Abstract
Background
Obsessive-compulsive disorder (OCD) often remains partially responsive to first-line treatments such as selective serotonin reuptake inhibitors (SSRI). N-acetylcysteine (NAC), a glutamate-modulating antioxidant, has shown promise as an adjunctive therapy, but prior studies frequently lacked standardized pharmacotherapy and cognitive outcome measures, particularly in Iranian populations.
Methods
In this 12-week, double-blind, placebo-controlled randomized clinical trial (IRCT20170123032145N7, registered on 2023-06-08), 35 adults with moderate to severe OCD were assigned to receive sertraline (200 mg/day) augmented with either NAC (2400 mg/day) or placebo. Clinical symptoms were assessed using the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) at baseline, weeks 4, 8, and 12. Cognitive functioning was evaluated before and after treatment using the Wisconsin Card Sorting Test and the D2 Test of Attention.
Results
This pilot study reveals a significant Time × Group interaction for Y-BOCS Total (p < 0.005), with the NAC group showing greater symptom reduction than placebo. The Obsession subscale demonstrates the strongest effect (p < 0.001), while Compulsion subscale improvements are comparable between groups. Clinical response rate ( ≥ 35% Y-BOCS reduction) is significantly higher in the NAC group (100%) versus placebo (92.6%, p = 0.004). Both groups improve on cognitive measures (processing speed and attention) over time, with no significant between-group differences. Adverse events are mild and comparable.
Conclusions
Adjunctive NAC may enhance early clinical response in OCD, particularly for obsessions, when added to high-dose SSRI (Sertraline) treatment. However, no cognitive advantage is observed within the 12-week period. These preliminary findings support NAC’s safety and potential utility as a short-term adjunctive treatment in OCD.
Subject terms: Obsessive compulsive disorder, Obsessive compulsive disorder
Plain Language Summary
Obsessive-compulsive disorder (OCD) causes unwanted thoughts and repetitive behaviors that interfere with daily life. Standard medications, such as sertraline, help some patients, but many continue to struggle. This study tests whether adding N-acetylcysteine (NAC), a natural dietary supplement, to standard medication could improve outcomes. We randomly assigned 35 adults with moderate to severe OCD to receive sertraline plus NAC or sertraline plus placebo for 12 weeks. People receiving NAC experienced faster relief from obsessive thoughts compared to those taking placebo, with 100% of NAC patients achieving meaningful improvement versus 92.6% in the placebo group. NAC appears safe and may accelerate symptom relief when combined with standard medication, offering patients a potential low-risk option for faster improvement in their symptoms.
Askari, Eghdami, et al. conduct a 12-week double-blind randomized trial testing adjunctive N-acetylcysteine versus placebo added to fixed-dose sertraline in adults with moderate to severe OCD. Adjunctive N-acetylcysteine yields faster and greater obsession symptom reduction than placebo, and is well tolerated, without adding cognitive benefit.
Introduction
Obsessive-compulsive disorder (OCD) is a chronic and debilitating psychiatric condition that affects an estimated 1.3% to 3% of the global population over a lifetime1. It is characterized by the presence of obsessions, compulsions, or both resulting in persistent, intrusive thoughts, urges, or images and repetitive behaviors or mental acts performed to cope with the distress. These symptoms often center around themes such as contamination, harm, symmetry, taboos, or religious matters, which significantly interfere with daily functioning and quality of life2. According to the Global Burden of Disease (GBD) Study, OCD ranks among the top ten leading causes of non-fatal disability (years lived with disability, YLDs) in many high-income countries, contributing to ~0.5–1.3% of total YLDs globally and an estimated 3 million disability-adjusted life years (DALYs) worldwide3.
The pathophysiology of OCD involves a multifaceted interplay of genetic, neurobiological, and environmental factors4. Traditional neurochemical models have emphasized the role of serotonergic, dopaminergic, noradrenergic, and cholinergic systems, leading to for first-line treatments such as selective serotonin reuptake inhibitors (SSRIs)5, clomipramine6, and cognitive behavioral therapy (CBT)7, particularly with exposure and response prevention (ERP)8. Sertraline is one of several first-line, FDA-approved SSRIs for the treatment of OCD in adults9. However, it is not the only drug with a formal indication for OCD; other SSRIs such as fluoxetine, fluvoxamine and paroxetine10. Current guidelines therefore recommend SSRIs (including sertraline) or clomipramine as first‑line pharmacotherapy, with the specific agent chosen largely on the basis of tolerability, comorbidities and patient preference rather than clear superiority in anti‑obsessional efficacy10.
Despite these established therapies, 40–60% of patients fail to achieve sufficient symptom relief or experience limiting side effects, highlighting the need for alternative or adjunctive treatment strategies11.
In addition to the core symptoms of obsessions and compulsions, individuals with OCD often display persistent cognitive deficits12. Especially in domains of executive functioning, such as set-shifting, response inhibition, and attention control13. Prior reviews indicated that these impairments are not only common but also trait-like, suggesting that they may reflect underlying neurobiological vulnerabilities rather than being exclusively secondary to symptom severity14. Importantly, these cognitive deficits are linked to poorer functional outcomes and may persist even after symptomatic improvement with SSRIs15. Despite their clinical relevance, cognitive impairments in OCD have received limited attention in treatment trials.
In recent years, glutamate dysregulation has emerged as a critical mechanism in OCD, particularly within the cortico-striato-thalamo-cortical (CSTC) circuits16. Elevated glutamatergic activity and impaired glutamate clearance have been observed in neuroimaging and genetic studies, supporting the exploration of glutamate-modulating agents such as N-acetylcysteine (NAC)17. NAC, a cysteine prodrug with antioxidant and neuroprotective properties, modulates extracellular glutamate levels via the cystine–glutamate antiporter and helps restoring redox balance, thereby targeting both glutamatergic dysfunction and oxidative stress18,19. Neuroinflammatory pathways, evident by increased pro-inflammatory cytokines and microglial activation also contribute to CSTC circuit abnormalities and may be modulated by NAC20.
Preclinical studies have shown that NAC reduces compulsive and impulsive behaviors in animal models, including excessive grooming and perseverative responses21. These findings parallel core OCD symptom dimensions and are accompanied by improvements in inhibitory control and reduced oxidative markers22. Early clinical trials in humans with OCD and related disorders (e.g., trichotillomania, excoriation disorder, and substance use disorders) suggest that NAC augmentation can reduce symptom severity, with a favorable safety and tolerability profile23. Randomized controlled trials (RCTs) of NAC in OCD and related conditions have shown mixed but encouraging results18. Some demonstrating significant symptom improvement, others reporting more modest or nonsignificant effects, potentially due to variability in study design, dosage, or patient characteristics.
Beyond its role in symptom reduction, NAC has shown potential cognitive benefits24. Preliminary evidence suggests it may enhance executive functioning, reduce cognitive rigidity, and improve attention25, all of which are frequently impaired in individuals with OCD. These multidimensional effects, likely mediated through glutamatergic modulation and antioxidative action, position NAC as a promising adjunctive treatment with both symptomatic and cognitive therapeutic potential in OCD26.
Despite the growing interest in NAC as an adjunctive treatment for OCD, prior studies often suffer from key methodological limitations. Many lack cognitive outcome measures, making it difficult to assess the broader neuropsychological impact of NAC. In addition, heterogeneity in SSRI regimens across studies complicates the interpretation of NAC’s additive effects18. The absence of standardized pharmacotherapy, along with limited use of rigorous methodologies (such as double-blind, placebo-controlled designs) further limits the generalizability of the findings. Moreover, further trials are needed to evaluate the effectiveness of treatment across diverse genetic and cultural backgrounds.
This pilot study reveals that adjunctive NAC enhances early clinical response in obsessive-compulsive disorder, particularly for obsessive symptoms, when added to high-dose sertraline. The findings demonstrate clinical response rates of 100% in the NAC group versus 92.6% in the placebo group, with maximal symptom separation evident at week eight. However, no cognitive advantages emerge within the 12-week treatment period. These results support NAC’s safety profile and suggest potential utility as a short-term adjunctive treatment in OCD, though the magnitude of benefit and its specific mechanisms warrant further investigation in larger, longer-duration trials.
Method
Participant selection and study setting
Participants were recruited between Sept2023-Dec2024 from outpatient psychiatric clinics affiliated with Iran University of Medical Sciences, Tehran, Iran. Eligibility was determined using the Structured Clinical Interview for DSM-5 (SCID-5)27, conducted by trained psychiatrists or supervised psychiatry residents.
Participants were included if they were between 18 and 60 years old, had a primary diagnosis of OCD based on DSM-5 criteria, exhibited a Yale-Brown Obsessive Compulsive Scale (Y-BOCS) score of ≥2128, had not received psychiatric medication or psychotherapy for at least six weeks prior to enrollment, and were able to provide written informed consent.
Participants with comorbid psychiatric disorders (except for mild depressive or anxiety symptoms not meeting diagnostic criteria), a history of neurological disorders, substance use disorders except for cigarette smoking, acute suicidal ideation, or serious medical conditions such as cardiac, renal, or hepatic disease in addition to individuals with intellectual disability, significant cognitive impairment, or current use of psychoactive substances were excluded.
Adverse events and dropout rates were tracked throughout the trial systematically using a brief self-designed checklist based on common treatment-related side effects; participants who developed moderate to severe side effects or experienced significant adverse medical reactions during the trial were to be withdrawn and provided with standard clinical care which none took place throughout the trial.
Study design and randomization
This study employed a randomized, double-blind, placebo-controlled clinical trial design with fixed dosing. Participants were randomly assigned to either the experimental condition or control condition group using block randomization (block size = 4), stratified by study site. Randomization sequences were computer-generated, and allocation concealment was maintained using sequentially numbered, opaque, sealed envelopes. Participants and assessors were blinded to group assignments. No patient or public involvement occurred in the design, conduct, or reporting of the trial.
Both groups received a standardized, fixed-dose regimen of sertraline to minimize confounding effects from variable dosing. Sertraline was initiated at 25 mg/day in week one, increased to 50 mg/day in week two, 75 mg/day in week three, 100 mg/day in week four, 150 mg/day in week five, and reached the target fixed dose of 200 mg/day by week six. This dose was maintained at 200 mg/day for the remainder of the 12-week trial. No individualized dose adjustments were allowed; All participants who complete the trial achieved and maintained the 200 mg/day target dose. Adherence to the sertraline titration schedule was monitored at each visit. No concurrent psychological treatments or additional psychiatric interventions were allowed during the study period. NAC was initiated as adjunctive therapy at 1200 mg every 12 h from week one and sustained throughout the trial, with medications taken daily at home.
Assessments and outcome measures
The first outcome measure was the change in the Y-BOCS Total Score from baseline to Week 12, and the secondary clinical outcomes included changes in the Y-BOCS Obsession and Compulsion subscales to evaluate specific symptom domains. Cognitive endpoints included changes in executive functioning and attention from baseline to Week 12.
Assessments were conducted at strict time intervals: baseline, week 4, week 8, and week 12 for symptom evaluation; and two timepoints for cognitive assessments: baseline, week 12. To minimize heterogeneity, all follow-up visits were scheduled within a window of ±3 days of the target date; and all evaluations were conducted by trained assessors who were blinded to treatment allocation. Assessors underwent standardized training, and reliability among them is established prior to data collection. Any diagnostic discrepancies were resolved by consulting with a senior faculty psychiatrist.
Clinical and cognitive measures
The study included both clinical and neurocognitive outcome measures:
Obsessive-compulsive symptoms were assessed using the Y-BOCS, a semi-structured clinician-administered scale with validated Persian translation29.
Executive functioning, cognitive flexibility, and problem-solving were measured using the Wisconsin Card Sorting Test (WCST)30.
Sustained and selective attention, processing speed, and accuracy were evaluated using the D2 Test of Selective Attention31.
Yale-Brown obsessive compulsive scale
The Y-BOCS was used to assess the severity of obsessive-compulsive symptoms at baseline and at weeks 0, 4, 8, and 12 of treatment. The Y-BOCS is a clinician-rated instrument consisting of 10 items, each scored on a 5-point scale from 0 (no symptoms) to 4 (extreme symptoms), resulting in a total score ranging from 0 to 4032. It provides a standardized measure of symptom severity and is widely employed in both clinical and research settings33. The Persian version of the Y-BOCS has demonstrated strong psychometric properties in previous studies, including high internal consistency and test-retest reliability, supporting its validity for use in Persian-speaking populations29.
Wisconsin card sorting test
The WCST was used to assess participants’ executive functioning at baseline (week 0) and at the end of the intervention (week 12). Originally developed by Berg and Grant, the WCST is designed to evaluate cognitive flexibility, particularly the ability to shift cognitive strategies in response to changing environmental contingencies30. It is widely recognized as a sensitive measure of executive function, including abstract reasoning, set-shifting, and problem-solving abilities30.
The WCST involves four stimulus cards and two sets of 64 response cards. Participants were instructed to match each response card to one of the stimulus cards and received feedback indicating whether their choice was correct or incorrect. Key outcome measures included the number of categories completed, perseverative errors, and set-loss errors, which collectively reflect various components of executive functioning30.
The change in each WCST scale from baseline to week 12 between the two study groups was analyzed to evaluate the effects of the intervention on executive function.
D2 test of selective attention
The D2 Test evaluates visual attention and concentration31. Participants scan rows of letters to identify instances of the target letter “d” with two dashes. The test reports the following indices:
Total Number of Items Processed (TNIP)
Omission Errors (OE)
Commission Errors (CE)
Total Errors (TE = OE + CE)
Concentration Performance (CP)
Fluctuation Rate (FR)
Functional Index (FI = TNIP − TE)
The D2 is completed in ~10 min.
Ethics approval and consent to participate
The study protocol was approved by the Ethics Committee of Iran University of Medical Sciences (ID: IR.IUMS.REC.1402.119). All participants provided written informed consent after receiving a full explanation of the study’s purpose and means. Participants were informed of their right to withdraw at any point without consequence. Individuals experiencing side effects or who wished to discontinue were withdrawn and offered standard clinical care. The trial was registered at the Iranian Registry of Clinical Trials on 2023-06-08 (www.irct.ir; IRCT ID: IRCT20170123032145N7).
Sample size calculation
A priori power analysis (G*Power 3.1.9.7) was conducted for the outcome, Y-BOCS total score, assuming a mixed repeated-measures design with 2 groups (NAC vs placebo) and 4 assessments (baseline, Weeks 4, 8, 12).
The target effect was a group × time interaction of medium magnitude (Cohen’s , approximately partial ), with , power = 0.80, correlation among repeated measures = 0.05, and nonsphericity correction = 1.034. This yielded a minimum total sample size of 26 (13 per arm).
Cognitive outcomes (WCST, D2) were exploratory and were not used to determine the sample size.
Blinding and compliance monitoring
The trial employed a double-blind design. The primary psychiatrist, and participants were all blinded to group assignments. Blinding was maintained using capsules identical in appearance for NAC and placebo and sequentially numbered, opaque, sealed envelopes for allocation concealment.
Treatment compliance was monitored through self-report at each visit. Participants were asked to report daily medication use, and adherence was discussed during each follow-up appointment.
Statistical analysis
Baseline demographic and clinical characteristics were summarized for the total sample and by treatment group. Categorical variables (e.g., sex) were reported as counts and percentages, while continuous variables (e.g., age, Y-BOCS scores, WCST, and D2) were described using means and standard deviations.
To assess baseline equivalence, the distribution of each variable was examined using the Shapiro-Wilk test and visual inspection of histograms and Q-Q plots35. Variables that were non-normally distributed were Y-BOCS total score, WCST non-perseverative errors, WCST categories completed, D2 CE, and D2 FR. These were analyzed using the Mann–Whitney U test. All other continuous variables were normally distributed and were compared using independent samples t-tests36. Categorical variables were assessed with chi-square tests or Fisher’s exact tests where appropriate. Assumptions of sphericity were tested using Mauchly’s test37. Greenhouse-Geisser corrections were applied when sphericity was violated38. Where appropriate, repeated-measures General Linear Models were conducted using pooled multiply imputed datasets39.
All statistical analyses were conducted using SPSS version 2740. Statistical significance was set at p <0.05 (two-tailed). Analyses follow the intention-to-treat (ITT) principle. Missing data were handled using multiple imputations (five datasets) assuming that data were missing at random. In addition, a mixed model for repeated measures (MMRM) on the observed case data (without imputation) was conducted as sensitivity analysis41, to assess the robustness of findings. Rubin’s Rules were applied to pool parameter estimates and standard errors42.
Missing outcome data were handled under a missing‑at‑random (MAR) assumption using multiple imputation with five imputed datasets, and a MMRM was also fitted on the observed cases to assess robustness. To further evaluate the MAR assumption, a sensitivity analysis approximating a missing‑not‑at‑random (MNAR) mechanism was conducted for Y‑BOCS Total by applying last‑observation‑carried‑forward (LOCF) to participants with missing post‑baseline values and re‑estimating the Group×Time interaction in a linear mixed‑effects model.
Multiplicity/type I error control
The primary confirmatory hypothesis was the Group × Time interaction for the Y‑BOCS Total score, tested two‑sided at α = 0.05. To control the overall type I error across multiple outcomes and contrasts, a prespecified hierarchical testing strategy was applied. First, the Group × Time interaction for Y‑BOCS Total was evaluated at the 0.05 significance level. Only if this primary test was statistically significant did we proceed to evaluate the Group × Time interactions for the three related Y‑BOCS outcomes (Total, Obsession, and Compulsion). For these three tests, the Hochberg step‑up procedure was used to control the family‑wise error rate (family α = 0.05; m = 3). Conditional on statistical significance within this family of tests, post‑hoc pairwise comparisons of estimated marginal means between treatment groups at Weeks 4, 8, and 12 were performed. These three time‑point contrasts within each outcome were adjusted using Bonferroni correction (m = 3 comparisons per outcome; adjusted α = 0.0167). This hierarchical gatekeeping approach was used to maintain control of the overall family‑wise type I error rate.
Outcome analyses
General linear models (GLM)
Repeated measures GLMs were used to assess treatment effects over time in variables with normally distributed residuals. In these analyses, time was treated as a within-subject factor, with four levels for the Y-BOCS subscales and two levels for WCST and D2 outcomes. The adjunctive therapy (NAC vs. placebo) was the between-subject factor. Bonferroni adjustment was applied to post-hoc estimated marginal mean comparisons (between-group contrasts at Weeks 4, 8, and 12; m = 3 per outcome). Wilks’ Lambda was used to evaluate multivariate within-subject effects39.
Linear mixed models (LLM)
For outcomes with non-normally distributed residuals (Y-BOCS Total, WCST Categories Completed, CE, and FR), LMMs were used. Fixed effects include time, group, and interaction. Random intercepts were included for each participant. Covariance structures (unstructured or compound symmetry) were chosen according to timepoint count. Models were estimated by Restricted Maximum Likelihood (REML) to better handle non-normality and missing data43.
Post-trial care
Upon completion of the 12-week trial, the investigational adjunctive intervention (NAC/placebo) was discontinued for all participants. Participants who demonstrated a satisfactory clinical response to sertraline continued receiving sertraline at the discretion of their treating psychiatrist. For participants with partial or no response, medication regimens were modified according to standard clinical practice guidelines. No further data collection happened after the endpoint.
Results
Participants characteristics
A total of 35 participants are enrolled in the study, with 19 randomized to the experimental group and 16 to the control group as presented in Fig. 1. The sample consists of of 10 males (28.6%) and 25 females (71.4%), with no significant difference in sex distribution between groups (χ²(1) = 0.10, p = 0.75). The mean age of participants is 39.3 years (SD = 9.9), with the experimental condition group averaging 38.26 years (SD = 10.4) and the control group 40.68 years (SD = 9.53); this difference is not statistically significant (p = 0.47).
Fig. 1.

Flowchart of the participants enrolled in the trial.
A total of nine participants (25.7%) discontinued the treatment before the final assessment all due to personal reasons, six from the experimental condition group and three from the control group. The overall dropout rate does not significantly differ between groups (χ²1) = 0.75, p = 0.39; Fisher’s exact p = 0.46).
Baseline comparison between groups
No significant differences are observed between the NAC and control groups at baseline for any demographic or clinical variable (p > 0.05 for all comparisons), indicating successful randomization and baseline comparability. A full summary of baseline characteristics is provided in Table 1.
Table 1.
Baseline demographic and clinical characteristics of participants with between-group comparisons
| Variable | Total (N = 35) | NAC + Sertraline (n = 19) | Placebo + Sertraline (n = 16) | p-value |
|---|---|---|---|---|
| Sex (n, % male) | 10 (28.6%) | 5 (26.3%) | 5 (31.3%) | 0.75a |
| Age (years), Mean ± SD | 39.3 ± 9.9 | 38.26 ± 10.4 | 40.68 ± 9.53 | 0.47b |
| Sex (Male/Female) | – | 5/14 | 5/11 | 1.0a |
| Y-BOCS Obsession, Mean ± SD | 14.51 ± 3.74 | 14.61 ± 3.22 | 14.68 ± 4.31 | 0.82c |
| Y-BOCS Compulsion, Mean ± SD | 14.65 ± 3.74 | 12.77 ± 3.63 | 12.56 ± 3.14 | 0.92c |
| Y-BOCS Total, Mean ± SD | 27.11 ± 3.58 | 27.88 ± 3.72 | 26.62 ± 3.15 | 0.55c |
| WCST Non-perseverative Errors, Mean ± SD | 24.17 ± 5.90 | 23.22 ± 4.55 | 25.25 ± 7.12 | 0.42c |
| WCST Perseverative Errors, Mean ± SD | 7.32 ± 3.81 | 6.33 ± 2.86 | 8.43 ± 4.48 | 0.21b |
| WCST Categories Completed, Mean ± SD | 3.05 ± 1.25 | 3.33 ± 1.02 | 2.75 ± 1.43 | 0.29c |
| D2 TNIP, Mean ± SD | 240.25 ± 45.10 | 235.57 ± 49.09 | 245.81 ± 40.84 | 0.52b |
| D2 Omission Errors, Mean ± SD | 62.45 ± 44.60 | 61.83 ± 46.69 | 57.50 ± 38.36 | 0.59b |
| D2 Commission Errors, Mean ± SD | 4.94 ± 4.02 | 4.38 ± 3.79 | 5.25 ± 4.26 | 0.68c |
| D2 Total Errors, Mean ± SD | 67.40 ± 43.40 | 66.22 ± 45.20 | 62.75 ± 36.55 | 0.60b |
| D2 Concentration Performance, Mean ± SD | 233.26 ± 42.41 | 231.21 ± 47.23 | 235.31 ± 36.77 | 0.56b |
| D2 Fluctuation Rate, Mean ± SD | 8.51 ± 5.14 | 8.05 ± 4.67 | 9.06 ± 5.76 | 0.62c |
| D2 Functional Index, Mean ± SD | 172.85 ± 88.01 | 173.77 ± 91.10 | 183.06 ± 76.98 | 0.53b |
aChi-square test (for categorical variables).
bIndependent samples t-test for normally distributed variables.
cMann–Whitney U test for non-normally distributed variables.
Yale-Brown obsessive compulsive scale
Y-BOCS total
The linear mixed-effects model reveals significant Group × Time interaction (p ≤0.005), indicating that the reduction in overall OCD symptoms over time is significantly greater in the NAC group compared to placebo. Estimated marginal means demonstrated that the NAC group has significantly lower Y-BOCS total scores compared to placebo at weeks four (MD = −2.52, 95% CI: −3.48 to −1.56), eight (MD = −2.78, 95% CI: −3.80 to −1.76), and 12 (MD = −1.49, 95% CI: −2.19 to −0.79), with maximal separation evident at week eight. These findings demonstrate that NAC augmentation provided clinically meaningful treatment effects, with the NAC group showing a steeper and more sustained decline in overall OCD symptom severity (Fig. 2).
Fig. 2. Mean Y-BOCS total score over time by treatment group.

The NAC group showed significantly greater reduction in symptoms compared to Placebo (Interaction p = 0.001).
According to the prespecified hierarchical testing strategy, the Group × Time interaction for Y‑BOCS Total (the primary endpoint) was first evaluated at the two‑sided 0.05 level. As this test was statistically significant, subsequent analyses of the Y‑BOCS outcomes were performed with multiplicity control.
Error bars indicate standard errors of the mean. Baseline sample sizes were NAC+sertraline n = 19 and placebo+sertraline n = 16, with n at subsequent visits reflecting observed data after dropout.
Y-BOCS obsession
The repeated measures general linear model reveals a significant main effect of time, (F(3, 615) = 1118.55, p < 0.001), indicating substantial reduction in obsession severity over the 12-week treatment period across all participants. More importantly, there is a significant Time × Group interaction, (F(3, 615) = 22.13, p = 0.001), demonstrating that the pattern and rate of symptom reduction differ significantly between the NAC and placebo groups. Contrasts reveal a significant quadratic Time × Group interaction, (F(1, 205) = 69.56, p = 0.001), indicating that the NAC group experience a steeper trajectory of improvement in the early phase of treatment, with faster response evident at Weeks 4 and 8, whereas the placebo group showed more gradual improvement across the treatment period.
Estimated marginal means reveal that the NAC group have significantly lower obsession scores compared to placebo at weeks four (MD = −2.22, 95% CI: −3.00 to −1.43), eight (MD = −2.60, 95% CI: −3.30 to −1.89), and 12 (MD = −1.32, 95% CI: −1.83 to −0.81), with maximal separation evident at week eight. These findings demonstrate clinically meaningful treatment effects favoring NAC augmentation (Fig. 3).
Fig. 3. Mean Y-BOCS obsession scores over time by treatment group.

Error bars represent standard errors. The NAC + Sertraline group shows significantly lower scores compared to placebo at Weeks 4, 8, and 12.
After Hochberg adjustment across the three prespecified Y‑BOCS Group × Time interaction tests (Total, Obsession, Compulsion), the Group × Time interaction remained significant for the Obsession subscale.
Asterisks represent mean Y-BOCS Obsession subscale scores for each treatment group at each time point that were plotted as outliers; error bars indicate standard errors of the mean. Baseline sample sizes were NAC+sertraline n = 19 and placebo+sertraline n = 16
Y-BOCS compulsion
The Compulsion Group × Time interaction is not significant and remained non‑significant after Hochberg multiplicity control across the Y‑BOCS interaction tests (p = 0.597), indicating both groups improve similarly on compulsive symptoms (Supplementary Fig. 1).
Clinical response rate
A responder analysis based on a ≥35% reduction in total Y-BOCS scores shows that 100% of participants in the NAC group and 92.6% in the placebo group achieved clinical response. This difference is statistically significant (χ²(1) = 8.71, p = 0.003; Fisher’s Exact p = 0.004), indicating that NAC augmentation may increase the probability of meaningful improvement in OCD symptomatology.
Table 2 demonstrates the mean of Y-BOCS scores at each timepoints and their comparison with the baseline scores. Within‑group baseline comparisons in this table are descriptive; confirmatory inference is based on the Group × Time interaction models described above.
Table 2.
The mean (±standard deviation) Y-BOCS scores of weeks 4, 8, and 12, and their comparison with the baseline scores (95% CI)
| NAC + Sertraline | Placebo + Sertraline | ||||||
|---|---|---|---|---|---|---|---|
| Mean ± SD | MD | Cohen’s d effect size | Mean ± SD | MD | Cohen’s d effect size | ||
| Obsession | Week 4 | 10.8 ± 3.29 | 3.57 ± 2.24 | 1.59 | 12.9 ± 3.81 | 1.76 ± 1.43 | 1.42 |
| Week 8 | 7.95 ± 2.50 | 6.42 ± 2.40 | 2.67 | 10.47 ± 3.58 | 4.22 ± 1.79 | 2.36 | |
| Week 12 | 5.8 ± 1.89 | 8.57 ± 2.60 | 3.30 | 7.09 ± 2.19 | 7.60 ± 2.91 | 2.61 | |
| Compulsion | Week 4 | 10.35 ± 2.93 | 2.34 ± 2.35 | 1.00 | 10.6 ± 2.92 | 1.96 ± 1.66 | 1.18 |
| Week 8 | 8.28 ± 2.93 | 4.41 ± 2.59 | 1.70 | 8.4 ± 2.13 | 4.17 ± 2.07 | 1.95 | |
| Week 12 | 5.65 ± 2.47 | 7.03 ± 3.18 | 2.21 | 5.64 ± 1.94 | 6.92 ± 2.39 | 2.89 | |
| Total | Week 4 | 21.08 ± 3.78 | 6.44 ± 3.41 | 1.89 | 23.5 ± 3.94 | 3.12 ± 2.91 | 1.07 |
| Week 8 | 16.21 ± 4.13 | 11.32 ± 3.57 | 3.17 | 18.92 ± 4.21 | 7.71 3.25 | 2.37 | |
| Week 12 | 11.38 2.93 | 16.15 3.72 | 4.34 | 12.87 ± 2.74 | 13.75 ± 2.77 | 4.97 | |
Cognitive outcomes
Changes in executive functioning (WCST) and attention (D2 Test) are summarized in Supplementary information.
For the WCST, there are no significant main effects of Time or Group, nor any significant Time × Group interactions in categories completed, perseverative errors, or non-perseverative errors (p = 0.24, p = 0.26, p = 0.64 respectively). Both groups show stable performance over the 12-week period (Supplementary Figs. 2–4 and Supplementary Table 1).
For the D2 Test of Attention, there is a significant main effect of Time for TNIP (p = 0.020) and Omission Errors (p = 0.022), indicating that all participants, regardless of treatment assignment, improve their processing speed and sustained attention over the course of the study. However, no significant Time × Group interactions are observed for any D2 index, suggesting that NAC augmentation do not confer additional cognitive benefits beyond the practice effects or general clinical improvement seen in the placebo group (Supplementary Figs. 5–11 and Supplementary Table 1).
Sensitivity analysis
Sensitivity analysis using a Mixed Model for Repeated Measures (MMRM) on the observed case data (without imputation) yields consistent results, confirming the robustness of the primary findings.
In the additional MNAR-oriented sensitivity analysis using LOCF for missing Y-BOCS Total values, the Group × Time interaction remains non-significant (p = 0.23), and the direction and magnitude of the estimated treatment effects closely parallel those from the MAR-based models. This supports the robustness of the efficacy findings to plausible deviations from the MAR assumption (Table 3).
Table 3.
Proportion of missing Y-BOCS Total scores at each visit by treatment group from baseline
| Visit | NAC sertraline (n = 19), n missing (%) | Placebo sertraline (n = 16), n missing (%) | Total (N = 35), n missing (%) |
|---|---|---|---|
| Week 4 | 1 (5.3%) | 1 (6.3%) | 2 (5.7%) |
| Week 8 | 1 (5.3%) | 1 (6.3%) | 2 (5.7%) |
| Week 12 | 1 (5.3%) | 2 (12.5%) | 3 (8.6%) |
Adverse drug reaction (ADR)
ADRs are transient and non-severe, without any cases necessitating treatment discontinuation. Using Fisher’s Exact Test, the frequency of side effects is not significantly different between the groups (Table 4)
Table 4.
Comparison of the frequency of adverse events between the two groups (N, %)
| ADR | NAC + Sertraline (n = 19) | Placebo + Sertraline (n = 16) | p-value |
|---|---|---|---|
| Decreased Libido | 2 (10.5%) | 2 (12.5%) | 1.0 |
| Decreased appetite | 1 (5.2%) | 1 (6.25%) | 1.0 |
| Headache | 1 (5.2%) | – | 1.0 |
| Dyspepsia | – | 1 (6.25%) | 0.4 |
Discussion
This randomized, double-blind clinical trial investigated the efficacy of N-acetylcysteine (NAC) as an adjunctive treatment to sertraline over a 12-week period, with parallel evaluation of clinical and cognitive outcomes in an Iranian population. This pilot study was designed to assess whether glutamatergic modulation via NAC could provide additional benefits beyond optimized SSRI therapy.
Our results demonstrated that NAC combined with sertraline was associated with a faster and numerically greater reduction in Y-BOCS obsession and total scores, reflected by a significant Time × Group interaction. Responder rates (defined as ≥35% reduction in Y-BOCS total score) were high in both groups, reaching 100% in the NAC+ sertraline arm and 92.6% in the placebo + sertraline arm. In contrast, aside from a small, non-significant trend toward improved attentional consistency, NAC did not confer statistically significant advantages over placebo on executive function or attention as measured by the WCST and D2 tests. Both treatment arms were well tolerated, with only mild and transient adverse events reported, no treatment discontinuations, and no significant between-group differences in side-effect profiles.
Taken together, these findings suggest that adjunctive NAC may be associated with an earlier reduction in obsessive symptoms. However, given the modest effect sizes and the absence of consistent between-group differences across all outcomes, this interpretation should be considered preliminary. This pattern is consistent with hypotheses suggesting that glutamatergic modulation may influence intrusive thoughts earlier in treatment, whereas serotonergic mechanisms are generally associated with more gradual clinical improvement. Nonetheless, the present design does not allow definitive separation of these temporal effects44,45.
Additionally, a degree of symptom-dimension specificity was observed. The apparent benefits of NAC were largely confined to obsessive symptoms, while compulsive behaviors showed less pronounced change. This distinction is clinically plausible, as compulsions are often more rooted behavioral patterns that may require longer treatment durations, targeted behavioral interventions such as ERP, or potentially higher NAC doses to achieve meaningful change18,46.
Despite this, the overall response rate across both groups was unusually high (93–100%). This ceiling effect may reflect: I) the robust efficacy of sertraline at 200 mg/day47, II) expectancy or placebo effects in a structured academic clinical trial setting48, or III) statistical fluctuation due to small sample size49. Such high overall response rates may have limited the statistical detectability of incremental between-group differences attributable specifically to NAC augmentation.
The present results are broadly consistent with prior research. A recent meta-analysis of six randomized controlled trials (n = 195) reported that NAC augmentation significantly reduced total Y-BOCS scores between weeks 5 and 818. However, that analysis did not identify significant improvements on obsession or compulsion subscales individually, and the observed benefits did not persist beyond 12 weeks, which is similar to the temporal pattern reported in the current study18.
These findings contribute to the growing body of evidence implicating glutamatergic dysregulation within CSTC circuits in obsessive-compulsive related disorders (OCRDs)50,51. Elevated glutamate signaling in these circuits has been linked to intrusive thoughts and impaired inhibitory control in neuroimaging and genetic studies50. NAC may target these disruptions by modulating extracellular glutamate through the cystine–glutamate antiporter by restoring redox balance52. The earlier reduction in obsessive symptoms observed in the NAC group is compatible with this mechanistic framework, although causal inferences should remain conservative52.
Importantly, the present findings align with conclusions from umbrella reviews examining glutamate-modulating agents (including NAC, memantine, riluzole, and ketamine) in OCRDs53–56. These reviews suggest that such agents are effective in reducing obsessions, especially early in treatment or among partial SSRI responders53–56. They further emphasize the CSTC specificity of glutamatergic interventions, with benefits concentrated on cortico-striatal hyperactivity rather than on broader cognitive domains57. This framework is consistent with the lack of significant NAC-related improvements in executive function or attention observed in the present study. Accordingly, the current findings extend prior reviews by providing controlled evidence of obsession-focused and temporally early clinical effects of NAC under fixed-dose SSRI adjunction, alongside complementary cognitive outcome data.
An alternative explanation for the observed early improvement in obsessive symptoms is the delayed therapeutic effect of sertraline itself. Selective serotonin reuptake inhibitors, particularly at higher doses, are well known to exert their full anti-obsessional effects after a latency period of ~8–12 weeks, reflecting gradual serotonergic neuroadaptation and downstream cortical–striatal modulation58. Consequently, the early symptom changes observed cannot be unequivocally attributed to NAC augmentation alone.
The absence of statistically significant cognitive benefits may be attributable to several factors. One important consideration is the practice effect, as both the WCST and D2 were administered only 12 weeks apart. Repeated exposure to these tasks can improve performance through familiarity with test structure, reduced performance anxiety, or recall of task demands rather than true cognitive change59. Meta-analytic evidence indicates that re-administration of such tests within two to three months can yield improvements of 0.5 to 1 standard deviation even in the absence of intervention60.
Although NAC did not significantly improve executive function or attention in our findings, inclusion of cognitive outcomes was justified by increasing recognition of persistent cognitive impairments in OCD61. Deficits in set-shifting and sustained attention have been linked to dysfunction within frontostriatal and cingulo-opercular networks61. While robust cognitive benefits were not observed over the 12-week period, subtle trends favoring NAC in attentional consistency suggest that this domain warrants further investigation.
Treatment duration may also have limited detection of cognitive effects. Glutamatergic and antioxidant mechanisms involved in cognitive plasticity may require longer than 12 weeks to manifest measurable changes62, particularly in executive functioning and sustained attention63. Additionally, ceiling effects may have constrained detectability, as several participants entered the trial with high baseline cognitive scores, leaving limited room for improvement on measures such as WCST categories completed and D2 concentration indices64. The modest sample size further raises the possibility of Type II error, reducing power to detect subtle between-group differences65.
Measurement sensitivity represents another consideration. While the WCST and D2 are well-validated instruments, they may lack sensitivity to detect nuanced changes in cognitive control or flexibility66. More refined assessments, such as stop-signal or emotional Stroop tasks, may be better suited to capture subtle neurocognitive effects of NAC67,68.
Finally, the use of high-dose sertraline (200 mg/day) may have produced a therapeutic ceiling, limiting the observable magnitude of NAC augmentation69. It is also plausible that glutamatergic modulation preferentially benefits individuals with underlying CSTC hyperactivity or redox imbalance70. Without baseline biomarker stratification (such as magnetic resonance spectroscopy or peripheral glutathione levels), potential responders and non-responders were likely pooled, limiting observable effects69.
Despite these limitations, this study has several strengths. The fixed-dose SSRI regimen ensured pharmacological consistency and minimized heterogeneity common in prior augmentation trials. Concurrent assessment of clinical and neurocognitive outcomes allowed exploration of symptom–cognition dissociation. Analytically, the study adhered to intention-to-treat principles, employed multiple imputation for missing data, and confirmed findings using MMRM analyses, all of which led to convergent results and support the robustness of the conclusions.
Future studies should employ larger samples to detect moderate adjunctive effects and extend treatment duration to assess longer-term clinical and cognitive outcomes. Exploration of higher NAC doses, if tolerable, may further clarify dose-response relationships. Biomarker-based stratification could help identify individuals most likely to benefit from glutamatergic modulation. Finally, incorporation of dimensional symptom measures and behavioral tasks (such as obsessive belief inventories, response inhibition paradigms, or ecologically valid assessments of compulsivity)71,72 may provide deeper insight into NAC’s specific therapeutic mechanisms.
Conclusion
The results of this pilot study suggest N-acetyl cysteine seems to act as an accelerator rather than a booster in SSRI-treated OCD, speeding the alleviation of obsessions, raising early responder rates, and doing so with great tolerability. Cognitive benefits are not demonstrated, likely owing to methodological ceilings. For clinicians, NAC remains a low-risk option worth practicing in patients seeking quicker obsession relief or partial responders. For researchers, larger, longer, biomarker enhanced studies are needed to assess who truly benefits and to clarify if NAC can add value beyond robust SSRI therapy.
Supplementary information
Description of Additional Supplementary files
Author contributions
S.E., S.V.S., M.T., A.G.J., E.S., and M.S. made substantial contributions to the conception and design of the work. S.A., A.G.J., M.Y., M.T., S.T.E. and M.S. had substantial contribution in data gathering. S.E. and M.S. analyzed and interpreted the data. S.E., M.S. had major contribution in writing the manuscript. All authors read and approved of the final manuscript.
Peer review
Peer review information
Communications Medicine thanks Dalei Chen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. A peer review file is available.
Funding
The authors disclose receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by Iran University of Medical Sciences (Grant no: 1401-4-99-25244).
Data availability
The individual de-identified participant data and the source data for the figures and tables can be found in the Supplementary Data.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
These authors contributed equally: Sanaz Askari, Shayan Eghdami.
Supplementary information
The online version contains supplementary material available at https://doi.org/10.1038/s43856-026-01711-6.
References
- 1.Stein, D. J. et al. Obsessive-compulsive Disorder in the World Mental Health Surveys (Research square, 2025). [DOI] [PMC free article] [PubMed]
- 2.Mancebo, M. C., Eisen, J. L., Grant, J. E. & Rasmussen, S. A. Obsessive compulsive personality disorder and obsessive compulsive disorder: clinical characteristics, diagnostic difficulties, and treatment. Ann. Clin. Psychiatry17, 197–204 (2005). [DOI] [PubMed] [Google Scholar]
- 3.Liu, D. et al. Time trends in anxiety disorders incidence across the BRICS: an age-period-cohort analysis for the GBD 2021. Front. Public Health12, 1467385 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Gillan, C. M., Robbins, T. W., Sahakian, B. J., van den Heuvel, O. A. & van Wingen, G. The role of habit in compulsivity. Eur. Neuropsychopharmacol.26, 828–840 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Eissazade, N. et al. Efficacy and safety of 5-hydroxytryptamine-3 (5-HT3) receptor antagonists in augmentation with selective serotonin reuptake inhibitors (SSRIs) in the treatment of moderate to severe obsessive–compulsive disorder: a systematic review and meta-analysis of randomized clinical trials. Sci. Rep.13, 20837 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Wilson, M. & Tripp, J. Clomipramine (StatPearls Publishing, 2024). [PubMed]
- 7.Fitri, M. & Ardi, Z. The use of cognitive behavioral therapy (CBT) to reduce obsessive compulsive disorder (OCD) behavior. J. Psychol. Counsel. Educ.2, 225–235 (2024). [Google Scholar]
- 8.Trent, E. S., Zhou, R. J., Mammo, L., Goodman, W. K. & Storch, E. A. High intensity approaches to exposure and response prevention for obsessive-compulsive disorder. Behav. Brain Res.481, 115427 (2025). [DOI] [PubMed]
- 9.Fenske, J. N. & Schwenk, T. L. Obsessive compulsive disorder: diagnosis and management. Am. Fam. Physician80, 239–245 (2009). [PubMed] [Google Scholar]
- 10.Kayser, R. R. Pharmacotherapy for treatment-resistant obsessive-compulsive disorder. J. Clin. psychiatry81, 19ac13182 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Roh, D., Jang, K. W. & Kim, C.-H. Clinical advances in treatment strategies for obsessive-compulsive disorder in adults. Clin. Psychopharmacol. Neurosci.21, 676 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Okasha, A. et al. Cognitive dysfunction in obsessive-compulsive disorder. Acta Psychiatr. Scand.101, 281–285 (2000). [PubMed] [Google Scholar]
- 13.Lawrence, N. S. et al. Decision making and set shifting impairments are associated with distinct symptom dimensions in obsessive-compulsive disorder. Neuropsychology20, 409 (2006). [DOI] [PubMed] [Google Scholar]
- 14.Calkins, A. W., Berman, N. C. & Wilhelm, S. Recent advances in research on cognition and emotion in OCD: a review. Curr. psychiatry Rep.15, 357 (2013). [DOI] [PubMed] [Google Scholar]
- 15.Sayyah, M., Eslami, K., AlaiShehni, S. & Kouti, L. Cognitive function before and during treatment with selective serotonin reuptake inhibitors in patients with depression or obsessive-compulsive disorder. Psychiatry J.2016, 5480391 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Boedhoe, P. S. et al. Subcortical brain volume, regional cortical thickness, and cortical surface area across disorders: findings from the ENIGMA ADHD, ASD, and OCD working groups. Am. J. Psychiatry177, 834–843 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Maraone, A., Tarsitani, L., Pinucci, I. & Pasquini, M. Antiglutamatergic agents for obsessive-compulsive disorder: where are we now and what are possible future prospects? World J. Psychiatry11, 568 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Eghdami, S. et al. The safety and efficacy of N-acetylcysteine as an augmentation in the treatment of obsessive-compulsive disorder in adults: a systematic review and meta-analysis of randomized clinical trials. Front Psychiatry15, 1421150 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Eghdami, S., Afrashteh, F., Shojaii, A., Abolhasani, M. & Motevalian, M. The therapeutic effect of alcoholic extract of Fumaria parviflora on high-fat diet-induced nonalcoholic fatty liver in rats: an animal experiment. Ann. Med. Surg.86, 2657–2664 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Meyer, J. Inflammation, obsessive-compulsive disorder, and related disorders. Curr. Top. Behav. Neurosci.49, 31–53 (2021). [DOI] [PubMed]
- 21.Kim, H.-B. et al. N-acetylcysteine alleviates depressive-like behaviors in adolescent EAAC1-/-mice and early life stress model rats. Int. J. Biol. Sci.20, 5450 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Pangrazzi, L. et al. The interplay between oxidative stress and inflammation supports autistic-related behaviors in mice. bioRxiv, https://www.biorxiv.org/content/10.1101/2023.09.11.557109v1.full (2023). [DOI] [PubMed]
- 23.Lee, D. K. & Lipner, S. R. The potential of N-acetylcysteine for treatment of trichotillomania, excoriation disorder, onychophagia, and onychotillomania: an updated literature review. Int. J. Environ. Res. Public Health19, 6370 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Bradlow, R. C., Berk, M., Kalivas, P. W., Back, S. E. & Kanaan, R. A. The potential of N-acetyl-L-cysteine (NAC) in the treatment of psychiatric disorders. CNS drugs36, 451–482 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Khasnavis, S., Belliveau, T., Arnsten, A. & Fesharaki-Zadeh, A. Combined use of guanfacine and N-acetylcysteine for the treatment of cognitive deficits after traumatic brain injury. Neurotrauma Rep.5, 226–231 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Vedaei, F. et al. Treatment effects of N-acetyl cysteine on resting-state functional MRI and cognitive performance in patients with chronic mild traumatic brain injury: a longitudinal study. Front. Neurol.15, 1282198 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Harm, M., Hope, M. & Household, A. Diagnostic and Statistical Manual of Mental Disorders, 5th edn (American Psychiatric Association 2013) www.lancaster.ac.uk.Arya.
- 28.Cervin, M. et al. Empirical severity benchmarks for obsessive-compulsive disorder across the lifespan. World Psychiatry21, 315–316 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Asadi, S. et al. Exploring yale-brown obsessive-compulsive scale symptom structure in Iranian OCD patients using item-based factor analysis. Psychiatry Res.245, 416–422 (2016). [DOI] [PubMed] [Google Scholar]
- 30.Puente, A. Wisconsin card sorting test. Test. Crit.4, 677–682 (1985). [Google Scholar]
- 31.Brickenkamp, R. & Zillmer, E. The d2 test of attention (1st USA ed.). (Hogrefe & Huber Pub., 1998).
- 32.Yousefzadeh, F. et al. 5-Hydroxytryptophan as adjuvant therapy in treatment of moderate to severe obsessive-compulsive disorder: a double-blind randomized trial with placebo control. Int. Clin. Psychopharmacol.35, 254–262 (2020). [DOI] [PubMed] [Google Scholar]
- 33.Askari, S. et al. Memantine augmentation of sertraline in the treatment of symptoms and executive function among patients with obsessive-compulsive disorder: A double-blind placebo-controlled, randomized clinical trial. BMC Psychiatry22, 34 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Faul, F., Erdfelder, E., Buchner, A. & Lang, A.-G. Statistical power analyses using G* Power 3.1: Tests for correlation and regression analyses. Behav. Res. methods41, 1149–1160 (2009). [DOI] [PubMed] [Google Scholar]
- 35.Shapiro, S. S. & Wilk, M. B. An analysis of variance test for normality (complete samples). Biometrika52, 591–611 (1965). [Google Scholar]
- 36.Mann, H. B. & Whitney, D. R. On a test of whether one of two random variables is stochastically larger than the other. Ann. Math. Stat.18, 50–60 (1947).
- 37.Mauchly, J. W. Significance test for sphericity of a normal n-variate distribution. Ann. Math. Stat.11, 204–209 (1940). [Google Scholar]
- 38.Greenhouse, S. W. & Geisser, S. On methods in the analysis of profile data. Psychometrika24, 95–112 (1959). [Google Scholar]
- 39.Schafer, J. L. & Graham, J. W. Missing data: our view of the state of the art. Psychol. Methods7, 147 (2002). [PubMed] [Google Scholar]
- 40.Field, A. Discovering Statistics using IBM SPSS Statistics (Sage publications limited; 2024).
- 41.Mallinckrodt, C. H., Clark, W. S. & David, S. R. Type I error rates from mixed effects model repeated measures versus fixed effects ANOVA with missing values imputed via last observation carried forward. Drug Inf. J.35, 1215–1225 (2001). [Google Scholar]
- 42.Little, R. & Rubin, D. Multiple imputation for nonresponse in surveys. Wiley10, 9780470316696 (1987). [Google Scholar]
- 43.West B. T., Welch K. B. & Galecki A. T. Linear Mixed Models: A Practical Guide using Statistical Software (Chapman and Hall/CRC; 2022).
- 44.Rodriguez, C. I. et al. Randomized controlled crossover trial of ketamine in obsessive-compulsive disorder: proof-of-concept. Neuropsychopharmacology38, 2475–2483 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Hassan, W. et al. Variations in obsessive compulsive disorder symptomatology across cultural dimensions. Front. Psychiatry15, 1329748 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Mogan, C. et al. An outcome study of an intensive, out-patient exposure and response prevention therapy for obsessive compulsive disorder. Cogn. Behav. Therapist18, e21 (2025). [Google Scholar]
- 47.Voss, E. A., Ryan, P. B., Stang, P. E., Hough, D. & Alphs, L. Switching from risperidone long-acting injectable to paliperidone long-acting injectable or oral antipsychotics: analysis of a Medicaid claims database. Int. Clin. Psychopharmacol.30, 151–157 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Hemmelgarn, B. R. et al. Relation between kidney function, proteinuria, and adverse outcomes. JAMA303, 423–429 (2010). [DOI] [PubMed] [Google Scholar]
- 49.Faber, J. & Fonseca, L. M. How sample size influences research outcomes. Dent. Press J. Orthod.19, 27–29 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Zhu, Y. et al. Decreased thalamic glutamate level in unmedicated adult obsessive–compulsive disorder patients detected by proton magnetic resonance spectroscopy. J. Affect. Disord.178, 193–200 (2015). [DOI] [PubMed] [Google Scholar]
- 51.Eghdami, S., Saeidi, M., Gunturu, S., Boroon, M. & Shalbafan, M. Gut microbiota and obsessive–compulsive disorder: a systematic review of mechanistic links, evidence from human and preclinical studies, and therapeutic prospects. Life15, 1585 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Baker, D. A. et al. Contribution of cystine–glutamate antiporters to the psychotomimetic effects of phencyclidine. Neuropsychopharmacology33, 1760–72 (2008). [DOI] [PMC free article] [PubMed]
- 53.Hadi, F., Kashefinejad, S., Kamalzadeh, L., Hoobehfekr, S. & Shalbafan, M. Glutamatergic medications as adjunctive therapy for moderate to severe obsessive-compulsive disorder in adults: a systematic review and meta-analysis. BMC Pharmacol. Toxicol.22, 69 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Marinova, Z., Chuang, D.-M. & Fineberg, N. Glutamate-modulating drugs as a potential therapeutic strategy in obsessive-compulsive disorder. Curr. Neuropharmacol.15, 977–995 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Pittenger, C. Glutamate modulators in the treatment of obsessive-compulsive disorder. Psychiatr. Ann.45, 308–315 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Shalbafan, M. et al. Fluvoxamine combination therapy with tropisetron for obsessive-compulsive disorder patients: a placebo-controlled, randomized clinical trial. J. Psychopharmacol.33, 1407–1414 (2019). [DOI] [PubMed] [Google Scholar]
- 57.Hajek, T. et al. Brain structural signature of familial predisposition for bipolar disorder: replicable evidence for involvement of the right inferior frontal gyrus. Biol. psychiatry73, 144–152 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Fineberg, N. & Brown, A. Pharmacotherapy for obsessive—compulsive disorder. Adv. Psychiatr. Treat.17, 419–434 (2011). [Google Scholar]
- 59.Calamia, M., Markon, K. & Tranel, D. Scoring higher the second time around: meta-analyses of practice effects in neuropsychological assessment. Clin. Neuropsychologist26, 543–570 (2012). [DOI] [PubMed] [Google Scholar]
- 60.Kirk, R. E. The importance of effect magnitude. In Handbook of Research Methods in Experimental Psychology (ed. Davis, S. F.) 83–105 (Blackwell Publishing Ltd, 2003).
- 61.Bakizadeh, F. et al. Cognitive rehabilitation for adult patients with obsessive-compulsive disorder: a systematic review of randomized controlled trials. Basic Clin. Neurosci.15, 287–300 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Franzoni, F. et al. Oxidative stress and cognitive decline: the neuroprotective role of natural antioxidants. Front. Neurosci.15, 729757 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 63.Wang, X. et al. The effects of enriched rehabilitation on cognitive function and serum glutamate levels post-stroke. Front Neurol.13, 829090 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 64.Wang, L., Zhang, Z., McArdle, J. J. & Salthouse, T. A. Investigating ceiling effects in longitudinal data analysis. Multivar. Behav. Res.43, 476–496 (2008). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 65.Cohen, J. Set correlation and contingency tables. Appl. Psychol. Meas.12, 425–434 (1988). [Google Scholar]
- 66.Bates, M. E. & Lemay, E. P. The d2 Test of Attention: Construct validity and extensions in scoring techniques. J. Int. Neuropsychol. Soc.10, 392–400 (2004). [DOI] [PubMed] [Google Scholar]
- 67.Verbruggen, F. & Logan, G. D. Response inhibition in the stop-signal paradigm. Trends Cogn. Sci.12, 418–424 (2008). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68.Etkin, A., Egner, T. & Kalisch, R. Emotional processing in anterior cingulate and medial prefrontal cortex. Trends Cogn. Sci.15, 85–93 (2011). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69.Johnson, C. F., Maxwell, M., Williams, B., Dougall, N. & MacGillivray, S. Dose-response effects of selective serotonin reuptake inhibitor monotherapy for the treatment of depression: systematic review of reviews and meta-narrative synthesis. BMJ Med.1, e000017 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 70.Berk, M. et al. N-acetyl cysteine for depressive symptoms in bipolar disorder—a double-blind randomized placebo-controlled trial. Biol. Psychiatry64, 468–475 (2008). [DOI] [PubMed] [Google Scholar]
- 71.Eghdami, S., Ahmadkhaniha, H. R., Baradaran, H. R. & Hirbod-Mobarakeh, A. Ecological momentary interventions for smoking cessation: a systematic review and meta-analysis. Soc. Psychiatry Psychiatr. Epidemiol.58, 1431–1445 (2023). [DOI] [PubMed] [Google Scholar]
- 72.Hirbod-Mobarakeh, A. et al. Ecological momentary interventions for bipolar disorder: a systematic review and meta-analysis. Soc. Psychiatry Psychiatric Epidemiol.61, 587–601 (2026). [DOI] [PubMed]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Description of Additional Supplementary files
Data Availability Statement
The individual de-identified participant data and the source data for the figures and tables can be found in the Supplementary Data.
