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The development of COVID-19 vaccines has been crucial in fighting the pandemic. However, misinformation about the COVID-19 pandemic and vaccines is spread on social media platforms at a rate that has made the World Health Organization coin the phrase infodemic. False claims about adverse vaccine side effects, such as vaccines being the cause of autism, were already considered a threat to global health before the outbreak of COVID-19. We aimed to synthesize the existing research on misinformation about COVID-19 vaccines spread on social media platforms and its effects. The secondary aim was to gain insight and gather knowledge about whether misinformation about autism and COVID-19 vaccines is being spread on social media platforms. We performed a literature search on September 9, 2021, and searched PubMed, PsycINFO, ERIC, EMBASE, Cochrane Library, and the Cochrane COVID-19 Study Register. We included publications in peer-reviewed journals that fulfilled the following criteria: original empirical studies, studies that assessed social media and misinformation, and studies about COVID-19 vaccines. Thematic analysis was used to identify the patterns (themes) of misinformation. Narrative qualitative synthesis was undertaken with the guidance of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 Statement and the Synthesis Without Meta-analysis reporting guideline. The risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal tool. Ratings of the certainty of evidence were based on recommendations from the Grading of Recommendations Assessment, Development and Evaluation Working Group. The search yielded 757 records, with 45 articles selected for this review. We identified 3 main themes of misinformation: medical misinformation, vaccine development, and conspiracies. Twitter was the most studied social media platform, followed by Facebook, YouTube, and Instagram. A vast majority of studies were from industrialized Western countries. We identified 19 studies in which the effect of social media misinformation on vaccine hesitancy was measured or discussed. These studies implied that the misinformation spread on social media had a negative effect on vaccine hesitancy and uptake. Only 1 study contained misinformation about autism as a side effect of COVID-19 vaccines. To prevent these misconceptions from taking hold, health authorities should openly address and discuss these false claims with both cultural and religious awareness in mind. Our review showed that there is a need to examine the effect of social media misinformation on vaccine hesitancy with a more robust experimental design. Furthermore, this review also demonstrated that more studies are needed from the Global South and on social media platforms other than the major platforms such as Twitter and Facebook. PROSPERO International Prospective Register of Systematic Reviews CRD42021277524; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021277524. RR2-10.31219/osf.io/tyevj.

Open research data provide considerable scientific, societal, and economic benefits. However, disclosure risks can sometimes limit the sharing of open data, especially in datasets that include sensitive details or information from individuals with rare disorders. This article introduces the concept of synthetic datasets, which is an emerging method originally developed to permit the sharing of confidential census data. Synthetic datasets mimic real datasets by preserving their statistical properties and the relationships between variables. Importantly, this method also reduces disclosure risk to essentially nil as no record in the synthetic dataset represents a real individual. This practical guide with accompanying R script enables biobehavioural researchers to create synthetic datasets and assess their utility via the synthpop R package. By sharing synthetic datasets that mimic original datasets that could not otherwise be made open, researchers can ensure the reproducibility of their results and facilitate data exploration while maintaining participant privacy. It is becoming increasingly common for scientists to share their data with other researchers. This makes it possible to independently verify reported results, which increases trust in research. Sometimes it is not possible to share certain datasets because they include sensitive information about individuals. In psychology and medicine, scientists have tried to remove identifying information from datasets before sharing them by, for example, adding minor artificial errors. But, even when researchers take these steps, it may still be possible to identify individuals, and the introduction of artificial errors can make it harder to verify the original results. One potential alternative to sharing sensitive data is to create ‘synthetic datasets’. Synthetic datasets mimic original datasets by maintaining the statistical properties of the data but without matching the original recorded values. Synthetic datasets are already being used, for example, to share confidential census data. However, this approach is rarely used in other areas of research. Now, Daniel S. Quintana demonstrates how synthetic datasets can be used in psychology and medicine. Three different datasets were studied to ensure that synthetic datasets performed well regardless of the type or size of the data. Quintana evaluated freely available software that could generate synthetic versions of these different datasets, which essentially removed any identifying information. The results obtained by analysing the synthetic datasets closely mimicked the original results. These tools could allow researchers to verify each other’s results more easily without jeopardizing the privacy of participants. This could encourage more collaboration, stimulate ideas for future research, and increase data sharing between research groups.

Background Despite its popularity as an inferential framework, classical null hypothesis significance testing (NHST) has several restrictions. Bayesian analysis can be used to complement NHST, however, this approach has been underutilized largely due to a dearth of accessible software options. JASP is a recently developed open-source statistical package that facilitates both Bayesian and NHST analysis using a graphical interface. This article provides an applied introduction to Bayesian inference with Bayes factors using JASP. Methods We use JASP to compare and contrast Bayesian alternatives for several common classical null hypothesis significance tests: correlations, frequency distributions, t-tests, ANCOVAs, and ANOVAs. These examples are also used to illustrate the strengths and limitations of both NHST and Bayesian hypothesis testing. Results A comparison of NHST and Bayesian inferential frameworks demonstrates that Bayes factors can complement p -values by providing additional information for hypothesis testing. Namely, Bayes factors can quantify relative evidence for both alternative and null hypotheses. Moreover, the magnitude of this evidence can be presented as an easy-to-interpret odds ratio. Conclusions While Bayesian analysis is by no means a new method, this type of statistical inference has been largely inaccessible for most psychiatry researchers. JASP provides a straightforward means of performing reproducible Bayesian hypothesis tests using a graphical “point and click” environment that will be familiar to researchers conversant with other graphical statistical packages, such as SPSS.

Reports on the modulatory role of the neuropeptide oxytocin on social cognition and behavior have steadily increased over the last two decades, stimulating considerable interest in its psychiatric application. Basic and clinical research in humans primarily employs intranasal application protocols. This approach assumes that intranasal administration increases oxytocin levels in the central nervous system via a direct nose-to-brain route, which in turn acts upon centrally-located oxytocin receptors to exert its behavioral effects. However, debates have emerged on whether intranasally administered oxytocin enters the brain via the nose-to-brain route and whether this route leads to functionally relevant increases in central oxytocin levels. In this review we outline recent advances from human and animal research that provide converging evidence for functionally relevant effects of the intranasal oxytocin administration route, suggesting that direct nose-to-brain delivery underlies the behavioral effects of oxytocin on social cognition and behavior. Moreover, advances in previously debated methodological issues, such as pre-registration, reproducibility, statistical power, interpretation of non-significant results, dosage, and sex differences are discussed and integrated with suggestions for the next steps in translating intranasal oxytocin into psychiatric applications.

Autonomic nervous system (ANS) dysfunction is a putative underlying mechanism for increased cardiovascular disease risk in individuals with psychiatric disorders. Previous studies suggest that this risk may be related to psychotropic medication use. In the present study we systematically reviewed and analyzed published studies of heart rate variability (HRV), measuring ANS output, to determine the effect of psychiatric illness and medication use. We searched for studies comparing HRV in physically healthy adults with a diagnosed psychiatric disorder to controls and comparing HRV pre- and post-treatment with a psychotropic medication. In total, 140 case–control (mood, anxiety, psychosis, dependent disorders, k = 151) and 30 treatment (antidepressants, antipsychotics; k = 43) studies were included. We found that HRV was reduced in all patient groups compared to controls (Hedges g = −0.583) with a large effect for psychotic disorders (Hedges g = −0.948). Effect sizes remained highly significant for medication-free patients compared to controls across all disorders. Smaller and significant reductions in HRV were observed for specific antidepressants and antipsychotics. Study quality significantly moderated effect sizes in case–control analyses, underscoring the importance of assessing methodological quality when interpreting HRV findings. Combined findings confirm substantial reductions in HRV across psychiatric disorders, and these effects remained significant even in medication-free individuals. Reductions in HRV may therefore represent a significant mechanism contributing to elevated cardiovascular risk in individuals with psychiatric disorders. The negative impact of specific medications on HRV suggest increased risk for cardiovascular disease in these groups, highlighting a need for treatment providers to consider modifiable cardiovascular risk factors to attenuate this risk.

There is widespread public and academic interest in understanding the uses and effects of digital media. Scholars primarily use self-report measures of the quantity or duration of media use as proxies for more objective measures, but the validity of these self-reports remains unclear. Advancements in data collection techniques have produced a collection of studies indexing both self-reported and log-based measures. To assess the alignment between these measures, we conducted a pre-registered meta-analysis of this research. Based on 106 effect sizes, we found that self-reported media use correlates only moderately with logged measurements, that self-reports were rarely an accurate reflection of logged media use and that measures of problematic media use show an even weaker association with usage logs. These findings raise concerns about the validity of findings relying solely on self-reported measures of media use. In a pre-registered meta-analysis, Parry et al. find that, when self-reported media use is compared with digital logs of media use, subjective judgements are often inaccurate. This suggests caution when self-reports are used to test associations between media use and other outcomes.

There is evidence that heart rate variability (HRV) is reduced in major depressive disorder (MDD), although there is debate about whether this effect is caused by medication or the disorder per se. MDD is associated with a two to fourfold increase in the risk of cardiac mortality, and HRV is a robust predictor of cardiac mortality; determining a direct link between HRV and not only MDD, but common comorbid anxiety disorders, will point to psychiatric indicators for cardiovascular risk reduction. To determine in physically healthy, unmedicated patients whether (1) HRV is reduced in MDD relative to controls, and (2) HRV reductions are driven by MDD alone, comorbid generalized anxiety disorder (GAD, characterized by anxious anticipation), or comorbid panic and posttraumatic stress disorders (PD/PTSD, characterized by anxious arousal). A case-control study in 2006 and 2007 on 73 MDD patients, including 24 without anxiety comorbidity, 24 with GAD, and 14 with PD/PTSD. Seventy-three MDD and 94 healthy age- and sex-matched control participants were recruited from the general community. Participants had no history of drug addiction, alcoholism, brain injury, loss of consciousness, stroke, neurological disorder, or serious medical conditions. There were no significant differences between the four groups in age, gender, BMI, or alcohol use. HRV was calculated from electrocardiography under a standardized short-term resting state condition. HRV was reduced in MDD relative to controls, an effect associated with a medium effect size. MDD participants with comorbid generalized anxiety disorder displayed the greatest reductions in HRV relative to controls, an effect associated with a large effect size. Unmedicated, physically healthy MDD patients with and without comorbid anxiety had reduced HRV. Those with comorbid GAD showed the greatest reductions. Implications for cardiovascular risk reduction strategies in otherwise healthy patients with psychiatric illness are discussed.

Oxytocin is a neuropeptide involved in animal and human reproductive and social behavior. Three oxytocin signaling genes have been frequently implicated in human social behavior: OXT (structural gene for oxytocin), OXTR (oxytocin receptor), and CD38 (oxytocin secretion). Here, we characterized the distribution of OXT , OXTR , and CD38 mRNA across the human brain by creating voxel-by-voxel volumetric expression maps, and identified putative gene pathway interactions by comparing gene expression patterns across 20,737 genes. Expression of the three selected oxytocin pathway genes was enriched in subcortical and olfactory regions and there was high co-expression with several dopaminergic and muscarinic acetylcholine genes, reflecting an anatomical basis for critical gene pathway interactions. fMRI meta-analysis revealed that the oxytocin pathway gene maps correspond with the processing of anticipatory, appetitive, and aversive cognitive states. The oxytocin signaling system may interact with dopaminergic and muscarinic acetylcholine signaling to modulate cognitive state processes involved in complex human behaviors. Oxytocin is a hormone and neurotransmitter involved in reproductive and social behavior, but the role of oxytocin-related genes in the human brain remains unclear. Here, the authors map oxytocin pathway gene expression and show that it overlaps with brain regions involved in reward and emotional states.

Oxytocin plays a vital role in social behavior and homeostatic processes, with animal models indicating that oxytocin receptor (OXTR) expression patterns in the brain influence behavior and physiology. However, the developmental trajectory of OXTR gene expression is unclear. By analyzing gene expression data in human post-mortem brain samples, from the prenatal period to late adulthood, we demonstrate distinct patterns of OXTR gene expression in the developing brain, with increasing OXTR expression along the course of the prenatal period culminating in a peak during early childhood. This early life OXTR expression peak pattern appears slightly earlier in a comparative macaque sample, which is consistent with the relative immaturity of the human brain during early life compared to macaques. We also show that a network of genes with strong spatiotemporal couplings with OXTR is enriched in several psychiatric illness and body composition phenotypes. Taken together, these results demonstrate that oxytocin signaling plays an important role in a diverse set of psychological and somatic processes across the lifespan.

Oxytocin (OT) plays a key regulatory role in human social behaviour. While prior studies have examined the effects of OT on observable social behaviours, studies have seldom examined the effects of OT on psychophysiological markers such as heart rate variability (HRV), which provides an index of individual's motivation for social behaviour. Furthermore, no studies have examined the impact of OT on HRV under resting conditions, which provides an index of maximal capacity for social engagement. To examine the effects of OT on HRV measures in healthy male participants while at rest. OT was hypothesised to increase HRV, compared to placebo, and that the effects would be greatest for a non-linear measure of HRV (the detrended fluctuation scaling exponent). Twenty-one male participants were recruited for this study. Participants were non-smokers, not on any medications and reported no history of psychiatric illness, neurological disorder, or any other serious medical condition (e.g. diabetes, cardiovascular disease). The study employed a randomised, placebo-controlled, within-subject, crossover, experimental design. HRV was calculated from electrocardiography under a standardized, 10-minute, resting state condition. As hypothesised, OT increased HRV and these effects were largest using the detrended fluctuation scaling exponent, a non-linear measure. These changes were observed in the absence of any change in state mood, as measured by the profile of mood states. Importantly, participants were unable to correctly guess which treatment they had been assigned at either of the two assessments. Together with the broader literature on OT and HRV, findings suggest that acute administration of OT may facilitate a fundamental psychophysiological feature of social behaviour, increasing capacity for social engagement. Findings also suggest that HRV changes may provide a novel biomarker of response to OT nasal spray that can be incorporated into research on response to treatment.