Computerized cognitive control training to reduce rumination in major depression: A randomized controlled trial.

OBJECTIVE: Rumination is a major risk factor for the onset and recurrence of depressive episodes and has been associated with deficits in updating working memory content. This randomized controlled trial examines whether training updating-specific cognitive control processes reduces daily ruminative thoughts in clinically depressed individuals. METHODS: Sixty-five individuals with a current major depressive episode were randomized to 10 sessions of either cognitive control training (N = 31) or placebo training (N = 34). The frequency and negativity of individuals' daily ruminative thoughts were assessed for seven days before training, after training, and at a 3-month follow-up using experience sampling methodology. Secondary outcomes were depressive symptoms, depressed mood, and level of disability. RESULTS: Cognitive control training led to stronger improvements in the trained task than placebo training. However, cognitive control training did not lead to greater reductions in the frequency or negativity of daily ruminative thoughts than placebo training. There were no training-specific effects on participants' depressive symptoms or level of disability. CONCLUSIONS: The robustness of the present null-findings, combined with the methodological strengths of the study, suggest that training currently depressed individuals to update emotional content in working memory does not affect the frequency or negativity of their daily ruminative thoughts.

Methylphenidate and Short-Term Cardiovascular Risk.

Importance: There are concerns about the safety of medications for treatment of attention-deficit/hyperactivity disorder (ADHD), with mixed evidence on possible cardiovascular risk. Objective: To assess whether short-term methylphenidate use is associated with risk of cardiovascular events. Design, Setting, and Participants: This retrospective, population-based cohort study was based on national Swedish registry data. Participants were individuals with ADHD aged 12 to 60 years with dispensed prescriptions of methylphenidate between January 1, 2007, and June 30, 2012. Each person receiving methylphenidate (n = 26 710) was matched on birth date, sex, and county to up to 10 nonusers without ADHD (n = 225 672). Statistical analyses were performed from September 13, 2022, to May 16, 2023. Main Outcomes and Measures: Rates of cardiovascular events, including ischemic heart disease, venous thromboembolism, heart failure, or tachyarrhythmias, 1 year before methylphenidate treatment and 6 months after treatment initiation were compared between individuals receiving methylphenidate and matched controls using a bayesian within-individual design. Analyses were stratified by history of cardiovascular events. Results: The cohort included 252 382 individuals (15 442 [57.8% men]; median age, 20 (IQR, 15-31) years). The overall incidence of cardiovascular events was 1.51 per 10 000 person-weeks (95% highest density interval [HDI], 1.35-1.69) for individuals receiving methylphenidate and 0.77 (95% HDI, 0.73-0.82) for the matched controls. Individuals treated with methylphenidate had an 87% posterior probability of having a higher rate of cardiovascular events after treatment initiation (incidence rate ratio [IRR], 1.41; 95% HDI, 1.09-1.88) compared with matched controls (IRR, 1.18; 95% HDI, 1.02-1.37). The posterior probabilities were 70% for at least a 10% increased risk of cardiovascular events in individuals receiving methylphenidate vs 49% in matched controls. No difference was found in this risk between individuals with and without a history of cardiovascular disease (IRR, 1.11; 95% HDI, 0.58-2.13). Conclusions and Relevance: In this cohort study, individuals receiving methylphenidate had a small increased cardiovascular risk vs matched controls in the 6 months after treatment initiation. However, there was little evidence for an increased risk of 20% or higher and for differences in risk increase between people with and without a history of cardiovascular disease. Therefore, before treatment initiation, careful consideration of the risk-benefit trade-off of methylphenidate would be useful, regardless of cardiovascular history.

Smoking is associated with increased eryptosis, suicidal erythrocyte death, in a large population-based cohort.

Smoking has multiple detrimental effects on health, and is a major preventable cause of premature death and chronic disease. Despite the well-described effect of inhaled substances from tobacco smoke on cell toxicity, the association between smoking and suicidal erythrocyte death, termed eryptosis, is virtually unknown. Therefore, the blood samples of 2023 participants of the German National Cohort Study (NAKO) were analyzed using flow cytometry analysis to determine eryptosis from fluorescent annexin V-FITC-binding to phosphatidylserine-exposing erythrocytes. Blood analyses were complemented by the measurement of hematologic parameters including red blood cell count, hematocrit, hemoglobin, mean corpuscular cell volume (MCV) and mean corpuscular hemoglobin (MCH). Eryptosis was higher in smokers than in non- and ex-smokers, and positively associated with the number of cigarettes smoked daily (r = 0.08, 95% CI [0.03, 0.12]). Interestingly, despite increased eryptosis, smokers had higher red blood cell indices than non-smokers. To conclude, smokers were characterized by higher eryptosis than non-smokers, without showing any obvious detrimental effect on classic hematological parameters.

Neural superstatistics for Bayesian estimation of dynamic cognitive models.

Mathematical models of cognition are often memoryless and ignore potential fluctuations of their parameters. However, human cognition is inherently dynamic. Thus, we propose to augment mechanistic cognitive models with a temporal dimension and estimate the resulting dynamics from a superstatistics perspective. Such a model entails a hierarchy between a low-level observation model and a high-level transition model. The observation model describes the local behavior of a system, and the transition model specifies how the parameters of the observation model evolve over time. To overcome the estimation challenges resulting from the complexity of superstatistical models, we develop and validate a simulation-based deep learning method for Bayesian inference, which can recover both time-varying and time-invariant parameters. We first benchmark our method against two existing frameworks capable of estimating time-varying parameters. We then apply our method to fit a dynamic version of the diffusion decision model to long time series of human response times data. Our results show that the deep learning approach is very efficient in capturing the temporal dynamics of the model. Furthermore, we show that the erroneous assumption of static or homogeneous parameters will hide important temporal information.

Association between vitamin D status and eryptosis-results from the German National Cohort Study.

Vitamin D, besides its classical effect on mineral homeostasis and bone remodeling, can also modulate apoptosis. A special form of apoptosis termed eryptosis appears in erythrocytes. Eryptosis is characterized by cell shrinkage, membrane blebbing, and cell membrane phospholipid disorganization and associated with diseases such as sepsis, malaria or iron deficiency, and impaired microcirculation. To our knowledge, this is the first study that linked vitamin D with eryptosis in humans. This exploratory cross-sectional trial investigated the association between the vitamin D status assessed by the concentration of plasma 25-hydroxyvitamin D (25(OH)D) and eryptosis. Plasma 25(OH)D was analyzed by LC-MS/MS, and eryptosis was estimated from annexin V-FITC-binding erythrocytes by FACS analysis in 2074 blood samples from participants of the German National Cohort Study. We observed a weak but clear correlation between low vitamin D status and increased eryptosis (r = - 0.15; 95% CI [- 0.19, - 0.10]). There were no differences in plasma concentrations of 25(OH)D and eryptosis between male and female subjects. This finding raises questions of the importance of vitamin D status for eryptosis in terms of increased risk for anemia or cardiovascular events.

Experimental induction of peritraumatic dissociation: The role of negative affect and pain and their psychophysiological and neural correlates.

While research has elucidated processes underlying dissociative symptoms in patients with posttraumatic stress disorder, little is known about the circumstances under which trauma-related dissociation initially arises. To experimentally investigate causes and concomitants of peritraumatic dissociation, we subjected sixty-nine healthy women to aversive-audiovisual and painful-electrical stimulation in a 2(aversive/neutral film) x 2(pain/no pain) within-subject design while recording psychophysiological and fMRI-BOLD responses. Afterwards, participants rated negative-affect, pain, and dissociation for each condition. Using Bayesian multilevel regression models, we examined (1) whether aversive-audiovisual and painful-electrical stimulation elicit higher dissociation-levels than control conditions and (2) whether stronger negative-affect and pain responses (operationalized via self-report, psychophysiological, and neural markers) correlate with higher dissociation-levels. Several key findings emerged: Both aversive-audiovisual and painful-electrical stimulation elicited dissociation. Dissociation was linked to higher self-reported negative-affect, but we did not find enough evidence linking it to psychophysiological and neural negative-affect markers. However, dissociation was associated with higher levels of self-reported pain, a skin-conductance-response-based pain marker, and the fMRI-BOLD-based Neurologic-Pain-Signature. Results indicate that both aversive-audiovisual and painful stimuli can independently cause dissociation. Critically, pain responses captured via self-report, psychophysiological, and neural markers were consistently linked to higher dissociation-levels suggesting a specific, evolutionary meaningful, contribution of pain to the rise of dissociation.

Heterogeneous heterogeneity by default: Testing categorical moderators in mixed-effects meta-analysis.

Categorical moderators are often included in mixed-effects meta-analysis to explain heterogeneity in effect sizes. An assumption in tests of categorical moderator effects is that of a constant between-study variance across all levels of the moderator. Although it rarely receives serious thought, there can be statistical ramifications to upholding this assumption. We propose that researchers should instead default to assuming unequal between-study variances when analysing categorical moderators. To achieve this, we suggest using a mixed-effects location-scale model (MELSM) to allow group-specific estimates for the between-study variance. In two extensive simulation studies, we show that in terms of Type I error and statistical power, little is lost by using the MELSM for moderator tests, but there can be serious costs when an equal variance mixed-effects model (MEM) is used. Most notably, in scenarios with balanced sample sizes or equal between-study variance, the Type I error and power rates are nearly identical between the MEM and the MELSM. On the other hand, with imbalanced sample sizes and unequal variances, the Type I error rate under the MEM can be grossly inflated or overly conservative, whereas the MELSM does comparatively well in controlling the Type I error across the majority of cases. A notable exception where the MELSM did not clearly outperform the MEM was in the case of few studies (e.g., 5). With respect to power, the MELSM had similar or higher power than the MEM in conditions where the latter produced non-inflated Type 1 error rates. Together, our results support the idea that assuming unequal between-study variances is preferred as a default strategy when testing categorical moderators.

A review of applications of the Bayes factor in psychological research.

The last 25 years have shown a steady increase in attention for the Bayes factor as a tool for hypothesis evaluation and model selection. The present review highlights the potential of the Bayes factor in psychological research. We discuss six types of applications: Bayesian evaluation of point null, interval, and informative hypotheses, Bayesian evidence synthesis, Bayesian variable selection and model averaging, and Bayesian evaluation of cognitive models. We elaborate what each application entails, give illustrative examples, and provide an overview of key references and software with links to other applications. The article is concluded with a discussion of the opportunities and pitfalls of Bayes factor applications and a sketch of corresponding future research lines. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Amortized Bayesian Model Comparison With Evidential Deep Learning.

Comparing competing mathematical models of complex processes is a shared goal among many branches of science. The Bayesian probabilistic framework offers a principled way to perform model comparison and extract useful metrics for guiding decisions. However, many interesting models are intractable with standard Bayesian methods, as they lack a closed-form likelihood function or the likelihood is computationally too expensive to evaluate. In this work, we propose a novel method for performing Bayesian model comparison using specialized deep learning architectures. Our method is purely simulation-based and circumvents the step of explicitly fitting all alternative models under consideration to each observed dataset. Moreover, it requires no hand-crafted summary statistics of the data and is designed to amortize the cost of simulation over multiple models, datasets, and dataset sizes. This makes the method especially effective in scenarios where model fit needs to be assessed for a large number of datasets, so that case-based inference is practically infeasible. Finally, we propose a novel way to measure epistemic uncertainty in model comparison problems. We demonstrate the utility of our method on toy examples and simulated data from nontrivial models from cognitive science and single-cell neuroscience. We show that our method achieves excellent results in terms of accuracy, calibration, and efficiency across the examples considered in this work. We argue that our framework can enhance and enrich model-based analysis and inference in many fields dealing with computational models of natural processes. We further argue that the proposed measure of epistemic uncertainty provides a unique proxy to quantify absolute evidence even in a framework which assumes that the true data-generating model is within a finite set of candidate models.

Not within spitting distance: Salivary immunoassays of estradiol have subpar validity for predicting cycle phase.

Salivary steroid immunoassays are widely used in psychoneuroendocrinological studies of menstrual cycle phase, puberty, and menopause. Though manufacturers advertise their assays as suitable, they have not been rigorously validated for these purposes. We collated data from eight menstrual cycle studies across > 1200 female participants and > 9500 time points. Seven studies collected saliva and one collected serum. All assayed estradiol and progesterone and had an independent measure of cycle phase (LH-surge, menstrual onset). In serum, cycle phase measures strongly predicted steroid concentrations. In saliva, cycle phase poorly predicted estradiol values, which showed an upward bias compared to expectations from serum. For salivary progesterone, predictability from cycle phase was mixed, low for enzyme-linked assays and moderate for tandem mass spectrometry. Imputing the population-average serum steroid changes from cycle phase may yield more valid values of hormonal changes for an independent person than directly assessing their hormone levels using salivary immunoassays.

The effectiveness of cognitive behavioural therapy for social anxiety disorder in routine clinical practice.

Numerous randomized controlled trials have shown cognitive behaviour therapy (CBT) to be effective in treating social anxiety disorder (SAD). Yet, less is known about the effectiveness of CBT for SAD conducted by psychotherapists in training in routine clinical practice. In this study, 231 patients with SAD were treated with CBT under routine conditions and were examined at pre- and post-treatment as well as at 6 and 12 months follow-up. We applied self-reports to assess symptoms of SAD (defined as primary outcome), depression and psychological distress (defined as secondary outcome). We conducted both completer and intent-to-treat analyses and also assessed the reliability of change with the reliable change index. Results revealed significant reductions in symptoms of SAD between pre- and post-assessments, with effect sizes ranging from d = 0.9 to 1.2. Depending on the SAD specific questionnaire applied, 47.8% to 73.5% of the sample showed a reliable positive change, whereas 1.9% to 3.8% showed a reliable negative change. Depressive symptoms and psychological distress also decreased significantly from pre- to post-assessment, with large effect sizes. Significant treatment gains regarding both primary and secondary outcomes were further observed at 6 and 12 months follow-up. The current findings based on a large sample of patients suggest that psychotherapists in CBT training working under routine conditions can effectively treat symptoms of SAD, depression and psychological distress.

Multiple pore lining residues modulate water permeability of GlpF.

The water permeability of aquaporins (AQPs) varies by more than an order of magnitude even though the pore structure, geometry, as well as the channel lining residues are highly conserved. However, channel gating by pH, divalent ions or phosphorylation was only shown for a minority of AQPs. Structural and in silico indications of water flux modulation by flexible side chains of channel lining residues have not been experimentally confirmed yet. Hence, the aquaporin "open state" is still considered to be a continuously open pore with water molecules permeating in a single-file fashion. Using protein mutations outside the selectivity filter in the aqua(glycerol)facilitator GlpF of Escherichia coli we, to the best of our knowledge, for the first time, modulate the position of the highly conserved Arg in the selectivity filter. This in turn enhances or reduces the unitary water permeability of GlpF as shown in silico by molecular dynamics (MD) simulations and in vitro with purified and reconstituted GlpF. This finding suggests that AQP water permeability can indeed be regulated by lipid bilayer asymmetry and the transmembrane potential. Strikingly, our long-term MD simulations reveal that not only the conserved Arg in the selectivity filter, but the position and dynamics of multiple other pore lining residues modulate water passage through GlpF. This finding is expected to trigger a wealth of future investigations on permeability and regulation of AQPs among others with the aim to tune water permeability for biotechnological applications.

Estradiol during (analogue-)trauma: Risk- or protective factor for intrusive re-experiencing?

Intrusions, a key symptom of posttraumatic stress disorder (PTSD), can occur in the form of images but also as pain sensations. Similar to audiovisual intrusions, the frequency and persistence of pain intrusions varies greatly between individuals. In the current study, we examined whether peritraumatic circulating 17ß-estradiol (E2) levels are a biologic factor associated with subsequent audiovisual (i.e., film) and pain intrusion development, and whether peritraumatic stress levels modulate this relationship. Forty-one free-cycling women participated in an ecologically informed trauma-pain-conditioning (TPC) paradigm, using trauma-films and pain as unconditioned stimuli. Independent variables were salivary peritraumatic E2 levels and stress indexed by salivary cortisol and self-reported state-anxiety during TPC. Outcomes were film- and pain-intrusions occurring during daily-life in the week following TPC and a Memory-Triggering-Task in response to conditioned stimuli 24 h after TPC. In the week after analogue-trauma, higher peritraumatic E2 levels were associated with a greater probability of experiencing film-intrusions in the beginning of the week, which switched to a lower probability toward the end of the week. This time-dependent relationship between E2 and film-intrusions only held for higher state-anxious women. In contrast, results indicated a consistent inverse relationship between peritraumatic E2 levels and pain-intrusions during daily-life and Memory-Triggering-Task. Together, these data suggest that higher peritraumatic E2 levels could be associated with lower long-term visual trauma intrusions, as well as lower pain-intrusions, and thereby possibly constitute a protective biologic factor for PTSD and potentially also for chronic pain.

Atlas of type 2 dopamine receptors in the human brain: Age and sex dependent variability in a large PET cohort.

BACKGROUND: The dopamine system contributes to a multitude of functions ranging from reward and motivation to learning and movement control, making it a key component in goal-directed behavior. Altered dopaminergic function is observed in neurological and psychiatric conditions. Numerous factors have been proposed to influence dopamine function, but due to small sample sizes and heterogeneous data analysis methods in previous studies their specific and joint contributions remain unresolved. METHODS: In this cross-sectional register-based study we investigated how age, sex, body mass index (BMI), as well as cerebral hemisphere and regional volume influence striatal type 2 dopamine receptor (D2R) availability in the human brain. We analyzed a large historical dataset (n=156, 120 males and 36 females) of [11C]raclopride PET scans performed between 2004 and 2018. RESULTS: Striatal D2R availability decreased through age for both sexes (2-5 % in striatal ROIs per 10 years) and was higher in females versus males throughout age (7-8% in putamen). BMI and striatal D2R availability were weakly associated. There was no consistent lateralization of striatal D2R. The observed effects were independent of regional volumes. These results were validated using two different spatial normalization methods, and the age and sex effects also replicated in an independent sample (n=135). CONCLUSIONS: D2R availability is dependent on age and sex, which may contribute to the vulnerability of neurological and psychiatric conditions involving altering D2R expression.

Workflow techniques for the robust use of bayes factors.

Inferences about hypotheses are ubiquitous in the cognitive sciences. Bayes factors provide one general way to compare different hypotheses by their compatibility with the observed data. Those quantifications can then also be used to choose between hypotheses. While Bayes factors provide an immediate approach to hypothesis testing, they are highly sensitive to details of the data/model assumptions and it's unclear whether the details of the computational implementation (such as bridge sampling) are unbiased for complex analyses. Here, we study how Bayes factors misbehave under different conditions. This includes a study of errors in the estimation of Bayes factors; the first-ever use of simulation-based calibration to test the accuracy and bias of Bayes factor estimates using bridge sampling; a study of the stability of Bayes factors against different MCMC draws and sampling variation in the data; and a look at the variability of decisions based on Bayes factors using a utility function. We outline a Bayes factor workflow that researchers can use to study whether Bayes factors are robust for their individual analysis. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The Mediating Effects of Work Characteristics on the Relationship between Transformational Leadership and Employee Well-Being: A Meta-Analytic Investigation.

Evidence points to an indirect relationship between transformational leadership (TFL) and employee well-being, and numerous work characteristics have been identified as mediators. However, the relative mediating effect of different types of job resources and job demands on the TFL-well-being relationship remains unclear, rendering it impossible to determine which ones are the most influential. This study aims to provide a comprehensive analysis of the relative mediation potential of different work characteristics in the TFL-well-being relationship in multiple three-level meta-analytical structural equation models of 243 samples. Based on the JD-R Model, this study extends this theoretical framework by suggesting TFL as a predisposing variable that influences both job resources and job demands, leading to changes in indicators of both positive and negative employee well-being. The results show that, while all the examined job resources and demands mediated the TFL-well-being relationship, organizational resources were identified as the strongest mediators. Furthermore, job demands had a strong mediating effect on the relationship between TFL and negative well-being, while job resources more strongly mediated TFL and positive well-being. We present a differentiated picture of how transformational leaders can influence their employees' well-being at the workplace, providing valuable knowledge for future research and practice.

On the Information Obtainable from Comparative Judgments.

Personality tests employing comparative judgments have been proposed as an alternative to Likert-type rating scales. One of the main advantages of a comparative format is that it can reduce faking of responses in high-stakes situations. However, previous research has shown that it is highly difficult to obtain trait score estimates that are both faking resistant and sufficiently accurate for individual-level diagnostic decisions. With the goal of contributing to a solution, I study the information obtainable from comparative judgments analyzed by means of Thurstonian IRT models. First, I extend the mathematical theory of ordinal comparative judgments and corresponding models. Second, I provide optimal test designs for Thurstonian IRT models that maximize the accuracy of people's trait score estimates from both frequentist and Bayesian statistical perspectives. Third, I derive analytic upper bounds for the accuracy of these trait estimates achievable through ordinal Thurstonian IRT models. Fourth, I perform numerical experiments that complement results obtained in earlier simulation studies. The combined analytical and numerical results suggest that it is indeed possible to design personality tests using comparative judgments that yield trait scores estimates sufficiently accurate for individual-level diagnostic decisions, while reducing faking in high-stakes situations. Recommendations for the practical application of comparative judgments for the measurement of personality, specifically in high-stakes situations, are given.

Can Regenerative Agriculture increase national soil carbon stocks? Simulated country-scale adoption of reduced tillage, cover cropping, and ley-arable integration using RothC.

Adopting Regenerative Agriculture (RA) practices on temperate arable land can increase soil organic carbon (SOC) concentration without reducing crop yields. RA is therefore receiving much attention as a climate change mitigation strategy. However, estimating the potential change in national soil carbon stocks following adoption of RA practices is required to determine its suitability for this. Here, we use a well-validated model of soil carbon turnover (RothC) to simulate adoption of three regenerative practices (cover cropping, reduced tillage intensity and incorporation of a grass-based ley phase into arable rotations) across arable land in Great Britain (GB). We develop a modelling framework which calibrates RothC using studies of these measures from a recent systematic review, estimating the proportional increase in carbon inputs to the soil compared to conventional practice, before simulating adoption across GB. We find that cover cropping would on average increase SOC stocks by 10 t·ha-1 within 30 years of adoption across GB, potentially sequestering 6.5 megatonnes of carbon dioxide per year (MtCO2·y-1). Ley-arable systems could increase SOC stocks by 3 or 16 t·ha-1, potentially providing 2.2 or 10.6 MtCO2·y-1 of sequestration over 30 years, depending on the length of the ley-phase (one and four years, respectively, in these scenarios). In contrast, our modelling approach finds little change in soil carbon stocks when practising reduced tillage intensity. Our results indicate that adopting RA practices could make a meaningful contribution to GB agriculture reaching net zero greenhouse gas emissions despite practical constraints to their uptake.

Disease progression of 213 patients hospitalized with Covid-19 in the Czech Republic in March-October 2020: An exploratory analysis.

We collected a multi-centric retrospective dataset of patients (N = 213) who were admitted to ten hospitals in Czech Republic and tested positive for SARS-CoV-2 during the early phases of the pandemic in March-October 2020. The dataset contains baseline patient characteristics, breathing support required, pharmacological treatment received and multiple markers on daily resolution. Patients in the dataset were treated with hydroxychloroquine (N = 108), azithromycin (N = 72), favipiravir (N = 9), convalescent plasma (N = 7), dexamethasone (N = 4) and remdesivir (N = 3), often in combination. To explore association between treatments and patient outcomes we performed multiverse analysis, observing how the conclusions change between defensible choices of statistical model, predictors included in the model and other analytical degrees of freedom. Weak evidence to constrain the potential efficacy of azithromycin and favipiravir can be extracted from the data. Additionally, we performed external validation of several proposed prognostic models for Covid-19 severity showing that they mostly perform unsatisfactorily on our dataset.

Low intensity technology-delivered cognitive behavioral therapy for obsessive-compulsive disorder: a meta-analysis.

BACKGROUND: Cognitive behavioral therapy (CBT) is a well-established treatment for people suffering from obsessive-compulsive disorder (OCD) and technology-based CBT applications are an emerging treatment option for people with OCD. These applications involve treatment protocols with automated content delivery and relatively low clinical contact. Whilst such CBT applications are promising, however, further investigation is needed to establish the efficacy of this treatment approach for individuals with OCD. The aim of the present study was to review the efficacy of technology-delivered CBT with minimal clinician support for OCD using a meta-analytic approach. METHODS: Randomized controlled trials (RCT) were identified through PsycINFO, Medline and Scopus resulting in 18 eligible studies (n = 1707). Control conditions comprised both passive (namely no treatment, other treatments and waitlist controls) and active. Measurement of OCD symptoms improvement was the outcome in each study. RESULTS: Participants in the technology-delivered CBT group scored lower on Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) (g = - 0.59, 95% CI = [- 0.99, - 0.18], p = 0.01), Y-BOCS and Dimensional Obsessive-Compulsive Scale (DOCS) combined (g = - 0.55, 95% CI = [- 0.87, - 0.24], p = 0.003) and Obsessive-Compulsive-Inventory-Revised (OCI-R) (g = - 0.36, 95% CI = [- 0.62, - 0.09], p = 0.02) at post-treatment than passive control groups. There were no significant findings when compared to controls with other treatments. CONCLUSIONS: This meta-analysis suggests that technology-delivered CBT with low personal contact intensity, relative to passive control groups, is an efficacious and promising treatment option for individuals with OCD. Further research is needed to allow for a comparison with control groups with other treatments.