Introducing the Situated Assessment Method, SAM^2, a psychometric approach that establishes individual differences for constructs in situations where they occur. The psychometric instrument developed here, the SAM^2 Habitual Behavior Instrument (SAM^2 HBI), assessed the regularity of good and bad habits.

The published article can be found here:  https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0286954

The SAM^2 HBI established individual traits for the regularity of performing good and bad habits, with large situation effects and large individual X situation interactions.  Good test reliability was achieved from broad coverage of low-coherence situations as test items.

The SAM^2 HBI also demonstrated high construct and content validity, with automaticity, consistency, immediate reward, and long-term reward predicting group habit regularity well (65% explained variance).  Prediction was even stronger for individuals (median 75% explained variance), with large multifaceted individual differences.

The SAM^2 HBI also captured well-known personality effects of self-control and neuroticism on performing good versus bad habits.  Cognitive-affective processes from the situated action cycle (situated and embodied cognition) explained nearly all the variance in these interactions.

A composite measure of habitualness established habitualness for behaviors at the group and individual levels. Their distribution questions the construct of ‘habit-hood.’ Most behaviors showed moderate levels of habitualness (e.g., study breaks).  Only a few showed high levels.

A composite measure of reward was strongly related to habitualness at the group and individual levels, implicating reward in habitual behavior. Self-control and neuroticism modulated the reward-habitualness relation, increasing with self-control and decreasing with neuroticism.

This work is relevant to habits researchers, especially those interested in the relation between reward and habitual behavior.  It is also relevant to researchers interested in situation effects and person X situation interactions, to researchers interested in the relation between personality and habitual behavior, to researchers interested in rich situational description, and to researchers interested in situated, embodied, grounded, and 4E cognition.

Three articles from Courtney Taylor Browne’s Lūka’s PhD dissertation are available on PsyArXiv. One uses the SAM2 framework to establish individual differences in trichotillomania. The other two use the SAM2 framework to establish individual differences in social connectedness, social support, and lonelines (one related to COVID-19). Here are the citations with links to the preprints:

Taylor Browne Lūka, C., Hendry, K., Dutriaux, L., Stevenson, J. L., & Barsalou, L. (2023). Developing and evaluating a situated assessment instrument for trichotillomania: The SAM² TAI. PsyArXiv preprint.

Taylor Browne Lūka, C., Iswaraan, B., & Barsalou, L.W. (2023). Developing the Situated Assessment Method (SAM²) to assess social connectedness and social support. PsyArXiv preprint.

Taylor Browne Lūka, C., & Barsalou, L. (2023). Using the Situated Assessment Method (SAM²) to measure social connectedness, social support, and loneliness before and during COVID-19. PsyArXiv preprint.

Three articles from Johanna Werner’s PhD dissertation are available on PsyArXiv. All use the SAM2 framework to establish motives for eating and drinking. Here are the citations with links to the preprints:

Werner, J., Papies, E.K., Best, M., Scheepers, C., & Barsalou, L.W. (2022). Habit, health, and socialising: New insights into diverse motives for alcoholic and non-alcoholic beverage consumption. PsyArXiv preprint.

Werner, J., Papies, E.K., Gelibter, E., & Barsalou, L.W. (2022). Why do you eat? Establishing individual consumption motives and their stability across eating situations. PsyArXiv preprint.

Werner, J., Kloidt, J., & Barsalou, L.W. (2022). Assessing individual motivation for consuming diverse food groups over a two-week period. PsyArXiv preprint.

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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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.

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.

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.

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.

As part of Wendy Hasenkamp’s excellent Mind and Life Podcast series, Lawrence Barsalou contributed Habits of mind in March 2021.

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.