Family system dynamics and type 1 diabetic glycemic variability: A vector-auto-regressive model.

Abstract

Statistical approaches rooted in econometric methodology, so far foreign to the psychiatric and psychological realms have provided exciting and substantial new insights into complex mind-body interactions over time and individuals. Over 120 days, this structured diary study explored the mutual interactions of emotions within a classic 3-person family system with its Type 1 diabetic adolescent's daily blood glucose variability. Glycemic variability was measured through daily standard deviations of blood glucose determinations (at least 3 per day). Emotions were captured individually utilizing the self-assessment manikin on affective valence (negative-positive), activation (calm-excited), and control (dominated-dominant). Auto- and cross-correlating the stationary absolute (level) values of the mutually interacting parallel time series data sets through vector autoregression (VAR, grounded in econometric theory) allowed for the formulation of 2 concordant models. Applying Cholesky Impulse Response Analysis at a 95% confidence interval, we provided evidence for an adolescent being happy, calm, and in control to exhibit less glycemic variability and hence diabetic derailment. A nondominating mother and a happy father seemed to also reduce glycemic variability. Random shocks increasing glycemic variability affected only the adolescent and her father: In 1 model, the male parent felt in charge; in the other, he calmed down while his daughter turned sad. All reactions to external shocks lasted for less than 4 full days. Extant literature on affect and glycemic variability in Type 1 diabetic adolescents as well as challenges arising from introducing econometric theory to the field were discussed.

New Methods in Exploring Old Topics: Case Studying Brittle Diabetes in the Family Context

“…Resulting from this data collection and primary analysis are ten time series: three time series for each of the three family members from the SAM, affective valence (happy, sad), arousal (excited, calm), and dominance (a sense of presence, distance to the current environment), as well as one time series recording glycemic variability (daily standard deviations of measurements). In contrast to Günther et al [ 1 ], these ten time series were further analyzed by a completely new statistical approach to vector autoregressive (VAR) modeling. While past analysis of this same set of data (see [ 1 ]) has also relied on basic VAR analysis, there had been some common shortcomings to the validity and scope of results, which we were able to remedy here, thus solving statistical shortcomings while also presenting completely new results in a clearer more clinically oriented fashion.…”

“…In contrast to Günther et al [ 1 ], these ten time series were further analyzed by a completely new statistical approach to vector autoregressive (VAR) modeling. While past analysis of this same set of data (see [ 1 ]) has also relied on basic VAR analysis, there had been some common shortcomings to the validity and scope of results, which we were able to remedy here, thus solving statistical shortcomings while also presenting completely new results in a clearer more clinically oriented fashion. How we were able to achieve this, the presentation of a newly developed optimized multivariate lag selection process in VAR analysis, and a comprehensive review of the principles of vector autoregression will be presented next.…”

“…It is our objective to reapply such primary assessment to the case of adolescent brittle diabetes (or more generally speaking, the psychosomatic underpinnings of diabetes type 1 in minors and young adults), while also trying to answer calls for more quantitative and statistically reliable approaches to doing so. This in mind, we have first selected a highly quantitative case study on family dynamics and brittle diabetes [ 1 ] and reviewed and reanalyzed its raw data through implementation of a new statistical procedure increasing the coefficient of determination in the new model by factor ten (while also presenting new and clearer findings), in order to then, in a second step, discuss and compare our results to possibly the historically most well-known set of qualitative case studies on the topic [ 2 ].…”

“…We will start by briefly revisiting the literature on the psychosomatics of adolescent instable diabetes type 1, present a case vignette and basic data collection method of the original case study we reexamine (which may be skipped by those familiar with the work published by [ 1 ]), followed by a detailed description of our new statistical approach and its results, concluding with a clear clinically oriented graphical presentation of our findings and their discussion in light of Minuchin et al's [ 2 ] qualitative findings.…”

“…The Case and Its Psychosomatic Background (adopted and revised from [ 1 ]) . The adolescent index patient of this case study was diagnosed with diabetes type 1 at age of four (clinical clues were polyuria, polydipsia, loss of appetite, a fungal infection, HbA 1c of 9.1 per cent, antibodies against islet cells, and GAD65).…”