed to investigate the effectiveness of tACS at 10 Hz and individual alpha frequencies, combined with CBM, on depression, attentional bias, and craving in individuals with a history of opium use in order to investigate the effectiveness of these promising interventions on craving, internalizing symptoms (depression and anxiety) related with opioid use disorder. Thus, the present study aimed to answer the following questions:

1. Is there a difference between the effectiveness of the 10 Hz tACS and the IAF based tACS method on craving, anxiety, depression and attentional bias in people with a history of opium use?

2. Is there a difference between the effectiveness of the tACS and the CBM on drug craving, anxiety, depression and attention bias in people with a history of opium use?

3. Is the combined intervention of tACS and CBM more effective than tACS and CBM separate interventions in reducing the craving, anxiety, depression, attention bias of people with a history of opium use?

Participants

The study involved 72 participants, with 15 individuals dedicated to each group. The age range of the participants was 18 to 65 years (M = 33.83, SD = 9.05). All participants were addicts with a history of opium abuse who were undergoing treatment at De-addiction camps in Khorramabad city for addiction treatment.

Study Design

The study utilized a randomized controlled design to investigate the effects of different interventions on participants. In the first phase, Participants were randomly assigned into two groups of tACS (10 Hz) and IAF tACS.(n=12 for each group). In the second phase the participants were allocated equally in 4 groups (CBM, CBM+tACS (10 Hz)+ tACS(10 Hz)+ Sham+ Control)(n=12) for each group. Two follow-ups were conduced after 30day and 90day. Study design is showed in a flow chart under recommendations of CONSORT in Figure 1.

Recruitment and Criteria

Participants were recruited from addiction treatment clinics based on inclusion criteria such as a history of at least 12 months of opium use disorder according to DSM-5 criteria, confirmed abstinence from all drugs except smoking for at least one week, a minimum of 20% reported craving for drug use, absence of certain medical conditions, and specific demographic characteristics. Exclusion criteria included being treated for another psychiatric disorder (except substance use disorders), serious neurological disorders, initiation of medications affecting the central nervous system, and missing more than one treatment session.

Group Allocation

Participants were divided into six groups:

Group one: tACS with 10Hz alpha.
Group two: tACS with individual alpha.
Group three: combined tACS and CBM.
Group four: CBM.
Group five: Sham.
Group six: Control.

Intervention

The electrical stimulation device was programmed by one of the principal investigators to deliver tACS or sham stimulation in a double-blind manner. The intervention consisted of five consecutive sessions, spaced at least 24 hours apart, with participants being intervened at consistent times throughout the day. All participants provided informed consent prior to their inclusion in the study, and ethical guidelines set forth by the Institutional Review Board were strictly adhered to throughout the research process. Intervention protocol was approved by the Ethics Committee at the USWRS in 12/9/2020 (IR.USWR.REC.1399.157).

2.2. Measures

2.2.1- Demographic questionnaire (BDSP):

This form included basic demographic information, history and pattern of substance use, type of treatments received, etc.

2.2.2- Dot probe task(CBM protocol):

The dot probe test is one of the most widely used tests to measure attention bias, which has been used in many attention bias studies. In this test, two stimuli (in the form of words or pictures), one of which is threatening and the other is neutral, are presented in each attempt for a specified period of time, then they disappear from the screen and a target symbol appears in place of one of the previous stimuli.

Pictures were used instead of words as stimuli to make the project reasonable for addicts from various educational backgrounds. For choosing the opioid craving-related picture, first, 100 craving-related pictures were selected from the International Affective Picture System and picture collection of SINA institute in Tehran. The pictures were shown to 20 non-participant opioids addicts to select the most stimulant pictures based on the degree of craving they made. Then, 40 target pictures were matched with neutral ones that must be compatible in composition, size, and color. Each trial began with a 500-ms black fixation cross (8×8 mm) located in the center of a white screen. Next, the fixation of two pictures, including a neutral on one side and a stimulant (opioids craving-related picture) on the other side, was simultaneously presented for 1000 ms. The height and vertical distance of each picture were 50 and 60 mm, respectively. After 1000 ms, the picture pair was randomly replaced with a target or dot (3 mm in diameter) either on the right or left side for 250 ms. In 50% of the trials, the target appeared in the presence of a neutral picture. The participants were asked to indicate the direction of the dot by pressing the matching button on the computer keyboard. The participants were orally instructed that the dot would appear in one of the right or left locations of the two pictures, and they were required to pay attention to the pictures and dots and perform the task as quickly and correctly as possible. In this case, both speed and accuracy were considered important factors. This task involved the participants in 160 dot-probe trials. Each of the 40 picture pairs was displayed 4 times (4*40). The distance of the participants’ eyes from the screen was 50 to 70 cm. The session lasted about 5–7 min. (Figure 2)

2.2.3- Desires for Drug Questionnaire (DDQ):

This questionnaire is widely recognized for its efficacy in assessing current drug cravings. Originally developed and standardized by Franken et al. (2002) for German-speaking heroin users, the questionnaire has since been adapted for Persian-speaking methamphetamine users. The Persian version comprises 14 questions organized into three subscales: "tendency to use drugs and negative reinforcement," "desire to use drugs," and "control and pleasure." Abharian et al. evaluated the questionnaire's validity using the Cronbach's alpha method, obtaining a general score of 0.70.63 and subscale scores of 0.78, 0.65, and 0.81 for the mentioned subscales, respectively (unpublished data). Participants rate their agreement with each item on a scale ranging from 1 (completely disagree) to 7 (completely agree).

2.2.4- DASS-21:

The Depression, Anxiety, and Stress Scales (DASS) questionnaire comprises 21 statements that assess various symptoms of negative emotions, including depression, anxiety, and stress. However, in the present study, only the depression and anxiety subscales were used in order to assess internalizing symptoms related with these psychopathologies. The depression subscale encompasses expressions related to an unhappy mood, lack of self-confidence, hopelessness, worthlessness, disinterest in activities, joylessness, and fatigue. Meanwhile, the anxiety subscale evaluates physiological overexcitement, fears, and situational anxieties.

Participants rate the intensity of each symptom experienced over the last week using a 4-point scale (ranging from 0 to 3). Each subscale consists of 7 questions, and scores are calculated by summing the responses within each subscale. One notable advantage of the DASS questionnaire is its ability to differentiate between depression and anxiety, which helps prevent overestimation of depression in diverse patient populations.

The psychometric properties of the DASS have been extensively studied. In non-clinical populations, the internal consistency coefficients for depression, anxiety, and stress subscales were reported as 0.91, 0.84, and 0.90, (Lovibond & Lovibond, 1995). In clinical populations, these coefficients were 0.96, 0.89, and 0.93, respectively (Brown et al., 1997). Additionally, retest coefficients for the DASS subscales ranged from 0.71 to 0.81 over a two-week interval in a sample of 20 patients (Brown et al., 1997).

The factorial structure of the DASS questionnaire has been supported by various studies, and its psychometric properties have been confirmed in different populations. For instance, a study with 227 Iranian chronic pain patients using confirmatory factor analysis found that the questionnaire's three-factor structure was valid. The internal consistency coefficients (Cronbach's alpha) for the depression, anxiety, and stress scales in this study were 0.87, 0.81, and 0.87, respectively. Moreover, the concurrent validity of the DASS-21 scales was established by correlating them with scores from the Beck Depression Scale and the Multimodal Pain Questionnaire (Moghaddam et al., 2008).

Scores on the depression subscale can range from 0 to 63, with higher scores indicating more severe depression. In the current study, the Cronbach's alpha values for the depression, anxiety, and were 0.75, 0.70, respectively. These findings suggest that the DASS questionnaire is a valid and reliable measure of negative emotional states.

2.2.5- Induced craving (VAS):

To assess induced craving, each participant was requested to recount three past scenarios that elicited drug cravings and resulted in drug use. Simultaneously, these statements are recorded. Subsequently, the participant reviews these situations and is prompted to envision them, rating their craving for opium on a Visual Analog Scale (VAS). The VAS in this study is a 100 mm linear scale ranging from 0 (indicating no desire at all) to 100 (indicating the most intense desire). The participant's highest level of craving is identified from these scenarios, and their response is documented. During the post-test phase, the same scenarios are revisited to evoke craving (Sinha et al., 2011).

2.2.6. tACS(classic 10 hz and Individual alpha frequency stimulation)

The tACS was applied using a battery-powered electrical stimulator and a pair of electrodes (5×7 cm) at 2-mA intensity. In order to target the DLPFC, the anodal electrode was placed on the F4 region and the cathodal electrode was placed on the F3 region (determined based on the 10-20 System of Electrode Placement). The stimulation was provided for 20 minutes with a 30s rise and fall time with Neurostim2. Devices were provided by Medina Teb company (www.medinateb.com).tACS (Real or sham) was delivered by electric stimulator ( Neurostim-2, Medinateb, Tehran) 10 hz stimulation was opted as the classic stimulation. In the IAF group, a 12-channel BioLine device (manufactured by Medinateb, Iran) was employed to record individual signals at three points: O1, O2, and Pz. To determine the Individual Alpha Frequency (IAF), a dedicated window in the Biosees software (manufactured by Medinateb, Iran) was utilized. The individual alpha peak for each participant was obtained through this process.

Data Analysis

Data analysis involved descriptive statistics such as frequency, mean, and standard deviation, as well as inferential statistics including analysis of covariance and t-tests to compare the six groups. SPSS version 22 was used for data analysis. Mixed repeated measures ANOVAs were used to compare groups based on each outcome variable.

Participants included 72 substance abusers that assigned in control group (n=12), tACS.10 hz (n=12), tACS. Real (n=12), Sham (n=12), CBM (n=12) and CBM+tACS (n=12). The mean age of all participants was 33.83 years (S.D = 9.05, range of 20-49 years). Chi-squares and Analysis of Variance (ANOVA) tests were performed to identify possible differences in demographic variables among the groups. No significant between–group differences were found for demographic variables include marital status, unset and duration of substance use, number of addicts and abstinance from substances Demographic variables are presented in Table 1.

Mixed Repeated measures ANOVA were conducted to test differences between the groups on the study variables. Group (tACS.10 hz, tACS. Real, Control, Sham, CBM and CBM+tACS) as between-subject and assessment time (pre-test, post-test, follow-up1 and follow-up2) as within-subject were tested. Similarities were found between the six groups at pretest (Table 2). A significant difference between-subject by within-subject interaction effect (TIME*GROUP) was found. One way ANOVA were then done for pre test, post-test, follow-up1 and follow-up2 comparisons among groups to assess group differences in before and after the intervention.

Mixed repeated measures ANOVA were conducted to test differences among the groups on the depression. Group (tACS.10 hz, tACS. Real, Control, Sham, CBM and CBM+tACS) as between-subject and assessment time (pre-intervention, post-intervention, follow-up1 and follow-up2) as within-subject were tested. Similarities were found between the groups at pretest, there was significant differences between groups [F (5, 41) =1.10 , P= 0.37, η2 =0.12], between-subject by within-subject interaction effect (TIME*GROUP) [F (15, 123) = 1.65, P= 0.069, η2 = 0.17] and within-subject effect (TIME) [F (3, 123) =17.87, P < 0.001, η2 =0.30] (Table 2 & Figure 3).

Mixed repeated measures ANOVA were conducted to test differences among the groups on the anxiety. Group (tACS.clasic, tACS. Real, Control, Sham, CBM and CBM+tACS) as between-subject and assessment time (pre-intervention, post-intervention, follow-up1 and follow-up2) as within-subject were tested. Similarities were found between the groups at pretest, there was significant differences between groups [F (5, 41) =1.26 , P= 0.29, η2 =0.13], between-subject by within-subject interaction effect (TIME*GROUP) [F (15, 123) = 2.05, P< 0.05, η2 = 0.20] and within-subject effect (TIME) [F (3, 123) =13.31, P < 0.001, η2 =0.24] (Table 2 & Figure 4).

Mixed repeated measures ANOVA were conducted to test differences among the groups on the drug dependence (DDQ). Group (tACS.10 hz, tACS. Real, Control, Sham, CBM and CBM+tACS) as between-subject and assessment time (pre-intervention, post-intervention, follow-up1 and follow-up2) as within-subject were tested. Similarities were found between the groups at pretest, there was significant differences between groups [F (5, 41) =1.99 , P< 0.05, η2 =0.20], between-subject by within-subject interaction effect (TIME*GROUP) [F (15, 123) = 2.78, P< 0.001, η2 = 0.25] and within-subject effect (TIME) [F (3, 123) =18.43, P < 0.001, η2 =0.31] (Table 2 & Figure 5).

Mixed repeated measures ANOVA were conducted to test differences among the groups on the (VAS). Group (tACS.10 hz, tACS. Real, Control, Sham, CBM and CBM+tACS) as between-subject and assessment time (pre-intervention, post-intervention, follow-up1 and follow-up2) as within-subject were tested. Similarities were found between the groups at pretest, there was significant differences between groups [F (5, 41) =1.99 , P= 0.05, η2 =0.20], between-subject by within-subject interaction effect (TIME*GROUP) [F (15, 123) = 2.78, P< 0.001, η2 = 0.25] and within-subject effect (TIME) [F (3, 123) =18.43, P < 0.001, η2 =0.31]. (Table 2 & Figure 6).

The present study investigated the impact of 5 sessions of 10 Hz tACS and 5 sessions of TACS based on IAF on the bilateral DLPFC (dorsolateral prefrontal cortex), with anodal stimulation of the right hemisphere and cathodal stimulation of the left hemisphere, on drug craving, anxiety, depression, and attention bias in individuals with substance use disorders.

The primary aim was to compare the efficacy of the two TACS methods. However, no significant differences were observed between the two tACS methods, and neither intervention was effective in reducing cravings, anxiety, depression, or attention bias in individuals with substance use disorders.

Individual alpha frequency (IAF) is known to decrease with age, potentially impacting cognitive abilities in adulthood (Cesnaite et al., 2023).

Garn et al. (2012) reported that individual alpha frequencies are not stable within individuals and can change over time and in response to cognitive states. Additionally, Fresnoza et al. (2018) investigated the effects of transcranial electrical stimulation with alternating current (TACS) on cortical excitability in both young and older individuals. They found that tACS, tailored to each individual's unique alpha frequency, increased cortical excitability in both groups. However, the study also revealed that the mechanisms underlying these effects differed between the groups, with both experiencing changes in intracortical inhibition. The results indicated that TACS had a similar positive effect on both groups, with no significant difference in performance based on age.

Furthermore, Fresnoza et al. (2018) observed an increase in GABA levels in the elderly group and a decrease in the young group following stimulation. This finding suggests that adults may benefit from reduced GABA-mediated inhibition in the sensory-motor cortex for motor sequence learning. Overall, the study suggested that tACS could be a valuable tool for modulating oscillatory activity for therapeutic and cognitive enhancement purposes.

In summary, the studies by Grandy et al. (2013) and Fresnoza et al. (2018) offer contrasting perspectives on the stability and modifiability of individual alpha frequency and its response to cognitive interventions. While Grandy et al. (2013) suggest that IAF is resistant to change, Fresnoza et al. (2018) provide evidence for the modifiability of IAF through TACS, highlighting its potential as a tool for cognitive enhancement. However, further research is needed to reconcile these differing findings and to fully understand the implications for cognitive interventions targeting individual alpha frequency.

Transcranial electrical stimulation (tACS) has demonstrated potential for improving mood and cognition in individuals with major depression, as evidenced by research conducted by Haller et al. (2020). This study involved six participants diagnosed with severe depression, divided into two groups. The first group received two 10-minute stimulation sessions, while the second group underwent ten consecutive days of 20-minute stimulation.

The results revealed a significant reduction in Hamilton depression and Beck depression rating scale scores for both groups, with reductions of 85% and 78% in the first group and 62% and 24% in the second group, respectively, indicating an improvement in depressive symptoms during the treatment period. Additionally, improvements in cognitive function were observed using the N-Back test, suggesting a positive impact of tACS on cognitive performance.

The findings suggest that tACS may contribute to the synchronization of disrupted frequency bands in the frontal and frontal cortex regions of the brain. This synchronization could potentially underlie the observed improvements in mood and cognitive function, highlighting the therapeutic potential of tACS for individuals with major depression. However, further research with larger sample sizes and controlled designs is needed to validate these findings and elucidate the mechanisms underlying the observed effects.

Basanovic et al. (2020) utilized Cognitive Bias Modification (CBM) as a preventive measure for depression in mid- to late-life individuals. The study involved twenty Australian adults diagnosed with depression and employed a controlled trial design. Over a period of 52 weeks, the intervention was administered using computer-based methods.

The secondary findings of the research demonstrated alterations in the severity of depression, as well as changes in attention and interpretation biases. However, the primary outcomes indicated the onset of major depression based on DSM-IV-TR criteria. Notably, by the sixth week of the intervention, a statistically significant difference in depression symptoms was observed between the active CBM group and the control group.

Furthermore, a systematic review and network meta-analysis conducted by Fodor et al. (2021) aimed to assess the efficacy of CBM in treating depression and anxiety disorders. The review suggested that while CBM demonstrates a sustainable effect, the magnitude of its effectiveness is modest. These findings underscore the potential of CBM as an intervention for depression; however, further research is warranted to comprehensively evaluate its long-term efficacy and clinical utility.

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The findings of the current study revealed a significant difference in the reduction of anxiety, depression, and attentional bias among individuals with a history of opium use when the combined tACS and CBM methods were compared to the separate use of tACS and CBM treatments. However, the study results indicated no significant difference in the reduction of craving among individuals with a history of opioid use when comparing the combined tACS and CBM methods to the separate use of these treatments.

In line with these findings, Mondino et al. (2020) investigated the combined approach of attention bias modification (ABM) and transcranial alternate electrical stimulation (tACS) in smokers to reduce craving and impulsive decisions. The study comprised two groups: one receiving the ABM method combined with active tACS stimulation (while the other group received sham ABM stimulation). The ABM method was utilized to evaluate attentional bias towards smoking cues using an eye-tracking device and reaction time on a visual-probe task during the passive viewing of smoking and neutral cues. Craving was assessed through a questionnaire regarding the urge to smoke and impulsive decision-making while awaiting a reward. The results indicated that when combined with ABM, active tACS decreased the duration of viewing smoking images (p = 0.03), halted the increase in spontaneous desire to smoke (p = 0.026), and reduced the proportion of impulsive choices (P = 0.049) compared to the sham and ABM methods alone. However, no statistically significant differences were observed in other dimensions of craving based on reaction time in this study.

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Kroczek et al. (2016) investigated the impact of transcranial direct current stimulation (tDCS) on craving, heart rate variability, and prefrontal brain hemodynamics during exposure to cigarette cues. Twenty-nine participants were randomly assigned to three groups: control (placebo), randomized, and double-blind, with a mean age of 25 years and a standard deviation of 5. For the tDCS procedure, the anode was positioned in the dorsal prefrontal cortex, while the cathode was placed in the orbitofrontal region, with a current intensity of 2 mA. The study's findings revealed that exposure to cigarette cues increased subjective craving and induced changes in heart rate among smokers. Moreover, the connectivity between the orbitofrontal and dorsolateral prefrontal cortices was stronger in the group receiving active stimulation compared to the placebo group. However, tDCS did not yield a significant difference in craving levels or heart rate variability during exposure to cigarette cues.

Salemink et al. (2013) employed the Cognitive Bias Modification (CBM) technique to treat anxiety in patients. The experimental group (n=18) received positive interpretations of ambiguous social situations online for eight days, while the control group (n=18) received a mix of 50% positive and 50% negative interpretations. The study's findings indicated that participants in the experimental group displayed a greater tendency toward positive interpretations compared to those in the control group. Additionally, both groups experienced reductions in anxiety, depression, and psychological tension.

In a systematic review conducted by Fodor et al. (2020) on cognitive bias modification (CBM) interventions in anxiety and depression disorders among individuals aged 18 years and older, studies were identified based on the inclusion of subjects exhibiting clinical or subclinical levels of anxiety or depression. The review revealed that CBM interventions demonstrated consistent yet modest benefits. However, it is important to note that the presence of heterogeneity and potential bias in the reviewed studies may diminish the reliability of these findings.

The current study has several limitations. Firstly, due to restricted participant access, randomization was not implemented as rigorously as desired. Secondly, the reliance on verbal induction of drug craving, requiring researcher presence for measurement, along with coordination challenges for participant attendance at treatment centers, led to unsuccessful follow-up attempts. Thirdly, the study only utilized a single measure to assess and modify cognitive bias. To comprehensively investigate the role of cognitive bias and its effects on craving-related outcomes, incorporating diverse measures to assess attention bias would be advantageous.

Despite these limitations, the present study's results indicate that transcranial electrical stimulation using a 10 Hz alternating current did not significantly differ from electrical stimulation using an individual alpha frequency (IAF). Additionally, cognitive bias modification (CBM) did not appear to mitigate the adverse effects of substance use, including anxiety, depression, and cravings. However, a notable distinction was observed in the combined CBM and tACS intervention compared to CBM or tACS alone, which may be attributed to the brain's adaptability and the effects of electrical stimulation. This study also identified several key areas for further exploration. While previous research has shown the positive effects of CBM on substance use outcomes, the underlying mechanism of this change remains unclear. Future studies should consider incorporating recent theories on attention bias, such as attention variability and control, to develop more effective interventions in this field.

Acknowledgments

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article.

Data availability statement

The data that supports the findings of this study are available from the corresponding author, upon request.

Declaration of generative AI and AI-assisted technologies in the writing process

During the preparation of this work, the authors used ChatGBT in order to improve language. After using this tool, the authors reviewed and edited the content as needed and takes full responsibility for the content of the publication.

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Table 1.

Demographic Characteristics based on Groups

Table 1. Demographic Characteristics based on Groups tACS

(n = 8)

tACSr

(n = 8)

control

(n = 7)

Sham

(n = 8)

CBM

(n=7)

CBM+tACS

(n=9)

Statistical

Analyses

Marital Status (single/married)

(5/3)

(6/2)

(5/2)

(5/3)

(3/4)

(5/4)

χ2(5) = 13.6, P=0.56

Prison (Yes/No)

(2/6)

(5/3)

(4/3)

(3/5)

(5/4)

χ2(5) = 4.05, P=0.54

Selling dug (Yes/No/No Answere)

(0/6/1)

(2/4/2)

(2/4/1)

(3/5/0)

(0/6/1)

(4/5/0)

χ2(10) = 10.55, P=0.39

Unset (S.D)

25.88 (5.27)

19.88 (5.35)

23.43 (5.88)

20.50 (3.70)

23.57 (6.32)

19.78 (3.73)

F(5,41) = 1.98, P= 0.107

Duration of addiction-years

9.50 (4.27)

6.63 (4.50)

7.43 (3.82)

7.38 (1.92)

7.14 (4.59)

11.00 (4.71)

F(5,41) = 1.44, P= 0.23

How many addicts do you know?

14.50 (8.14)

24.88 (31.45)

15.29 (12.25)

11.38 (6.27)

12.43 (8.63)

24.67 (28.95)

F(5,41) = 0.77, P= 0.57

Abstinance from substances-days

29.00 (11.50)

40.25 (27.91)

29.86 (12.72)

30.75 (13.37)

27.43 (14.21)

32.67 (13.51)

F(5,41) = 0.59, P= 0.71

Table 2. Mean and standard deviation of measures in the assessment sessions in the study groups

Group, M (SD)
Measures	tACS.10 hz	tACS. real	Control	Sham	CBM	CBM+tACS
Depression
Pre-test	17.88(2.74)	18.75(2.43)	17.86(5.87)	15.50(6.02)	17.71(4.92)	16.56 (5.17)
Post-test	16.38 (2.50)	16.13(5.03)	16.86(6.66)	13.88(5.51)	16.71(2.69)	11.67(4.74)
Follow up 1	16.0(2.33)	15.25(2.71)	16.86(5.01)	14.37(5.50)	16.14(3.43)	12.44(3.39)
Follow up 2	15.75(2.61)	16.0(3.54)	17.29(4.34)	15.0(5.63)	15.86(2.85)	12.56(3.87)
Anxiety
Pre-test	15.0(2.77)	15.25(3.01)	14.57(3.73)	14.63(4.74)	16.86(2.79)	15.89(4.25)
Post-test	12.75(2.12)	14.63(2.72)	13.86(4.06)	13.13(3.68)	16.14(3.48)	11.33(4.12)
Follow up 1	13.00(1.85)	14.00(1.85)	13.43(4.11)	13.00(2.4)	16.14(2.61)	12.00(3.27)
Follow up 2	12.13(1.35)	13.63(2.44)	15.00(3.46)	13.75(1.67	14.43(2.23)	11.67(2.44)
DDQ
Pre-test	67.13(10.69)	68.88(6.81)	63.00(7.87)	69.25(10.74)	65.43(8.79)	66.11(7.20)
Post-test	61.0(11.04)	60.50(11.26)	64.29(6.89)	66.13(16.36)	55.86(9.28)	49.89(7.18)
Follow up 1	64.13(9.17)	61.63(8.45)	65.71(5.64)	68.63(9.11)	59.29(12.07)	52.78(8.41)
Follow up 2	63.50(10.73)	62.38(11.57)	63.14(6.25)	65.75(5.17)	59.86(10.35)	52.56(9.55)
VAS
Pre-test	62.50(24.92)	67.50(13.62)	66.14(20.75)	60.0(14.88)	65.71(13.67)	64.44(15.29)
Post-test	64.38(18.79)	50.63(22.74)	71.43(23.57)	61.88(18.69)	47.14(10.35)	41.11(11.11)
Follow up 1	60.00(15.11)	48.13(16.46)	62.14(14.96)	58.13(15.33)	49.29(23.17)	45.56(13.09)
Follow up 2	59.38(11.78)	50.63(11.47)	67.14(18.89)	61.88(10.67)	52.14(19.76)	46.44(9.48

Note: M: mean, SD: standard deviation, DDQ: Drug Dependence Questionar

Table 3. The result of mixed repated ANOVAs for effect of group and time on mental distress and drug dependance

Task	Source	df	F	P-Value	Partial eta
Depression
	Time	3-123	17.873	0.001	0.304
	Group	5-41	1.104	0.373	0.119
	Time*Group	15-123	1.653	0.069	0.168
Anxiety
	Time	3-123	13.314	0.001	0.245
	Group	5-41	1.261	0.299	0.133
	Time*Group	15-123	2.057	0.028	0.201
DDQ
	Time	3-123	18.43	0.001	0.31
	Group	5-41	1.99	0.049	0.20
	Time*Group	15-123	2.78	0.001	0.25
VAS
	Time	3-123	7.17	0.001	0.16
	Group	5-41	1.76	0.142	0.177
	Time*Group	15-123	1.86	0.034	0.18

No competing interests reported.

Effectiveness of Transcranial Alternating Current Stimulation (tACS) and Cognitive Bias Modification (CBM) in Treating Anxiety, Depression, Attentional Bias, and Drug Craving in Opioid-Dependent Patients; A Randomized controlled trial

Status:

Version 1

Abstract

Figures

1. Introduction

2. Methods

3. Results

4. Discussion

Declarations

References

Tables

Additional Declarations

Status:

Version 1