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SGSSS STUDENTSHIP – APPLICATIONS OPEN

Developing and assessing a digital health app that implements the Situated Assessment Method to decrease distress and increase eustress

In this project, our team will build and evaluate a health app to help individuals learn about and regulate life stress. In previous work, we developed a new instrument for measuring an individual’s stress, the Situated Assessment Method (SAM2). Unlike other instruments that establish an overall measure of an individual’s stress level, SAM2 provides rich information about associated stress mechanisms. SAM2 is also novel in assessing both negative stress (distress) and positive stress (eustress), and typically explains 70-80% of the variance in distress and eustress, while establishing insight into associated stress mechanisms. Interestingly and significantly, performing the SAM2 assessment procedure across multiple timepoints induces learning about distress and eustress. Individuals increasingly understand how the distress and eustress they experience is related to specific stress mechanisms.

In a series of longitudinal studies, this project will build and assess a health app that implements the SAM2 procedure. Of particular interest is building an effective digital tool that promotes learning about distress and eustress to decrease distress and increase eustress (shifting the affect associated with stress from negative to positive). Besides collecting data that tracks distress and eustress longitudinally, the app will continually assess user learning and app engagement.

The PhD student will become part of a large lab group at the University of Glasgow that focuses on health cognition and behaviour. The two Glasgow supervisors (Lawrence Barsalou, Esther Papies) will provide training in health cognition, behaviour change, and research methods. The industry partner (Aleksandar Matic, Koa Health) will serve as an equal third supervisor, providing training in app development, implementation, and assessment. The PhD project will play a foundational role for developing future collaborative projects that aim to develop increasingly powerful apps for decreasing distress and increasing eustress.

Applicants must meet the following eligibility criteria:

Essential application criteria (required):

  • Completed undergraduate degree in Psychology
  • Basic training in psychological methods and statistics
  • Significant previous programming experience in at least one language (e.g., R, Python)

 Desirable application criteria (optional):

  • Advanced training in psychological methods and statistics
  • Background in health psychology, a health-related occupation, or other health-related experience
  • Experience with app development (such as Android, iOS, and/or web programming)

Please note that all applicants must also meet the ESRC eligibility criteria. ESRC eligibility information can be found here.

For full details and to apply for this studentship, please visit the Scottish Graduate School of Social Science (SGSSS) website here.

New publication: Cognitive Psychology (2nd ed.). McGraw Hill.

Gilhooly, K., Lyddy, F., Pollick, F., & Buratti, S. (2020). Cognitive Psychology (2nd ed.). McGraw Hill.

https://www.mheducation.co.uk/cognitive-psychology-2e-9781526848277-emea-group

Societies have always depended upon humanity’s ability to correctly perceive situations and determine suitable subsequent actions. Since this requires us to accurately deal with information, it is important to understand not only how we (mostly) do this, but also how errors may arise. 

This is the focus of the new, second edition of Cognitive Psychology, one of the most dynamic areas in its field. Accessible yet comprehensive, this text aims to overcome the gap that arises between real life and laboratory studies, by providing an appropriate balance of research versus application.

New paper: Exploring the feasibility of mitigating VR-HMD-induced cybersickness using cathodal transcranial direct current stimulation. In 2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) (pp. 123-129). IEEE.

http://eprints.gla.ac.uk/224089/

Li, G., Varela, F. M., Habib, A., Zhang, Q., McGill, M., Brewster, S., & Pollick, F. (2020, December). Exploring the feasibility of mitigating VR-HMD-induced cybersickness using cathodal transcranial direct current stimulation. In 2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) (pp. 123-129). IEEE.

Many head-mounted virtual reality display (VR-HMD) applications that involve moving visual environments (e.g., virtual rollercoaster, car and airplane driving) will trigger cybersickness (CS). Previous research Arshad et al. (2015) has explored the inhibitory effect of cathodal transcranial direct current stimulation (tDCS) on vestibular cortical excitability, applied to traditional motion sickness (MS), however its applicability to CS, as typically experienced in immersive VR, remains unknown. The presented double-blinded 2x2x3 mixed design experiment (independent variables: stimulation condition [cathodal/anodal]; timing of VR stimulus exposure [before/after tDCS]; sickness scenario [slight symptoms onset/moderate symptoms onset/recovery]) aims to investigate whether the tDCS protocol adapted from Arshad et al. (2015) is effective at delaying the onset of CS symptoms and/or accelerating recovery from them in healthy participants. Quantitative analysis revealed that the cathodal tDCS indeed delayed the onset of slight symptoms if compared to that in anodal condition. However, there are no significant differences in delaying the onset of moderate symptoms nor shortening time to recovery between the two stimulation types. Possible reasons for present findings are discussed and suggestions for future studies are proposed.

New paper: A Review of Electrostimulation-based Cybersickness Mitigations. In 2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) (pp. 151-157). IEEE.

https://eprints.gla.ac.uk/224088/

Li, G., McGill, M., Brewster, S., & Pollick, F. (2020, December). A Review of Electrostimulation-based Cybersickness Mitigations. In 2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) (pp. 151-157). IEEE.

With the development of consumer virtual reality (VR), people have increasing opportunities to experience cybersickness (CS) –- a kind of visuallyinduced motion sickness (MS). In view of the importance of CS mitigation (CSM), this paper reviews the methods of electrostimulation-based CSM (e-CSM), broadly categorised as either “VR-centric” or “Human-centric”. “VR-centric” refers to approaches where knowledge regarding the visual motion being experienced in VR directly affects how the neurostimulation is delivered, whereas “Human-centric” approaches focus on the inhibition or enhancement of human functions per se without knowledge of the experienced visual motion. We DIFFERENT E-found that 1) most e-CSM approaches are based on visual-vestibular sensory conflict theory –- one of the generally-accepted aetiologies of MS, 2) the majority of eCSM approaches are vestibular system-centric, either stimulating it to compensate for the mismatched vestibular sensory responses, or inhibiting it to make an artificial and temporary dysfunction in vestibular sensory organs or cortical areas, 3) Vestibular sensory organbased solutions are able to mitigate CS with immediate effect, while the real-time effect of vestibular cortical areas-based methods remains unclear, due to limited public data, 4) Based on subjective assessment, VRcentric approaches could relieve all three kinds of symptoms (nausea, oculomotor, and disorientation), which appears superior to the human-centric ones that could only alleviate one of the symptom types or just have an overall relief effect. Finally, we propose promising future research directions in the development of e-CSM.

New paper: Up-regulation of Supplementary Motor Area activation with fMRI Neurofeedback during Motor Imagery.

https://www.eneuro.org/content/8/1/ENEURO.0377-18.2020

Al-Wasity, S., Vogt, S., Vuckovic, A., & Pollick, F. E. (2020). Up-regulation of Supplementary Motor Area activation with fMRI Neurofeedback during Motor Imagery. eNeuro.

Functional magnetic resonance imaging (fMRI) neurofeedback (NF) is a promising tool to study the relationship between behavior and brain activity. It enables people to self-regulate their brain signal. Here, we applied fMRI NF to train healthy participants to increase activity in their supplementary motor area (SMA) during a motor imagery (MI) task of complex body movements while they received a continuous visual feedback signal. This signal represented the activity of participants’ localized SMA regions in the NF group and a prerecorded signal in the control group (sham feedback). In the NF group only, results showed a gradual increase in SMA-related activity across runs. This upregulation was largely restricted to the SMA, while other regions of the motor network showed no, or only marginal NF effects. In addition, we found behavioral changes, i.e., shorter reaction times in a Go/No-go task after the NF training only. These results suggest that NF can assist participants to develop greater control over a specifically targeted motor region involved in motor skill learning. The results contribute to a better understanding of the underlying mechanisms of SMA NF based on MI with a direct implication for rehabilitation of motor dysfunctions.

New paper: Understanding and supporting law enforcement professionals working with distressing material: Findings from a qualitative study.

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0242808

Denk-Florea, C. B., Gancz, B., Gomoiu, A., Ingram, M., Moreton, R., & Pollick, F. (2020). Understanding and supporting law enforcement professionals working with distressing material: Findings from a qualitative study. Plos one15(11), e0242808.

This study aimed to extend previous research on the experiences and factors that impact law enforcement personnel when working with distressing materials such as child sexual abuse content. A sample of 22 law enforcement personnel working within one law enforcement organisation in England, United Kingdom participated in anonymous semi-structured interviews. Results were explored thematically and organised in the following headings: “Responses to the material”, “Impact of working with distressing evidence”, “Personal coping strategies” and “Risks and mitigating factors”. Law enforcement professionals experienced heightened affective responses to personally relevant material, depictions of violence, victims’ displays of emotions, norm violations and to various mediums. These responses dampened over time due to desensitisation. The stress experienced from exposure to the material sometimes led to psychological symptoms associated with Secondary Traumatic Stress. Job satisfaction, self-care activities, the coping strategies used when viewing evidence, detachment from work outside working hours, social support and reducing exposure to the material were found to mediate law enforcement professionals’ resilience. Exposure to distressing material and the risks associated with this exposure were also influenced by specific organisational procedures implemented as a function of the funding available and workload. Recommendations for individual and organisational practices to foster resilience emerged from this research. These recommendations are relevant to all organisations where employees are required to view distressing content.

UKRI Centre for Doctoral Training in Socially Intelligent Artificial Agents Studentships

The Centre for Doctoral Training offers PhD studentships for UK residents (fees and stipend), and a limited number of international studentships for exceptional candidates. To be eligible for an award, candidates must fulfil UKRI’s residency criteria and hold a 1st or 2:1 undergraduate degree in a subject relevant to the CDT including, but not limited to, computing science, psychology, linguistics, mathematics, sociology, engineering, physics, etc.

To apply for the studentship, please visit the SOCIAL AI website and read the full application instructions. Applicants are required to choose three prospective doctoral projects from a list available on the SOCIAL AI website and detail their suitability for these research projects in their cover letter. Applications are submitted via the University of Glasgow central admissions portal. The deadline for the September 2021 intake is 28th February 2021.

Please send any enquiries to social-cdt@glasgow.ac.uk or visit www.socialcdt.org.

New paper: LexOPS: An R package and user interface for the controlled generation of word stimuli

https://link.springer.com/epdf/10.3758/s13428-020-01389-1?sharing_token=q5qq3sdnK5Cv3KiPQ7jJsJAH0g46feNdnc402WrhzypVLBRCe-RrGW4M8jmeSOlDdGIx8GNei1Rfuxn4LA3t80j01MvBfBvcY19hj5K1lnvki5V4u3a3Nc5roP71wk_KLod3wclVwC7sdyHUGuU_phXsoPsH-DRd89IH5u18y64%3D

LexOPS is an R package and user interface designed to facilitate the generation of word stimuli for use in research. Notably, the tool permits the generation of suitably controlled word lists for any user-specified factorial design and can be adapted for use with any language. It features an intuitive graphical user interface, including the visualization of both the distributions within and relationships among variables of interest. An inbuilt database of English words is also provided, including a range of lexical variables commonly used in psycholinguistic research. This article introduces LexOPS, outlining the features of the package and detailing the sources of the inbuilt dataset. We also report a validation analysis, showing that, in comparison to stimuli of existing studies, stimuli optimized with LexOPS generally demonstrate greater constraint and consistency in variable manipulation and control. Current instructions for installing and using LexOPS are available at https://JackEdTaylor.github.io/LexOPSdocs/.

New paper: Tweet valence, volume of abuse, and observers’ dark tetrad personality factors influence victim-blaming and the perceived severity of twitter cyberabuse

Hand, C.J., Scott, G.G., Brodie, Z.P., Ye, X., & Sereno, S.C. (2021). Tweet valence, volume of abuse, and observers’ dark tetrad personality factors influence victim-blaming and the perceived severity of
twitter cyberabuse. Computers in Human Behavior Reports, 3. 

https://www.sciencedirect.com/science/article/pii/S245195882100004X

Previous research into Twitter cyberabuse has yielded several findings: victim-blaming (VB) was influenced by victims’ initial tweet-valence; perceived severity (PS) was influenced independently by tweet valence and abuse volume; VB and PS were predicted by observer narcissism and psychopathy. However, this previous research was limited by its narrow focus on celebrity victims, and lack of consideration of observer sadism. The current study investigated 125 observers’ VB and PS perceptions of lay-user cyberabuse, and influence of observers’ Dark Tetrad scores (psychopathy, narcissism, Machiavellianism, sadism). We manipulated initial-tweet valence (negative, neutral, positive) and received abuse volume (low, high). Our results indicated that VB was highest following negative initial tweets; VB was higher following high-volume abuse. PS did not differ across initial-tweet valences; PS was greater following a high abuse volume. Regression analyses revealed that observer sadism predicted VB across initial-tweet valences; psychopathy predicted PS when initial tweets were ‘emotive’ (negative, positive), whereas Machiavellianism predicted PS when they were neutral. Our results show that perceptions of lay-user abuse are influenced interactively by victim-generated content and received abuse volume. Our current results contrast with perceptions of celebrity-abuse, which is mostly determined by victim-generated content. Findings are contextualised within the Warranting Theory of impression formation.

New paper: Investigating the foreign language effect as a mitigating influence on the ‘optimality bias’ in moral judgements

Bodig, E., Toivo, W., & Scheepers, C. (2019). Investigating the foreign language effect as a mitigating influence on the ‘optimality bias’ in moral judgements. Journal of Cultural Cognitive Science, DOI: 10.1007/s41809-019-00050-4 .


Abstract Bilinguals often display reduced emotional resonance their second language (L2) and therefore tend to be less prone to decision-making biases in their L2 (e.g., Costa, Foucart, Arnon, Aparici, & Apesteguia, 2014; Costa, Foucart, Hayakawa, et al., 2014) – a phenomenon coined Foreign Language Effect (FLE). The present pre-registered experiments investigated whether FLE can mitigate a special case of cognitive bias, called optimality bias, which occurs when observers erroneously blame actors for making “suboptimal” choices, even when there was not sufficient information available for the actor to identify the best choice (De Freitas & Johnson, 2018). In Experiment 1, L1 English speakers (N=63) were compared to L2 English speakers from various L1 backgrounds (N=56). In Experiment 2, we compared Finnish bilinguals completing the study in either Finnish (L1, N=103) or English (L2, N=108). Participants read a vignette describing the same tragic outcome resulting from either an optimal or suboptimal choice made by a hypothetical actor with insufficient knowledge. Their blame attributions were measured using a 4-item scale. A strong optimality bias was observed; participants assigned significantly more blame in the suboptimal choice conditions, despite being told that the actor did not know which choice was best. However, no clear interaction with language was found. In Experiment 1, bilinguals gave reliably higher blame scores than natives. In Experiment 2, no clear influence of target language was found, but the results suggested that the FLE is actually more detrimental than helpful in the domain of blame attribution. Future research should investigate the benefits of emotional involvement in blame attribution, including factors such as empathy and perspective-taking.

Keywords Bilingualism, Foreign Language Effect, attribution, decision-making, blame