Intuitive Decision-Making by People with Diabetes

People with diabetes often find it challenging to maintain their blood sugar levels, in part because diabetes is a complicated disease. When the kidneys don't produce enough insulin fast enough to adjust for changes in digestion or activity, blood sugar can fluctuate rapidly, even over the course of a single day. To manage this, people with diabetes often need to make changes in multiple areas: adopting a low-carbohydrate diet, managing the timing and amount of exercise they get, keeping track of the times when their blood sugar rises and falls, potentially giving themselves a dose of insulin around mealtimes, managing stress, and other preventive measures as well. 

But despite all of this complexity, the people who manage their diabetes most successfully are often the least obsessive about the fine details. When my Dad was first diagnosed with diabetes, he checked his blood sugar often (using finger sticks; continuous glucose monitoring [CGM] devices weren’t yet a thing). But over time, he did that less and less. Instead, he managed what he ate (for instance, he always refused deserts), he would get up and walk after a meal, and he would snack on something healthy like fruit. Until other health problems intervened, his diabetes stayed pretty well controlled. In a 2023 study of adolescents using CGM devices, my colleagues and I found something similar: People who interact less with their CGM tend to have better blood sugar numbers throughout the day. We interpreted this finding as a sign of situational awareness, a person’s ability to recognize subtle bodily signs that might tell them their blood sugar is going out of range and to adjust their behavior to compensate. From a Two Minds Theory perspective, we suggested that these perceptions and reactions probably take place at the level of the Intuitive Mind, outside of the person’s conscious awareness. Furthermore, multiple studies show that Narrative-Mind-focused educational interventions like CDC’s Diabetes Self-Management Education Program have limited effects on long-term self-management or glucose control in diabetes.

Two Minds Theory isn’t the only framework that might explain intuitive self-management of behavior. Let’s take a look at what else is out there. Starting from a clinical perspective, Skinner et al. (2003) identified “four theories and a philosophy” underpinning diabetes self-management. The four theories are (a) Leventhal’s model (described in a recent blog post); (b) a self-regulation theory that predicts self-management from illness representations and efficacy beliefs (as in the Theory of Planned Behavior or the older Health Belief Model, two approaches that rely heavily on Narrative-Mind variables that probably predict beliefs rather than behavior); (c) self-determination theory, a newer model that predicts self-management based on autonomous motivation for behavior (an Intuitive-Mind factor), and (d) social learning theory (Bandura’s model, which emphasizes self-efficacy). Of these theories, (b) and (d) are relatively cognitive and propose deliberate rather than automatic explanations for self-management behaviors; (c) is consistent with an automatic self-management view, and relies on social factors – in particular the quality of the patient-provider relationship – that are connected to the Intuitive Mind. Notably, self-determination theory has also been proposed as an explanation for why motivational interviewing helps people to change their behavior (the relational hypothesis of MI). Of these four major theories, Leventhal’s model is the most similar to TMT, focusing on the patient’s internal experiences rather than on the social dynamics of treatment. Another review, by Quinton and Brunton (2017) identified volition and motivation as non-cognitive processes that can affect behavior, operating in parallel with beliefs as in Leventhal’s dual-process model, Kahneman’s system 1/system 2 model, or TMT. Quinton and Brunton note that various understandings exist to explain how the two processes interact and what happens when they offer conflicting guidance. The question of “which system works when” is one that our newer Two Minds Theory was specifically proposed to resolve.

With regard to Leventhal’s model, a recent review article by Orbell and Phillips (2019) using this framework is relevant. The authors discuss automatic self-management processes at length, but their primary emphasis is on automatic detection and interpretation of symptoms, which then feed into the more cognitive pathway; although direct influences of automatic processes on behavior are considered, they are given relatively little attention and are framed in cognitive language as “automatic coping processes” that are related to cognitive schemas. A paper by Scollan-Koliopoulos et al. (2011) provides a good example of this problem: Although the study identifies an interesting phenomenon of intergenerational transmission of illness representations, this study ostensibly based on Leventhal’s dual-process model only discusses the cognitive pathway to health behavior, as operationalized using the Illness Perception Questionnaire. In a 2022 conceptual paper, Hagger and Orbell proposed an extended version of Leventhal’s common-sense model, and suggested that both the cognitive and the emotional pathways predicted self-management behaviors, with different factors influencing approach versus avoidant coping strategies. A 2023 meta-analysis by the same authors is interesting in that it identified correlates for each type of illness perception, but the emotion-focused/Intuitive Mind pathway was not included. Hagger and Koch (2017) did test the emotion-representation pathway of Leventhal’s model; interestingly, they found it had an effect on problem-focused coping but not on emotion-focused coping. The strongest evidence for automatic processes presented in Orbell and Phillips’s (2019) review is an effect on cognitive interpretation and attention bias, not a direct effect on behavior. In its conclusion, this review does suggest “strategic automatization of coping behaviors” as a potential strategy to improve self-management, but it goes no further in suggesting how this might be accomplished. Overall, studies of Leventhal’s model as an explanation for self-management behaviors are promising, but the cognitive/Narrative pathway is over-emphasized and the emotional/Intuitive pathway is relatively neglected, which is my major critique of Leventhal’s model overall.

Baumeister’s Strength Energy Model (Baumeister & Vohs, 2007) is another theory that could explain non-conscious forces affecting self-management behaviors. This theory posits that self-control is a limited resource connected to blood glucose levels. A 2018 article by Castonguay et al. reviewed the idea that “ego depletion” connected to reduced self-control resources will lead to reduced physical activity among people with type 2 diabetes. A 2008 dissertation by Holmquist used Baumeister’s model to predict self-regulatory fatigue by first using a gaze regulation task to deplete people’s self-control resources, and then demonstrating that these participants were less likely to engage in subsequent physical activity. Baumeister’s model is potentially relevant to people with diabetes, who do have problems regulating glucose, and therefore may also experience self-management failures. It might be particularly interesting to focus on mealtimes, when blood sugar tends to fluctuate the most, in order to study the effects of those fluctuations on people’s perceived willpower and their objective level of success at self-management behaviors. But so far, this model seems mainly to suggest ways in which self-management could be disrupted, rather than ways in which people with diabetes can build self-management ability over time.

A final major model that has been applied to understand automatic processes in diabetes self-management is Klein’s Naturalistic Decision Making. Lippa et al. (2008) identified the skill of problem detection as essential for successful diabetes self-management, a finding that’s very close to our own observation of adolescents with type 1 diabetes. A different Klein(2008) conducted a qualitative study of patients’ problems in type 2 diabetes self-management, and found that challenges to self-management emerged from dynamic relationships between behaviors and outcomes, trouble with symptom recognition in the “ill-structured problem” of self-management, and difficulty making revised plans for self-management when problems arose. We note that the qualitative question posed to participants in Klein’s study – “what made you decide to check your blood glucose?” – was very similar to the quantitative question asked in our own recent study of adolescents with type 1 diabetes (results coming soon!). Another qualitative study by Tanenbaum et al.(2016) found that patients with successful self-management of type 2 diabetes were guided by “aha” moments and tried to normalize self-management behaviors as “general healthy living,” something that could be seen as habitual. Finally, a 2020 mixed-method study by Hamilton et al. examined T1D self-management strategies using Michie’s integrative intervention model, the Behavior Change Wheel. In this study, similar results were seen based on both stakeholder interviews and literature review methods. The strategies identified fell into three categories, labeled as “routine,” “reactive,” and “reflective.” The “reflective” type involves identifying patterns over time, and may align well with the concept of situational awareness. We believe that Two Minds Theory will allow us to improve on these past studies by using quantitative data to directly test the effects of proactive and reactive self-management strategies in T1D self-management. Klein’s approach merely suggests that intuitive self-management strategies will be seen in successful self-management, and has not generally been tested using quantitative measures. One potential exception was a 2022 Health Psychology article by Cummings et al., which did use quantitative measures to assess automaticity in T1D self-management. Although this study did not explicitly reference Klein’s model, it did show a relationship between automaticity and self-reported self-management success. The study that we have currently underway will improve on that approach with an objective measure of self-management success (time in target glucose range).

Overall, these varied theories paint a broad picture of how non-conscious processes affect diabetes self-management. TMT is less cognitive than Leventhal’s model, and more quantifiable than Klein’s, although I suggest that it is compatible with both of these prior approaches, differing mainly in some fine details about the links (or lack thereof) between thoughts and behaviors. Baumeister’s model and Self-Determination Theory propose Intuitive-level variables like glucose levels, perceived autonomy, and social support that might be relevant in further studies using TMT. As proposed in our original theory paper on TMT, studies will be most successful in explaining self-management behavior if they use daily experience sampling or sensor measures to capture data in real time, and in the contexts of daily life where the behaviors must be implemented over the long term for successful control of diabetes.