Ecological Momentary Assessment of Positive and Negative Affect and Associations with Blood Glucose in Teens with Type 1 Diabetes

Applications of the experience sampling method (ESM) in paediatric healthcare: a systematic review

BACKGROUND

With the Experience Sampling Method (ESM) participants are asked to provide self-reports of their symptoms, feelings, thoughts and behaviours in daily life. This preregistered systematic review assessed how ESM is being used to monitor emotional well-being, somatic health, fatigue and pain in children and adolescents with a chronic somatic illness.

METHODS

Databases were searched from inception. Studies were selected if they included children or adolescents aged 0-25 years with a chronic somatic illness and used ESM focussing on mental health or psychosocial wellbeing, biopsychosocial factors and/or somatic health. Two reviewers extracted data of the final 47 papers, describing 48 studies.

RESULTS

Most studies evaluated what factors influence medical or psychological symptoms and how symptoms influence each other. Another common purpose was to study the feasibility of ESM or ESM as part of an app or intervention. Study methods were heterogeneous and most studies lack adequate reporting of ESM applications and results.

CONCLUSIONS

While ESM holds great potential for providing results and feedback to patients and caregivers, little use is being made of this option. Future studies should consider what they report in their studies, conduct a priori power analyses and how ESM can be embedded in clinical practice.

IMPACT

While ESM has many clinical applications, it is currently mostly used for research purposes. Current studies using ESM are heterogeneous and lack consistent, high-quality reporting. There is great potential in ESM for providing patients and parents with personalised feedback.

Nocturnal hypoglycemia is associated with next day cognitive performance in adults with type 1 diabetes: Pilot data from the GluCog study

OBJECTIVE

 Individuals with type 1 diabetes (T1D) have increased risk for cognitive dysfunction and high rates of sleep disturbance. Despite associations between glycemia and cognitive performance using cross-sectional and experimental methods few studies have evaluated this relationship in a naturalistic setting, or the impact of nocturnal versus daytime hypoglycemia. Ecological Momentary Assessment (EMA) may provide insight into the dynamic associations between cognition, affective, and physiological states. The current study couples EMA data with continuous glucose monitoring (CGM) to examine the within-person impact of nocturnal glycemia on next day cognitive performance in adults with T1D. Due to high rates of sleep disturbance and emotional distress in people with T1D, the potential impacts of sleep characteristics and negative affect were also evaluated.

METHODS

 This pilot study utilized EMA in 18 adults with T1D to examine the impact of glycemic excursions, measured using CGM, on cognitive performance, measured via mobile cognitive assessment using the TestMyBrain platform. Multilevel modeling was used to test the within-person effects of nocturnal hypoglycemia and hyperglycemia on next day cognition.

RESULTS

 Results indicated that increases in nocturnal hypoglycemia were associated with slower next day processing speed. This association was not significantly attenuated by negative affect, sleepiness, or sleep quality.

CONCLUSIONS

 These results, while preliminary due to small sample size, showcase the power of intensive longitudinal designs using ambulatory cognitive assessment to uncover novel determinants of cognitive fluctuation in real world settings, an approach that may be utilized in other populations. Findings suggest reducing nocturnal hypoglycemia may improve cognition in adults with T1D.

Links of positive affect and stress to HbA1c: a prospective longitudinal study

While affect is linked to a number of diabetes outcomes, the specific role of positive affect (PA) in HbA1c remains unclear. The present study examined whether PA prospectively predicted lower HbA1c among adults with type 2 diabetes and whether this relation was moderated by stress. Participants were 123 adults (44.7% female; 60.2% White, 39.8% Black) recently diagnosed with type 2 diabetes. Perceived stress, diabetes-specific distress, and PA were assessed at baseline; HbA1c was assessed at baseline (T1), six months (T2), and five years (T3). PA was cross-sectionally associated with lower HbA1c at T1 and prospectively predicted lower HbA1c at T3. PA interacted with both measures of T1 stress to predict T1 HbA1c, and PA interacted with T3 perceived stress to predict T3 HbA1c. Interactions were consistent with stress buffering. Sensitivity analyses attentuated findings, but robust evidence remained for PA as a protective factor for blood glucose five years later and for a stress-buffering effect of PA on diabetes-specific distress. Findings suggest PA may be a clinically useful indicator among adults with type 2 diabetes and may be particularly important for those experiencing the greatest stress from their disease.

Updated Psychosocial Surveys With Continuous Glucose Monitoring Items for Youth With Type 1 Diabetes and Their Caregivers

AIM

We added items relevant to continuous glucose monitoring (CGM) to the Diabetes Family Conflict Scale (DFC), Diabetes Family Responsibility Questionnaire (DFR), and Blood Glucose Monitoring Communication Questionnaire (GMC) and evaluated the psychometric properties of the updated surveys.

RESEARCH DESIGN AND METHODS

Youth with type 1 diabetes who recently started CGM and their parents completed the updated surveys and additional psychosocial surveys. Medical data were collected from self-reports and review of the medical record.

RESULTS

Youth (N = 114, 49% adolescent girls) were aged 13.3 ± 2.7 years and had mean glycated hemoglobin (HbA1c) 7.9 ± 0.9%; 87% of them used pump therapy. The updated surveys demonstrated high internal consistency (DFC youth: α = .91, parent: α = .81; DFR youth: α = .88, parent: α = .93; and GMC youth: α = .88, parent: α = .86). Higher youth and parent DFC scores (more diabetes-specific family conflict) and GMC scores (more negative affect related to glucose monitoring) were associated with more youth and parent depressive symptoms (r = 0.28-0.60, P ≤ .003), more diabetes burden (r = 0.31-0.71, P ≤ .0009), more state anxiety (r = 0.24 to r = 0.46, P ≤ .01), and lower youth quality of life (r = -0.29 to -0.50, P ≤ .002). Higher youth and parent DFR scores (more parent involvement in diabetes management) were associated with younger youth age (youth: r = -0.76, P < .0001; parent: r = -0.81, P < .0001) and more frequent blood glucose monitoring (youth: r = 0.27, P = .003; parent: r = 0.35, P = .0002).

CONCLUSIONS

The updated DFC, DFR, and GMC surveys maintain good psychometric properties. The addition of CGM items expands the relevance of these surveys for youth with type 1 diabetes who are using CGM and other diabetes technologies.

Coordination of glucose monitoring, self-care behaviour and mental health: achieving precision monitoring in diabetes

Monitoring of glucose plays an essential role in the management of diabetes. However, to fully understand and meaningfully interpret glucose levels, additional information on context is necessary. Important contextual factors include data on behaviours such as eating, exercise, medication-taking and sleep, as well as data on mental health aspects such as stress, affect, diabetes distress and depressive symptoms. This narrative review provides an overview of the current state and future directions of precision monitoring in diabetes. Precision monitoring of glucose has made great progress over the last 5 years with the emergence of continuous glucose monitoring (CGM), automated analysis of new glucose variables and visualisation of CGM data via the ambulatory glucose profile. Interestingly, there has been little progress in the identification of subgroups of people with diabetes based on their glycaemic profile. The integration of behavioural and mental health data could enrich such identification of subgroups to stimulate precision medicine. There are a handful of studies that have used innovative methodology such as ecological momentary assessment to monitor behaviour and mental health in people's everyday life. These studies indicate the importance of the interplay between behaviour, mental health and glucose. However, automated integration and intelligent interpretation of these data sources are currently not available. Automated integration of behaviour, mental health and glucose could lead to the identification of certain subgroups that, for example, show a strong association between mental health and glucose in contrast to subgroups that show independence of mental health and glucose. This could inform precision diagnostics and precision therapeutics. We identified just-in-time adaptive interventions as a potential means by which precision monitoring could lead to precision therapeutics. Just-in-time adaptive interventions consist of micro-interventions that are triggered in people's everyday lives when a certain problem is identified using monitored behaviour, mental health and glucose variables. Thus, these micro-interventions are responsive to real-life circumstances and are adaptive to the specific needs of an individual with diabetes. We conclude that, with current developments in big data analysis, there is a huge potential for precision monitoring in diabetes.