MRC funding for the SOCITS methodological framework

MRC funding to develop the SOCITS methodological framework has been received by a University of Glasgow team led by PI Mark McCann (School of Health and Wellbeing), together with co-PIs Emily Long, Corinna Eisenbroch, Claire Goodfellow (School of Health and Wellbeing), Lawrence Barsalou (School of Psychology and Neuroscience), and Julie Cameron (Mental Health Foundation). Working with secondary schools in Scotland, our team will develop a SOCial sITuational Systems approach for measuring and modeling influences on adolescent mental health. Specifically, we will develop a novel multimethod framework that assesses adolescent mental health in a situated manner embedded within a complex systems perspective. Focusing on the specific mental health issues of stress and social isolation, we will integrate qualitative interviewing, psychometric measurement, network modeling, and agent-based modeling to develop a general framework that can potentially be applied to diverse mental health issues in adolescence.

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SAM2 Habits preprint online

A preprint of the following article is now available on PsyArXiv via the link below:

Dutriaux, L., Clark, N., Papies, E.K., Scheepers, C., & Barsalou, L.W. (2021). The Situated Assessment Method (SAM2): Establishing individual differences in habitual behavior.

Abstract:  From the perspectives of grounded, situated, and embodied cognition, we have developed a new approach for assessing individual differences.  Because this approach is grounded in two dimensions of situatedness—situational experience and the Situated Action Cycle—we refer to it as the Situated Assessment Method (SAM2).  Rather than abstracting over situations during assessment of a construct (as in traditional assessment instruments), SAM2 assesses a construct in situations where it occurs, simultaneously measuring factors from the Situated Action Cycle known to influence it.  To demonstrate this framework, we developed the SAM2 Habitual Behavior Instrument (SAM2 HBI).  Across three studies with a total of 442 participants, the SAM2 HBI produced a robust and replicable pattern of results at both the group and individual levels.  Three trait-level measures of behavior regularity across 80 behaviors, 40 positive behaviors, and 40 negative behaviors exhibited large reliable individual differences.  Several sources of evidence demonstrated the construct validity of these measures.  At both the group and individual levels, the SAM2 measure of behavior regularity was associated with factors from the Situated Action Cycle known to influence habitual behavior in the literature (consistency, automaticity, immediate reward, long-term reward).  Regressions explained approximately 65% of the variance at the group level and a median of approximately 75% at the individual level.  The SAM2 measure of behavior regularity also exhibited well-established interactions with personality measures for self-control and neuroticism.  Cognitive-affective processes from the Situated Action Cycle explained nearly all the variance in these interactions.  Finally, a composite measure of habitualness established habitual behaviors at both the group and individual levels.  Additionally, a composite measure of reward was strongly related to the composite measure of habitualness, increasing with self-control and decreasing with neuroticism.

Effects of Food Exposure on Food Preference (open-access article online)

The online publication of the following article is now available via the link below:

Dutriaux, L., Papies, E.K., Fallon, J., Garcia-Marques, L., & Barsalou, L.W. (2021). Incidental exposure to hedonic and healthy food features affects food preferences one day later. Cognitive Research: Principles and Implications. Open-access online publication.

Abstract:  Memories acquired incidentally from exposure to food information in the environment may often become active to later affect food preferences.  Because conscious use of these memories is not requested or required, these incidental learning effects constitute a form of indirect memory.  In an experiment using a novel food preference paradigm (n = 617), we found that brief incidental exposure to hedonic versus healthy food features indirectly affected food preferences a day later, explaining approximately 10% of the variance in preferences for tasty versus healthy foods.  It follows that brief incidental exposure to food information can affect food preferences indirectly for at least a day.  When hedonic and health exposure were each compared to a no-exposure baseline, a general effect of hedonic exposure emerged across individuals, whereas health exposure only affected food preferences for high-BMI individuals.  This pattern suggests that focusing attention on hedonic food features engages common affective processes across the general population, whereas focusing attention on healthy food features engages eating restraint goals associated with high-BMI.  Additionally, incidental exposure to food features primarily changed preferences for infrequently consumed foods, having less impact on habitually consumed foods.  These findings offer insight into how hedonic information in the obesogenic food environment contributes to unhealthy eating behavior that leads to overweight and obesity.  These findings further motivate the development of interventions that counteract the effects of exposure to hedonic food information and that broaden the effects of exposure to healthy food information.

SITUATE receives an Early Concept Development Award from the Wellcome Trust

Through the University of Glasgow’s Translational Research Initiative, Lawrence Barsalou and Christoph Scheepers have received an Early Concept Development Award from the Wellcome Trust for a project entitled, “Implementing and evaluating a prototype of the SITUATE digital health platform.”  Funds from this grant will support building a SITUATE prototype and assessing it in focus groups of end users and mental health professionals.  Should this proof-of-concept work be successful, more ambitious attempts to develop and distribute SITUATE will follow.

Abstract.  With support from University of Glasgow’s Research and Innovation Services, we developed a commercial project within the framework of the ARC Accelerator Program.  In this project, we designed a digital health tool, SITUATE, that offers a novel precision medicine resource for helping individuals work with a wide variety of health and social behaviours.

Although the rates of behavioural problems have skyrocketed since the pandemic, they were already high beforehand and will undoubtedly continue to remain high indefinitely.  Should SITUATE prove to be an effective tool, it would offer a scalable source of intervention for helping diverse groups of clients.  Because SITUATE requires minimal professional supervision, it could also help take pressure off health care professionals with overwhelming caseloads.  It also has significant potential for use in task-sharing public health networks, where minimally trained individuals distribute a health tool effectively to other community members (e.g., in the Red Cross / Red Crescent).

To date, we have developed the assessment component of SITUATE extensively in the domains of stress, eating, drinking, trichotillomania (compulsive hair pulling), loneliness, and emotion.  We understand SITUATE’s assessment properties well and have much of the relevant software in place.

Recently, we have begun to see how SITUATE’s assessment component could be extended into additional domains, including sustainability, suicidal tendences, hypertension, racism, sectarianism, and trust.  Most recently, we have begun exploring SITUATE’s potential as a training and intervention tool.  Besides collecting preliminary data related to training, we have developed a detailed design of a SITUATE prototype that integrates assessment, instruction, habit training, performance monitoring, and feedback in a single platform (through client devices linked with a cloud host).  We aim to build and begin evaluating this prototype in the coming year.

Welcome two new PhD students: Chiara Wilke and Juliane Kloidt

We are most fortunate to have recruited two talented students into our research group.  Both received their undergraduate degrees here in Psychology and Neuroscience at the University of Glasgow.

Chiara Wilke received her degree in 2020 and then performed post graduate work last year in Germany.  She has returned to perform a PhD on a collaborative project funded by the Scottish Graduate School of Social Science (SGSSS) entitled, “Developing and assessing a digital health app that implements the Situated Assessment Method to decrease distress and increase eustress.”  Her supervisors are Lawrence Barsalou from the University of Glasgow (primary), Aleksandar Matic from Koa Health (secondary), and Esther Papies from University of Glasgow (secondary).

Project abstract.  This project 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, we 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 will provide training in health cognition, behaviour change, and research methods. The industry partner 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.  

Juliane Kloidt received her degree in 2021 and then joined the Center for Doctoral Training in Socially Intelligent Artificial Agents here on a project, entitled, “Improving engagement with mobile health apps by understanding (mis)alignment between design elements and personal characteristics.”  Her supervisors are Lawrence Barsalou from the University of Glasgow (primary) and Aleksandar Matic from Koa Health (secondary).

Project abstract.  This project will deepen understanding of how to personalise mobile health apps to user personal characteristics aiming to improve the engagement and ultimately intervention effectiveness. The main objectives will be the following:  (1) Identify specific links between personal characteristics and service design elements that predict engagement and/or drop-outs, (2) Explore if the engagement with mobile health apps can be improved by avoiding misaligned (reinforcing aligned) design elements with personal characteristics that pre-dominantly drive drop-outs (engagement), (3) Deliver a set of takeaways for designing socially intelligent interfaces aware of personal characteristics

Extensive literature research will be first conducted to characterise design elements, and to identify the links to personal characteristics that can influence engagement. This will result in a set of hypotheses on the relationship between different personal characteristics and the engagement mechanisms. Sequentially, one or more studies will be conducted to capture personal traits of the users who have already used a selected set of relevant mobile health apps. By applying standard statistical methods as well as machine learning (to unpack more complex interplay between personal characteristics and design elements), this data will be used to identify engagement/drop-out predictors. The learnings will be used to design and test personalisation in a real-world scenario.

Barsalou Abstract Concepts talk online

As part of a Workshop on Fresh / New Perspectives on Abstract Concepts presented by Sapienza University of Rome and the TRAINCREASE Project in March 2021, Lawrence Barsalou presented a talk, “Moving beyond the distinction between concrete and abstract concepts.” A video recording of the talk can be found on YouTube here.

Applications open for SGSSS PhD Position

Applications have now opened for the following PhD position:

Lawrence Barsalou and Esther Papies (University of Glasgow) and Aleksandar Matic (Koa Health) have been awarded a PhD position from the Scottish Graduate School of Social Science beginning in the fall of 2021.  This studentship is associated with SGSSS program that fosters collaborative projects between academia and industry. 

In this project, our team will build and evaluate a health app to help individuals learn about and regulate life stress (utilizing the Situated Assessment Method developed at Glasgow, together with other tools developed at Koa Health).  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). 

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 (Barsalou and Papies) will provide training in health cognition, behaviour change, and research methods.  The industry partner (Matic) 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.  Students without a masters degree are eligible and will be funded for an additional year of masters training.

If you are interested in applying for this position, please do so by clicking on the image below:

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Lawrence Barsalou receives a position in the ARC Accelerator Programme to develop and commercialise the Situated Assessment Method

January 2021

The ARC Accelerator Programme is a first-of-its-kind opportunity designed specifically to help social science researchers to develop ideas based on their research into businesses or ventures that help people, society and the economy.  In the 2021 programme, 15 UK-wide training positions were available across participating universities.

The ARC Accelerator is a six-month programme in which trainees benefit from:  (1) support for exploring and developing their idea, (2) a three-week entrepreneurial bootcamp led by industry experts, (3) specialised sector-specific training with access to experts, investors, and key networks, (4) mentorship to validate ideas, develop business models, and support pitches for funding and investment.

While participating in the ARC programmer, I aim to develop, implement, and distribute the Situated Assessment Method (SAM2) for measuring, predicting, and changing health behaviours, including stress, social connectiveness, eating habits, trichotillomania, etc.  This novel and powerful approach has significant potential for being implemented in digital health apps for use by clinicians, health practitioners, and private individuals.

New PhD position available: Improving engagement with mobile health apps by understanding (mis)alignment between design elements and personal characteristics

January 2021

Aleksandar Matic (Koa Health) and Lawrence Barsalou (University of Glasgow) are supervising this PhD project in the University of Glasgow Center for Doctoral Training in Socially Intelligent Artificial Agents.  Applications are open for the position that begins in Fall 2021, beginning with a year of funded masters work, followed by three years of funded PhD work.

Project summary:  A growing consensus has concluded that improving engagement with health apps requires personalisation at an individual level.  In this project, we will pursue two novel approaches for improving engagement with health apps.

First, we will conduct a retrospective exploration of previous app use as documented in the literature. Specifically, we will assess( a) personal characteristics of individuals who have previously used mobile health apps, (b) design elements (including intervention mechanisms) of these apps, and (c) outcomes related to app engagement (e.g., drop-out rates, frequency of use). Of focal interest will be how personal characteristics and app design interact to produce different levels of app engagement.  We aim to publish a major review of the literature based on this work.

Second, in a well-established stress app that we continue to develop, we will allow users to configure its design features in various ways.  We will also collect data about users’ personal characteristics.  From these data, we hope to develop design principles for tailoring future apps and intervention mechanisms to specific individuals.  A series of studies will be performed in this line of work, together with related publications.

This project is likely to focus on stress as the primary-use case.  In a related project, we are developing and evaluating stress apps that measure and predict stress in specific situations, linking psychological assessment to physiological data harvested implicitly from wearables.  In a third project, we are implementing behaviour change interventions in digital health apps to reduce distress and increase eustress.  Work from all three projects will be integrated to develop maximally effective stress apps, tailored to individuals, that effectively measure, predict, and alter stress experience.

Application sites: https://socialcdt.org/https://socialcdt.org/how-to-apply/