Behavioral, cognitive and emotional determinants of getting vaccinated for COVID-19 and the mediating role of institutional trust among young adults in Cyprus.

BACKGROUND: Vaccination uptake is a complex behavior, influenced by numerous factors. Behavioral science theories are commonly used to explain the psychosocial determinants of an individual's health behavior. This study examined the behavioural, cognitive, and emotional determinants of COVID-19 vaccination intention based on well-established theoretical models: Acceptance and Commitment Therapy (ACT), Capability, Opportunity, Motivation, and Behaviour (COM-B) and the Health Belief Model (HBM). Additionally, it examined the mediating role of institutional trust in the relationship between determinants of these models and vaccination intentions. METHODS: A cross-sectional study was conducted from January to May 2022, where university students in Cyprus completed an online survey. RESULTS: A total of 484 university students completed the online survey, with 23.8% reporting being vaccinated with fewer than three vaccination doses and/or no intention to vaccinate further. Hierarchical logistic regression analysis showed that higher scores in institutional trust, perceived severity, motivation, physical and psychological capability were significantly associated with higher odds of intending to vaccinate. Higher psychological flexibility and not being infected with COVID-19 were also associated with higher odds of vaccination intention, but not in the final model when all determinants were included. Additionally, significant indirect effects of psychological and physical capability, motivation and perceived severity on vaccination intention were found to be mediated by institutional trust. CONCLUSIONS: When tackling COVID-19 vaccination hesitancy, behavioural, cognitive, and emotional aspects should be considered. Stakeholders and policymakers are advised to implement targeted vaccination programs in young people while at the same time building trust and improving their capabilities and motivation towards getting vaccinated.

Individual differences in learning from probabilistic reward and punishment predicts smoking status.

INTRODUCTION: The ability to update reward and punishment contingencies is a fundamental aspect of effective decision-making, requiring the ability to successfully adapt to the changing demands of one's environment. In the case of nicotine addiction, research has predominantly focused on reward- and punishment-based learning processes among current smokers relative to non-smokers, whereas less is known about these processes in former smokers. METHODS: In a total sample of 105 students, we used the Probabilistic Selection Task to examine differences in reinforcement learning among 41 current smokers, 29 ex-smokers, and 35 non-smokers. The PST was comprised of a training and test phase that allowed for the comparison of learning from positive versus negative feedback. RESULTS: The test phase of the Probabilistic Selection Task significantly predicted smoking status. Current and non-smokers were classified with moderate accuracy, whereas ex-smokers were typically misclassified as smokers. Lower rates of learning from rewards were associated with an increased likelihood of being a smoker or an ex-smoker compared with being a non-smoker. Higher rates of learning from punishment were associated with an increased likelihood of being a smoker relative to non-smoker. However, learning from punishment did not predict ex-smoker status. CONCLUSIONS: Current smokers and ex-smokers were less likely to learn from rewards, supporting the hypothesis that deficient reward processing is a feature of chronic addiction. In addition, current smokers were more sensitive to punishment than ex-smokers, contradicting some recent findings.

A Combination of Impulsivity Subdomains Predict Alcohol Intoxication Frequency.

BACKGROUND: Impulsivity, broadly characterized as the tendency to act prematurely without foresight, is linked to alcohol misuse in college students. However, impulsivity is a multidimensional construct and different subdomains likely underlie different patterns of alcohol misuse. Here, we quantified the association between alcohol intoxication frequency and alcohol consumption frequency and choice, action, cognitive, and trait domains of impulsivity. METHODS: University student drinkers (n = 106) completed a battery of demographic and alcohol-related items, as well as self-report and task-based measures indexing different facets of impulsivity. Two orthogonal latent factors, intoxication frequency and alcohol consumption frequency, were generated. Their validity was demonstrated with respect to adverse consequences of alcohol use. Machine learning with penalized regression and feature selection was then utilized to predict intoxication and alcohol consumption frequency using all impulsivity subdomains. Out-of-sample validation was used to quantify model performance. RESULTS: Impulsivity measures alone were significant predictors of intoxication frequency, but not consumption frequency. Propensity for increased intoxication frequency was characterized by increased trait impulsivity, including the Disinhibition subscale of the Sensation Seeking Scale, Attentional and Non-planning subscales of the Barratt Impulsiveness Scale, increased task-based cognitive impulsivity (response time variability), and increased choice impulsivity (steeper delay discounting on a delay discounting questionnaire). A model combining impulsivity domains with other risk factors (gender; nicotine, cannabis, and other drug use; executive functioning; and learning processes) was also significant but did not outperform the model comprising of impulsivity alone. CONCLUSIONS: Intoxication frequency, but not consumption frequency, was characterized by a number of impulsivity subdomains.

Neural circuitry underlying sustained attention in healthy adolescents and in ADHD symptomatology.

Moment-to-moment reaction time variability on tasks of attention, often quantified by intra-individual response variability (IRV), provides a good indication of the degree to which an individual is vulnerable to lapses in sustained attention. Increased IRV is a hallmark of several disorders of attention, including Attention-Deficit/Hyperactivity Disorder (ADHD). Here, task-based fMRI was used to provide the first examination of how average brain activation and functional connectivity patterns in adolescents are related to individual differences in sustained attention as measured by IRV. We computed IRV in a large sample of adolescents (n = 758) across 'Go' trials of a Stop Signal Task (SST). A data-driven, multi-step analysis approach was used to identify networks associated with low IRV (i.e., good sustained attention) and high IRV (i.e., poorer sustained attention). Low IRV was associated with greater functional segregation (i.e., stronger negative connectivity) amongst an array of brain networks, particularly between cerebellum and motor, cerebellum and prefrontal, and occipital and motor networks. In contrast, high IRV was associated with stronger positive connectivity within the motor network bilaterally and between motor and parietal, prefrontal, and limbic networks. Consistent with these observations, a separate sample of adolescents exhibiting elevated ADHD symptoms had increased fMRI activation and stronger positive connectivity within the same motor network denoting poorer sustained attention, compared to a matched asymptomatic control sample. With respect to the functional connectivity signature of low IRV, there were no statistically significant differences in networks denoting good sustained attention between the ADHD symptom group and asymptomatic control group. We propose that sustained attentional processes are facilitated by an array of neural networks working together, and provide an empirical account of how the functional role of the cerebellum extends to cognition in adolescents. This work highlights the involvement of motor cortex in the integrity of sustained attention, and suggests that atypically strong connectivity within motor networks characterizes poor attentional capacity in both typically developing and ADHD symptomatic adolescents.

The functional-cognitive framework as a tool for accelerating progress in cognitive neuroscience: On the benefits of bridging rather than reducing levels of analyses.

The subject matter of neuroscience research is complex, and synthesising the wealth of data from this research to better understand mental processes is challenging. A useful strategy, therefore, may be to distinguish explicitly between the causal effects of the environment on behaviour (i.e. functional analyses) and the mental processes that mediate these effects (i.e. cognitive analyses). In this article, we describe how the functional-cognitive (F-C) framework can accelerate cognitive neuroscience and also advance a functional treatment of brain activity. We first highlight that cognitive neuroscience can particularly benefit from the F-C approach by providing an alternative to the problematic practice of reducing cognitive constructs to behavioural and/or neural proxies. Next, we outline how functional (behaviour-environment) relations can serve as a bridge between cognitive and neural processes by restoring mental constructs to their original role as heuristic tools. Finally, we give some examples of how both cognitive neuroscience and traditional functional approaches can mutually benefit from the F-C framework.

A meta-analysis of criterion effects for the Implicit Relational Assessment Procedure (IRAP) in the clinical domain.

BACKGROUND AND OBJECTIVES: The Implicit Relational Assessment Procedure (IRAP) is a technique that is attracting a substantial body of research literature, particularly within the clinical domain. METHOD: In response, the present paper outlines a meta-analysis of clinically-focused IRAP effects (N = 494) to provide the first estimate of how well such effects validate against their respective criterion variables in general. RESULTS: The meta-analysis incorporated clinically-focused IRAP effects from 15 studies yielding a large effect size, r¯ = .45, with a desirably narrow 95% credibility interval (.23, .67). The funnel plot and subsequent sensitivity analyses indicated that this meta-effect was not subject to publication bias. LIMITATIONS: The present meta-effect is an estimate based upon an IRAP literature that is still evolving rapidly in the clinical domain, and so as per its accompanying credibility interval, all conclusions that follow are necessarily provisional even if bounded. Apart from the fact that the current meta-effect might be subject to inadvertent under- and/or over-estimations of the current literature, the present meta-effect might strengthen with further refinements of the IRAP. CONCLUSIONS: The current meta-effect provides the means to calculate what sample size would be required to achieve a statistical power of .80 when testing the criterion validity of clinically-focused IRAP effects using a given parametric statistic. For example, first-order Pearson correlations would hypothetically require an N of 29-37 for such purposes depending upon how conservatively over-estimation of the present meta-effect is controlled for. Overall, the IRAP compares favourably with alternative implicit measures in clinical psychology.